patent_num
int64 3.93M
10.2M
| claim_num1
int64 1
519
| claim_num2
int64 2
520
| sentence1
stringlengths 40
15.9k
| sentence2
stringlengths 88
20k
| label
float64 0.5
0.99
|
|---|---|---|---|---|---|
9,846,744 | 11 | 13 | 11. A computer implemented method of generating a list of playable media objects, the method comprising the steps of: querying at least one internet search engine with the search query object; generating additional terms related to the search query object based on results returned by the internet search engine, wherein generating additional terms comprises: receiving a page identified in the result returned by the internet search engine, parsing the received page to identify a plurality of sections in the page, extracting terms from each section of the plurality of sections, scoring each of the plurality of sections based at least in part on the respective extracted terms to generate a plurality of scores, and selecting additional terms from a subset of the plurality of sections based at least in part on the plurality of scores; identifying one or more media storage web sites having playable media objects related to the generated additional terms; and generating a list of playable media objects from the playable media objects at the media storage web sites. | 11. A computer implemented method of generating a list of playable media objects, the method comprising the steps of: querying at least one internet search engine with the search query object; generating additional terms related to the search query object based on results returned by the internet search engine, wherein generating additional terms comprises: receiving a page identified in the result returned by the internet search engine, parsing the received page to identify a plurality of sections in the page, extracting terms from each section of the plurality of sections, scoring each of the plurality of sections based at least in part on the respective extracted terms to generate a plurality of scores, and selecting additional terms from a subset of the plurality of sections based at least in part on the plurality of scores; identifying one or more media storage web sites having playable media objects related to the generated additional terms; and generating a list of playable media objects from the playable media objects at the media storage web sites. 13. The method of claim 11 , further comprising transmitting at least one of the listed playable media objects in response to a user request. | 0.661058 |
9,875,298 | 1 | 4 | 1. A computer-implemented method of automated generation of a search query, said method comprising: accessing a first search query; determining that a first portion of said first search query includes a semantic key, wherein said semantic key is associated with at least one semantic sub-key, and wherein said at least one semantic sub-key is a hyponym of said semantic key; responsive to said determining, automatically generating a second search query based on said first search query, wherein said second search query is free of said first portion; performing a first search based on said second search query, wherein first search results generated responsive to said first search comprise a plurality of documents, and wherein each document of said plurality of documents includes at least one respective instance of at least one semantic sub-key associated with said semantic key; performing a second search based on said first search query; accessing second search results generated responsive to said second search; analyzing said first and second search results to automatically determine third search results for output, wherein said third search results are selected from a group consisting of said first search results and said second search results; and responsive to a user input, outputting fourth search results, wherein said fourth search results are different from said third search results, and wherein said fourth search results are selected from a group consisting of said first search results and said second search results wherein said analyzing further comprises determining a ratio of a quantity associated with said first search results to a quantity associated with said second search results, and wherein said analyzing further comprises automatically determining said first search results as said third search results for output if said ratio exceeds a predetermined threshold; outputting said third search results; wherein said analyzing further comprises: determining a first score associated with said first search results; determining a second score associated with said second search results; determining said first search results as said third search results for output if said first score exceeds said second score; and determining said second search results as said third search results for output if said second score exceeds said first score. | 1. A computer-implemented method of automated generation of a search query, said method comprising: accessing a first search query; determining that a first portion of said first search query includes a semantic key, wherein said semantic key is associated with at least one semantic sub-key, and wherein said at least one semantic sub-key is a hyponym of said semantic key; responsive to said determining, automatically generating a second search query based on said first search query, wherein said second search query is free of said first portion; performing a first search based on said second search query, wherein first search results generated responsive to said first search comprise a plurality of documents, and wherein each document of said plurality of documents includes at least one respective instance of at least one semantic sub-key associated with said semantic key; performing a second search based on said first search query; accessing second search results generated responsive to said second search; analyzing said first and second search results to automatically determine third search results for output, wherein said third search results are selected from a group consisting of said first search results and said second search results; and responsive to a user input, outputting fourth search results, wherein said fourth search results are different from said third search results, and wherein said fourth search results are selected from a group consisting of said first search results and said second search results wherein said analyzing further comprises determining a ratio of a quantity associated with said first search results to a quantity associated with said second search results, and wherein said analyzing further comprises automatically determining said first search results as said third search results for output if said ratio exceeds a predetermined threshold; outputting said third search results; wherein said analyzing further comprises: determining a first score associated with said first search results; determining a second score associated with said second search results; determining said first search results as said third search results for output if said first score exceeds said second score; and determining said second search results as said third search results for output if said second score exceeds said first score. 4. The method of claim 1 further comprising: performing at least one operation using a second portion of said first search query to determine whether to generate said second search query. | 0.868864 |
8,332,883 | 34 | 35 | 34. The medium of claim 27 , wherein the instructions further cause a machine to aggregate output signals from a plurality of viewers. | 34. The medium of claim 27 , wherein the instructions further cause a machine to aggregate output signals from a plurality of viewers. 35. The medium of claim 34 , wherein the instructions further cause a machine to calculate at least one of a maximum, a minimum, an average, a deviation, a derivative, an amplitude or a trend of at least one parameter of the output signals to aggregate the output signals. | 0.5 |
9,472,113 | 1 | 5 | 1. A computer-implemented method comprising: under control of one or more computing devices configured with specific computer executable instructions, causing output of a first portion of a plurality of portions of digital content via a computing device, wherein the digital content corresponds to physical content; causing a user perceptible cue source to output a user perceptible cue on the physical content at a first position in the physical content corresponding to the first portion of the digital content; and maintaining synchronous output of the digital content and the user perceptible cue on the physical content based at least in part on content synchronization information that associates each portion of the plurality of portions of the digital content with a respective position in the physical content. | 1. A computer-implemented method comprising: under control of one or more computing devices configured with specific computer executable instructions, causing output of a first portion of a plurality of portions of digital content via a computing device, wherein the digital content corresponds to physical content; causing a user perceptible cue source to output a user perceptible cue on the physical content at a first position in the physical content corresponding to the first portion of the digital content; and maintaining synchronous output of the digital content and the user perceptible cue on the physical content based at least in part on content synchronization information that associates each portion of the plurality of portions of the digital content with a respective position in the physical content. 5. The computer-implemented method of claim 1 , wherein the physical content comprises at least one of a book, a newspaper, a magazine, a newsletter, or a computing device displaying content. | 0.818786 |
8,225,408 | 27 | 28 | 27. The method of claim 26 wherein tokens and rules have names associated therewith, and wherein said dynamically building comprises assigning values to nodes in the parse tree, the value of a node corresponding to a token being the name of the corresponding token, and the value of a node corresponding to a rule being the name of the corresponding rule. | 27. The method of claim 26 wherein tokens and rules have names associated therewith, and wherein said dynamically building comprises assigning values to nodes in the parse tree, the value of a node corresponding to a token being the name of the corresponding token, and the value of a node corresponding to a rule being the name of the corresponding rule. 28. The method of claim 27 wherein said dynamically building comprises storing an indicator for a matched rule in the new parent node of the parse tree when the rule is matched. | 0.5 |
8,615,664 | 29 | 37 | 29. The system of claim 1 , wherein said source identity association module configured to associate the source identity data with the particular item, the source identity association module including at least a source identity inclusion module configured to include into the electronic message one or more identities of the one or more sensors, the one or more sensors having been used to derive, at least in part, the inference data acquired by the inference data acquisition module comprises: a source identity inclusion module configured to include into the electronic message the source identity data acquired by the source identity acquisition module, the acquired source identity data including at least one or more identities of the one or more sensors. | 29. The system of claim 1 , wherein said source identity association module configured to associate the source identity data with the particular item, the source identity association module including at least a source identity inclusion module configured to include into the electronic message one or more identities of the one or more sensors, the one or more sensors having been used to derive, at least in part, the inference data acquired by the inference data acquisition module comprises: a source identity inclusion module configured to include into the electronic message the source identity data acquired by the source identity acquisition module, the acquired source identity data including at least one or more identities of the one or more sensors. 37. The system of claim 29 , wherein said source identity inclusion module configured to include into the electronic message the source identity data acquired by the source identity acquisition module, the acquired source identity data including at least one or more identities of the one or more sensors comprises: a source identity inclusion module configured to include into, and as one or more parts of, the electronic message an identity for at least one of a facial expression sensor device or a skin characteristic sensor device used to derive the inference data acquired by the inference data acquisition module. | 0.5 |
8,225,378 | 1 | 3 | 1. A device comprising: memory and a processor; an auditing scheme module, stored in the memory and executable on the processor; and an access control scheme module, stored in the memory and executable on the processor, that is integrated with the auditing scheme module, wherein the access control scheme module makes authorization decisions in response to access requests for resources, the authorization decisions including inputs, outputs, and internal data, and the auditing scheme module includes an audit policy that comprises audit policy rules, the audit policy rules including audit content rules that: specify what audit information from any of the inputs, the outputs, or the internal data is to be included in an audit record, and specify logical deduction data used or produced during evaluation algorithms of the authorization decisions, the logical deduction data comprising proof graphs indicating respective logical chains of deductions that occur within the evaluation algorithms. | 1. A device comprising: memory and a processor; an auditing scheme module, stored in the memory and executable on the processor; and an access control scheme module, stored in the memory and executable on the processor, that is integrated with the auditing scheme module, wherein the access control scheme module makes authorization decisions in response to access requests for resources, the authorization decisions including inputs, outputs, and internal data, and the auditing scheme module includes an audit policy that comprises audit policy rules, the audit policy rules including audit content rules that: specify what audit information from any of the inputs, the outputs, or the internal data is to be included in an audit record, and specify logical deduction data used or produced during evaluation algorithms of the authorization decisions, the logical deduction data comprising proof graphs indicating respective logical chains of deductions that occur within the evaluation algorithms. 3. The device as recited in claim 1 , wherein the audit content rules further specify inputs to the authorization decisions in terms of logical assertions. | 0.581081 |
9,645,656 | 12 | 17 | 12. An apparatus comprising an input device having a plurality of selectable input items enabling text input by ambiguous input sequences entered by a device user, the apparatus further comprising a processor and a display, wherein the processor is arranged to control a primary process of receiving a user input on the input device, wherein an input sequence is being generated in dependence of selection of an input item by manipulating the user input device, wherein each input item is associated with at least one character, the generated input sequence corresponds to the sequence of input items that have been selected, and wherein the generated input sequence has a textual interpretation of the characters associated with the input sequence, wherein the textual interpretation is ambiguous, and displaying on the display a textual interpretation; and wherein the processor is arranged to control a secondary process, initiated upon receiving an input associated with a delete-character command, of: deleting a character of the textual interpretation, at a position thereof, wherein the deleted character corresponds to a first input item, and returning to the primary process where textual interpretations associated with the deleted character for said position are excluded, and displaying an updated textual interpretation, wherein the updated textual interpretation, at a position corresponding to the deleted character of the textual interpretation, has another character being associated with a second input item of the input device, wherein the second input item is in vicinity of the first input item; such that the primary and secondary processes are performed until a user input associated with a confirm-text command is received. | 12. An apparatus comprising an input device having a plurality of selectable input items enabling text input by ambiguous input sequences entered by a device user, the apparatus further comprising a processor and a display, wherein the processor is arranged to control a primary process of receiving a user input on the input device, wherein an input sequence is being generated in dependence of selection of an input item by manipulating the user input device, wherein each input item is associated with at least one character, the generated input sequence corresponds to the sequence of input items that have been selected, and wherein the generated input sequence has a textual interpretation of the characters associated with the input sequence, wherein the textual interpretation is ambiguous, and displaying on the display a textual interpretation; and wherein the processor is arranged to control a secondary process, initiated upon receiving an input associated with a delete-character command, of: deleting a character of the textual interpretation, at a position thereof, wherein the deleted character corresponds to a first input item, and returning to the primary process where textual interpretations associated with the deleted character for said position are excluded, and displaying an updated textual interpretation, wherein the updated textual interpretation, at a position corresponding to the deleted character of the textual interpretation, has another character being associated with a second input item of the input device, wherein the second input item is in vicinity of the first input item; such that the primary and secondary processes are performed until a user input associated with a confirm-text command is received. 17. The apparatus of claim 12 , further comprising a register, wherein the secondary process includes storing the deleted character and position of the deleted character in a temporary data structure in said register, and the primary process includes accessing the temporary data structure from said register upon performing the textual interpretation, wherein the temporary data structure is discarded when the confirm-text command is received. | 0.69973 |
7,962,849 | 7 | 10 | 7. A computer program product comprising a computer readable storage device having a computer program recorded therein, said computer program adapted to be executed on a processor of a computer system to perform a method for processing a user input character string entered by a user into the computer system, said computer system comprising a browser, said method comprising: receiving the user input character string, said user input character string conforming to a native character set and encoding of the browser for a language selected by the user; converting the user input character string to a converted character string consisting of characters of a Universal Character Set (UCS) which are independent of platform and language, wherein the converted character string comprises a plurality of leading whitespace characters, a plurality of trailing whitespace characters, and a middle character string comprising remaining whitespace characters that include at least one grouping of at least two consecutive whitespace characters, wherein the middle character string is disposed between the leading whitespace characters and the trailing whitespace characters, and wherein the leftmost character and the rightmost character of the middle character string are not whitespace characters; transforming the converted character string to a transformed character string by a first transformation or a second transformation, wherein said transforming the converted character string to the transformed character string by the first transformation comprises removing the leading whitespace characters and the trailing whitespace characters in the converted character string such that the transformed character string does not comprise any leading whitespace character, does not comprise any trailing whitespace character, and comprises the remaining whitespace characters; and wherein said transforming the converted character string to the transformed character string by the second transformation comprises removing the trailing whitespace characters in the converted character string such that the transformed character string does not comprise any trailing whitespace character and comprises both the leading whitespace characters and the remaining whitespace characters; and after said transforming, converting each grouping of the at least one grouping of at least two consecutive whitespace characters in the middle character string of the transformed character string to a single whitespace character, resulting in the transformed character string being converted to a resultant character string; wherein the method comprises modifying the user input character string to generate the resultant character string; wherein if said transforming consists of transforming the converted character string to the transformed character string by the first transformation, then said modifying consists of said converting the user input character string, said transforming the converted character string, and said converting each grouping; wherein if said transforming consists of transforming the converted character string to the transformed character string by the second transformation, then said modifying comprises said converting the user input character string, said transforming the converted character string, and said converting each grouping. | 7. A computer program product comprising a computer readable storage device having a computer program recorded therein, said computer program adapted to be executed on a processor of a computer system to perform a method for processing a user input character string entered by a user into the computer system, said computer system comprising a browser, said method comprising: receiving the user input character string, said user input character string conforming to a native character set and encoding of the browser for a language selected by the user; converting the user input character string to a converted character string consisting of characters of a Universal Character Set (UCS) which are independent of platform and language, wherein the converted character string comprises a plurality of leading whitespace characters, a plurality of trailing whitespace characters, and a middle character string comprising remaining whitespace characters that include at least one grouping of at least two consecutive whitespace characters, wherein the middle character string is disposed between the leading whitespace characters and the trailing whitespace characters, and wherein the leftmost character and the rightmost character of the middle character string are not whitespace characters; transforming the converted character string to a transformed character string by a first transformation or a second transformation, wherein said transforming the converted character string to the transformed character string by the first transformation comprises removing the leading whitespace characters and the trailing whitespace characters in the converted character string such that the transformed character string does not comprise any leading whitespace character, does not comprise any trailing whitespace character, and comprises the remaining whitespace characters; and wherein said transforming the converted character string to the transformed character string by the second transformation comprises removing the trailing whitespace characters in the converted character string such that the transformed character string does not comprise any trailing whitespace character and comprises both the leading whitespace characters and the remaining whitespace characters; and after said transforming, converting each grouping of the at least one grouping of at least two consecutive whitespace characters in the middle character string of the transformed character string to a single whitespace character, resulting in the transformed character string being converted to a resultant character string; wherein the method comprises modifying the user input character string to generate the resultant character string; wherein if said transforming consists of transforming the converted character string to the transformed character string by the first transformation, then said modifying consists of said converting the user input character string, said transforming the converted character string, and said converting each grouping; wherein if said transforming consists of transforming the converted character string to the transformed character string by the second transformation, then said modifying comprises said converting the user input character string, said transforming the converted character string, and said converting each grouping. 10. The computer program product of claim 7 , wherein the user input character string is a null character string. | 0.885859 |
8,478,747 | 1 | 3 | 1. A method for making recommendations to a user, the method comprising: storing data relating to user usage patterns, wherein the data includes an application portion having information as to items which were used and a context portion having information as to the context in which the items were used, wherein the context is the situation in which the user or device operated by the user is operating when the items were used; clustering the data into clusters of data points; computing, for each of the clusters, a centroid, wherein the centroid includes an application portion and a context portion; selecting at least one cluster similar to a current user context by comparing a data point representing the current user context to the context portions of one or more of the centroids; and computing, for each of one or more items, an expectation value of user usage pattern for the corresponding item by selecting data points within the selected similar clusters that have application portions indicating the use of the corresponding item and determining the similarity of the current user context to the context portions of the selected data points, wherein the expectation values are used to recommend one or more of the items. | 1. A method for making recommendations to a user, the method comprising: storing data relating to user usage patterns, wherein the data includes an application portion having information as to items which were used and a context portion having information as to the context in which the items were used, wherein the context is the situation in which the user or device operated by the user is operating when the items were used; clustering the data into clusters of data points; computing, for each of the clusters, a centroid, wherein the centroid includes an application portion and a context portion; selecting at least one cluster similar to a current user context by comparing a data point representing the current user context to the context portions of one or more of the centroids; and computing, for each of one or more items, an expectation value of user usage pattern for the corresponding item by selecting data points within the selected similar clusters that have application portions indicating the use of the corresponding item and determining the similarity of the current user context to the context portions of the selected data points, wherein the expectation values are used to recommend one or more of the items. 3. The method of claim 1 , further comprising: computing, for each of one or more items, a threshold based on values for the application portions of the selected similar clusters. | 0.5 |
9,949,103 | 10 | 14 | 10. A system comprising: a processor; and a memory in communication with the processor, the memory containing program instructions that, when executed by the processor, are configured to cause the processor to perform a method comprising: determining, by the processor and using natural language processing, a writing style of content of a composed message written by a composer; analyzing, by the processor and using natural language processing, a set of previous messages written by the composer; identifying, based on the analyzing, writing habits of the composer; identifying, by the processor, a difference between the writing style of the content and the writing habits of the composer; determining, by the processor and based on the difference, that the composer was in an impaired state when composing the message; and displaying, by the processor and through a graphical user interface, a notification of the difference to the composer after a pre-determined wait time, wherein the wait time is based on the magnitude of the difference identified between the writing style and the writing habits. | 10. A system comprising: a processor; and a memory in communication with the processor, the memory containing program instructions that, when executed by the processor, are configured to cause the processor to perform a method comprising: determining, by the processor and using natural language processing, a writing style of content of a composed message written by a composer; analyzing, by the processor and using natural language processing, a set of previous messages written by the composer; identifying, based on the analyzing, writing habits of the composer; identifying, by the processor, a difference between the writing style of the content and the writing habits of the composer; determining, by the processor and based on the difference, that the composer was in an impaired state when composing the message; and displaying, by the processor and through a graphical user interface, a notification of the difference to the composer after a pre-determined wait time, wherein the wait time is based on the magnitude of the difference identified between the writing style and the writing habits. 14. The system of claim 10 , wherein the difference between the writing style and the writing habits comprises using more unrecognizable words in the writing style than the writing habits. | 0.711656 |
9,916,365 | 10 | 11 | 10. A computer-based system comprising processor, memory, and machine readable code stored in memory and executable by processor for linking documents that refer to other documents through implicit linkages, the system is configured to: identify a first document, the first document comprising an authoritative comment regarding a second document; establish an explicit linkage between the first document and the second document based upon the authoritative comment; identify one or more third documents, based upon the existence of a citation relationship between the second document and each of the one or more third documents; detect an implicit relationship between the first document and the one or more third documents by using common information between the second document and the one or more third documents; generate an impact value for each of the one or more third documents by comparing the implicit relationship with the first document to the explicit relationship with the second document, the impact value being an indicator of the implicit relationship between the first document and each of the one or more third documents; link the first document to the one or more third documents based upon the impact value; and present the one or more third documents in response to a query for the first document. | 10. A computer-based system comprising processor, memory, and machine readable code stored in memory and executable by processor for linking documents that refer to other documents through implicit linkages, the system is configured to: identify a first document, the first document comprising an authoritative comment regarding a second document; establish an explicit linkage between the first document and the second document based upon the authoritative comment; identify one or more third documents, based upon the existence of a citation relationship between the second document and each of the one or more third documents; detect an implicit relationship between the first document and the one or more third documents by using common information between the second document and the one or more third documents; generate an impact value for each of the one or more third documents by comparing the implicit relationship with the first document to the explicit relationship with the second document, the impact value being an indicator of the implicit relationship between the first document and each of the one or more third documents; link the first document to the one or more third documents based upon the impact value; and present the one or more third documents in response to a query for the first document. 11. The system of claim 10 , wherein the impact value is indicative to an implicit relationship between the first document and the one or more third documents and is displayed to a user. | 0.5 |
8,849,818 | 1 | 12 | 1. A computer-implemented method, comprising: providing a rating icon for a first document in a group of documents; receiving from a user, through a selection of the rating icon, a user rating of the first document in the group of documents; generating a first user-specific rating for the first document based on the user rating, wherein the first user-specific rating corresponds to the user and is distinct from respective user-specific ratings of other users for the group of documents; receiving a search request sent by the user; identifying a plurality of documents that satisfy the search request, wherein the plurality documents includes a second document that has not previously been rated by the user and is in the group of documents; and sending a response to the search request, the response including instructions to display a ranked set of links to at least some of the plurality of documents that satisfy the search request, wherein the ranked set of the links includes a link to the second document, wherein the link to the second document is displayed with the first user-specific rating. | 1. A computer-implemented method, comprising: providing a rating icon for a first document in a group of documents; receiving from a user, through a selection of the rating icon, a user rating of the first document in the group of documents; generating a first user-specific rating for the first document based on the user rating, wherein the first user-specific rating corresponds to the user and is distinct from respective user-specific ratings of other users for the group of documents; receiving a search request sent by the user; identifying a plurality of documents that satisfy the search request, wherein the plurality documents includes a second document that has not previously been rated by the user and is in the group of documents; and sending a response to the search request, the response including instructions to display a ranked set of links to at least some of the plurality of documents that satisfy the search request, wherein the ranked set of the links includes a link to the second document, wherein the link to the second document is displayed with the first user-specific rating. 12. The method of claim 1 , wherein sending the response to the search request includes sending instructions to display a plurality of sorting options for sorting the links in the ranked set of links. | 0.755501 |
8,082,143 | 11 | 12 | 11. A hardware computer readable storage medium storing computer readable instructions which, when executed by a computer cause the computer to perform a method of identifying treelet translation pairs for use in a machine translation system that translates a source language input into a target language output, the method comprising: accessing a corpus of pairs of aligned, parallel syntactic dependency structures, each pair including a source language dependency structure having nodes that represent lexical items, the nodes being aligned with nodes representing lexical items in a target language dependency structure; enumerating connected sets of source nodes in the source language dependency structure as possible source treelets; and extracting well formed treelet translation pairs from the possible source treelets and aligned portions of a corresponding target language dependency structure. | 11. A hardware computer readable storage medium storing computer readable instructions which, when executed by a computer cause the computer to perform a method of identifying treelet translation pairs for use in a machine translation system that translates a source language input into a target language output, the method comprising: accessing a corpus of pairs of aligned, parallel syntactic dependency structures, each pair including a source language dependency structure having nodes that represent lexical items, the nodes being aligned with nodes representing lexical items in a target language dependency structure; enumerating connected sets of source nodes in the source language dependency structure as possible source treelets; and extracting well formed treelet translation pairs from the possible source treelets and aligned portions of a corresponding target language dependency structure. 12. The hardware computer readable medium of claim 11 wherein each child node of a parent node is considered to be connected to other child nodes of the parent node. | 0.831288 |
6,102,966 | 4 | 7 | 4. The method described in claim 1 including renaming fields of the computer program with corresponding different field names, wherein the renaming the fields of the computer program comprises: identifying the classes of the computer program; identifying original field names of fields within each class identified in the identifying the classes of the computer program; and replacing the original field names within each class with the corresponding different field names. | 4. The method described in claim 1 including renaming fields of the computer program with corresponding different field names, wherein the renaming the fields of the computer program comprises: identifying the classes of the computer program; identifying original field names of fields within each class identified in the identifying the classes of the computer program; and replacing the original field names within each class with the corresponding different field names. 7. The method described in claim 4 including disregarding local variable names of the computer program. | 0.80566 |
9,092,495 | 1 | 4 | 1. A method comprising: at a computing device including one or more processors and memory storing one or more programs: identifying a set of values from a plurality of facts associated with an entity, wherein the plurality of facts are stored in a fact repository, and a respective fact in the plurality of facts includes: (i) an attribute descriptive of the fact; and (ii) a value corresponding to the attribute; responsive to a search for a first value, in the set of values, included in a first fact in the plurality of facts: identifying, in the plurality of facts, a second fact associated with the entity; and causing to be displayed to a user: (A) a link to the second fact, wherein: the link, when selected, invokes a search of the fact repository in accordance with one or more search parameters; and the one or more search parameters include a value corresponding to an attribute included in the second fact; and (B) information representing a confidence value associated with the second fact. | 1. A method comprising: at a computing device including one or more processors and memory storing one or more programs: identifying a set of values from a plurality of facts associated with an entity, wherein the plurality of facts are stored in a fact repository, and a respective fact in the plurality of facts includes: (i) an attribute descriptive of the fact; and (ii) a value corresponding to the attribute; responsive to a search for a first value, in the set of values, included in a first fact in the plurality of facts: identifying, in the plurality of facts, a second fact associated with the entity; and causing to be displayed to a user: (A) a link to the second fact, wherein: the link, when selected, invokes a search of the fact repository in accordance with one or more search parameters; and the one or more search parameters include a value corresponding to an attribute included in the second fact; and (B) information representing a confidence value associated with the second fact. 4. The method of claim 1 , wherein the first value corresponds to a name of a person, and further comprising: causing to be displayed to a user: (D) values representing one or more related persons. | 0.714493 |
9,424,351 | 1 | 3 | 1. One or more computer-storage media storing computer-useable instructions that, when used by a computing device, cause the computing device to perform a method for utilizing a hybrid-distribution system for identifying relevant documents based on a search query, the method comprising: allocating a group of documents to a segment, the group of documents being indexed by atom in a reverse index and indexed by document in a forward index wherein atoms in the reverse index are accessed in a matching process and a preliminary ranking process and wherein documents in the forward index are accessed in a final ranking process; storing a different portion of the reverse index and the forward index on each of a plurality of nodes that form the segment; first, accessing the reverse index portion stored on each of a first set of nodes having portions of the reverse index; identifying a first set of documents that is relevant to the search query, wherein the first set of documents is identified as being relevant to the search query by way of the matching process and the preliminary ranking process; second, based on document identifications associated with the first set of documents, accessing the forward index portion stored on each of a second set of nodes having portions of the forward index; identifying a second set of documents from the first set of documents, wherein the second set of documents is identified by way of the final ranking process; limiting a quantity of relevant documents in the first set of documents identified to the second set of documents; and communicating for presentation search results for the search query based on the second set of documents. | 1. One or more computer-storage media storing computer-useable instructions that, when used by a computing device, cause the computing device to perform a method for utilizing a hybrid-distribution system for identifying relevant documents based on a search query, the method comprising: allocating a group of documents to a segment, the group of documents being indexed by atom in a reverse index and indexed by document in a forward index wherein atoms in the reverse index are accessed in a matching process and a preliminary ranking process and wherein documents in the forward index are accessed in a final ranking process; storing a different portion of the reverse index and the forward index on each of a plurality of nodes that form the segment; first, accessing the reverse index portion stored on each of a first set of nodes having portions of the reverse index; identifying a first set of documents that is relevant to the search query, wherein the first set of documents is identified as being relevant to the search query by way of the matching process and the preliminary ranking process; second, based on document identifications associated with the first set of documents, accessing the forward index portion stored on each of a second set of nodes having portions of the forward index; identifying a second set of documents from the first set of documents, wherein the second set of documents is identified by way of the final ranking process; limiting a quantity of relevant documents in the first set of documents identified to the second set of documents; and communicating for presentation search results for the search query based on the second set of documents. 3. The computer-storage media of claim 1 , wherein a quantity of nodes in the second set of nodes is greater than the quantity of nodes in the first set of nodes. | 0.723549 |
9,367,742 | 1 | 2 | 1. An object monitoring apparatus, comprising: an image receiver configured to receive at least one frame of captured images; an edge image generator configured to generate an edge image by detecting edges of objects appearing in the frame; a reference image generator configured to generate a reference image by detecting a part corresponding to a background in the frame to thereby define the detected part as a background edge, the reference image generated by repeatedly detecting as many as or more than a predetermined number an edge commonly appearing over a plurality of the frames; a candidate object extractor configured to extract one or more candidate object pixels by comparing the edge image with the reference image, and to extract a candidate object by grouping the extracted candidate object pixels into the candidate object; and an object-of-interest determiner configured to determine whether the candidate object is an object-of-interest based on a size of the candidate object and a duration time of detection of the candidate object. | 1. An object monitoring apparatus, comprising: an image receiver configured to receive at least one frame of captured images; an edge image generator configured to generate an edge image by detecting edges of objects appearing in the frame; a reference image generator configured to generate a reference image by detecting a part corresponding to a background in the frame to thereby define the detected part as a background edge, the reference image generated by repeatedly detecting as many as or more than a predetermined number an edge commonly appearing over a plurality of the frames; a candidate object extractor configured to extract one or more candidate object pixels by comparing the edge image with the reference image, and to extract a candidate object by grouping the extracted candidate object pixels into the candidate object; and an object-of-interest determiner configured to determine whether the candidate object is an object-of-interest based on a size of the candidate object and a duration time of detection of the candidate object. 2. The object monitoring apparatus of claim 1 , further comprising: an updater configured to update the candidate object into the reference image when the object-of-interest determiner determines that the candidate object is not the object-of-interest. | 0.676093 |
9,003,283 | 6 | 8 | 6. The method as described in claim 5 , wherein the selected text includes a plurality of discrete selected text sections, and the parameters include a plurality of parameter units each representative of the corresponding selected text section. | 6. The method as described in claim 5 , wherein the selected text includes a plurality of discrete selected text sections, and the parameters include a plurality of parameter units each representative of the corresponding selected text section. 8. The method as described in claim 6 , wherein each parameter unit includes a first character of the selected text section, a last character of the selected text section, a serial number, and the amount of the characters of the selected text section. | 0.5 |
9,729,381 | 1 | 4 | 1. A method comprising: receiving geographical location information for an entity; receiving a proprietary name for the entity; and geocoding the geographical location information into a hierarchical address by first transforming the geographical location information into latitude/longitude coordinates, next transforming the latitude/longitude coordinates to reference grid coordinates, wherein a reference grid for the geographical location is selected, at least in part, according to the geographical location's proximity to a regional centroid of a candidate reference grid or a governmental jurisdiction associated with the geographical location, and determining the hierarchical address based on the location of the latitude/longitude coordinates of the geographical location of the entity within the reference grid. | 1. A method comprising: receiving geographical location information for an entity; receiving a proprietary name for the entity; and geocoding the geographical location information into a hierarchical address by first transforming the geographical location information into latitude/longitude coordinates, next transforming the latitude/longitude coordinates to reference grid coordinates, wherein a reference grid for the geographical location is selected, at least in part, according to the geographical location's proximity to a regional centroid of a candidate reference grid or a governmental jurisdiction associated with the geographical location, and determining the hierarchical address based on the location of the latitude/longitude coordinates of the geographical location of the entity within the reference grid. 4. The method of claim 1 , wherein the proprietary name and the hierarchical address serve as alternate keys for accessing a record in a Unified Geographic Database (UGD). | 0.75431 |
8,768,723 | 13 | 20 | 13. Apparatus comprising: at least one processor; and a memory storing processor-executable instructions that, when executed by the at least one processor, perform a method comprising: receiving an original free-form text narrative of a patient encounter provided by a clinician; re-formatting the original free-form text narrative in a manner that facilitates clinical fact extraction performed by a fact extraction engine on a formatted text resulting from the re-formatting; extracting one or more clinical facts from the formatted text using the fact extraction engine, wherein a first fact of the one or more clinical facts is extracted from a first portion of the formatted text, wherein the first portion of the formatted text is a formatted version of a first portion of the original free-form text narrative, the extracting comprising analyzing the formatted text to identify a set of one or more features of at least the first portion of the formatted text, correlating the set of features to one or more abstract semantic concepts, and generating computer-readable data that expresses the one or more abstract semantic concepts as the one or more clinical facts extracted from the formatted text; and providing to a user an indicator that distinguishes the first portion of the original free-form text narrative that resulted in extraction of the first fact, from other portions of the original free-form text narrative that did not result in the extraction of the first fact. | 13. Apparatus comprising: at least one processor; and a memory storing processor-executable instructions that, when executed by the at least one processor, perform a method comprising: receiving an original free-form text narrative of a patient encounter provided by a clinician; re-formatting the original free-form text narrative in a manner that facilitates clinical fact extraction performed by a fact extraction engine on a formatted text resulting from the re-formatting; extracting one or more clinical facts from the formatted text using the fact extraction engine, wherein a first fact of the one or more clinical facts is extracted from a first portion of the formatted text, wherein the first portion of the formatted text is a formatted version of a first portion of the original free-form text narrative, the extracting comprising analyzing the formatted text to identify a set of one or more features of at least the first portion of the formatted text, correlating the set of features to one or more abstract semantic concepts, and generating computer-readable data that expresses the one or more abstract semantic concepts as the one or more clinical facts extracted from the formatted text; and providing to a user an indicator that distinguishes the first portion of the original free-form text narrative that resulted in extraction of the first fact, from other portions of the original free-form text narrative that did not result in the extraction of the first fact. 20. The apparatus of claim 13 , wherein the method further comprises prompting a user to approve the foimatted text. | 0.81761 |
8,001,195 | 10 | 12 | 10. A system for identifying spam in an email text, the system comprising a processor, a memory, and computer code loaded into the memory for implementing: (a) a lexical vector module coupled to a database containing numerical values corresponding to unique words of the email text, the lexical vector module being configured to generate a lexical vector of the email text as a plurality of the unique numerical values corresponding to a unique word and a number of occurrences of each corresponding unique word in the email text; (b) a histogram module for generating histograms of lexical vectors for each unique numerical identifier of each corresponding unique word in the email text; (c) a lexical vector database accessible by the histogram module; (d) a length calculation module coupled to the lexical vector module and connected to the lexical vector database; and (e) a comparison nodule coupled to the histogram module, (f) wherein the histogram of the lexical vector of the incoming email text is generated in the histogram module and compared only a single time to histograms of lexical vectors of known spam texts stored in the lexical vector database, and (g) wherein the lexical vector is generated after the email text is normalized morphologically and after meaningless and noise words are filtered out from the email text, filtering multi-symbol meaningless human-language words and noise human-language words. | 10. A system for identifying spam in an email text, the system comprising a processor, a memory, and computer code loaded into the memory for implementing: (a) a lexical vector module coupled to a database containing numerical values corresponding to unique words of the email text, the lexical vector module being configured to generate a lexical vector of the email text as a plurality of the unique numerical values corresponding to a unique word and a number of occurrences of each corresponding unique word in the email text; (b) a histogram module for generating histograms of lexical vectors for each unique numerical identifier of each corresponding unique word in the email text; (c) a lexical vector database accessible by the histogram module; (d) a length calculation module coupled to the lexical vector module and connected to the lexical vector database; and (e) a comparison nodule coupled to the histogram module, (f) wherein the histogram of the lexical vector of the incoming email text is generated in the histogram module and compared only a single time to histograms of lexical vectors of known spam texts stored in the lexical vector database, and (g) wherein the lexical vector is generated after the email text is normalized morphologically and after meaningless and noise words are filtered out from the email text, filtering multi-symbol meaningless human-language words and noise human-language words. 12. The system of claim 10 , wherein the comparison module produces a control value. | 0.820513 |
8,135,757 | 1 | 9 | 1. A computer implemented method, comprising: providing a program coded in a first programming language having data structures, wherein at least one of the data structures includes a reference to reusable code; generating a model file providing a source name identifying the reusable code, elements and attributes in a second programming language for the reference to the reusable code in the program; invoking a generator with a reference to the model file; processing, by the invoked generator, the data structure coded in the first programming language to generate a data structure schema in a second programming language describing elements and attributes of the data structure coded in the first programming language; determining instances of the source name indicated in the model file in the data structure; and generating, for the determined instances of the source name in the data structure, a reference in the data structure schema to the reusable code identified by the source name, wherein the reference generated in the data structure schema includes the element and attribute information indicated in the model file. | 1. A computer implemented method, comprising: providing a program coded in a first programming language having data structures, wherein at least one of the data structures includes a reference to reusable code; generating a model file providing a source name identifying the reusable code, elements and attributes in a second programming language for the reference to the reusable code in the program; invoking a generator with a reference to the model file; processing, by the invoked generator, the data structure coded in the first programming language to generate a data structure schema in a second programming language describing elements and attributes of the data structure coded in the first programming language; determining instances of the source name indicated in the model file in the data structure; and generating, for the determined instances of the source name in the data structure, a reference in the data structure schema to the reusable code identified by the source name, wherein the reference generated in the data structure schema includes the element and attribute information indicated in the model file. 9. The method of claim 1 , further comprising: processing a script file including references to at least one model file to invoke the generator, wherein the generator determines instances of the source name in the program for each model file referenced in the script file, and wherein the generator generates for each determined instance of each source name the reference in the program schema to the reusable code identified by the source name. | 0.5 |
10,133,860 | 7 | 9 | 7. A computer implemented method for generating authorization code, said method comprising: storing, in a memory, a set of computer instructions; executing, by a processor, said set of computer instructions; receiving, by a user-input module, a base-sentence having a plurality of alpha-numeric characters as a user-input; calculating, by a first calculator, the total number of characters in the base-sentence provided by the user and determining a nearest prefect square matrix based on the total number of characters calculated in the user inputted base-sentence; generating, by a first matrix-generator, a first matrix by populating each cell of the first matrix with at least one character of the base-sentence; generating, by a pattern-generator, patterns by selecting at least a cell of the first-matrix; enabling, by a pattern-selector, the user to select a pattern from a group of generated patterns; extracting, by a first extractor, ASCII values corresponding to each of the characters of the selected pattern and generating, by a second matrix-generator, a second matrix by populating each cell of the second matrix with ASCII value of each characters of the selected pattern, wherein the number of columns of the second matrix is equal to the number of rows of the first matrix; extracting, by a second extractor, at least a coordinate of each the characters of the selected pattern and calculating, by a second calculator, the total number of characters in the extracted coordinates of the selected pattern and generating, by a third matrix-generator , a third matrix by populating each cell of the third matrix with a coordinate value from the extracted coordinates of the selected pattern; matrix-multiplying, by a matrix-multiplier, the second matrix and the third matrix for obtaining a fourth matrix and converting, by a hex-convertor, each of the cell value of the fourth matrix into a hex value; hashing, by a hash-convertor, the hex values of the fourth matrix for obtaining the authorization code; receiving, a request from the user for the base-sentence; and extracting the base-sentence in response to the request from the user. | 7. A computer implemented method for generating authorization code, said method comprising: storing, in a memory, a set of computer instructions; executing, by a processor, said set of computer instructions; receiving, by a user-input module, a base-sentence having a plurality of alpha-numeric characters as a user-input; calculating, by a first calculator, the total number of characters in the base-sentence provided by the user and determining a nearest prefect square matrix based on the total number of characters calculated in the user inputted base-sentence; generating, by a first matrix-generator, a first matrix by populating each cell of the first matrix with at least one character of the base-sentence; generating, by a pattern-generator, patterns by selecting at least a cell of the first-matrix; enabling, by a pattern-selector, the user to select a pattern from a group of generated patterns; extracting, by a first extractor, ASCII values corresponding to each of the characters of the selected pattern and generating, by a second matrix-generator, a second matrix by populating each cell of the second matrix with ASCII value of each characters of the selected pattern, wherein the number of columns of the second matrix is equal to the number of rows of the first matrix; extracting, by a second extractor, at least a coordinate of each the characters of the selected pattern and calculating, by a second calculator, the total number of characters in the extracted coordinates of the selected pattern and generating, by a third matrix-generator , a third matrix by populating each cell of the third matrix with a coordinate value from the extracted coordinates of the selected pattern; matrix-multiplying, by a matrix-multiplier, the second matrix and the third matrix for obtaining a fourth matrix and converting, by a hex-convertor, each of the cell value of the fourth matrix into a hex value; hashing, by a hash-convertor, the hex values of the fourth matrix for obtaining the authorization code; receiving, a request from the user for the base-sentence; and extracting the base-sentence in response to the request from the user. 9. The method as claimed in claim 7 , wherein the step of calculating the total number of characters in the extracted coordinates of the selected pattern further includes a step of determining, by the determinator, a nearest prefect square matrix based on the calculated total number of extracted prefect square matrix. | 0.682903 |
7,966,187 | 32 | 50 | 32. A method of evaluating compliance of at least one agent with at least one script that governs, at least in part, at least one interaction processed by at least one agent, the method comprising at least the following: creating at least one voice record of at least one interaction processed by the at least one agent at an agent workstation; defining at least first data relating to evaluating compliance of the at least one agent with the at least one script; and processing the at least one voice record against the at least first data, wherein the voice record is divided into viewable panel-level segments, wherein a panel-level time displacement stamp is assigned to each panel of the panel-level segments, wherein each panel-level segment is compared with a corresponding portion of the first data, wherein a confidence level threshold of the automatic speech recognition component is used to evaluate the accuracy of each panel-level segment based on an output of a comparison between each panel-level segment and its corresponding portion of the first data, wherein a score is assigned to each panel-level segment, each score indicating a match accuracy between the panel-level segment to which it is assigned and its assigned panel-level segment's corresponding portion of the first data, wherein the scores are evaluated against a standard, the standard defining a required score for each of the panel-level segments to be declared as a match to their corresponding portions of the first data, a set of action rules being applied to the output of the processing to direct a quality assurance action to be taken. | 32. A method of evaluating compliance of at least one agent with at least one script that governs, at least in part, at least one interaction processed by at least one agent, the method comprising at least the following: creating at least one voice record of at least one interaction processed by the at least one agent at an agent workstation; defining at least first data relating to evaluating compliance of the at least one agent with the at least one script; and processing the at least one voice record against the at least first data, wherein the voice record is divided into viewable panel-level segments, wherein a panel-level time displacement stamp is assigned to each panel of the panel-level segments, wherein each panel-level segment is compared with a corresponding portion of the first data, wherein a confidence level threshold of the automatic speech recognition component is used to evaluate the accuracy of each panel-level segment based on an output of a comparison between each panel-level segment and its corresponding portion of the first data, wherein a score is assigned to each panel-level segment, each score indicating a match accuracy between the panel-level segment to which it is assigned and its assigned panel-level segment's corresponding portion of the first data, wherein the scores are evaluated against a standard, the standard defining a required score for each of the panel-level segments to be declared as a match to their corresponding portions of the first data, a set of action rules being applied to the output of the processing to direct a quality assurance action to be taken. 50. The method of claim 32 , wherein processing the at least one voice record includes evaluating whether the at least one agent spoke at least one word included in the at least first data. | 0.680743 |
7,712,016 | 11 | 19 | 11. A computer-readable storage medium having a set of instructions which, when executed performs a method for utilizing an object model in a word processing application program for managing a plurality content regions for displaying specific types of content in an electronic document, the method executed by the set of instructions comprising: providing a plurality of objects in the object model, wherein the plurality of objects comprises a plurality of properties, a plurality of methods, and a plurality of events each functionally associated with the plurality of content regions; exposing an application programming interface (API) in the object model for accessing the plurality of objects, wherein exposing the API in the object model for accessing the plurality of objects comprises exposing an interactive content pane comprising: at least one content region and a selection region for the at least one content region within the interactive content pane; receiving a selection of the selection region for the at least one content region; providing, in response to the selection of the selection region for the at least one content region, a dropdown list corresponding to the plurality of objects, the dropdown list of the plurality of objects comprising entries associated with the plurality of properties, the plurality of methods, and the plurality of events; receiving a selection of a first entry in the dropdown list, the first entry being associated with adding at least one content region, wherein adding the at least one content region comprises adding the at least one content region based on at least one parameter and at least one object for specifying the at least one content region, the at least one parameter corresponding to a specific type of content associated with the at least one content region and the at least one object corresponding to a location for adding the at least one content region; adding the at least one content region in accordance with the at least one parameter and the at least one object; receiving a selection of second entry in the drop down list; and utilizing, in response to receiving the selection of the second entry, one of the plurality of properties, the plurality of methods, and the plurality of events associated with the second entry to manage the selected at least one content region. | 11. A computer-readable storage medium having a set of instructions which, when executed performs a method for utilizing an object model in a word processing application program for managing a plurality content regions for displaying specific types of content in an electronic document, the method executed by the set of instructions comprising: providing a plurality of objects in the object model, wherein the plurality of objects comprises a plurality of properties, a plurality of methods, and a plurality of events each functionally associated with the plurality of content regions; exposing an application programming interface (API) in the object model for accessing the plurality of objects, wherein exposing the API in the object model for accessing the plurality of objects comprises exposing an interactive content pane comprising: at least one content region and a selection region for the at least one content region within the interactive content pane; receiving a selection of the selection region for the at least one content region; providing, in response to the selection of the selection region for the at least one content region, a dropdown list corresponding to the plurality of objects, the dropdown list of the plurality of objects comprising entries associated with the plurality of properties, the plurality of methods, and the plurality of events; receiving a selection of a first entry in the dropdown list, the first entry being associated with adding at least one content region, wherein adding the at least one content region comprises adding the at least one content region based on at least one parameter and at least one object for specifying the at least one content region, the at least one parameter corresponding to a specific type of content associated with the at least one content region and the at least one object corresponding to a location for adding the at least one content region; adding the at least one content region in accordance with the at least one parameter and the at least one object; receiving a selection of second entry in the drop down list; and utilizing, in response to receiving the selection of the second entry, one of the plurality of properties, the plurality of methods, and the plurality of events associated with the second entry to manage the selected at least one content region. 19. The computer-readable storage medium of claim 11 , wherein utilizing the plurality of methods comprises setting at least one parameter and utilizing the plurality of events comprises setting the at least one parameter. | 0.900981 |
8,255,260 | 17 | 20 | 17. The computer-readable storage medium of claim 15 , further comprising additional instructions, which, when executed by a processor, cause the processor to perform the steps comprising storing the filtered exception object data records in a container based on a subscription to the exception object data records. | 17. The computer-readable storage medium of claim 15 , further comprising additional instructions, which, when executed by a processor, cause the processor to perform the steps comprising storing the filtered exception object data records in a container based on a subscription to the exception object data records. 20. The computer-readable storage medium of claim 17 , wherein the filtered exception object data records are stored in the persistent container when no user is subscribed to the filtered exception object data records. | 0.5 |
8,214,382 | 1 | 3 | 1. A method of enforcing database predicate constraints on database accesses, comprising: receiving, by a database management system stored on a non-transitory computer readable medium and executable by a processor, a database query; parsing, by the database management system, the query based on query constraints defined in system tables, wherein the query constraints require a where clause in the query and limit the where clause in the query; examining, by the database management system, the query for the existence of the where clause; examining, by the database management system, the where clause to determine compliance with the query constraints defined in the system tables; validating the syntax of the query before executing the query; executing, by the database management system, the query only when the query contains the where clause, the where clause complies with the query constraints defined in the system tables, and the query complies with user classification constraints stored in tables of the database management system to apply different levels of access for queries to different user classifications, wherein the user classification constraints are applied to client devices; and rejecting, by the database management system, the query when the query does not contain the where clause, or when the query does contain the where clause and the where clause does not comply with the query constraints defined in the system tables, or when the query does not comply with the user classification constraints. | 1. A method of enforcing database predicate constraints on database accesses, comprising: receiving, by a database management system stored on a non-transitory computer readable medium and executable by a processor, a database query; parsing, by the database management system, the query based on query constraints defined in system tables, wherein the query constraints require a where clause in the query and limit the where clause in the query; examining, by the database management system, the query for the existence of the where clause; examining, by the database management system, the where clause to determine compliance with the query constraints defined in the system tables; validating the syntax of the query before executing the query; executing, by the database management system, the query only when the query contains the where clause, the where clause complies with the query constraints defined in the system tables, and the query complies with user classification constraints stored in tables of the database management system to apply different levels of access for queries to different user classifications, wherein the user classification constraints are applied to client devices; and rejecting, by the database management system, the query when the query does not contain the where clause, or when the query does contain the where clause and the where clause does not comply with the query constraints defined in the system tables, or when the query does not comply with the user classification constraints. 3. The method of claim 1 , wherein the method executes in a database management system. | 0.776923 |
9,449,282 | 13 | 14 | 13. A web server for ranking unlabeled matches, each of the unlabeled matches existing between a first member of a dating website and a corresponding one of a first set of members of the dating website, the web server comprising: a memory storing data associated with the dating website; and at least one of processor, that when executed, performs operations comprising: receiving, from a first mobile device, messages and profile views directed toward one of a second set of members of the dating website, the first mobile device being associated with the first member of the dating website; receiving, from a second mobile device, messages and profile views directed toward the first member of the dating website, the second mobile device being one of a plurality of mobile devices, and wherein each of the plurality of mobile devices is associated with a corresponding one of the second set of members of the dating website; receiving a plurality of labeled matches, wherein each of the plurality of labeled matches exists between the first member of the dating website and the corresponding one of the second set of members of the dating website, and wherein each of the plurality of labeled matches are labeled based on a dating profile of the first member of the dating website, a dating profile of the corresponding one of the second set of members of the dating website, and behavioral features, the behavioral features comprising: a first density of profile views initiated by the first member of the dating website toward the corresponding one of the second set of members of the dating website, the first density of profile views being measured within a time period between a first message and a last message exchanged between the first member of the dating website and the corresponding one of the second set of members of the dating website, a second density of profile views initiated by the corresponding one of the second set of members of the dating website toward the first member of the dating website, the second density of profile views being measured within the time period, a message disparity that identifies a difference between a number of messages sent by the first member of the dating website and a number of messages sent by the corresponding one of the second set of members of the dating website, a number of times that the first member of the dating website viewed the dating profile of the corresponding one of the second set of members of the dating website, a number of times that the corresponding one of the second set of members of the dating website viewed the dating profile of the first member of the dating website, and whether the first member of the dating website and the corresponding one of the second set of members of the dating website exchange phone numbers with one another; determining a probability of relevance of each of the plurality of labeled matches based on the behavioral features, wherein: the probability of relevance increases as a first difference decreases and the probability of relevance decreases as the first difference increases, the first difference being between the first density of profile views initiated by the first member of the dating website toward the corresponding one of the second set of members of the dating website within the time period and the second density of profile views initiated by the corresponding one of the second set of members of the dating website toward the first member of the dating website within the time period, the probability of relevance increases as the message disparity decreases and the probability of relevance decreases as the message disparity increases, the probability of relevance increases as a second difference decreases and the probability of relevance decreases as the second difference increases, the second difference being between the number of times that the first member of the dating website viewed the dating profile of the corresponding one of the second set of members of the dating website and the number of times that the corresponding one of the second set of members of the dating website viewed the dating profile of the first member of the dating website, and ones of the plurality of labeled matches where the first member of the dating website and the corresponding one of the second set of members of the dating website exchange phone numbers with one another are assigned a higher probability of relevance than other ones of the plurality of labeled matches where the first member of the dating website and the corresponding one of the second set of members of the dating website do not exchange phone numbers with one another; for each of the plurality of labeled matches: comparing, on an attribute-by-attribute basis, first binary data in each attribute of the dating profile of the first member of the dating website to second binary data in a corresponding attribute of the dating profile of the corresponding one of the second set of members of the dating website to produce ranking features of each of the plurality of labeled matches, and correlating the ranking features of each of the plurality of labeled matches to the probability of relevance of each of the plurality of labeled matches to produce a ranking function; training boosted regression trees based on the probability of relevance of each of the plurality of labeled matches, the behavioral features, the ranking features of each of the plurality of labeled matches, the ranking function, the dating profile of the first member of the dating website, and the dating profile of the corresponding one of the second set of members of the dating website, wherein, upon completion of the training, the boosted regression trees are configured to utilize, as input, ranking features observed from a given unlabeled match and generate, as output, a probability of relevance of the given unlabeled match; determining, utilizing the boosted regression trees a probability of relevance of each of the unlabeled matches by: comparing, on an attribute-by-attribute basis, the first binary data in each attribute of the dating profile of the first member of the dating website, to third binary data in a corresponding attribute of a dating profile of the corresponding one of the first set of members of the dating website to produce ranking features of each of the unlabeled matches, wherein each of the unlabeled matches lack the behavioral features, and calculating the probability of relevance each of the unlabeled matches by inputting, into the ranking function, the ranking features of each of the unlabeled matches and retrieving, from the ranking function, the probability of relevance each of the unlabeled matches, wherein the ranking features of each of the unlabeled matches are used as a proxy for the behavioral features; calculating a rank for each of the unlabeled matches based on the probability of relevance of each of the unlabeled matches to generate a set of ranked matches; and transmitting, over a network interface, at least a portion of the set of ranked matches to the first mobile device associated with the first member of the dating website. | 13. A web server for ranking unlabeled matches, each of the unlabeled matches existing between a first member of a dating website and a corresponding one of a first set of members of the dating website, the web server comprising: a memory storing data associated with the dating website; and at least one of processor, that when executed, performs operations comprising: receiving, from a first mobile device, messages and profile views directed toward one of a second set of members of the dating website, the first mobile device being associated with the first member of the dating website; receiving, from a second mobile device, messages and profile views directed toward the first member of the dating website, the second mobile device being one of a plurality of mobile devices, and wherein each of the plurality of mobile devices is associated with a corresponding one of the second set of members of the dating website; receiving a plurality of labeled matches, wherein each of the plurality of labeled matches exists between the first member of the dating website and the corresponding one of the second set of members of the dating website, and wherein each of the plurality of labeled matches are labeled based on a dating profile of the first member of the dating website, a dating profile of the corresponding one of the second set of members of the dating website, and behavioral features, the behavioral features comprising: a first density of profile views initiated by the first member of the dating website toward the corresponding one of the second set of members of the dating website, the first density of profile views being measured within a time period between a first message and a last message exchanged between the first member of the dating website and the corresponding one of the second set of members of the dating website, a second density of profile views initiated by the corresponding one of the second set of members of the dating website toward the first member of the dating website, the second density of profile views being measured within the time period, a message disparity that identifies a difference between a number of messages sent by the first member of the dating website and a number of messages sent by the corresponding one of the second set of members of the dating website, a number of times that the first member of the dating website viewed the dating profile of the corresponding one of the second set of members of the dating website, a number of times that the corresponding one of the second set of members of the dating website viewed the dating profile of the first member of the dating website, and whether the first member of the dating website and the corresponding one of the second set of members of the dating website exchange phone numbers with one another; determining a probability of relevance of each of the plurality of labeled matches based on the behavioral features, wherein: the probability of relevance increases as a first difference decreases and the probability of relevance decreases as the first difference increases, the first difference being between the first density of profile views initiated by the first member of the dating website toward the corresponding one of the second set of members of the dating website within the time period and the second density of profile views initiated by the corresponding one of the second set of members of the dating website toward the first member of the dating website within the time period, the probability of relevance increases as the message disparity decreases and the probability of relevance decreases as the message disparity increases, the probability of relevance increases as a second difference decreases and the probability of relevance decreases as the second difference increases, the second difference being between the number of times that the first member of the dating website viewed the dating profile of the corresponding one of the second set of members of the dating website and the number of times that the corresponding one of the second set of members of the dating website viewed the dating profile of the first member of the dating website, and ones of the plurality of labeled matches where the first member of the dating website and the corresponding one of the second set of members of the dating website exchange phone numbers with one another are assigned a higher probability of relevance than other ones of the plurality of labeled matches where the first member of the dating website and the corresponding one of the second set of members of the dating website do not exchange phone numbers with one another; for each of the plurality of labeled matches: comparing, on an attribute-by-attribute basis, first binary data in each attribute of the dating profile of the first member of the dating website to second binary data in a corresponding attribute of the dating profile of the corresponding one of the second set of members of the dating website to produce ranking features of each of the plurality of labeled matches, and correlating the ranking features of each of the plurality of labeled matches to the probability of relevance of each of the plurality of labeled matches to produce a ranking function; training boosted regression trees based on the probability of relevance of each of the plurality of labeled matches, the behavioral features, the ranking features of each of the plurality of labeled matches, the ranking function, the dating profile of the first member of the dating website, and the dating profile of the corresponding one of the second set of members of the dating website, wherein, upon completion of the training, the boosted regression trees are configured to utilize, as input, ranking features observed from a given unlabeled match and generate, as output, a probability of relevance of the given unlabeled match; determining, utilizing the boosted regression trees a probability of relevance of each of the unlabeled matches by: comparing, on an attribute-by-attribute basis, the first binary data in each attribute of the dating profile of the first member of the dating website, to third binary data in a corresponding attribute of a dating profile of the corresponding one of the first set of members of the dating website to produce ranking features of each of the unlabeled matches, wherein each of the unlabeled matches lack the behavioral features, and calculating the probability of relevance each of the unlabeled matches by inputting, into the ranking function, the ranking features of each of the unlabeled matches and retrieving, from the ranking function, the probability of relevance each of the unlabeled matches, wherein the ranking features of each of the unlabeled matches are used as a proxy for the behavioral features; calculating a rank for each of the unlabeled matches based on the probability of relevance of each of the unlabeled matches to generate a set of ranked matches; and transmitting, over a network interface, at least a portion of the set of ranked matches to the first mobile device associated with the first member of the dating website. 14. The web server as recited in claim 13 , wherein the behavioral features further comprise at least one selected from a group consisting of: 1) the first member of the dating website viewed the dating profile of the corresponding one of the second set of members of the dating website but did not send a message to the corresponding one of the second set of members of the dating website; and 2) the corresponding one of the second set of members of the dating website viewed the dating profile of the first member of the dating website but did not send a message to the first member of the dating website. | 0.610256 |
8,862,581 | 1 | 4 | 1. A method for concentration detection, the method comprising the steps of: extracting temporal features from brain signals; classifying the extracted temporal features using a classifier to give a score x 1 ; extracting spectral-spatial features from brain signals; selecting spectral-spatial features containing discriminative information between concentration and non-concentration states from the set of extracted spectral-spatial features; classifying the selected spectral-spatial features using a classifier to give a score x 2 ; combining the scores x 1 and x 2 to give a single score; and determining whether the subject is in a concentration state based on the single score; wherein the step of extracting spectral-spatial features of brain signals further comprises the steps of: extracting respective brain signal components in discrete frequency windows using filter banks to obtain spectral features of brain signals; and applying a common spatial pattern (CSP) algorithm to each of the spectral features using a CSP array to obtain the spectral-spatial features of brain signals. | 1. A method for concentration detection, the method comprising the steps of: extracting temporal features from brain signals; classifying the extracted temporal features using a classifier to give a score x 1 ; extracting spectral-spatial features from brain signals; selecting spectral-spatial features containing discriminative information between concentration and non-concentration states from the set of extracted spectral-spatial features; classifying the selected spectral-spatial features using a classifier to give a score x 2 ; combining the scores x 1 and x 2 to give a single score; and determining whether the subject is in a concentration state based on the single score; wherein the step of extracting spectral-spatial features of brain signals further comprises the steps of: extracting respective brain signal components in discrete frequency windows using filter banks to obtain spectral features of brain signals; and applying a common spatial pattern (CSP) algorithm to each of the spectral features using a CSP array to obtain the spectral-spatial features of brain signals. 4. The method as claimed in claim 1 , wherein said filter banks comprise low-order bandpass Chebyshev Type II filters with a pass-band width of 4 Hertz (Hz). | 0.858047 |
8,595,635 | 15 | 19 | 15. A non-transitory computer-readable medium having contents adapted to cause a computing system to perform a method for selecting content items from a source web page and posting content items to a web log, the method comprising: loading a source web page; displaying the loaded source web page to provide a plurality of displayed content items; receiving via a user pointing device of the computing system input selecting one or more selected content items from among the plurality of displayed content items, the selected content items being selectable exclusive of non-selected content items among the plurality of display content items; receiving access credentials for a web log; accessing the web log at a network location by communicating the received access credentials to the web log; receiving, from one or more blog servers, web log publication information associated with the web log, the web log publication information including a web log ID and a corresponding URL; comparing the URL of the web log publication information with a URL of the access credentials; determining that the URL of the web log publication information matches the URL of the access credentials; and transmitting the web log ID and a post including a definition of the selected content items to the web log in a format suitable for receipt and posting of the selected content items on the web log. | 15. A non-transitory computer-readable medium having contents adapted to cause a computing system to perform a method for selecting content items from a source web page and posting content items to a web log, the method comprising: loading a source web page; displaying the loaded source web page to provide a plurality of displayed content items; receiving via a user pointing device of the computing system input selecting one or more selected content items from among the plurality of displayed content items, the selected content items being selectable exclusive of non-selected content items among the plurality of display content items; receiving access credentials for a web log; accessing the web log at a network location by communicating the received access credentials to the web log; receiving, from one or more blog servers, web log publication information associated with the web log, the web log publication information including a web log ID and a corresponding URL; comparing the URL of the web log publication information with a URL of the access credentials; determining that the URL of the web log publication information matches the URL of the access credentials; and transmitting the web log ID and a post including a definition of the selected content items to the web log in a format suitable for receipt and posting of the selected content items on the web log. 19. The computer-readable medium of claim 15 , further comprising: displaying a preview window prior to transmitting the definition of the selected content items to the web log; and displaying in the preview window the one or more selected content items in a manner in which the selected content items will be presented in the web log. | 0.504438 |
9,690,786 | 5 | 9 | 5. In a computer network, a method for dynamically creating one or more hyperlinks within an electronic text file, comprising the steps of: analyzing the electronic text file by term weighting words in the electronic text file to identify one or more keywords contextually relevant to the electronic text file; for at least one keyword of the one or more keywords: querying a multimedia content database to identify at least one multimedia video content item related to the at least one keyword, the multimedia video content item identified by comparing the at least one keyword to metadata associated with multimedia video content in the multimedia content database; generating at least one hyperlink for the keyword, the generated hyperlink including a pointer to the identified multimedia video content item related to the keyword for subsequent retrieval of the multimedia video content item; inserting a keyword hyperlink into the electronic text file prior to a web server sending the electronic text file to a user device, the keyword hyperlink linking the at least one keyword to a display based on the generated hyperlink; responsive to inserting the keyword hyperlink into the electronic text file, and prior to receiving a request for the multimedia video content item, copying the multimedia video content item from the multimedia content database into a particular memory; the web server responding to a request from the user device for the multimedia video content item by accessing the multimedia video content item from the particular memory. | 5. In a computer network, a method for dynamically creating one or more hyperlinks within an electronic text file, comprising the steps of: analyzing the electronic text file by term weighting words in the electronic text file to identify one or more keywords contextually relevant to the electronic text file; for at least one keyword of the one or more keywords: querying a multimedia content database to identify at least one multimedia video content item related to the at least one keyword, the multimedia video content item identified by comparing the at least one keyword to metadata associated with multimedia video content in the multimedia content database; generating at least one hyperlink for the keyword, the generated hyperlink including a pointer to the identified multimedia video content item related to the keyword for subsequent retrieval of the multimedia video content item; inserting a keyword hyperlink into the electronic text file prior to a web server sending the electronic text file to a user device, the keyword hyperlink linking the at least one keyword to a display based on the generated hyperlink; responsive to inserting the keyword hyperlink into the electronic text file, and prior to receiving a request for the multimedia video content item, copying the multimedia video content item from the multimedia content database into a particular memory; the web server responding to a request from the user device for the multimedia video content item by accessing the multimedia video content item from the particular memory. 9. The method of claim 5 , wherein the pointer includes storage addresses within the computer network for the identified multimedia video content item. | 0.816748 |
8,996,340 | 1 | 5 | 1. A method for establishing an aid in diagnosis of a complex system of an aircraft comprising a plurality of sub-systems, at least one sub-system of the plurality of sub-systems comprising circuitry configured to monitor and provide notifications regarding at least one detected event, the method using: a failure condition graph at least partially modeling the complex system, the failure condition graph comprising a plurality of peaks, each peak being connected by a logic implication relationship to at least one other peak of the plurality of peaks, the plurality of peaks comprising: one peak representing a failure condition event; and one peak representing only at least one element of the complex system, the at least one element being able to break down, and the method comprising: receiving at least one message of notification of occurrence of the at least one detected event; creating a set of failure events, each said failure event of the set of failure events being associated with a peak of the failure condition graph linked to the at least one received notification message; for each said failure event of the set of failure events, constructing, from the failure condition graph, at least one logic expression leading to the failure event, the at least one logic expression being based on elements of the complex system; creating at least one group of failure events of the set of failure events, the at least one element being common to two logic expressions linked to two separate failure events of the at least one group, the logic expressions associated with the failure events of the at least one group representing a diagnosis relating to the at least one detected event; and determining minimal vertexes of the logic expressions of the failure events of the at least one group of failure events, the minimal vertexes forming minimal diagnoses of the diagnosis relating to the at least one detected event. | 1. A method for establishing an aid in diagnosis of a complex system of an aircraft comprising a plurality of sub-systems, at least one sub-system of the plurality of sub-systems comprising circuitry configured to monitor and provide notifications regarding at least one detected event, the method using: a failure condition graph at least partially modeling the complex system, the failure condition graph comprising a plurality of peaks, each peak being connected by a logic implication relationship to at least one other peak of the plurality of peaks, the plurality of peaks comprising: one peak representing a failure condition event; and one peak representing only at least one element of the complex system, the at least one element being able to break down, and the method comprising: receiving at least one message of notification of occurrence of the at least one detected event; creating a set of failure events, each said failure event of the set of failure events being associated with a peak of the failure condition graph linked to the at least one received notification message; for each said failure event of the set of failure events, constructing, from the failure condition graph, at least one logic expression leading to the failure event, the at least one logic expression being based on elements of the complex system; creating at least one group of failure events of the set of failure events, the at least one element being common to two logic expressions linked to two separate failure events of the at least one group, the logic expressions associated with the failure events of the at least one group representing a diagnosis relating to the at least one detected event; and determining minimal vertexes of the logic expressions of the failure events of the at least one group of failure events, the minimal vertexes forming minimal diagnoses of the diagnosis relating to the at least one detected event. 5. The method according to claim 1 , wherein the failure condition graph further comprises at least one peak representing a logic operation, at least one of the logic expressions comprising a logic operation represented by a peak of the failure condition graph. | 0.812769 |
8,370,156 | 1 | 2 | 1. One or more computer-readable storage media storing computer-executable instructions that when executed on a computer perform a method of modifying a system representation, the media storing one or more instructions for: simultaneously providing, using the computer: a first representation of a system, and a second representation of the system; receiving a user action associated with the first or second representation; analyzing: the first representation, and the second representation; automatically determining, using the computer, a first set of modifications for modifying one of the first or second representation, the first set of modifications determined: live based on the user action, and based on the analyzing; displaying, on a display device, the first set of modifications within the one of the first or second representation; and automatically determining a second set of modifications to be made in the unmodified one of the first or second representation based on the first set of modifications. | 1. One or more computer-readable storage media storing computer-executable instructions that when executed on a computer perform a method of modifying a system representation, the media storing one or more instructions for: simultaneously providing, using the computer: a first representation of a system, and a second representation of the system; receiving a user action associated with the first or second representation; analyzing: the first representation, and the second representation; automatically determining, using the computer, a first set of modifications for modifying one of the first or second representation, the first set of modifications determined: live based on the user action, and based on the analyzing; displaying, on a display device, the first set of modifications within the one of the first or second representation; and automatically determining a second set of modifications to be made in the unmodified one of the first or second representation based on the first set of modifications. 2. The computer-readable storage media of claim 1 , wherein the one or more instructions further comprise instructions for: modifying the one of the first or second representations based on a first subset of the first set of modifications upon a user action indicating approval of the first subset of the first set of modifications; and automatically modifying the second set of modifications to be made in the unmodified one of the first or second representation based on the first subset of the first set of modifications. | 0.5 |
9,128,732 | 16 | 19 | 16. The medium of claim 15 , wherein the heuristic indicators are associated with environmental settings to allow adjustment between effectiveness of the protection and efficiency of execution of the code stream. | 16. The medium of claim 15 , wherein the heuristic indicators are associated with environmental settings to allow adjustment between effectiveness of the protection and efficiency of execution of the code stream. 19. The medium of claim 16 , wherein the heuristic indicators include a dynamically generated random value, and wherein the next code is selected if the proportion and the dynamically generated random value satisfy a particular relationship. | 0.637048 |
8,776,011 | 17 | 19 | 17. An apparatus for managing components of an application enablement suite (AES), comprising: a workflow designer engine server including a workflow designer engine module; and a developer portal server including a developer portal module in operative communication with the workflow designer engine module, wherein the workflow designer engine module and developer portal module are configured to communicate with an AES; wherein the developer portal module is configured to provide an application developer with access to the workflow designer engine module in response to a proper authentication sequence, wherein the authentication sequence is initiated in response to the application developer activating the workflow designer engine module via a user device in operative communication with the developer portal module; wherein the workflow designer engine module is configured to activate a composite network application manager in response to the application developer selecting a manage composite network application function via the user device in conjunction with a graphical user interface (GUI) controlled by the developer portal module; wherein the workflow designer engine module and developer portal module are configured to create a new composite network application using archetypes of the workflow designer engine module and repositories in storage devices of the developer portal module in response to the application developer defining at least some parameters for the new composite network application in conjunction with the GUI, wherein the new composite network application is associated with a new or existing composite network service available to subscribers via the AES and associated with at least one of multiple network services, multiple service providers, multiple service networks, and multiple communication sessions; wherein the workflow designer engine module is configured to activate an application program interface (API) manager in response to the application developer selecting a manage API function via the user device in conjunction with the GUI; wherein the workflow designer engine module and developer portal module are configured to create a new API using archetypes of the workflow designer engine module and repositories in storage devices of the developer portal module in response to the application developer defining at least some parameters for the new API in conjunction with the GUI, wherein the new API is associated with the new composite network application; wherein the workflow designer engine and developer portal are configured to form a layer between the GUI and the AES; wherein the archetypes include a configurable set of basic definitions and design patterns accessible to the application developer via the developer portal for creation of the new network application; wherein the repositories include a configurable set of application features accessible to the application developer via the developer portal for creation of the new network application. | 17. An apparatus for managing components of an application enablement suite (AES), comprising: a workflow designer engine server including a workflow designer engine module; and a developer portal server including a developer portal module in operative communication with the workflow designer engine module, wherein the workflow designer engine module and developer portal module are configured to communicate with an AES; wherein the developer portal module is configured to provide an application developer with access to the workflow designer engine module in response to a proper authentication sequence, wherein the authentication sequence is initiated in response to the application developer activating the workflow designer engine module via a user device in operative communication with the developer portal module; wherein the workflow designer engine module is configured to activate a composite network application manager in response to the application developer selecting a manage composite network application function via the user device in conjunction with a graphical user interface (GUI) controlled by the developer portal module; wherein the workflow designer engine module and developer portal module are configured to create a new composite network application using archetypes of the workflow designer engine module and repositories in storage devices of the developer portal module in response to the application developer defining at least some parameters for the new composite network application in conjunction with the GUI, wherein the new composite network application is associated with a new or existing composite network service available to subscribers via the AES and associated with at least one of multiple network services, multiple service providers, multiple service networks, and multiple communication sessions; wherein the workflow designer engine module is configured to activate an application program interface (API) manager in response to the application developer selecting a manage API function via the user device in conjunction with the GUI; wherein the workflow designer engine module and developer portal module are configured to create a new API using archetypes of the workflow designer engine module and repositories in storage devices of the developer portal module in response to the application developer defining at least some parameters for the new API in conjunction with the GUI, wherein the new API is associated with the new composite network application; wherein the workflow designer engine and developer portal are configured to form a layer between the GUI and the AES; wherein the archetypes include a configurable set of basic definitions and design patterns accessible to the application developer via the developer portal for creation of the new network application; wherein the repositories include a configurable set of application features accessible to the application developer via the developer portal for creation of the new network application. 19. The apparatus set forth in claim 17 wherein the workflow designer engine module is configured to activate an application enabler manager in response to the application developer selecting a manage application enabler function via the user device in conjunction with the GUI; and wherein the workflow designer engine module and developer portal module are configured to create a new application enabler using archetypes of the workflow designer engine module and repositories in storage devices of the developer portal module in response to the application developer defining at least some parameters for the new application enabler in conjunction with the GUI, wherein the new application enabler is associated with the new composite network application. | 0.562356 |
8,380,521 | 8 | 14 | 8. A computer-readable medium having computer-executable instructions for execution by a processing system, the computer-readable medium comprising instructions for: evaluating a conference stream with a speech recognition algorithm; determining if a hot word is identified in the conference stream, wherein at least a caller name is used to populate a voice template for identifying the hot word; responsive to determining the hot word is in the conference stream, identifying a speaker of the hot word; and suppressing the hot word in the stream prior to transmission of the stream to conference participants. | 8. A computer-readable medium having computer-executable instructions for execution by a processing system, the computer-readable medium comprising instructions for: evaluating a conference stream with a speech recognition algorithm; determining if a hot word is identified in the conference stream, wherein at least a caller name is used to populate a voice template for identifying the hot word; responsive to determining the hot word is in the conference stream, identifying a speaker of the hot word; and suppressing the hot word in the stream prior to transmission of the stream to conference participants. 14. The computer-readable medium of claim 8 , comprising instructions for: determining if a participant's name was spoken in a pre-defined interval subsequent to the hot word; and invoking a conference feature associated with the hot word on behalf of a participant having the participant's name. | 0.5 |
8,239,751 | 1 | 2 | 1. A computer-implemented method for adding information to a spreadsheet, comprising: on a client system having one or more processors and memory storing one or more programs to be executed by the one or more processors: displaying a spreadsheet; receiving a request to add a cell value to the spreadsheet, the request containing a reference to an object and an attribute; generating a query corresponding to the request; sending the query to a fact repository; receiving the requested cell value from the fact repository, wherein the cell value correspond to a value of a fact, the fact being associated with an object in the fact repository, wherein a respective fact includes an attribute field indicating an attribute and a value field describing the indicated attributes, wherein objects in the fact repository are created by: extracting facts from web documents; determining entities with which the extracted facts are associated; storing the extracted facts in the fact repository; and associating the stored extracted facts with objects corresponding to the determined entities; inserting the received cell value into the spreadsheet. | 1. A computer-implemented method for adding information to a spreadsheet, comprising: on a client system having one or more processors and memory storing one or more programs to be executed by the one or more processors: displaying a spreadsheet; receiving a request to add a cell value to the spreadsheet, the request containing a reference to an object and an attribute; generating a query corresponding to the request; sending the query to a fact repository; receiving the requested cell value from the fact repository, wherein the cell value correspond to a value of a fact, the fact being associated with an object in the fact repository, wherein a respective fact includes an attribute field indicating an attribute and a value field describing the indicated attributes, wherein objects in the fact repository are created by: extracting facts from web documents; determining entities with which the extracted facts are associated; storing the extracted facts in the fact repository; and associating the stored extracted facts with objects corresponding to the determined entities; inserting the received cell value into the spreadsheet. 2. The method of claim 1 , wherein the spreadsheet is a web spreadsheet page. | 0.886431 |
8,990,134 | 11 | 12 | 11. A computer-usable non-transitory medium having executable computer program instructions embodied therein for training video location classifiers, actions of the computer program instructions comprising: storing a set of locations, each location uniquely corresponding to a geographic area having a unique geographic placement; providing a user interface for uploading a video, the user interface comprising a user interface element for specifying locations from the stored set of locations; receiving, from users via the user interface, a set of uploaded videos, each uploaded video labeled with a location from the stored set of locations, the location specified using the user interface; selecting, for each of a plurality of the locations, a location training set comprising ones of the uploaded videos that are labeled with the location; for each of a plurality of video location classifiers, each video location classifier associated with one of the locations: for each uploaded video of the location training set for the associated location, deriving a set of features associated with the uploaded video, the set of features comprising: audiovisual features extracted from content of the uploaded video; upload location information derived from an internet protocol (IP) address from which the uploaded video was uploaded; landmark scores indicating whether the uploaded video contains landmark features, the landmark scores being produced by applying trained landmark classifiers to the uploaded video; category scores indicating whether the uploaded video represents predetermined categories, the category scores produced by category classifiers that are trained based at least in part on a set of videos considered to represent the categories; and textual features derived from metadata of the uploaded video; training the video location classifier based at least in part on the features derived from the uploaded videos in the location training set; for an unlabeled video not labeled with a location from the stored set of locations, and for a first one of the trained video location classifiers: deriving a set of features comprising audiovisual features extracted from content of the unlabeled video, upload location information derived from the IP address from which the video was uploaded, landmark scores indicating whether the unlabeled video contains landmark features, category scores indicating whether the unlabeled video represents predetermined categories, and textual features derived from metadata of the unlabeled video; applying the first one of the trained video location classifiers to the set of features derived for the unlabeled video, thereby producing a location score indicating how strongly the unlabeled video represents the location associated with the first one of the trained video location classifiers; predicting based on the location score, that the unlabeled video represents the location associated with the first one of the trained video location classifiers; and providing, to a user, a visual representation of a map, the map including a visual indication of the unlabeled video on a portion of the map corresponding to the location associated with the first one of the trained video location classifiers. | 11. A computer-usable non-transitory medium having executable computer program instructions embodied therein for training video location classifiers, actions of the computer program instructions comprising: storing a set of locations, each location uniquely corresponding to a geographic area having a unique geographic placement; providing a user interface for uploading a video, the user interface comprising a user interface element for specifying locations from the stored set of locations; receiving, from users via the user interface, a set of uploaded videos, each uploaded video labeled with a location from the stored set of locations, the location specified using the user interface; selecting, for each of a plurality of the locations, a location training set comprising ones of the uploaded videos that are labeled with the location; for each of a plurality of video location classifiers, each video location classifier associated with one of the locations: for each uploaded video of the location training set for the associated location, deriving a set of features associated with the uploaded video, the set of features comprising: audiovisual features extracted from content of the uploaded video; upload location information derived from an internet protocol (IP) address from which the uploaded video was uploaded; landmark scores indicating whether the uploaded video contains landmark features, the landmark scores being produced by applying trained landmark classifiers to the uploaded video; category scores indicating whether the uploaded video represents predetermined categories, the category scores produced by category classifiers that are trained based at least in part on a set of videos considered to represent the categories; and textual features derived from metadata of the uploaded video; training the video location classifier based at least in part on the features derived from the uploaded videos in the location training set; for an unlabeled video not labeled with a location from the stored set of locations, and for a first one of the trained video location classifiers: deriving a set of features comprising audiovisual features extracted from content of the unlabeled video, upload location information derived from the IP address from which the video was uploaded, landmark scores indicating whether the unlabeled video contains landmark features, category scores indicating whether the unlabeled video represents predetermined categories, and textual features derived from metadata of the unlabeled video; applying the first one of the trained video location classifiers to the set of features derived for the unlabeled video, thereby producing a location score indicating how strongly the unlabeled video represents the location associated with the first one of the trained video location classifiers; predicting based on the location score, that the unlabeled video represents the location associated with the first one of the trained video location classifiers; and providing, to a user, a visual representation of a map, the map including a visual indication of the unlabeled video on a portion of the map corresponding to the location associated with the first one of the trained video location classifiers. 12. The computer-usable non-transitory medium of claim 11 , wherein the user interface element comprises an electronic map, such that clicking on a portion of the electronic map specifies, as the location of the uploaded video, coordinates corresponding to the portion. | 0.67823 |
4,159,536 | 12 | 13 | 12. Apparatus for electrically translating a multi-letter word selected from one language into a corresponding word in another language, comprising: (a) input means for generating electrical signals indicative of the letters in the selected word; (b) symbol storage means for permanently storing at predetermined addresses readable signals representative of corresponding words in both languages, said readable signals including letter signals representative of each letter in each word and for storing address signals in association with said readable signals representative of words in one language for identifying the address of the corresponding word in the other language; (c) comparison means connected with said input means and said symbol storage means for comparing said electrical signals generated by said input means with said readable signals and for reading out said address signals associated with the readable signals which correspond to said electrical signals generated by said input means; (d) symbol read out and display means connected with said symbol storage means and said comparison means for visually displaying the selected word and for reading out and displaying the word represented by the readable signals stored at the address read out by said comparison means. | 12. Apparatus for electrically translating a multi-letter word selected from one language into a corresponding word in another language, comprising: (a) input means for generating electrical signals indicative of the letters in the selected word; (b) symbol storage means for permanently storing at predetermined addresses readable signals representative of corresponding words in both languages, said readable signals including letter signals representative of each letter in each word and for storing address signals in association with said readable signals representative of words in one language for identifying the address of the corresponding word in the other language; (c) comparison means connected with said input means and said symbol storage means for comparing said electrical signals generated by said input means with said readable signals and for reading out said address signals associated with the readable signals which correspond to said electrical signals generated by said input means; (d) symbol read out and display means connected with said symbol storage means and said comparison means for visually displaying the selected word and for reading out and displaying the word represented by the readable signals stored at the address read out by said comparison means. 13. Apparatus as defined in claim 12, wherein said comparison means includes letter comparing means for: (a) comparing the electrical signals generated by said input means representative of the first letter of the selected word with the letter signals representative of the first letter of each word stored in said symbol storage means, (b) comparing the electrical signals representative of the second letter of said selected word with the letter signals representative of the second letter of each word stored in said symbol storage means which was detected to have a first letter identical to the first letter of said selected word, and (c) continuing to compare the electrical signals representative of the successive letters in the selected word with the letter signals representative of the corresponding letters in each word stored in said symbol storage means until only one word stored in said symbol storage means is identified by said comparison means as having the same letters and the same sequence of letters as said selected word. | 0.5 |
9,582,804 | 6 | 7 | 6. The method of claim 1 wherein a first hyperlink of the one or more hyperlinks identifies a network addressable advertiser resource, wherein the first hyperlink, when activated, causes a processor of the computing device to access the network addressable advertiser resource. | 6. The method of claim 1 wherein a first hyperlink of the one or more hyperlinks identifies a network addressable advertiser resource, wherein the first hyperlink, when activated, causes a processor of the computing device to access the network addressable advertiser resource. 7. The method of claim 6 wherein the first hyperlink, when activated, causes the processor to access the network addressable advertiser resource in a redirection process with a remote server. | 0.5 |
9,319,469 | 1 | 8 | 1. A method for securely communicating between a host and a service application running on a selected external application server to allow a service application running on the external application server to access a document maintained by the host, said method comprising the steps of: initiating a transaction, by the host, with the selected external application server by transmitting an action request from the host to the service application running on the selected external application server, the action request being against an entry point address associated with the service application; initiating a communication with the selected external application server to obtain a proof key adapted to validate a proof signature; receiving said proof key in response to said communication; providing the selected external application server with an access token and a document identifier for use in fulfilling said action request; receiving a metadata request comprising said access token and said document identifier; validating said access token prior to responding to said metadata request; sending a metadata response comprising selected metadata based on said action request when said access token is valid; receiving a content request comprising said access token and said document identifier; validating said access token prior to responding to said content request; and sending a content response comprising content from the document identified by said document identifier when said access token is valid. | 1. A method for securely communicating between a host and a service application running on a selected external application server to allow a service application running on the external application server to access a document maintained by the host, said method comprising the steps of: initiating a transaction, by the host, with the selected external application server by transmitting an action request from the host to the service application running on the selected external application server, the action request being against an entry point address associated with the service application; initiating a communication with the selected external application server to obtain a proof key adapted to validate a proof signature; receiving said proof key in response to said communication; providing the selected external application server with an access token and a document identifier for use in fulfilling said action request; receiving a metadata request comprising said access token and said document identifier; validating said access token prior to responding to said metadata request; sending a metadata response comprising selected metadata based on said action request when said access token is valid; receiving a content request comprising said access token and said document identifier; validating said access token prior to responding to said content request; and sending a content response comprising content from the document identified by said document identifier when said access token is valid. 8. The method of claim 1 characterized in that said step of initiating a transaction with a selected external application server occurs in response to the step of navigating a user agent to an endpoint address on said host in response to an instruction from a user via a user agent. | 0.525253 |
9,275,023 | 1 | 5 | 1. A method for further adapting eXtensible Stylesheet Language (XSL) to HyperText Markup Language (HTML) document transformations, the method comprising: identifying, by a web computing device, a plurality of rules matching one or more elements in an HTML document; identifying, by the web computing device, a plurality of actions associated with each of the identified plurality of rules; grouping, by the web computing device, each of the matching identified plurality of actions together into one or more corresponding groups; filtering, by the web computing device, the grouped plurality of actions based on one or more filtering rules when two or more of the grouped plurality of actions match; removing, by the web computing device, one or more of the plurality of actions in each of the one or more corresponding groups based on the one or more filtering rules; applying, by the web computing device, the remaining grouped plurality of actions that match after the filtering to transform the matching one or more elements in the HTML document; and providing, by the web computing device, the transformed HTML document. | 1. A method for further adapting eXtensible Stylesheet Language (XSL) to HyperText Markup Language (HTML) document transformations, the method comprising: identifying, by a web computing device, a plurality of rules matching one or more elements in an HTML document; identifying, by the web computing device, a plurality of actions associated with each of the identified plurality of rules; grouping, by the web computing device, each of the matching identified plurality of actions together into one or more corresponding groups; filtering, by the web computing device, the grouped plurality of actions based on one or more filtering rules when two or more of the grouped plurality of actions match; removing, by the web computing device, one or more of the plurality of actions in each of the one or more corresponding groups based on the one or more filtering rules; applying, by the web computing device, the remaining grouped plurality of actions that match after the filtering to transform the matching one or more elements in the HTML document; and providing, by the web computing device, the transformed HTML document. 5. The method as set forth in claim 1 , wherein the one or more filtering rules comprises removing remove-element, replace-element, linearize-table, set-meta-category, set-attribute, remove-attribute, set-content, append-content, all preceding set-meta-category, set-attribute, remove-attribute, set-content, or append-content when the identified plurality of actions in the one or more corresponding groups comprises linearize-table. | 0.535332 |
7,849,459 | 1 | 4 | 1. A computer-implemented method for deploying an application in a resource constrained environment, the application comprising a computer program written in the Java® computer programming language, the method comprising: identifying a resource constraint of a target system including identifying a target system having limited processing capacity; filtering the application in dependence upon the identified resource constraint including: preprocessing a tag library of the application, including identifying a tag library descriptor of the application and copying a listener from the tag library descriptor to a deployment descriptor for the application; identifying a hierarchy of classes of the application stored in a single file; storing each class of the hierarchy as a separate file accessible to the application; and identifying to a runtime platform the copying of the listener from the tag library descriptor to the deployment descriptor, including setting a flag in the application. | 1. A computer-implemented method for deploying an application in a resource constrained environment, the application comprising a computer program written in the Java® computer programming language, the method comprising: identifying a resource constraint of a target system including identifying a target system having limited processing capacity; filtering the application in dependence upon the identified resource constraint including: preprocessing a tag library of the application, including identifying a tag library descriptor of the application and copying a listener from the tag library descriptor to a deployment descriptor for the application; identifying a hierarchy of classes of the application stored in a single file; storing each class of the hierarchy as a separate file accessible to the application; and identifying to a runtime platform the copying of the listener from the tag library descriptor to the deployment descriptor, including setting a flag in the application. 4. The method of claim 1 further comprising decompressing the single file containing the hierarchy of classes. | 0.865196 |
8,731,920 | 11 | 19 | 11. A non-transitory computer-readable medium comprising computer program instructions executable to perform a method for use with a system, the system including a first document, the first document containing at least some information in common with a spoken audio stream, the method comprising: (A) identifying text in the first document, wherein the text represents a concept; (B) identifying, based on the identified text and a repository of finite state grammars, a plurality of spoken forms of the concept, including at least one spoken form not contained in the first document, wherein all of the plurality of spoken forms have the same content as each other; (C) replacing the identified text with a finite state grammar specifying the plurality of spoken forms of the concept to produce a second document; (D) generating a document-specific language model based on the second document, comprising generating at least some of the document-specific language model based on the finite state grammar. | 11. A non-transitory computer-readable medium comprising computer program instructions executable to perform a method for use with a system, the system including a first document, the first document containing at least some information in common with a spoken audio stream, the method comprising: (A) identifying text in the first document, wherein the text represents a concept; (B) identifying, based on the identified text and a repository of finite state grammars, a plurality of spoken forms of the concept, including at least one spoken form not contained in the first document, wherein all of the plurality of spoken forms have the same content as each other; (C) replacing the identified text with a finite state grammar specifying the plurality of spoken forms of the concept to produce a second document; (D) generating a document-specific language model based on the second document, comprising generating at least some of the document-specific language model based on the finite state grammar. 19. The non-transitory computer-readable medium of claim 11 , wherein the method further comprises: (E) before (D), normalizing the second document to produce a normalized document. | 0.728228 |
9,684,650 | 13 | 14 | 13. The method of claim 12 wherein the penalty comprises a tree-structured l p -norm. | 13. The method of claim 12 wherein the penalty comprises a tree-structured l p -norm. 14. The method of claim 13 wherein the penalty comprises a tree-structured l 2 -norm. | 0.5 |
10,114,872 | 17 | 20 | 17. A non-transitory computer-readable medium having program code recorded thereon for analyzing data, the program code being executed by a processor and comprising: program code to generate, by an entity, a query based at least in part on a topic of interest; program code to execute the query on a plurality of data sources, at least one of the plurality of data sources comprising at least one of knowledge center information, frequently asked questions (FAQs), user comments, customer service data, or a combination thereof; program code to select, by the entity, a data source from the plurality of data sources for monitoring based on a correlation between the data source and the topic of interest, the correlation determined based on results of the executed query; program code to monitor, based on a set schedule, the data source for matches to the query to extract data from the data source when at least an update to stored data matches the query, newly added data matches the query, or a combination thereof; program code to extract data from the data source when at least an update to stored data matches the query, newly added data matches the query, or a combination thereof; program code to determine an extraction rate for extracting the data, the extraction rate indicating an amount of the data that is extracted over a first time period; program code to determine a first processing rate for processing the extracted data with a number of parallel processors, the first processing rate indicating an amount of extracted data that is processed over a second time period; program code to dynamically adjust the number of parallel processors for analyzing the extracted data based on the extraction rate to obtain a second processing rate that is greater than the first processing rate; program code to analyze, with the parallel processors, the extracted data to determine at least one of a sentiment, an index, a pattern, or a combination thereof; program code to establish a two-way communication channel, between at least the entity that selected the data source for monitoring and a user device of a user that provided data to the data source, based on the analysis of the extracted data; program code to transmit, from the entity via the two-way communication channel, a first message directed to the user device based on the analysis of the extracted data; and program code to receive, from the user device via the two-way communication channel, a second message in response to the first message directed to the user device. | 17. A non-transitory computer-readable medium having program code recorded thereon for analyzing data, the program code being executed by a processor and comprising: program code to generate, by an entity, a query based at least in part on a topic of interest; program code to execute the query on a plurality of data sources, at least one of the plurality of data sources comprising at least one of knowledge center information, frequently asked questions (FAQs), user comments, customer service data, or a combination thereof; program code to select, by the entity, a data source from the plurality of data sources for monitoring based on a correlation between the data source and the topic of interest, the correlation determined based on results of the executed query; program code to monitor, based on a set schedule, the data source for matches to the query to extract data from the data source when at least an update to stored data matches the query, newly added data matches the query, or a combination thereof; program code to extract data from the data source when at least an update to stored data matches the query, newly added data matches the query, or a combination thereof; program code to determine an extraction rate for extracting the data, the extraction rate indicating an amount of the data that is extracted over a first time period; program code to determine a first processing rate for processing the extracted data with a number of parallel processors, the first processing rate indicating an amount of extracted data that is processed over a second time period; program code to dynamically adjust the number of parallel processors for analyzing the extracted data based on the extraction rate to obtain a second processing rate that is greater than the first processing rate; program code to analyze, with the parallel processors, the extracted data to determine at least one of a sentiment, an index, a pattern, or a combination thereof; program code to establish a two-way communication channel, between at least the entity that selected the data source for monitoring and a user device of a user that provided data to the data source, based on the analysis of the extracted data; program code to transmit, from the entity via the two-way communication channel, a first message directed to the user device based on the analysis of the extracted data; and program code to receive, from the user device via the two-way communication channel, a second message in response to the first message directed to the user device. 20. The non-transitory computer-readable medium of claim 17 , in which the two-way communication channel comprises at least one of short message service (SMS), click-to-voice, interactive voice response (IVR), e-mail, phone, Internet protocol, message board, social media, digital communication, or a combination thereof. | 0.5 |
8,762,414 | 2 | 3 | 2. The process according to claim 1 , wherein two or more of the generic individuals are distributed into classes of individuals having shared characteristics, and wherein the selection rule and the organization rule engage the classes of individuals. | 2. The process according to claim 1 , wherein two or more of the generic individuals are distributed into classes of individuals having shared characteristics, and wherein the selection rule and the organization rule engage the classes of individuals. 3. The process according to claim 2 , wherein each of the selection rule and the organization rule is part of a ruleset, and wherein the ruleset comprises at least one rule associated with each class of individuals. | 0.5 |
8,301,615 | 22 | 23 | 22. The method of claim 21 , wherein: the label definitions include a uniform resource locator (URL) label for applying to a URL in a result in the first ordered result and the second ordered result; and applying a label to at least a portion of the first ordered result and the second ordered result includes applying the URL label to the result, the result being associated with the URL. | 22. The method of claim 21 , wherein: the label definitions include a uniform resource locator (URL) label for applying to a URL in a result in the first ordered result and the second ordered result; and applying a label to at least a portion of the first ordered result and the second ordered result includes applying the URL label to the result, the result being associated with the URL. 23. The method of claim 22 , wherein: the results modification description includes one or more promotion criteria for promoting a search result based on the URL label applied to the search result; and generating modified results includes moving up in ordering of the ordered results a search result having the URL label. | 0.5 |
7,801,899 | 1 | 12 | 1. A machine-implemented method comprising: receiving a request for keyword suggestions, the request including a seed keyword with which the keyword suggestions are to be generated; accepting, from two or more keyword suggestion tools, at least two heterogeneous sets of keyword suggestions for an online advertisement, wherein each set of keyword suggestions includes targeting keyword suggestions that are ranked and scored by a keyword suggestion tool that suggested the set of keyword suggestions, and wherein targeting keyword suggestions in each set of targeting keyword suggestions have been generated based on the seed keyword; for each heterogeneous sets of keyword suggestions accepted from the at least two or more keyword suggestion tools, determining, by one or more processors, a new normalized score for each of the targeting keyword suggestions in the heterogeneous set of keyword suggestions, wherein the new normalized score is computed based on a cardinal aspect of the targeting keyword suggestion and an ordinal aspect of the targeting keyword suggestion in the heterogeneous set of keyword suggestions, the cardinal aspect representing an absolute score corresponding to the targeting keyword suggestion and the ordinal aspect representing a rank of the targeting keyword suggestion in the heterogeneous set of keyword suggestions, and wherein the new normalized score for each targeting keyword suggestion in a particular set of heterogeneous keyword suggestions is defined as a sum of a first weight multiplied by the cardinal aspect and a second weight multiplied by the ordinal aspect; generating, by the one or more processors, an adjusted new score for each targeting keyword suggestion based on a result of a function of a new normalized score corresponding to the targeting keyword suggestion and trust factor of a keyword suggestion tool from which the targeting keyword was accepted, the trust factor representing a measure of reliability of the keyword suggestion tool; combining, by the one or more processors, the targeting keyword suggestions scored by a first keyword suggestion tool selected from the at least two or more keyword suggestion tools and the targeting keyword suggestions scored by a second suggestion tool selected from the at least two or more keyword suggestion tools using the new scores to generate a combined set of ordered and scored suggestions according to the adjusted new score for each targeting keyword suggestion; and providing the combined set of keyword suggestions to a user device. | 1. A machine-implemented method comprising: receiving a request for keyword suggestions, the request including a seed keyword with which the keyword suggestions are to be generated; accepting, from two or more keyword suggestion tools, at least two heterogeneous sets of keyword suggestions for an online advertisement, wherein each set of keyword suggestions includes targeting keyword suggestions that are ranked and scored by a keyword suggestion tool that suggested the set of keyword suggestions, and wherein targeting keyword suggestions in each set of targeting keyword suggestions have been generated based on the seed keyword; for each heterogeneous sets of keyword suggestions accepted from the at least two or more keyword suggestion tools, determining, by one or more processors, a new normalized score for each of the targeting keyword suggestions in the heterogeneous set of keyword suggestions, wherein the new normalized score is computed based on a cardinal aspect of the targeting keyword suggestion and an ordinal aspect of the targeting keyword suggestion in the heterogeneous set of keyword suggestions, the cardinal aspect representing an absolute score corresponding to the targeting keyword suggestion and the ordinal aspect representing a rank of the targeting keyword suggestion in the heterogeneous set of keyword suggestions, and wherein the new normalized score for each targeting keyword suggestion in a particular set of heterogeneous keyword suggestions is defined as a sum of a first weight multiplied by the cardinal aspect and a second weight multiplied by the ordinal aspect; generating, by the one or more processors, an adjusted new score for each targeting keyword suggestion based on a result of a function of a new normalized score corresponding to the targeting keyword suggestion and trust factor of a keyword suggestion tool from which the targeting keyword was accepted, the trust factor representing a measure of reliability of the keyword suggestion tool; combining, by the one or more processors, the targeting keyword suggestions scored by a first keyword suggestion tool selected from the at least two or more keyword suggestion tools and the targeting keyword suggestions scored by a second suggestion tool selected from the at least two or more keyword suggestion tools using the new scores to generate a combined set of ordered and scored suggestions according to the adjusted new score for each targeting keyword suggestion; and providing the combined set of keyword suggestions to a user device. 12. The machine-implemented method of claim 1 further comprising: removing targeting keyword suggestions determined to be bad words. | 0.839024 |
6,073,144 | 6 | 7 | 6. A computer program product for use in conjunction with a computer system, the computer system including a user interface to display a document and issue commands to edit the document, the computer program product comprising a computer readable storage medium and a computer program mechanism embedded therein, the computer program mechanism comprising: a data structure representing the document as a hierarchical document, the hierarchical document comprising starttags and endtags and leaf contents between ones of the starttags and endtags, the data structure including starttag, endtag and leaf items representing corresponding ones of the starttags, endtags, and leaf contents; each of the starttag and endtag items representing the starttags and endtags having a corresponding index associated therewith, the data structure further including an index offset for each of the starttag and endtag items, each index offset indicating an offset to a corresponding complementary starttag or endtag item in the hierarchical document; and a document editor, executable by the computer system, for editing the hierarchical document in response to the issued commands, the document editor including instructions for traversing the data structure, both forward and backward, using the index offsets to skip over ones of the items in the data structure without having to inspect the contents of the skipped items. | 6. A computer program product for use in conjunction with a computer system, the computer system including a user interface to display a document and issue commands to edit the document, the computer program product comprising a computer readable storage medium and a computer program mechanism embedded therein, the computer program mechanism comprising: a data structure representing the document as a hierarchical document, the hierarchical document comprising starttags and endtags and leaf contents between ones of the starttags and endtags, the data structure including starttag, endtag and leaf items representing corresponding ones of the starttags, endtags, and leaf contents; each of the starttag and endtag items representing the starttags and endtags having a corresponding index associated therewith, the data structure further including an index offset for each of the starttag and endtag items, each index offset indicating an offset to a corresponding complementary starttag or endtag item in the hierarchical document; and a document editor, executable by the computer system, for editing the hierarchical document in response to the issued commands, the document editor including instructions for traversing the data structure, both forward and backward, using the index offsets to skip over ones of the items in the data structure without having to inspect the contents of the skipped items. 7. The computer program product of claim 6, the data structure further including pointers, each pointer linking one of the items to the corresponding index associated therewith; and the document editor further including instructions for traversing the data structure using the pointers to access the contents of the items. | 0.5 |
6,119,122 | 1 | 5 | 1. A computer system, comprising: a) a management service for a computer network having a plurality of objects of different types, each of said objects having at least one associated attribute with an attribute syntax, a plurality of said attributes having an associated value being of a data type corresponding to the attribute syntax of the associated attribute; b) a data structure adapted to represent one or more attributes and associated values of a target object, said data structure being capable of being modified; c) a user interface for displaying at least a portion of the data structure as an attribute tree structure irrespective of the target object type, said user interface being adapted to receive inputs from a human user; d) one or more generic syntax editors adapted to receive inputs from a human user to modify the data structure, each of said one or more generic syntax editors corresponding to at least one attribute syntax; and e) a mechanism to modify the target object to include modifications made to the data structure. | 1. A computer system, comprising: a) a management service for a computer network having a plurality of objects of different types, each of said objects having at least one associated attribute with an attribute syntax, a plurality of said attributes having an associated value being of a data type corresponding to the attribute syntax of the associated attribute; b) a data structure adapted to represent one or more attributes and associated values of a target object, said data structure being capable of being modified; c) a user interface for displaying at least a portion of the data structure as an attribute tree structure irrespective of the target object type, said user interface being adapted to receive inputs from a human user; d) one or more generic syntax editors adapted to receive inputs from a human user to modify the data structure, each of said one or more generic syntax editors corresponding to at least one attribute syntax; and e) a mechanism to modify the target object to include modifications made to the data structure. 5. A computer system recited in claim 1, wherein the tree structure is displayed subordinate to a target object. | 0.722772 |
9,466,225 | 4 | 5 | 4. The apparatus according to claim 1 , wherein the processor is further programmed to give a question relating to a keyword to the user; and calculate a correct answer rate based on an answer to the question from the user, to generate a learning history including information associated with the question and the correct answer rate, wherein the score indicating the degree of emphasis of the keyword calculates the score which becomes lower as the correct answer rate increases, in accordance with the learning history. | 4. The apparatus according to claim 1 , wherein the processor is further programmed to give a question relating to a keyword to the user; and calculate a correct answer rate based on an answer to the question from the user, to generate a learning history including information associated with the question and the correct answer rate, wherein the score indicating the degree of emphasis of the keyword calculates the score which becomes lower as the correct answer rate increases, in accordance with the learning history. 5. The apparatus according to claim 4 , wherein the processor is further programmed to estimate an attribute of the keyword, wherein the giving of the question relating to the keyword to the user converts a first character string indicating the keyword into a second character string indicating the attribute, and wherein the generated synthesized speech obtained by synthesizing speech of the keyword synthesizes speech of the second character string. | 0.5 |
9,229,914 | 1 | 3 | 1. A computer program comprising: a computer-readable storage medium, wherein the computer-readable storage medium is not a transitory, propagating signal per se, having stored thereon computer-readable program code that, when executed by a system comprising a processor and a memory, optimizes a layout of an electronic document, the computer-readable storage medium comprising: computer-readable program code that processes the electronic document to identify a plurality of document sections within the electronic document; computer-readable program code that, recursively, combines a plurality of document sections in at least a first page of a modified document and reduces a presentation size of content within the document sections so that the combined document sections fit within the first page of the modified document; and computer-readable program code that, with each recursive combination of document sections: identifies first perceptual features of content of the combined document sections based on the content as presented in an original version of the electronic document, and generates a corresponding first perceptual value derived from the first perceptual features, wherein the first perceptual value is a first perceptual hash value generated by performing a first perceptual hash on the content of the combined document sections as presented in the original version of the electronic document; identifies second perceptual features of content of the combined document sections based on the content as presented in a modified version of the electronic document in which the document sections are combined into the first page, and generates a corresponding second perceptual value derived from the second perceptual features, wherein the second perceptual value is a second perceptual hash value generated by performing a second perceptual hash on the content of the combined document sections as presented in the modified version of the electronic document in which the document sections are combined into the first page; generates a first perceptual delta value by comparing the first perceptual value derived from the first perceptual features to the second perceptual value derived from the second perceptual features; determines whether the first perceptual delta value at least equals a first threshold value; responsive to determining that the first perceptual delta value at least equals the first threshold value, ceases the recursive combination of document sections into the first page; and responsive to determining that the first perceptual delta value does not at least equal the first threshold value, continues the recursive combination of document sections in at least the first page. | 1. A computer program comprising: a computer-readable storage medium, wherein the computer-readable storage medium is not a transitory, propagating signal per se, having stored thereon computer-readable program code that, when executed by a system comprising a processor and a memory, optimizes a layout of an electronic document, the computer-readable storage medium comprising: computer-readable program code that processes the electronic document to identify a plurality of document sections within the electronic document; computer-readable program code that, recursively, combines a plurality of document sections in at least a first page of a modified document and reduces a presentation size of content within the document sections so that the combined document sections fit within the first page of the modified document; and computer-readable program code that, with each recursive combination of document sections: identifies first perceptual features of content of the combined document sections based on the content as presented in an original version of the electronic document, and generates a corresponding first perceptual value derived from the first perceptual features, wherein the first perceptual value is a first perceptual hash value generated by performing a first perceptual hash on the content of the combined document sections as presented in the original version of the electronic document; identifies second perceptual features of content of the combined document sections based on the content as presented in a modified version of the electronic document in which the document sections are combined into the first page, and generates a corresponding second perceptual value derived from the second perceptual features, wherein the second perceptual value is a second perceptual hash value generated by performing a second perceptual hash on the content of the combined document sections as presented in the modified version of the electronic document in which the document sections are combined into the first page; generates a first perceptual delta value by comparing the first perceptual value derived from the first perceptual features to the second perceptual value derived from the second perceptual features; determines whether the first perceptual delta value at least equals a first threshold value; responsive to determining that the first perceptual delta value at least equals the first threshold value, ceases the recursive combination of document sections into the first page; and responsive to determining that the first perceptual delta value does not at least equal the first threshold value, continues the recursive combination of document sections in at least the first page. 3. The computer program product of claim 1 , further comprising: computer-readable program code that, responsive to determining that the first perceptual delta value at least equals the first threshold value, determines whether the first perceptual delta value at least equals a second threshold value; computer-readable program code that, responsive to determining that the first perceptual delta value at least equals the second threshold value, rejects a most recent combination of document sections into the first page of the modified document; and computer-readable program code that, responsive to determining that the first perceptual delta value does not at least equal the second threshold value, outputs at least the first page of the modified document as an output document. | 0.5 |
8,751,418 | 15 | 18 | 15. A system comprising: a processor; and a non-transitory computer readable storage medium storing processor-executable computer program instructions that when executed, cause a computer processor to perform operations comprising: receiving focus information descriptive of a search engine advertising campaign from an advertising campaign manager, the focus information comprising two or more keyword search strings, each keyword search string paired with at least one bid parameter, a relative importance of each keyword search string characterized by the at least one bid parameter; accessing a respective consumption history of each of a plurality of entities in a storage; identifying, at an audience selection system, a training set of entities from the storage by examining each of the respective consumption histories for one or more proxy events, each proxy event comprising a keyword search matching at least one of the two or more keyword search strings described in the focus information; weighting each proxy event according to the at least one bid parameter paired with each proxy event's keyword search string; creating a weighted training set by weighting each entity in the training set according to the proxy event weights of the one or more proxy events found in each entity's respective consumption history; building a behavioral model based on the weighted training set; receiving a specified entity's consumption history; and assessing the suitability of the specific entity for selection by applying the behavioral model to the specified entity's consumption history. | 15. A system comprising: a processor; and a non-transitory computer readable storage medium storing processor-executable computer program instructions that when executed, cause a computer processor to perform operations comprising: receiving focus information descriptive of a search engine advertising campaign from an advertising campaign manager, the focus information comprising two or more keyword search strings, each keyword search string paired with at least one bid parameter, a relative importance of each keyword search string characterized by the at least one bid parameter; accessing a respective consumption history of each of a plurality of entities in a storage; identifying, at an audience selection system, a training set of entities from the storage by examining each of the respective consumption histories for one or more proxy events, each proxy event comprising a keyword search matching at least one of the two or more keyword search strings described in the focus information; weighting each proxy event according to the at least one bid parameter paired with each proxy event's keyword search string; creating a weighted training set by weighting each entity in the training set according to the proxy event weights of the one or more proxy events found in each entity's respective consumption history; building a behavioral model based on the weighted training set; receiving a specified entity's consumption history; and assessing the suitability of the specific entity for selection by applying the behavioral model to the specified entity's consumption history. 18. The system of claim 15 wherein: the bid parameter comprises a maximum bid. | 0.85 |
9,292,737 | 1 | 5 | 1. A payment document classification system, comprising: a communication unit which receives an image of a payment document captured by a mobile device; a preprocessing unit which extracts at least one feature from the image; a comparison unit which compares the at least one extracted feature with at least one known feature of a payment document type to determine a likelihood that the payment document matches the at least one payment document type, wherein the comparison unit is further configured to compare a plurality of extracted features with a plurality of known features in a series, starting with an extracted feature which requires the least computation time of the plurality of extracted features; and a classification unit which classified the payment document as at least one payment document type based on the likelihood that the payment document matches the at least one payment document type. | 1. A payment document classification system, comprising: a communication unit which receives an image of a payment document captured by a mobile device; a preprocessing unit which extracts at least one feature from the image; a comparison unit which compares the at least one extracted feature with at least one known feature of a payment document type to determine a likelihood that the payment document matches the at least one payment document type, wherein the comparison unit is further configured to compare a plurality of extracted features with a plurality of known features in a series, starting with an extracted feature which requires the least computation time of the plurality of extracted features; and a classification unit which classified the payment document as at least one payment document type based on the likelihood that the payment document matches the at least one payment document type. 5. The system of claim 1 , wherein the at least one feature includes one or more horizontal lines and one or more vertical lines. | 0.757519 |
9,545,579 | 3 | 4 | 3. The computer-readable non-transitory medium storing the program according to claim 1 , wherein the judgment involves judging whether there is the commonality on the basis of moving directions among the non-specific characters of which moving directions are not similar to that of the specific character. | 3. The computer-readable non-transitory medium storing the program according to claim 1 , wherein the judgment involves judging whether there is the commonality on the basis of moving directions among the non-specific characters of which moving directions are not similar to that of the specific character. 4. The computer-readable non-transitory medium storing the program according to claim 3 , wherein the judgment involves judging whether there is commonality on the basis of an evaluation that is based on movement of the specific character and movement of the non-specific characters of which moving directions are similar to that of the specific character, and an evaluation that is based on movement of the non-specific characters of which moving directions are not similar to that of the specific character. | 0.5 |
8,612,433 | 1 | 8 | 1. A system to provide a search result, the system comprising: a search term reception unit to receive a search term; a processor to extract information corresponding to at least one of a first personal network associated with the search term and a second personal network different than the first personal network; a search result providing unit to provide a document associated with at least one of the first personal network and the second personal network as a search result of the search term; and a neighbor information extraction unit to extract information corresponding to at least one neighbor having interests corresponding to interests of a user, the information corresponding to the at least one neighbor being based, at least in part, on a profile of the user, the profile being configured using keywords in a document prepared by the user, and the search term being received from the user, the keywords being time-variable and corresponding to keywords having the highest frequency of occurrence in the document. | 1. A system to provide a search result, the system comprising: a search term reception unit to receive a search term; a processor to extract information corresponding to at least one of a first personal network associated with the search term and a second personal network different than the first personal network; a search result providing unit to provide a document associated with at least one of the first personal network and the second personal network as a search result of the search term; and a neighbor information extraction unit to extract information corresponding to at least one neighbor having interests corresponding to interests of a user, the information corresponding to the at least one neighbor being based, at least in part, on a profile of the user, the profile being configured using keywords in a document prepared by the user, and the search term being received from the user, the keywords being time-variable and corresponding to keywords having the highest frequency of occurrence in the document. 8. The system of claim 1 , wherein the search result providing unit is configured to provide the document associated with the at least one of the first personal network and the second personal network as a search result of the search term by arranging the document among documents associated with the search term, based on an order of net association comprising an association with respect to the search term and an association between the user providing the search term and the at least one of the first personal network and the second personal network. | 0.5 |
8,370,275 | 7 | 11 | 7. A computer program product comprising a tangible computer readable recordable storage medium including computer useable program code for identifying one or more inconsistencies between an unstructured document and a back-end fact-base, the computer program product including: computer useable program code for automatically parsing a query document and comparing the document with a back-end fact-base comprising facts relevant to the document; computer useable program code for deriving one or more relevant facts from the query document by identifying one or more fact triples of three categorical elements in the back-end fact-base; computer useable program code for identifying one or more inconsistencies between the one or more relevant facts from the document and the facts stored in the back-end fact-base; and computer useable program code for providing a response to the query document, wherein the response additionally includes the one or more identified inconsistencies. | 7. A computer program product comprising a tangible computer readable recordable storage medium including computer useable program code for identifying one or more inconsistencies between an unstructured document and a back-end fact-base, the computer program product including: computer useable program code for automatically parsing a query document and comparing the document with a back-end fact-base comprising facts relevant to the document; computer useable program code for deriving one or more relevant facts from the query document by identifying one or more fact triples of three categorical elements in the back-end fact-base; computer useable program code for identifying one or more inconsistencies between the one or more relevant facts from the document and the facts stored in the back-end fact-base; and computer useable program code for providing a response to the query document, wherein the response additionally includes the one or more identified inconsistencies. 11. The computer program product of claim 7 , wherein the computer useable program code for comparing the query document with a back-end fact-base comprises computer useable program code for determining one or more relevant facts from the back-end fact-base given the one or more facts contained in the document. | 0.569061 |
9,444,914 | 8 | 10 | 8. A method comprising: providing an information unit to packet controller logic circuits implementing a distribution module, an aggregation module, and multiple interleaved sequences of configurable parsing engines and concatenating modules forming configurable parsing engine and concatenating module pairs: distributing the information unit between multiple interleaved sequences of configurable parsing engines and concatenating modules by applying a load balancing scheme in order to distribute the information unit; processing different portions of the information unit by different configurable parsing engines; and collecting outputs from the multiple interleaved sequences, wherein the processing comprises processing, by at least one configurable parsing engine, a portion of the information unit in response to a previous processing result provided from a previous configurable parsing engine and generating a current processing result to be used by a next configurable parsing engine, wherein the multiple interleaved sequences include a first interleaved sequence having at least two sequential configurable parsing engine and concatenating module pairs, and wherein at least a portion of the information unit is processed sequentially by the at least two configurable parsing engine and concatenating module pairs. | 8. A method comprising: providing an information unit to packet controller logic circuits implementing a distribution module, an aggregation module, and multiple interleaved sequences of configurable parsing engines and concatenating modules forming configurable parsing engine and concatenating module pairs: distributing the information unit between multiple interleaved sequences of configurable parsing engines and concatenating modules by applying a load balancing scheme in order to distribute the information unit; processing different portions of the information unit by different configurable parsing engines; and collecting outputs from the multiple interleaved sequences, wherein the processing comprises processing, by at least one configurable parsing engine, a portion of the information unit in response to a previous processing result provided from a previous configurable parsing engine and generating a current processing result to be used by a next configurable parsing engine, wherein the multiple interleaved sequences include a first interleaved sequence having at least two sequential configurable parsing engine and concatenating module pairs, and wherein at least a portion of the information unit is processed sequentially by the at least two configurable parsing engine and concatenating module pairs. 10. The method according to claim 8 , comprising configuring each configurable parsing engine by providing to the configurable parsing engine processing metadata indicative of a manner in which the information unit portion should be processed by the configurable parsing engine. | 0.517361 |
9,710,961 | 3 | 7 | 3. A method of claim 1 , further comprising: determining display information about the user interface of the device; determining detail capacity associated with a total amount of detail that can be presented in the user interface; and allocating the detail capacity among the objects to be rendered in the geographic map according to the prioritization, wherein the rendering is performed differentially according to the allocation. | 3. A method of claim 1 , further comprising: determining display information about the user interface of the device; determining detail capacity associated with a total amount of detail that can be presented in the user interface; and allocating the detail capacity among the objects to be rendered in the geographic map according to the prioritization, wherein the rendering is performed differentially according to the allocation. 7. A method of claim 3 , wherein the geographic map is partitioned into sections and the detail capacity is determined individually for each section. | 0.682979 |
6,081,804 | 9 | 10 | 9. A method for performing rapid, multi-dimensional word searches comprising: storing one or more objects, the objects comprising a plurality of words; specifying a search query and a search space, the search query comprising a multi-dimensional combination of words and attributes, the search space identifying one or more objects; creating a data structure based on the search query, the data structure comprising: a lead character table for partially recognizing the words contained in the search query; a word table for storing at least the words contained in the search query; an operator table for storing in post-fix order at least the words contained in the search query and the attributes specifying one or more boolean operators contained in the search query; and a granularity table for storing at least the attributes specifying one or more granularity restrictions contained in the search query, the granularity restrictions requiring the words to appear within one or more granularity boundaries; creating a list of target objects based on the data structure and the search space, the list of target objects consisting of objects from the search space which satisfy the search query; and displaying the list of target objects. | 9. A method for performing rapid, multi-dimensional word searches comprising: storing one or more objects, the objects comprising a plurality of words; specifying a search query and a search space, the search query comprising a multi-dimensional combination of words and attributes, the search space identifying one or more objects; creating a data structure based on the search query, the data structure comprising: a lead character table for partially recognizing the words contained in the search query; a word table for storing at least the words contained in the search query; an operator table for storing in post-fix order at least the words contained in the search query and the attributes specifying one or more boolean operators contained in the search query; and a granularity table for storing at least the attributes specifying one or more granularity restrictions contained in the search query, the granularity restrictions requiring the words to appear within one or more granularity boundaries; creating a list of target objects based on the data structure and the search space, the list of target objects consisting of objects from the search space which satisfy the search query; and displaying the list of target objects. 10. The computer system of claim 9 wherein the search query limits the word search of the search space to one or more specified fields within the objects in the search space. | 0.5 |
8,856,236 | 33 | 37 | 33. A method of providing service to first party via a telephony connection, the method comprising the steps of: providing indication that a second party using an instant communications client desires to communicate with the first party using a messaging response system; providing communications among the first party and the second party, wherein the first party engages in communication using audio information via the telephony connection; receiving information from the first party relating to how charges associated with the use of the service are to be billed, wherein an account of the first party is identified by both a screen name of the first party and a service provider identifier associated with a service provider of the first party, and wherein the service provider is one of a plurality of service providers that can be used to access the messaging response system; and providing to the first party audio information corresponding to textual information from the second party, wherein an aspect of providing the audio information corresponding to the textual information is affected by preference information pertaining to at least one of the first party, the second party and the instant communications client and the aspect relates to a voice characteristic imparted to synthesized speech in the audio information. | 33. A method of providing service to first party via a telephony connection, the method comprising the steps of: providing indication that a second party using an instant communications client desires to communicate with the first party using a messaging response system; providing communications among the first party and the second party, wherein the first party engages in communication using audio information via the telephony connection; receiving information from the first party relating to how charges associated with the use of the service are to be billed, wherein an account of the first party is identified by both a screen name of the first party and a service provider identifier associated with a service provider of the first party, and wherein the service provider is one of a plurality of service providers that can be used to access the messaging response system; and providing to the first party audio information corresponding to textual information from the second party, wherein an aspect of providing the audio information corresponding to the textual information is affected by preference information pertaining to at least one of the first party, the second party and the instant communications client and the aspect relates to a voice characteristic imparted to synthesized speech in the audio information. 37. The method of claim 33 further comprising: receiving from the first party an indication that a mode of communication is acceptable to the first party. | 0.586022 |
7,769,339 | 1 | 2 | 1. A computer-implemented method comprising: applying an essay to a plurality of trait models with a computer; identifying a plurality of features associated with a vocabulary usage trait of the plurality of trait models with the computer; identifying multiple features associated with a discourse trait of the plurality of trait models with the computer, wherein the identifying multiple features comprises identifying a thesis, a main idea, a supporting idea, and a conclusion; automatically determining a plurality of trait scores based on the plurality of trait models with the computer, each trait score generated from a respective trait model; and assigning a score to the essay with the computer, based on the plurality of trait scores. | 1. A computer-implemented method comprising: applying an essay to a plurality of trait models with a computer; identifying a plurality of features associated with a vocabulary usage trait of the plurality of trait models with the computer; identifying multiple features associated with a discourse trait of the plurality of trait models with the computer, wherein the identifying multiple features comprises identifying a thesis, a main idea, a supporting idea, and a conclusion; automatically determining a plurality of trait scores based on the plurality of trait models with the computer, each trait score generated from a respective trait model; and assigning a score to the essay with the computer, based on the plurality of trait scores. 2. The method of claim 1 , further comprising: determining a content vector score based on a plurality of cosine values associated with the vocabulary usage trait; identifying a relatively high cosine value of the plurality of cosine values; and identifying a vector length based on a plurality of vectors associated with the vocabulary usage trait. | 0.5 |
8,358,843 | 1 | 2 | 1. A method comprising: using one or more computers, obtaining digital image information, wherein the digital image information corresponds to a digital image, and wherein the digital image is from a digital photograph taken by a portable electronic device; using one or more computers, utilizing one or more character recognition techniques, determining a URI or URL included within the digital image; and wirelessly transmitting the URI or URI to the portable electronic device. | 1. A method comprising: using one or more computers, obtaining digital image information, wherein the digital image information corresponds to a digital image, and wherein the digital image is from a digital photograph taken by a portable electronic device; using one or more computers, utilizing one or more character recognition techniques, determining a URI or URL included within the digital image; and wirelessly transmitting the URI or URI to the portable electronic device. 2. The method of claim 1 , comprising obtaining the digital image information, wherein the digital image is from a digital photograph taken by a cell phone camera or a camera phone. | 0.65458 |
8,375,352 | 15 | 16 | 15. The software tool of claim 14 wherein the list of software functions includes for each software function: a name and a description; a feature name to which the software function belongs, where the feature name is selected from the list of product features residing in the relational database on the server computer; a location where source code for the software function can be found; a list of input data items to the software function, where the list of input data items is selected from a list of candidate input data items which is taken from the data dictionary residing in the relational database on the server computer; and a list of output data items from the software function, where the list of output data items is selected from a list of candidate output data items which is taken from the data dictionary residing in the relational database on the server computer. | 15. The software tool of claim 14 wherein the list of software functions includes for each software function: a name and a description; a feature name to which the software function belongs, where the feature name is selected from the list of product features residing in the relational database on the server computer; a location where source code for the software function can be found; a list of input data items to the software function, where the list of input data items is selected from a list of candidate input data items which is taken from the data dictionary residing in the relational database on the server computer; and a list of output data items from the software function, where the list of output data items is selected from a list of candidate output data items which is taken from the data dictionary residing in the relational database on the server computer. 16. The software tool of claim 15 further comprising approval templates for approving items in the list of product features, the list of software functions, the data dictionary, the glossary, and the acronym library, where approval may only be provided by users with a designated approver role in the software tool. | 0.5 |
8,315,879 | 9 | 10 | 9. The computer-readable medium of claim 8 further comprising: computer usable program code for creating the document identifier; and computer usable program code for receiving an indication that a change should be made to a document identified by the document identifier. | 9. The computer-readable medium of claim 8 further comprising: computer usable program code for creating the document identifier; and computer usable program code for receiving an indication that a change should be made to a document identified by the document identifier. 10. The computer-readable medium of claim 9 , wherein the indication is selected from the group consisting of an alphanumeric text based indication and an audio indication. | 0.5 |
4,689,817 | 1 | 7 | 1. A microprocessor controlled speech synthesizer for generating the audio information of a set of characters which includes a first subset of lower case letters and a second subset of upper case capital letters so that the operator can audibly distinguish between upper and lower case letters from an external input, said synthesizer comprising; a microprocessor unit connected to a first memory for the storage of speech data and to a second memory for the storage of externally originated input characters, said microprocessor unit comprising control means responsive to said speech data from the first memory for forming a speech pattern corresponding to said input characters; a speech generator connected to said first memory and controlled by the control means of said microprocessor for producing audio signals representing said set of characters; said microprocessor unit further comprising a character recognition means connected to said first and second memories and to said speech generator for recognizing from the externally originated input characters those characters which belong to said second subset of upper case capital letters and for introducing a first modification in the speech pattern for said characters belonging to the second subset; said first modification comprising a changing of at least one pitch component or a changing of a voice characterizing component of the speech pattern while maintaining the identity of the second subset of upper case capital letters; said microprocessor further comprising a position determining means for determing the position of at least one letter of a word made up of characters presented and for introducing a second modification in the speech pattern for said letter while maintaining its identity, said second modification comprising a modification of a pitch component and/or a voice characterizing component of the speech pattern. | 1. A microprocessor controlled speech synthesizer for generating the audio information of a set of characters which includes a first subset of lower case letters and a second subset of upper case capital letters so that the operator can audibly distinguish between upper and lower case letters from an external input, said synthesizer comprising; a microprocessor unit connected to a first memory for the storage of speech data and to a second memory for the storage of externally originated input characters, said microprocessor unit comprising control means responsive to said speech data from the first memory for forming a speech pattern corresponding to said input characters; a speech generator connected to said first memory and controlled by the control means of said microprocessor for producing audio signals representing said set of characters; said microprocessor unit further comprising a character recognition means connected to said first and second memories and to said speech generator for recognizing from the externally originated input characters those characters which belong to said second subset of upper case capital letters and for introducing a first modification in the speech pattern for said characters belonging to the second subset; said first modification comprising a changing of at least one pitch component or a changing of a voice characterizing component of the speech pattern while maintaining the identity of the second subset of upper case capital letters; said microprocessor further comprising a position determining means for determing the position of at least one letter of a word made up of characters presented and for introducing a second modification in the speech pattern for said letter while maintaining its identity, said second modification comprising a modification of a pitch component and/or a voice characterizing component of the speech pattern. 7. A device as claimed in claim 1, characterized in that said second modification of a pitch component of the speech pattern comprises a pitch decrease within the duration of the speech pattern with respect to a mean pitch component of the speech pattern. | 0.526022 |
9,558,280 | 33 | 36 | 33. A non-transitory computer-readable medium coupled to one or more processors having instructions stored thereon that, when executed by said one or more processors, causes said one or more processors to perform operations comprising: receiving, from a client device operated by a user, a request for a content item; in response to said request, identifying content items available to be sent to said client device; determining one or more designated geographic locations for each of the identified content items; determining one or more contacts of said user, said determined one or more contacts being members of a social network of said user; for each of the identified content items: determining a score for the content item based on a number of tagging actions that were performed by the user's contacts at the determined designated geographic location for the identified content item, wherein said tagging actions mark an association of a person with a particular geographic location; selecting, from the identified content items, a particular content item to be sent to the client device based on the scores; determining that a timestamp associated with at least one of the tagging actions performed at the designated geographic location for the particular content item is within a time period specified by a provider of the particular content item, the timestamp indicating a time of the tagging action; constructing, based on the determination that the timestamp is within the time period, an annotation that identifies at least one of the user's contacts with the tagging action corresponding to the designated geographic location and indicates the time of the tagging action based on the timestamp associated with the at least one location record; and sending said annotation to said client device. | 33. A non-transitory computer-readable medium coupled to one or more processors having instructions stored thereon that, when executed by said one or more processors, causes said one or more processors to perform operations comprising: receiving, from a client device operated by a user, a request for a content item; in response to said request, identifying content items available to be sent to said client device; determining one or more designated geographic locations for each of the identified content items; determining one or more contacts of said user, said determined one or more contacts being members of a social network of said user; for each of the identified content items: determining a score for the content item based on a number of tagging actions that were performed by the user's contacts at the determined designated geographic location for the identified content item, wherein said tagging actions mark an association of a person with a particular geographic location; selecting, from the identified content items, a particular content item to be sent to the client device based on the scores; determining that a timestamp associated with at least one of the tagging actions performed at the designated geographic location for the particular content item is within a time period specified by a provider of the particular content item, the timestamp indicating a time of the tagging action; constructing, based on the determination that the timestamp is within the time period, an annotation that identifies at least one of the user's contacts with the tagging action corresponding to the designated geographic location and indicates the time of the tagging action based on the timestamp associated with the at least one location record; and sending said annotation to said client device. 36. The computer-readable medium of claim 33 , wherein said computer-readable medium coupled to said one or more processors has further instructions stored thereon that, when executed by said one or more processors, cause said one or more processors to perform operations further comprising: receiving a location tag, wherein the location tag includes the tagging action and a user ID of the person making the tagging action; and storing a location record with data representing said location tag in a database. | 0.846177 |
9,633,653 | 17 | 20 | 17. One or more non-transitory computer-readable media maintaining instructions executable by one or more processors to perform operations comprising: determining an n-gram comprising a sequence of one or more words based at least in part on parsing a plurality of digital works, wherein the plurality of digital works are associated with a particular subject matter category; associating a first probability of occurrence with the n-gram based at least in part on a frequency of occurrence of the n-gram in the plurality of digital works; and determining language model difference information based at least in part on the first probability of occurrence associated with the n-gram differs from a second probability of occurrence of the n-gram in a base language model by more than a threshold amount; and determining a word based at least in part on a captured utterance, the base language model and the language model difference information. | 17. One or more non-transitory computer-readable media maintaining instructions executable by one or more processors to perform operations comprising: determining an n-gram comprising a sequence of one or more words based at least in part on parsing a plurality of digital works, wherein the plurality of digital works are associated with a particular subject matter category; associating a first probability of occurrence with the n-gram based at least in part on a frequency of occurrence of the n-gram in the plurality of digital works; and determining language model difference information based at least in part on the first probability of occurrence associated with the n-gram differs from a second probability of occurrence of the n-gram in a base language model by more than a threshold amount; and determining a word based at least in part on a captured utterance, the base language model and the language model difference information. 20. The one or more non-transitory computer-readable media as recited in claim 17 , further comprising generating the base language model based at least in part on at least one of a webpage, an electronic book, a news feed, a social network site, a microblog, or a closed captioning feed. | 0.5 |
9,020,962 | 19 | 20 | 19. The system of claim 13 , wherein the executable and operational data are further effective to cause the one or more processors to evaluate similarity of the candidate articles to the principal article by evaluating similarity of out-links of the principal article and the candidate articles. | 19. The system of claim 13 , wherein the executable and operational data are further effective to cause the one or more processors to evaluate similarity of the candidate articles to the principal article by evaluating similarity of out-links of the principal article and the candidate articles. 20. The system of claim 19 , wherein the executable and operational data are further effective to cause the one or more processors to evaluate similarity of out-links of the principal article and the candidate articles by evaluating similarity of both link text and link destination for the out-links of the principal article and the candidate articles. | 0.5 |
8,175,389 | 12 | 13 | 12. The computer-readable medium of claim 10 wherein a relative geometry of a stroke comprises a relative position and a proportional size of said stroke relative to other strokes of a symbol. | 12. The computer-readable medium of claim 10 wherein a relative geometry of a stroke comprises a relative position and a proportional size of said stroke relative to other strokes of a symbol. 13. The computer-readable medium of claim 12 wherein said relative position comprises a relative horizontal position and a relative vertical position of said stroke relative to said other strokes of said symbol. | 0.5 |
9,665,276 | 17 | 19 | 17. A non-transitory computer-readable storage medium encoded with instructions that, when executed, causes at least one processor of a computing device to perform operations comprising: outputting, for display, a graphical keyboard comprising a plurality of keys; receiving an indication of a continuous gesture comprising a first path in a first direction from a first key of the plurality of keys to a second key of the plurality of keys; determining that the continuous gesture comprises a second path from the second key that ends at the first key and retraces at least a portion of the first path from the first key to the second key, wherein the second path is in a second direction that is substantially reverse to the first direction; and responsive to determining that the second path ends at the first key and retraces at least the portion of the first path from the first key back to the second key in the second direction that is substantially reverse to the first direction, and that the continuous gesture further comprises a third path to a third key, outputting, for display, a character string a third character subsequent to the first character and without the second character output between the first character and third character. | 17. A non-transitory computer-readable storage medium encoded with instructions that, when executed, causes at least one processor of a computing device to perform operations comprising: outputting, for display, a graphical keyboard comprising a plurality of keys; receiving an indication of a continuous gesture comprising a first path in a first direction from a first key of the plurality of keys to a second key of the plurality of keys; determining that the continuous gesture comprises a second path from the second key that ends at the first key and retraces at least a portion of the first path from the first key to the second key, wherein the second path is in a second direction that is substantially reverse to the first direction; and responsive to determining that the second path ends at the first key and retraces at least the portion of the first path from the first key back to the second key in the second direction that is substantially reverse to the first direction, and that the continuous gesture further comprises a third path to a third key, outputting, for display, a character string a third character subsequent to the first character and without the second character output between the first character and third character. 19. The non-transitory computer-readable storage medium of claim 17 , encoded with instructions that, when executed, causes the at least one processor of the computing device to perform operations comprising: comparing at least the first character and the second character to a language model. | 0.673719 |
8,423,424 | 1 | 14 | 1. A method programmed in a non-transitory memory of a device comprising: a. automatically accessing a web page; b. automatically analyzing web page content of the web page; c. automatically fact checking the web page content with the device by comparing the web page content with source information to determine the factual accuracy of the web page content, including computing a source result value based on source quantities and source ratings, wherein the source result value is used to determine a result of the fact checking, wherein fact checking includes a first fact check and a second fact check, wherein the first fact check and the second fact check each utilize a different set of fact checking criteria; and d. automatically indicating a status of the web page content in real-time based on the result of the comparison of the web page content with the source information. | 1. A method programmed in a non-transitory memory of a device comprising: a. automatically accessing a web page; b. automatically analyzing web page content of the web page; c. automatically fact checking the web page content with the device by comparing the web page content with source information to determine the factual accuracy of the web page content, including computing a source result value based on source quantities and source ratings, wherein the source result value is used to determine a result of the fact checking, wherein fact checking includes a first fact check and a second fact check, wherein the first fact check and the second fact check each utilize a different set of fact checking criteria; and d. automatically indicating a status of the web page content in real-time based on the result of the comparison of the web page content with the source information. 14. The method of claim 1 wherein fact checking is performed using cloud computing. | 0.934646 |
8,253,694 | 19 | 23 | 19. A computer-implemented method comprising: displaying consonants of an Indic language script in corresponding first objects in a user interface, wherein the first objects are arranged circumferentially to define an interior region in which no other objects displaying characters are displayed; in response to detecting a first single selection of a first object, displaying, within the interior region while continuing to display the first objects, second letters in corresponding second objects, wherein each of the second letters is a combination, according to a language rule of the Indic language script, of the consonant displayed in the first object and a dependent vowel marker in the Indic language script, wherein the combination of the consonant and a dependent vowel marker is a single letter in the Indic language script; and in response to detecting a subsequent selection of one of the selected first object or one of the displayed second objects, displaying the letter corresponding to the subsequently selected object in another user interface. | 19. A computer-implemented method comprising: displaying consonants of an Indic language script in corresponding first objects in a user interface, wherein the first objects are arranged circumferentially to define an interior region in which no other objects displaying characters are displayed; in response to detecting a first single selection of a first object, displaying, within the interior region while continuing to display the first objects, second letters in corresponding second objects, wherein each of the second letters is a combination, according to a language rule of the Indic language script, of the consonant displayed in the first object and a dependent vowel marker in the Indic language script, wherein the combination of the consonant and a dependent vowel marker is a single letter in the Indic language script; and in response to detecting a subsequent selection of one of the selected first object or one of the displayed second objects, displaying the letter corresponding to the subsequently selected object in another user interface. 23. The method of claim 19 , wherein the other user interface is a text box. | 0.769697 |
6,134,559 | 1 | 3 | 1. A method for integrating objects defined by different type systems into a single integrated object oriented system, said method comprising the steps of: providing an integrated object oriented system comprising, an integrated type system that supports a superset of features from a plurality of foreign object systems, said foreign object systems comprising a plurality of foreign objects defined by foreign type systems that are different from said integrated type system, said foreign objects including at least one method; receiving into said integrated object oriented system a plurality of said foreign objects from said different foreign object systems; converting said foreign objects into uniform object model objects defined by said integrated type system; and executing said foreign objects as uniform object model objects in a run time environment without loss of features provided by said foreign objects. | 1. A method for integrating objects defined by different type systems into a single integrated object oriented system, said method comprising the steps of: providing an integrated object oriented system comprising, an integrated type system that supports a superset of features from a plurality of foreign object systems, said foreign object systems comprising a plurality of foreign objects defined by foreign type systems that are different from said integrated type system, said foreign objects including at least one method; receiving into said integrated object oriented system a plurality of said foreign objects from said different foreign object systems; converting said foreign objects into uniform object model objects defined by said integrated type system; and executing said foreign objects as uniform object model objects in a run time environment without loss of features provided by said foreign objects. 3. The method as set forth in claim 1, further comprising the step of exposing said uniform object model objects including the steps of: receiving a request in said integrated object oriented system for a foreign object; and presenting, in response to said request, a uniform object model object, so as to provide a uniform view of all objects accessible in said integrated object oriented system. | 0.5 |
4,374,625 | 1 | 20 | 1. An automatic word ending text recorder of the kind having: text display means to display a sequence of text characters in intelligible form in response to character and function identifying signals, keyboard means including a plurality of alphanumeric, symbol and function keys to produce a keycode signal unique to any operator-actuated key, and decoding means responsive to keycode signals from said keyboard means to produce said character and function identifying signals, wherein the improvement comprises: word ending means within said decoding means producing one of at least two groups of one or more character identifying signals in response to actuation of a selected key on said keyboard, each group of character identifying signals representing a different word ending and wherein said word ending means includes means for selecting among said groups depending upon identification of one or more key actuations prior to actuation of said selected key. | 1. An automatic word ending text recorder of the kind having: text display means to display a sequence of text characters in intelligible form in response to character and function identifying signals, keyboard means including a plurality of alphanumeric, symbol and function keys to produce a keycode signal unique to any operator-actuated key, and decoding means responsive to keycode signals from said keyboard means to produce said character and function identifying signals, wherein the improvement comprises: word ending means within said decoding means producing one of at least two groups of one or more character identifying signals in response to actuation of a selected key on said keyboard, each group of character identifying signals representing a different word ending and wherein said word ending means includes means for selecting among said groups depending upon identification of one or more key actuations prior to actuation of said selected key. 20. The apparatus of claim 1 wherein said word ending means includes first means responsive to actuation of a function key, subsequent to actuation of said selected key, to clear a register, a hyphen flag register, means to set said hyphen flag register on detection of actuation of a hyphen key, means to reset said hyphen flag register on detection of an alpha key, means responsive to detection of a function key actuation to inhibit operation of said first means. | 0.605574 |
7,831,922 | 1 | 9 | 1. A method of processing pointer input, comprising: providing a transparent first graphical user interface overlaying a second graphical user interface; receiving pointer input in a handwriting area corresponding to the transparent first graphical user interface; displaying a guideline at a first position when a pen contacts a first position in the handwriting area; displaying the guideline at a second position only when the pen is lifted from the first position and subsequently contacts a second position in the handwriting area a threshold distance from the first position, wherein the threshold distance depends upon a direction of movement of the pen from the first position to the second position; displaying handwriting objects represented by the pointer input in the transparent first graphical user interface; recognizing text from the pointer input; and providing the recognized text to a software application. | 1. A method of processing pointer input, comprising: providing a transparent first graphical user interface overlaying a second graphical user interface; receiving pointer input in a handwriting area corresponding to the transparent first graphical user interface; displaying a guideline at a first position when a pen contacts a first position in the handwriting area; displaying the guideline at a second position only when the pen is lifted from the first position and subsequently contacts a second position in the handwriting area a threshold distance from the first position, wherein the threshold distance depends upon a direction of movement of the pen from the first position to the second position; displaying handwriting objects represented by the pointer input in the transparent first graphical user interface; recognizing text from the pointer input; and providing the recognized text to a software application. 9. The method of processing pointer input recited in claim 1 , further comprising: deleting the handwriting guideline when the pen has beyond a threshold distance above the handwriting area. | 0.731638 |
7,650,286 | 1 | 7 | 1. A system for using a computer to identify a matching resume for a job description, comprising: a memory device resident in the computer; and a processor disposed in communication with the memory device, the processor configured to: receive the job description that includes at least one job requirement, each said at least one job requirement comprising a required skill or experience-related phrase and a required term of experience for the required skill or experience-related phrase; store the job description; receive at least one resume; parse each said at least one resume to: locate at least one skill or experience-related phrase in the resume; determine an experience range for each said at least one skill or experience-related phrase by examining a use of each said at least one skill or experience-related phrase in the resume; and compute a term of experience for each said at least one skill or experience-related phrase based on the experience range, wherein the term of experience for each said at least one skill or experience-related phrase is a summation of the term of experience for each occurrence of the phrase associated with a different experience range, wherein said at least one skill or experience-related phrase includes the required skill or experience-related phrase for at least one of said at least one job requirement, wherein each resume summarizes a candidate's career and qualifications, and wherein each resume conveys personal and business-related characteristics that the candidate believes to be relevant to a prospective employer; store each said at least one resume; compute, for each said at least one resume, the term of experience for the required skill or experience-related phrase for each said at least one job requirement; and determine whether each said at least one resume is the matching resume that satisfies the job description. | 1. A system for using a computer to identify a matching resume for a job description, comprising: a memory device resident in the computer; and a processor disposed in communication with the memory device, the processor configured to: receive the job description that includes at least one job requirement, each said at least one job requirement comprising a required skill or experience-related phrase and a required term of experience for the required skill or experience-related phrase; store the job description; receive at least one resume; parse each said at least one resume to: locate at least one skill or experience-related phrase in the resume; determine an experience range for each said at least one skill or experience-related phrase by examining a use of each said at least one skill or experience-related phrase in the resume; and compute a term of experience for each said at least one skill or experience-related phrase based on the experience range, wherein the term of experience for each said at least one skill or experience-related phrase is a summation of the term of experience for each occurrence of the phrase associated with a different experience range, wherein said at least one skill or experience-related phrase includes the required skill or experience-related phrase for at least one of said at least one job requirement, wherein each resume summarizes a candidate's career and qualifications, and wherein each resume conveys personal and business-related characteristics that the candidate believes to be relevant to a prospective employer; store each said at least one resume; compute, for each said at least one resume, the term of experience for the required skill or experience-related phrase for each said at least one job requirement; and determine whether each said at least one resume is the matching resume that satisfies the job description. 7. The system of claim 1 , wherein the job description comprises a document in an electronic format. | 0.867725 |
9,398,030 | 7 | 12 | 7. A system comprising: at least a memory and a processor to implement a web application, the web application configured to perform operations comprising: receiving a call from a third party object that requests a domain context; ascertaining the domain context of the third party object; returning the domain context to the third party object; requiring the third party object to include its associated domain context in subsequent calls that the third party object makes; receiving a subsequent call from the third party object; ascertaining, from the subsequent call, the domain context of the third party object; and making a domain context-based decision based on the ascertained domain context by refusing to allow the subsequent call to execute if the third party object's ascertained domain context does not match a target window domain context or allowing the subsequent call to execute if the third party object's ascertained domain context matches the target window domain context. | 7. A system comprising: at least a memory and a processor to implement a web application, the web application configured to perform operations comprising: receiving a call from a third party object that requests a domain context; ascertaining the domain context of the third party object; returning the domain context to the third party object; requiring the third party object to include its associated domain context in subsequent calls that the third party object makes; receiving a subsequent call from the third party object; ascertaining, from the subsequent call, the domain context of the third party object; and making a domain context-based decision based on the ascertained domain context by refusing to allow the subsequent call to execute if the third party object's ascertained domain context does not match a target window domain context or allowing the subsequent call to execute if the third party object's ascertained domain context matches the target window domain context. 12. The one or more computer-readable storage media as recited in claim 7 , wherein the receiving the call that requests the domain context is performed by a web browser. | 0.658635 |
8,805,670 | 1 | 10 | 1. A method for language translation comprising: providing program code to launch a translation window associated with a primary window; providing a link to the program code, wherein when the primary window is displayed on a screen and the user selects the link, the program code causes the translation window to open on the screen in combination with the primary window; in the translation window, indicating input information in a first language; translating the input information from the first language to information in a second language; in the translation window, displaying the information in the second language; and permitting scrolling of the primary window independently from the translation window. | 1. A method for language translation comprising: providing program code to launch a translation window associated with a primary window; providing a link to the program code, wherein when the primary window is displayed on a screen and the user selects the link, the program code causes the translation window to open on the screen in combination with the primary window; in the translation window, indicating input information in a first language; translating the input information from the first language to information in a second language; in the translation window, displaying the information in the second language; and permitting scrolling of the primary window independently from the translation window. 10. The method of claim 1 wherein the translating the input information from the first language to information in a second language comprises: querying a first source for the information in the second language, wherein the first source is a different from a second source for which a document is being displayed in the primary window. | 0.5 |
7,639,257 | 17 | 19 | 17. A computer-implemented method for constructing a text document, the method comprising: performing operations by a programmable processor of a first computer, comprising: receiving user input at the first computer selecting a character for insertion into a text document; identifying in a memory of the first computer a glyphlet representing the selected character, the glyphlet being a data structure including both a set of one or more character attributes defining semantic information of the selected character and a set of one or more glyph attributes defining appearance information for a glyph representative of the selected character, the glyph attributes including all the information necessary to render a glyph image of the glyph; inserting the character into the text document by inserting a reference to the identified glyphlet into the text document, where the reference can be used to access the sets of character and glyph attributes from the glyphlet for the character selected by the user input; and displaying the character in the text document, the displayed character being rendered from the glyph attributes. | 17. A computer-implemented method for constructing a text document, the method comprising: performing operations by a programmable processor of a first computer, comprising: receiving user input at the first computer selecting a character for insertion into a text document; identifying in a memory of the first computer a glyphlet representing the selected character, the glyphlet being a data structure including both a set of one or more character attributes defining semantic information of the selected character and a set of one or more glyph attributes defining appearance information for a glyph representative of the selected character, the glyph attributes including all the information necessary to render a glyph image of the glyph; inserting the character into the text document by inserting a reference to the identified glyphlet into the text document, where the reference can be used to access the sets of character and glyph attributes from the glyphlet for the character selected by the user input; and displaying the character in the text document, the displayed character being rendered from the glyph attributes. 19. The method of claim 17 , wherein: the reference to the identified glyphlet includes one or more in-band values defined in an encoding standard. | 0.525806 |
7,502,783 | 21 | 23 | 21. A method as recited in claim 19 , wherein an initial set of topics is pre-defined. | 21. A method as recited in claim 19 , wherein an initial set of topics is pre-defined. 23. A method as recited in claim 21 , further comprising: accepting from a user a rating for a particular attachment between a particular topic of the set of topics and a particular information item, such that a plurality of attachments between the particular topic and the particular information item can have different ratings. | 0.5 |
7,716,470 | 20 | 21 | 20. The system of claim 19 , wherein the control unit compiles the program written in the high-level programming language into a bytecode, translates the bytecode into a program written in the low-level programming language, and tokenizes the program written in the low-level programming language into the boot code. | 20. The system of claim 19 , wherein the control unit compiles the program written in the high-level programming language into a bytecode, translates the bytecode into a program written in the low-level programming language, and tokenizes the program written in the low-level programming language into the boot code. 21. The system of claim 20 , wherein the control unit gathers compilation information while the control unit compiles the program written in the high-level language into the bytecode and generates the certification such that the certificate includes the compilation information as the annotation defining the proof of security for both (i) one or more blocks of bytecode generated from the high-level programming language and (ii) one or more corresponding blocks of the boot code resulting from the translation of the one or more blocks of the bytecode into the program written in the low-level programming language and subsequent tokenization of the program written in the low-level programming language. | 0.5 |
8,311,838 | 1 | 9 | 1. A method for processing a voice input provided in response to a prompt, comprising: at an electronic device with at least one processor and memory: automatically providing a sequence of prompts, wherein each prompt is associated with a respective time period of a plurality of time periods; receiving a voice input while a prompt of the sequence of prompts is being provided; identifying a characteristic time associated with the received voice input; identifying a time period of the plurality of time periods that includes the characteristic time; and applying the received voice input to a respective prompt of the sequence of prompts associated with the identified time period. | 1. A method for processing a voice input provided in response to a prompt, comprising: at an electronic device with at least one processor and memory: automatically providing a sequence of prompts, wherein each prompt is associated with a respective time period of a plurality of time periods; receiving a voice input while a prompt of the sequence of prompts is being provided; identifying a characteristic time associated with the received voice input; identifying a time period of the plurality of time periods that includes the characteristic time; and applying the received voice input to a respective prompt of the sequence of prompts associated with the identified time period. 9. The method of claim 1 , wherein identifying a characteristic time further comprises: identifying a characteristic time stamp during which the voice input is received. | 0.669922 |
7,707,160 | 24 | 28 | 24. The computer system of claim 12 wherein the query answering module is operable to facilitate transmission of the factual knowledge in response to a request transmitted from a first one of the computers to a second one of the computers. | 24. The computer system of claim 12 wherein the query answering module is operable to facilitate transmission of the factual knowledge in response to a request transmitted from a first one of the computers to a second one of the computers. 28. The computer system of claim 24 wherein the network is the internet. | 0.856574 |
7,800,620 | 1 | 8 | 1. A computer-implemented method of graphics processing in a computer system that includes a processor and memory, the method comprising: receiving a parallel processing request at a parallel programming interface, the parallel processing request comprising an evaluation request of one or more parallel operations on one or more input arrays, wherein the parallel processing request is initially represented as a first expression tree, the first expression tree comprising two or more texture coordinate operations, wherein one or more nodes of the first expression tree comprise program objects that provide shader code corresponding to a graphics environment; with the computer system, composing the two or more texture coordinate operations to form a second expression tree having a composed texture read operation, wherein the composed texture read operation is a leaf of the second expression tree; with the computer system, creating one or more shader programs formed according to resource constraints of the graphics environment, wherein the shader programs comprise at least a portion of the shader code provided by one or more of the program objects; with the computer system, invoking the one or more shader programs in the graphics environment; receiving an output responsive to invoking the one or more shader programs in the graphics environment; and returning the output as a response to the evaluation request. | 1. A computer-implemented method of graphics processing in a computer system that includes a processor and memory, the method comprising: receiving a parallel processing request at a parallel programming interface, the parallel processing request comprising an evaluation request of one or more parallel operations on one or more input arrays, wherein the parallel processing request is initially represented as a first expression tree, the first expression tree comprising two or more texture coordinate operations, wherein one or more nodes of the first expression tree comprise program objects that provide shader code corresponding to a graphics environment; with the computer system, composing the two or more texture coordinate operations to form a second expression tree having a composed texture read operation, wherein the composed texture read operation is a leaf of the second expression tree; with the computer system, creating one or more shader programs formed according to resource constraints of the graphics environment, wherein the shader programs comprise at least a portion of the shader code provided by one or more of the program objects; with the computer system, invoking the one or more shader programs in the graphics environment; receiving an output responsive to invoking the one or more shader programs in the graphics environment; and returning the output as a response to the evaluation request. 8. The method of claim 1 wherein a resource constraint of the graphics environment comprises a constraint on the number of texture reads in a shader program. | 0.651111 |
8,150,736 | 32 | 33 | 32. The computing device of claim 26 , wherein the retrieval is performed through a SQL procedure to access a database that includes the version of the marketing information. | 32. The computing device of claim 26 , wherein the retrieval is performed through a SQL procedure to access a database that includes the version of the marketing information. 33. The computing device of claim 32 , wherein the SQL procedure is selected using the locale identifier value. | 0.653125 |
4,829,572 | 13 | 20 | 13. A method for processing a spoken utterance consisting of a sequence of phonemes said method comprising the steps of: detecting the frequency distribution of the energy of the utterance for a plurality of time intervals within the duration of a single phoneme; separating each frequency distribution into a plurality of frequency bandwidths; deriving at least one energy spectrum representing the energy present in the phoneme as a function of frequency for a plurality of frequency distributions coverting a sequency of time intervals; and deriving at least a pair of sweep spectra representing the change in energy present in the phoneme from one frequency to another as a function of time for a plurality of frequency distributions, whereby the spoken phoneme can be represented by the energy spectrum and the sweep spectra to facilitate speech recognition. | 13. A method for processing a spoken utterance consisting of a sequence of phonemes said method comprising the steps of: detecting the frequency distribution of the energy of the utterance for a plurality of time intervals within the duration of a single phoneme; separating each frequency distribution into a plurality of frequency bandwidths; deriving at least one energy spectrum representing the energy present in the phoneme as a function of frequency for a plurality of frequency distributions coverting a sequency of time intervals; and deriving at least a pair of sweep spectra representing the change in energy present in the phoneme from one frequency to another as a function of time for a plurality of frequency distributions, whereby the spoken phoneme can be represented by the energy spectrum and the sweep spectra to facilitate speech recognition. 20. The method of claim 13 wherein the separating step includes passing the detected energy through a plurality of lowpass filters, and amplifying the output of adjacent lowpass filters with difference amplifiers to separate the detected energy into a plurality of frequency bandwidths. | 0.555901 |
8,458,164 | 5 | 6 | 5. The computer-implemented system of claim 3 , further comprising means for confirming selection of the one or more grouped predicates for ungrouping. | 5. The computer-implemented system of claim 3 , further comprising means for confirming selection of the one or more grouped predicates for ungrouping. 6. The computer-implemented system of claim 5 , further comprising means responsive to selection confirmation for removing the indications of the grouping from the first display area. | 0.646718 |
8,612,369 | 1 | 8 | 1. A computer-implemented method to apply a query to a set of documents, comprising: by a computer: reconstructing a document term matrix XεR N×M where N is a number of documents and M is a number of words, by minimizing reconstruction errors with min ∥X−UA∥, where A is a fixed projection matrix and U is a column orthogonal matrix; determining a loss function and parameter gradients to generate U; fixing U while determining the loss function and sparse regularization constraints on the projection matrix A; generating parameter coefficients and generating a sparse projection matrix A; and generating a Sparse Latent Semantic Analysis (Sparse SLA) model and applying the model to a set of documents and displaying documents matching a query. | 1. A computer-implemented method to apply a query to a set of documents, comprising: by a computer: reconstructing a document term matrix XεR N×M where N is a number of documents and M is a number of words, by minimizing reconstruction errors with min ∥X−UA∥, where A is a fixed projection matrix and U is a column orthogonal matrix; determining a loss function and parameter gradients to generate U; fixing U while determining the loss function and sparse regularization constraints on the projection matrix A; generating parameter coefficients and generating a sparse projection matrix A; and generating a Sparse Latent Semantic Analysis (Sparse SLA) model and applying the model to a set of documents and displaying documents matching a query. 8. The method of claim 1 , comprising initializing U 0 = ( I D 0 ) , where I comprises a unity matrix and D comprises a dimensionality of a latent space. | 0.816986 |
10,109,270 | 1 | 3 | 1. A method performed by one or more computers, the method comprising: receiving, by the one or more computers, context data from a client device of a user; selecting, by the one or more computers, a user context corresponding to the context data from the client device, the user context being selected from among a plurality of user contexts, and the user context indicating a level of complexity of speech that the user is likely able to comprehend at a given time when the context data was received; selecting, by the one or more computers and from among a plurality of candidate text segments that correspond to different levels of complexity of speech, the text segment for text-to-speech synthesis by a text-to-speech module that best matches the selected user context; generating, by the one or more computers, audio data comprising a synthesized utterance of the selected text segment using the text-to-speech module; and providing, by the one or more computers and to the client device, the audio data comprising the synthesized utterance of the selected text segment. | 1. A method performed by one or more computers, the method comprising: receiving, by the one or more computers, context data from a client device of a user; selecting, by the one or more computers, a user context corresponding to the context data from the client device, the user context being selected from among a plurality of user contexts, and the user context indicating a level of complexity of speech that the user is likely able to comprehend at a given time when the context data was received; selecting, by the one or more computers and from among a plurality of candidate text segments that correspond to different levels of complexity of speech, the text segment for text-to-speech synthesis by a text-to-speech module that best matches the selected user context; generating, by the one or more computers, audio data comprising a synthesized utterance of the selected text segment using the text-to-speech module; and providing, by the one or more computers and to the client device, the audio data comprising the synthesized utterance of the selected text segment. 3. The method of claim 1 , further comprising generating each of the plurality of candidate text segments from one or more search results identified by a search engine in response to a query from the user. | 0.825085 |
9,342,508 | 8 | 12 | 8. A method comprising: using a processor, parsing content, based on a canonicalization pattern in the content, from a third party source that is publically available and includes text that is not localized; responsive to the parsing, using the processor, forming a template from the content that includes the text in a human language specific to a particular locale that is to be supported and conforms the data according to a cultural convention used in the particular locale; using the processor, filtering the content for presentation based, at least in part, on attributes of the data for presentation; and using the formed template to cause the computing device to present the filtered content with the text in the human language that corresponds to the particular locale from which a request for the content is received, in which the human language is different from a human language implemented by the text that is not localized. | 8. A method comprising: using a processor, parsing content, based on a canonicalization pattern in the content, from a third party source that is publically available and includes text that is not localized; responsive to the parsing, using the processor, forming a template from the content that includes the text in a human language specific to a particular locale that is to be supported and conforms the data according to a cultural convention used in the particular locale; using the processor, filtering the content for presentation based, at least in part, on attributes of the data for presentation; and using the formed template to cause the computing device to present the filtered content with the text in the human language that corresponds to the particular locale from which a request for the content is received, in which the human language is different from a human language implemented by the text that is not localized. 12. A method as described in claim 8 , wherein the content is included in a feed of content that is available via a network. | 0.82029 |
9,020,840 | 1 | 10 | 1. A method for custom-fitting a service solution to consumer requirements, comprising: acquiring a request for the service solution from a consumer via a conversational interface executed on a processor; issuing a query to a service knowledge base to obtain a set of service knowledge representation items from the service knowledge base; obtaining the set of service knowledge representation items from the service knowledge base; analyzing each service knowledge representation item to determine whether a custom-fit service solution can be developed; determining that a custom-fit service solution can be developed; computing, by the conversational interface executed on the processor, the query to be issued to the service knowledge base based on the request for the service solution, and forwarding the query to a service specification mining module, wherein the service specification mining module synthesizes the custom-fit service solution and transmits the custom-fit service solution to the conversational interface; assetizing the custom-fit service solution, wherein the custom-fit service solution is added to the service knowledge base; and determining that the request cannot be fulfilled automatically by concluding that each parameter of every service knowledge representation item of the set of the service knowledge representation items is an unpluggable parameter. | 1. A method for custom-fitting a service solution to consumer requirements, comprising: acquiring a request for the service solution from a consumer via a conversational interface executed on a processor; issuing a query to a service knowledge base to obtain a set of service knowledge representation items from the service knowledge base; obtaining the set of service knowledge representation items from the service knowledge base; analyzing each service knowledge representation item to determine whether a custom-fit service solution can be developed; determining that a custom-fit service solution can be developed; computing, by the conversational interface executed on the processor, the query to be issued to the service knowledge base based on the request for the service solution, and forwarding the query to a service specification mining module, wherein the service specification mining module synthesizes the custom-fit service solution and transmits the custom-fit service solution to the conversational interface; assetizing the custom-fit service solution, wherein the custom-fit service solution is added to the service knowledge base; and determining that the request cannot be fulfilled automatically by concluding that each parameter of every service knowledge representation item of the set of the service knowledge representation items is an unpluggable parameter. 10. The method of claim 1 , wherein a service knowledge representation item is machine-processable content obtained from a service characterization. | 0.76129 |
9,076,121 | 1 | 9 | 1. A computer-implemented method of categorizing items to be sold by a retailer, the method being implemented on a computer comprising one or more physical processors executing one or more computer executable instructions which, when executed by the one or more physical processors, cause the computer to perform the method, the method comprising: obtaining, by the computer, an item attribute that describes an item to be sold by the retailer; obtaining, by the computer, a data structure of the retailer that describes a plurality of categories including a first category and a second category of items sold by the retailer, wherein the data structure comprises a hierarchy that describes an association between the first category and the second category; determining, by the computer, that the item belongs to the first category based on the data structure of the retailer and the item attribute; determining, by the computer, that the item is associated with the second category based on the hierarchy and the first category; and providing, by the computer, an indication of the first category and the second category. | 1. A computer-implemented method of categorizing items to be sold by a retailer, the method being implemented on a computer comprising one or more physical processors executing one or more computer executable instructions which, when executed by the one or more physical processors, cause the computer to perform the method, the method comprising: obtaining, by the computer, an item attribute that describes an item to be sold by the retailer; obtaining, by the computer, a data structure of the retailer that describes a plurality of categories including a first category and a second category of items sold by the retailer, wherein the data structure comprises a hierarchy that describes an association between the first category and the second category; determining, by the computer, that the item belongs to the first category based on the data structure of the retailer and the item attribute; determining, by the computer, that the item is associated with the second category based on the hierarchy and the first category; and providing, by the computer, an indication of the first category and the second category. 9. The method of claim 1 , the method further comprising: obtaining, by the computer, a location attribute of the item that indicates a location associated with where a manufacturer would provide the item; comparing, by the computer, the location attribute with a retailer location attribute associated with the data structure, wherein the retailer location attribute indicates where a given item is to be sold; and determining, by the computer, where the item is to be sold by the retailer based on the comparison. | 0.5 |
6,097,806 | 8 | 9 | 8. The method of selecting a language as in claim 7 wherein the step of downloading the indication to the basic rate line interface further comprises accessing a message display utility which displays messages from the automatic call distributor and using the indication as a pointer to a memory address. | 8. The method of selecting a language as in claim 7 wherein the step of downloading the indication to the basic rate line interface further comprises accessing a message display utility which displays messages from the automatic call distributor and using the indication as a pointer to a memory address. 9. The method of selecting a language as in claim 8 wherein the step of using the indication as a pointer to a memory address further comprises inserting the pointer in a text retrieval routine. | 0.5 |
9,047,873 | 1 | 2 | 1. A communication apparatus comprising: a microphone to receive sound when a user speaks and to convert the received sound into a voice signal; a voice activity detection processor to detect spoken words and informative sounds within the voice signal; a voice-to-text processor programmed to convert the spoken words and the informative sounds of the voice signal into a text message, wherein the text message includes text identifying the user as originator of the voice signal; a transmitter configured to transmit the voice signal, the text message, or both the voice signal and text message to other users; a receiver configured to receive one or more voice signals, text messages, or voice signals and text messages from one or more users via a communication network; a protective facemask; and a display device to display, adjacent or integral to the protective facemask, the one or more text messages from the one or more users. | 1. A communication apparatus comprising: a microphone to receive sound when a user speaks and to convert the received sound into a voice signal; a voice activity detection processor to detect spoken words and informative sounds within the voice signal; a voice-to-text processor programmed to convert the spoken words and the informative sounds of the voice signal into a text message, wherein the text message includes text identifying the user as originator of the voice signal; a transmitter configured to transmit the voice signal, the text message, or both the voice signal and text message to other users; a receiver configured to receive one or more voice signals, text messages, or voice signals and text messages from one or more users via a communication network; a protective facemask; and a display device to display, adjacent or integral to the protective facemask, the one or more text messages from the one or more users. 2. The communication apparatus of claim 1 , wherein the user and the other one or more users are firefighters. | 0.932349 |
8,793,132 | 11 | 12 | 11. The computer-readable storage device according to claim 9 , wherein the grammar database includes at least one of a fixed-phrase grammar, an acknowledgement grammar, and a recognition grammar. | 11. The computer-readable storage device according to claim 9 , wherein the grammar database includes at least one of a fixed-phrase grammar, an acknowledgement grammar, and a recognition grammar. 12. The computer-readable storage device according to claim 11 , wherein: the fixed-phrase grammar includes fixed phrases for starting and ending a confirmation; and the word database includes spellings and pronunciations of the fixed phrases for starting and ending a confirmation. | 0.5 |
9,014,363 | 1 | 9 | 1. A method for a computer apparatus for automatically generating a customer interaction log for an interaction between a customer and an agent, the method comprising: automatically analyzing received input corresponding to an interaction in the form of a call transcript between the customer and the agent to generate a customer interaction log using at least one model; displaying the customer interaction log for review by the agent at a graphical user interface of an agent computer; enabling the agent to provide feedback associated with the displayed generated customer interaction log by way of the graphical user interface; and automatically updating, based on the agent feedback, at least the customer interaction log. | 1. A method for a computer apparatus for automatically generating a customer interaction log for an interaction between a customer and an agent, the method comprising: automatically analyzing received input corresponding to an interaction in the form of a call transcript between the customer and the agent to generate a customer interaction log using at least one model; displaying the customer interaction log for review by the agent at a graphical user interface of an agent computer; enabling the agent to provide feedback associated with the displayed generated customer interaction log by way of the graphical user interface; and automatically updating, based on the agent feedback, at least the customer interaction log. 9. The method of claim 1 further comprising storing the customer interaction log, the agent feedback, or both. | 0.863861 |
9,177,481 | 13 | 23 | 13. A system for determining a suitable landing area for an aircraft, comprising: a processor; and memory having instructions stored thereon that, when executed by the processor, cause the system to: receive signals indicative of terrain information for a terrain with a three-dimension (3D) perception system; receive signals indicative of image information for the terrain with a camera perception system, the image information separate from the terrain information; evaluate the terrain information and generate information indicative of a landing zone candidate region; co-register in a coordinate system the landing zone candidate region and the image information; segment image regions corresponding to the landing zone candidate regions to generate segmented regions; classify the segmented regions into semantic classes; determine contextual information from a contextual model and using the contextual information to detect an error in at least one semantic class; and ranking and prioritizing the semantic class. | 13. A system for determining a suitable landing area for an aircraft, comprising: a processor; and memory having instructions stored thereon that, when executed by the processor, cause the system to: receive signals indicative of terrain information for a terrain with a three-dimension (3D) perception system; receive signals indicative of image information for the terrain with a camera perception system, the image information separate from the terrain information; evaluate the terrain information and generate information indicative of a landing zone candidate region; co-register in a coordinate system the landing zone candidate region and the image information; segment image regions corresponding to the landing zone candidate regions to generate segmented regions; classify the segmented regions into semantic classes; determine contextual information from a contextual model and using the contextual information to detect an error in at least one semantic class; and ranking and prioritizing the semantic class. 23. The system of claim 13 , wherein the processor is configured to prioritize the semantic classes based on one of priority or suitability. | 0.661836 |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.