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8,211,155 | 12 | 17 | 12. A dynamic pedicle screw comprising: a bone screw having a longitudinal axis, a proximal end and a distal end; the distal end of the bone screw having suitable surface texture and adapted to engage a vertebra; a housing at the proximal end of the bone screw; a bore in the housing aligned with the longitudinal axis of the bone screw, the bore having an open end and a closed end, the closed end of the bore terminating in a spherical pocket; an elongated deflectable post having a ball-shaped retainer at a first end; the deflectable post being positioned in the bore of the housing such that the ball-shaped retainer is positioned within the spherical pocket and a second end of the deflectable post extends through the open end of the bore coaxial to the longitudinal axis of the screw; and a compliant sleeve positioned within the bore between the deflectable post and the housing; and wherein the compliant sleeve is shaped to control deflection of the deflectable post from alignment with the longitudinal axis of the bone screw. | 12. A dynamic pedicle screw comprising: a bone screw having a longitudinal axis, a proximal end and a distal end; the distal end of the bone screw having suitable surface texture and adapted to engage a vertebra; a housing at the proximal end of the bone screw; a bore in the housing aligned with the longitudinal axis of the bone screw, the bore having an open end and a closed end, the closed end of the bore terminating in a spherical pocket; an elongated deflectable post having a ball-shaped retainer at a first end; the deflectable post being positioned in the bore of the housing such that the ball-shaped retainer is positioned within the spherical pocket and a second end of the deflectable post extends through the open end of the bore coaxial to the longitudinal axis of the screw; and a compliant sleeve positioned within the bore between the deflectable post and the housing; and wherein the compliant sleeve is shaped to control deflection of the deflectable post from alignment with the longitudinal axis of the bone screw. 17. The dynamic pedicle screw of claim 12 , wherein said sleeve comprises a hydrophilic polymer. | 0.92381 |
7,826,600 | 1 | 2 | 1. A method of caching documents in a voice recognition system, the method comprising: receiving a requested voice application resource from a server; compiling the requested voice application resource into a representative lightweight executable object model that may be executed without being reparsed; storing the representative object model with the compiled voice application resource in cache memory for execution; and, executing the compiled voice application resource in the representative object model from cache memory without first reparsing and recompiling the voice application resource. | 1. A method of caching documents in a voice recognition system, the method comprising: receiving a requested voice application resource from a server; compiling the requested voice application resource into a representative lightweight executable object model that may be executed without being reparsed; storing the representative object model with the compiled voice application resource in cache memory for execution; and, executing the compiled voice application resource in the representative object model from cache memory without first reparsing and recompiling the voice application resource. 2. The method of claim 1 , further comprising compressing the representative object model before storing it in memory for execution. | 0.5 |
9,256,584 | 1 | 4 | 1. A system for providing a spellchecker function and for use with documents having rich text, the system comprising: a CPU, a computer readable memory and a computer readable storage media; program instructions to initialize a dictionary containing words; program instructions to create at least one signature for each dictionary word; program instructions to add each dictionary word to at least one list keyed by each of the at least one signatures for each dictionary word; program instructions to determine that a word is misspelled by checking the dictionary for the misspelled word resulting in a null value, the checking the dictionary comprising determining whether the misspelled word is present in the at least one list for a primary signature of the misspelled word, and when the misspelled word is not present in the at least one list, then the misspelled word is not spelled correctly resulting in the null value; program instructions to create a substitution list for the misspelled word when the misspelled word is not spelled correctly, which includes: creating at least one signature associated with the misspelled word; finding all the dictionary words in the at least one list keyed by the at least one signature associated with the misspelled word; and selecting best matches to the misspelled word; and program instructions to provide from the selected best matches at least one replacement word for the misspelled word in the documents having rich text, wherein the program instructions are stored on the computer readable storage media for execution by the CPU via the computer readable memory. | 1. A system for providing a spellchecker function and for use with documents having rich text, the system comprising: a CPU, a computer readable memory and a computer readable storage media; program instructions to initialize a dictionary containing words; program instructions to create at least one signature for each dictionary word; program instructions to add each dictionary word to at least one list keyed by each of the at least one signatures for each dictionary word; program instructions to determine that a word is misspelled by checking the dictionary for the misspelled word resulting in a null value, the checking the dictionary comprising determining whether the misspelled word is present in the at least one list for a primary signature of the misspelled word, and when the misspelled word is not present in the at least one list, then the misspelled word is not spelled correctly resulting in the null value; program instructions to create a substitution list for the misspelled word when the misspelled word is not spelled correctly, which includes: creating at least one signature associated with the misspelled word; finding all the dictionary words in the at least one list keyed by the at least one signature associated with the misspelled word; and selecting best matches to the misspelled word; and program instructions to provide from the selected best matches at least one replacement word for the misspelled word in the documents having rich text, wherein the program instructions are stored on the computer readable storage media for execution by the CPU via the computer readable memory. 4. The system of claim 1 , wherein the providing includes providing more than one replacement words in an ordered list for selection, wherein the more than one replacement words are ordered based upon a score. | 0.539648 |
8,688,433 | 1 | 3 | 1. A method for translating messages, comprising: receiving a message from a first user to a second user via one of a plurality of accounts associated with the second user, the message in a first language; accessing a storage device of a client processing device associated with the second user to determine a preferred language of the second user for the one of the plurality of accounts associated with the second user, wherein each of the plurality of accounts associated with the second user identifies a different preferred language; and translating the message to the preferred language of the second user for the one of the plurality of accounts associated with the second user when the first language is not the same as the preferred language of the second user for the one of the plurality of accounts associated with the second user. | 1. A method for translating messages, comprising: receiving a message from a first user to a second user via one of a plurality of accounts associated with the second user, the message in a first language; accessing a storage device of a client processing device associated with the second user to determine a preferred language of the second user for the one of the plurality of accounts associated with the second user, wherein each of the plurality of accounts associated with the second user identifies a different preferred language; and translating the message to the preferred language of the second user for the one of the plurality of accounts associated with the second user when the first language is not the same as the preferred language of the second user for the one of the plurality of accounts associated with the second user. 3. The method of claim 1 further comprising: receiving a reply message from the second user to the first user, the reply message in a second language; accessing a storage device of a client processing device associated with the first user to determine a preferred language of the first user; and translating the reply message to the preferred language of the first user when the second language is not the same as the preferred language of the first user. | 0.5 |
8,010,367 | 1 | 10 | 1. A method for authenticating a user, comprising: prompting a user for a free-form password in a password establishment dialog; receiving a user utterance; processing the utterance through a speech recognition engine to generate an acoustic baseform; associating the user with the acoustic baseform in a speaker-dependent password recognition grammar; matching, in a password usage dialog, user utterances against the acoustic baseform in the speaker-dependent password recognition grammar associated with the user, the matching thereby verifying both the free-form password and the user that provided the user utterance; and using results from the matching to determine whether to grant the user access to a secure resource. | 1. A method for authenticating a user, comprising: prompting a user for a free-form password in a password establishment dialog; receiving a user utterance; processing the utterance through a speech recognition engine to generate an acoustic baseform; associating the user with the acoustic baseform in a speaker-dependent password recognition grammar; matching, in a password usage dialog, user utterances against the acoustic baseform in the speaker-dependent password recognition grammar associated with the user, the matching thereby verifying both the free-form password and the user that provided the user utterance; and using results from the matching to determine whether to grant the user access to a secure resource. 10. The method of claim 1 , wherein said steps of claim 1 are steps performed automatically by at least one machine in accordance with at least one computer program having a plurality of code sections that are executable by the at least one machine, said at least one computer program being stored in a machine readable memory. | 0.548343 |
7,739,280 | 1 | 5 | 1. A user-interface method of selecting and presenting a collection of content items in which the presentation is ordered at least in part based on inferring preferences of a given user from a plurality of users of an input device, the preferences of the plurality of users of the input device being learned based on content items selected by the plurality of users, the method comprising: providing a set of content items, each content item having at least one associated descriptive term to describe the content item; receiving incremental inputs from a shared input device; in response to said incremental input, presenting a corresponding subset of content items; receiving from the shared input device selection actions of content items; analyzing the descriptive terms associated with the selected content items to learn a composite set of preferred descriptive terms of the plurality of users of the shared input device, wherein the shared input device used by the plurality of users is a solitary input device used by each user of the plurality of users so that the composite set of preferred descriptive terms collectively describes the descriptive terms associated with content items selected by each of the users of the plurality; inferring preferences of individual users of the plurality of users of the shared input device from the composite set of preferred descriptive terms by decomposing the composite set of preferred descriptive terms into individual sets of preferred descriptive terms, said decomposition act utilizing prespecified statistical models of preferences of a population according to demographic information; subsequent to learning the composite set of preferred descriptive terms of the plurality of users, receiving at least one content item selection action from one of the individual users and selecting an individual set of preferred descriptive terms for use in subsequent content item selections based on comparing said at least one selected content item to the individual sets of preferred descriptive terms; in response to receiving subsequent incremental input from the shared input device, selecting and ordering a collection of content items based on the individual set of preferred descriptive terms selected for use in subsequent content item selections; and presenting the ordered collection of content items on a display device. | 1. A user-interface method of selecting and presenting a collection of content items in which the presentation is ordered at least in part based on inferring preferences of a given user from a plurality of users of an input device, the preferences of the plurality of users of the input device being learned based on content items selected by the plurality of users, the method comprising: providing a set of content items, each content item having at least one associated descriptive term to describe the content item; receiving incremental inputs from a shared input device; in response to said incremental input, presenting a corresponding subset of content items; receiving from the shared input device selection actions of content items; analyzing the descriptive terms associated with the selected content items to learn a composite set of preferred descriptive terms of the plurality of users of the shared input device, wherein the shared input device used by the plurality of users is a solitary input device used by each user of the plurality of users so that the composite set of preferred descriptive terms collectively describes the descriptive terms associated with content items selected by each of the users of the plurality; inferring preferences of individual users of the plurality of users of the shared input device from the composite set of preferred descriptive terms by decomposing the composite set of preferred descriptive terms into individual sets of preferred descriptive terms, said decomposition act utilizing prespecified statistical models of preferences of a population according to demographic information; subsequent to learning the composite set of preferred descriptive terms of the plurality of users, receiving at least one content item selection action from one of the individual users and selecting an individual set of preferred descriptive terms for use in subsequent content item selections based on comparing said at least one selected content item to the individual sets of preferred descriptive terms; in response to receiving subsequent incremental input from the shared input device, selecting and ordering a collection of content items based on the individual set of preferred descriptive terms selected for use in subsequent content item selections; and presenting the ordered collection of content items on a display device. 5. The method of claim 1 , further comprising inferring which individual user entered the subsequent incremental input based on comparing the subsequent incremental input to the individual sets of preferred descriptive terms, wherein the act of selecting and ordering the collection of content items is based on the individual set of preferred descriptive terms corresponding to the inferred individual user. | 0.755102 |
8,255,218 | 23 | 24 | 23. A computing device comprising: an output device configured to display a graphical user interface (GUI) including a first input field and a second input field; a microphone configured to receive vocal input from a user, wherein at least a portion of the vocal input is intended for input into the first input field; an input device configured to receive a selection by the user of the second input field; an audio conversion module configured to identify vocal input received prior to the selection of the second input field as first vocal input intended for the first input field, and to identify vocal input received after the selection of the second input field as second vocal input intended for the second input field; and a input field module configured to graphically input a first text portion in the first input field, wherein the first text portion is based upon conversion of the first vocal input into textual characters by an automatic speech recognition (ASR) engine, and to graphically input a second text portion in the second input field, wherein the second text portion is based upon conversion of the second vocal input into textual characters by the ASR engine. | 23. A computing device comprising: an output device configured to display a graphical user interface (GUI) including a first input field and a second input field; a microphone configured to receive vocal input from a user, wherein at least a portion of the vocal input is intended for input into the first input field; an input device configured to receive a selection by the user of the second input field; an audio conversion module configured to identify vocal input received prior to the selection of the second input field as first vocal input intended for the first input field, and to identify vocal input received after the selection of the second input field as second vocal input intended for the second input field; and a input field module configured to graphically input a first text portion in the first input field, wherein the first text portion is based upon conversion of the first vocal input into textual characters by an automatic speech recognition (ASR) engine, and to graphically input a second text portion in the second input field, wherein the second text portion is based upon conversion of the second vocal input into textual characters by the ASR engine. 24. The computing device of claim 23 , wherein: the output device configured to display the GUI including a third input field; the input device is configured to receive a selection by the user of the third input field; the audio conversion module configured to identify vocal input received after the selection of the third input field as third vocal input intended for the third input field; and the text module is configured to graphically input a third text portion in the third input field, wherein the third text portion is based upon conversion of the third vocal input into textual characters by the ASR engine. | 0.5 |
9,002,701 | 1 | 14 | 1. A method comprising: receiving, using a processor, an input identifying search criteria for searching an electronic text; determining, using the processor, text subgroups within the electronic text; selecting, using the processor, a text subgroup relating to a current user position within the electronic text and the search criteria; determining, using the processor, a similarity relationship between the search criteria and one or more text subgroups adjacent to the selected text subgroup; creating, using the processor, a text cluster by associating the search criteria with the one or more adjacent text subgroups based on the determined similarity relationship to the search criteria; determining, using the processor, an activity indication of times when a user has read other text subgroups within the electronic text; determining, using the processor, a similarity relationship between the text cluster and the other text subgroups; linking, using the processor, the text cluster to one of the other text subgroups based on the determined similarity relationship to the one of the other text subgroups; and presenting, using the processor, a graphic representing the similarity relationship between the one of the other text subgroups and the text cluster based on the activity indication of times when the user read the other text subgroups. | 1. A method comprising: receiving, using a processor, an input identifying search criteria for searching an electronic text; determining, using the processor, text subgroups within the electronic text; selecting, using the processor, a text subgroup relating to a current user position within the electronic text and the search criteria; determining, using the processor, a similarity relationship between the search criteria and one or more text subgroups adjacent to the selected text subgroup; creating, using the processor, a text cluster by associating the search criteria with the one or more adjacent text subgroups based on the determined similarity relationship to the search criteria; determining, using the processor, an activity indication of times when a user has read other text subgroups within the electronic text; determining, using the processor, a similarity relationship between the text cluster and the other text subgroups; linking, using the processor, the text cluster to one of the other text subgroups based on the determined similarity relationship to the one of the other text subgroups; and presenting, using the processor, a graphic representing the similarity relationship between the one of the other text subgroups and the text cluster based on the activity indication of times when the user read the other text subgroups. 14. The method of claim 1 , further comprising storing a navigational aid in metadata of the electronic text that indicates the similarity relationship between the text cluster and the other text subgroups. | 0.852011 |
9,117,006 | 11 | 14 | 11. A method for recommending keywords, comprising: receiving a set of product information including a product title; extracting and parsing the product title into a set of parsed elements; finding a plurality of candidate keywords corresponding to at least a subset of the set of parsed elements based at least in part on stored predetermined mappings between parsed data and keywords; determining a plurality of composite correlation scores for corresponding ones of the plurality of candidate keywords, wherein determining the plurality of composite correlation scores includes determining a first composite correlation score associated with a first candidate keyword of the plurality of candidate keywords, wherein determining the first composite correlation score associated with the first candidate keyword includes determining an industry index value associated with the first candidate keyword, including: determining a first similarity value between one or more industries associated with the first candidate keyword and one or more industries associated with sets of product information that are relevant to the first candidate keyword; determining a second similarity value between the one or more industries associated with the first candidate keyword and one or more industries of one or more seller users associated with the sets of product information that are relevant to the first candidate keyword; and determining the industry index value associated with the first candidate keyword based at least in part on a combination of the first similarity value and the second similarity value; and sorting at least a subset of the plurality of candidate keywords into a ranked list based on at least a subset of the plurality of composite correlation scores; and selecting a set of one or more keywords to recommend from the plurality of candidate keywords based at least in part on the ranked list. | 11. A method for recommending keywords, comprising: receiving a set of product information including a product title; extracting and parsing the product title into a set of parsed elements; finding a plurality of candidate keywords corresponding to at least a subset of the set of parsed elements based at least in part on stored predetermined mappings between parsed data and keywords; determining a plurality of composite correlation scores for corresponding ones of the plurality of candidate keywords, wherein determining the plurality of composite correlation scores includes determining a first composite correlation score associated with a first candidate keyword of the plurality of candidate keywords, wherein determining the first composite correlation score associated with the first candidate keyword includes determining an industry index value associated with the first candidate keyword, including: determining a first similarity value between one or more industries associated with the first candidate keyword and one or more industries associated with sets of product information that are relevant to the first candidate keyword; determining a second similarity value between the one or more industries associated with the first candidate keyword and one or more industries of one or more seller users associated with the sets of product information that are relevant to the first candidate keyword; and determining the industry index value associated with the first candidate keyword based at least in part on a combination of the first similarity value and the second similarity value; and sorting at least a subset of the plurality of candidate keywords into a ranked list based on at least a subset of the plurality of composite correlation scores; and selecting a set of one or more keywords to recommend from the plurality of candidate keywords based at least in part on the ranked list. 14. The method of claim 11 , wherein determining the plurality of composite correlation scores includes determining the first composite correlation score associated with the first candidate keyword based at least in part on a text-based correlation value between the first candidate keyword and a corresponding parsed element from the set of parsed elements. | 0.69244 |
7,571,485 | 14 | 15 | 14. A computer readable medium containing a computer program product for preventing unauthorized network activity, the computer program product comprising: program code for detecting an attempt by a computer to communicate with a remote site over a computer network; program code for querying a database containing descriptions of known legitimate sites for an entry describing the remote site, wherein the database has hierarchical entries according to a schema, and a level of the hierarchy describes data gathered by a class of remote sites; program code for comparing a data gathering profile for the site described by the database entry to a request for data made by the remote site; and program code for determining whether the remote site is to be treated as suspicious based at least on the results of the comparing step. | 14. A computer readable medium containing a computer program product for preventing unauthorized network activity, the computer program product comprising: program code for detecting an attempt by a computer to communicate with a remote site over a computer network; program code for querying a database containing descriptions of known legitimate sites for an entry describing the remote site, wherein the database has hierarchical entries according to a schema, and a level of the hierarchy describes data gathered by a class of remote sites; program code for comparing a data gathering profile for the site described by the database entry to a request for data made by the remote site; and program code for determining whether the remote site is to be treated as suspicious based at least on the results of the comparing step. 15. The computer program product of claim 14 further comprising: program code for, responsive to locating an entry in the database describing the remote site, comparing the database entry describing the remote site to the remote site itself, to determine whether the remote site conforms to the database description; program code for, responsive to determining that the remote site conforms to the database description, determining that the remote site is legitimate; and program code for, responsive to determining that the remote site does not conform to the database description, determining that the remote site is suspicious. | 0.567901 |
9,501,295 | 12 | 13 | 12. The computer program product of claim 11 , wherein said resulting composite values list of valid locales and languages combinations is used at least for one of the following processes: adjustment of a user interface; and presenting a list of language and locale combination options for selection to a user. | 12. The computer program product of claim 11 , wherein said resulting composite values list of valid locales and languages combinations is used at least for one of the following processes: adjustment of a user interface; and presenting a list of language and locale combination options for selection to a user. 13. The computer program product of claim 12 , wherein said adjustment process of said user interface further comprises: generating a list of valid language and locale combinations based on at least one language and at least one locale accepted by a browser and a user preferred language and locale setting; matching said list of valid language and locale combinations with said resulting composite values list of valid locales and languages combinations; eliminating valid combinations of said list of valid language and locale combinations which are not supported by said service management system resulting in a modified list of valid language and locale combinations; and translating user interface elements and messages based on said modified list of valid language and locale combinations. | 0.5 |
9,471,705 | 15 | 16 | 15. One or more computer-readable non-transitory storage media embodying software operable when executed to: receive a request from a client device for a target structured document; in response to the received request from the client device and in a first response phase: access a data structure comprising an entry for the target structured document and one or more first resources associated with the target structured document; for each of one or more of the first resources associated with the target structured document: compute a probability for the first resource that represents a likelihood that the first resource will be included in a response to a future request for the target structured document; compare the probability to a first predetermined threshold; and when the probability exceeds the first predetermined threshold, identify the first resource as a selected first resource for the target structured document; generate a first response portion comprising one or more of: one or more of the selected first resources; or one or more references to one or more of the selected first resources; send the first response portion to the client; and further in response to the received request from the client device and in a second response phase taking place after sending the first response portion: for each of one or more of the second resources associated with the target structured document: compute a probability for the second resource that represents a likelihood that the second resource will be included in a response to a future request for the target structured document; compare the probability to a second predetermined threshold; and when the probability exceeds the second predetermined threshold, identify the second resource as a selected second resource for the target structured document; generate a second response portion comprising structured document language code for the target structured document and one or more of: one or more of the selected second resources associated with the target structured document; or one or more references to one or more of the selected second resources; and send the second response portion to the same client device. | 15. One or more computer-readable non-transitory storage media embodying software operable when executed to: receive a request from a client device for a target structured document; in response to the received request from the client device and in a first response phase: access a data structure comprising an entry for the target structured document and one or more first resources associated with the target structured document; for each of one or more of the first resources associated with the target structured document: compute a probability for the first resource that represents a likelihood that the first resource will be included in a response to a future request for the target structured document; compare the probability to a first predetermined threshold; and when the probability exceeds the first predetermined threshold, identify the first resource as a selected first resource for the target structured document; generate a first response portion comprising one or more of: one or more of the selected first resources; or one or more references to one or more of the selected first resources; send the first response portion to the client; and further in response to the received request from the client device and in a second response phase taking place after sending the first response portion: for each of one or more of the second resources associated with the target structured document: compute a probability for the second resource that represents a likelihood that the second resource will be included in a response to a future request for the target structured document; compare the probability to a second predetermined threshold; and when the probability exceeds the second predetermined threshold, identify the second resource as a selected second resource for the target structured document; generate a second response portion comprising structured document language code for the target structured document and one or more of: one or more of the selected second resources associated with the target structured document; or one or more references to one or more of the selected second resources; and send the second response portion to the same client device. 16. The media of claim 15 , wherein: the target structured document comprises a Hyper Text Markup Language (HTML) document; the HTML document comprises a head element and one or more other HTML elements; the first response portion comprises a first portion of the head element; and the second response portion comprises the remainder of the HTML document including a second portion of the head element. | 0.5 |
8,112,705 | 1 | 5 | 1. A computer implemented method of magnifying a portion of a document in a browser, comprising: presenting a first document in a first display area in the browser, wherein the first document is displayed with an original font size; receiving a selection of a portion of the first document for magnified display; generating a magnified display of the portion of the first document to form a magnified portion, wherein the magnified display of the portion comprises text in a second font size that is larger than the original font size, wherein generating the magnified display further comprises: presenting the magnified portion in a magnifier window in a second display area within the first display area, wherein the second display area is presented on top of at least a portion of the first display area and obstructs from view the portion of the first display area; analyzing a document object model for the first document; and identifying a portion of the document object model that corresponds to the portion of the first document, wherein the magnified display of the portion of the first document is generated based on the portion of the document object model receiving a request for an action, wherein the action is to be applied within the magnified display in the magnifier window; and performing the action with respect to the magnified display, wherein the magnified portion presents the portion of the document object model and retains full browser functionality within the magnifier window. | 1. A computer implemented method of magnifying a portion of a document in a browser, comprising: presenting a first document in a first display area in the browser, wherein the first document is displayed with an original font size; receiving a selection of a portion of the first document for magnified display; generating a magnified display of the portion of the first document to form a magnified portion, wherein the magnified display of the portion comprises text in a second font size that is larger than the original font size, wherein generating the magnified display further comprises: presenting the magnified portion in a magnifier window in a second display area within the first display area, wherein the second display area is presented on top of at least a portion of the first display area and obstructs from view the portion of the first display area; analyzing a document object model for the first document; and identifying a portion of the document object model that corresponds to the portion of the first document, wherein the magnified display of the portion of the first document is generated based on the portion of the document object model receiving a request for an action, wherein the action is to be applied within the magnified display in the magnifier window; and performing the action with respect to the magnified display, wherein the magnified portion presents the portion of the document object model and retains full browser functionality within the magnifier window. 5. The computer implemented method of claim 1 , wherein generating the magnified display of the portion of the first document to form the magnified portion comprises generating the magnified display based upon a magnification factor. | 0.72907 |
7,783,658 | 13 | 17 | 13. A computer-readable storage medium storing program instructions for implementing a method executable by a processor for identifying one or more target entities, the method comprising: receiving an input data set, wherein the input data set includes a plurality of tokens that reflect the one or more target entities; determining which of the tokens are labels; identifying one or more candidate entities that are related to each of the labels, wherein individual ones of the candidate entities are associated with a number of candidates; assigning a weight to each candidate entity of a label based on each candidate entity's associated number of candidates, wherein the weight that is assigned to a particular one of the candidate entities is related to an inverse of the number of candidates associated with the particular candidate entity; ranking the candidate entities of the label according to the assigned weights; and outputting one of the plurality of candidate entities for the label that has been assigned a highest weight value. | 13. A computer-readable storage medium storing program instructions for implementing a method executable by a processor for identifying one or more target entities, the method comprising: receiving an input data set, wherein the input data set includes a plurality of tokens that reflect the one or more target entities; determining which of the tokens are labels; identifying one or more candidate entities that are related to each of the labels, wherein individual ones of the candidate entities are associated with a number of candidates; assigning a weight to each candidate entity of a label based on each candidate entity's associated number of candidates, wherein the weight that is assigned to a particular one of the candidate entities is related to an inverse of the number of candidates associated with the particular candidate entity; ranking the candidate entities of the label according to the assigned weights; and outputting one of the plurality of candidate entities for the label that has been assigned a highest weight value. 17. The computer-readable storage medium of claim 13 , wherein if a candidate entity of a first label is associated with a second label, the method further comprises: modifying the weight of the candidate entity of the first label. | 0.659292 |
5,404,510 | 4 | 16 | 4. A method as claimed in claim 3 wherein the candidate indexes are ordered by request value of importance, the method further comprising, with identification of each candidate index, searching previously identified indexes for an existing index that is similar to the candidate index and choosing from the steps of a) creating a new index, b) reusing the best existing index and c) modifying the best existing index to satisfy the context of the candidate index, choice of steps a, b and c being dependent on match between the candidate index and the best existing index and the value of importance of the requests for which the indexes are identified. | 4. A method as claimed in claim 3 wherein the candidate indexes are ordered by request value of importance, the method further comprising, with identification of each candidate index, searching previously identified indexes for an existing index that is similar to the candidate index and choosing from the steps of a) creating a new index, b) reusing the best existing index and c) modifying the best existing index to satisfy the context of the candidate index, choice of steps a, b and c being dependent on match between the candidate index and the best existing index and the value of importance of the requests for which the indexes are identified. 16. A method as claimed in claim 4 wherein the best existing index is changed to the candidate index if the best existing index is sorted, the candidate index is either hash or sorted, the best existing index has a lesser number of columns, the columns of the best existing index match in identity and position, and the importance of the candidate index is greater than a threshold relative to the importance of the best existing index. | 0.528139 |
7,617,176 | 11 | 12 | 11. A computer implemented system that facilitates processing of search results, comprising: a memory having stored therein computer-executable instructions configured to implement the clustering system, including: means for receiving search results that contain titles and snippets of information; means for extracting phrases from the search results, with phrases occurring in titles being weighted more heavily than keywords occurring in snippets; means for calculating properties for each of the phrases, wherein the properties include phrase frequency and inverted document frequency, phrase length, cluster entropy and phrase independence; means for applying a regression model learned from previous training data to process the properties into a salient score for each phrase; means for ranking the phrases in descending order according to respective salient scores, wherein the top-ranked phrases are salient phrases; means for dynamically generating one or more candidate clusters of the search results, wherein the candidate clusters are labeled by the salient phrases and the names of the candidate clusters being phrases when a salient keyword is merged with other salient keywords; means for merging candidate clusters to form final clusters; means for merging a first cluster and a second cluster into a third cluster, when overlap of the first and second clusters exceeds a predetermined threshold; and means for adjusting cluster names of the final clusters to generate a new cluster name for the third cluster. | 11. A computer implemented system that facilitates processing of search results, comprising: a memory having stored therein computer-executable instructions configured to implement the clustering system, including: means for receiving search results that contain titles and snippets of information; means for extracting phrases from the search results, with phrases occurring in titles being weighted more heavily than keywords occurring in snippets; means for calculating properties for each of the phrases, wherein the properties include phrase frequency and inverted document frequency, phrase length, cluster entropy and phrase independence; means for applying a regression model learned from previous training data to process the properties into a salient score for each phrase; means for ranking the phrases in descending order according to respective salient scores, wherein the top-ranked phrases are salient phrases; means for dynamically generating one or more candidate clusters of the search results, wherein the candidate clusters are labeled by the salient phrases and the names of the candidate clusters being phrases when a salient keyword is merged with other salient keywords; means for merging candidate clusters to form final clusters; means for merging a first cluster and a second cluster into a third cluster, when overlap of the first and second clusters exceeds a predetermined threshold; and means for adjusting cluster names of the final clusters to generate a new cluster name for the third cluster. 12. The system of claim 11 , wherein the regression model is a linear regression model, a logistic regression model, a trained support vector regression model or an automatic classifier system. | 0.5 |
9,208,592 | 1 | 10 | 1. A computer-implemented system for providing a display of clusters, comprising: a processor; a display module to present a plurality of cluster spines in a two-dimensional display, wherein each cluster spine comprises a vector of document clusters; a compass positioned over at least a portion of the clusters of one or more of the cluster spines; spine labels provided for at least one of the cluster spines within the compass and placed around a circumference of the compass; a pinning module to pin one of the spine labels to the compass at a fixed location; a reorientation module to reorient the compass within the display; and the two-dimensional display to display the pinned spine label at the fixed location on the reoriented compass. | 1. A computer-implemented system for providing a display of clusters, comprising: a processor; a display module to present a plurality of cluster spines in a two-dimensional display, wherein each cluster spine comprises a vector of document clusters; a compass positioned over at least a portion of the clusters of one or more of the cluster spines; spine labels provided for at least one of the cluster spines within the compass and placed around a circumference of the compass; a pinning module to pin one of the spine labels to the compass at a fixed location; a reorientation module to reorient the compass within the display; and the two-dimensional display to display the pinned spine label at the fixed location on the reoriented compass. 10. A system according to claim 1 , wherein each spine label comprises a common concept that connects the clusters appearing in the associated cluster spine. | 0.767062 |
7,721,226 | 9 | 11 | 9. The system of claim 8 , wherein placing the glom widget near the current writing location further comprises placing the glom widget such that user movement to access the glom widget is decreased as compared to accessing a corresponding command contained within a fixed menu. | 9. The system of claim 8 , wherein placing the glom widget near the current writing location further comprises placing the glom widget such that user movement to access the glom widget is decreased as compared to accessing a corresponding command contained within a fixed menu. 11. The system of claim 9 , wherein the glom widget menu is customizable. | 0.777439 |
9,009,172 | 18 | 19 | 18. The method of claim 1 , wherein the step of comparing the stored node of the parsed XML event with one or more nodes stored in the first data structure or the second data structure further comprises: setting, by the computing device, the child node comparison indicator to “True” and the status comparison indicator to “TagMatch”, when a comparable stored node of the stored node of the parsed XML event exists, the parsed XML event is the start element, and the node mismatch indicator is set to “False”; comparing, by the computing device, the set of tag attributes and the values of the set of tag attributes of the comparable stored node with the set of tag attributes and the values of the set of tag attributes of the stored node of the parsed XML event, when the child node comparison indicator is set to “True”; outputting, by the computing device, a difference result comprising differences in the set of tag attributes and the values of the set of tag attributes of the comparable stored node and the stored node of the parsed XML event; removing, by the computing device, the outputted set of tag attributes of the comparable stored node and the outputted set of tag attributes of the stored node from the first data structure and the second data structure after the difference result is outputted; and performing the step (f), whereby the XML event indicator is set to the XML document of the parsed XML event. | 18. The method of claim 1 , wherein the step of comparing the stored node of the parsed XML event with one or more nodes stored in the first data structure or the second data structure further comprises: setting, by the computing device, the child node comparison indicator to “True” and the status comparison indicator to “TagMatch”, when a comparable stored node of the stored node of the parsed XML event exists, the parsed XML event is the start element, and the node mismatch indicator is set to “False”; comparing, by the computing device, the set of tag attributes and the values of the set of tag attributes of the comparable stored node with the set of tag attributes and the values of the set of tag attributes of the stored node of the parsed XML event, when the child node comparison indicator is set to “True”; outputting, by the computing device, a difference result comprising differences in the set of tag attributes and the values of the set of tag attributes of the comparable stored node and the stored node of the parsed XML event; removing, by the computing device, the outputted set of tag attributes of the comparable stored node and the outputted set of tag attributes of the stored node from the first data structure and the second data structure after the difference result is outputted; and performing the step (f), whereby the XML event indicator is set to the XML document of the parsed XML event. 19. The method of claim 18 , further comprising, when the child node comparison indicator is set to ‘True’, performing the step (g), whereby in the step (f), the XML event indicator set to the XML document of the parsed XML event in each iteration, until the end element of the stored node of the parsed XML event, that set the child comparison indicator to ‘True’, is parsed. | 0.5 |
9,141,741 | 21 | 22 | 21. The system of claim 20 , in which the at least one processor or at least one processor core that is to maintain one or more pertinent elements is further to: determine whether the object includes a switch module; determine whether the object includes a legal mixed-signal; and determine whether the object includes a legal expression recognized by an extension to the standardized power format. | 21. The system of claim 20 , in which the at least one processor or at least one processor core that is to maintain one or more pertinent elements is further to: determine whether the object includes a switch module; determine whether the object includes a legal mixed-signal; and determine whether the object includes a legal expression recognized by an extension to the standardized power format. 22. The system of claim 21 , in which the at least one processor or at least one processor core that is to maintain one or more pertinent elements is further to: identify a first element from the one or more pertinent elements of the at least a part of the power data; determine whether the first element includes a legal signal for the standardized power format; identify a first database from the one or more databases for the first element; determine whether there exists a second element in the one or more pertinent element; identify the second element from the one or more pertinent elements of the at least a part of the power data; determine whether the second element includes the illegal signal for the standardized power format; and identify a second database from the one or more databases for the second element. | 0.5 |
9,223,850 | 1 | 8 | 1. A method of searching a plurality of data files, wherein each data file includes a plurality of data items, the method comprising: using a processor to: select training corpora; train a language model for speech processing using said selected corpora; process speech using said language model, wherein selecting training corpora includes: inputting at least one data file relating to the subject matter of the speech to be processed; determining a plurality of index items, wherein each index item includes a combination of n data items and n is an integer of 2 or more; expressing each data file as a file vector with each component of the vector indicating the frequency of a different index item within the data file, wherein the index items to which the components of the vector correspond are the same for all data files, and wherein the n data items which constitute an index item do not have to be located adjacent to one another in a data file, and at least one index item includes data items from more than one data file; and expressing a search query using said index items as a vector; and search said plurality of data files by comparing the search query expressed as a vector with said file vectors. | 1. A method of searching a plurality of data files, wherein each data file includes a plurality of data items, the method comprising: using a processor to: select training corpora; train a language model for speech processing using said selected corpora; process speech using said language model, wherein selecting training corpora includes: inputting at least one data file relating to the subject matter of the speech to be processed; determining a plurality of index items, wherein each index item includes a combination of n data items and n is an integer of 2 or more; expressing each data file as a file vector with each component of the vector indicating the frequency of a different index item within the data file, wherein the index items to which the components of the vector correspond are the same for all data files, and wherein the n data items which constitute an index item do not have to be located adjacent to one another in a data file, and at least one index item includes data items from more than one data file; and expressing a search query using said index items as a vector; and search said plurality of data files by comparing the search query expressed as a vector with said file vectors. 8. The method according to claim 1 , wherein the file vectors are arranged in a matrix, and said matrix is factorised. | 0.724299 |
8,504,380 | 3 | 4 | 3. A method according to claim 1 , further comprising excluding, by the computing device, from said subset individual tasks whose association with previous clinical trial protocols fail a particular association strength criterion. | 3. A method according to claim 1 , further comprising excluding, by the computing device, from said subset individual tasks whose association with previous clinical trial protocols fail a particular association strength criterion. 4. A method according to claim 3 , wherein said particular association strength criterion excludes individual tasks from said subset that are indicated in said historical database as having been included in no more than a predetermined percentage of previous clinical trial protocols that satisfy user-specified filtering criteria. | 0.531161 |
9,417,941 | 6 | 7 | 6. The processing device of claim 1 , where the instruction sequence comprises one or more non-selected instructions, which are not in the subsequence of selected instructions. | 6. The processing device of claim 1 , where the instruction sequence comprises one or more non-selected instructions, which are not in the subsequence of selected instructions. 7. The processing device of claim 6 , wherein the processing device is arranged, in response to execution of each of the non-selected instructions, to set the status word to a value, which is independent of input data of the instruction sequence and results of preceding instructions of the instruction sequence. | 0.509434 |
10,027,804 | 11 | 18 | 11. A method for providing hiring recommendations of agents within a call center, comprising: receiving into a call center, a voice sample collected from a candidate agent via a handset; gathering via a speech recognition server the voice sample from the candidate agent, wherein the server comprises a central processing unit, memory, an input port that receives the voice sample from the handset, and an output port; measuring via a spectrum analyzer device within the voice sample voice characteristics comprising at least one of pitch, range of resonance frequencies of vowel, average resonance frequency of particular vowels, spectral tilt, breathiness, creakiness, nasality, speed of words, pause duration and intonation and comparing the voice characteristics from the voice sample with at least one graph comprising voice characteristics for two or more populations of a trait, which are each represented by a curve; assigning a score to the candidate agent by identifying at least a portion of the voice characteristics from the voice sample on the graph based on the comparison, assigning a numerical value to each identified voice characteristic from the voice sample based on the comparison, and summing the numerical values for the identified voice characteristics as the score; identifying by the server one of the populations to which the candidate agent belongs for that trait based on the assigned score; and providing by the server a recommendation for hire within the call center for the candidate agent based on the assigned score and the identified population. | 11. A method for providing hiring recommendations of agents within a call center, comprising: receiving into a call center, a voice sample collected from a candidate agent via a handset; gathering via a speech recognition server the voice sample from the candidate agent, wherein the server comprises a central processing unit, memory, an input port that receives the voice sample from the handset, and an output port; measuring via a spectrum analyzer device within the voice sample voice characteristics comprising at least one of pitch, range of resonance frequencies of vowel, average resonance frequency of particular vowels, spectral tilt, breathiness, creakiness, nasality, speed of words, pause duration and intonation and comparing the voice characteristics from the voice sample with at least one graph comprising voice characteristics for two or more populations of a trait, which are each represented by a curve; assigning a score to the candidate agent by identifying at least a portion of the voice characteristics from the voice sample on the graph based on the comparison, assigning a numerical value to each identified voice characteristic from the voice sample based on the comparison, and summing the numerical values for the identified voice characteristics as the score; identifying by the server one of the populations to which the candidate agent belongs for that trait based on the assigned score; and providing by the server a recommendation for hire within the call center for the candidate agent based on the assigned score and the identified population. 18. A method according to claim 11 , further comprising: applying a threshold to the score; and providing the recommendation for hire when the score satisfies the threshold. | 0.672348 |
9,519,629 | 10 | 12 | 10. A system comprising: one or more memories; one or more hardware processors in communication with the one or more memories; and an optimization component stored in the one or more memories and executed by the at least one processor to: analyze a plurality of styles associated with one or more pages, to identify at least one common rule shared by at least some of the plurality of styles, the plurality of styles defined in a cascading style sheet file and including one or more rules; combine the at least one common rule shared by at least some of the plurality of styles to define a common style that includes the at least one common rule; associate the common style that includes the at least one common rule with an owner of the common style that is at least one of an individual, an entity, or an organization responsible for the common style; and dynamically provide the common style that includes the at least one common rule in response to a request for at least one of the one or more pages. | 10. A system comprising: one or more memories; one or more hardware processors in communication with the one or more memories; and an optimization component stored in the one or more memories and executed by the at least one processor to: analyze a plurality of styles associated with one or more pages, to identify at least one common rule shared by at least some of the plurality of styles, the plurality of styles defined in a cascading style sheet file and including one or more rules; combine the at least one common rule shared by at least some of the plurality of styles to define a common style that includes the at least one common rule; associate the common style that includes the at least one common rule with an owner of the common style that is at least one of an individual, an entity, or an organization responsible for the common style; and dynamically provide the common style that includes the at least one common rule in response to a request for at least one of the one or more pages. 12. The system of claim 10 , wherein the common style is defined as a class in a cascading style sheet (CSS). | 0.827532 |
9,984,772 | 3 | 4 | 3. The method of claim 1 , wherein the natural language processing framework identifies target medical syntax by matching the plurality of sentences to one or more ontology references. | 3. The method of claim 1 , wherein the natural language processing framework identifies target medical syntax by matching the plurality of sentences to one or more ontology references. 4. The method of claim 3 , wherein the target medical syntax comprises a description of one or more diseases. | 0.574219 |
10,120,933 | 14 | 26 | 14. A device for language processing that represents both sematic and orientation content within a text, the device comprising: circuitry configured to receive ordered data elements representing respective words in a text, the ordered data elements including a first data element and a second data element, which is sequential with the first data element; generate, based on a plurality of semantic classes corresponding respectively to blades of a graded vector space representing clusters of semantic meaning, a first subspace formed within the graded vector space by the first data element, a second subspace within the graded vector space by the second data element, a first set of data elements corresponding to one or more first semantic classes that include the first data element, and a second set of data elements corresponding to one or more second semantic classes that include the second data element; encode, when the one or more first semantic classes is non-degenerate with the one or more second semantic classes, the first data element with respect to the second data element such that the an encoded subspace formed by encoding the first data element with respect to the second data element is oriented with respect to an order of the first data element with respect to the second data element, the encoding being performed by computing one of a left contraction and a right contraction of the first set of data elements with respect to the second set of data elements; compute respective components of a weight distribution of the first data element with respect to the second data element, the components of the weight distribution corresponding to respective ordered pairs for each of the one or more first semantic classes with respect to the one or more second semantic classes; and determine a dominant semantic class of to an ordered sequence of the first data element and the second data element, the dominant semantic class representing an oriented semantic context of the ordered sequence of the first and second data elements, and the dominant semantic class being determined as a semantic class corresponding to a component having a maximum magnitude of the weight distribution, wherein the left contraction is one of a Clifford Algebra left contraction and a Geometric Algebra left contraction, and the right contraction is one of a Clifford Algebra right contraction and a Geometric Algebra right contraction. | 14. A device for language processing that represents both sematic and orientation content within a text, the device comprising: circuitry configured to receive ordered data elements representing respective words in a text, the ordered data elements including a first data element and a second data element, which is sequential with the first data element; generate, based on a plurality of semantic classes corresponding respectively to blades of a graded vector space representing clusters of semantic meaning, a first subspace formed within the graded vector space by the first data element, a second subspace within the graded vector space by the second data element, a first set of data elements corresponding to one or more first semantic classes that include the first data element, and a second set of data elements corresponding to one or more second semantic classes that include the second data element; encode, when the one or more first semantic classes is non-degenerate with the one or more second semantic classes, the first data element with respect to the second data element such that the an encoded subspace formed by encoding the first data element with respect to the second data element is oriented with respect to an order of the first data element with respect to the second data element, the encoding being performed by computing one of a left contraction and a right contraction of the first set of data elements with respect to the second set of data elements; compute respective components of a weight distribution of the first data element with respect to the second data element, the components of the weight distribution corresponding to respective ordered pairs for each of the one or more first semantic classes with respect to the one or more second semantic classes; and determine a dominant semantic class of to an ordered sequence of the first data element and the second data element, the dominant semantic class representing an oriented semantic context of the ordered sequence of the first and second data elements, and the dominant semantic class being determined as a semantic class corresponding to a component having a maximum magnitude of the weight distribution, wherein the left contraction is one of a Clifford Algebra left contraction and a Geometric Algebra left contraction, and the right contraction is one of a Clifford Algebra right contraction and a Geometric Algebra right contraction. 26. The device of claim 14 , wherein type of semantic class of the plurality of semantic classes is assigned a unique metric, the unique metric being utilized in the computation of one of the left contraction and a right contraction operations as a measure within one of the respective blades. | 0.697314 |
8,713,054 | 20 | 23 | 20. The method of claim 12 , further comprising: establishing a hierarchal algorithm associated with said at least one criterion of said electronic document security regimen, establishing an overall document mark for said electronic document from said hierarchal algorithm, where said hierarchal algorithm uses said classification mark existing for said at least one informational portion of said electronic document and inserting said overall document mark into said electronic document. | 20. The method of claim 12 , further comprising: establishing a hierarchal algorithm associated with said at least one criterion of said electronic document security regimen, establishing an overall document mark for said electronic document from said hierarchal algorithm, where said hierarchal algorithm uses said classification mark existing for said at least one informational portion of said electronic document and inserting said overall document mark into said electronic document. 23. The method of claim 20 , wherein said electronic document security regimen further comprising at least one requirement for a final classification mark and wherein said overall document mark is established as said final classification mark where said at least one requirement is met, and where said overall document mark is established as an interim mark where said at least one requirement is not met. | 0.5 |
8,566,277 | 1 | 6 | 1. A system comprising: a non-transitory computer-readable medium storing computer-executable code, the computer-executable code comprising: a client interface module for generating an interface for receiving a copybook selection, the client interface module adapted for communication to receive the copybook selection; an import module for importing a copybook from a database, the copybook corresponding with a set of COBOL data stored in the database that includes a REDEFINE clause, the import module adapted for communication to receive the copybook selection from the client interface module and to import the copybook from the database; an object model module for creating an object model for the copybook, the object model module adapted for communication to receive the copybook from the import module and store the object model in a model library; and a modeler module for receiving the set of COBOL data and forming, based at least in part on the received set of COBOL data, an object instance that is equivalent to the set of COBOL data, the object instance including one or more representations for a complete set of one or more properties included in the REDEFINE clause without requiring custom coding for the forming of the object instance, the modeler module adapted for communication to receive the set of COBOL data from the database and to retrieve the object model from the model library, the modeler module including a REDEFINE module for identifying an instance of the REDEFINE clause and automatically forming the REDEFINE clause as the object instance, the REDEFINE module adapted to read the set of COBOL data. | 1. A system comprising: a non-transitory computer-readable medium storing computer-executable code, the computer-executable code comprising: a client interface module for generating an interface for receiving a copybook selection, the client interface module adapted for communication to receive the copybook selection; an import module for importing a copybook from a database, the copybook corresponding with a set of COBOL data stored in the database that includes a REDEFINE clause, the import module adapted for communication to receive the copybook selection from the client interface module and to import the copybook from the database; an object model module for creating an object model for the copybook, the object model module adapted for communication to receive the copybook from the import module and store the object model in a model library; and a modeler module for receiving the set of COBOL data and forming, based at least in part on the received set of COBOL data, an object instance that is equivalent to the set of COBOL data, the object instance including one or more representations for a complete set of one or more properties included in the REDEFINE clause without requiring custom coding for the forming of the object instance, the modeler module adapted for communication to receive the set of COBOL data from the database and to retrieve the object model from the model library, the modeler module including a REDEFINE module for identifying an instance of the REDEFINE clause and automatically forming the REDEFINE clause as the object instance, the REDEFINE module adapted to read the set of COBOL data. 6. The system of claim 1 , wherein the set of COBOL data is a COBOL data file. | 0.875399 |
8,837,018 | 10 | 16 | 10. The image forming apparatus according to claim 9 , wherein the foreign object detecting unit detects a stripe pattern that extends in a scanning direction in the image data on the page of the document scanned by the image scanning unit to detect whether a foreign object exists on the scanning unit. | 10. The image forming apparatus according to claim 9 , wherein the foreign object detecting unit detects a stripe pattern that extends in a scanning direction in the image data on the page of the document scanned by the image scanning unit to detect whether a foreign object exists on the scanning unit. 16. The image forming apparatus according to claim 10 , wherein, if the stripe pattern is detected in the image data on the last page of the document, the control unit compares the position in a primary scanning direction of the stripe pattern in the image data on a page of the document, which is scanned before the last page of the document, with the position in the primary scanning direction of the stripe pattern in the image data on the last page of the document to cause the display unit to display a guidance image prompting a user to clean the scanning face if a difference in position between the stripe patterns is over a predetermined threshold value. | 0.500753 |
9,087,121 | 8 | 10 | 8. A system for determining solutions to a problem experienced by a user with respect to a data processing system, comprising: a processor; a memory storing instructions operable to be executed by the processor, wherein the instructions include instructions to: select a collection of documents; analyze the text in each document using plain text analysis and an unstructured information management application containing text analytics rules to identify problems and associated solutions, the plain text analysis using a problem dictionary containing words and phrases that identify sentences describing problems and a solution dictionary containing words and phrases that identify sentences describing solutions to problems; create a searchable index of problems and associated solutions and storing the index in a database; receive a problem description from a user of the problem experienced by the user with respect to the data processing system, after creating the searchable index; analyze the received problem description using plain text analysis to extract one or more keywords from the problem description; search the index of problems and associated solutions using the one or more extracted keywords; return one or more documents containing words or phrases that are similar to the one or more extracted keywords; and present the documents relevant for the problem and associated solutions to the user. | 8. A system for determining solutions to a problem experienced by a user with respect to a data processing system, comprising: a processor; a memory storing instructions operable to be executed by the processor, wherein the instructions include instructions to: select a collection of documents; analyze the text in each document using plain text analysis and an unstructured information management application containing text analytics rules to identify problems and associated solutions, the plain text analysis using a problem dictionary containing words and phrases that identify sentences describing problems and a solution dictionary containing words and phrases that identify sentences describing solutions to problems; create a searchable index of problems and associated solutions and storing the index in a database; receive a problem description from a user of the problem experienced by the user with respect to the data processing system, after creating the searchable index; analyze the received problem description using plain text analysis to extract one or more keywords from the problem description; search the index of problems and associated solutions using the one or more extracted keywords; return one or more documents containing words or phrases that are similar to the one or more extracted keywords; and present the documents relevant for the problem and associated solutions to the user. 10. The system of claim 8 , wherein the instructions to present the documents include instructions to organize the documents relevant for the problem and associated solutions based on a correlation of keywords and frequency of solutions. | 0.554511 |
9,177,127 | 7 | 10 | 7. A knowledge-based authentication (KBA) system constructed and arranged to generate a KBA question configured to be provided to a person requesting authentication as a user that is a member of an organization, the KBA question including a query, a correct answer corresponding to the query, and a set of incorrect answers corresponding to the query, the KBA system comprising: a network interface; memory; and a controller including controlling circuitry, the controlling circuitry being constructed and arranged to: produce personal information management (PIM) data from communications involving members of the organization, PIM data from communications involving a particular member of the organization including a reference to the particular member; obtain a set of user facts from the PIM data that includes a reference to the user; generate a set of confounders from user facts of the set of user facts; and select incorrect answers from the set of confounders to form the set of incorrect answers corresponding to the query of the KBA question; wherein the controlling circuitry is further constructed and arranged to: produce the query and the corresponding correct answer of the KBA question from a first subset of the user facts; wherein generating the set of confounders from the user facts includes: producing the set of confounders from a second subset of the user facts, the second subset of the user facts being distinct from the first subset of the user facts; wherein the PIM data includes a set of emails, each email of the set of emails including a header containing i) a user identifier that identifies the user, and ii) a context that identifies subject matter of the email; wherein producing the query and the corresponding correct answer of the KBA question includes: extracting the context from the header of an email of a first subset of emails of the set of emails, the first subset of user facts being derived from the first subset of emails; wherein producing the set of confounders includes: extracting a confounder of the set of confounders from the header of an email of a second subset of emails of the set of emails, the second subset of user facts being derived from the second subset of emails; and wherein the controlling circuitry is further constructed and arranged to: arrange the user identifier, the context, and the set of confounders in an entry in a confounder database. | 7. A knowledge-based authentication (KBA) system constructed and arranged to generate a KBA question configured to be provided to a person requesting authentication as a user that is a member of an organization, the KBA question including a query, a correct answer corresponding to the query, and a set of incorrect answers corresponding to the query, the KBA system comprising: a network interface; memory; and a controller including controlling circuitry, the controlling circuitry being constructed and arranged to: produce personal information management (PIM) data from communications involving members of the organization, PIM data from communications involving a particular member of the organization including a reference to the particular member; obtain a set of user facts from the PIM data that includes a reference to the user; generate a set of confounders from user facts of the set of user facts; and select incorrect answers from the set of confounders to form the set of incorrect answers corresponding to the query of the KBA question; wherein the controlling circuitry is further constructed and arranged to: produce the query and the corresponding correct answer of the KBA question from a first subset of the user facts; wherein generating the set of confounders from the user facts includes: producing the set of confounders from a second subset of the user facts, the second subset of the user facts being distinct from the first subset of the user facts; wherein the PIM data includes a set of emails, each email of the set of emails including a header containing i) a user identifier that identifies the user, and ii) a context that identifies subject matter of the email; wherein producing the query and the corresponding correct answer of the KBA question includes: extracting the context from the header of an email of a first subset of emails of the set of emails, the first subset of user facts being derived from the first subset of emails; wherein producing the set of confounders includes: extracting a confounder of the set of confounders from the header of an email of a second subset of emails of the set of emails, the second subset of user facts being derived from the second subset of emails; and wherein the controlling circuitry is further constructed and arranged to: arrange the user identifier, the context, and the set of confounders in an entry in a confounder database. 10. A system according to claim 7 , wherein extracting the confounder of the set of confounders from the header of the email includes: from the emails of the second subset of emails, generating a list of references to other members of the organization, from the list of references to the other members of the organization, generating a group of peers of the user according to a link strength between the user and another member of the organization, and selecting the confounder from the group of peers of the user. | 0.5 |
8,549,489 | 2 | 12 | 2. The method of claim 1 wherein the predefined command comprises an enterable word and a constant word, wherein the entry component corresponds to the enterable word. | 2. The method of claim 1 wherein the predefined command comprises an enterable word and a constant word, wherein the entry component corresponds to the enterable word. 12. The method of claim 2 wherein the enterable word comprises a condition word comprising a first condition value logically related to a second condition value. | 0.85175 |
8,805,933 | 14 | 25 | 14. A method for building an interest profile for a user comprising: performing the following steps using one or more processors: creating an interest profile for a user; capturing an outgoing document; determining an electronic message thread comprising the outgoing document and one or more documents related to the outgoing document which are part of the same conversation as the outgoing document, wherein the one or more documents related to the outgoing document include at least some terms or content not present in the outgoing document, and wherein the one or more documents of the message thread includes a stored incoming document; scanning the message thread for at least one of terms or content to determine at least one item of interest for the user based on the at least one of terms or content of the scanned message thread, wherein the at least one item of interest is not otherwise determinable from the terms or content of the outgoing document, and wherein one or more terms and content of the stored incoming document and of the outgoing document are weighted differently when determining the at least one item of interest; and adding said at least one item of interest to the interest profile. | 14. A method for building an interest profile for a user comprising: performing the following steps using one or more processors: creating an interest profile for a user; capturing an outgoing document; determining an electronic message thread comprising the outgoing document and one or more documents related to the outgoing document which are part of the same conversation as the outgoing document, wherein the one or more documents related to the outgoing document include at least some terms or content not present in the outgoing document, and wherein the one or more documents of the message thread includes a stored incoming document; scanning the message thread for at least one of terms or content to determine at least one item of interest for the user based on the at least one of terms or content of the scanned message thread, wherein the at least one item of interest is not otherwise determinable from the terms or content of the outgoing document, and wherein one or more terms and content of the stored incoming document and of the outgoing document are weighted differently when determining the at least one item of interest; and adding said at least one item of interest to the interest profile. 25. The method of claim 14 , wherein the message thread includes a plurality of stored incoming documents and a plurality of stored outgoing documents, wherein the one or more terms and content of the plurality of stored incoming documents is weighted differently from the one or more terms and content of the plurality of outgoing documents when determining the at least one item of interest. | 0.750951 |
9,263,047 | 3 | 5 | 3. The server of claim 1 , wherein the operations further comprise: recognizing a word in the voice message, wherein the recognizing is based on the context of the voice message; and generating text representing the voice message, wherein the enhanced message comprises the text and the additional content. | 3. The server of claim 1 , wherein the operations further comprise: recognizing a word in the voice message, wherein the recognizing is based on the context of the voice message; and generating text representing the voice message, wherein the enhanced message comprises the text and the additional content. 5. The server of claim 3 , wherein the operations further comprise selecting a speech recognition grammar, wherein the selecting is in accordance with the context of the voice message, and wherein the text is generated according to the speech recognition grammar. | 0.5 |
9,141,668 | 1 | 3 | 1. A computer-implemented method to determine individuals having desired skills, the method comprising: receiving, by an application and from a requesting entity, a request to identify individuals having a desired skill specified in the request, wherein the application includes a semantic layer, a knowledge management system (KMS) layer, and a collaboration layer, wherein the request comprises a query composed according to a query language not supported by the KMS layer; reformulating the query by the semantic layer and into a different query language supported by the KMS layer; identifying, by accessing a data store using the reformulated query: (i) a first individual having the specified skill and (ii) a first characterization of a skill level of the first individual in the specified skill, wherein the first characterization is stored in the data store and is determined based on input from a plurality of individuals, wherein the data store contains a body of knowledge represented by the KMS layer; and upon determining, by the collaboration layer and by operation of one or more computer processors, that a count of the plurality of individuals is less than a desired count of individuals characterizing the skill level of the first individual, confirming the skill level of the first individual by requesting at least a second individual to provide a second characterization of the skill level of the first individual in the specified skill, wherein the second individual is not included in the plurality of individuals. | 1. A computer-implemented method to determine individuals having desired skills, the method comprising: receiving, by an application and from a requesting entity, a request to identify individuals having a desired skill specified in the request, wherein the application includes a semantic layer, a knowledge management system (KMS) layer, and a collaboration layer, wherein the request comprises a query composed according to a query language not supported by the KMS layer; reformulating the query by the semantic layer and into a different query language supported by the KMS layer; identifying, by accessing a data store using the reformulated query: (i) a first individual having the specified skill and (ii) a first characterization of a skill level of the first individual in the specified skill, wherein the first characterization is stored in the data store and is determined based on input from a plurality of individuals, wherein the data store contains a body of knowledge represented by the KMS layer; and upon determining, by the collaboration layer and by operation of one or more computer processors, that a count of the plurality of individuals is less than a desired count of individuals characterizing the skill level of the first individual, confirming the skill level of the first individual by requesting at least a second individual to provide a second characterization of the skill level of the first individual in the specified skill, wherein the second individual is not included in the plurality of individuals. 3. The computer-implemented method according to claim 1 , wherein the reformulated query has a predetermined syntax. | 0.91172 |
8,868,430 | 11 | 12 | 11. The method of claim 10 , further comprising: receiving an indication of one of speech and text as a desired output at the second communication terminal, wherein generating the translated signal in the language translation unit comprises generating the translated signal representing one of speech and text in the second human language responsive to the indication of the desired output. | 11. The method of claim 10 , further comprising: receiving an indication of one of speech and text as a desired output at the second communication terminal, wherein generating the translated signal in the language translation unit comprises generating the translated signal representing one of speech and text in the second human language responsive to the indication of the desired output. 12. The method of claim 11 , wherein the indication of the desired output comprises speech, and further comprising: receiving, from the first communication terminal, an indication of a sex and/or an age of a user thereof, wherein generating the translated signal in the language translation unit comprises generating the translated signal representing speech in the second human language in real time using a voice in accordance with the indication of the sex and/or the age of the user of the first communication terminal. | 0.5 |
8,131,715 | 1 | 2 | 1. A computer-readable medium that stores instructions executable by a computer, the computer-readable medium comprising: one or more instructions to identify documents in a network; one or more instructions to assign initial scores to the documents, where the initial score assigned to one of the documents that has been previously bookmarked by a user is higher than the initial score assigned to another one of the documents that has not been previously bookmarked by the user; one or more instructions to determine a score for a particular one of the documents based on the initial scores assigned to the documents that point to the particular one of the documents; and one or more instructions to store the score for the particular one of the documents. | 1. A computer-readable medium that stores instructions executable by a computer, the computer-readable medium comprising: one or more instructions to identify documents in a network; one or more instructions to assign initial scores to the documents, where the initial score assigned to one of the documents that has been previously bookmarked by a user is higher than the initial score assigned to another one of the documents that has not been previously bookmarked by the user; one or more instructions to determine a score for a particular one of the documents based on the initial scores assigned to the documents that point to the particular one of the documents; and one or more instructions to store the score for the particular one of the documents. 2. The computer-readable medium of claim 1 , where the one or more instructions to determine the score for the particular one of the documents include: one or more instructions to determine the score for the particular one of the documents based on a sum of the initial scores assigned to the documents that point to the particular one of the documents. | 0.592379 |
7,752,417 | 1 | 2 | 1. A computer-implemented method, comprising, during execution of a first application: receiving, on behalf of said first application, a first memory request directed to a first virtual memory address; translating said first virtual memory address to a corresponding first physical address according to a first address translation technique; analyzing performance of said first application; dynamically selecting a second address translation technique for translating virtual memory addresses to corresponding physical memory addresses on behalf of said first application; and subsequent to said selecting a second address translation technique, receiving, on behalf of said first application, a second memory request directed to a second virtual memory address, and translating said second virtual memory address to a corresponding second physical address according to said second address translation technique; wherein said dynamically selecting a second address translation technique is dependent, at least in part, on a user policy and on results of said analyzing; and wherein said dynamically selecting and said translating according to said second address translation technique are performed transparently to said first application. | 1. A computer-implemented method, comprising, during execution of a first application: receiving, on behalf of said first application, a first memory request directed to a first virtual memory address; translating said first virtual memory address to a corresponding first physical address according to a first address translation technique; analyzing performance of said first application; dynamically selecting a second address translation technique for translating virtual memory addresses to corresponding physical memory addresses on behalf of said first application; and subsequent to said selecting a second address translation technique, receiving, on behalf of said first application, a second memory request directed to a second virtual memory address, and translating said second virtual memory address to a corresponding second physical address according to said second address translation technique; wherein said dynamically selecting a second address translation technique is dependent, at least in part, on a user policy and on results of said analyzing; and wherein said dynamically selecting and said translating according to said second address translation technique are performed transparently to said first application. 2. The method of claim 1 , further comprising determining said first address translation technique dependent on a predicted distribution of virtual memory addresses to be accessed by said first application. | 0.873775 |
9,245,024 | 10 | 18 | 10. A system for providing content segments to a first resource having a first video, comprising: a processor; and a computer-readable storage medium having encoded thereon a program of instructions executed by the processor, wherein the processor: systematically browses one or more second resources hosting a plurality of online documents, the one or more second resources unaffiliated with the first resource; identifies the first video embedded in an online document of the plurality of online documents; extracts contextual information from the online document; generates a set of criteria based on the extracted contextual information; receives a request for a content segment from the first resource; selects a responsive content segment based on the set of criteria; and provides to the first resource the responsive content segment to be displayed with the first video. | 10. A system for providing content segments to a first resource having a first video, comprising: a processor; and a computer-readable storage medium having encoded thereon a program of instructions executed by the processor, wherein the processor: systematically browses one or more second resources hosting a plurality of online documents, the one or more second resources unaffiliated with the first resource; identifies the first video embedded in an online document of the plurality of online documents; extracts contextual information from the online document; generates a set of criteria based on the extracted contextual information; receives a request for a content segment from the first resource; selects a responsive content segment based on the set of criteria; and provides to the first resource the responsive content segment to be displayed with the first video. 18. The system of claim 10 , wherein the processor further: extracts a video identification from the first video embedded in a second resource of the one or more second resources; compares the video identification with a corresponding video identification of the first video displayed at the first resource; and when the video identification matches the corresponding video identification, serves the responsive content segment. | 0.5 |
8,978,140 | 6 | 8 | 6. The computer-implemented method of claim 5 , further comprising configuring the data mining module, wherein configuring the data mining module includes defining a characteristic indicative of a targeted attribute, and configuring the data mining module to identify requests having the attribute. | 6. The computer-implemented method of claim 5 , further comprising configuring the data mining module, wherein configuring the data mining module includes defining a characteristic indicative of a targeted attribute, and configuring the data mining module to identify requests having the attribute. 8. The computer-implemented method of claim 6 , wherein the attribute is a type of HTTP request header data. | 0.635135 |
8,152,636 | 8 | 9 | 8. The party kit of claim 6 , wherein the storage medium includes a link to an interactive display configured to view the different themes and register for a theme party, each having the one or more animated characters associated therewith. | 8. The party kit of claim 6 , wherein the storage medium includes a link to an interactive display configured to view the different themes and register for a theme party, each having the one or more animated characters associated therewith. 9. The party kit of claim 8 , wherein the interactive display is a plurality of web pages including at least one of: a home page, a theme page, a party experience page, a party package page, an explanation page and a registration page. | 0.5 |
8,645,679 | 1 | 4 | 1. A method for merging security constraints associated with an application when using security annotations, comprising: during application deployment, generating a list of role names; during application runtime in an application server, retrieving security constraints for the application from a plurality of sources, the sources including dynamic and static security annotations, and a deployment descriptor; and using the list of role names and the security constraints retrieved from the plurality of sources to generate a set of merged security constraints having an order of precedence. | 1. A method for merging security constraints associated with an application when using security annotations, comprising: during application deployment, generating a list of role names; during application runtime in an application server, retrieving security constraints for the application from a plurality of sources, the sources including dynamic and static security annotations, and a deployment descriptor; and using the list of role names and the security constraints retrieved from the plurality of sources to generate a set of merged security constraints having an order of precedence. 4. The method as described in claim 1 wherein the step of using the list of role names and the security constraints retrieved comprises: merging one or more dynamic security annotations with one or more static security annotations to generate a set of runtime constraints; and merging one or more security constraints from the deployment descriptor with the set of runtime constraints and the list of roles to generate the set of merged security constraints. | 0.5 |
8,930,380 | 16 | 20 | 16. A computer program product embodied in a non-transitory computer readable storage medium and comprising computer instructions for: receiving raw data generated at a first remote device; calculating at least one confidence measure indicating a level of correspondence between the raw data and at least one parser rule included in an existing set of parser rules; determining that the raw data does not conform to any parser rules included in the existing set of parser rules based at least in part on a determination that the at least one confidence measure does not meet a predefined threshold; in response to the determination that the raw data does not conform to any parser rules included in the existing set, obtaining structure information associated with the raw data, wherein obtaining the structure information includes at least one of: determining a first segment of the raw data that is populated by a repeating static value; and determining a second segment of the raw data that is populated by variable values included in a set comprising a plurality of such variable values; automatically generating at least one new parser rule based at least in part on the structure information; parsing at least a portion of the raw data using the at least one new parser rule; receiving additional raw data generated at a second remote device, wherein the additional raw data generated at the second remote device has an unspecified source; and recommending to an administrator of the second remote device that the source of the additional raw data be set to a name provided by an administrator of the first remote device. | 16. A computer program product embodied in a non-transitory computer readable storage medium and comprising computer instructions for: receiving raw data generated at a first remote device; calculating at least one confidence measure indicating a level of correspondence between the raw data and at least one parser rule included in an existing set of parser rules; determining that the raw data does not conform to any parser rules included in the existing set of parser rules based at least in part on a determination that the at least one confidence measure does not meet a predefined threshold; in response to the determination that the raw data does not conform to any parser rules included in the existing set, obtaining structure information associated with the raw data, wherein obtaining the structure information includes at least one of: determining a first segment of the raw data that is populated by a repeating static value; and determining a second segment of the raw data that is populated by variable values included in a set comprising a plurality of such variable values; automatically generating at least one new parser rule based at least in part on the structure information; parsing at least a portion of the raw data using the at least one new parser rule; receiving additional raw data generated at a second remote device, wherein the additional raw data generated at the second remote device has an unspecified source; and recommending to an administrator of the second remote device that the source of the additional raw data be set to a name provided by an administrator of the first remote device. 20. The computer program product of claim 16 further comprising computer instructions for asking an administrator of the first remote device to provide a name of a source of the raw data and wherein the processor is further configured to associate the name with the generated parser rule. | 0.5 |
9,658,931 | 1 | 7 | 1. A computer system for testing a remote system, the computer system comprising: a memory unit that stores instructions; and at least one processing unit that executes the instructions to: receive a representation of a graphical user interface of the remote system; and control a flow of execution based on a testing script, the flow of execution including: search the received representation of the remote system graphical user interface for a graphical element based on an image analysis; and responsive to a result of searching the received representation of the remote system graphical user interface for the graphical element, automatically provide a signal through a communications channel to execute an emulated user input action on the remote system graphical user interface, wherein the input action is specified by a specific script command in the testing script. | 1. A computer system for testing a remote system, the computer system comprising: a memory unit that stores instructions; and at least one processing unit that executes the instructions to: receive a representation of a graphical user interface of the remote system; and control a flow of execution based on a testing script, the flow of execution including: search the received representation of the remote system graphical user interface for a graphical element based on an image analysis; and responsive to a result of searching the received representation of the remote system graphical user interface for the graphical element, automatically provide a signal through a communications channel to execute an emulated user input action on the remote system graphical user interface, wherein the input action is specified by a specific script command in the testing script. 7. The computer system of claim 1 , wherein the at least one processing unit further executes the instructions to: determine a location of the graphical element when a presence of the graphical element is found within the received representation of the remote system graphical user interface. | 0.681917 |
8,832,151 | 17 | 22 | 17. A computer-implemented system, comprising: memory configured to store a container document; and at least one hardware processor interoperably coupled to the memory and configured to: establish a relationship between a partner and a hosted server system based on a received request from the partner; receive a request from a partner administrator to customize a container document to provide to a partner end user, the container document including a first level of content and configurations selected by the partner administrator; receive an identification of the partner end user with access to the container document from the partner administrator; serve a customized container document to the partner end user; and receive a request from the partner end user to customize the container document. | 17. A computer-implemented system, comprising: memory configured to store a container document; and at least one hardware processor interoperably coupled to the memory and configured to: establish a relationship between a partner and a hosted server system based on a received request from the partner; receive a request from a partner administrator to customize a container document to provide to a partner end user, the container document including a first level of content and configurations selected by the partner administrator; receive an identification of the partner end user with access to the container document from the partner administrator; serve a customized container document to the partner end user; and receive a request from the partner end user to customize the container document. 22. The system of claim 17 , wherein the partner administrator can configure the container document through a web application. | 0.798077 |
8,635,223 | 22 | 23 | 22. A method for providing a classification suggestion for a document, comprising the steps of: maintaining a corpus of documents comprising reference documents each associated with a classification and uncoded documents; generating a cluster of uncoded documents; determining a neighborhood of reference documents for at least one of the uncoded documents in the cluster; determining a classification of the neighborhood using a classifier; and suggesting the classification of the neighborhood as a suggested classification code for the at least one uncoded document; assigning a further classification code to the at least one uncoded document based on instructions from a user; identifying a difference between the assigned classification code and the suggested classification code; and displaying the difference between the assigned classification code and the suggested classification code, wherein the steps are performed by a suitably programmed computer. | 22. A method for providing a classification suggestion for a document, comprising the steps of: maintaining a corpus of documents comprising reference documents each associated with a classification and uncoded documents; generating a cluster of uncoded documents; determining a neighborhood of reference documents for at least one of the uncoded documents in the cluster; determining a classification of the neighborhood using a classifier; and suggesting the classification of the neighborhood as a suggested classification code for the at least one uncoded document; assigning a further classification code to the at least one uncoded document based on instructions from a user; identifying a difference between the assigned classification code and the suggested classification code; and displaying the difference between the assigned classification code and the suggested classification code, wherein the steps are performed by a suitably programmed computer. 23. The method according to claim 22 , further comprising: marking the at least one uncoded ESI item with a different assigned classification code than the suggested classification code with a visual indicator. | 0.5 |
8,352,467 | 1 | 4 | 1. A method performed by a data processing apparatus, the method comprising: determining one or more trust relationships between a user and one or more entities based on a frequency with which the user visits one or more resources associated with the one or more entities; receiving a search query from the user; identifying one or more resources responsive to the search query, wherein each of the resources is associated with one or more annotation label terms assigned by the one or more entities; determining whether a query label term matches any of the one or more annotation label terms; identifying, for each of the one or more annotation label terms matching the query label term, a trust rank of the entity that associated the annotation label term with the resource, each trust rank indicating a level of trust for annotation label terms that are assigned by the entity, and each trust rank being based on the determined one or more trust relationships that are based on the frequency with which the user visits the one or more resources; determining a relevance score of each of one or more resources that have the annotation label term based on the respective trust rank, the relevance score indicating a degree of relevance between the respective resource and the query term; ranking each of the one or more resources based on the respective relevance scores; and providing the ranking. | 1. A method performed by a data processing apparatus, the method comprising: determining one or more trust relationships between a user and one or more entities based on a frequency with which the user visits one or more resources associated with the one or more entities; receiving a search query from the user; identifying one or more resources responsive to the search query, wherein each of the resources is associated with one or more annotation label terms assigned by the one or more entities; determining whether a query label term matches any of the one or more annotation label terms; identifying, for each of the one or more annotation label terms matching the query label term, a trust rank of the entity that associated the annotation label term with the resource, each trust rank indicating a level of trust for annotation label terms that are assigned by the entity, and each trust rank being based on the determined one or more trust relationships that are based on the frequency with which the user visits the one or more resources; determining a relevance score of each of one or more resources that have the annotation label term based on the respective trust rank, the relevance score indicating a degree of relevance between the respective resource and the query term; ranking each of the one or more resources based on the respective relevance scores; and providing the ranking. 4. The method of claim 1 , wherein: identifying, for each of the one or more annotation label terms matching the query label term, a trust rank of the entity that associated the annotation label term with the resource, each trust rank indicating a level of trust for annotation label terms that are associated by the entity, and each trust rank being based on the determined one or more trust relationships that are based on the frequency with which the user visits the one or more resources comprises: calculating an aggregated trust rank based on two or more trust ranks; and determining a relevance score of each of one or more resources that have the annotation label term based on the respective trust rank, the relevance score indicating a degree of relevance between the respective resource and the query term comprises: determining the relevance score of each of the one or more resources that have the annotation label term based on the respective aggregated trust rank. | 0.5 |
8,819,045 | 1 | 5 | 1. A method for case insensitive searching of a variable width encoded pattern in a block of text, the method comprising: (a) determining, by a device, for each character in a pattern for which to search for a match within a block of text, a corresponding lower case Unicode value, the pattern comprising variable-width encoded characters; (b) establishing, by the device, an index table of jump values for the pattern, the index table comprising a hash to each corresponding lower case Unicode value that identifies a number of byte lengths for the corresponding character; (c) jumping, by the device responsive to the index table of jump values, a pointer to the block of text to a pivot element in the block of text based on a byte length of the pattern and the byte length of a last character of the pattern; and (d) comparing, by the device, a lower case Unicode value of the pivot element to the corresponding lower case Unicode value of the character of the last character of the pattern. | 1. A method for case insensitive searching of a variable width encoded pattern in a block of text, the method comprising: (a) determining, by a device, for each character in a pattern for which to search for a match within a block of text, a corresponding lower case Unicode value, the pattern comprising variable-width encoded characters; (b) establishing, by the device, an index table of jump values for the pattern, the index table comprising a hash to each corresponding lower case Unicode value that identifies a number of byte lengths for the corresponding character; (c) jumping, by the device responsive to the index table of jump values, a pointer to the block of text to a pivot element in the block of text based on a byte length of the pattern and the byte length of a last character of the pattern; and (d) comparing, by the device, a lower case Unicode value of the pivot element to the corresponding lower case Unicode value of the character of the last character of the pattern. 5. The method of claim 1 , wherein step (c) further comprises setting, by the device, the pointer at a beginning of the block of text. | 0.749064 |
7,921,133 | 7 | 10 | 7. A method for handling a free text search query, comprising: enabling a particular grid component within a grid environment, wherein the grid environment comprises a plurality of computing systems each comprising at least one resource communicatively connected over a network to share each said at least one resource through a plurality of web services implemented within a web services layer extended by an open grid services infrastructure atop a grid service layer comprising at least one grid service implemented within the open grid services architecture enabling interfacing with each at least one resource, wherein the particular grid component comprises at least one of said at least one resource; specifying, using a processor, the particular grid component to interpret a meaning of a particular aspect of at least one of a plurality of specifications within at least one search query distributed by at least one search service from among the at least one grid service; responsive to receiving a free text string with a particular plurality of specifications for a particular search query from the at least one search service, interpreting, using the processor, by the particular component the meaning of the particular aspect of at least one specification within the particular plurality of specifications within the free text string; and returning, using the processor, from the particular grid component the interpreted meaning to the search service to synthesize with other interpreted meanings for other aspects of the free text string returned to the search service by other grid components from among the plurality of grid components. | 7. A method for handling a free text search query, comprising: enabling a particular grid component within a grid environment, wherein the grid environment comprises a plurality of computing systems each comprising at least one resource communicatively connected over a network to share each said at least one resource through a plurality of web services implemented within a web services layer extended by an open grid services infrastructure atop a grid service layer comprising at least one grid service implemented within the open grid services architecture enabling interfacing with each at least one resource, wherein the particular grid component comprises at least one of said at least one resource; specifying, using a processor, the particular grid component to interpret a meaning of a particular aspect of at least one of a plurality of specifications within at least one search query distributed by at least one search service from among the at least one grid service; responsive to receiving a free text string with a particular plurality of specifications for a particular search query from the at least one search service, interpreting, using the processor, by the particular component the meaning of the particular aspect of at least one specification within the particular plurality of specifications within the free text string; and returning, using the processor, from the particular grid component the interpreted meaning to the search service to synthesize with other interpreted meanings for other aspects of the free text string returned to the search service by other grid components from among the plurality of grid components. 10. The method according to claim 7 , wherein specifying the particular grid component to interpret a meaning of a particular aspect of at least one of a plurality of specifications within at least one search query distributed by at least one search service from among the at least one grid service further comprises specifying the particular grid component to interpret the aspect of a color by detecting at least one word indicating a particular color and returning an interpreted meaning comprising a color family for the particular color. | 0.53833 |
8,010,527 | 1 | 25 | 1. A method implemented within a computer system comprising a central processing unit (CPU) and a random access memory (RAM), the method comprising: a. utilizing the CPU and RAM to obtain a history of online activities of a user; b. utilizing the CPU and RAM to receive user preference information from the user; c. utilizing the CPU and RAM to identify a plurality of online information resources linking to online resources viewed by the user, wherein each of the plurality of online information resources is associated with an online information source; d. utilizing the CPU and RAM to generate a plurality of relevance scores for each of the identified online information resource; and e. using the generated plurality of relevance scores to generate a ranked list of recommended online information sources, wherein a rank of each online information source is determined by aggregating at least some of the plurality of relevance scores of the identified online information resources according to the received user preference information, wherein: the ranked list comprises links to online sources that are not in the history of the online activities of the user, the online information resource is a blog post, the online resource viewed by the user is a visited web page, the online information source is a source blog web page, and the online source is a related web feed. | 1. A method implemented within a computer system comprising a central processing unit (CPU) and a random access memory (RAM), the method comprising: a. utilizing the CPU and RAM to obtain a history of online activities of a user; b. utilizing the CPU and RAM to receive user preference information from the user; c. utilizing the CPU and RAM to identify a plurality of online information resources linking to online resources viewed by the user, wherein each of the plurality of online information resources is associated with an online information source; d. utilizing the CPU and RAM to generate a plurality of relevance scores for each of the identified online information resource; and e. using the generated plurality of relevance scores to generate a ranked list of recommended online information sources, wherein a rank of each online information source is determined by aggregating at least some of the plurality of relevance scores of the identified online information resources according to the received user preference information, wherein: the ranked list comprises links to online sources that are not in the history of the online activities of the user, the online information resource is a blog post, the online resource viewed by the user is a visited web page, the online information source is a source blog web page, and the online source is a related web feed. 25. The method of claim 1 , wherein obtaining a history of online activities of a user further comprises obtaining a list of online resources viewed by the user. | 0.768012 |
9,552,349 | 2 | 11 | 2. The method of claim 1 , wherein said dictionary hash table is pre-created prior to obtaining said candidate word, further comprising the step of obtaining said dictionary hash table having entries in a dictionary of known correctly spelled words and wherein said dictionary hash table and said at least one variant dictionary hash table are based on said dictionary and are comprised of at least one distance one variation for each of said entries, wherein said distance one variation comprises one or more of a deletion, insertion, replacement, and transposition operation performed on said entries; and wherein the step of evaluating said lookup variants utilizing said at least one variant dictionary hash table further comprises the step of evaluating one or more distance one variants utilizing said at least one variant dictionary hash table. | 2. The method of claim 1 , wherein said dictionary hash table is pre-created prior to obtaining said candidate word, further comprising the step of obtaining said dictionary hash table having entries in a dictionary of known correctly spelled words and wherein said dictionary hash table and said at least one variant dictionary hash table are based on said dictionary and are comprised of at least one distance one variation for each of said entries, wherein said distance one variation comprises one or more of a deletion, insertion, replacement, and transposition operation performed on said entries; and wherein the step of evaluating said lookup variants utilizing said at least one variant dictionary hash table further comprises the step of evaluating one or more distance one variants utilizing said at least one variant dictionary hash table. 11. The method of claim 2 , further comprising the steps of generating all single character deletions of said at least one candidate word and testing said single character deletions against transposition and deletion hash tables, and accumulating matches. | 0.718543 |
8,620,022 | 14 | 16 | 14. A system for controlling an event structure, the system comprising: a multiple-person interaction primitives recognizing unit to recognize multiple-person interaction primitives from an image, which is displayed on a display screen; and a multi-thread parser to compose an event by inference based on temporal relations using the multiple-person interaction primitives, and to determine a final event by eliminating an unnecessary event from the composed event and adding a new event in the composed event after the unnecessary event is eliminated. | 14. A system for controlling an event structure, the system comprising: a multiple-person interaction primitives recognizing unit to recognize multiple-person interaction primitives from an image, which is displayed on a display screen; and a multi-thread parser to compose an event by inference based on temporal relations using the multiple-person interaction primitives, and to determine a final event by eliminating an unnecessary event from the composed event and adding a new event in the composed event after the unnecessary event is eliminated. 16. The system of claim 14 , wherein the multi-thread parser eliminates the unnecessary event using an expansion of an Early-Stolcke parser model including the temporal relations. | 0.761968 |
10,152,965 | 11 | 12 | 11. The system of claim 7 , wherein the operations further comprise: in response to updating a pronunciation dictionary to include the first phonetic representation, increasing a global counter associated with the first phonetic representation. | 11. The system of claim 7 , wherein the operations further comprise: in response to updating a pronunciation dictionary to include the first phonetic representation, increasing a global counter associated with the first phonetic representation. 12. The system of claim 11 , wherein the operations further comprise: determining that the global counter associated with the first phonetic representation satisfies a predetermined threshold; and in response to determining that the global counter associated with the first phonetic pronunciation has exceeded a predetermined threshold, updating a pronunciation dictionary entry in a global pronunciation dictionary that is associated with the entity name to include the first phonetic representation associated with the different transcription. | 0.5 |
9,501,469 | 19 | 30 | 19. A non-transitory computer-readable medium comprising computer program instructions, wherein the computer program instructions are executable by a computer processor to perform a 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. | 19. A non-transitory computer-readable medium comprising computer program instructions, wherein the computer program instructions are executable by a computer processor to perform a 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. 30. The non-transitory computer-readable medium of claim 19 , wherein the first part of the sentence comprises the subject, and wherein the second part of the sentence comprises the object. | 0.746649 |
6,023,578 | 17 | 32 | 17. A computer program product for generating an object oriented application for an object oriented environment, said object oriented environment comprising a programming model and a data model, said computer program product comprising: a computer readable storage medium having computer readable code means embodied in said medium, said computer readable code means comprising: computer instruction means for generating a computer program design for said object oriented model application using a modeling tool; and computer instruction means for mapping the modeling tool generated computer program design to the data model of said object oriented environment to thereby create metadata in said data model wherein said computer instruction means for mapping comprises computer instruction means for defining a first package, wherein said first package partitions the computer program design into at least two parts without requiring reference to model semantics. | 17. A computer program product for generating an object oriented application for an object oriented environment, said object oriented environment comprising a programming model and a data model, said computer program product comprising: a computer readable storage medium having computer readable code means embodied in said medium, said computer readable code means comprising: computer instruction means for generating a computer program design for said object oriented model application using a modeling tool; and computer instruction means for mapping the modeling tool generated computer program design to the data model of said object oriented environment to thereby create metadata in said data model wherein said computer instruction means for mapping comprises computer instruction means for defining a first package, wherein said first package partitions the computer program design into at least two parts without requiring reference to model semantics. 32. The computer program product for generating according to claim 17, wherein said computer readable program code means for mapping further comprises computer readable program code means for mapping the first package to at least one of a file and a module in the data model. | 0.813179 |
7,640,531 | 18 | 22 | 18. A method of managing application development, comprising: maintaining, in a first document, a first list of interactions between a plurality of applications; maintaining, in a second document, a second list of interactions within one or more of the plurality of applications; maintaining, in a third document, a third list of existing interactions; providing a tool that communicates with the first, the second, and the third documents; using the tool to count a number of business operation points based on the interactions in the first list and the second list, the tool monitors the third list and reduces the count for interactions in the first list and the second list having associated existing interactions in the third list, wherein the first list of interactions and the second list of interactions include a plurality of types of interactions, the plurality of types of interactions includes two or more of group consisting of internal logical files types of interactions, external interfaces files types of interactions, external inputs types of interactions, external outputs types of interactions, and external queries types of interactions, and wherein the business operation points include interactions between applications and interactions within an application between components of the application, but do not include the components of the applications themselves or interactions with external non-application entities; measuring hours expended developing the application; calculating a productivity metric for developing the application based on a count of business operation points delivered by an outsourcing firm developing the application and the hours expended by the outsourcing firm developing the application; calculating a productivity rate of change based on the productivity metric of the outsourcing firm for developing the one or more applications and a productivity metric of the outsourcing firm for developing a previous one or more applications; and designing incentive packages for the outsourcing firm based on the productivity rate of change. | 18. A method of managing application development, comprising: maintaining, in a first document, a first list of interactions between a plurality of applications; maintaining, in a second document, a second list of interactions within one or more of the plurality of applications; maintaining, in a third document, a third list of existing interactions; providing a tool that communicates with the first, the second, and the third documents; using the tool to count a number of business operation points based on the interactions in the first list and the second list, the tool monitors the third list and reduces the count for interactions in the first list and the second list having associated existing interactions in the third list, wherein the first list of interactions and the second list of interactions include a plurality of types of interactions, the plurality of types of interactions includes two or more of group consisting of internal logical files types of interactions, external interfaces files types of interactions, external inputs types of interactions, external outputs types of interactions, and external queries types of interactions, and wherein the business operation points include interactions between applications and interactions within an application between components of the application, but do not include the components of the applications themselves or interactions with external non-application entities; measuring hours expended developing the application; calculating a productivity metric for developing the application based on a count of business operation points delivered by an outsourcing firm developing the application and the hours expended by the outsourcing firm developing the application; calculating a productivity rate of change based on the productivity metric of the outsourcing firm for developing the one or more applications and a productivity metric of the outsourcing firm for developing a previous one or more applications; and designing incentive packages for the outsourcing firm based on the productivity rate of change. 22. The method of claim 18 wherein the second document is further defined as an application model document and wherein the second list of interactions is further defined as one or more sequence diagrams within the application model document. | 0.518 |
7,486,294 | 1 | 22 | 1. In a computing environment, a computer-implemented system for composing computer-displayable graphics, the system comprising: a high-level compositing and animation engine and a low-level engine, the high-level engine being instantiated on a per-application basis and the low-level engine servicing requests from multiple applications; a markup language, the markup language comprising graphics instructions, the graphics instructions comprising a string format and an object notation, the object notation comprising graphics elements from a graphics element class; a graphics object model comprising: a base class visual object which is a container for graphical content, which provides base functionality for other visual types and from which other visual types derive, a container visual object which is a container for visuals and which may contain other container visual objects, a drawing visual object which is a container for graphical content, and a graphics element class, the element class comprising a shape class, an image class, a video class, and a canvas class, and the element class being integrated with a general property system; a type converter, the type converter configured to convert a graphics instruction in string format to a visual application programming interface (API) object; a parser/translator, the parser/translator configured to a) interpret graphics instructions, the graphics instructions comprising direct code calls, object model code calls, and graphics instructions written using the markup language, b) access the type converter, the type converter configured to convert a graphics instruction in string format to a visual API object, and c) interpret the markup code and, upon interpreting the markup code, add elements of the graphics elements class to an element tree; a presenter system, the presenter system configured to translate graphics element trees into calls to a visual API; a visual API, the visual API configured to a) interface with the presenter system, interface with the parser/translator, and interface with direct code calls from programming languages, and b) in response to requests from the presenter system, the parser/translator, creates scene objects within a scene graph; and a display interface operable to facilitate display of the graphics objects within the scene graph. | 1. In a computing environment, a computer-implemented system for composing computer-displayable graphics, the system comprising: a high-level compositing and animation engine and a low-level engine, the high-level engine being instantiated on a per-application basis and the low-level engine servicing requests from multiple applications; a markup language, the markup language comprising graphics instructions, the graphics instructions comprising a string format and an object notation, the object notation comprising graphics elements from a graphics element class; a graphics object model comprising: a base class visual object which is a container for graphical content, which provides base functionality for other visual types and from which other visual types derive, a container visual object which is a container for visuals and which may contain other container visual objects, a drawing visual object which is a container for graphical content, and a graphics element class, the element class comprising a shape class, an image class, a video class, and a canvas class, and the element class being integrated with a general property system; a type converter, the type converter configured to convert a graphics instruction in string format to a visual application programming interface (API) object; a parser/translator, the parser/translator configured to a) interpret graphics instructions, the graphics instructions comprising direct code calls, object model code calls, and graphics instructions written using the markup language, b) access the type converter, the type converter configured to convert a graphics instruction in string format to a visual API object, and c) interpret the markup code and, upon interpreting the markup code, add elements of the graphics elements class to an element tree; a presenter system, the presenter system configured to translate graphics element trees into calls to a visual API; a visual API, the visual API configured to a) interface with the presenter system, interface with the parser/translator, and interface with direct code calls from programming languages, and b) in response to requests from the presenter system, the parser/translator, creates scene objects within a scene graph; and a display interface operable to facilitate display of the graphics objects within the scene graph. 22. The system of claim 1 wherein one of the graphics elements includes clipping property data. | 0.780093 |
9,519,682 | 13 | 16 | 13. A non-transitory computer-readable storage device having computer-executable instructions stored thereon such that when the storage device is accessed by a computing device, the instructions are executable by the computing device to perform actions, comprising: identifying, for a given action, a trusted group of user accounts from a plurality of user accounts using a respective trustworthiness score for the given action assigned to each user account of the plurality, wherein the given action refers to an online activity that is performed by one or more users associated with respective user accounts, each user account's trustworthiness score being determined using inputs received from the each user account for the given action, the trustworthiness score being used to identify the trusted group of user accounts whose input is to be used to classify an item, wherein the item refers to an article of the internet that can have an action performed on it, and to identify other user accounts whose input is to be excluded from classifying the item the identifying comprising generating an initial trustworthiness score for a user account of the plurality using a trained trustworthiness classifier and a feature set about the user account, the trained trustworthiness classifier comprising a number of machine-implemented algorithms used to evolve behaviors based on input data, the feature set comprising online user behavioral features and static profile features about the user account, wherein the online user behavioral features comprise online activity features and the static profile features comprise user registration features the initial trustworthiness score for the user account is used at least initially to determine whether or not to include the user account in the trusted group of user accounts for the given action; monitoring inputs for the given action and about an item, the inputs about the item from the one or more trusted groups for the given action are used to classify the item as one of spam and non-spam, such that any input about the item from other than the trusted group of user accounts formed for the given action is excluded from being used to classify the item; and evolving the trusted group based on modified trustworthiness scores of the plurality of user accounts for the given action, each modified trustworthiness score is determined, in part, by a comparison of an input about the item from a corresponding user account and inputs about the item from other user accounts in the plurality of user accounts, wherein evolving the trusted group further comprises at least one of moving at least one user account into the trusted group that previously was not in the trusted group and moving at least one user account out of the trusted group that was previously in the trusted group. | 13. A non-transitory computer-readable storage device having computer-executable instructions stored thereon such that when the storage device is accessed by a computing device, the instructions are executable by the computing device to perform actions, comprising: identifying, for a given action, a trusted group of user accounts from a plurality of user accounts using a respective trustworthiness score for the given action assigned to each user account of the plurality, wherein the given action refers to an online activity that is performed by one or more users associated with respective user accounts, each user account's trustworthiness score being determined using inputs received from the each user account for the given action, the trustworthiness score being used to identify the trusted group of user accounts whose input is to be used to classify an item, wherein the item refers to an article of the internet that can have an action performed on it, and to identify other user accounts whose input is to be excluded from classifying the item the identifying comprising generating an initial trustworthiness score for a user account of the plurality using a trained trustworthiness classifier and a feature set about the user account, the trained trustworthiness classifier comprising a number of machine-implemented algorithms used to evolve behaviors based on input data, the feature set comprising online user behavioral features and static profile features about the user account, wherein the online user behavioral features comprise online activity features and the static profile features comprise user registration features the initial trustworthiness score for the user account is used at least initially to determine whether or not to include the user account in the trusted group of user accounts for the given action; monitoring inputs for the given action and about an item, the inputs about the item from the one or more trusted groups for the given action are used to classify the item as one of spam and non-spam, such that any input about the item from other than the trusted group of user accounts formed for the given action is excluded from being used to classify the item; and evolving the trusted group based on modified trustworthiness scores of the plurality of user accounts for the given action, each modified trustworthiness score is determined, in part, by a comparison of an input about the item from a corresponding user account and inputs about the item from other user accounts in the plurality of user accounts, wherein evolving the trusted group further comprises at least one of moving at least one user account into the trusted group that previously was not in the trusted group and moving at least one user account out of the trusted group that was previously in the trusted group. 16. The non-transitory computer-readable storage device of claim 13 , wherein the one or more other network devices further enables actions, the actions comprising: modifying the trustworthiness score assigned to each user account, comprising: when input from a given user account matches the input from the other user accounts, increasing a trustworthiness score of the given user account; and decreasing the trustworthiness score of the given user account when input from the given user account does not match the input from the other user accounts. | 0.5 |
8,065,299 | 11 | 14 | 11. A computer-implemented method comprising: receiving and recording, by a server digital processing system (DPS), a first query received from a plurality of independent users during a search session; providing, by the server DPS, one or more search results to the independent users in response to the query during their respective search sessions, wherein each independent user is enabled to pick at least one of the provided search results; receiving and recording, by the server DPS, a plurality of search results picked by the independent users during their respective search sessions; receiving and recording, by the server DPS, a plurality of second queries received from the independent users during their respective search sessions; receiving, by the server DPS, the first query from a user; determining, by the server DPS, a first topic associated with the first query; correlating, by the server DPS, the first query with at least one of the recorded second queries to form a query-to-query association and a recorded picked search result and to form a query-to-pick association in order to determine a second topic related to the first topic; and providing, by the server DPS, one or more query suggestions to the user, the one or more query suggestions based upon the determined first and second topics. | 11. A computer-implemented method comprising: receiving and recording, by a server digital processing system (DPS), a first query received from a plurality of independent users during a search session; providing, by the server DPS, one or more search results to the independent users in response to the query during their respective search sessions, wherein each independent user is enabled to pick at least one of the provided search results; receiving and recording, by the server DPS, a plurality of search results picked by the independent users during their respective search sessions; receiving and recording, by the server DPS, a plurality of second queries received from the independent users during their respective search sessions; receiving, by the server DPS, the first query from a user; determining, by the server DPS, a first topic associated with the first query; correlating, by the server DPS, the first query with at least one of the recorded second queries to form a query-to-query association and a recorded picked search result and to form a query-to-pick association in order to determine a second topic related to the first topic; and providing, by the server DPS, one or more query suggestions to the user, the one or more query suggestions based upon the determined first and second topics. 14. The computer-implemented method of claim 11 wherein the evaluation of one or more of the query suggestions as a correct spelling of an erroneously spelled first query is based on criteria selected from the group consisting of textual similarity to the first query, more common than the received first query, issued subsequently to the first query more often than issued prior to the first query, and results in a greater number of user picks than the first query. | 0.5 |
8,549,464 | 9 | 12 | 9. The one or more computer-readable memory devices or storage devices of claim 7 , the acts further comprising: reusing the reusable expression graph by: binding the parameter node to another bindable term comprising a third expression, and evaluating the first expression using the third expression instead of the second expression without rebuilding an entirety of the first expression. | 9. The one or more computer-readable memory devices or storage devices of claim 7 , the acts further comprising: reusing the reusable expression graph by: binding the parameter node to another bindable term comprising a third expression, and evaluating the first expression using the third expression instead of the second expression without rebuilding an entirety of the first expression. 12. The one or more computer-readable memory devices or storage devices of claim 9 , wherein the third expression contains a plurality of hard values. | 0.592391 |
8,869,019 | 9 | 14 | 9. A non-transitory computer-readable medium storing instructions, which when executed by a set of one or more processors, cause the set of processors to perform operations comprising: parsing a set of one or more web pages of a website; generating a first plurality of n-grams based on at least content that is included on the set of one or more web pages, wherein n is at least two; determining a relevancy value for each of the first plurality of n-grams; generating a second plurality of n-grams based on at least removing any of the first plurality of n-grams whose corresponding relevancy value is below a relevancy value threshold; for each one of the second plurality of n-grams, determining whether that one of the second plurality of n-grams is similar to another one of the second plurality of n-grams, generating a third plurality of n-grams based on at least removing any of those second plurality of n-grams that have been determined as being similar to another one of the second plurality of n-grams; for at least one of the third plurality of n-grams, determining whether there is at least one of the set of web pages of the website that that is directed at content regarding that n-gram; and responsive to determining that there is not at least one of the set of web pages of the website that is directed at content regarding the at least one of the third plurality of n-grams, performing the following: automatically creating a web page with content directed at the at least one of the third plurality of n-grams, wherein automatically creating the web page includes, using a same template of the website for the created web page, inserting content into the created web page with existing content of the website that is related to the at least one of the third plurality of n-grams, and adding a title for the created web page based on the at least one of the third plurality of n-grams; providing the created web page in a graphical editor for a user to review the created web page; and creating a set of one or more links to the reviewed and created web page on one or more of the set of web pages of the website so that the created web page is not an orphan web page. | 9. A non-transitory computer-readable medium storing instructions, which when executed by a set of one or more processors, cause the set of processors to perform operations comprising: parsing a set of one or more web pages of a website; generating a first plurality of n-grams based on at least content that is included on the set of one or more web pages, wherein n is at least two; determining a relevancy value for each of the first plurality of n-grams; generating a second plurality of n-grams based on at least removing any of the first plurality of n-grams whose corresponding relevancy value is below a relevancy value threshold; for each one of the second plurality of n-grams, determining whether that one of the second plurality of n-grams is similar to another one of the second plurality of n-grams, generating a third plurality of n-grams based on at least removing any of those second plurality of n-grams that have been determined as being similar to another one of the second plurality of n-grams; for at least one of the third plurality of n-grams, determining whether there is at least one of the set of web pages of the website that that is directed at content regarding that n-gram; and responsive to determining that there is not at least one of the set of web pages of the website that is directed at content regarding the at least one of the third plurality of n-grams, performing the following: automatically creating a web page with content directed at the at least one of the third plurality of n-grams, wherein automatically creating the web page includes, using a same template of the website for the created web page, inserting content into the created web page with existing content of the website that is related to the at least one of the third plurality of n-grams, and adding a title for the created web page based on the at least one of the third plurality of n-grams; providing the created web page in a graphical editor for a user to review the created web page; and creating a set of one or more links to the reviewed and created web page on one or more of the set of web pages of the website so that the created web page is not an orphan web page. 14. The non-transitory computer-readable medium of claim 9 , wherein determining whether there is at least one of the set of web pages of the website that that is directed at content regarding that n-gram includes analyzing the parsed set of web pages of the website including, determining whether that n-gram is included in a URL of one of the parsed set of web pages; determining whether that n-gram is included in a title of one of the parsed set of web pages; and determining whether that n-gram is included with a frequency over a threshold of a web page. | 0.731544 |
8,972,261 | 10 | 17 | 10. A computer-implemented method for voice transcription error reduction, comprising the steps of: obtaining speech utterances from a voice stream and assigning each speech utterance with a transcribed value and a confidence score; identifying as questionable utterances, those utterances with transcription values associated with lower confidence scores; selecting one of the questionable utterances and generating a pool of related utterances comprising the selected questionable utterance and a predetermined number of questionable utterances, wherein the predetermined number of questionable utterances are assigned transcribed values similar to the transcribed value of the selected questionable utterance and are from other voice streams; receiving a common transcribed value for a portion of the questionable utterances in the pool of related utterances; and generating using those transcribed values with high confidence scores and using the common transcribed value, a transcribed message, wherein the steps are performed by a suitably-programmed computer. | 10. A computer-implemented method for voice transcription error reduction, comprising the steps of: obtaining speech utterances from a voice stream and assigning each speech utterance with a transcribed value and a confidence score; identifying as questionable utterances, those utterances with transcription values associated with lower confidence scores; selecting one of the questionable utterances and generating a pool of related utterances comprising the selected questionable utterance and a predetermined number of questionable utterances, wherein the predetermined number of questionable utterances are assigned transcribed values similar to the transcribed value of the selected questionable utterance and are from other voice streams; receiving a common transcribed value for a portion of the questionable utterances in the pool of related utterances; and generating using those transcribed values with high confidence scores and using the common transcribed value, a transcribed message, wherein the steps are performed by a suitably-programmed computer. 17. A method according to claim 10 , further comprising: determining a range of transcribed values; and identifying as the predetermined number of questionable utterances, questionable utterances that are from the other voice streams and that have been assigned transcribed values that fall within the range. | 0.713755 |
8,396,901 | 8 | 9 | 8. The method according to claim 1 , wherein for said identified hierarchical structure, said converting step further comprises: generating an SQL ancestry table to define the inter-relationships among nodes of said identified hierarchical structure of said XML encoded dataset. | 8. The method according to claim 1 , wherein for said identified hierarchical structure, said converting step further comprises: generating an SQL ancestry table to define the inter-relationships among nodes of said identified hierarchical structure of said XML encoded dataset. 9. The method according to claim 8 , wherein said ancestry table includes a descendant node identifier field and an ancestor node identifier field. | 0.5 |
7,480,783 | 5 | 6 | 5. A method according to claim 1 , wherein the index is a multibit index. | 5. A method according to claim 1 , wherein the index is a multibit index. 6. A method according to claim 5 , wherein the multibit index comprises n bits, where n is the maximum number of bits required to represent the misalignment of the word. | 0.5 |
7,483,831 | 30 | 33 | 30. In the device of claim 29 , the further improvement wherein the process includes generating a current candidate frequency-wise gain as a function of a broadband gain adjustment of a prior candidate frequency-wise gain. | 30. In the device of claim 29 , the further improvement wherein the process includes generating a current candidate frequency-wise gain as a function of a broadband gain adjustment of a prior candidate frequency-wise gain. 33. In the device of claim 30 , the further improvement wherein the process includes a noise-minimizing frequency-wise gain adjustment step comprising adjusting the current candidate frequency-wise gain to compensate for a noise spectrum associated with the communications path. | 0.566978 |
10,102,245 | 2 | 4 | 2. The method of claim 1 , wherein searching the one or more indexes of the one or more verticals further comprises: if the first number is greater than a second threshold number, then searching the one or more first indexes, the one or more second indexes, and one or more third indexes, wherein each third index is related to objects of a third object-type different than the first object-type and the second object-type, and wherein the second threshold number is greater than the first threshold number. | 2. The method of claim 1 , wherein searching the one or more indexes of the one or more verticals further comprises: if the first number is greater than a second threshold number, then searching the one or more first indexes, the one or more second indexes, and one or more third indexes, wherein each third index is related to objects of a third object-type different than the first object-type and the second object-type, and wherein the second threshold number is greater than the first threshold number. 4. The method of claim 2 , wherein the first, second, and third object-types are each selected from a group consisting of: a user; a photo; a post; a comment; a message; an event listing; a webpage; an application; a location; a user-profile page; a concept-profile page; a user group; an audio file; a video; an offer; or a coupon. | 0.5 |
9,818,032 | 7 | 8 | 7. The device of claim 1 , wherein assigning respective relevancy scores to the frames includes extracting behavioral indicators of a person who took the video from the video. | 7. The device of claim 1 , wherein assigning respective relevancy scores to the frames includes extracting behavioral indicators of a person who took the video from the video. 8. The device of claim 7 , wherein the behavioral indicators includes at least one of a lack of motion of a camera used to capture the video or an increased zoom of the camera used to capture the video to indicate an increased relevancy. | 0.5 |
9,223,869 | 1 | 6 | 1. A non-transitory, computer-readable storage medium storing computer program code, the computer program code comprising instructions executable by a first device of a first user to perform a method for interacting with a web search infrastructure, the first user having a preference for reading text of a first language, the web search infrastructure gathering both first web text of a second language and second web text of a third language, the method comprising: directing the first device to automatically identify the second language within first search results received from the web search infrastructure, the first search results including at least a portion of the first web text, the automatic identification of the second language being performed using a web browser agent comprising a plurality of translation modules configured to provide auxiliary language translation assistance for different languages, wherein at least a portion of the web browser agent is provided from the web search infrastructure before receiving the first search results; wherein the browser agent is further configured to provide a toolbar on a web browser screen, the toolbar including buttons for enabling translation from the first language to at least the second language; directing the first device to automatically identify the third language within second search results received from the web search infrastructure, the second search results including at least a portion of the second web text; directing the first device to respond to the identification of the second language by offering to the first user via the first device remote language-translation processing services to be conducted by the web search infrastructure; directing the first device to respond to the identification of the third language by offering to the first user via the first device local language-translation processing services to be conducted by the first device; and presenting the translation results on the first device, wherein the translation results are determined by using a conjugate terms database, wherein the translation results include results having meanings that differ from one another due to alternate meanings of a search string in the first language used to produce the first web text of the second language and the second web text of the third language. | 1. A non-transitory, computer-readable storage medium storing computer program code, the computer program code comprising instructions executable by a first device of a first user to perform a method for interacting with a web search infrastructure, the first user having a preference for reading text of a first language, the web search infrastructure gathering both first web text of a second language and second web text of a third language, the method comprising: directing the first device to automatically identify the second language within first search results received from the web search infrastructure, the first search results including at least a portion of the first web text, the automatic identification of the second language being performed using a web browser agent comprising a plurality of translation modules configured to provide auxiliary language translation assistance for different languages, wherein at least a portion of the web browser agent is provided from the web search infrastructure before receiving the first search results; wherein the browser agent is further configured to provide a toolbar on a web browser screen, the toolbar including buttons for enabling translation from the first language to at least the second language; directing the first device to automatically identify the third language within second search results received from the web search infrastructure, the second search results including at least a portion of the second web text; directing the first device to respond to the identification of the second language by offering to the first user via the first device remote language-translation processing services to be conducted by the web search infrastructure; directing the first device to respond to the identification of the third language by offering to the first user via the first device local language-translation processing services to be conducted by the first device; and presenting the translation results on the first device, wherein the translation results are determined by using a conjugate terms database, wherein the translation results include results having meanings that differ from one another due to alternate meanings of a search string in the first language used to produce the first web text of the second language and the second web text of the third language. 6. The non-transitory, computer-readable storage medium of claim 1 , the method further comprising directing the first device to receive second language related data. | 0.662602 |
9,792,027 | 8 | 9 | 8. A computer-implemented method comprising causing output of a sequential content and a visual content, wherein output of the visual content is synchronized to output of the sequential content; causing display within the visual content of an output indicator, wherein the output indicator advances during output of the sequential content and indicates a position within the visual content corresponding to a current output position of the sequential content; causing reception of an input pointer referencing an input position within the visual content that is distinct from the position indicated by the output indicator; and during advancement of the output indicator, causing output of the sequential content to be modified based at least in part on a distance between the position indicated by the output indicator and the input position. | 8. A computer-implemented method comprising causing output of a sequential content and a visual content, wherein output of the visual content is synchronized to output of the sequential content; causing display within the visual content of an output indicator, wherein the output indicator advances during output of the sequential content and indicates a position within the visual content corresponding to a current output position of the sequential content; causing reception of an input pointer referencing an input position within the visual content that is distinct from the position indicated by the output indicator; and during advancement of the output indicator, causing output of the sequential content to be modified based at least in part on a distance between the position indicated by the output indicator and the input position. 9. The computer-implemented method of claim 8 , wherein the distance between the input position and the position indicated by the output indicator is determined based at least in part on a length of time required, at a current output speed, to alter the current output position of the sequential content to correspond to the received input pointer. | 0.80837 |
10,120,933 | 14 | 15 | 14. A device for language processing that represents both sematic and orientation content within a text, the device comprising: circuitry configured to receive ordered data elements representing respective words in a text, the ordered data elements including a first data element and a second data element, which is sequential with the first data element; generate, based on a plurality of semantic classes corresponding respectively to blades of a graded vector space representing clusters of semantic meaning, a first subspace formed within the graded vector space by the first data element, a second subspace within the graded vector space by the second data element, a first set of data elements corresponding to one or more first semantic classes that include the first data element, and a second set of data elements corresponding to one or more second semantic classes that include the second data element; encode, when the one or more first semantic classes is non-degenerate with the one or more second semantic classes, the first data element with respect to the second data element such that the an encoded subspace formed by encoding the first data element with respect to the second data element is oriented with respect to an order of the first data element with respect to the second data element, the encoding being performed by computing one of a left contraction and a right contraction of the first set of data elements with respect to the second set of data elements; compute respective components of a weight distribution of the first data element with respect to the second data element, the components of the weight distribution corresponding to respective ordered pairs for each of the one or more first semantic classes with respect to the one or more second semantic classes; and determine a dominant semantic class of to an ordered sequence of the first data element and the second data element, the dominant semantic class representing an oriented semantic context of the ordered sequence of the first and second data elements, and the dominant semantic class being determined as a semantic class corresponding to a component having a maximum magnitude of the weight distribution, wherein the left contraction is one of a Clifford Algebra left contraction and a Geometric Algebra left contraction, and the right contraction is one of a Clifford Algebra right contraction and a Geometric Algebra right contraction. | 14. A device for language processing that represents both sematic and orientation content within a text, the device comprising: circuitry configured to receive ordered data elements representing respective words in a text, the ordered data elements including a first data element and a second data element, which is sequential with the first data element; generate, based on a plurality of semantic classes corresponding respectively to blades of a graded vector space representing clusters of semantic meaning, a first subspace formed within the graded vector space by the first data element, a second subspace within the graded vector space by the second data element, a first set of data elements corresponding to one or more first semantic classes that include the first data element, and a second set of data elements corresponding to one or more second semantic classes that include the second data element; encode, when the one or more first semantic classes is non-degenerate with the one or more second semantic classes, the first data element with respect to the second data element such that the an encoded subspace formed by encoding the first data element with respect to the second data element is oriented with respect to an order of the first data element with respect to the second data element, the encoding being performed by computing one of a left contraction and a right contraction of the first set of data elements with respect to the second set of data elements; compute respective components of a weight distribution of the first data element with respect to the second data element, the components of the weight distribution corresponding to respective ordered pairs for each of the one or more first semantic classes with respect to the one or more second semantic classes; and determine a dominant semantic class of to an ordered sequence of the first data element and the second data element, the dominant semantic class representing an oriented semantic context of the ordered sequence of the first and second data elements, and the dominant semantic class being determined as a semantic class corresponding to a component having a maximum magnitude of the weight distribution, wherein the left contraction is one of a Clifford Algebra left contraction and a Geometric Algebra left contraction, and the right contraction is one of a Clifford Algebra right contraction and a Geometric Algebra right contraction. 15. The device of claim 14 , wherein the circuitry is further configured to partition the received ordered data elements into the plurality of semantic classes based on a dissimilarity metric, the plurality of semantic classes including the one or more first semantic classes and the one or more second semantic classes. | 0.669421 |
7,689,555 | 10 | 17 | 10. A computer readable storage medium containing a program which, when executed, performs an operation for providing access to data in a database, comprising: receiving, from a requesting entity, a search request for data available through a database abstraction model, wherein the database abstraction model provides: (i) a plurality of logical fields each specifying an access method for accessing data in the database; and (ii) at least one model entity that specifies an identifier in the database used to identify instances of the model entity and further specifies a set of the logical fields used to access data related to the model entity, wherein the identifier comprises a primary key of a table in the database, and wherein the search request specifies the model entity to be searched and at least one search term; identifying, of the set of logical fields related to the model entity, logical fields that are candidates for containing data matching the at least one search term; accessing, for each instance of the model entity in the database, data for each of the identified logical fields using the access method specified for the respective identified logical field; identifying, for each instance, whether the accessed data contains the at least one search term, and if so, adding the identifier for the specific instance of the model entity to a set of search results; and returning the search results to the requesting entity. | 10. A computer readable storage medium containing a program which, when executed, performs an operation for providing access to data in a database, comprising: receiving, from a requesting entity, a search request for data available through a database abstraction model, wherein the database abstraction model provides: (i) a plurality of logical fields each specifying an access method for accessing data in the database; and (ii) at least one model entity that specifies an identifier in the database used to identify instances of the model entity and further specifies a set of the logical fields used to access data related to the model entity, wherein the identifier comprises a primary key of a table in the database, and wherein the search request specifies the model entity to be searched and at least one search term; identifying, of the set of logical fields related to the model entity, logical fields that are candidates for containing data matching the at least one search term; accessing, for each instance of the model entity in the database, data for each of the identified logical fields using the access method specified for the respective identified logical field; identifying, for each instance, whether the accessed data contains the at least one search term, and if so, adding the identifier for the specific instance of the model entity to a set of search results; and returning the search results to the requesting entity. 17. The computer readable storage medium of claim 10 , wherein the operation further comprises: providing a query building interface configured to provide an interface for composing the search request, wherein the query interface includes controls for selecting the model entity to be searched and for specifying the at least one search term. | 0.734472 |
9,239,876 | 2 | 3 | 2. The system of claim 1 further comprising a storage for storing the file and its tag information. | 2. The system of claim 1 further comprising a storage for storing the file and its tag information. 3. The system of claim 2 wherein the storage is Internet-based storage that is remote to the user. | 0.5 |
10,140,270 | 1 | 5 | 1. A method, comprising: detecting a conflict relating to a graphical object in a first version of a digital document and the graphical object in a second version of the digital document; categorizing the conflict as a conflict to be resolved automatically based on an application of conflict resolution logic, wherein the conflict resolution logic comprises: applying at least one conflict rule evaluating a property affecting a presentation of the graphical object, and determining that the conflict modifies the presentation of the graphical object; and automatically resolving the conflict by updating, in a user interface of a productivity service, one or more of the first version of the digital document and the second version of the digital document based on the categorizing. | 1. A method, comprising: detecting a conflict relating to a graphical object in a first version of a digital document and the graphical object in a second version of the digital document; categorizing the conflict as a conflict to be resolved automatically based on an application of conflict resolution logic, wherein the conflict resolution logic comprises: applying at least one conflict rule evaluating a property affecting a presentation of the graphical object, and determining that the conflict modifies the presentation of the graphical object; and automatically resolving the conflict by updating, in a user interface of a productivity service, one or more of the first version of the digital document and the second version of the digital document based on the categorizing. 5. The method of claim 1 , wherein the property affecting the presentation of the graphical object is a size change of the graphical object within the digital document. | 0.522727 |
8,924,871 | 5 | 7 | 5. The GUI evaluation system according to claim 1 , wherein the input/output component group specifying section further includes a large group specifying section for specifying a large group, the large group specification being based on a set of i) a medium group and ii) another medium group close to the medium group, and the input/output component layout determining section determines a variation in arrangement of a small group or an input/output component close to the text display in a medium group included in a large group to evaluate appropriateness of alignment of input/output components. | 5. The GUI evaluation system according to claim 1 , wherein the input/output component group specifying section further includes a large group specifying section for specifying a large group, the large group specification being based on a set of i) a medium group and ii) another medium group close to the medium group, and the input/output component layout determining section determines a variation in arrangement of a small group or an input/output component close to the text display in a medium group included in a large group to evaluate appropriateness of alignment of input/output components. 7. The GUI evaluation system according to claim 5 , wherein the input/output component layout determining section compares positions of placing same-level groups included in a large group to evaluate the appropriateness of the layout between elements. | 0.541971 |
7,613,731 | 39 | 40 | 39. A method for presenting an electronic document to a viewer to facilitate comprehension and control display and speed of delivery, comprising the steps of: assigning an emphasis value to each word in the electronic document using a knowledge database thereby generating a first tagged file of assigned emphasis values for each word; processing the first tagged file in a computer system, including deriving emphasis values for recognizability and comprehensibility and pairing selected words as a cognitive cluster to be treated as one word, to generate a second tagged file of derived emphasis values; processing the second tagged file in the computer system, 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; and presenting the electronic document to the viewer on an electronic display device or printer. | 39. A method for presenting an electronic document to a viewer to facilitate comprehension and control display and speed of delivery, comprising the steps of: assigning an emphasis value to each word in the electronic document using a knowledge database thereby generating a first tagged file of assigned emphasis values for each word; processing the first tagged file in a computer system, including deriving emphasis values for recognizability and comprehensibility and pairing selected words as a cognitive cluster to be treated as one word, to generate a second tagged file of derived emphasis values; processing the second tagged file in the computer system, 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; and presenting the electronic document to the viewer on an electronic display device or printer. 40. The method for presenting an electronic document of claim 39 wherein the knowledge database comprises at least one of a cognitive cluster database, a rarity database, a geographical similarity database, a part of speech database, and a context database. | 0.539427 |
9,412,392 | 47 | 51 | 47. A method for processing voice commands, the method comprising: at a electronic device: receiving user input; in response to receiving user input, recording at least a portion of a voice command; storing contextual information of the electronic device, the contextual information related to a state of the electronic device at a time the at least a portion of the voice command is recorded; after recording the at least a portion of the voice command and storing the contextual information, transmitting the at least a portion of the recorded voice command and the stored contextual information from the electronic device to remote computing equipment; and receiving, from the remote computing equipment, data related to processing the voice command. | 47. A method for processing voice commands, the method comprising: at a electronic device: receiving user input; in response to receiving user input, recording at least a portion of a voice command; storing contextual information of the electronic device, the contextual information related to a state of the electronic device at a time the at least a portion of the voice command is recorded; after recording the at least a portion of the voice command and storing the contextual information, transmitting the at least a portion of the recorded voice command and the stored contextual information from the electronic device to remote computing equipment; and receiving, from the remote computing equipment, data related to processing the voice command. 51. The method of claim 47 , wherein the at least a portion of the recorded voice command and the stored contextual information are transmitted to the remote computing equipment simultaneously. | 0.71194 |
8,768,906 | 1 | 5 | 1. A method comprising: under control of one or more processors configured with executable instructions, receiving a primary keyword inputted by a user and a plurality of requests for retrieving keywords related to the primary keyword received from the user; recording a frequency at which the plurality of requests for retrieving keywords related to the primary keyword are received from the user; selecting a candidate group of related keywords from groups of related keywords corresponding to the primary keyword based on the frequency at which the plurality of requests for retrieving keywords related to the primary keyword are received from the user; and displaying related keywords in the candidate group of related keywords. | 1. A method comprising: under control of one or more processors configured with executable instructions, receiving a primary keyword inputted by a user and a plurality of requests for retrieving keywords related to the primary keyword received from the user; recording a frequency at which the plurality of requests for retrieving keywords related to the primary keyword are received from the user; selecting a candidate group of related keywords from groups of related keywords corresponding to the primary keyword based on the frequency at which the plurality of requests for retrieving keywords related to the primary keyword are received from the user; and displaying related keywords in the candidate group of related keywords. 5. The method as recited in claim 1 , further comprising generating the groups of related keywords, the generating comprising: determining one or more fixed keywords and one or more rotating keywords from the related keywords of the groups; and adding a fixed keyword of the one or more fixed keywords and a rotating keyword of the one or more rotating keywords into at least one group of related keywords. | 0.530093 |
9,271,130 | 12 | 13 | 12. The system of claim 1 , wherein the processor is further configured to respond to a request from the first user to retrieve one or more archived messages. | 12. The system of claim 1 , wherein the processor is further configured to respond to a request from the first user to retrieve one or more archived messages. 13. The system of claim 12 , wherein responding to the request includes transmitting the one or more archived messages to the first user in an email or in a text message. | 0.5 |
7,720,282 | 5 | 8 | 5. A computer-implemented method using a processor to perform the steps of: a) receiving a first image and a second image, at least a portion of the first image representing a first view of a scene and at least a portion of the second image representing a second view of the scene; b) determining a first image intensity function of the first image; c) determining a second image intensity function of the second image; d) determining a disparity map based on the first image and the second image; e) determining a cyclopean image based on the first image and the second image; f) determining an energy function including a matching likelihood, a color likelihood, and a stereo disparity likelihood based on the first image intensity function, the second image intensity function, the disparity map and the cyclopean image; g) optimizing the energy function to determine a segmentation state variable value for a plurality of pixels in a reference image, the reference image including the first image, the second image, or the cyclopean image, the segmentation state variable value indicating a segmentation layer of the pixel, the segmentation layer being a member of a group comprising a foreground layer and a background layer. | 5. A computer-implemented method using a processor to perform the steps of: a) receiving a first image and a second image, at least a portion of the first image representing a first view of a scene and at least a portion of the second image representing a second view of the scene; b) determining a first image intensity function of the first image; c) determining a second image intensity function of the second image; d) determining a disparity map based on the first image and the second image; e) determining a cyclopean image based on the first image and the second image; f) determining an energy function including a matching likelihood, a color likelihood, and a stereo disparity likelihood based on the first image intensity function, the second image intensity function, the disparity map and the cyclopean image; g) optimizing the energy function to determine a segmentation state variable value for a plurality of pixels in a reference image, the reference image including the first image, the second image, or the cyclopean image, the segmentation state variable value indicating a segmentation layer of the pixel, the segmentation layer being a member of a group comprising a foreground layer and a background layer. 8. The computer-implemented method of claim 5 , wherein optimizing includes using one member of a group consisting of layered dynamic programming and layered graph cut. | 0.708333 |
9,747,510 | 1 | 2 | 1. A computer-implemented method to modify a layout of text content having characters rendered on a mobile device, the computer-implemented method comprising: upon detecting the mobile device being reoriented from a first orientation to a second orientation while the mobile device is displaying characters of a first language according to the first orientation, re-rendering the display of the characters of the first language while maintaining a horizontal layout comprising a layout displayed horizontally in rows going from left-to-right and ordered from top-to-bottom, wherein the individual characters of the first language are displayed right-side-up in the first and second orientations; and upon detecting the mobile device being reoriented from the first orientation to the second orientation while the mobile device is displaying characters of a second language according to the first orientation, re-rendering the display of the characters of the second language from the horizontal layout to a vertical layout comprising a layout displayed vertically in columns going from top-to-bottom and ordered from right-to-left, wherein the individual characters of the second language are displayed right-side-up in the first and second orientations. | 1. A computer-implemented method to modify a layout of text content having characters rendered on a mobile device, the computer-implemented method comprising: upon detecting the mobile device being reoriented from a first orientation to a second orientation while the mobile device is displaying characters of a first language according to the first orientation, re-rendering the display of the characters of the first language while maintaining a horizontal layout comprising a layout displayed horizontally in rows going from left-to-right and ordered from top-to-bottom, wherein the individual characters of the first language are displayed right-side-up in the first and second orientations; and upon detecting the mobile device being reoriented from the first orientation to the second orientation while the mobile device is displaying characters of a second language according to the first orientation, re-rendering the display of the characters of the second language from the horizontal layout to a vertical layout comprising a layout displayed vertically in columns going from top-to-bottom and ordered from right-to-left, wherein the individual characters of the second language are displayed right-side-up in the first and second orientations. 2. The computer-implemented method of claim 1 , wherein the mobile device provides a scrolling element used to navigate the text content from top-to-bottom when displayed according to the first orientation and from right-to-left when displayed according to the second orientation. | 0.614325 |
9,064,004 | 1 | 11 | 1. In a computing environment, a method of representing structured data extracted from unstructured data in a fashion which allows querying using relational database concepts, the method comprising: receiving user input specifying one or more database views; receiving user input specifying an information extraction technique, the information extraction technique defining how to extract structured data from unstructured data and the information extraction technique comprising a phrase semantic extraction technique which determines a semantic relationship about one or more words based upon a semantic environment of the one or more words; receiving user input specifying a corpus of data comprising unstructured data, the unstructured data comprising data that is not organized semantically such that it does not have a formalized type and is not in a formal entity level relationship; and applying the extraction technique to the corpus of data to extract structured data from the unstructured data of the corpus of data and to produce the one or more database views including the extracted structured data. | 1. In a computing environment, a method of representing structured data extracted from unstructured data in a fashion which allows querying using relational database concepts, the method comprising: receiving user input specifying one or more database views; receiving user input specifying an information extraction technique, the information extraction technique defining how to extract structured data from unstructured data and the information extraction technique comprising a phrase semantic extraction technique which determines a semantic relationship about one or more words based upon a semantic environment of the one or more words; receiving user input specifying a corpus of data comprising unstructured data, the unstructured data comprising data that is not organized semantically such that it does not have a formalized type and is not in a formal entity level relationship; and applying the extraction technique to the corpus of data to extract structured data from the unstructured data of the corpus of data and to produce the one or more database views including the extracted structured data. 11. The method of claim 1 , wherein the extraction technique comprises entity disambiguation. | 0.592105 |
8,489,615 | 9 | 13 | 9. A non-transitory computer-readable storage medium having stored therein instructions which, when executed by a processor, cause the processor to perform operations comprising: analyzing a past behavior pattern associated with a user to yield an analysis; ranking subjects, logistics, and resources that the user is likely to use for a communication event based at least in part on the analysis to yield a ranked subjects list, a ranked logistics list, and a ranked resources list; and while in the communication event: detecting a current communication context; suggesting predicted resources from the ranked resources list to the user; and updating the analysis based on user interactions with the predicted resources. | 9. A non-transitory computer-readable storage medium having stored therein instructions which, when executed by a processor, cause the processor to perform operations comprising: analyzing a past behavior pattern associated with a user to yield an analysis; ranking subjects, logistics, and resources that the user is likely to use for a communication event based at least in part on the analysis to yield a ranked subjects list, a ranked logistics list, and a ranked resources list; and while in the communication event: detecting a current communication context; suggesting predicted resources from the ranked resources list to the user; and updating the analysis based on user interactions with the predicted resources. 13. The non-transitory computer-readable storage medium of claim 9 , wherein the non-transitory computer-readable storage medium stores additional instructions which result in the operations further comprising: upon clicking on a name of another communication event attendee, displaying resources associated with that attendee. | 0.50753 |
8,910,034 | 2 | 4 | 2. The method as claimed in claim 1 , wherein the fragment object includes a third set of data corresponding to a transformation of the document fragment of the source document, further comprising: (f) transforming the decrypted document fragment of the source document based on the third set of data; and (g) incorporating the transformed decrypted document fragment into the referencing document. | 2. The method as claimed in claim 1 , wherein the fragment object includes a third set of data corresponding to a transformation of the document fragment of the source document, further comprising: (f) transforming the decrypted document fragment of the source document based on the third set of data; and (g) incorporating the transformed decrypted document fragment into the referencing document. 4. The method as claimed in claim 2 , wherein the transformation of the decrypted document fragment of the source document is a summarization of the decrypted document fragment of the source document. | 0.771167 |
8,620,907 | 1 | 4 | 1. One or more tangible computer storage media storing computer-useable instructions that, when used by a computing device, cause the computing device to perform a method comprising: receiving a search query; reformulating the search query to identify one or more atoms used to query a search index, the search index storing a plurality of atoms, the plurality of atoms comprising one or more n-grams, one or more n-tuples, and one or more near n-tuples; identifying an initial set of documents from the search index based on the one or more atoms identified in the reformulated search query; computing preliminary scores for each document in the initial set of documents using both a simplified scoring function and pre-computed scores stored in the search index for document/atom pairs for the one or more atoms and the initial set of documents, wherein a pre-computed score for each document/atom pair represents the importance of an atom extracted from the document, and wherein the simplified scoring function is derived at least in part from ranking features of a full ranking algorithm; selecting a pruned set of documents from the initial set of documents based on the preliminary scores; computing a ranking score for each document in the pruned set of documents using the full ranking algorithm different from the simplified scoring function to provide a set of ranked documents; and providing search results for presentation to an end user based on the set of ranked documents. | 1. One or more tangible computer storage media storing computer-useable instructions that, when used by a computing device, cause the computing device to perform a method comprising: receiving a search query; reformulating the search query to identify one or more atoms used to query a search index, the search index storing a plurality of atoms, the plurality of atoms comprising one or more n-grams, one or more n-tuples, and one or more near n-tuples; identifying an initial set of documents from the search index based on the one or more atoms identified in the reformulated search query; computing preliminary scores for each document in the initial set of documents using both a simplified scoring function and pre-computed scores stored in the search index for document/atom pairs for the one or more atoms and the initial set of documents, wherein a pre-computed score for each document/atom pair represents the importance of an atom extracted from the document, and wherein the simplified scoring function is derived at least in part from ranking features of a full ranking algorithm; selecting a pruned set of documents from the initial set of documents based on the preliminary scores; computing a ranking score for each document in the pruned set of documents using the full ranking algorithm different from the simplified scoring function to provide a set of ranked documents; and providing search results for presentation to an end user based on the set of ranked documents. 4. The one or more computer storage media of claim 1 , wherein the simplified scoring function is based on the full ranking algorithm. | 0.836186 |
9,582,829 | 2 | 3 | 2. The system of claim 1 , wherein to communicate the one or more of the plurality of repayment plans to the user via the user device, the interface is further configured to communicate a highest priority repayment plan of the plurality of payment plans. | 2. The system of claim 1 , wherein to communicate the one or more of the plurality of repayment plans to the user via the user device, the interface is further configured to communicate a highest priority repayment plan of the plurality of payment plans. 3. The system of claim 2 , wherein the interface is further configured to: receive a response to communicating the highest priority repayment plan; and communicate a second highest priority repayment plan of the plurality of payment plans when the response indicates the user rejects the highest priority repayment plan. | 0.5 |
8,862,602 | 1 | 3 | 1. A system comprising: a server computer configured to receive a search query from a client device, the search query comprising a text string; a parsing logic configured to parse the search query using parsing criteria based on one or more dictionaries to determine keywords associated with the search query, wherein the keywords associated with the search query include one or more portions of the text string; the server computer configured to search a database using the keywords associated with the search query and obtain a search result that includes a universal resource locator, wherein the server computer is configured to identify a plurality of the keywords in the universal resource locator, to modify the universal resource locator by inserting previously non-existing space between at least two of the plurality of identified keywords in the universal resource locator, to generate display data comprising the modified universal resource locator having the plurality of identified keywords and the inserted space therebetween, and to send the display data to the client device; wherein the server computer inserts the space in the universal resource locator by inserting a HTML tag between characters of the universal resource locator before sending the display data to the client device, wherein the HTML tag comprises at least one of a div tag, an italics tag, and a span tag. | 1. A system comprising: a server computer configured to receive a search query from a client device, the search query comprising a text string; a parsing logic configured to parse the search query using parsing criteria based on one or more dictionaries to determine keywords associated with the search query, wherein the keywords associated with the search query include one or more portions of the text string; the server computer configured to search a database using the keywords associated with the search query and obtain a search result that includes a universal resource locator, wherein the server computer is configured to identify a plurality of the keywords in the universal resource locator, to modify the universal resource locator by inserting previously non-existing space between at least two of the plurality of identified keywords in the universal resource locator, to generate display data comprising the modified universal resource locator having the plurality of identified keywords and the inserted space therebetween, and to send the display data to the client device; wherein the server computer inserts the space in the universal resource locator by inserting a HTML tag between characters of the universal resource locator before sending the display data to the client device, wherein the HTML tag comprises at least one of a div tag, an italics tag, and a span tag. 3. The system of claim 1 , wherein the space is not a space character. | 0.884488 |
8,977,555 | 6 | 13 | 6. A computer-implemented method comprising: under control of one or more computing devices configured with specific computer-executable instructions, transmitting, to a client device: an audio presentation comprising a first portion and a second portion, wherein the first portion corresponds to a first item and the second portion corresponds to a second item; a first marker corresponding to the first item; and a second marker corresponding to the second item; receiving, from the client device: audio data comprising a user utterance; and marker data comprising the first marker or the second marker; and selecting an item based at least on the marker data or the audio data, wherein the selected item comprises the first item or the second item. | 6. A computer-implemented method comprising: under control of one or more computing devices configured with specific computer-executable instructions, transmitting, to a client device: an audio presentation comprising a first portion and a second portion, wherein the first portion corresponds to a first item and the second portion corresponds to a second item; a first marker corresponding to the first item; and a second marker corresponding to the second item; receiving, from the client device: audio data comprising a user utterance; and marker data comprising the first marker or the second marker; and selecting an item based at least on the marker data or the audio data, wherein the selected item comprises the first item or the second item. 13. The computer-implemented method of claim 6 , wherein the first portion and the second portion are transmitted in separate transmissions. | 0.78125 |
6,083,276 | 1 | 2 | 1. A computer-implemented method for creating and configuring a component-based application, the method comprising the steps of: receiving an application description file containing a definition of a component-based application; generating, in a memory, a representation of a parse tree based on the application description file, the parse tree comprising at least one leaf; for each of a first subset of the leaves, mapping the leaf to a target class; and instantiating a component associated with the target class; and for at least a subset of the instantiated components, invoking at least one method of the component to launch the application. | 1. A computer-implemented method for creating and configuring a component-based application, the method comprising the steps of: receiving an application description file containing a definition of a component-based application; generating, in a memory, a representation of a parse tree based on the application description file, the parse tree comprising at least one leaf; for each of a first subset of the leaves, mapping the leaf to a target class; and instantiating a component associated with the target class; and for at least a subset of the instantiated components, invoking at least one method of the component to launch the application. 2. The method of claim 1, wherein the step of generating a representation of a parse tree comprises parsing the application description file. | 0.795652 |
8,712,775 | 7 | 11 | 7. A non-transitory computer-readable storage medium comprising instructions for: receiving input of a plurality of sample phrases each comprising a plurality of words; representing each sample phrase as a node in a tree; forming a mathematical expression for each pair of nodes in the tree, the mathematical expression comprising a plurality of words found in the sample phrases of the pair of nodes and an indication of whether a word is a common word that occurs in each of the plurality of phrases or an optional word that occurs in some of the plurality of phrases for the pair of nodes; and generating a compact mathematical expression by comparing mathematical expressions, wherein the compact mathematical expression includes each of the plurality of words found in the sample phrases and an indication of whether each of the plurality of words is a common word or an optional word. | 7. A non-transitory computer-readable storage medium comprising instructions for: receiving input of a plurality of sample phrases each comprising a plurality of words; representing each sample phrase as a node in a tree; forming a mathematical expression for each pair of nodes in the tree, the mathematical expression comprising a plurality of words found in the sample phrases of the pair of nodes and an indication of whether a word is a common word that occurs in each of the plurality of phrases or an optional word that occurs in some of the plurality of phrases for the pair of nodes; and generating a compact mathematical expression by comparing mathematical expressions, wherein the compact mathematical expression includes each of the plurality of words found in the sample phrases and an indication of whether each of the plurality of words is a common word or an optional word. 11. The non-transitory computer-readable storage medium of claim 7 comprising instructions for receiving input of further sample phrases. | 0.687215 |
9,069,963 | 1 | 6 | 1. A method of executable computer program inspection, comprising: interrogating simultaneously, with at least one processor, each of a plurality of executable computer program objects stored in a tangible computer readable medium for one or more symbols that are embedded in the objects; identifying dependencies between the symbols based on the presence or absence of the symbols in at least two of the plurality of executable computer program objects; constructing a plurality of component groups, wherein each group of the plurality of component groups include executable computer program objects that share identical symbols, wherein the symbols of each component group are unique to that component group; constructing a directed graph representation of hierarchical relationships between the plurality of component groups based on the identified dependencies between the symbols in the plurality of executable computer program objects, wherein the directed graph includes each component group of the plurality of component groups as a node of the directed graph and a directed edge from a first node of the directed graph to a second node of the directed graph if all the symbols of the component associated with the second node are also present in the component associated with the first node; eliminating a component of the plurality of components that comprises exactly the same symbols as another component of the plurality of components; and storing the hierarchical relationships in a data structure. | 1. A method of executable computer program inspection, comprising: interrogating simultaneously, with at least one processor, each of a plurality of executable computer program objects stored in a tangible computer readable medium for one or more symbols that are embedded in the objects; identifying dependencies between the symbols based on the presence or absence of the symbols in at least two of the plurality of executable computer program objects; constructing a plurality of component groups, wherein each group of the plurality of component groups include executable computer program objects that share identical symbols, wherein the symbols of each component group are unique to that component group; constructing a directed graph representation of hierarchical relationships between the plurality of component groups based on the identified dependencies between the symbols in the plurality of executable computer program objects, wherein the directed graph includes each component group of the plurality of component groups as a node of the directed graph and a directed edge from a first node of the directed graph to a second node of the directed graph if all the symbols of the component associated with the second node are also present in the component associated with the first node; eliminating a component of the plurality of components that comprises exactly the same symbols as another component of the plurality of components; and storing the hierarchical relationships in a data structure. 6. The method of claim 1 , comprising: receiving the plurality of executable computer program objects. | 0.732984 |
9,858,054 | 5 | 6 | 5. The method according to claim 1 , further comprising combining two BCD operations in the first compiler expression into one BCD operation. | 5. The method according to claim 1 , further comprising combining two BCD operations in the first compiler expression into one BCD operation. 6. The method according to claim 5 , wherein combining two BCD operation in the first compiler expression into one BCD operation comprises: if: an operation to perform conversion from packed decimal operands of two consecutive first and second instructions to zoned decimal operands is issued, a right-end byte address of the packed decimal operand of the first instruction is the same as a left-end byte address of the packed decimal operand of the second instruction, and a right-end byte address of a zoned decimal operand of the first instruction obtained by converting the packed decimal operand of the first instruction to the zoned decimal operand is the same as a left-end byte address of a zoned decimal operand of the second instruction obtained by converting the packed decimal operand of the second instruction to the zoned decimal operand, converting an operand obtained by combining the packed decimal operand of the first instruction and the packed decimal operand of the second instruction to an operand obtained by combining the zoned decimal operand of the first instruction and the zoned decimal operand of the second instruction; or if: an operation to perform conversion from zoned decimal operands of two consecutive first and second instructions to packed decimal operands is issued, a right-end byte address of the zoned decimal operand of the first instruction is the same as a left-end byte address of the zoned decimal operand of the second instruction, and a right-end byte address of a packed decimal operand of the first instruction obtained by converting the zoned decimal operand of the first instruction to the packed decimal operand is the same as a left-end byte address of a packed decimal operand of the second instruction obtained by converting the zoned decimal operand of the second instruction to the packed decimal operand, converting an operand obtained by combining the zoned decimal operand of the first instruction and the zoned decimal operand of the second instruction to an operand obtained by combining the packed decimal operand of the first instruction and the packed decimal operand of the second instruction. | 0.5 |
8,463,786 | 2 | 4 | 2. The process of claim 1 , wherein the process action of accessing a set of topically related documents comprises an action of accessing documents identified in a prescribed number of the top ranking search results found in one or more searches based on a search query pertaining a topic of interest. | 2. The process of claim 1 , wherein the process action of accessing a set of topically related documents comprises an action of accessing documents identified in a prescribed number of the top ranking search results found in one or more searches based on a search query pertaining a topic of interest. 4. The process of claim 2 , wherein the search results are provided by a user. | 0.786885 |
7,865,394 | 60 | 71 | 60. A method of creating and distributing individualized multimedia messages over a computer network using an email message sent simultaneously to at least five hundred recipients, comprising: retrieving information about an intended message recipient from a recipient database using a computer; personalizing a multimedia message for each said recipient based on the retrieved information using a computer with unique recipient information for at least five hundred recipients and the multimedia message including computer files comprising at least one of text and graphics files, and further comprising at least one of audio and video files; and delivering, by using an email sent simultaneously to each of the at least five hundred recipients, the multimedia message to each of said recipients over a computer network and wherein at least some of said individualized multimedia content for said at least five hundred recipients are different from at least some other of said individualized multimedia content. | 60. A method of creating and distributing individualized multimedia messages over a computer network using an email message sent simultaneously to at least five hundred recipients, comprising: retrieving information about an intended message recipient from a recipient database using a computer; personalizing a multimedia message for each said recipient based on the retrieved information using a computer with unique recipient information for at least five hundred recipients and the multimedia message including computer files comprising at least one of text and graphics files, and further comprising at least one of audio and video files; and delivering, by using an email sent simultaneously to each of the at least five hundred recipients, the multimedia message to each of said recipients over a computer network and wherein at least some of said individualized multimedia content for said at least five hundred recipients are different from at least some other of said individualized multimedia content. 71. A method as noted in claim 60 , wherein the unique recipient information is provided within the at least one of audio and video files and the at least one of text and graphics files and wherein in the step of delivering the multimedia message, it is delivered in response to opening the email. | 0.598649 |
7,720,827 | 9 | 11 | 9. A network meta-data library that is part of a telecommunications network hardware component operable to: receive at least one or more changes associated with one or more telecommunication models; link one or more portions of one or more stored telecommunication models to the received changes; generate one or more maps of the linked portions; generate one or more transformation models using one or more of the generated maps; and forward the one or more transformation models to a mediation unit to enable the generation of one or more normalized models. | 9. A network meta-data library that is part of a telecommunications network hardware component operable to: receive at least one or more changes associated with one or more telecommunication models; link one or more portions of one or more stored telecommunication models to the received changes; generate one or more maps of the linked portions; generate one or more transformation models using one or more of the generated maps; and forward the one or more transformation models to a mediation unit to enable the generation of one or more normalized models. 11. The meta-data library as in claim 9 further operable to link the portions on a portion-by-portion basis. | 0.810526 |
8,768,057 | 1 | 11 | 1. A method of classifying marking types on images of a document, the method comprising: supplying the document containing the images to a segmenter; segmenting the images received by the segmenter including identifying neatly written or printed text by grouping selected feature points along predetermined orientations, the feature points including local extrema of bounding contours of connected components, and subtracting enclosing boundary boxes of text lines from remaining document material to fragment connected components that are part of the text lines and part of extraneous markings; supplying the fragments to a classifier, the classifier providing a category score to each fragment, wherein the classifier is trained from groundtruth images whose pixels are labeled according to known marking types; and assigning a same label to all pixels in a fragment when the fragment is classified by the classifier. | 1. A method of classifying marking types on images of a document, the method comprising: supplying the document containing the images to a segmenter; segmenting the images received by the segmenter including identifying neatly written or printed text by grouping selected feature points along predetermined orientations, the feature points including local extrema of bounding contours of connected components, and subtracting enclosing boundary boxes of text lines from remaining document material to fragment connected components that are part of the text lines and part of extraneous markings; supplying the fragments to a classifier, the classifier providing a category score to each fragment, wherein the classifier is trained from groundtruth images whose pixels are labeled according to known marking types; and assigning a same label to all pixels in a fragment when the fragment is classified by the classifier. 11. The method according to claim 1 , further including: training the classifier from the groundtruth images using a machine learning algorithm. | 0.742857 |
7,630,639 | 15 | 19 | 15. A computer readable medium not including signals storing a computer program that when executed by a computer causes the computer to perform a method for controlling transmission in an Optical Network Unit (ONU) in an Ethernet passive optical network (EPON), wherein the ONU implements a data-link layer and a physical layer, the method comprising: receiving, at the physical layer of an ONU, a word which is communicated from the data-link layer of the ONU, wherein the word may be a data word or an idle word; delaying the word, at the physical layer in the ONU, for a pre-determined amount of time before allowing the word to be transmitted by a transmitter, thereby providing time for turning the transmitter on or off; and turning the transmitter at the physical layer in the ONU on or off based on the current state of the transmitter and the content of the received words without data-link layer sending a control signal across multiple sublayers to the physical layer in the ONU. | 15. A computer readable medium not including signals storing a computer program that when executed by a computer causes the computer to perform a method for controlling transmission in an Optical Network Unit (ONU) in an Ethernet passive optical network (EPON), wherein the ONU implements a data-link layer and a physical layer, the method comprising: receiving, at the physical layer of an ONU, a word which is communicated from the data-link layer of the ONU, wherein the word may be a data word or an idle word; delaying the word, at the physical layer in the ONU, for a pre-determined amount of time before allowing the word to be transmitted by a transmitter, thereby providing time for turning the transmitter on or off; and turning the transmitter at the physical layer in the ONU on or off based on the current state of the transmitter and the content of the received words without data-link layer sending a control signal across multiple sublayers to the physical layer in the ONU. 19. The computer readable medium not including signals of claim 15 , wherein the method further comprises determining the amount of time for which the word is delayed based on a laser turn-on time, an automatic gain control (AGC) time, and a data and clock recovery (CDR) time. | 0.647583 |
8,713,018 | 1 | 6 | 1. A system for providing reference items as a suggestion for classifying uncoded electronically stored information items, comprising: a set of reference electronically stored information items each associated with one of a plurality of classification codes and a visual representation of that classification code comprising at least one of a shape and a symbol, wherein the visual representation of each of the classification codes is different from the visual representations of the remaining classification codes; a set of uncoded electronically stored information items each associated with a visual representation different from the visual representations of the classification codes; a processor to execute modules, comprising: a clustering module to combine one or more of the coded reference electronically stored information items with the set of the uncoded electronically stored information items and to group the combined uncoded electronically stored information items and one or more coded reference electronically stored information items into clusters; and a display to visually depict relationships between the uncoded electronically stored information items and the one or more coded reference electronically stored information items in at least one of the clusters as suggestions for classifying the uncoded electronically stored information items in that cluster by displaying the visual representation associated with each of the coded reference electronically stored information items in that cluster and the visual representation associated with each of the uncoded electronically stored information items in that cluster. | 1. A system for providing reference items as a suggestion for classifying uncoded electronically stored information items, comprising: a set of reference electronically stored information items each associated with one of a plurality of classification codes and a visual representation of that classification code comprising at least one of a shape and a symbol, wherein the visual representation of each of the classification codes is different from the visual representations of the remaining classification codes; a set of uncoded electronically stored information items each associated with a visual representation different from the visual representations of the classification codes; a processor to execute modules, comprising: a clustering module to combine one or more of the coded reference electronically stored information items with the set of the uncoded electronically stored information items and to group the combined uncoded electronically stored information items and one or more coded reference electronically stored information items into clusters; and a display to visually depict relationships between the uncoded electronically stored information items and the one or more coded reference electronically stored information items in at least one of the clusters as suggestions for classifying the uncoded electronically stored information items in that cluster by displaying the visual representation associated with each of the coded reference electronically stored information items in that cluster and the visual representation associated with each of the uncoded electronically stored information items in that cluster. 6. A system according to claim 1 , wherein each uncoded electronically stored information item in the at least one cluster is represented by a symbol in the display and each of the one or more coded reference electronically stored information items is represented by an additional symbol in the display, and further wherein the coded reference electronically stored information items associated with different classification codes are distinguished by assigning a different color to the different symbols. | 0.640313 |
10,002,167 | 1 | 11 | 1. A method, executed on a suitably programmed computing device, for managing data, the method comprising: extracting, by a search engine, a plurality of data field descriptors from at least one database from each of a plurality of disparate data sources, comprising the search engine: performing a preliminary database access function to determine access to each of the at least one database, wherein for each database: determining a schema of the database, and determining available data fields of the database; using the plurality of data field descriptors from each of the at least one database, developing a data field result list upon which a query may be run, by: providing a display of the plurality of data field descriptors and control data from the at least one database, the control data comprising one or more of constraints, fields, keywords, and truncations used for extracting the plurality of data field descriptors from the at least one database, and saving the plurality of data field descriptors and the control data as the data field result list for each of the at least one database; receiving, from a graphical user interface, a user search request directed to the data field result list; transforming the user search request into a dataset query based on the data field result list by combining the user search request with an API request; communicating the dataset query to the at least one database; searching the at least one database using the dataset query; and managing, based on the data field result list, data from the at least one database comprising providing a response to the dataset query of the at least one database. | 1. A method, executed on a suitably programmed computing device, for managing data, the method comprising: extracting, by a search engine, a plurality of data field descriptors from at least one database from each of a plurality of disparate data sources, comprising the search engine: performing a preliminary database access function to determine access to each of the at least one database, wherein for each database: determining a schema of the database, and determining available data fields of the database; using the plurality of data field descriptors from each of the at least one database, developing a data field result list upon which a query may be run, by: providing a display of the plurality of data field descriptors and control data from the at least one database, the control data comprising one or more of constraints, fields, keywords, and truncations used for extracting the plurality of data field descriptors from the at least one database, and saving the plurality of data field descriptors and the control data as the data field result list for each of the at least one database; receiving, from a graphical user interface, a user search request directed to the data field result list; transforming the user search request into a dataset query based on the data field result list by combining the user search request with an API request; communicating the dataset query to the at least one database; searching the at least one database using the dataset query; and managing, based on the data field result list, data from the at least one database comprising providing a response to the dataset query of the at least one database. 11. The method of claim 1 , further comprising communicating with a different data source using an adapter configured to communicate in the language of the different data source. | 0.681004 |
8,276,130 | 11 | 18 | 11. A computer-readable memory device having computer-executable instructions for performing a method for compiling a source program comprising: a syntax analysis unit configured to syntactically analyze at least one of the source program or an output from a lexical analysis unit, the syntax analysis unit further configured to: identify a hint related to vector alignment, said hint related to vector alignment including a modifier of a vector identifier; and determine whether a vector is vector aligned based on said identified hint related to vector alignment; and a code generation unit configured to generate a simplified code based on said identified hint related to vector alignment. | 11. A computer-readable memory device having computer-executable instructions for performing a method for compiling a source program comprising: a syntax analysis unit configured to syntactically analyze at least one of the source program or an output from a lexical analysis unit, the syntax analysis unit further configured to: identify a hint related to vector alignment, said hint related to vector alignment including a modifier of a vector identifier; and determine whether a vector is vector aligned based on said identified hint related to vector alignment; and a code generation unit configured to generate a simplified code based on said identified hint related to vector alignment. 18. The computer-readable memory device according to claim 11 , further comprising: a semantic analysis unit configured to semantically analyze at least one of said source program or an output received from the syntax analysis unit. | 0.710723 |
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