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21. A method comprising: receiving a question into a Question Answering (QA) system; said QA system comparing said question to a corpus of data; said QA system generating hypotheses about relationships between linguistic and semantic entities of said question and said corpus of data; said QA system generating a plurality of candidate answers to said question using said hypotheses; said QA system evaluating sources of evidence used to generate said plurality of candidate answers to identify marginal evidence, said marginal evidence contributing only partially to a candidate answer; said QA system determining a confidence score for each of said plurality of candidate answers; determining a missing piece of knowledge, said missing piece of knowledge comprising information that would enable said QA system to further develop said confidence score; formulating a follow-on inquiry to obtain said missing piece of knowledge; outputting said follow-on inquiry to an external expert community source separate from said QA system to obtain responses to said follow-on inquiry; receiving from said external expert community source responses to said follow-on inquiry comprising said missing piece of knowledge; inputting said missing piece of knowledge into said QA system; and said QA system automatically developing additional logical rules and additional evidence for said QA system based on said obtained missing piece of information.
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21. A method comprising: receiving a question into a Question Answering (QA) system; said QA system comparing said question to a corpus of data; said QA system generating hypotheses about relationships between linguistic and semantic entities of said question and said corpus of data; said QA system generating a plurality of candidate answers to said question using said hypotheses; said QA system evaluating sources of evidence used to generate said plurality of candidate answers to identify marginal evidence, said marginal evidence contributing only partially to a candidate answer; said QA system determining a confidence score for each of said plurality of candidate answers; determining a missing piece of knowledge, said missing piece of knowledge comprising information that would enable said QA system to further develop said confidence score; formulating a follow-on inquiry to obtain said missing piece of knowledge; outputting said follow-on inquiry to an external expert community source separate from said QA system to obtain responses to said follow-on inquiry; receiving from said external expert community source responses to said follow-on inquiry comprising said missing piece of knowledge; inputting said missing piece of knowledge into said QA system; and said QA system automatically developing additional logical rules and additional evidence for said QA system based on said obtained missing piece of information. 23. The method of claim 21 , said QA system further comprising a plurality of passages, said method further comprising comparing said question to said plurality of passages to provide said plurality of candidate answers to said question.
| 0.738983 |
26. In a computer system, a method for associating electronic mail messages with data elements comprising: obtaining an electronic mail message via an electronic mail messaging system; creating an association between one or more elements of said electronic mail message to one or more elements of data in one or more data sources external to said electronic mail messaging system wherein creating the association between said one or more elements of said electronic mail message comprises analyzing said electronic mail message to determine one or more external data sources from which said one or more elements of data are to be retrieved, wherein said one or more elements of data comprise workflow data associated with an order in which activities associated with a given task are completed, and wherein said association manager is configured to facilitate workflow management by providing a context for said one or more elements of said electronic mail message and said one or more elements of data; and via a user interface, enabling a user to create one or more sensory cues indicative of said association of one or more elements of said electronic mail message with said one or more elements of data from said data sources.
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26. In a computer system, a method for associating electronic mail messages with data elements comprising: obtaining an electronic mail message via an electronic mail messaging system; creating an association between one or more elements of said electronic mail message to one or more elements of data in one or more data sources external to said electronic mail messaging system wherein creating the association between said one or more elements of said electronic mail message comprises analyzing said electronic mail message to determine one or more external data sources from which said one or more elements of data are to be retrieved, wherein said one or more elements of data comprise workflow data associated with an order in which activities associated with a given task are completed, and wherein said association manager is configured to facilitate workflow management by providing a context for said one or more elements of said electronic mail message and said one or more elements of data; and via a user interface, enabling a user to create one or more sensory cues indicative of said association of one or more elements of said electronic mail message with said one or more elements of data from said data sources. 33. The method of claim 26 , wherein an association between said one or more elements of said electronic mail message and said one or more elements of data is created programmatically.
| 0.589182 |
1. A method for chaining animations, the method comprising: receiving image data that is representative of captured motion; selecting a pre-canned animation; identifying at least one parameter that is indicative of a transition point, wherein a parameter of the transition point is set based at least in part on a gesture difficulty; and chaining an animation of the captured motion and the pre-canned animation by at least displaying the captured motion and the pre-canned animation in sequence, wherein chaining the animation of the captured motion and the pre-canned animation comprises blending the animation of the captured motion to the pre-canned animation or blending the pre-canned animation to the animation of the captured motion, wherein determining that the at least one parameter is satisfied triggers the chaining the animation of the captured motion and the pre-canned animation.
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1. A method for chaining animations, the method comprising: receiving image data that is representative of captured motion; selecting a pre-canned animation; identifying at least one parameter that is indicative of a transition point, wherein a parameter of the transition point is set based at least in part on a gesture difficulty; and chaining an animation of the captured motion and the pre-canned animation by at least displaying the captured motion and the pre-canned animation in sequence, wherein chaining the animation of the captured motion and the pre-canned animation comprises blending the animation of the captured motion to the pre-canned animation or blending the pre-canned animation to the animation of the captured motion, wherein determining that the at least one parameter is satisfied triggers the chaining the animation of the captured motion and the pre-canned animation. 5. The method in accordance with claim 1 , further comprising selecting multiple pre-canned animations and blending the multiple pre-canned animations to generate a new pre-canned animation, and selecting the new pre-canned animation for chaining with the animation of the captured motion.
| 0.754653 |
1. Network apparatus configured to provide information to at least one client apparatus in communication therewith, the network apparatus comprising: a wireless interface; and a network interface in data communication with the wireless interface; wherein said network apparatus is configured to: receive via the wireless interface a digitized representation of a speech input, the digitized representation generated by a speech recognition apparatus of the at least one client apparatus, the input relating to an organization or entity which a user of the at least one client apparatus wishes to locate; forward the digitized representation via the network interface to a server disposed remotely from the client apparatus, for identification by the server of a location associated with the organization or entity, and retrieval of data associated with the location; receive the data, the data relating to a graphical or visual representation of the location, the graphical or visual representation of the location being useful to aid a user in finding the organization or entity, the graphical or visual representation of the location also comprising a graphical or visual representation of the surroundings of the organization or entity; and forward the received data to the at least one client apparatus via the wireless interface for display on a display device of the client apparatus.
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1. Network apparatus configured to provide information to at least one client apparatus in communication therewith, the network apparatus comprising: a wireless interface; and a network interface in data communication with the wireless interface; wherein said network apparatus is configured to: receive via the wireless interface a digitized representation of a speech input, the digitized representation generated by a speech recognition apparatus of the at least one client apparatus, the input relating to an organization or entity which a user of the at least one client apparatus wishes to locate; forward the digitized representation via the network interface to a server disposed remotely from the client apparatus, for identification by the server of a location associated with the organization or entity, and retrieval of data associated with the location; receive the data, the data relating to a graphical or visual representation of the location, the graphical or visual representation of the location being useful to aid a user in finding the organization or entity, the graphical or visual representation of the location also comprising a graphical or visual representation of the surroundings of the organization or entity; and forward the received data to the at least one client apparatus via the wireless interface for display on a display device of the client apparatus. 11. The apparatus of claim 1 , wherein the network apparatus is further configured to receive inputs generated by the user in progressing through a menu structure comprising multiple possible matching destinations or locations or entities in an iterative or hierarchical fashion.
| 0.699189 |
18. The system of claim 17 , wherein the processing unit executes the program instructions stored on the computer-readable storage medium via the computer readable memory and thereby further: resends an unanswered outgoing message portion comprising the character combination text string to the second user in response to the first user selecting a displayed unanswered outgoing message portion comprising the character combination text string and entering a resend prompt into the message entry interface; saves an unanswered outgoing message portion comprising the character combination text string to an off-line storage means in response to the first user selecting a displayed unanswered outgoing message portion comprising the character combination text string and entering a save prompt into the message entry interface; and deletes an unanswered outgoing message portion comprising the character combination text string in response to the first user selecting a displayed unanswered outgoing message portion comprising the character combination text string and entering a delete prompt into the message entry interface.
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18. The system of claim 17 , wherein the processing unit executes the program instructions stored on the computer-readable storage medium via the computer readable memory and thereby further: resends an unanswered outgoing message portion comprising the character combination text string to the second user in response to the first user selecting a displayed unanswered outgoing message portion comprising the character combination text string and entering a resend prompt into the message entry interface; saves an unanswered outgoing message portion comprising the character combination text string to an off-line storage means in response to the first user selecting a displayed unanswered outgoing message portion comprising the character combination text string and entering a save prompt into the message entry interface; and deletes an unanswered outgoing message portion comprising the character combination text string in response to the first user selecting a displayed unanswered outgoing message portion comprising the character combination text string and entering a delete prompt into the message entry interface. 19. The system of claim 18 , wherein the outgoing message portion comprising the special text string is smaller than an entire message comprising the message portion; wherein the real-time interactive communication system message entry interface is an internet relay chat, an instant messaging, a chat-room or an ICQ application interface; and wherein the real-time interactive communication system message entry interface is not a web log, a web blog, a bulletin board, or an email application interface.
| 0.780659 |
13. A system, comprising: a processor implemented in hardware; a computer having the processor; and means for maintaining, by the computer, metadata corresponding to a plurality of documents of a help system of a software development environment, wherein the metadata indicates whether a document includes information that is pertinent to a perspective and a view of the software development environment, wherein: a plurality of perspectives are maintained; a plurality views are contained within each perspective of the plurality of perspectives; and the plurality of views contained within a particular perspective of the plurality of perspectives are accessible via selection of the particular perspective; means for receiving, by the computer, a search term from a user in a current development context of the software development environment, wherein the user prefers information to be returned based on the search term in the current development context over information based on the search term in other development contexts; means for augmenting, by a query construction application, a search query with the received search term, the current perspective, and currently opened views of the current perspective in the current development context, in response to receiving the search term from the user; means for sending the augmented search query to a search engine executing within the computer, in response to the augmenting of the search query by the query construction application; and means for generating, by the search engine executing within the computer, search results comprising selected documents from the plurality of documents, wherein the selected documents of the help system of the software development environment are based on at least the augmented search query and the metadata maintained with the plurality of documents.
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13. A system, comprising: a processor implemented in hardware; a computer having the processor; and means for maintaining, by the computer, metadata corresponding to a plurality of documents of a help system of a software development environment, wherein the metadata indicates whether a document includes information that is pertinent to a perspective and a view of the software development environment, wherein: a plurality of perspectives are maintained; a plurality views are contained within each perspective of the plurality of perspectives; and the plurality of views contained within a particular perspective of the plurality of perspectives are accessible via selection of the particular perspective; means for receiving, by the computer, a search term from a user in a current development context of the software development environment, wherein the user prefers information to be returned based on the search term in the current development context over information based on the search term in other development contexts; means for augmenting, by a query construction application, a search query with the received search term, the current perspective, and currently opened views of the current perspective in the current development context, in response to receiving the search term from the user; means for sending the augmented search query to a search engine executing within the computer, in response to the augmenting of the search query by the query construction application; and means for generating, by the search engine executing within the computer, search results comprising selected documents from the plurality of documents, wherein the selected documents of the help system of the software development environment are based on at least the augmented search query and the metadata maintained with the plurality of documents. 14. The system of claim 13 , wherein the means for generating the search results further performs: categorizing, ordering and ranking the selected documents based on relevance of the metadata to the current development context, wherein the categorized, ordered and ranked documents are presented as the search results to the user.
| 0.582117 |
1. A non-transitory computer-readable recording medium having stored therein a program for causing a computer to execute a process for putting trouble handling cases occurring in the past in an information system into knowledge data, and for recommending a handling method using a trouble handling knowledge obtained by putting the trouble handling cases into the knowledge data, and a symptom of a trouble when the trouble occurs, the process comprising: obtaining candidates of a handling method for a trouble requested to be handled by searching the trouble handling knowledge; recording to a storing unit a history of handling methods executed for each symptom and a history of candidates of the handling method at the time of the execution as handling history information; assigning priorities to the candidates of the handling method obtained by the obtaining step in the handling history information recorded in the storing unit; returning to a handling request source the handling method for the trouble requested to be handled after assigning a priority to the handling method using priority assignment information obtained by the assigning; and integrating, into one, handling history information having a plurality of common portions in the handling history information recorded in the handling history management information, wherein: the assigning step assigns a higher priority to a handling method candidate effective also as to other symptoms being handled, as an appearance frequency of the candidates of the handling method in handling history information of the other symptoms being handled becomes higher, the appearance frequency recognized by referring to handling history information of the other symptoms being handled, and the integrating step refers to pieces of handling history information within the handling history management information, compares the pieces of handling history information to determine whether a ratio of common portions to an entire history of handling methods is equal to or larger than a certain value, and determines that there are a plurality of common portions when the ratio of common portions is equal to or larger than the certain value.
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1. A non-transitory computer-readable recording medium having stored therein a program for causing a computer to execute a process for putting trouble handling cases occurring in the past in an information system into knowledge data, and for recommending a handling method using a trouble handling knowledge obtained by putting the trouble handling cases into the knowledge data, and a symptom of a trouble when the trouble occurs, the process comprising: obtaining candidates of a handling method for a trouble requested to be handled by searching the trouble handling knowledge; recording to a storing unit a history of handling methods executed for each symptom and a history of candidates of the handling method at the time of the execution as handling history information; assigning priorities to the candidates of the handling method obtained by the obtaining step in the handling history information recorded in the storing unit; returning to a handling request source the handling method for the trouble requested to be handled after assigning a priority to the handling method using priority assignment information obtained by the assigning; and integrating, into one, handling history information having a plurality of common portions in the handling history information recorded in the handling history management information, wherein: the assigning step assigns a higher priority to a handling method candidate effective also as to other symptoms being handled, as an appearance frequency of the candidates of the handling method in handling history information of the other symptoms being handled becomes higher, the appearance frequency recognized by referring to handling history information of the other symptoms being handled, and the integrating step refers to pieces of handling history information within the handling history management information, compares the pieces of handling history information to determine whether a ratio of common portions to an entire history of handling methods is equal to or larger than a certain value, and determines that there are a plurality of common portions when the ratio of common portions is equal to or larger than the certain value. 6. The non-transitory computer-readable medium according to claim 1 , wherein the integrating step determines that handling histories have a plurality of common portions when one handling history matches a forward portion of another handling history, when one handling history is included in another handling history, or when one handling history matches a backward portion of another handling history.
| 0.509978 |
13. The method of claim 3 wherein the recorded audio/visual records and associated text include more than one subject and records of similar behaviors of each subject is observable concurrently by selecting a behavior which is common to each subject.
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13. The method of claim 3 wherein the recorded audio/visual records and associated text include more than one subject and records of similar behaviors of each subject is observable concurrently by selecting a behavior which is common to each subject. 14. The method of claim 13 wherein a subject is chosen from the list consisting of one or more species, living subject, organism, lifeform, living or nonliving systems, organic or inorganic reaction and physical phenomena.
| 0.913306 |
4. The method according to claim 3 , wherein the at least one spatial predicate of a reference spatial object includes: (a) a task-relevant spatial object or a concept of the task-relevant spatial objects; and (b) at least one spatial relationship between the reference spatial object and the task-relevant spatial object or at least one spatial relationship between the reference spatial object and the concept of task-relevant spatial objects.
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4. The method according to claim 3 , wherein the at least one spatial predicate of a reference spatial object includes: (a) a task-relevant spatial object or a concept of the task-relevant spatial objects; and (b) at least one spatial relationship between the reference spatial object and the task-relevant spatial object or at least one spatial relationship between the reference spatial object and the concept of task-relevant spatial objects. 5. The method according to claim 4 , wherein the at least one spatial relationship includes one or more of: a topological relationship, a metrical relationship, and a directional relationship, the topological relationship including one of: an intersection, an adjacency, and an inclusion, the metrical relationship including one of: a distance, an area, and a closeness, the directional relationship including one of: above, behind, north, west, east, south, northeast, southwest, northwest, and southeast.
| 0.892079 |
11. A method in accordance with claim 1, wherein said receiving step comprises receiving at least one edited pre-existing character in the handwriting capture widget.
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11. A method in accordance with claim 1, wherein said receiving step comprises receiving at least one edited pre-existing character in the handwriting capture widget. 12. A method in accordance with claim 11, wherein said method further comprises the steps of: receiving a user selection of a current data entry on the display screen; and displaying in each of the text entry widgets pre-existing characters from the respective data entry fields of the received user selected current data entry, wherein said receiving and displaying steps are performed prior to said assigning step.
| 0.802502 |
1. A frequency domain based magnetic ink character recognition (MICR) system, comprising: a computer device having a memory and processor, comprising: a segmentation system for segmenting inputted MICR data into sets of temporal data for inputted characters; a Fourier system for generating a set of Fourier components from temporal data for an inputted character, wherein the set of Fourier components comprises six components including a fundamental and next five harmonics; a normalization system for normalizing the set of Fourier components to generate a normalized set of Fourier components, wherein the normalized set of Fourier components include magnitudes that sum to a predetermined value; and a matching system for comparing the normalized set of Fourier components with each of a set of reference waveforms to determine an identity of the inputted character, wherein the set of reference waveforms comprises a corresponding six components including a corresponding fundamental and corresponding next five harmonics, and wherein the comparing, comprises: calculating a set of difference value between each component in the normalized set of Fourier components and an associated component in a reference waveform; weighting each difference value such that a difference value calculated for a relatively higher Fourier component receives a relatively lower weight; summing each of the weighted difference values; comparing concavities between the normalized set of Fourier components and each set of reference waveforms; and assigning values based upon a degree of concavity matching.
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1. A frequency domain based magnetic ink character recognition (MICR) system, comprising: a computer device having a memory and processor, comprising: a segmentation system for segmenting inputted MICR data into sets of temporal data for inputted characters; a Fourier system for generating a set of Fourier components from temporal data for an inputted character, wherein the set of Fourier components comprises six components including a fundamental and next five harmonics; a normalization system for normalizing the set of Fourier components to generate a normalized set of Fourier components, wherein the normalized set of Fourier components include magnitudes that sum to a predetermined value; and a matching system for comparing the normalized set of Fourier components with each of a set of reference waveforms to determine an identity of the inputted character, wherein the set of reference waveforms comprises a corresponding six components including a corresponding fundamental and corresponding next five harmonics, and wherein the comparing, comprises: calculating a set of difference value between each component in the normalized set of Fourier components and an associated component in a reference waveform; weighting each difference value such that a difference value calculated for a relatively higher Fourier component receives a relatively lower weight; summing each of the weighted difference values; comparing concavities between the normalized set of Fourier components and each set of reference waveforms; and assigning values based upon a degree of concavity matching. 4. The frequency domain MICR system of claim 1 , wherein the matching system includes a reference waveform for each character in a character set.
| 0.5 |
13. A system for query generation for searchable content, comprising: a processor configured to: receive an identifier for a web site comprising searchable content, wherein the searchable content includes one or more web pages of the web site, and wherein the web site is to be optimized for higher rankings in organic search results of a search engine; generate a set of queries for the web site using an inverse search engine, wherein the generated set of queries includes one or more queries that are relevant to the searchable content of the web site, wherein the generating the set of queries comprises: determine candidate queries for the searchable content of the web site; determine a relevance for each of the candidate queries, wherein the determining the relevance is based on a number of terms of each candidate query present in a web page of the web site; and determine a topicality for each of the candidate queries; optimize the web site for organic searches using the generated set of queries to generate an optimized version of the web site; and perform a feedback loop to determine whether the optimized version of the web site is resulting in higher rankings in organic search results of the search engine; and a memory coupled to the processor and configured to provide the processor with instructions.
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13. A system for query generation for searchable content, comprising: a processor configured to: receive an identifier for a web site comprising searchable content, wherein the searchable content includes one or more web pages of the web site, and wherein the web site is to be optimized for higher rankings in organic search results of a search engine; generate a set of queries for the web site using an inverse search engine, wherein the generated set of queries includes one or more queries that are relevant to the searchable content of the web site, wherein the generating the set of queries comprises: determine candidate queries for the searchable content of the web site; determine a relevance for each of the candidate queries, wherein the determining the relevance is based on a number of terms of each candidate query present in a web page of the web site; and determine a topicality for each of the candidate queries; optimize the web site for organic searches using the generated set of queries to generate an optimized version of the web site; and perform a feedback loop to determine whether the optimized version of the web site is resulting in higher rankings in organic search results of the search engine; and a memory coupled to the processor and configured to provide the processor with instructions. 15. The system recited in claim 13 , wherein the searchable content of the web site is received as an input to the inverse search engine, and the generated set of queries including ranked queries is provided as an output from the inverse search engine.
| 0.747531 |
1. A computer-implemented method for analyzing a patent application and providing a visual representation, the method comprising: receiving a selection from a user to view claims of the patent application in a claim tree hierarchical structure; displaying, by a computer, the claims in the claim tree hierarchical structure on a display, wherein the claim tree hierarchical structure visually depicts relationships between the claims; identifying one or more words of at least one of the claims that constitutes one or more elements; displaying, in the claim tree hierarchical structure, the words constituting the one or more elements in association with the claims; receiving a selection from a user to search a selected element from the one or more elements in association with the claims; loading, into a memory of the computer, at least one database storing patents, patent applications, and court opinions that relates to the patents or the patent applications; searching the at least one database for the selected element, wherein the results of the search indicate that the selected element has a defined prior usage in patents or patent applications with earlier priority dates stored in the at least one database and corresponding case reference information in court opinions stored in the at least one database, the defined prior usage informing how the selected element has been used in the patents or patent applications with earlier priority dates to provide a meaning of the selected element, and the case reference information indicating how the selected element has been interpreted by courts; and displaying the selected element with a first visual indication indicating that the selected element has been used in the patents or patent applications with earlier priority dates from the at least one database, and a second visual indication indicating that the selected element has been interpreted by courts.
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1. A computer-implemented method for analyzing a patent application and providing a visual representation, the method comprising: receiving a selection from a user to view claims of the patent application in a claim tree hierarchical structure; displaying, by a computer, the claims in the claim tree hierarchical structure on a display, wherein the claim tree hierarchical structure visually depicts relationships between the claims; identifying one or more words of at least one of the claims that constitutes one or more elements; displaying, in the claim tree hierarchical structure, the words constituting the one or more elements in association with the claims; receiving a selection from a user to search a selected element from the one or more elements in association with the claims; loading, into a memory of the computer, at least one database storing patents, patent applications, and court opinions that relates to the patents or the patent applications; searching the at least one database for the selected element, wherein the results of the search indicate that the selected element has a defined prior usage in patents or patent applications with earlier priority dates stored in the at least one database and corresponding case reference information in court opinions stored in the at least one database, the defined prior usage informing how the selected element has been used in the patents or patent applications with earlier priority dates to provide a meaning of the selected element, and the case reference information indicating how the selected element has been interpreted by courts; and displaying the selected element with a first visual indication indicating that the selected element has been used in the patents or patent applications with earlier priority dates from the at least one database, and a second visual indication indicating that the selected element has been interpreted by courts. 13. The computer-implemented method of claim 1 , further comprising: displaying, in association with at least one of the claims, a designation indicating whether the at least one of the claims is independent, dependent, or multiple dependent; and generating a report of the claims, the report comprising a number of the claims, a claim tree, and a claim chart summarizing claim relationships.
| 0.5 |
7. A method of projecting a representation of an Extensible Markup Language (XML) document, the method comprising steps of: A) receiving the XML document as input; B) receiving at least one XPath query to be evaluated against the XML document; C) deriving a set of XPath expressions from the XML document, wherein the XPath expressions are represented as a rooted XPath expression tree with labeled vertices and edges, and wherein the XPath expression tree comprises at least one axis selected from a group consisting of: backward, ancestor, parent, following, preceding, following-sibling, and preceding-sibling axes; and D) constructing a projection of the XML document for evaluation of the XPath query, the projection based on the XPath expression tree, wherein the constructing step comprises: 1) normalizing the XPath expression tree into a canonical form, wherein the normalizing step comprises: a) rewriting instances of following, preceding, following-sibling and preceding-sibling axes in the XPath expression tree into order-blind axes, such as parent and ancestor, by introducing new vertices such that there are no more instances of following and preceding in the rewritten XPath expression tree; and b) merging vertices of the rewritten XPath expression tree to remove redundancies; 2) traversing the XML document in a depth-first manner to build a tree representation of the XML document, the traversing step comprising: a) generating start events when the traversal first visits an element; b) generating end events once the traversal of a subtree rooted at that element is finished; c) concurrently with generating the events, constructing nodes for all elements that may participate in an embedding; and d) adding all ancestor nodes of the elements that may participate in an embedding; E) evaluating the at least one XPath query against the tree representation in a bottom-up manner to produce a result such that the result of the evaluation of the XPath query on the projection of the XML document is the same as a result of evaluation of the XPath query on the XML document and comprises all nodes that are solutions of the XPath query, and their backward axes; and F) serializing the result.
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7. A method of projecting a representation of an Extensible Markup Language (XML) document, the method comprising steps of: A) receiving the XML document as input; B) receiving at least one XPath query to be evaluated against the XML document; C) deriving a set of XPath expressions from the XML document, wherein the XPath expressions are represented as a rooted XPath expression tree with labeled vertices and edges, and wherein the XPath expression tree comprises at least one axis selected from a group consisting of: backward, ancestor, parent, following, preceding, following-sibling, and preceding-sibling axes; and D) constructing a projection of the XML document for evaluation of the XPath query, the projection based on the XPath expression tree, wherein the constructing step comprises: 1) normalizing the XPath expression tree into a canonical form, wherein the normalizing step comprises: a) rewriting instances of following, preceding, following-sibling and preceding-sibling axes in the XPath expression tree into order-blind axes, such as parent and ancestor, by introducing new vertices such that there are no more instances of following and preceding in the rewritten XPath expression tree; and b) merging vertices of the rewritten XPath expression tree to remove redundancies; 2) traversing the XML document in a depth-first manner to build a tree representation of the XML document, the traversing step comprising: a) generating start events when the traversal first visits an element; b) generating end events once the traversal of a subtree rooted at that element is finished; c) concurrently with generating the events, constructing nodes for all elements that may participate in an embedding; and d) adding all ancestor nodes of the elements that may participate in an embedding; E) evaluating the at least one XPath query against the tree representation in a bottom-up manner to produce a result such that the result of the evaluation of the XPath query on the projection of the XML document is the same as a result of evaluation of the XPath query on the XML document and comprises all nodes that are solutions of the XPath query, and their backward axes; and F) serializing the result. 12. The method of claim 7 wherein the traversing step further comprises removing unsatisfiable XPath expressions.
| 0.558039 |
1. A method comprising: reading a plurality of entity population rules, each entity population rule describing a mapping from an input schema to an output schema, the output schema conforming to an entity declaration, the entity declaration describing an entity including at least one nested entity; compiling the plurality of entity population rules into at least one executable query, wherein compiling the plurality of entity population rules comprises topologically sorting the entities defined by the plurality of entity population rules based on at least one dependency among the plurality of entity population rules and generating a query by traversing from a leaf to a root of the topologically sorted entities; reading a plurality of input records from a first data store, the input records conforming to the input schema; applying a compiled entity resolution rule to the plurality of input records to determine a link between members of the plurality of input records; applying one of the plurality of entity population rules to the plurality of input records to create a plurality of output records complying with the output schema; subsequent to applying one of the plurality of entity population rules, recompiling the plurality of entity population rules; and populating an index of nested entities using the at least one executable query, the index complying with an index declaration, the index declaration describing an index of nested entities, and the index including the link.
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1. A method comprising: reading a plurality of entity population rules, each entity population rule describing a mapping from an input schema to an output schema, the output schema conforming to an entity declaration, the entity declaration describing an entity including at least one nested entity; compiling the plurality of entity population rules into at least one executable query, wherein compiling the plurality of entity population rules comprises topologically sorting the entities defined by the plurality of entity population rules based on at least one dependency among the plurality of entity population rules and generating a query by traversing from a leaf to a root of the topologically sorted entities; reading a plurality of input records from a first data store, the input records conforming to the input schema; applying a compiled entity resolution rule to the plurality of input records to determine a link between members of the plurality of input records; applying one of the plurality of entity population rules to the plurality of input records to create a plurality of output records complying with the output schema; subsequent to applying one of the plurality of entity population rules, recompiling the plurality of entity population rules; and populating an index of nested entities using the at least one executable query, the index complying with an index declaration, the index declaration describing an index of nested entities, and the index including the link. 2. The method of claim 1 , wherein applying the one of the plurality of entity population rules comprises applying a user defined function to the plurality of input records.
| 0.64959 |
15. A system comprising: one or more processors; and one or more computer readable media comprising instructions that, when executed by the one or more processors, cause the one or more processors to: populate a character entry field with one or more characters entered by a first user input; output a set of multiple phrases that include the one or more characters entered by the first user input; receive a second user input identifying a selected term from a selected phrase of the set of multiple phrases, the selected term including the one or more characters entered by the first user input; and pin the selected term into the character entry field.
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15. A system comprising: one or more processors; and one or more computer readable media comprising instructions that, when executed by the one or more processors, cause the one or more processors to: populate a character entry field with one or more characters entered by a first user input; output a set of multiple phrases that include the one or more characters entered by the first user input; receive a second user input identifying a selected term from a selected phrase of the set of multiple phrases, the selected term including the one or more characters entered by the first user input; and pin the selected term into the character entry field. 17. The system of claim 15 , wherein the instructions, when executed by the one or more processors, cause the one or more processors to: not pin at least one other term of the selected phrase into the character entry field.
| 0.586957 |
11. A non-transitory machine readable medium having a set of instructions stored therein which when executed cause a machine to perform a set of operations comprising: receiving an updated server software for a first server, the first server sharing resources with server software of a second server; checking an expiration of a statement of compatibility; checking compatibility of the updated server software with the server software of the second server through a statement of compatibility stored in a shared storage module, the statement of compatibility defining sets of compatible versions of server software; selecting automatically one of a parallel update process and a rolling update process to install the updated server software based on the checking of the compatibility, the parallel update process to update the server software of the first server for updated server software that is incompatible with the server software of the second server at a same time the server software of the second server is updated and the rolling update process to update the server software of the first server for updated server software that is compatible with the server software of the second server while the second server is executing the compatible server software; and scheduling automatically the parallel update process in response to the expiration of the statement of compatibility.
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11. A non-transitory machine readable medium having a set of instructions stored therein which when executed cause a machine to perform a set of operations comprising: receiving an updated server software for a first server, the first server sharing resources with server software of a second server; checking an expiration of a statement of compatibility; checking compatibility of the updated server software with the server software of the second server through a statement of compatibility stored in a shared storage module, the statement of compatibility defining sets of compatible versions of server software; selecting automatically one of a parallel update process and a rolling update process to install the updated server software based on the checking of the compatibility, the parallel update process to update the server software of the first server for updated server software that is incompatible with the server software of the second server at a same time the server software of the second server is updated and the rolling update process to update the server software of the first server for updated server software that is compatible with the server software of the second server while the second server is executing the compatible server software; and scheduling automatically the parallel update process in response to the expiration of the statement of compatibility. 12. The non-transitory machine readable medium of claim 11 , having a further set of instruction stored therein which when executed cause a machine to perform a set of operations further comprising: downloading the statement of compatibility from a remote server.
| 0.557114 |
70. A computer system for presenting an electronic document to a viewer to facilitate comprehension and control display and speed of delivery, the computer system including a computer program product, the computer program product comprising: program instructions that group selected words into a cognitive cluster to be treated as a single word; program instructions that assign an emphasis value to each word and cognitive cluster in the electronic document using a knowledge database thereby generating a first tagged file of assigned emphasis values for each word and cognitive cluster; program instructions that process the first tagged file, including deriving emphasis values for recognizability and comprehensibility, to generate a second tagged file of derived emphasis values; program instructions that process the second tagged file, including facilitating editing of properties of selected words and cognitive clusters in the electronic document, to generate a property deliverable file that dynamically controls the presentation of the electronic document to the viewer; a printer or an electronic display device; and program instructions that present the electronic document to the viewer on the electronic display device or to the printer.
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70. A computer system for presenting an electronic document to a viewer to facilitate comprehension and control display and speed of delivery, the computer system including a computer program product, the computer program product comprising: program instructions that group selected words into a cognitive cluster to be treated as a single word; program instructions that assign an emphasis value to each word and cognitive cluster in the electronic document using a knowledge database thereby generating a first tagged file of assigned emphasis values for each word and cognitive cluster; program instructions that process the first tagged file, including deriving emphasis values for recognizability and comprehensibility, to generate a second tagged file of derived emphasis values; program instructions that process the second tagged file, including facilitating editing of properties of selected words and cognitive clusters in the electronic document, to generate a property deliverable file that dynamically controls the presentation of the electronic document to the viewer; a printer or an electronic display device; and program instructions that present the electronic document to the viewer on the electronic display device or to the printer. 95. The computer system for presenting an electronic document of claim 70 wherein the computer program product further comprises program instructions that customize the presentation of the electronic document.
| 0.645367 |
12. A computer-implemented method of generating one or more attribute models learned from a user's driving preferences, comprising: receiving, by one or more processors, attribute data for a set of driving sessions for a user, wherein attribute data for each driving session includes measurements relevant to one or more target attributes, wherein each driving session is defined in terms of one or more road segments of one or more roads traversed by the user during the set of driving sessions, wherein receiving attribute data for a set of driving sessions for a user comprises receiving sensor data; applying, by the one or more processors, attribute estimation rules to the attribute data to compute an attribute value for each target attribute along each road segment traversed at least once in the driving sessions; assigning, by the one or more processors, a default attribute value for one or more unseen road segments of the one or more roads identified in each driving session, wherein unseen road segments correspond to road segments not yet traversed by the user during any one of the driving sessions; determining and storing, by the one or more processors, an attribute model comprising attribute values computed or assigned for each road segment of the one or more roads traversed by the user during the set of driving sessions; and accessing, by the one or more processors, the attribute model to generate directions for use in navigation.
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12. A computer-implemented method of generating one or more attribute models learned from a user's driving preferences, comprising: receiving, by one or more processors, attribute data for a set of driving sessions for a user, wherein attribute data for each driving session includes measurements relevant to one or more target attributes, wherein each driving session is defined in terms of one or more road segments of one or more roads traversed by the user during the set of driving sessions, wherein receiving attribute data for a set of driving sessions for a user comprises receiving sensor data; applying, by the one or more processors, attribute estimation rules to the attribute data to compute an attribute value for each target attribute along each road segment traversed at least once in the driving sessions; assigning, by the one or more processors, a default attribute value for one or more unseen road segments of the one or more roads identified in each driving session, wherein unseen road segments correspond to road segments not yet traversed by the user during any one of the driving sessions; determining and storing, by the one or more processors, an attribute model comprising attribute values computed or assigned for each road segment of the one or more roads traversed by the user during the set of driving sessions; and accessing, by the one or more processors, the attribute model to generate directions for use in navigation. 14. The computer-implemented method of claim 12 , further comprising: determining, by the one or more processors, if one or more implicit conditions applies to each target attribute, and when an implicit condition is determined to apply to a given target attribute, the method further comprising: forming, by the one or more processors, a mini-model for each given target attribute by merging attribute data for each driving session; identifying, by the one or more processors, pairs of like mini-models using a similarity metric; merging, by the one or more processors, attribute data from identified pairs of like mini-models; and determining and storing, by the one or more processors, a combined model from attribute values computed or assigned from attribute data merged from identified pairs of like mini-models.
| 0.5 |
11. A method comprising: receiving a request, over a network at a social shopping platform, from a user in a first community of users, the social shopping platform including a plurality of network-based marketplaces respectively associated with a plurality of communities, the plurality of communities including the first community of users that is associated with a first network-based marketplace; identifying the first network-based marketplace from the plurality of network-based marketplaces based on the request, the request for an activity associated with the first network-based marketplace that is used by the first community of users to transact items of a single domain that is of interest to the first community of users; updating a first reputation score based on a user reputation score for the user and based upon the activity associated with the first network-based marketplace; and updating the user reputation score based on the first reputation score.
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11. A method comprising: receiving a request, over a network at a social shopping platform, from a user in a first community of users, the social shopping platform including a plurality of network-based marketplaces respectively associated with a plurality of communities, the plurality of communities including the first community of users that is associated with a first network-based marketplace; identifying the first network-based marketplace from the plurality of network-based marketplaces based on the request, the request for an activity associated with the first network-based marketplace that is used by the first community of users to transact items of a single domain that is of interest to the first community of users; updating a first reputation score based on a user reputation score for the user and based upon the activity associated with the first network-based marketplace; and updating the user reputation score based on the first reputation score. 19. The method of claim 11 , wherein the updating the reputation score is responsive to the receiving, and wherein the updating the user reputation score is responsive to the receiving.
| 0.607013 |
1. A method for providing a text automatic response using a text ARS development tool, comprising: generating, by a manager device, a menu tree using a web-based text ARS development tool; generating, by the manager device, a pre-defined XML document set based on the menu tree that is generated to correspond to each menu based on a shape selected according to an attribute of each menu; transmitting, by the manager device, the XML document set to a text ARS server; and combining, by the text ARS server, texts included in one of the XML document set to transmit the texts to a user device.
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1. A method for providing a text automatic response using a text ARS development tool, comprising: generating, by a manager device, a menu tree using a web-based text ARS development tool; generating, by the manager device, a pre-defined XML document set based on the menu tree that is generated to correspond to each menu based on a shape selected according to an attribute of each menu; transmitting, by the manager device, the XML document set to a text ARS server; and combining, by the text ARS server, texts included in one of the XML document set to transmit the texts to a user device. 3. The method of claim 1 , wherein the generating of the XML document set comprises generating an XML document to correspond to each menu included in the menu tree.
| 0.758021 |
13. A medical implant assembly for securing an elongate rod to a bone, the medical implant assembly comprising: a shank with a lower body for fixation to a bone and an integral upper portion having an outer convex substantially spherical surface; a receiver having a base and a pair of upright arms extending upward from the base with inner surfaces defining an open channel for receiving the elongate rod, the arm inner surfaces having a closure top guide and advancement feature formed thereon, the base defining a chamber having an upper capture portion, a lower locking portion, and communicating with a receiver bottom surface through a lower opening, the open channel communicating with the chamber, the receiver having a central axis and a contact portion between the lower opening and the open channel and facing inwardly toward the central axis; a retainer positioned within the chamber before the shank is bottom loaded into the receiver through the lower opening, the retainer having a through-and-through gap extending from a top surface to a bottom surface of the retainer; and a lower pressure insert positioned within the receiver before the shank is bottom loaded into the receiver and engageable with the receiver inwardly-facing contact portion to prevent the insert from moving downwardly toward the chamber prior to the shank being capture by the retainer, wherein after the shank upper portion is bottom loaded into the receiver through the lower opening and captured by the retainer, the insert is forced downward toward the lower locking portion with a tool into an interference engagement with the receiver inwardly-facing contact portion that prevents the lower pressure insert from moving back up within the receiver, and wherein the wherein the insert and retainer cooperate with the receiver to limit pivotal motion of the shank with respect to the receiver to a single plane.
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13. A medical implant assembly for securing an elongate rod to a bone, the medical implant assembly comprising: a shank with a lower body for fixation to a bone and an integral upper portion having an outer convex substantially spherical surface; a receiver having a base and a pair of upright arms extending upward from the base with inner surfaces defining an open channel for receiving the elongate rod, the arm inner surfaces having a closure top guide and advancement feature formed thereon, the base defining a chamber having an upper capture portion, a lower locking portion, and communicating with a receiver bottom surface through a lower opening, the open channel communicating with the chamber, the receiver having a central axis and a contact portion between the lower opening and the open channel and facing inwardly toward the central axis; a retainer positioned within the chamber before the shank is bottom loaded into the receiver through the lower opening, the retainer having a through-and-through gap extending from a top surface to a bottom surface of the retainer; and a lower pressure insert positioned within the receiver before the shank is bottom loaded into the receiver and engageable with the receiver inwardly-facing contact portion to prevent the insert from moving downwardly toward the chamber prior to the shank being capture by the retainer, wherein after the shank upper portion is bottom loaded into the receiver through the lower opening and captured by the retainer, the insert is forced downward toward the lower locking portion with a tool into an interference engagement with the receiver inwardly-facing contact portion that prevents the lower pressure insert from moving back up within the receiver, and wherein the wherein the insert and retainer cooperate with the receiver to limit pivotal motion of the shank with respect to the receiver to a single plane. 15. The medical implant assembly of claim 13 , wherein a bottom surface of the insert is spaced from the top surface of the retainer.
| 0.793831 |
1. A relative translation system, comprising: a relative translation assembly, having a fixed support member, a translatable member supported by the fixed support member, and a translation guide portion to facilitate translation of the translatable member relative to the fixed support member, the translation guide portion having a fixed translation member and a movable translation member, the movable translation member fixedly coupled to a swing arm, the swing arm rotatably coupled to the fixed support member to provide a rotation of the movable translation member about an axis, the fixed translation member and the movable translation member operate together to constrain movement of the translatable member in a translational degree of freedom, wherein, the movable translation member is configured to maintain preload on the fixed and movable translation members and accommodate thermal expansion; and a drive mechanism configured to cause translation of the translatable member relative to the fixed support member.
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1. A relative translation system, comprising: a relative translation assembly, having a fixed support member, a translatable member supported by the fixed support member, and a translation guide portion to facilitate translation of the translatable member relative to the fixed support member, the translation guide portion having a fixed translation member and a movable translation member, the movable translation member fixedly coupled to a swing arm, the swing arm rotatably coupled to the fixed support member to provide a rotation of the movable translation member about an axis, the fixed translation member and the movable translation member operate together to constrain movement of the translatable member in a translational degree of freedom, wherein, the movable translation member is configured to maintain preload on the fixed and movable translation members and accommodate thermal expansion; and a drive mechanism configured to cause translation of the translatable member relative to the fixed support member. 2. The system of claim 1 , wherein the drive mechanism comprises: a drive shaft having a threaded portion; a first bearing to facilitate rotation of the drive shaft, the bearing being configured to support the drive shaft and interface with the fixed support member; and a drive member engaged with the threaded portion of the drive shaft and configured to be fixed to the translatable member to facilitate translation relative to the threaded portion upon rotation of the drive shaft, wherein an angle of misalignment of the bearing compensates for drive shaft rotational misalignment, and wherein a position of the drive member is adjustable upon assembly to compensate for drive axis translational misalignment.
| 0.5 |
12. A Multiple System Operation system (MSO), comprising: storage for video content in an original markup language that includes layout, rendering, UI interaction, and dynamic aspects of the video content, wherein the video content comprises Extensible Hypertext Markup Language (XHTML) with Cascading Style Sheets (CSS) and includes a plurality of display objects, each display object having one or more conditions; and one or more headends each having one or more servers, wherein each server includes a compiler to: compile the processed video content with a routine specific to a predetermined client to create one or more serialized binary bit streams corresponding to the video content, wherein the serialized binary bit streams preserves the layout, rendering, UI interaction, and dynamic aspects of the video content from the original markup language, wherein the compiler processes the video content via a markup-specific routine to generate one or more rendering-style records for each of the one or more conditions of each display object, wherein one or more types of interactive input can be the one or more conditions upon which the rendering-style record for each display object is generated.
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12. A Multiple System Operation system (MSO), comprising: storage for video content in an original markup language that includes layout, rendering, UI interaction, and dynamic aspects of the video content, wherein the video content comprises Extensible Hypertext Markup Language (XHTML) with Cascading Style Sheets (CSS) and includes a plurality of display objects, each display object having one or more conditions; and one or more headends each having one or more servers, wherein each server includes a compiler to: compile the processed video content with a routine specific to a predetermined client to create one or more serialized binary bit streams corresponding to the video content, wherein the serialized binary bit streams preserves the layout, rendering, UI interaction, and dynamic aspects of the video content from the original markup language, wherein the compiler processes the video content via a markup-specific routine to generate one or more rendering-style records for each of the one or more conditions of each display object, wherein one or more types of interactive input can be the one or more conditions upon which the rendering-style record for each display object is generated. 13. The MSO as defined in claim 12 , wherein each of said headends is to broadcast on a network selected from the group consisting of: a cable television broadcasting network; a satellite television broadcasting network; an air wave broadcasting television network; a local area network; a wide area network; and the Internet.
| 0.582386 |
13. A computer system comprising: one or more processors, one or more computer-readable memories and one or more computer-readable, tangible storage devices; program instructions, stored on at least one of the one or more storage devices for execution by at least one of the one or more processors via at least one of the one or more memories, to, when in an instructional environment, train of a dynamic string analysis handler of a string analysis module to effectively handle a subset of a plurality of string queries having a plurality of contextual metadata received from a client application, wherein the dynamic string analysis handler is operating in a training mode, wherein an effectiveness of the dynamic string analysis handler is based upon feedback from the client application, and, wherein the subset of string queries represents a spectrum of string queries expected to be generated by the client application in an operational environment; program instructions, stored on at least one of the one or more storage devices for execution by at least one of the one or more processors via at least one of the one or more memories, to, upon completion of the training, synthesize a string analysis algorithm selection policy for the client application, wherein said string analysis algorithm selection policy is based upon interactions between the dynamic string analysis handler and client application when handling the subset of string queries during training, wherein the string analysis algorithm selection policy correlates a context of a string query in the subset to a usage of a string analysis algorithm; and program instructions, stored on at least one of the one or more storage devices for execution by at least one of the one or more processors via at least one of the one or more memories, to, when in the operational environment, dynamically handle the plurality of string queries having the plurality of contextual metadata received from the client application in accordance with the string analysis algorithm selection policy by the dynamic string analysis handler, wherein the dynamic string analysis handler is operating in a production mode, wherein the string analysis algorithm to be used for a string query is dynamically and independently determined.
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13. A computer system comprising: one or more processors, one or more computer-readable memories and one or more computer-readable, tangible storage devices; program instructions, stored on at least one of the one or more storage devices for execution by at least one of the one or more processors via at least one of the one or more memories, to, when in an instructional environment, train of a dynamic string analysis handler of a string analysis module to effectively handle a subset of a plurality of string queries having a plurality of contextual metadata received from a client application, wherein the dynamic string analysis handler is operating in a training mode, wherein an effectiveness of the dynamic string analysis handler is based upon feedback from the client application, and, wherein the subset of string queries represents a spectrum of string queries expected to be generated by the client application in an operational environment; program instructions, stored on at least one of the one or more storage devices for execution by at least one of the one or more processors via at least one of the one or more memories, to, upon completion of the training, synthesize a string analysis algorithm selection policy for the client application, wherein said string analysis algorithm selection policy is based upon interactions between the dynamic string analysis handler and client application when handling the subset of string queries during training, wherein the string analysis algorithm selection policy correlates a context of a string query in the subset to a usage of a string analysis algorithm; and program instructions, stored on at least one of the one or more storage devices for execution by at least one of the one or more processors via at least one of the one or more memories, to, when in the operational environment, dynamically handle the plurality of string queries having the plurality of contextual metadata received from the client application in accordance with the string analysis algorithm selection policy by the dynamic string analysis handler, wherein the dynamic string analysis handler is operating in a production mode, wherein the string analysis algorithm to be used for a string query is dynamically and independently determined. 16. The computer system of claim 13 , comprising: a client application configured to issue query requests comprising the string query and the plurality of contextual metadata regarding the string query, wherein said string query requires string analysis; a string analysis module configured to provide the client application with results of the string analysis responsive to issued query requests, said string analysis module further comprising: a plurality of string analysis algorithms representing different string analysis techniques; and a dynamic string analysis handler configured to, when in the training mode, utilize a heuristic strategy to synthesize the string analysis algorithm selection policy based upon interactions with the client application in an instructional environment, wherein an interaction comprises at least a query request from the client application, a response to the query request by the dynamic string analysis handler, and a selection feedback regarding the response from the client application, wherein the query request of the interactions utilizes the subset of string queries expected to be generated by the client application in the operational environment.
| 0.661404 |
9. A system for improving search relevance for a user search, the system comprising: a search database having a plurality of document identifiers for each of a plurality of referenced documents; a processing device operative to, based on executable instructions, generate a search results page in response to a search request, the search results page including the plurality of document identifiers such that the search results page is presented to a user; a user selection monitoring device operative to determine user selection of one of the document identifiers, including monitoring a page position of the user selected document identifier, and the processing device further operative to, based on the executable instructions: determine a perceived relevance factor for the selected document identifier including prior probability calculations based on the page position of the user selected document identifier to determine relevance based on a position of the document identifier on the search results page and an inverse of the probability calculations to determine relevance of the identifier and identifier meta data; and calculate a relevance factor for the selected document identifier based on the perceived relevance factor and a plurality of document attribute based relevant scores.
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9. A system for improving search relevance for a user search, the system comprising: a search database having a plurality of document identifiers for each of a plurality of referenced documents; a processing device operative to, based on executable instructions, generate a search results page in response to a search request, the search results page including the plurality of document identifiers such that the search results page is presented to a user; a user selection monitoring device operative to determine user selection of one of the document identifiers, including monitoring a page position of the user selected document identifier, and the processing device further operative to, based on the executable instructions: determine a perceived relevance factor for the selected document identifier including prior probability calculations based on the page position of the user selected document identifier to determine relevance based on a position of the document identifier on the search results page and an inverse of the probability calculations to determine relevance of the identifier and identifier meta data; and calculate a relevance factor for the selected document identifier based on the perceived relevance factor and a plurality of document attribute based relevant scores. 10. The system of claim 9 further comprising: a search index operatively coupled to the processing device, the search index having the relevance factor stored therein.
| 0.525242 |
10. A method of providing entities the ability to create, manage, and/or store fine-grained metadata, artifacts, or other software related items of a domain by providing a relational model that stores these items in a way that allows rich querying using database routines and other tools, the method comprising: identifying software related items of a domain; accessing a set of schema guidelines that describe how the software related items of a schematized model of the domain are to be categorized in query tables of a repository, the software related items including both executables and metadata that describes the executables, wherein the set of schema guidelines includes two or more of: naming guidelines; script file guidelines; table guidelines; indexing guidelines; viewing guidelines; procedure and function guidelines; foreign key guidelines; query guidelines; or cursor use guidelines; arranging the software related items into the query tables according to the schema guidelines; providing the software related items to a repository after they have been arranged according to the schema guidelines and in such a way as to cause the organized software related items to be stored by the repository within a plurality of query tables of the repository, wherein the organized software related items are stored in rows of the query tables at the repository, wherein each row includes a container version ID field storing a container version ID that identifies a container to which the organized software related items stored in the row pertain, and wherein the containers are versioned based on when changes to the organized software related items the containers contain are made.
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10. A method of providing entities the ability to create, manage, and/or store fine-grained metadata, artifacts, or other software related items of a domain by providing a relational model that stores these items in a way that allows rich querying using database routines and other tools, the method comprising: identifying software related items of a domain; accessing a set of schema guidelines that describe how the software related items of a schematized model of the domain are to be categorized in query tables of a repository, the software related items including both executables and metadata that describes the executables, wherein the set of schema guidelines includes two or more of: naming guidelines; script file guidelines; table guidelines; indexing guidelines; viewing guidelines; procedure and function guidelines; foreign key guidelines; query guidelines; or cursor use guidelines; arranging the software related items into the query tables according to the schema guidelines; providing the software related items to a repository after they have been arranged according to the schema guidelines and in such a way as to cause the organized software related items to be stored by the repository within a plurality of query tables of the repository, wherein the organized software related items are stored in rows of the query tables at the repository, wherein each row includes a container version ID field storing a container version ID that identifies a container to which the organized software related items stored in the row pertain, and wherein the containers are versioned based on when changes to the organized software related items the containers contain are made. 18. The method of claim 10 , further comprising: storing the plurality of software related items in the software repository using a universal entity-property-value schema; and upon receiving a request to process an application associated with the domain, retrieving the plurality of software related items using the universal entity-property-value schema.
| 0.863602 |
10. A method implemented on a computer comprising a processor, the method comprising: receiving a text content containing text; tokenizing the text content into a plurality of terms each comprising an element selected from the group of elements consisting at least of a word, a phrase, a sentence, a paragraph; identifying a first term in the text content; identifying, in at least a portion of the text content, a second term, wherein the portion of the text content contains the first term or is grammatically or semantically associated with the first term; identifying a first grammatical attribute associated with the second term, or identifying a first semantic attribute associated with the second term; selecting the second term as a term related to the first term based at least on the first grammatical attribute or the first semantic attribute; marking the first term for use as a first-level entity in a hierarchical format, and marking the second term for use as a second-level entity in the hierarchical format, wherein the second-level entity is marked as an element under or subordinate to the first-level entity; and outputting the first term and the second term to be used for at least providing a relational or hierarchical representation of the informational elements in the text content; when the first term is used to represent a first-level category node, and the second term is used to represent a second-level category node or the content of the first-level category, an embodiment format of at least one of the category nodes includes a text element, a folder or a directory, or a link name associated with the linked contents on a device selected from the group of devices consisting at least of a computer file system, an email system, a web-based or cloud-based system, a mobile or handheld computing or communication device; when the first term and the second term are displayed, a display format comprises at least representing the first term as a topic or information focus in the text content, and the second term as a comment or attribute associated with the topic or the information focus; or representing the first term as a folder or directory in an electronic content management system, and the second term as a sub-folder or sub-directory in the electronic content management system; when the text content or the first term is made searchable using a query or is associated with a search index to produce a search result, a display format of the search result comprises the first term with one or more of its corresponding second terms if the first term matches a keyword in the search query.
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10. A method implemented on a computer comprising a processor, the method comprising: receiving a text content containing text; tokenizing the text content into a plurality of terms each comprising an element selected from the group of elements consisting at least of a word, a phrase, a sentence, a paragraph; identifying a first term in the text content; identifying, in at least a portion of the text content, a second term, wherein the portion of the text content contains the first term or is grammatically or semantically associated with the first term; identifying a first grammatical attribute associated with the second term, or identifying a first semantic attribute associated with the second term; selecting the second term as a term related to the first term based at least on the first grammatical attribute or the first semantic attribute; marking the first term for use as a first-level entity in a hierarchical format, and marking the second term for use as a second-level entity in the hierarchical format, wherein the second-level entity is marked as an element under or subordinate to the first-level entity; and outputting the first term and the second term to be used for at least providing a relational or hierarchical representation of the informational elements in the text content; when the first term is used to represent a first-level category node, and the second term is used to represent a second-level category node or the content of the first-level category, an embodiment format of at least one of the category nodes includes a text element, a folder or a directory, or a link name associated with the linked contents on a device selected from the group of devices consisting at least of a computer file system, an email system, a web-based or cloud-based system, a mobile or handheld computing or communication device; when the first term and the second term are displayed, a display format comprises at least representing the first term as a topic or information focus in the text content, and the second term as a comment or attribute associated with the topic or the information focus; or representing the first term as a folder or directory in an electronic content management system, and the second term as a sub-folder or sub-directory in the electronic content management system; when the text content or the first term is made searchable using a query or is associated with a search index to produce a search result, a display format of the search result comprises the first term with one or more of its corresponding second terms if the first term matches a keyword in the search query. 19. The method of claim 10 , when the first grammatical attribute is identified and used, the first grammatical attribute includes a subject, a predicate, a sub-phrase of a multi-word phrase, a modifier in a multi-word phrase, a head of a multi-word phrase, a direct or indirect object, a predicative, a complement; and the first grammatical attribute further includes parts of speech, wherein the parts of speech include at least a noun or a pronoun, a transitive or intransitive verb or modal verb or link verb, an adjective, an adverb, a preposition, an article, a conjunction.
| 0.547281 |
1. A method of recognizing words, comprising: accepting a stroke as an input on a virtual keyboard coupled to a computer, the computer programmed to perform the steps of: defining word patterns of a plurality of known words by a plurality of paths, wherein each path connects elements in the known word on the virtual keyboard, wherein the virtual keyboard comprises virtual keys, each virtual key representing a letter in a word without a temporary target letter being placed adjacent to a location of a stroke; processing the stroke using a combination of a plurality of channels, each channel selectively measuring a different aspect of a similarity of the stroke to a plurality of possible paths on the virtual keyboard; converting each different aspect of the stroke's similarity to probability estimates; a shape channel of the plurality of channels measuring a shape aspect of the stroke, and outputting a probability estimate; a location channel of the plurality of channels measuring location aspect of the stroke, and outputting a probability estimate, wherein the location channel measures the location aspect of the stroke concurrently with the shape channel measuring the shape aspect of the stroke; mathematically integrating, using Bayes' theorem, the probability estimates of the plurality of channels to produce integrated probability estimates of candidate words corresponding to the stroke; and based on the integrated probability estimates of the candidate words, recognizing the stroke as a known word.
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1. A method of recognizing words, comprising: accepting a stroke as an input on a virtual keyboard coupled to a computer, the computer programmed to perform the steps of: defining word patterns of a plurality of known words by a plurality of paths, wherein each path connects elements in the known word on the virtual keyboard, wherein the virtual keyboard comprises virtual keys, each virtual key representing a letter in a word without a temporary target letter being placed adjacent to a location of a stroke; processing the stroke using a combination of a plurality of channels, each channel selectively measuring a different aspect of a similarity of the stroke to a plurality of possible paths on the virtual keyboard; converting each different aspect of the stroke's similarity to probability estimates; a shape channel of the plurality of channels measuring a shape aspect of the stroke, and outputting a probability estimate; a location channel of the plurality of channels measuring location aspect of the stroke, and outputting a probability estimate, wherein the location channel measures the location aspect of the stroke concurrently with the shape channel measuring the shape aspect of the stroke; mathematically integrating, using Bayes' theorem, the probability estimates of the plurality of channels to produce integrated probability estimates of candidate words corresponding to the stroke; and based on the integrated probability estimates of the candidate words, recognizing the stroke as a known word. 3. The method of claim 1 , wherein the plurality of channels comprises a tunnel model channel, wherein the tunnel of a word pattern comprises a predetermined width on either side of a set of the virtual keys representing a set of letters of a word on the virtual keyboard, and wherein the tunnel model channel is applied to the stroke before any other channel is applied to the stroke.
| 0.569338 |
1. A method for identifying characters in a handwritten input on a touch-sensitive device, the method comprising: establishing an anchor point on the touch-sensitive device; establishing distances from the anchor point to one or more reference support lines; receiving a handwritten user input via the touch-sensitive device; identifying a set of candidate characters based on the handwritten user input; estimating support lines for each of the candidate characters; associating temporary reference support lines for each candidate character based on: an angle of the estimated support lines for the candidate character and the established anchor point, and the established distances from the anchor point to the one or more reference support lines; for each candidate character, measuring a deviation between the estimated support lines and temporary reference support lines to determine a scale and position deviation from an expectation for each candidate character, and combining the measured deviation with candidate expectation deviation measurements for properties other than scale and position; ranking each candidate character based on a total deviation measurement for each candidate character; and, identifying a best-ranked candidate character based at least in part on a smallest total deviation measurement.
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1. A method for identifying characters in a handwritten input on a touch-sensitive device, the method comprising: establishing an anchor point on the touch-sensitive device; establishing distances from the anchor point to one or more reference support lines; receiving a handwritten user input via the touch-sensitive device; identifying a set of candidate characters based on the handwritten user input; estimating support lines for each of the candidate characters; associating temporary reference support lines for each candidate character based on: an angle of the estimated support lines for the candidate character and the established anchor point, and the established distances from the anchor point to the one or more reference support lines; for each candidate character, measuring a deviation between the estimated support lines and temporary reference support lines to determine a scale and position deviation from an expectation for each candidate character, and combining the measured deviation with candidate expectation deviation measurements for properties other than scale and position; ranking each candidate character based on a total deviation measurement for each candidate character; and, identifying a best-ranked candidate character based at least in part on a smallest total deviation measurement. 5. The method of claim 1 wherein: the reference support lines include a helpline and a baseline and the helpline and the baseline are parallel; the helpline is a first predetermined perpendicular distance from the anchor point; and the baseline is a second predetermined perpendicular distance from the anchor point.
| 0.72216 |
1. In a computing environment, a method executed at least in part on at least one processor, comprising: receiving a query; extracting features related to the query that comprise a context feature set, and a frequency feature set, the context feature set comprising textual context-related features of query keyword data in news items, the frequency feature set comprising keyword frequency data in the news items; using the features to estimate whether the query is a news-related query, including by providing the features to a classifier that is built by referencing data that corresponds to news items updated within a preset time period with at least one data source that has not been updated within the preset time period, and by detecting temporal changes associated with the data that corresponds to news items updated within the preset time period; receiving classification output corresponding to a predicted click-through rate from the classifier; estimating from the classification output whether the query is a news-related query; and outputting results based at least in part on the estimate of whether the query is news-related.
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1. In a computing environment, a method executed at least in part on at least one processor, comprising: receiving a query; extracting features related to the query that comprise a context feature set, and a frequency feature set, the context feature set comprising textual context-related features of query keyword data in news items, the frequency feature set comprising keyword frequency data in the news items; using the features to estimate whether the query is a news-related query, including by providing the features to a classifier that is built by referencing data that corresponds to news items updated within a preset time period with at least one data source that has not been updated within the preset time period, and by detecting temporal changes associated with the data that corresponds to news items updated within the preset time period; receiving classification output corresponding to a predicted click-through rate from the classifier; estimating from the classification output whether the query is a news-related query; and outputting results based at least in part on the estimate of whether the query is news-related. 2. The method of claim 1 wherein extracting the features related to the query comprises evaluating at least one word in the query against frequency information in the data that corresponds to news items updated within the preset time period.
| 0.714795 |
7. One or more computer-readable storage devices having computer-executable instructions stored thereon that, when executed, direct a computer to perform a method, the method comprising: providing a quantifier input parameter that decides whether the quantified formula holds; setting the quantifier input parameter to true and finding at least one quantifier instantiation that restricts at least one possible value for the input parameter by performing a quantifier instantiation method, the quantifier instantiation method comprising: making a quantified assumption as to the input parameter; partially evaluating a pattern in the quantified assumption by run-time values of non-bound parameters; applying a maximal partial evaluation on the pattern to create a maximally partially evaluated pattern such that constant folding is applied to all sub-terms that do not contain any quantified variables; and at run-time, building a symbolic state of the program based on a symbolic representation of the current state of the program; labeling each node in the symbolic state with a corresponding concrete run-time value; enumerating the sub-terms that appear in the symbolic state; and matching the maximally partially evaluated pattern against the enumerated sub-terms; and setting the quantifier input parameter to false and non-deterministically finding a value for the bound variable of the quantifier such that the quantified formula does not hold for this value.
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7. One or more computer-readable storage devices having computer-executable instructions stored thereon that, when executed, direct a computer to perform a method, the method comprising: providing a quantifier input parameter that decides whether the quantified formula holds; setting the quantifier input parameter to true and finding at least one quantifier instantiation that restricts at least one possible value for the input parameter by performing a quantifier instantiation method, the quantifier instantiation method comprising: making a quantified assumption as to the input parameter; partially evaluating a pattern in the quantified assumption by run-time values of non-bound parameters; applying a maximal partial evaluation on the pattern to create a maximally partially evaluated pattern such that constant folding is applied to all sub-terms that do not contain any quantified variables; and at run-time, building a symbolic state of the program based on a symbolic representation of the current state of the program; labeling each node in the symbolic state with a corresponding concrete run-time value; enumerating the sub-terms that appear in the symbolic state; and matching the maximally partially evaluated pattern against the enumerated sub-terms; and setting the quantifier input parameter to false and non-deterministically finding a value for the bound variable of the quantifier such that the quantified formula does not hold for this value. 12. The one or more computer-readable storage devices of claim 7 wherein the method further comprises: identifying at least one test case when the quantifier input parameter is true; and identifying at least one test case when the quantifier input parameter is false.
| 0.910845 |
1. A method comprising: receiving a query for a target data set managed by a database management system, the query specifying a predicate for a particular column of the target data set, said predicate comprising a filtering value to be compared with row values of the particular column of the target data set; prior to accessing a plurality of data block sets that store the target data set in persistent storage, identifying a plurality of in-memory summaries, each in-memory summary of said plurality of in-memory summaries corresponding to a corresponding data block set from the plurality of data block sets, said each in- memory summary comprising one or more in-memory data structures, each in- memory data structure of said one or more in-memory data structures representing values stored in the corresponding data block set in a corresponding column of the target data set; wherein a particular in-memory data structure of said plurality of in-memory summaries represents values of the particular column stored in a particular data block set of said plurality of data block sets; determining whether the particular data block set can possibly contain the filtering value in the particular column by at least determining, based on the particular in- memory data structure, a set of membership of said filtering value in the values of the particular column stored in said particular data block set; if the determination is that the particular data block set cannot possibly contain the filtering value in the particular column, skipping a retrieval of the particular data block set from the persistent storage in evaluating the query; if the determination is that the particular data block set can possibly contain the filtering value in the particular column, retrieving the particular data block set from the persistent storage for evaluating the query; and wherein the method is executed by one or more computing devices.
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1. A method comprising: receiving a query for a target data set managed by a database management system, the query specifying a predicate for a particular column of the target data set, said predicate comprising a filtering value to be compared with row values of the particular column of the target data set; prior to accessing a plurality of data block sets that store the target data set in persistent storage, identifying a plurality of in-memory summaries, each in-memory summary of said plurality of in-memory summaries corresponding to a corresponding data block set from the plurality of data block sets, said each in- memory summary comprising one or more in-memory data structures, each in- memory data structure of said one or more in-memory data structures representing values stored in the corresponding data block set in a corresponding column of the target data set; wherein a particular in-memory data structure of said plurality of in-memory summaries represents values of the particular column stored in a particular data block set of said plurality of data block sets; determining whether the particular data block set can possibly contain the filtering value in the particular column by at least determining, based on the particular in- memory data structure, a set of membership of said filtering value in the values of the particular column stored in said particular data block set; if the determination is that the particular data block set cannot possibly contain the filtering value in the particular column, skipping a retrieval of the particular data block set from the persistent storage in evaluating the query; if the determination is that the particular data block set can possibly contain the filtering value in the particular column, retrieving the particular data block set from the persistent storage for evaluating the query; and wherein the method is executed by one or more computing devices. 7. The method of claim 1 , wherein the particular in-memory data structure is a dictionary data structure; the method further comprising: generating a hash value for the filtering value by applying a hash algorithm to the filtering value; comparing the hash value of the filtering value to one or more hash values stored in the dictionary data structure; if the hash value for the filtering value exists in the dictionary data structure, then determining the particular data block set can possibly contain the filtering value in the particular column of the target data set; and if the hash value for the filtering value does not exist in the dictionary data structure, then determining the particular data block set cannot possibly contain the filtering value in the particular column of the target data set.
| 0.592341 |
1. A memory having computer executable instructions encoded thereon, the computer executable instructions executed by a processor to perform location-related mining operations, the operations comprising: identifying a particular travelogue; decomposing the particular travelogue by identifying at least two non-overlapping segments of the particular travelogue, each segment including a representation of at least one location; representing a collection of travelogues with a term-document matrix, the collection of travelogues comprising the particular travelogue, and each word of the particular travelogue representing: a location, a local topic, and a term in a sequence; or a global topic and a term in a sequence; using a probabilistic topic model, decomposing the term-document matrix into one or more matrices comprising: a term-local topic matrix; a local topic-location matrix; or a location-document matrix; and representing a particular location by a multinomial distribution over local topics while associating a document with a multinomial distribution over global topics.
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1. A memory having computer executable instructions encoded thereon, the computer executable instructions executed by a processor to perform location-related mining operations, the operations comprising: identifying a particular travelogue; decomposing the particular travelogue by identifying at least two non-overlapping segments of the particular travelogue, each segment including a representation of at least one location; representing a collection of travelogues with a term-document matrix, the collection of travelogues comprising the particular travelogue, and each word of the particular travelogue representing: a location, a local topic, and a term in a sequence; or a global topic and a term in a sequence; using a probabilistic topic model, decomposing the term-document matrix into one or more matrices comprising: a term-local topic matrix; a local topic-location matrix; or a location-document matrix; and representing a particular location by a multinomial distribution over local topics while associating a document with a multinomial distribution over global topics. 2. A memory as recited in claim 1 , wherein the one or more matrices further comprise at least one of a term-global topic matrix or a global topic-document matrix.
| 0.545797 |
1. A method performed by one or more server devices, the method comprising: storing, by a processor associated with the one or more server devices, a user profile that includes an author likelihood score of a particular user, the author likelihood score estimating a likelihood that the particular user will become an author of comments; receiving, by a processor associated with the one or more server devices and from users, one or more explicit requests for comments for a particular document, the one or more explicit requests for comments being associated with the users selecting a visual object to request comments about the particular document when the particular document is a document without comments; receiving, by a processor associated with the one or more server devices, an indication that the particular user has accessed flail the particular document; determining, by a processor associated with the one or more server devices, that the particular document has been identified as needing comments when a quantity of the one or more explicit requests for comments, received for the particular document, exceeds a threshold; retrieving, by a processor associated with the one or more server devices and from the user profile, the author likelihood score for the particular user, based on determining that the particular document has been identified as needing comments; determining, by a processor associated with the one or more server devices, whether the retrieved author likelihood score is greater than a particular threshold; and providing, by a processor associated with the one or more server devices, a suggestion to the particular user to write a comment about the particular document, based on: determining that the retrieved author likelihood score is greater than the particular threshold, and determining that the particular document has been identified as needing comments.
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1. A method performed by one or more server devices, the method comprising: storing, by a processor associated with the one or more server devices, a user profile that includes an author likelihood score of a particular user, the author likelihood score estimating a likelihood that the particular user will become an author of comments; receiving, by a processor associated with the one or more server devices and from users, one or more explicit requests for comments for a particular document, the one or more explicit requests for comments being associated with the users selecting a visual object to request comments about the particular document when the particular document is a document without comments; receiving, by a processor associated with the one or more server devices, an indication that the particular user has accessed flail the particular document; determining, by a processor associated with the one or more server devices, that the particular document has been identified as needing comments when a quantity of the one or more explicit requests for comments, received for the particular document, exceeds a threshold; retrieving, by a processor associated with the one or more server devices and from the user profile, the author likelihood score for the particular user, based on determining that the particular document has been identified as needing comments; determining, by a processor associated with the one or more server devices, whether the retrieved author likelihood score is greater than a particular threshold; and providing, by a processor associated with the one or more server devices, a suggestion to the particular user to write a comment about the particular document, based on: determining that the retrieved author likelihood score is greater than the particular threshold, and determining that the particular document has been identified as needing comments. 4. The method of claim 1 , further comprising: identifying the particular document as a document without comments, where the particular document is associated with a product, a business, a book, or a published paper; and identifying the particular document as needing comments based on: identifying the particular document as a document without comments, and the particular document being associated with a product, a business, a book, or a published paper.
| 0.6945 |
12. A method for use with a group of patents retrieved from a data warehouse, the group of retrieved patents related to a given seed patent from an originating industry, the method comprising: extracting a set of similar patents from said group of retrieved patents, each of said similar patents associated with said given seed patent using a statistical method; classifying said given seed patent and said set of similar patents by at least one of assignees and industries; generating an industry taxonomy for said given seed patent and said set of similar patents using at least one of a structured feature and an unstructured feature; mapping assignees of said similar patents to related industries using said industry taxonomy; computing the overall similarity between said originating industry and said related industries; and computing patent similarity between said seed patent and patents assigned to said related industries.
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12. A method for use with a group of patents retrieved from a data warehouse, the group of retrieved patents related to a given seed patent from an originating industry, the method comprising: extracting a set of similar patents from said group of retrieved patents, each of said similar patents associated with said given seed patent using a statistical method; classifying said given seed patent and said set of similar patents by at least one of assignees and industries; generating an industry taxonomy for said given seed patent and said set of similar patents using at least one of a structured feature and an unstructured feature; mapping assignees of said similar patents to related industries using said industry taxonomy; computing the overall similarity between said originating industry and said related industries; and computing patent similarity between said seed patent and patents assigned to said related industries. 16. The method of claim 12 further comprising overlaying trend information on said industry taxonomy to identify recent industries.
| 0.634223 |
1. A method for creating digitized text for a record from an image of the record, comprising: obtaining a digital image of a record; evaluating the record image in order to locate each of multiple word images; for each located word image, identifying multiple word features of that word image; assigning each of the multiple word images that have similar word features to one of a plurality of word clusters; selecting a representative word image in each of the word clusters as a centroid; reviewing, by an analyst, the centroid in each of the word clusters, and entering digitized text for the centroid; and assigning the digitized text for the centroid to all other word images in the same word cluster as the centroid.
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1. A method for creating digitized text for a record from an image of the record, comprising: obtaining a digital image of a record; evaluating the record image in order to locate each of multiple word images; for each located word image, identifying multiple word features of that word image; assigning each of the multiple word images that have similar word features to one of a plurality of word clusters; selecting a representative word image in each of the word clusters as a centroid; reviewing, by an analyst, the centroid in each of the word clusters, and entering digitized text for the centroid; and assigning the digitized text for the centroid to all other word images in the same word cluster as the centroid. 5. The method of claim 1 , wherein the record is a historical record having handwritten words, and wherein the multiple word images are each an image of one of the handwritten words.
| 0.777002 |
4. The process of claim 1 , wherein the process action of personalizing results of the search based on knowledge of the identified site or IO comprises the actions of: maintaining a record of the individuals' search or interaction history in the search engine; and displaying aspects of the individuals' search or interaction history record to the individuals.
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4. The process of claim 1 , wherein the process action of personalizing results of the search based on knowledge of the identified site or IO comprises the actions of: maintaining a record of the individuals' search or interaction history in the search engine; and displaying aspects of the individuals' search or interaction history record to the individuals. 5. The process of claim 4 , wherein the process action of displaying aspects of the individuals' search or interaction history record to the individuals comprises at least one of the following actions: emphasizing PNQs residing in said record; or emphasizing sites or IOs that are strongly associated with PNQs; or emphasizing sites or IOs that are visited at the end of a session; or displaying said aspects to the individuals automatically at the beginning of a new session; or displaying said aspects to the individuals in context as the individuals conduct a related follow-on search; or displaying said aspects to the individuals prior to the search on a search page; or displaying said aspects to the individuals prior to the search as part of a graphical user interface for the query.
| 0.884413 |
31. An apparatus for generating a structured text from an unstructured text, the apparatus comprising a computer system configured to: segment the unstructured text into text sections; assign, to at least one text section, a topic being indicative of content of the at least one text section, the topic being associated with a plurality of section headings; identify a text portion as being a full or partial verbalization of a section heading for the at least one text section, the section heading being selected from the plurality of section headings associated with the topic assigned to the at least one text section; provide to a user a first structured text comprising the at least one text section and the section heading for the at least one text section, wherein the text portion identified as being a full or partial verbalization of the section heading is removed from the first structured text; receive user input indicating at least one modification to the first structured text; and process the at least one modification received from the user to generate a second structured text.
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31. An apparatus for generating a structured text from an unstructured text, the apparatus comprising a computer system configured to: segment the unstructured text into text sections; assign, to at least one text section, a topic being indicative of content of the at least one text section, the topic being associated with a plurality of section headings; identify a text portion as being a full or partial verbalization of a section heading for the at least one text section, the section heading being selected from the plurality of section headings associated with the topic assigned to the at least one text section; provide to a user a first structured text comprising the at least one text section and the section heading for the at least one text section, wherein the text portion identified as being a full or partial verbalization of the section heading is removed from the first structured text; receive user input indicating at least one modification to the first structured text; and process the at least one modification received from the user to generate a second structured text. 32. The apparatus according to claim 31 , wherein the section heading for the at least one text section is a section heading in the plurality of section headings that is most frequently selected for the topic assigned to the at least one text section.
| 0.661976 |
9. Apparatus for classifying structural input data, the apparatus comprising: a memory; and a processor operatively coupled to the memory and configured to: construct multiple classifiers, wherein each classifier is constructed on a subset of training data, using selected composite features from the subset of training data, the composite features being selected by iteratively applying a feature selection step wherein multiple disjoint feature sets are identified to represent the structural input data in different feature spaces, and the structural input data, when characterized by a skewed prior class distribution, being subjected to a sampling step to obtain a balanced class distribution; and compute a consensus among the multiple classifiers in accordance with a voting scheme such that at least a portion of the structural input data is assigned to a particular class in accordance with the computed consensus.
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9. Apparatus for classifying structural input data, the apparatus comprising: a memory; and a processor operatively coupled to the memory and configured to: construct multiple classifiers, wherein each classifier is constructed on a subset of training data, using selected composite features from the subset of training data, the composite features being selected by iteratively applying a feature selection step wherein multiple disjoint feature sets are identified to represent the structural input data in different feature spaces, and the structural input data, when characterized by a skewed prior class distribution, being subjected to a sampling step to obtain a balanced class distribution; and compute a consensus among the multiple classifiers in accordance with a voting scheme such that at least a portion of the structural input data is assigned to a particular class in accordance with the computed consensus. 10. The apparatus of claim 9 , wherein the subset of training data is selected from a full training dataset, among which positive and negative data are balanced.
| 0.528828 |
14. A server for processing an application search query, the server comprising: a storage device that stores: a plurality of application representations, each application representation being a data structure representing a different application and including one or more features of the application, the features of the application being extracted from one or more documents obtained from one or more respective sources, each document relating to the application; and a search index that indexes the plurality of application representations, each application representation representing a different application and including one or more features of the application; a processing device that executes computer-readable instructions, the computer-executable instructions causing the processing device to: receive a search query from a partner device; determine a set of subqueries based on the search query; extract query features of the search query from the search query; determine an initial result set of application representations based on the set of subqueries and the search index, the initial result set including a set of one or more application representations from the plurality of application representations; determine a score for each application representation in the initial result set of application representations based on the set of query features and one or more machine-learned scoring models; determine a ranked result set based on the scores for the application representations of the initial result set, the ranked result set indicating one or more applications that correspond to the search query; and provide the ranked result set to the partner.
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14. A server for processing an application search query, the server comprising: a storage device that stores: a plurality of application representations, each application representation being a data structure representing a different application and including one or more features of the application, the features of the application being extracted from one or more documents obtained from one or more respective sources, each document relating to the application; and a search index that indexes the plurality of application representations, each application representation representing a different application and including one or more features of the application; a processing device that executes computer-readable instructions, the computer-executable instructions causing the processing device to: receive a search query from a partner device; determine a set of subqueries based on the search query; extract query features of the search query from the search query; determine an initial result set of application representations based on the set of subqueries and the search index, the initial result set including a set of one or more application representations from the plurality of application representations; determine a score for each application representation in the initial result set of application representations based on the set of query features and one or more machine-learned scoring models; determine a ranked result set based on the scores for the application representations of the initial result set, the ranked result set indicating one or more applications that correspond to the search query; and provide the ranked result set to the partner. 20. The server of claim 14 where the query features are based on the query terms and the contextual data.
| 0.704772 |
1. A method for distributing secure digital content that can be indexed by third party search engines, the method comprising: generating a text stream from the digital content by stripping all graphic information and punctuation from the digital content; fragmenting the text stream into multi-word phrases that are each contained in the digital content; randomly assembling the phrases into a scrambled document such that the scrambled document contains at least nearly all of the words and at least most of the phrases as are contained in the digital content; and making the scrambled document available to third party search engines to permit indexing of the scrambled document that will result in an index that is comparable to an index that would result if the third party search engine indexed the digital content.
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1. A method for distributing secure digital content that can be indexed by third party search engines, the method comprising: generating a text stream from the digital content by stripping all graphic information and punctuation from the digital content; fragmenting the text stream into multi-word phrases that are each contained in the digital content; randomly assembling the phrases into a scrambled document such that the scrambled document contains at least nearly all of the words and at least most of the phrases as are contained in the digital content; and making the scrambled document available to third party search engines to permit indexing of the scrambled document that will result in an index that is comparable to an index that would result if the third party search engine indexed the digital content. 5. The method of claim 1 wherein the randomly assembling step comprises forming a stream of phrases and randomly swapping the position of phrases in the phrase stream.
| 0.585845 |
1. A system, comprising: an inference data acquisition module configured to acquire inference data that indicate an inferred mental state of an authoring user in connection with a particular item of an electronic message, the inference data derived based, at least in part, on at least one physical characteristic of the authoring user; one or more sensors configured to sense the at least one physical characteristic of the authoring user in connection with the particular item of the electronic message; a source identity acquisition module configured to acquire source identity data providing at least one identity of one or more sources that provide a basis, at least in part, for the inference data, the one or more sources including at least the one or more sensors; an inference data association module configured to associate the inference data with the particular item, the inference data association module including at least an inference data inclusion module configured to include the inference data into the electronic message; and a source identity association module configured to associate the source identity data with the particular item, the source identity association module including at least a source identity inclusion module configured to include into the electronic message one or more identities of the one or more sensors, the one or more sensors having been used to derive, at least in part, the inference data acquired by the inference data acquisition module; and wherein the electronic message thereby includes at least a data pair that includes at least the inference data that indicate the inferred mental state of the authoring user in connection with the particular item and the one or more identities of the one or more sensors used to derive, at least in part, the inference data.
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1. A system, comprising: an inference data acquisition module configured to acquire inference data that indicate an inferred mental state of an authoring user in connection with a particular item of an electronic message, the inference data derived based, at least in part, on at least one physical characteristic of the authoring user; one or more sensors configured to sense the at least one physical characteristic of the authoring user in connection with the particular item of the electronic message; a source identity acquisition module configured to acquire source identity data providing at least one identity of one or more sources that provide a basis, at least in part, for the inference data, the one or more sources including at least the one or more sensors; an inference data association module configured to associate the inference data with the particular item, the inference data association module including at least an inference data inclusion module configured to include the inference data into the electronic message; and a source identity association module configured to associate the source identity data with the particular item, the source identity association module including at least a source identity inclusion module configured to include into the electronic message one or more identities of the one or more sensors, the one or more sensors having been used to derive, at least in part, the inference data acquired by the inference data acquisition module; and wherein the electronic message thereby includes at least a data pair that includes at least the inference data that indicate the inferred mental state of the authoring user in connection with the particular item and the one or more identities of the one or more sensors used to derive, at least in part, the inference data. 16. The system of claim 1 , wherein said source identity acquisition module configured to acquire source identity data providing at least one identity of one or more sources that provide a basis, at least in part, for the inference data, the one or more sources including at least the one or more sensors comprises: a source identity acquisition module configured to acquire at least one identity of the one or more sources from a memory.
| 0.617235 |
1. At a Web server, a method for identifying appropriate client-side script references, the method comprising: an act of receiving, at a Web server, a Web page request from a Web browser; an act of accessing a server side page that corresponds to the requested Web page, the server side page including a script manager reference that references a script manager script; an act of executing the server side page, including executing the script manager referenced by the script manager reference to load the script manager; an act of the script manager receiving a list of client-side script references that are to be included in the Web page to be sent to the Web browser; an act of the script manager determining, based on script selection rules, whether the list of client-side script references is to be modified prior to sending the list to the Web browser, including, for at least one client-side script reference in the list: (i) a first act of determining, based on the script selection rules, if the client-side script referenced by the client-side script reference is appropriately optimized for executing in a designated script execution environment at the Web browser; or (ii) a second act of determining, based on the script selection rules, if the client-side script referenced by the client-side script, reference is stored in a location that is an appropriate source; an act of the script manager modifying the list of client-side script references by replacing at least one client-side script reference in the list with a different client-side script reference that was selected as a more appropriate client-side script reference based on the script selection rules, wherein modifying the list includes replacing a client-side script reference that references a release version of a client-side script with a client-side script reference that references a debug version of a client-side script; and an act of sending the modified list of client-side script references to the browser to be used in rendering the Web page.
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1. At a Web server, a method for identifying appropriate client-side script references, the method comprising: an act of receiving, at a Web server, a Web page request from a Web browser; an act of accessing a server side page that corresponds to the requested Web page, the server side page including a script manager reference that references a script manager script; an act of executing the server side page, including executing the script manager referenced by the script manager reference to load the script manager; an act of the script manager receiving a list of client-side script references that are to be included in the Web page to be sent to the Web browser; an act of the script manager determining, based on script selection rules, whether the list of client-side script references is to be modified prior to sending the list to the Web browser, including, for at least one client-side script reference in the list: (i) a first act of determining, based on the script selection rules, if the client-side script referenced by the client-side script reference is appropriately optimized for executing in a designated script execution environment at the Web browser; or (ii) a second act of determining, based on the script selection rules, if the client-side script referenced by the client-side script, reference is stored in a location that is an appropriate source; an act of the script manager modifying the list of client-side script references by replacing at least one client-side script reference in the list with a different client-side script reference that was selected as a more appropriate client-side script reference based on the script selection rules, wherein modifying the list includes replacing a client-side script reference that references a release version of a client-side script with a client-side script reference that references a debug version of a client-side script; and an act of sending the modified list of client-side script references to the browser to be used in rendering the Web page. 13. The method as recited in claim 1 , wherein the act of modifying the list further comprises: an act of determining that a first client-side script reference that is selected to replace a second client-side script reference in the list is already included in the list; and an act of removing the second client-side script reference from the list and an act of not adding the first client-side script reference selected to replace the second client-side script reference to the list.
| 0.5 |
1. A method of automatically developing an ontology via a computer system based on communication data and summarizing the communication data using the ontology, wherein the ontology is a structural representation of language elements and the relationships between those language elements within the dataset stored in memory of the computer system, the method comprising: receiving, by the computer system, the communication data, wherein the communication data comprises conversational communication data; developing, by the computer system, the ontology by: segmenting the communication data into meaning units, each meaning unit is a sequence of words that express an idea; identifying terms within the meaning units in the communication data, wherein the terms are individual words or short phrases that represent basic concepts in the communication data; defining relations between the terms, wherein the relations are defined binary directed relationships between terms; and grouping the relations into themes, wherein each relation is grouped into only a single theme; identifying, by the computer system, one or more relevant themes in the communication data from the themes in the ontology, wherein the relevant themes include a set of the relations in the ontology that compose the relevant themes; locating, by the computer system, the relevant themes in the communication data; creating, by the computer system, snippets of the communication data to include the located relevant themes, wherein the snippets include a certain number of characters, words, lines, sentences and/or meaning units in the communication data before and/or after each located theme; and displaying, by the computer system, the snippets.
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1. A method of automatically developing an ontology via a computer system based on communication data and summarizing the communication data using the ontology, wherein the ontology is a structural representation of language elements and the relationships between those language elements within the dataset stored in memory of the computer system, the method comprising: receiving, by the computer system, the communication data, wherein the communication data comprises conversational communication data; developing, by the computer system, the ontology by: segmenting the communication data into meaning units, each meaning unit is a sequence of words that express an idea; identifying terms within the meaning units in the communication data, wherein the terms are individual words or short phrases that represent basic concepts in the communication data; defining relations between the terms, wherein the relations are defined binary directed relationships between terms; and grouping the relations into themes, wherein each relation is grouped into only a single theme; identifying, by the computer system, one or more relevant themes in the communication data from the themes in the ontology, wherein the relevant themes include a set of the relations in the ontology that compose the relevant themes; locating, by the computer system, the relevant themes in the communication data; creating, by the computer system, snippets of the communication data to include the located relevant themes, wherein the snippets include a certain number of characters, words, lines, sentences and/or meaning units in the communication data before and/or after each located theme; and displaying, by the computer system, the snippets. 7. The method of claim 1 , wherein the conversational communication data is one or more selected from the group consisting of: a transcript of an interpersonal interaction; an audio recording; streaming audio; transcription of spoken content; written correspondence or communication; email; physical mail; internet chat; and text message.
| 0.5 |
4. The method according to claim 2 , wherein identifying the at least one of the plurality of database connections comprises: matching the keyword with analytics metadata for a plurality of databases associated with the at least one of the plurality of database connections; and if a match occurs, selecting the at least one of the plurality of database connections for rating.
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4. The method according to claim 2 , wherein identifying the at least one of the plurality of database connections comprises: matching the keyword with analytics metadata for a plurality of databases associated with the at least one of the plurality of database connections; and if a match occurs, selecting the at least one of the plurality of database connections for rating. 6. The method according to claim 4 , wherein the rating comprises: assigning a score to each of the plurality of databases associated with the at least one of the plurality of database connections, based on the matching.
| 0.915411 |
1. A computer-implemented method of constructing a user knowledge profile, the method including: automatically assigning a confidence level to content within an electronic document associated with a first user, the content being potentially indicative of a user knowledge base of the first user; and storing the content in either a first or a second portion of a user knowledge profile of the first user according to the assigned confidence level, wherein the first and the second portions of the user knowledge profile of the first user have different access restrictions with respect to a second user.
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1. A computer-implemented method of constructing a user knowledge profile, the method including: automatically assigning a confidence level to content within an electronic document associated with a first user, the content being potentially indicative of a user knowledge base of the first user; and storing the content in either a first or a second portion of a user knowledge profile of the first user according to the assigned confidence level, wherein the first and the second portions of the user knowledge profile of the first user have different access restrictions with respect to a second user. 29. The method of claim 1 wherein the electronic document comprises an electronic mail message generated by the first user.
| 0.609125 |
9. In a system including one or more reduced dimensionality indexes to multidimensional data, a method for searching for k records most similar to specified data, using the one or more indexes, the method comprising the steps of: identifying the specified data with a cluster based on clustering information, said cluster being a partition from an original data input set; after said identifying step, reducing a dimensionality of the specified data, based on dimensionality reduction information for an identified cluster; recursively applying said identifying and reducing steps until a corresponding lowest level of a hierarchy of reduced dimensionality clusters has been reached; generating dimensionality reduction information for reduced dimensionality specified data, in response to said reducing; and retrieving the .ltoreq.k records most similar to the specified data from the identified cluster using the one or more reduced dimensionality indexes, the dimensionality reduction information and the reduced dimensionality specified data.
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9. In a system including one or more reduced dimensionality indexes to multidimensional data, a method for searching for k records most similar to specified data, using the one or more indexes, the method comprising the steps of: identifying the specified data with a cluster based on clustering information, said cluster being a partition from an original data input set; after said identifying step, reducing a dimensionality of the specified data, based on dimensionality reduction information for an identified cluster; recursively applying said identifying and reducing steps until a corresponding lowest level of a hierarchy of reduced dimensionality clusters has been reached; generating dimensionality reduction information for reduced dimensionality specified data, in response to said reducing; and retrieving the .ltoreq.k records most similar to the specified data from the identified cluster using the one or more reduced dimensionality indexes, the dimensionality reduction information and the reduced dimensionality specified data. 10. The method of claim 9, further comprising the steps of: identifying one or more other candidate clusters which can contain records closer to the specified data than the farthest of the k records retrieved; searching a closest other candidate cluster to the specified data, in response to said identifying step; and repeating said identifying and searching for all said other candidate clusters.
| 0.658722 |
6. An information processing method comprising: storing, to a first memory, a plurality of patterns each expressed in at least one of a character, a character string and a symbol, and for each a semantic class representing a type or meaning of information matching; storing, to a second memory, intention estimation knowledge information for estimating an intention of a user organized by type of annotation and related semantic class of information; displaying a document; receiving, from the user, an annotation of at least one of an underline, a box, a character, a character string, a symbol, and a symbol string in a position on the displayed document that identifies coverage of a certain portion of the displayed document and concurrently displaying said document and said user-inputted annotation concurrently on said displayed document; recognizing a type of the annotation and a coverage of the annotation in the displayed document; providing a semantic class for information matching a pattern in the coverage of the displayed document identified by the user-inputted annotation; estimating an intention of the user based on the intention estimation knowledge information determined by the semantic class and the type of recognized annotation, wherein the intention of the user corresponds to an action the user intends to perform; selecting the action intended by the user based on the estimated intention; executing the action selected by extracting at least one information item from the displayed document and creating an output including the one information item; and displaying a view of the output created by the execution unit.
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6. An information processing method comprising: storing, to a first memory, a plurality of patterns each expressed in at least one of a character, a character string and a symbol, and for each a semantic class representing a type or meaning of information matching; storing, to a second memory, intention estimation knowledge information for estimating an intention of a user organized by type of annotation and related semantic class of information; displaying a document; receiving, from the user, an annotation of at least one of an underline, a box, a character, a character string, a symbol, and a symbol string in a position on the displayed document that identifies coverage of a certain portion of the displayed document and concurrently displaying said document and said user-inputted annotation concurrently on said displayed document; recognizing a type of the annotation and a coverage of the annotation in the displayed document; providing a semantic class for information matching a pattern in the coverage of the displayed document identified by the user-inputted annotation; estimating an intention of the user based on the intention estimation knowledge information determined by the semantic class and the type of recognized annotation, wherein the intention of the user corresponds to an action the user intends to perform; selecting the action intended by the user based on the estimated intention; executing the action selected by extracting at least one information item from the displayed document and creating an output including the one information item; and displaying a view of the output created by the execution unit. 9. The method according to claim 6 , wherein inputting the annotation includes inputting an annotation for creating an address book, estimating the intention includes estimating the intention of the user that creates the address book based on the type of the annotation, and selecting the action includes selecting an action for creating the address book from the storage unit based on the estimated intention, and executing the action includes extracting information items required for creation of the address book from the document and arranging the information items on the address book.
| 0.688947 |
1. A method of creating a physically based crank-resolved simplified computer implementable engine model, the method comprising: obtaining a complete crank-resolved computer implementable engine model, wherein the complete crank-resolved computer implementable engine model is operable to simulate engine operation of the entire engine, including simulating wave-action effects throughout the engine, and produce outputs based on parametric inputs to the engine; selecting, from the complete crank-resolved computer implementable engine model, one or more elements defining start and end points of the physically based crank-resolved simplified computer implementable engine model which is to be created; obtaining from a library of rules, at least one computer implementable model creation rule corresponding to the one or more selected elements; creating, using a computer, the physically based crank-resolved simplified computer implementable engine model using the at least one computer implementable model creation rule, wherein the physically based crank-resolved simplified computer implementable engine model is also operable to simulate engine operation, including simulating wave-action effects throughout the simplified engine model, and produce outputs in real time based on the parametric inputs to the engine; wherein said simplified computer implementable engine model employs an approximation for a mathematical function employed by the complete crank-resolved engine model, comprising: identifying an operation which the complete crank-resolved engine model employs, for which a corresponding mathematical function requires a complex numerical algorithm; obtaining an approximation to the mathematical function which requires a simplified algorithm; and generating a control rule under which, when a simplified engine model implementing the operation is created from the complete crank-resolved engine model, the approximation will be employed instead of the mathematical function, and wherein said generated control rule is stored in a module which is operable to create a simplified engine model from the complete crank-resolved engine model; and simulating engine operation, including simulating wave-action effects throughout the simplified engine model, using the computer and the physically based crank-resolved simplified computer implementable engine model.
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1. A method of creating a physically based crank-resolved simplified computer implementable engine model, the method comprising: obtaining a complete crank-resolved computer implementable engine model, wherein the complete crank-resolved computer implementable engine model is operable to simulate engine operation of the entire engine, including simulating wave-action effects throughout the engine, and produce outputs based on parametric inputs to the engine; selecting, from the complete crank-resolved computer implementable engine model, one or more elements defining start and end points of the physically based crank-resolved simplified computer implementable engine model which is to be created; obtaining from a library of rules, at least one computer implementable model creation rule corresponding to the one or more selected elements; creating, using a computer, the physically based crank-resolved simplified computer implementable engine model using the at least one computer implementable model creation rule, wherein the physically based crank-resolved simplified computer implementable engine model is also operable to simulate engine operation, including simulating wave-action effects throughout the simplified engine model, and produce outputs in real time based on the parametric inputs to the engine; wherein said simplified computer implementable engine model employs an approximation for a mathematical function employed by the complete crank-resolved engine model, comprising: identifying an operation which the complete crank-resolved engine model employs, for which a corresponding mathematical function requires a complex numerical algorithm; obtaining an approximation to the mathematical function which requires a simplified algorithm; and generating a control rule under which, when a simplified engine model implementing the operation is created from the complete crank-resolved engine model, the approximation will be employed instead of the mathematical function, and wherein said generated control rule is stored in a module which is operable to create a simplified engine model from the complete crank-resolved engine model; and simulating engine operation, including simulating wave-action effects throughout the simplified engine model, using the computer and the physically based crank-resolved simplified computer implementable engine model. 2. The method as claimed in claim 1 , wherein the step of using the at least one computer implementable model creation rule to create the physically based crank-resolved simplified computer implementable engine model includes generating a computer code representing the simplified model.
| 0.841932 |
15. A mobile device comprising: a camera; a memory operatively connected to the camera to receive at least an image therefrom; at least one processor operatively connected to the memory to execute a plurality of instructions stored in the memory; wherein the plurality of instructions cause the at least one processor to: rotate at least the plurality of regions through a common angle φ, to obtain a set of skew-corrected regions; after rotation through the common angle φ, apply to the set of skew-corrected regions one or more tests that determine presence of text, to identify a subset of regions likely to be text; after application of the one or more tests, determine a slant angle θ of at least a portion of a region in the subset, by combining a plurality of angles of a plurality of lines relative to a common direction, each line in the plurality of lines representing multiple line segments in the region that are at least one pixel wide, located adjacent to one another, and formed by pixels of text; use the slant angle θ to change first coordinates of at least pixels in the portion, whereby a first height at a first end of the portion and a second height at a second end of the portion remain unchanged after the use; and store in the memory, at least changed first coordinates generated by the use.
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15. A mobile device comprising: a camera; a memory operatively connected to the camera to receive at least an image therefrom; at least one processor operatively connected to the memory to execute a plurality of instructions stored in the memory; wherein the plurality of instructions cause the at least one processor to: rotate at least the plurality of regions through a common angle φ, to obtain a set of skew-corrected regions; after rotation through the common angle φ, apply to the set of skew-corrected regions one or more tests that determine presence of text, to identify a subset of regions likely to be text; after application of the one or more tests, determine a slant angle θ of at least a portion of a region in the subset, by combining a plurality of angles of a plurality of lines relative to a common direction, each line in the plurality of lines representing multiple line segments in the region that are at least one pixel wide, located adjacent to one another, and formed by pixels of text; use the slant angle θ to change first coordinates of at least pixels in the portion, whereby a first height at a first end of the portion and a second height at a second end of the portion remain unchanged after the use; and store in the memory, at least changed first coordinates generated by the use. 18. The mobile device of claim 15 wherein the plurality of instructions further cause the at least one processor to: cluster regions in the subset, when a test of geometry is satisfied; wherein the instructions to cluster are to execute after application of the one or more tests and before determination of the slant angle θ.
| 0.614861 |
21. A system comprising a processor coupled to a memory for indexing one or more items of content, the system comprising: a text extractor operative to extract one or more items of text from an item of content; a concept dictionary operative to maintain concepts; a context dictionary operative to maintain related concepts associated with the concepts maintained in the concept dictionary; and an aboutness extractor operative to: tokenize the one or more extracted items of text into one or more concepts maintained in the concept dictionary based on past queries submitted by one or more users; identify one or more related concepts associated with the one or more concepts in the item of content based on the context dictionary; obtain a support score for the individual one or more concepts based on whether one or more of the one or more concepts appear in the item of content and/or whether one or more of the one or more related concepts appear in the item of content; generate an index, the index comprising the item of content associated with the one or more concepts and corresponding support scores for the individual one or more concepts; receive a search query; identify, based on the index, a set of items of content responsive to the search query, wherein individual items of content in the set are indexed with one or more concepts that are related to the search query; obtain, for each individual item of content in the set, a sum of support scores associated with the one or more concepts that are related to the search query; and provide the set, wherein the items of content in the set are sorted based on the sum of support scores.
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21. A system comprising a processor coupled to a memory for indexing one or more items of content, the system comprising: a text extractor operative to extract one or more items of text from an item of content; a concept dictionary operative to maintain concepts; a context dictionary operative to maintain related concepts associated with the concepts maintained in the concept dictionary; and an aboutness extractor operative to: tokenize the one or more extracted items of text into one or more concepts maintained in the concept dictionary based on past queries submitted by one or more users; identify one or more related concepts associated with the one or more concepts in the item of content based on the context dictionary; obtain a support score for the individual one or more concepts based on whether one or more of the one or more concepts appear in the item of content and/or whether one or more of the one or more related concepts appear in the item of content; generate an index, the index comprising the item of content associated with the one or more concepts and corresponding support scores for the individual one or more concepts; receive a search query; identify, based on the index, a set of items of content responsive to the search query, wherein individual items of content in the set are indexed with one or more concepts that are related to the search query; obtain, for each individual item of content in the set, a sum of support scores associated with the one or more concepts that are related to the search query; and provide the set, wherein the items of content in the set are sorted based on the sum of support scores. 23. The system of claim 21 , wherein an item of content comprises a document.
| 0.58046 |
11. A context inference system, comprising: a mobile device, comprising: a information receiving unit, receiving at least one context information; and a context operation platform, coupled to the information receiving unit and performing a context inference process, the context operation platform comprising: an information collection module, collecting an information used for inferring a context; a data classification and storage module, storing and classifying a user preference information of a user; an inference module, inferring the context; and a service request module, obtaining a service information; at least one information sending unit, transmitting the at least one context information to the mobile device, wherein the at least one information sending unit is mounted on at least one object, and the at least one context information is a related information of the at least one object; and a remote server, providing the service information, the remote server comprising: a service information classification and storage module, classifying and storing a content regarding the service information; and a management data module, managing the service information classification and storage module; wherein the context operation platform performs the context inference process based on the context information, the service information, and a user preference information in order to forecast a need of the user and provide a recommendation information to the user.
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11. A context inference system, comprising: a mobile device, comprising: a information receiving unit, receiving at least one context information; and a context operation platform, coupled to the information receiving unit and performing a context inference process, the context operation platform comprising: an information collection module, collecting an information used for inferring a context; a data classification and storage module, storing and classifying a user preference information of a user; an inference module, inferring the context; and a service request module, obtaining a service information; at least one information sending unit, transmitting the at least one context information to the mobile device, wherein the at least one information sending unit is mounted on at least one object, and the at least one context information is a related information of the at least one object; and a remote server, providing the service information, the remote server comprising: a service information classification and storage module, classifying and storing a content regarding the service information; and a management data module, managing the service information classification and storage module; wherein the context operation platform performs the context inference process based on the context information, the service information, and a user preference information in order to forecast a need of the user and provide a recommendation information to the user. 17. The context inference system according to claim 11 , wherein the related information comprises a plurality of characteristic values regarding the at least one object, a plurality of characteristic values regarding the location of the at least one object, a current time, or a combination of the characteristic values regarding the at least one object, the characteristic values regarding the location of the at least one object, and the current time.
| 0.534943 |
1. A method of searching documents, comprising: indexing a plurality of documents into a document library stored in a database; receiving a query document; comparing, using a processor, the query document with each indexed document to generate a score for each indexed document, the score representing a measure of similarity between the query document and each indexed document; determining a commonality among particular ones of the indexed documents, other than the measure of similarity; displaying, at a user interface, a query result based on the score for each indexed document and based on the commonality; calculating hash values for each indexed document over each of a plurality of alternative windows; storing the hash values for each indexed document over each of the plurality of alternative windows; receiving user input selecting a particular one of the plurality of alternative windows; in response to receiving the selection of the particular one of the plurality of alternative windows, calculating hash values for the query document using the particular one of the plurality of alternative windows; and comparing the hash values for the query document with the hash values corresponding to the particular one of the plurality of alternative windows for each of the indexed documents to determine a measure of similarity between the query document and each indexed document.
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1. A method of searching documents, comprising: indexing a plurality of documents into a document library stored in a database; receiving a query document; comparing, using a processor, the query document with each indexed document to generate a score for each indexed document, the score representing a measure of similarity between the query document and each indexed document; determining a commonality among particular ones of the indexed documents, other than the measure of similarity; displaying, at a user interface, a query result based on the score for each indexed document and based on the commonality; calculating hash values for each indexed document over each of a plurality of alternative windows; storing the hash values for each indexed document over each of the plurality of alternative windows; receiving user input selecting a particular one of the plurality of alternative windows; in response to receiving the selection of the particular one of the plurality of alternative windows, calculating hash values for the query document using the particular one of the plurality of alternative windows; and comparing the hash values for the query document with the hash values corresponding to the particular one of the plurality of alternative windows for each of the indexed documents to determine a measure of similarity between the query document and each indexed document. 2. The method of claim 1 , wherein the plurality of alternative windows comprise words, sentences, paragraphs, and pages.
| 0.636816 |
1. A method performed by at least one computer processor, the method comprising: (A) obtaining, from a user, first data representing a first part of a sentence, wherein the first part of the sentence comprises a first one of a subject, a predicate, and an object; (B) obtaining, from the user, second data representing a second part of the sentence, wherein the second part of the sentence comprises a second one of the subject, the predicate, and the object; (C) identifying a synonym of the first part of the sentence; (D) identifying a synonym of the second part of the sentence; (E) forming a first query from the synonym of the first part of the sentence and the synonym of the second part of the sentence, comprising: (E)(1) selecting a first form for the first query, wherein the first form specifies a first one of the following sequences: subject, predicate, object; subject, predicate; subject, object; predicate, object; (E)(2) forming the first query in the first form the forming comprising: (E)(2)(a) if the first form specifies the sequence subject, predicate, object, then forming the first query to include a subject followed by a predicate followed by an object, wherein the subject, predicate, and object are selected from the first part of the sentence, the second part of the sentence, the synonym of the first part of the sentence, and the synonym of the second part of the sentence; (E)(2)(b) if the first form specifies the sequence subject, predicate, then forming the first query to include a subject followed by a predicate, wherein the subject and predicate are selected from the first part of the sentence, the second part of the sentence, the synonym of the first part of the sentence, and the synonym of the second part of the sentence; (E)(2)(c) if the first form specifies the sequence subject, object, then forming the first query to include a subject followed by an object, wherein the subject and object are selected from the first part of the sentence, the second part of the sentence, the synonym of the first part of the sentence, and the synonym of the second part of the sentence; and (E)(2)(d) if the first form specifies the sequence predicate, object, then forming the first query to include a predicate followed by an object, wherein the predicate and object are selected from the first part of the sentence, the second part of the sentence, the synonym of the first part of the sentence, and the synonym of the second part of the sentence; and (F) searching a dataset in memory using the first query to identify a first subset of the dataset; (G) providing, to the user, executed by the computer processor, output representing the subset of the dataset wherein the sentence differs from the first query.
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1. A method performed by at least one computer processor, the method comprising: (A) obtaining, from a user, first data representing a first part of a sentence, wherein the first part of the sentence comprises a first one of a subject, a predicate, and an object; (B) obtaining, from the user, second data representing a second part of the sentence, wherein the second part of the sentence comprises a second one of the subject, the predicate, and the object; (C) identifying a synonym of the first part of the sentence; (D) identifying a synonym of the second part of the sentence; (E) forming a first query from the synonym of the first part of the sentence and the synonym of the second part of the sentence, comprising: (E)(1) selecting a first form for the first query, wherein the first form specifies a first one of the following sequences: subject, predicate, object; subject, predicate; subject, object; predicate, object; (E)(2) forming the first query in the first form the forming comprising: (E)(2)(a) if the first form specifies the sequence subject, predicate, object, then forming the first query to include a subject followed by a predicate followed by an object, wherein the subject, predicate, and object are selected from the first part of the sentence, the second part of the sentence, the synonym of the first part of the sentence, and the synonym of the second part of the sentence; (E)(2)(b) if the first form specifies the sequence subject, predicate, then forming the first query to include a subject followed by a predicate, wherein the subject and predicate are selected from the first part of the sentence, the second part of the sentence, the synonym of the first part of the sentence, and the synonym of the second part of the sentence; (E)(2)(c) if the first form specifies the sequence subject, object, then forming the first query to include a subject followed by an object, wherein the subject and object are selected from the first part of the sentence, the second part of the sentence, the synonym of the first part of the sentence, and the synonym of the second part of the sentence; and (E)(2)(d) if the first form specifies the sequence predicate, object, then forming the first query to include a predicate followed by an object, wherein the predicate and object are selected from the first part of the sentence, the second part of the sentence, the synonym of the first part of the sentence, and the synonym of the second part of the sentence; and (F) searching a dataset in memory using the first query to identify a first subset of the dataset; (G) providing, to the user, executed by the computer processor, output representing the subset of the dataset wherein the sentence differs from the first query. 6. The method of claim 1 , wherein (C) comprises identifying a hyponym of the second part of the sentence.
| 0.599971 |
1. A method comprising: storing reliability data that indicates, for each source of a plurality of sources, a reliability rating of said each source; wherein a first source of the plurality of sources has a first reliability rating that indicates a reliability of the first source, and a second source of the plurality of sources has a second reliability rating that indicates a reliability of the second source and that is different than the first reliability rating; wherein at least one of the first reliability rating or the second reliability rating is based on previous fact checking results; receiving information to be fact checked; selecting at least one of the first source or the second source from among the plurality of sources based on the first reliability rating or the second reliability rating, wherein a difference between the first reliability rating and the second reliability rating indicates that one source is more reliable than the other source; in response to receiving the information to be fact checked, performing a comparison of the information to be fact checked with source information from one or more sources to determine factual accuracy of the information and to generate a fact checking result representative of a factual accuracy of the information, the one or more sources comprising the at least one of the first source or the second source; causing an icon indicative of the fact checking result to be displayed; wherein the method is performed by one or more computing devices.
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1. A method comprising: storing reliability data that indicates, for each source of a plurality of sources, a reliability rating of said each source; wherein a first source of the plurality of sources has a first reliability rating that indicates a reliability of the first source, and a second source of the plurality of sources has a second reliability rating that indicates a reliability of the second source and that is different than the first reliability rating; wherein at least one of the first reliability rating or the second reliability rating is based on previous fact checking results; receiving information to be fact checked; selecting at least one of the first source or the second source from among the plurality of sources based on the first reliability rating or the second reliability rating, wherein a difference between the first reliability rating and the second reliability rating indicates that one source is more reliable than the other source; in response to receiving the information to be fact checked, performing a comparison of the information to be fact checked with source information from one or more sources to determine factual accuracy of the information and to generate a fact checking result representative of a factual accuracy of the information, the one or more sources comprising the at least one of the first source or the second source; causing an icon indicative of the fact checking result to be displayed; wherein the method is performed by one or more computing devices. 8. The method of claim 1 further comprising causing to be displayed a video, wherein the information is from the video.
| 0.539346 |
15. A database system capable of analyzing a plurality of database queries within a database environment, the database system comprising: one or more databases; an intelligent query analysis agent coupled to receive a first statistical evaluation of a first query plan for a first database query corresponding to a first database having a first database schema and a second statistical evaluation for a second query plan for a second database query corresponding to a second database having a second database schema, to compare the first statistical evaluation and the second statistical evaluation to determine whether the first query plan matches the second query plan, to cause to be stored in the one or more databases an indication that the first query matches the second query if the first statistical evaluation matches the second statistical evaluation, to determine a function that provides the first query plan, to determine if the second query plan is provided by the function that provides the first query plan, to evaluate data objects referenced by the first query plan and the second query plan if the function provides both the first query plan and the second query plan to determine if the first query plan and the second query plan are syntactically different versions of equivalent database queries, and to cause to be stored in the database statistics if the first query plan and the second query plan are syntactically different versions of equivalent database queries.
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15. A database system capable of analyzing a plurality of database queries within a database environment, the database system comprising: one or more databases; an intelligent query analysis agent coupled to receive a first statistical evaluation of a first query plan for a first database query corresponding to a first database having a first database schema and a second statistical evaluation for a second query plan for a second database query corresponding to a second database having a second database schema, to compare the first statistical evaluation and the second statistical evaluation to determine whether the first query plan matches the second query plan, to cause to be stored in the one or more databases an indication that the first query matches the second query if the first statistical evaluation matches the second statistical evaluation, to determine a function that provides the first query plan, to determine if the second query plan is provided by the function that provides the first query plan, to evaluate data objects referenced by the first query plan and the second query plan if the function provides both the first query plan and the second query plan to determine if the first query plan and the second query plan are syntactically different versions of equivalent database queries, and to cause to be stored in the database statistics if the first query plan and the second query plan are syntactically different versions of equivalent database queries. 20. The system of claim 15 wherein the first query plan is directed to a first database having a first schema and the second query plan is directed to a second database having a second schema.
| 0.913762 |
5. A method comprising: receiving a plurality of glyphs; identifying a first character corresponding to a first glyph of the plurality of glyphs, and a second character corresponding to a second glyph of the plurality of glyphs; identifying a first font for the first glyph of the plurality of glyphs, wherein identifying the first font comprises: identifying a candidate font for the first glyph; determining that the candidate font is a most commonly used font for a related set of two or more of the plurality of glyphs; determining that the candidate font that is the most commonly used font is a dominant font for the related set of two or more of the plurality of glyphs; and identifying a final font for glyphs in the related set based at least in part on the dominant font; identifying a second font for the second glyph of the plurality of glyphs, wherein the second font is different than the first font, and wherein the first font and the second font are identified based on two or more of the plurality of glyphs; and generating a reflowable content file indicating the first character for the first glyph of the plurality of glyphs, the second character for the second glyph of the plurality of glyphs, the first font for the first glyph of the plurality of glyphs, and the second font for the second glyph of the plurality of glyphs.
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5. A method comprising: receiving a plurality of glyphs; identifying a first character corresponding to a first glyph of the plurality of glyphs, and a second character corresponding to a second glyph of the plurality of glyphs; identifying a first font for the first glyph of the plurality of glyphs, wherein identifying the first font comprises: identifying a candidate font for the first glyph; determining that the candidate font is a most commonly used font for a related set of two or more of the plurality of glyphs; determining that the candidate font that is the most commonly used font is a dominant font for the related set of two or more of the plurality of glyphs; and identifying a final font for glyphs in the related set based at least in part on the dominant font; identifying a second font for the second glyph of the plurality of glyphs, wherein the second font is different than the first font, and wherein the first font and the second font are identified based on two or more of the plurality of glyphs; and generating a reflowable content file indicating the first character for the first glyph of the plurality of glyphs, the second character for the second glyph of the plurality of glyphs, the first font for the first glyph of the plurality of glyphs, and the second font for the second glyph of the plurality of glyphs. 13. The method of claim 5 , wherein each set of the related set of two or more of the plurality of glyphs comprises at least one of a word, line, or a paragraph.
| 0.718695 |
13. An apparatus for sequence analysis comprising: memory configured to store relations in a relational database; and a processor configured to carry out a comparison of at least one query sequence and at least one subject sequence, each stored as relations in the relational database, as one or more Structured Query Language (SQL) queries formulated to include at least one join operation, wherein at least one SQL query is formulated with a controls table that specifies parameters of the comparison, and store a result of the comparison as a result relation in the relational database, wherein a number of tuples in the result relation is larger than a multiplicative product of a number of tuples in the at least one subject sequence times a number of tuples in the at least one query sequence, to accommodate multiple points of alignment between each combination of the at least one query sequence and the at least one subject sequence that are compared.
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13. An apparatus for sequence analysis comprising: memory configured to store relations in a relational database; and a processor configured to carry out a comparison of at least one query sequence and at least one subject sequence, each stored as relations in the relational database, as one or more Structured Query Language (SQL) queries formulated to include at least one join operation, wherein at least one SQL query is formulated with a controls table that specifies parameters of the comparison, and store a result of the comparison as a result relation in the relational database, wherein a number of tuples in the result relation is larger than a multiplicative product of a number of tuples in the at least one subject sequence times a number of tuples in the at least one query sequence, to accommodate multiple points of alignment between each combination of the at least one query sequence and the at least one subject sequence that are compared. 16. An apparatus as in claim 13 wherein the comparison is carried out as a relational join of subject sequences against one or more query sequences.
| 0.562117 |
1. A method comprising: identifying a first object, the first object including code that contains a first code portion; identifying a second object, the second object including a graphical model containing a first graphical element; identifying a first mapping between the first graphical element and the first code portion; identifying a second graphical element, included in the graphical model, that corresponds to the first graphical element; identifying a second mapping between the second graphical element and a second code portion included in the code; receiving information associated with an edit to the first code portion; and regenerating: the first graphical element based on the first mapping and the information associated with the edit to the first code portion, the second graphical element based on regenerating the first graphical element, and the second code portion based on the second mapping and regenerating the second graphical element, the identifying of the first object, the identifying of the second object, the identifying of the first mapping, the identifying of the second graphical element, the identifying of the second mapping, the receiving, and the regenerating being performed by a processor.
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1. A method comprising: identifying a first object, the first object including code that contains a first code portion; identifying a second object, the second object including a graphical model containing a first graphical element; identifying a first mapping between the first graphical element and the first code portion; identifying a second graphical element, included in the graphical model, that corresponds to the first graphical element; identifying a second mapping between the second graphical element and a second code portion included in the code; receiving information associated with an edit to the first code portion; and regenerating: the first graphical element based on the first mapping and the information associated with the edit to the first code portion, the second graphical element based on regenerating the first graphical element, and the second code portion based on the second mapping and regenerating the second graphical element, the identifying of the first object, the identifying of the second object, the identifying of the first mapping, the identifying of the second graphical element, the identifying of the second mapping, the receiving, and the regenerating being performed by a processor. 4. The method of claim 1 , where regenerating the first graphical element includes: receiving, from a user, information related to modifying the first mapping; and regenerating the first graphical element further based on the information related to modifying the first mapping.
| 0.707627 |
17. A computer-implemented search system for locating and rating a plurality of electronic mentions of respective ones of a plurality of endorsers, comprising: a server computer having a tangible computer processor, the processor in data communication with a non-transitory computer memory that stores instructions which, when executed on the processor, cause the computer to implement: a web crawl engine that finds mentions of ones of the plurality of endorsers in proximity to respective ones of a plurality of keywords; a content reviewer that electronically presents to live reviewer the found mentions, wherein the live reviewer assigns a respective rating to respective ones of the found mentions; a scoring input for receiving a first rating of a particular one of the found mentions from the live reviewer; at least one electronic rating input for receiving second ratings of the same particular one of the found mentions; a correlator that normalizes the ratings of the particular one of the found mentions at least in part by comparing the first rating to the second ratings, and that correlates ones of the plurality of endorsers to a desired purchaser profile based at least in part on the normalized rating; and a management engine that manages the first and second ones of the ratings, wherein said management engine provides for modifications of at least one of the first rating and the second ratings.
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17. A computer-implemented search system for locating and rating a plurality of electronic mentions of respective ones of a plurality of endorsers, comprising: a server computer having a tangible computer processor, the processor in data communication with a non-transitory computer memory that stores instructions which, when executed on the processor, cause the computer to implement: a web crawl engine that finds mentions of ones of the plurality of endorsers in proximity to respective ones of a plurality of keywords; a content reviewer that electronically presents to live reviewer the found mentions, wherein the live reviewer assigns a respective rating to respective ones of the found mentions; a scoring input for receiving a first rating of a particular one of the found mentions from the live reviewer; at least one electronic rating input for receiving second ratings of the same particular one of the found mentions; a correlator that normalizes the ratings of the particular one of the found mentions at least in part by comparing the first rating to the second ratings, and that correlates ones of the plurality of endorsers to a desired purchaser profile based at least in part on the normalized rating; and a management engine that manages the first and second ones of the ratings, wherein said management engine provides for modifications of at least one of the first rating and the second ratings. 27. The search system of claim 17 , wherein the normalization comprises a prioritization of the keywords.
| 0.529192 |
14. A system to calculate time weight in an RDF graph, comprising: an inference engine module; a first communication interface to the inference engine module, the first communication interface configured to provide one or more triples of the RDF graph to the inference engine module, the one or more triples comprising a time information; a first communication interface to the inference engine module, the first communication interface configured to provide an epoch time to the inference engine, wherein the inference engine module is configured: to calculate an elapsed time from the epoch time to the time value; and to inversely weight the time information by the elapsed time, to provide a calculated time weight.
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14. A system to calculate time weight in an RDF graph, comprising: an inference engine module; a first communication interface to the inference engine module, the first communication interface configured to provide one or more triples of the RDF graph to the inference engine module, the one or more triples comprising a time information; a first communication interface to the inference engine module, the first communication interface configured to provide an epoch time to the inference engine, wherein the inference engine module is configured: to calculate an elapsed time from the epoch time to the time value; and to inversely weight the time information by the elapsed time, to provide a calculated time weight. 20. The system of claim 14 , wherein the time information of the one or more triples of the RDF graph comprises a RDF reification statement of the RDF graph.
| 0.725854 |
1. A communication system comprising: machine memory or circuits comprising logic to expand a text message into a web page and to provide a link to the web page to a recipient device, the web page comprising image content representing a subject or verb of the text message; machine memory or circuits comprising logic to form a query for the image content from key words in the text message combined with key words for an emote in the text message; and a collage generator forming a collage of the image content and content expressing a mood of the emote.
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1. A communication system comprising: machine memory or circuits comprising logic to expand a text message into a web page and to provide a link to the web page to a recipient device, the web page comprising image content representing a subject or verb of the text message; machine memory or circuits comprising logic to form a query for the image content from key words in the text message combined with key words for an emote in the text message; and a collage generator forming a collage of the image content and content expressing a mood of the emote. 2. The communication system of claim 1 , further comprising machine memory or circuits comprising logic to select the image content based on available copy rights.
| 0.596591 |
3. The method of claim 1 , further comprising failing to find a language object corresponding with the at least one of the prefix objects and, responsive thereto, initiating said identifying an spelling substitution.
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3. The method of claim 1 , further comprising failing to find a language object corresponding with the at least one of the prefix objects and, responsive thereto, initiating said identifying an spelling substitution. 4. The method of claim 3 , further comprising: obtaining an associated frequency object associated with the identified language object and having a frequency value; and associating the frequency value of the associated frequency object with the at least one of the prefix objects.
| 0.909003 |
1. A method for managing the interaction of participants in a social network utilizing computers having nodes, and storage comprising the steps of: in a social network having linked computers, gathering information for at least two participants on the social network via at least one of the computers, and assigning each participant to a computer node; identifying an original state for each computer node via at least another of the computers; identifying similarly-situated participants by identifying similarly-situated computer nodes in the social network via the at least another of the computers; managing interaction of the similarly-situated participants by managing the computer node assigned to each of the similarly-situated participants via at least one of the networks; for each of the computer nodes having a new state at some point in time that is a change in state from the original state, identifying the new state for each of the computer nodes having the new state via at least another of the computers wherein the new state is different than the original state and indicates a state change; identifying the change to the computer node's new state from the original state of each computer node that was assigned to each of the similarly-situated participants via the at least another of the computers after the state change; and storing on the storage, information about the identified state change.
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1. A method for managing the interaction of participants in a social network utilizing computers having nodes, and storage comprising the steps of: in a social network having linked computers, gathering information for at least two participants on the social network via at least one of the computers, and assigning each participant to a computer node; identifying an original state for each computer node via at least another of the computers; identifying similarly-situated participants by identifying similarly-situated computer nodes in the social network via the at least another of the computers; managing interaction of the similarly-situated participants by managing the computer node assigned to each of the similarly-situated participants via at least one of the networks; for each of the computer nodes having a new state at some point in time that is a change in state from the original state, identifying the new state for each of the computer nodes having the new state via at least another of the computers wherein the new state is different than the original state and indicates a state change; identifying the change to the computer node's new state from the original state of each computer node that was assigned to each of the similarly-situated participants via the at least another of the computers after the state change; and storing on the storage, information about the identified state change. 18. The method of claim 1 comprising the further step of storing on the storage, information about the similarly-situated participants after the state change.
| 0.542553 |
13. A system, comprising: a processor; and a non-transitory computer-readable medium communicatively coupled to the processor, the processor being configured to execute programming code stored in the non-transitory computer-readable medium and thereby cause the processor to perform operations comprising: receiving, as input to a neural network, a query object and a visual medium including the query object, generating, from a first subset of layers in the neural network, representations of the query object and the visual medium defining features of the query object and the visual medium, generating a plurality of heat maps by applying a second subset of layers in the neural network to the representations, wherein the plurality of heat maps include (i) a first heat map generated from a first combination of a first query object representation and a first visual medium representation and (ii) a second heat map generated from a second combination of a second query object representation and a second visual medium representation, pooling the first heat map and the second heat map to create a set of concatenated layers, generating an output heat map from the set of concatenated layers, wherein the output heat map identifies a location of pixels corresponding to the query object within the visual medium, and generating an updated visual medium using the output heat map to highlight the query object within the visual medium.
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13. A system, comprising: a processor; and a non-transitory computer-readable medium communicatively coupled to the processor, the processor being configured to execute programming code stored in the non-transitory computer-readable medium and thereby cause the processor to perform operations comprising: receiving, as input to a neural network, a query object and a visual medium including the query object, generating, from a first subset of layers in the neural network, representations of the query object and the visual medium defining features of the query object and the visual medium, generating a plurality of heat maps by applying a second subset of layers in the neural network to the representations, wherein the plurality of heat maps include (i) a first heat map generated from a first combination of a first query object representation and a first visual medium representation and (ii) a second heat map generated from a second combination of a second query object representation and a second visual medium representation, pooling the first heat map and the second heat map to create a set of concatenated layers, generating an output heat map from the set of concatenated layers, wherein the output heat map identifies a location of pixels corresponding to the query object within the visual medium, and generating an updated visual medium using the output heat map to highlight the query object within the visual medium. 16. The system of claim 13 , wherein the representations include a first representation of the query object and a second representation of the visual medium, wherein generating the plurality of heat maps using the representations includes convolving the first representation with overlapping regions of the second representation.
| 0.517125 |
1. A method comprising: extracting, via a processor and independent of user input, first task data from a web-site, wherein the first task data is based on a structure of a web page in the web-site; formatting the first task data into first formatted task data comprising a first topic section, a first hyperlink section, and a first content/answer section; extracting, independent of the user input, second task data from the web-site, wherein the second task data is based on the structure of the web page in the web-site; formatting the second task data into second formatted task data comprising a second topic section, a second hyperlink section, and a second content/answer section; analyzing the first formatted task data and the second formatted task data, to yield an analysis; when, based on the analysis, the first topic section is determined to be thematically coherent with the second topic section, merging the first formatted task data and the second formatted task data into third formatted task data; receiving a spoken natural language user query; organizing task data into a ranked hierarchical structure based on the spoken natural language user query, wherein the task data comprises one of (1) the first formatted task data and the second formatted task data, and (2) the third formatted task data; generating a ranked list of relevant responses to the spoken natural language user query using the ranked hierarchical structure to perform vector space modeling; and initiating a two-way, natural language spoken dialog to provide a response to the spoken natural language user query according to the ranked list.
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1. A method comprising: extracting, via a processor and independent of user input, first task data from a web-site, wherein the first task data is based on a structure of a web page in the web-site; formatting the first task data into first formatted task data comprising a first topic section, a first hyperlink section, and a first content/answer section; extracting, independent of the user input, second task data from the web-site, wherein the second task data is based on the structure of the web page in the web-site; formatting the second task data into second formatted task data comprising a second topic section, a second hyperlink section, and a second content/answer section; analyzing the first formatted task data and the second formatted task data, to yield an analysis; when, based on the analysis, the first topic section is determined to be thematically coherent with the second topic section, merging the first formatted task data and the second formatted task data into third formatted task data; receiving a spoken natural language user query; organizing task data into a ranked hierarchical structure based on the spoken natural language user query, wherein the task data comprises one of (1) the first formatted task data and the second formatted task data, and (2) the third formatted task data; generating a ranked list of relevant responses to the spoken natural language user query using the ranked hierarchical structure to perform vector space modeling; and initiating a two-way, natural language spoken dialog to provide a response to the spoken natural language user query according to the ranked list. 11. The method of claim 1 , wherein extracting the first task data and the second task data further comprises extracting data relationship information.
| 0.563488 |
13. A method comprising: using a hardware-implemented associator to associate a first numerical value with a first keyword that is a part of a search query, the first numerical value representing a percentage of times the first keyword is referenced in a plurality of search queries; using a hardware-implemented tracker to track user activity associated with the first keyword; using a second hardware-implemented associator to associate a second numerical value with the first keyword based upon the user activity, the second numerical value representing a percentage of times user activity is associated with the first keyword relative to a plurality of user activities; using a hardware-implemented calculator to find a difference value between the first and second numerical values, and to associate this difference value with the first keyword; using a hardware-implemented sorter to sort keywords based upon the difference values; and using a hardware-implemented outputer to output results of the sorting.
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13. A method comprising: using a hardware-implemented associator to associate a first numerical value with a first keyword that is a part of a search query, the first numerical value representing a percentage of times the first keyword is referenced in a plurality of search queries; using a hardware-implemented tracker to track user activity associated with the first keyword; using a second hardware-implemented associator to associate a second numerical value with the first keyword based upon the user activity, the second numerical value representing a percentage of times user activity is associated with the first keyword relative to a plurality of user activities; using a hardware-implemented calculator to find a difference value between the first and second numerical values, and to associate this difference value with the first keyword; using a hardware-implemented sorter to sort keywords based upon the difference values; and using a hardware-implemented outputer to output results of the sorting. 15. The method of claim 13 , further comprising: using a hardware-implemented extractor to extract keywords from the search query; using a hardware-implemented adder to add the extracted keywords to existing keywords; using a hardware-implemented re-calculator to re-calculate a percentage value relating to each keyword, the percentage value representing a percentage of search queries that each of the existing keywords has been used in a plurality of searches; and using a hardware-implemented storage to store the re-calculated percentage values into a keyword database.
| 0.6162 |
8. A system comprising: a non-transitory computer readable medium having instructions stored thereon; and data processing apparatus programmed to execute the instructions to perform operations comprising: applying training documents to links in a current generative model that each connect a respective terminal node that represents a corresponding word to a respective cluster node that represents a corresponding cluster of conceptually related words, to determine a respective expected count for each of the links; selecting, from the links that each connect a respective terminal node that represents a corresponding word to a respective cluster node that represents a corresponding cluster of conceptually related words, a first subset of one or more links that are each associated with more than a predetermined number of sources of the training documents; for each selected link of the first subset, determining (i) a significance of the link, and (ii) a link rating for the link based on the expected count for the link and the significance; ranking the selected links of the first subset based on the link ratings; selecting a second subset of the ranked links; and generating a new generative model using only the selected links of the second subset, without using any of the links in the current generative model that were not selected for the second subset.
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8. A system comprising: a non-transitory computer readable medium having instructions stored thereon; and data processing apparatus programmed to execute the instructions to perform operations comprising: applying training documents to links in a current generative model that each connect a respective terminal node that represents a corresponding word to a respective cluster node that represents a corresponding cluster of conceptually related words, to determine a respective expected count for each of the links; selecting, from the links that each connect a respective terminal node that represents a corresponding word to a respective cluster node that represents a corresponding cluster of conceptually related words, a first subset of one or more links that are each associated with more than a predetermined number of sources of the training documents; for each selected link of the first subset, determining (i) a significance of the link, and (ii) a link rating for the link based on the expected count for the link and the significance; ranking the selected links of the first subset based on the link ratings; selecting a second subset of the ranked links; and generating a new generative model using only the selected links of the second subset, without using any of the links in the current generative model that were not selected for the second subset. 9. The system of claim 8 , wherein applying a training document to links in a current generative model that each connect a respective terminal node that represents a corresponding word to a respective cluster node that represents a corresponding cluster of conceptually related words, to determine a respective expected count for each of the links comprises: activating each of one or more respective terminal nodes; determining a model structure based on the one or more activated respective terminal nodes; and determining, based on the one or more activated respective terminal nodes, expected counts for the links.
| 0.524681 |
1. A computer-readable storage media having computer executable instructions, the instructions, when executed, performing a method comprising: receiving a parsable stream that includes an identifier associated with a command; retrieving definitional information based on the identifier that describes an expected parameter for the command; creating an object based on the definitional information; storing a parameter obtained from the parsable stream in the object in accordance with the definitional information associated with the expected parameter; applying a plurality of directives to the parsable stream, the plurality of directives comprising: a processing directive configured to manipulate the parameter before providing the object with the parameter to the command and includes specific size limits for strings and for collections that can be processed; a documentation directive that, when requested, generates textual information about the parameter and provides a description of correct syntax when an invalid syntax is encountered; an interaction directive that determines a user interface for input of the expected parameter, wherein the interaction directive is applied if the expected parameter is not received in the parsable stream; and providing the object to the command, the object having a method invocable by the command, wherein: the definitional information and the plurality of directives are either derived from a reflection-based shell or extended by a developer of the command; the reflection-based shell provides one or more categories of directives and one or more directives under each category of directives; and the definition information and the plurality of directives associated with a first command are different from the definition information and the plurality of directives associated with a second command.
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1. A computer-readable storage media having computer executable instructions, the instructions, when executed, performing a method comprising: receiving a parsable stream that includes an identifier associated with a command; retrieving definitional information based on the identifier that describes an expected parameter for the command; creating an object based on the definitional information; storing a parameter obtained from the parsable stream in the object in accordance with the definitional information associated with the expected parameter; applying a plurality of directives to the parsable stream, the plurality of directives comprising: a processing directive configured to manipulate the parameter before providing the object with the parameter to the command and includes specific size limits for strings and for collections that can be processed; a documentation directive that, when requested, generates textual information about the parameter and provides a description of correct syntax when an invalid syntax is encountered; an interaction directive that determines a user interface for input of the expected parameter, wherein the interaction directive is applied if the expected parameter is not received in the parsable stream; and providing the object to the command, the object having a method invocable by the command, wherein: the definitional information and the plurality of directives are either derived from a reflection-based shell or extended by a developer of the command; the reflection-based shell provides one or more categories of directives and one or more directives under each category of directives; and the definition information and the plurality of directives associated with a first command are different from the definition information and the plurality of directives associated with a second command. 8. A computer-readable storage media of claim 1 , the method further comprising: applying a data validation directive to determine whether the parsable stream meets a criterion specified by the data validation directive associated with the definitional information; and in response to applying the data validation directive, generating an validation error message, wherein the validation error message includes information from the documentation directive.
| 0.547757 |
17. A computer program product comprising a computer usable medium having a computer readable program code embedded therein for controlling a data processing apparatus, the computer readable program code configured to cause the data processing apparatus to execute a process for authenticating a printed document, the printed document including a hierarchical barcode stamp and a document image printed on a front side of a recording medium and first barcode stamps printed on a front or back side of the same recording medium, the process comprising: (a) receiving a front side image and a back side image from the printed document; (b) extracting the document image and the hierarchical barcode stamp from the front side image; (c) processing the document image extracted in step (b) to obtain first processed data; (d) extracting a first code from the hierarchical barcode stamp extracted in step (b); (e) reading and decoding the first barcode stamps in the front side image and/or the back side image to obtain second processed data encoded therein; (f) calculating a second code from the second processed data; (g) comparing the first code and the second code to determine whether the first barcode stamps have been altered; and (h) comparing first processed data and second processed data to determine whether the printed document has been altered.
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17. A computer program product comprising a computer usable medium having a computer readable program code embedded therein for controlling a data processing apparatus, the computer readable program code configured to cause the data processing apparatus to execute a process for authenticating a printed document, the printed document including a hierarchical barcode stamp and a document image printed on a front side of a recording medium and first barcode stamps printed on a front or back side of the same recording medium, the process comprising: (a) receiving a front side image and a back side image from the printed document; (b) extracting the document image and the hierarchical barcode stamp from the front side image; (c) processing the document image extracted in step (b) to obtain first processed data; (d) extracting a first code from the hierarchical barcode stamp extracted in step (b); (e) reading and decoding the first barcode stamps in the front side image and/or the back side image to obtain second processed data encoded therein; (f) calculating a second code from the second processed data; (g) comparing the first code and the second code to determine whether the first barcode stamps have been altered; and (h) comparing first processed data and second processed data to determine whether the printed document has been altered. 21. The computer program product of claim 17 , further comprising: (i) extracting first metadata from the hierarchical barcode stamp extracted in step (b); (j) obtaining second metadata encoded in the first barcode stamps; and (k) comparing the first metadata and the second metadata to determine whether the printed document has been altered.
| 0.503274 |
18. The apparatus of claim 17 , wherein the incorrect input type comprises any one of an incorrect input due to a continuous key press, an incorrect input due to an adjacent key press, an incorrect input due to a key omission, and an incorrect input due to key input order.
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18. The apparatus of claim 17 , wherein the incorrect input type comprises any one of an incorrect input due to a continuous key press, an incorrect input due to an adjacent key press, an incorrect input due to a key omission, and an incorrect input due to key input order. 19. The apparatus of claim 18 , wherein, the controller is configured to: if the operating conditions of the at least one or more incorrect input types having the high frequency of occurrence are met, determine the cost of the insert operation, the delete operation or the replace operation as the first value and otherwise, determine the cost of the insert operation, the delete operation or the replace operation as the second value higher than the first value, if the operation condition of the incorrect input following the continuous key pressing is met, the controller is configured to apply the cost of the insert operation as ‘1’ and otherwise, apply the cost of the insert operation as ‘3’, if the operation condition of the incorrect input following the key omission is met, the controller applies the cost of the delete operation as ‘1’ and otherwise, applies ‘3’, if the operation condition of the incorrect input following the key input order is met, the controller is configured to apply the cost of the replace operation as ‘1’ and otherwise, apply the cost of the replace operation as ‘3’, or if the operation condition of the incorrect input following the adjacent key pressing is met and the possibility of incorrect input is high, the controller applies ‘1’ and, if the possibility of incorrect input is low, applies the cost as ‘2’ and otherwise, apply the cost as ‘3’.
| 0.588378 |
1. A computer-implemented method performed by a computing device comprising a data store including computer-executable instructions of a computerized tax return preparation application and a processor executing the computer-executable instructions of the computerized tax return preparation application, the computer-implemented method comprising: the computing device, by executing a rule-based logic agent, reading first runtime data of an electronic tax return from a shared data store, selecting candidate topics or questions from a data structure comprising a plurality of rows defining respective rules and a plurality of columns defining respective questions, generating a plurality of non-binding suggestions of candidate topics or questions to be presented to the user based at least in part upon the first runtime data and the data structure, and generating prioritization data associated with the plurality of non-binding suggestions; the computing device, by executing a user interface controller in communication with the rule-based logic agent, receiving the plurality of non-binding suggestions from the rule-based logic agent; the computing device, by executing a pagination engine associated with the user interface controller, receiving prioritization data generated by the rule-based logic agent and associated with the plurality of non-binding suggestions, and generating an output based at least in part upon the prioritization data; the computing device, by executing the user interface controller, generating an interview screen that is presented to the user through a display of the computing device, the interview screen comprising a first paginated screen including topics or questions of at least one selected non-binding suggestion generated by the rule-based logic agent and structured based at least in part upon the pagination engine outputs; the computing device, by executing the user interface controller, receiving user input through the first paginated screen, the user input corresponding to selection of a topic or question of the first paginated screen, and writing the response to the shared data store shared with the rule-based logic agent to update the first runtime data and generate second runtime data; and the computing device, by executing a calculation engine, reading the second runtime data from the shared data store, determining a calculation result based on performing a calculation using the second runtime data, and writing the calculation result to the shared data store to update the second runtime data and generate third runtime data.
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1. A computer-implemented method performed by a computing device comprising a data store including computer-executable instructions of a computerized tax return preparation application and a processor executing the computer-executable instructions of the computerized tax return preparation application, the computer-implemented method comprising: the computing device, by executing a rule-based logic agent, reading first runtime data of an electronic tax return from a shared data store, selecting candidate topics or questions from a data structure comprising a plurality of rows defining respective rules and a plurality of columns defining respective questions, generating a plurality of non-binding suggestions of candidate topics or questions to be presented to the user based at least in part upon the first runtime data and the data structure, and generating prioritization data associated with the plurality of non-binding suggestions; the computing device, by executing a user interface controller in communication with the rule-based logic agent, receiving the plurality of non-binding suggestions from the rule-based logic agent; the computing device, by executing a pagination engine associated with the user interface controller, receiving prioritization data generated by the rule-based logic agent and associated with the plurality of non-binding suggestions, and generating an output based at least in part upon the prioritization data; the computing device, by executing the user interface controller, generating an interview screen that is presented to the user through a display of the computing device, the interview screen comprising a first paginated screen including topics or questions of at least one selected non-binding suggestion generated by the rule-based logic agent and structured based at least in part upon the pagination engine outputs; the computing device, by executing the user interface controller, receiving user input through the first paginated screen, the user input corresponding to selection of a topic or question of the first paginated screen, and writing the response to the shared data store shared with the rule-based logic agent to update the first runtime data and generate second runtime data; and the computing device, by executing a calculation engine, reading the second runtime data from the shared data store, determining a calculation result based on performing a calculation using the second runtime data, and writing the calculation result to the shared data store to update the second runtime data and generate third runtime data. 26. The method of claim 1 , the prioritization data comprising multiple variables representative of relative relevance of a question or topic based at least in part upon the fourth runtime data read by the rule-based logic agent.
| 0.676135 |
13. Computer software, provided in a non-transitory computer-readable medium, that handles event data received by a mobile device, the software comprising: executable code that obtains the event data from a plurality of applications; executable code that generates a filtered set of event data by filtering out, from the event data, at least a subset of the event data based on pre-determined filtering rules that are independent of any pre-determined grouping rules; executable code for determining whether grouping candidate event data exists in the filtered set of event data; executable code that, in accordance with a determination that grouping candidate event data exists in the filtered set of event data, applies the pre-determined grouping rules to the filtered set of event data to generate one or more groups within the filtered set of event data; and executable code that, in accordance with a determination that grouping candidate event data does not exist in the filtered set of event data, forgoes applying the pre-determined grouping rules to the filtered set of event data; executable code that applies pre-determined auto-filing rules to the filtered set of event data, wherein the pre-determined auto-filing rules: automatically store a first portion of the filtered set of event data; and generate a remainder set of event data from a second portion of the filtered set of event data, different from the first portion of the filtered set of event data, wherein the second portion of the filtered set of event data is not automatically stored, wherein the pre-determined auto-filing rules are separate from the pre-determined grouping rules, and wherein the pre-determined auto-filing rules are not applied until after the pre-determined grouping rules are applied; and, executable code for displaying, on a display of the mobile device, a user interface that displays content that corresponds to one or more events of the remainder set of the event data, wherein the content that corresponds to the one or more events of the remainder set of the event data includes grouped content that corresponds to at least one of the one or more groups within the filtered set of data.
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13. Computer software, provided in a non-transitory computer-readable medium, that handles event data received by a mobile device, the software comprising: executable code that obtains the event data from a plurality of applications; executable code that generates a filtered set of event data by filtering out, from the event data, at least a subset of the event data based on pre-determined filtering rules that are independent of any pre-determined grouping rules; executable code for determining whether grouping candidate event data exists in the filtered set of event data; executable code that, in accordance with a determination that grouping candidate event data exists in the filtered set of event data, applies the pre-determined grouping rules to the filtered set of event data to generate one or more groups within the filtered set of event data; and executable code that, in accordance with a determination that grouping candidate event data does not exist in the filtered set of event data, forgoes applying the pre-determined grouping rules to the filtered set of event data; executable code that applies pre-determined auto-filing rules to the filtered set of event data, wherein the pre-determined auto-filing rules: automatically store a first portion of the filtered set of event data; and generate a remainder set of event data from a second portion of the filtered set of event data, different from the first portion of the filtered set of event data, wherein the second portion of the filtered set of event data is not automatically stored, wherein the pre-determined auto-filing rules are separate from the pre-determined grouping rules, and wherein the pre-determined auto-filing rules are not applied until after the pre-determined grouping rules are applied; and, executable code for displaying, on a display of the mobile device, a user interface that displays content that corresponds to one or more events of the remainder set of the event data, wherein the content that corresponds to the one or more events of the remainder set of the event data includes grouped content that corresponds to at least one of the one or more groups within the filtered set of data. 14. Computer software, according to claim 13 , wherein the event data include at least one of: photos, videos, recorded voice notes, phone calls, voice mails, user location data, messaging data, calendar entries, email messages, wireless data transmissions, and events scheduled from software applications and online services.
| 0.506936 |
2. The computing device of claim 1 , wherein the content of the source document is reflowable content.
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2. The computing device of claim 1 , wherein the content of the source document is reflowable content. 3. The computing device of claim 2 , wherein the computing device is further configured by the at least one executable module to obtain a global drawing representation table describing all drawing representations of contours and vertices of textual content utilized within the source document and store the global drawing representation table in the optimized document.
| 0.919521 |
21. The system of claim 20 , wherein the far-end dictionary generator component is further configured to identify one or more video frames from the video session for use as the one or more reference video frames to facilitate generation of one or more dictionary elements, based at least in part on defined coding criterion the defined coding criterion relating to at least one of quality of a visual image of a video frame or an amount of change detected in a visual scene depicted in a subset of video frames.
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21. The system of claim 20 , wherein the far-end dictionary generator component is further configured to identify one or more video frames from the video session for use as the one or more reference video frames to facilitate generation of one or more dictionary elements, based at least in part on defined coding criterion the defined coding criterion relating to at least one of quality of a visual image of a video frame or an amount of change detected in a visual scene depicted in a subset of video frames. 22. The system of claim 21 , further comprising a far-end identifier component configured to identify one or more frame identifiers respectively associated with the one or more reference video frames.
| 0.891556 |
7. The method of claim 5 , wherein said re-ranking comprises re-ranking using one or more additional features based on known properties of noun phrases and prepositional phrases.
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7. The method of claim 5 , wherein said re-ranking comprises re-ranking using one or more additional features based on known properties of noun phrases and prepositional phrases. 9. The method of claim 7 , wherein the one or more additional features comprises using the web as a language model.
| 0.951131 |
1. A method comprising: maintaining, by a computer system comprising at least one server computer, a plurality of data and at least one classification for each of the plurality of data; wherein each data of the plurality of data is aggregated from a plurality data sources and is abstracted into one or more of a plurality of standardized formats based on a type of the data; wherein the computer system has executing thereon a plurality of distinct classification engines, the plurality of distinct classification engines comprising: an a priori classification engine that is configured to classify data based on a set of user-specified classification rules; an a posteriori classification engine that is configured to classify data based on one or more probabilistic algorithm, wherein the one or more probabilistic algorithm is based on statistical analysis of collected data and multiple attributes associated with the collected data; wherein the posteriori classification engine is further configured to reclassify the previously classified data in response to a determination that the previously classified data was not correctly classified; and a heuristics engine that is configured to determine whether a plurality of characteristics are associated with the data and response to a positive determination, classify data based on metadata associated with the data; wherein each said at least one classification is performed by one of the plurality of distinct classification engines at a time of data collection and prior to storing the data in a database; receiving, by the computer system, query input from a user in accordance with at least one standardized format of the plurality of standardized formats; and querying, by the computer system, at least a portion of the plurality of data responsive to the query input.
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1. A method comprising: maintaining, by a computer system comprising at least one server computer, a plurality of data and at least one classification for each of the plurality of data; wherein each data of the plurality of data is aggregated from a plurality data sources and is abstracted into one or more of a plurality of standardized formats based on a type of the data; wherein the computer system has executing thereon a plurality of distinct classification engines, the plurality of distinct classification engines comprising: an a priori classification engine that is configured to classify data based on a set of user-specified classification rules; an a posteriori classification engine that is configured to classify data based on one or more probabilistic algorithm, wherein the one or more probabilistic algorithm is based on statistical analysis of collected data and multiple attributes associated with the collected data; wherein the posteriori classification engine is further configured to reclassify the previously classified data in response to a determination that the previously classified data was not correctly classified; and a heuristics engine that is configured to determine whether a plurality of characteristics are associated with the data and response to a positive determination, classify data based on metadata associated with the data; wherein each said at least one classification is performed by one of the plurality of distinct classification engines at a time of data collection and prior to storing the data in a database; receiving, by the computer system, query input from a user in accordance with at least one standardized format of the plurality of standardized formats; and querying, by the computer system, at least a portion of the plurality of data responsive to the query input. 2. The method of claim 1 , wherein the querying comprises: formatting one or more queries based on the query input; receiving one or more user credentials from the user; validating the user based at least in part on the user credentials; attaching user permissions to the one or more queries; and retrieving data of the plurality of data that satisfies the one or more queries.
| 0.51028 |
12. A computer system comprising at least one processor and a nontransitory computer-readable storage medium, the non-transitory computer-readable storage medium storing an executable program which directs the processor in performing a computer-implemented method for automatically assessing credibility of a particular website, the computer-implemented method comprising: classifying the particular website based on subject matter of the particular website, the particular website comprising a plurality of elements that produce a presentation of the website when rendered, each element of the plurality of elements defined by at least one attribute; identifying a set of credibility scoring rules based on the classification of the particular website, said set of credibility scoring rules for computing credibility of the particular website based on encoded preferences of a primary demographic of users for websites of the same classification as the particular website; for each particular element of the plurality of elements, producing a credibility score identifying whether the particular element when rendered for display according to the at least one attribute defined for that particular element increases credibility of the particular website by attracting more visitors to the particular website or decreases credibility of the particular website by discouraging visitors to the particular website, wherein producing the credibility score for a particular element comprises (i) selecting a particular credibility scoring rule from the identified set of credibility scoring rules that quantifies a credibility impact of the particular element and (ii) passing the at least one attribute defined for the particular element to the particular credibility scoring rule in order to generate a credibility score as output; and presenting credibility of the particular website by (i) rendering each particular element of the plurality of elements according to the at least one attribute that is defined for each particular element thereby producing a display of the particular website and (ii) overlaying each particular element with the credibility score that is computed for that particular element.
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12. A computer system comprising at least one processor and a nontransitory computer-readable storage medium, the non-transitory computer-readable storage medium storing an executable program which directs the processor in performing a computer-implemented method for automatically assessing credibility of a particular website, the computer-implemented method comprising: classifying the particular website based on subject matter of the particular website, the particular website comprising a plurality of elements that produce a presentation of the website when rendered, each element of the plurality of elements defined by at least one attribute; identifying a set of credibility scoring rules based on the classification of the particular website, said set of credibility scoring rules for computing credibility of the particular website based on encoded preferences of a primary demographic of users for websites of the same classification as the particular website; for each particular element of the plurality of elements, producing a credibility score identifying whether the particular element when rendered for display according to the at least one attribute defined for that particular element increases credibility of the particular website by attracting more visitors to the particular website or decreases credibility of the particular website by discouraging visitors to the particular website, wherein producing the credibility score for a particular element comprises (i) selecting a particular credibility scoring rule from the identified set of credibility scoring rules that quantifies a credibility impact of the particular element and (ii) passing the at least one attribute defined for the particular element to the particular credibility scoring rule in order to generate a credibility score as output; and presenting credibility of the particular website by (i) rendering each particular element of the plurality of elements according to the at least one attribute that is defined for each particular element thereby producing a display of the particular website and (ii) overlaying each particular element with the credibility score that is computed for that particular element. 16. The computer-implemented method of claim 12 , wherein presenting the action comprises displaying the action as text that is overlaid the specific element during presentation of the credibility of the particular website.
| 0.710214 |
6. A method of finding relationships between objects in a database comprising: generating an instance graph expressing relationships between the objects in said database; receiving a query including at least two terms; rewriting, heuristically, the query into an ordered list of sub-query terms, wherein the ordered list begins with first and second search terms; executing, with a processor, the first search term in a query, wherein said executing derives a subset of said database; performing a relationship search that ranks each object in said instance graph with respect to said subset; filtering out the objects of said relationship search, wherein each filtered out object has a score below a predetermined threshold; generating a summary graph using the subset of said executing; aggregating to said summary graph two or more of said filtered out objects which are related to at least one object having a score above said predetermined threshold; and executing said second search term on said summary graph, wherein the execution outputs second subset.
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6. A method of finding relationships between objects in a database comprising: generating an instance graph expressing relationships between the objects in said database; receiving a query including at least two terms; rewriting, heuristically, the query into an ordered list of sub-query terms, wherein the ordered list begins with first and second search terms; executing, with a processor, the first search term in a query, wherein said executing derives a subset of said database; performing a relationship search that ranks each object in said instance graph with respect to said subset; filtering out the objects of said relationship search, wherein each filtered out object has a score below a predetermined threshold; generating a summary graph using the subset of said executing; aggregating to said summary graph two or more of said filtered out objects which are related to at least one object having a score above said predetermined threshold; and executing said second search term on said summary graph, wherein the execution outputs second subset. 7. The method of claim 6 wherein said received query includes a third search term and further comprising executing said third search term on the results of said second subset.
| 0.712418 |
9. One or more computer-storage media having embodied thereon a data structure for a first schema describing a data store, the data structure being useable by a computing device to query the data store, the data structure comprising: a first property description element describing a first individual property of the data store including one or more static attributes and one or more contextual attributes that combine to describe the first individual property wherein each static attribute has a corresponding static attribute value and each contextual attribute has a corresponding contextual attribute value, wherein a static attribute associated with the first individual property is immutable and has the same static attribute value within all schemas that include the first individual property, wherein a contextual attribute is able to have different contextual attribute values among different schemas that include the first individual property, and wherein contextual attribute values are defined within each schema that has the contextual attribute; a property reference element describing a second individual property of the data store by referencing a second property description element from a second schema that includes static attributes and corresponding static attribute values wherein the property reference specifies contextual attributes and corresponding contextual attribute values, wherein the static attributes apply to all schemas that reference the second property description element, and wherein the contextual attributes apply only to the first schema: an item type description element describing an item type for at least one item in the data store, the item type description element including one or more properties that define the item type; and a kind description element describing a kind for at least one item in the data store, the kind description element including one or more properties for the kind, wherein the kind is a collection of logically related item types.
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9. One or more computer-storage media having embodied thereon a data structure for a first schema describing a data store, the data structure being useable by a computing device to query the data store, the data structure comprising: a first property description element describing a first individual property of the data store including one or more static attributes and one or more contextual attributes that combine to describe the first individual property wherein each static attribute has a corresponding static attribute value and each contextual attribute has a corresponding contextual attribute value, wherein a static attribute associated with the first individual property is immutable and has the same static attribute value within all schemas that include the first individual property, wherein a contextual attribute is able to have different contextual attribute values among different schemas that include the first individual property, and wherein contextual attribute values are defined within each schema that has the contextual attribute; a property reference element describing a second individual property of the data store by referencing a second property description element from a second schema that includes static attributes and corresponding static attribute values wherein the property reference specifies contextual attributes and corresponding contextual attribute values, wherein the static attributes apply to all schemas that reference the second property description element, and wherein the contextual attributes apply only to the first schema: an item type description element describing an item type for at least one item in the data store, the item type description element including one or more properties that define the item type; and a kind description element describing a kind for at least one item in the data store, the kind description element including one or more properties for the kind, wherein the kind is a collection of logically related item types. 11. The one or more computer-storage media of claim 9 , where the data structure further comprises a property reference list element that acts as a container for one or more property reference elements within the first schema.
| 0.550117 |
12. The method according to claim 1 , wherein the creating further comprises: identifying the at least one keyword by examining a set of one or more previously-stored documents to identify documents related to the at least one text document.
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12. The method according to claim 1 , wherein the creating further comprises: identifying the at least one keyword by examining a set of one or more previously-stored documents to identify documents related to the at least one text document. 14. The method according to claim 12 , wherein examining to identify documents related to the at least one text document comprises identifying the documents based on a cosine similarity metric.
| 0.944719 |
8. The method of claim 7 , further comprising, based on the acoustic activity map, assigning weights to the audio streams based on the SNR quality metric.
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8. The method of claim 7 , further comprising, based on the acoustic activity map, assigning weights to the audio streams based on the SNR quality metric. 9. The method of claim 8 , further comprising, based on the acoustic activity map, assigning weights to the audio streams further based on the degree to which the associated audio device, that provides a respective one of the audio streams, measures noise.
| 0.880464 |
7. A non-transitory recording medium having a computer-readable information processing program recorded thereon that causes a computer included in an information processing apparatus: wherein said computer comprises at least one processor operable to read and operate according to instructions within said computer-readable information processing program, and at least one memory operable to store at least portions of said computer-readable information processing program for access by said processor, and wherein said computer-readable information processing program includes algorithms to cause said processor to implement: a specifying unit that specifies information of a search target selected by a user, from a plurality of pieces of information about search targets which are displayed as a search result according to an order matching a display ranking associated with the searched search targets, and which include attribute values of the search targets; a comparing unit that, when a search target is selected according to a user input and remaining search targets are not selected according to the same user input, compares the attribute value of the selected search target with the attribute value of a non-selected search target, among the remaining search targets, when a condition that the display ranking of the non-selected search target in the search result is higher than the display ranking of the selected search target is met, wherein each of the attribute values of the selected search target and the non-selected search target is a value of an attribute item set in advance; and a control unit that, when the attribute value of the selected search target is more advantageous for the user than the attribute value of the non-selected search target as a result of the comparison by the comparing unit, performs control such that information about a search target, among the remaining search targets, whose attribute value is more advantageous than that of the selected search target changes to a display mode, the display mode being visually distinguishable from information about a search target, among the remaining search targets, whose attribute value is disadvantageous than that of the selected search target, wherein according to a type of the attribute item set in advance, it is predetermined whether a lower or higher attribute value is advantageous to the user, and the higher attribute value is disadvantageous when it is predetermined that the lower attribute value is advantageous and the lower attribute value is disadvantageous when it is predetermined that the higher attribute value is advantageous.
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7. A non-transitory recording medium having a computer-readable information processing program recorded thereon that causes a computer included in an information processing apparatus: wherein said computer comprises at least one processor operable to read and operate according to instructions within said computer-readable information processing program, and at least one memory operable to store at least portions of said computer-readable information processing program for access by said processor, and wherein said computer-readable information processing program includes algorithms to cause said processor to implement: a specifying unit that specifies information of a search target selected by a user, from a plurality of pieces of information about search targets which are displayed as a search result according to an order matching a display ranking associated with the searched search targets, and which include attribute values of the search targets; a comparing unit that, when a search target is selected according to a user input and remaining search targets are not selected according to the same user input, compares the attribute value of the selected search target with the attribute value of a non-selected search target, among the remaining search targets, when a condition that the display ranking of the non-selected search target in the search result is higher than the display ranking of the selected search target is met, wherein each of the attribute values of the selected search target and the non-selected search target is a value of an attribute item set in advance; and a control unit that, when the attribute value of the selected search target is more advantageous for the user than the attribute value of the non-selected search target as a result of the comparison by the comparing unit, performs control such that information about a search target, among the remaining search targets, whose attribute value is more advantageous than that of the selected search target changes to a display mode, the display mode being visually distinguishable from information about a search target, among the remaining search targets, whose attribute value is disadvantageous than that of the selected search target, wherein according to a type of the attribute item set in advance, it is predetermined whether a lower or higher attribute value is advantageous to the user, and the higher attribute value is disadvantageous when it is predetermined that the lower attribute value is advantageous and the lower attribute value is disadvantageous when it is predetermined that the higher attribute value is advantageous. 8. The non-transitory recording medium according to claim 7 , wherein, when the selected search target and the non-selected search target comprises a plurality of attribute values, respectively, the comparing unit compares the attribute value of the selected search target with the attribute values of the non-selected search target for each of the plurality of attribute values to determine the attribute value of the selected search target which is more advantageous for the user than that of the non-selected search target, and the control unit performs the control when the determined attribute value of a search target, among the remaining search targets, is more advantageous for the user than the determined attribute value of the selected search target.
| 0.51373 |
6. The computer-readable medium of claim 1 , wherein the filtering includes filtering out a cluster center entry in the global center vector table that includes feature vectors having no more than at least one user and at least one URL that are absent from the search queries.
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6. The computer-readable medium of claim 1 , wherein the filtering includes filtering out a cluster center entry in the global center vector table that includes feature vectors having no more than at least one user and at least one URL that are absent from the search queries. 7. The computer-readable medium of claim 6 , wherein the filtering out the cluster entry includes filtering out a cluster entry using an inverted user list that lists the users enumerated in the subgraph and an inverted URL list that lists the URLs enumerated in the subgraph.
| 0.889727 |
20. The computer-readable medium of claim 18 , wherein instantiating the tool pane further comprises receiving a field value directing the tool pane to be initiated.
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20. The computer-readable medium of claim 18 , wherein instantiating the tool pane further comprises receiving a field value directing the tool pane to be initiated. 21. The computer-readable medium of claim 20 , wherein the field value further includes a unique identifier for a selected component within the markup document, such that the tool pane instantiated is associated with the selected component.
| 0.919446 |
1. A computer implemented method of preparing an executable representation of a rating model, the method comprising: defining an actuary-manipulable representation of a rating model, the actuary-manipulable representation embodied in computer readable media and encoding therein variables, factor tables and calculation sequences of the rating model, the factor tables having one or more axes bound to respective ones of the variables and the calculation sequences defined in terms of steps operative on values of the variables and cells of the factor tables; and transforming the actuary-manipulable representation to the executable representation, the executable representation embodied in computer readable media and encoding therein resultant computer program code including a runtime lookup facility for identification of runtime identifiers in the executable representation corresponding to ones of the variables and a calculate method executable to generate a quote based on inputs supplied via a predefined input interface, wherein the transforming is performed at least in part by a compiler that executes on a computational machine.
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1. A computer implemented method of preparing an executable representation of a rating model, the method comprising: defining an actuary-manipulable representation of a rating model, the actuary-manipulable representation embodied in computer readable media and encoding therein variables, factor tables and calculation sequences of the rating model, the factor tables having one or more axes bound to respective ones of the variables and the calculation sequences defined in terms of steps operative on values of the variables and cells of the factor tables; and transforming the actuary-manipulable representation to the executable representation, the executable representation embodied in computer readable media and encoding therein resultant computer program code including a runtime lookup facility for identification of runtime identifiers in the executable representation corresponding to ones of the variables and a calculate method executable to generate a quote based on inputs supplied via a predefined input interface, wherein the transforming is performed at least in part by a compiler that executes on a computational machine. 10. The computer implemented method of claim 1 , wherein, for a particular calculation sequence retrieved from the computer readable media encoding of the actuary-manipulable representation, the transforming includes: decomposing the particular calculation sequence encoded therein into layers, each layer including those steps thereof that are at a same flow control level; for each layer, traversing the steps thereof to identify those of the variables used by the layer; for each layer, traversing the calculation sequence to identify the steps of the layer targeted by other steps of the calculation sequence and emitting code allocating storage for results of the targeted steps; and for each layer, emitting code for variable test and index calculations of the layer, wherein the emitted code is stored as part of an in-media computer readable encoding of at least a functional precursor to the resultant computer program code.
| 0.5 |
25. A dictation transcription interface as recited in claim 24, wherein said computer central processing unit writes a transcription control signal for controlling a transcription function via said computer bus to said memory storage means during a first cycle of said bus clock period and in response to said vectored interrupt handling system processing a selected one of said plurality of said input interrupt signals, wherein said memory storage means generates a stored transcription control signal by storing said transcription control signal.
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25. A dictation transcription interface as recited in claim 24, wherein said computer central processing unit writes a transcription control signal for controlling a transcription function via said computer bus to said memory storage means during a first cycle of said bus clock period and in response to said vectored interrupt handling system processing a selected one of said plurality of said input interrupt signals, wherein said memory storage means generates a stored transcription control signal by storing said transcription control signal. 26. A dictation transcription interface as recited in claim 25, wherein said processor system reads said stored transcription control signal from said memory storage means via said host bus during a second cycle of said bus clock period.
| 0.879834 |
1. A computer-implemented method of extracting information from co-occurring Hyper Text Mark-up Language (HTML) structured documents, the method comprising: presenting a list of web sites to a user; receiving one or more of the web sites selected from the user for data extraction; collecting a plurality of co-occurring different HTML structured documents for each of the selected web sites at a computer comprising a processor; forming a plurality of clusters comprising different subsets of the co-occurring HTML structured documents, wherein: each cluster comprises a different HTML structured document of the plurality of co-occurring HTML structured documents as a centroid document and other HTML structured documents of the plurality of co-occurring HTML structured documents that achieve a threshold of similarity with respect to the centroid document, the clusters are formed by comparing each co-occurring HTML structured document to each centroid document of each cluster based on relative structural similarity of HTML data structure of each co-occurring HTML structured document with respect to HTML data structure of each centroid document of each cluster, an alignment algorithm is used to determine the co-occurring HTML structured documents that achieve the threshold of similarity with respect to each centroid document by comparing structured locations of data fields for storing data elements within each centroid document and structured locations of corresponding data fields for storing data elements within each of the co-occurring HTML structured documents, the co-occurring HTML structured documents are compared to each centroid document based on similarity of structured locations of corresponding data fields within the HTML data structures without regard to content of data elements stored in the corresponding data fields within the HTML data structures, and the relative structural similarity of a particular co-occurring HTML structured document with respect to a particular centroid document is penalized when the co-occurring HTML structured document includes a data field that is within the particular centroid document in a different structured location; displaying a list of clusters; displaying the centroid document of a particular cluster selected from the list of clusters; marking a data element on the centroid document of the particular cluster; identifying a data element on each of the other HTML structured documents of the particular cluster that is stored within a data field having a structured location that corresponds to the structured location of the data field storing the marked data element within the centroid document of the particular cluster; and providing a user interface displaying content of data elements identified from the other HTML structured documents of the particular cluster on a computer display.
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1. A computer-implemented method of extracting information from co-occurring Hyper Text Mark-up Language (HTML) structured documents, the method comprising: presenting a list of web sites to a user; receiving one or more of the web sites selected from the user for data extraction; collecting a plurality of co-occurring different HTML structured documents for each of the selected web sites at a computer comprising a processor; forming a plurality of clusters comprising different subsets of the co-occurring HTML structured documents, wherein: each cluster comprises a different HTML structured document of the plurality of co-occurring HTML structured documents as a centroid document and other HTML structured documents of the plurality of co-occurring HTML structured documents that achieve a threshold of similarity with respect to the centroid document, the clusters are formed by comparing each co-occurring HTML structured document to each centroid document of each cluster based on relative structural similarity of HTML data structure of each co-occurring HTML structured document with respect to HTML data structure of each centroid document of each cluster, an alignment algorithm is used to determine the co-occurring HTML structured documents that achieve the threshold of similarity with respect to each centroid document by comparing structured locations of data fields for storing data elements within each centroid document and structured locations of corresponding data fields for storing data elements within each of the co-occurring HTML structured documents, the co-occurring HTML structured documents are compared to each centroid document based on similarity of structured locations of corresponding data fields within the HTML data structures without regard to content of data elements stored in the corresponding data fields within the HTML data structures, and the relative structural similarity of a particular co-occurring HTML structured document with respect to a particular centroid document is penalized when the co-occurring HTML structured document includes a data field that is within the particular centroid document in a different structured location; displaying a list of clusters; displaying the centroid document of a particular cluster selected from the list of clusters; marking a data element on the centroid document of the particular cluster; identifying a data element on each of the other HTML structured documents of the particular cluster that is stored within a data field having a structured location that corresponds to the structured location of the data field storing the marked data element within the centroid document of the particular cluster; and providing a user interface displaying content of data elements identified from the other HTML structured documents of the particular cluster on a computer display. 5. The method of claim 1 , where in the threshold is predetermined.
| 0.602443 |
1. A method for associating coronary angiography image annotations with a SYNTAX score for assessment of coronary artery disease comprising: receiving and processing, by a system comprising one or more processors, a plurality of angiogram videos from a coronary angiography study into a plurality of frames for each of the plurality of angiogram videos; extracting, by the system, a key frame from the plurality of frames for each of the plurality of angiogram videos, wherein extracting the key frame for each of the plurality of angiogram videos comprises detecting, by the system, a presence of a contrast agent in one or more frames of the plurality of frames of each given angiogram video, and using edge detection, edge curve following and pairing of curves on opposing sides of an artery to identify a representative frame of the given angiogram video having extended parallel curves; displaying to a user, by the system via a browsing interface, each of the extracted key frames; in response to receiving a selection from the user of a key frame from the displayed key frames, displaying, by the system via a video view interface, the angiogram video that is associated with the selected key frame; receiving, by the system, a lesion annotation from the user for a frame of the angiogram video; based on receiving the lesion annotation, displaying, by the system, a SYNTAX score questionnaire in the video viewer interface; based on receiving answers to the SYNTAX score questionnaire from the user, annotating, by the system, the frame of the angiogram video with the answers to the SYNTAX score questionnaire from the user; saving, by the system, the answers to the SYNTAX score questionnaire with the annotated frame in a database; computing and displaying a SYNTAX score for the lesion based on the answers to the SYNTAX score questionnaire; and generating a lesion report for a selected lesion that shows the answers of the SYNTAX score questionnaire for the selected lesion along with one or more frames illustrating the selected lesion.
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1. A method for associating coronary angiography image annotations with a SYNTAX score for assessment of coronary artery disease comprising: receiving and processing, by a system comprising one or more processors, a plurality of angiogram videos from a coronary angiography study into a plurality of frames for each of the plurality of angiogram videos; extracting, by the system, a key frame from the plurality of frames for each of the plurality of angiogram videos, wherein extracting the key frame for each of the plurality of angiogram videos comprises detecting, by the system, a presence of a contrast agent in one or more frames of the plurality of frames of each given angiogram video, and using edge detection, edge curve following and pairing of curves on opposing sides of an artery to identify a representative frame of the given angiogram video having extended parallel curves; displaying to a user, by the system via a browsing interface, each of the extracted key frames; in response to receiving a selection from the user of a key frame from the displayed key frames, displaying, by the system via a video view interface, the angiogram video that is associated with the selected key frame; receiving, by the system, a lesion annotation from the user for a frame of the angiogram video; based on receiving the lesion annotation, displaying, by the system, a SYNTAX score questionnaire in the video viewer interface; based on receiving answers to the SYNTAX score questionnaire from the user, annotating, by the system, the frame of the angiogram video with the answers to the SYNTAX score questionnaire from the user; saving, by the system, the answers to the SYNTAX score questionnaire with the annotated frame in a database; computing and displaying a SYNTAX score for the lesion based on the answers to the SYNTAX score questionnaire; and generating a lesion report for a selected lesion that shows the answers of the SYNTAX score questionnaire for the selected lesion along with one or more frames illustrating the selected lesion. 6. The method of claim 1 , wherein annotating the frame of the angiogram video with the answers to the SYNTAX score questionnaire comprises recording a run identifier of the frame, a frame identifier of the frame, a position of the lesion in the frame, a patient identifier, and an identifier of the user who completed the SYNTAX score questionnaire.
| 0.506184 |
17. A computer program product embodied on a tangible computer readable medium for facilitating a closing of a real estate transaction, comprising: code to receive real estate transaction information for a real estate transaction; wherein the real estate transaction information comprises information identifying a first party to the transaction and information identifying a property of the real estate transaction; wherein the first party comprises a party obtaining a real estate loan from a lender at the closing; wherein the real estate transaction information comprises information relating to a plurality of terms of the loan; code to store the real estate transaction information in a memory in a virtual file; code to search a plurality of the virtual files for the search criterion in response to receiving a first input; code to output information of one or more virtual files satisfying the search criterion; code to update information in the one virtual file based a second user input that comprises an update to one of the one or more virtual files; code to compile one or more electronic documents to be used in the real estate transaction with at least some of the real estate transaction information; code to output said one or more compiled electronic documents for review by one or more parties to the transaction; code to store data of a third user input that comprises an electronic signature indicating approval of at least one of said compiled electronic documents by a party to the transaction, code to determine payment amounts to be made to one or more entities who are not a party to the real estate transaction; code to store a digital image of at least one ancillary document, and code to output electronic closing documents for the real estate transaction that comprise: said at least one ancillary document; said electronic document with the electronic signature.
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17. A computer program product embodied on a tangible computer readable medium for facilitating a closing of a real estate transaction, comprising: code to receive real estate transaction information for a real estate transaction; wherein the real estate transaction information comprises information identifying a first party to the transaction and information identifying a property of the real estate transaction; wherein the first party comprises a party obtaining a real estate loan from a lender at the closing; wherein the real estate transaction information comprises information relating to a plurality of terms of the loan; code to store the real estate transaction information in a memory in a virtual file; code to search a plurality of the virtual files for the search criterion in response to receiving a first input; code to output information of one or more virtual files satisfying the search criterion; code to update information in the one virtual file based a second user input that comprises an update to one of the one or more virtual files; code to compile one or more electronic documents to be used in the real estate transaction with at least some of the real estate transaction information; code to output said one or more compiled electronic documents for review by one or more parties to the transaction; code to store data of a third user input that comprises an electronic signature indicating approval of at least one of said compiled electronic documents by a party to the transaction, code to determine payment amounts to be made to one or more entities who are not a party to the real estate transaction; code to store a digital image of at least one ancillary document, and code to output electronic closing documents for the real estate transaction that comprise: said at least one ancillary document; said electronic document with the electronic signature. 18. The computer program product of claim 17 , further comprising code to maintain information of a date for disbursing funds and wherein the date is subsequent to a closing date of the real estate transaction.
| 0.5 |
14. A computer-program product tangibly embodied in a non-transitory machine readable medium to perform a method for protecting numerical control codes, the computer-program product comprising instructions operable to cause a computer to: decrypt an encrypted text file that defines how an event for a tool path data set is processed, wherein the encrypted text file includes an encrypted seed number that has a fixed number of first random characters padded before and after a translated seed number, and includes second random characters inserted after each character in a translated instruction string; process said decrypted text file to obtain a set of instructions; format said set of instructions according to a definition file, wherein the definition file contains static information related to a machine tool and a corresponding controller for the machine tool; and output said set of formatted instructions, whereby postprocessed machine controls are written that can be executed by the controller.
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14. A computer-program product tangibly embodied in a non-transitory machine readable medium to perform a method for protecting numerical control codes, the computer-program product comprising instructions operable to cause a computer to: decrypt an encrypted text file that defines how an event for a tool path data set is processed, wherein the encrypted text file includes an encrypted seed number that has a fixed number of first random characters padded before and after a translated seed number, and includes second random characters inserted after each character in a translated instruction string; process said decrypted text file to obtain a set of instructions; format said set of instructions according to a definition file, wherein the definition file contains static information related to a machine tool and a corresponding controller for the machine tool; and output said set of formatted instructions, whereby postprocessed machine controls are written that can be executed by the controller. 15. The computer-program product of claim 14 , wherein said encrypted text file is written in an interpretive language.
| 0.69824 |
3. The method of claim 2 , wherein assigning the classifier function comprises: computing stationary probabilities and transition probabilities based on how often a link and node are selected.
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3. The method of claim 2 , wherein assigning the classifier function comprises: computing stationary probabilities and transition probabilities based on how often a link and node are selected. 4. The method of claim 3 , wherein selecting whether to follow a link is done according to a predefined random walk definition.
| 0.924609 |
15. A system for register-transfer level (RTL) design checking for exploring simulation mismatches, synthesis mismatches, or ambiguous language semantics associated with generating a derived design from RTL design code, the system comprising: at least one processor configured to generate an internal representation of an RTL design for an electronic circuit design by using the RTL design code; a design violation pattern database to contain design violation patterns, wherein the design violation patterns identify violations relating to the simulation mismatches, synthesis mismatches, or ambiguous language semantics associated with generating the derived design that are otherwise undetected during equivalence checking between the derived design and the RTL design code; and a design match engine configured to compare the RTL design code with the design violation patterns contained in the design violation pattern database, and wherein the at least one processor is further configured to assign a rule object to a design pattern in the RTL design code, when the design match engine determines that the design pattern in the RTL design code matches one of the design violation patterns in the design violation pattern database, and to generate a violation report comprising the rule objects and their corresponding design violation patterns.
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15. A system for register-transfer level (RTL) design checking for exploring simulation mismatches, synthesis mismatches, or ambiguous language semantics associated with generating a derived design from RTL design code, the system comprising: at least one processor configured to generate an internal representation of an RTL design for an electronic circuit design by using the RTL design code; a design violation pattern database to contain design violation patterns, wherein the design violation patterns identify violations relating to the simulation mismatches, synthesis mismatches, or ambiguous language semantics associated with generating the derived design that are otherwise undetected during equivalence checking between the derived design and the RTL design code; and a design match engine configured to compare the RTL design code with the design violation patterns contained in the design violation pattern database, and wherein the at least one processor is further configured to assign a rule object to a design pattern in the RTL design code, when the design match engine determines that the design pattern in the RTL design code matches one of the design violation patterns in the design violation pattern database, and to generate a violation report comprising the rule objects and their corresponding design violation patterns. 23. The system, of claim 15 , wherein the at least one processor is further configured to: select one of the rule objects in the violation report, graphically display at least a portion the design schematic corresponding to the selected rule object, and hi-light at least one of at least one unit and at least one connection corresponding to the selected rule object.
| 0.553228 |
1. A method of building a speech to text decoder, comprising: at a device having one or more processors and memory: acquiring data samples for building a language model; performing categorized sentence mining in the acquired data samples to obtain mining results comprising a respective set of sentences obtained through the categorized sentence mining for each of a plurality of categories; obtaining categorized training samples based on the mining results; building a text classifier based on the categorized training samples; classifying the data samples using the text classifier to obtain a respective class vocabulary and a respective training corpus for each of a plurality of categories; mining the respective training corpus for each category according to the respective class vocabulary for the category to obtain a respective set of high-frequency language templates; performing training on the respective set of high-frequency language templates for each category to obtain a respective template-based language model for the category; performing training on the respective training corpus for each category to obtain a respective class-based language model for the category; and performing training on the respective class vocabulary for each category to obtain a respective lexicon-based language model, wherein the respective template-based language model, the respective class-based language model, and the respective lexicon-based language model for a given category are language models for a given field, and the method further comprises: building the speech to text decoder according to a previously obtained acoustic model, the respective template-based language model, the respective class-based language model and the respective lexicon-based language model for the given field, and the data samples.
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1. A method of building a speech to text decoder, comprising: at a device having one or more processors and memory: acquiring data samples for building a language model; performing categorized sentence mining in the acquired data samples to obtain mining results comprising a respective set of sentences obtained through the categorized sentence mining for each of a plurality of categories; obtaining categorized training samples based on the mining results; building a text classifier based on the categorized training samples; classifying the data samples using the text classifier to obtain a respective class vocabulary and a respective training corpus for each of a plurality of categories; mining the respective training corpus for each category according to the respective class vocabulary for the category to obtain a respective set of high-frequency language templates; performing training on the respective set of high-frequency language templates for each category to obtain a respective template-based language model for the category; performing training on the respective training corpus for each category to obtain a respective class-based language model for the category; and performing training on the respective class vocabulary for each category to obtain a respective lexicon-based language model, wherein the respective template-based language model, the respective class-based language model, and the respective lexicon-based language model for a given category are language models for a given field, and the method further comprises: building the speech to text decoder according to a previously obtained acoustic model, the respective template-based language model, the respective class-based language model and the respective lexicon-based language model for the given field, and the data samples. 4. The method of claim 1 , wherein: classifying the data samples using the text classifier to obtain the respective class vocabulary and the respective training corpus for each of a plurality of categories further comprises: mining for sentences with a high degree of similarity in the data samples through the text classifier to obtain classification results comprising highly similar sentences; obtaining term frequency statistics on sentences in the classification results; selecting class words according to the term frequency statistics to obtain the respective class vocabulary for each of the plurality of categories; and taking sentences corresponding to the class words in the respective class vocabulary for each category as the respective training corpus for the category.
| 0.585106 |
5. A method, comprising: receiving text at a local device as part of a text communication; buffering the received text for a provisional time period prior to transmitting the buffered text over a communication network to a remote device; displaying the buffered text in substantially real time as the text is being received, wherein the received text is displayed on the local device during the provisional time period; allowing the buffered text to be modified during the provisional time period; and transmitting the buffered text over the communication network to the remote device independently of the provisional time period when a send character is detected.
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5. A method, comprising: receiving text at a local device as part of a text communication; buffering the received text for a provisional time period prior to transmitting the buffered text over a communication network to a remote device; displaying the buffered text in substantially real time as the text is being received, wherein the received text is displayed on the local device during the provisional time period; allowing the buffered text to be modified during the provisional time period; and transmitting the buffered text over the communication network to the remote device independently of the provisional time period when a send character is detected. 11. The method according to claim 5 , further comprising: transmitting the buffered text before expiration of the provisional time period in response to the buffered text forming a complete expression.
| 0.584407 |
19. A system for classifying a financial transaction of an item, comprising: a computer processor; a classification engine executing on the computer processor and configured to: receive a text description of the item involved in the financial transaction; process the text description of the item to generate a search term; and receive, from a user, feedback that a target category based a target affinity score is incorrect; a category module operatively connected to the classification engine and executing on the computer processor and configured to: receive the search term from the classification engine; select, based on the search term, a set of named categories of a plurality of named categories; and generate, in response to the feedback, a revised set of named categories by removing the target category from the set of named categories; a search module operatively connected to the classification engine and executing on the computer processor and configured to: conduct, using a search engine determined by a search algorithm, a first search for the search term and each named category of the set of named categories; process a first plurality of results of the first search; conduct a second search for the search term and each named category of the revised set of named categories; and process a second plurality of results of the second search; and a calculator operatively connected to the classification engine and executing on the computer processor and configured to: calculate, using the first plurality of results of the first search and an affinity algorithm, an affinity score of a plurality of affinity scores for each named category of the set of named categories; identify a first target affinity score of the plurality of affinity scores, wherein the affinity algorithm for one of the set of named categories uses the function: log {n(x & y)/[n(x)×n(y)]}, wherein n(x) is a first number of web pages comprising the search term, n(y) is a second number of web pages comprising the one of the set of named categories, n(x & y) is a third number of web pages comprising the search term and the one of the set of named categories, and log is a logarithm; identify a target category from the set of named categories based on the first target affinity score; send, to the classification engine, the text description of the item involved in the financial transaction and the target category; calculate, using the second plurality of results of the second search, a second affinity score of a second plurality of affinity scores for each named category of the revised set of named categories; identify a second target affinity score of the second plurality of affinity scores; identify a revised target category from the revised set of named categories based on the second target affinity score; and send, to the classification engine, the revised target category, wherein the classification engine displays, to the user, the text description of the item involved in the financial transaction, the target category based the target affinity score, and the revised target category based on the second target affinity score.
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19. A system for classifying a financial transaction of an item, comprising: a computer processor; a classification engine executing on the computer processor and configured to: receive a text description of the item involved in the financial transaction; process the text description of the item to generate a search term; and receive, from a user, feedback that a target category based a target affinity score is incorrect; a category module operatively connected to the classification engine and executing on the computer processor and configured to: receive the search term from the classification engine; select, based on the search term, a set of named categories of a plurality of named categories; and generate, in response to the feedback, a revised set of named categories by removing the target category from the set of named categories; a search module operatively connected to the classification engine and executing on the computer processor and configured to: conduct, using a search engine determined by a search algorithm, a first search for the search term and each named category of the set of named categories; process a first plurality of results of the first search; conduct a second search for the search term and each named category of the revised set of named categories; and process a second plurality of results of the second search; and a calculator operatively connected to the classification engine and executing on the computer processor and configured to: calculate, using the first plurality of results of the first search and an affinity algorithm, an affinity score of a plurality of affinity scores for each named category of the set of named categories; identify a first target affinity score of the plurality of affinity scores, wherein the affinity algorithm for one of the set of named categories uses the function: log {n(x & y)/[n(x)×n(y)]}, wherein n(x) is a first number of web pages comprising the search term, n(y) is a second number of web pages comprising the one of the set of named categories, n(x & y) is a third number of web pages comprising the search term and the one of the set of named categories, and log is a logarithm; identify a target category from the set of named categories based on the first target affinity score; send, to the classification engine, the text description of the item involved in the financial transaction and the target category; calculate, using the second plurality of results of the second search, a second affinity score of a second plurality of affinity scores for each named category of the revised set of named categories; identify a second target affinity score of the second plurality of affinity scores; identify a revised target category from the revised set of named categories based on the second target affinity score; and send, to the classification engine, the revised target category, wherein the classification engine displays, to the user, the text description of the item involved in the financial transaction, the target category based the target affinity score, and the revised target category based on the second target affinity score. 24. The system of claim 19 , further comprising: a storage repository configured to store a plurality of search algorithms and a plurality of affinity algorithms.
| 0.540778 |
13. A system comprising: a memory; and a processing device operatively coupled to the memory, the processing device being configured to execute operations comprising: identify an original topic representation for a set of electronic documents stored at least temporarily in a non-transitory storage media; perform, by a processor, an informativeness analysis on the original topic representation; perform a topic consistency analysis on the original topic representation; perform a topic redundancy analysis on the original topic representation in view of a second topic representation, wherein when performing a topic redundancy analysis on the original topic representation in view of a second topic representation, the processing device is configured to: identify a first set of knowledge points in the original topic representation and a second set of knowledge points in the second topic representation; identify a semantic vector representation of each knowledge point of the first set of knowledge points and second set of knowledge points; calculate a first centroid of the original topic representation and a second centroid of the second topic representation; calculate an average semantic distance between the first centroid and the second centroid; in response to determining that the average semantic distance between the first centroid and the second centroid is below a third threshold, merge the original topic representation and the second topic representation; and in response to determining that the average semantic distance between the first centroid and the second centroid is above the third threshold, keep the original topic representation and the second topic representation; and generate a refined topic representation based on the informativeness analysis, the consistency analysis, and the redundancy analysis.
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13. A system comprising: a memory; and a processing device operatively coupled to the memory, the processing device being configured to execute operations comprising: identify an original topic representation for a set of electronic documents stored at least temporarily in a non-transitory storage media; perform, by a processor, an informativeness analysis on the original topic representation; perform a topic consistency analysis on the original topic representation; perform a topic redundancy analysis on the original topic representation in view of a second topic representation, wherein when performing a topic redundancy analysis on the original topic representation in view of a second topic representation, the processing device is configured to: identify a first set of knowledge points in the original topic representation and a second set of knowledge points in the second topic representation; identify a semantic vector representation of each knowledge point of the first set of knowledge points and second set of knowledge points; calculate a first centroid of the original topic representation and a second centroid of the second topic representation; calculate an average semantic distance between the first centroid and the second centroid; in response to determining that the average semantic distance between the first centroid and the second centroid is below a third threshold, merge the original topic representation and the second topic representation; and in response to determining that the average semantic distance between the first centroid and the second centroid is above the third threshold, keep the original topic representation and the second topic representation; and generate a refined topic representation based on the informativeness analysis, the consistency analysis, and the redundancy analysis. 16. The system of claim 13 , wherein when performing the topic consistency analysis on the original topic representation, the processing device is configured to: identify a set of knowledge points in the original topic representation; identify a semantic vector representation of each knowledge point of the set of knowledge points; calculate a centroid of the original topic representation; calculate an average semantic distance to the centroid for the original topic representation; in response to determining that the average semantic distance to the centroid for the original topic representation is above a second threshold, remove the original topic representation; and in response to determining that the average semantic distance to the centroid for the original topic representation is below the second threshold, keep the original topic representation.
| 0.518917 |
1. A method for providing an extensible macro language comprising: maintaining, in a repository, a predefined macro language comprising a plurality of keywords and a plurality of associated commands for execution; using a parser to parse a macro language expression to identify a new keyword in the macro language expression that is not within the plurality of keywords in the predefined macro language; using a macro handler comprising a macro processor to retrieve, from a registry of keywords and associated executable codes, an executable code associated with the new keyword identified in the macro language expression, the executable code corresponding to a procedure that is not performed by the execution of the predefined macro language alone; and using the macro handler to execute the executable code retrieved from the registry to run the extended macro command associated with the new keyword in the macro language expression without recompiling the macro language, the executable code associated with the new keyword not included in the predefined macro language and resulting in the performance of a procedure that is not performed by execution of the predefined macro language alone.
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1. A method for providing an extensible macro language comprising: maintaining, in a repository, a predefined macro language comprising a plurality of keywords and a plurality of associated commands for execution; using a parser to parse a macro language expression to identify a new keyword in the macro language expression that is not within the plurality of keywords in the predefined macro language; using a macro handler comprising a macro processor to retrieve, from a registry of keywords and associated executable codes, an executable code associated with the new keyword identified in the macro language expression, the executable code corresponding to a procedure that is not performed by the execution of the predefined macro language alone; and using the macro handler to execute the executable code retrieved from the registry to run the extended macro command associated with the new keyword in the macro language expression without recompiling the macro language, the executable code associated with the new keyword not included in the predefined macro language and resulting in the performance of a procedure that is not performed by execution of the predefined macro language alone. 6. The method of claim 1 , wherein the registry of keywords comprises a table of keywords and associated macro commands.
| 0.91037 |
10. A method for searching content comprising: maintaining a log of queries; dividing said queries into individual query terms; analyzing said queries and partitioning the individual query terms into collections based on co-occurrence of the individual query terms within the queries, wherein co-occurrence of given ones of the individual query terms in a particular one of the queries comprises the given individual query terms co-occurring in a particular query; representing said query terms as nodes within a construct, with edges connecting the nodes, wherein each edge of said edges is assigned a frequency weight for representing co-occurrence in the queries of query terms represented by the nodes connected by a corresponding edge; partitioning, by a computer, said construct into sets based on said edges; distributing linking indices for the query terms to different index servers, depending upon the sets in which said query terms are located; maintaining a map indicating which of the index servers store corresponding ones of the linking indices for individual query terms; and distributing query terms in a new query to the index servers based on said map.
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10. A method for searching content comprising: maintaining a log of queries; dividing said queries into individual query terms; analyzing said queries and partitioning the individual query terms into collections based on co-occurrence of the individual query terms within the queries, wherein co-occurrence of given ones of the individual query terms in a particular one of the queries comprises the given individual query terms co-occurring in a particular query; representing said query terms as nodes within a construct, with edges connecting the nodes, wherein each edge of said edges is assigned a frequency weight for representing co-occurrence in the queries of query terms represented by the nodes connected by a corresponding edge; partitioning, by a computer, said construct into sets based on said edges; distributing linking indices for the query terms to different index servers, depending upon the sets in which said query terms are located; maintaining a map indicating which of the index servers store corresponding ones of the linking indices for individual query terms; and distributing query terms in a new query to the index servers based on said map. 13. The method as set forth in claim 10 wherein said partitioning further takes into account how often the query terms are found in the content.
| 0.614103 |
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