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8,214,359 | 9 | 10 | 9. The method of claim 1 , wherein the order of the plurality of search results is based on a degree of match, for each search result, between the search keywords and words in a document corresponding to the search result. | 9. The method of claim 1 , wherein the order of the plurality of search results is based on a degree of match, for each search result, between the search keywords and words in a document corresponding to the search result. 10. The method of claim 9 , wherein the order of the plurality of search results is further based on an estimate of a quality of each search result. | 0.962341 |
9,582,761 | 7 | 10 | 7. A system comprising: one or more data processors; and a non-transitory computer readable storage medium containing instructions which when executed on the one or more data processors, cause the one or more processors to perform operations including: receiving a set of data files; determining a plurality of rule sets based on the set of data files, wherein determining a rule set includes applying a context to a rule set; comparing two rule sets of the plurality of rule sets, wherein comparing includes identifying a dimensional differentiator for the two rules sets and a common node for the two rule sets, wherein the dimensional differentiator is only associated with one context, and wherein the common node is associated with both contexts; generating a canonical rule set using the compared rule sets, the dimensional differentiator, and the common node; generating a visualization of the canonical rule set, wherein the visualization includes a visual indicator for distinguishing the dimensional differentiator from the common node; and presenting the visualization of the canonical rule set on a display. | 7. A system comprising: one or more data processors; and a non-transitory computer readable storage medium containing instructions which when executed on the one or more data processors, cause the one or more processors to perform operations including: receiving a set of data files; determining a plurality of rule sets based on the set of data files, wherein determining a rule set includes applying a context to a rule set; comparing two rule sets of the plurality of rule sets, wherein comparing includes identifying a dimensional differentiator for the two rules sets and a common node for the two rule sets, wherein the dimensional differentiator is only associated with one context, and wherein the common node is associated with both contexts; generating a canonical rule set using the compared rule sets, the dimensional differentiator, and the common node; generating a visualization of the canonical rule set, wherein the visualization includes a visual indicator for distinguishing the dimensional differentiator from the common node; and presenting the visualization of the canonical rule set on a display. 10. The system of claim 7 , wherein presenting the canonical rule set includes distinguishing the dimensional differentiator by context. | 0.744361 |
10,115,055 | 2 | 7 | 2. The system according to claim 1 , wherein the random character level modifications are selected from the group consisting of: adding random characters, deleting characters, transposing characters and replacing characters. | 2. The system according to claim 1 , wherein the random character level modifications are selected from the group consisting of: adding random characters, deleting characters, transposing characters and replacing characters. 7. The system according to claim 2 , further comprising a random modification selector for randomly selecting the character level modifications from the group. | 0.960953 |
8,639,636 | 1 | 5 | 1. A method comprising: tracking user behavior across multiple modalities for interacting with a device; storing representations of the user behavior in a log as descriptors, each descriptor associated with a modality, the descriptors comprising a first descriptor associated with a first modality and a second descriptor associated with a second modality, wherein the first modality and the second modality are distinct modalities; normalizing the descriptors, wherein the first descriptor and the second descriptor are normalized based on: (1) the first modality, (2) the second modality, (3) the device, and (4) a format associated with the device, to yield normalized descriptors; merging the normalized descriptors into a unified click stream; generating a behavioral model by analyzing the unified click stream; and upon receiving user input associated with modifying a presentation of search results associated with a search, dynamically modifying the presentation by using the behavioral model to generate the search results. | 1. A method comprising: tracking user behavior across multiple modalities for interacting with a device; storing representations of the user behavior in a log as descriptors, each descriptor associated with a modality, the descriptors comprising a first descriptor associated with a first modality and a second descriptor associated with a second modality, wherein the first modality and the second modality are distinct modalities; normalizing the descriptors, wherein the first descriptor and the second descriptor are normalized based on: (1) the first modality, (2) the second modality, (3) the device, and (4) a format associated with the device, to yield normalized descriptors; merging the normalized descriptors into a unified click stream; generating a behavioral model by analyzing the unified click stream; and upon receiving user input associated with modifying a presentation of search results associated with a search, dynamically modifying the presentation by using the behavioral model to generate the search results. 5. The method of claim 1 , wherein the user behavior is filtered according to relevance. | 0.917448 |
7,617,450 | 16 | 18 | 16. A computer-readable storage medium having computer-executable instructions stored thereon which, when executed by a computer, will cause the computer to perform a method for inserting and reusing document parts in an electronic document created within a word processing application program, the method comprising: receiving a selection of a document part category; displaying a gallery of document parts associated with the selected document part category, wherein displaying a gallery of document parts associated with the selected document part category comprises displaying a preview of each document part in the gallery and displaying a description of each document part in the gallery, wherein the document parts include reusable portions of document content; receiving a selection of a document part from the gallery, wherein the document part includes a role identifier that indicates a role of the document part within the electronic document; automatically inserting at least one of author information and current date information in the displayed preview using previously stored document properties associated with the word processing application program; identifying the role indicated by the role identifier; inserting the selected document part in the electronic document in accordance with the identified role; receiving user data; and modifying the selected document part with the received user data, wherein modifying the selected document part with the received user data comprises adding additional data to the selected document part, the additional data comprising at least one document part from one or more alternative galleries of document parts and selecting an option from a menu comprising a plurality of options for modifying the selected document part, wherein selecting the option from the menu for modifying the selected document part comprises generating a submenu displaying thumbnails of additional document parts from the gallery and an option for removing a currently displayed document part, and wherein the submenu is utilized to replace a currently displayed document part with one of the additional document parts from the gallery without returning to the gallery, and wherein the selected document part defines a page layout for the electronic document. | 16. A computer-readable storage medium having computer-executable instructions stored thereon which, when executed by a computer, will cause the computer to perform a method for inserting and reusing document parts in an electronic document created within a word processing application program, the method comprising: receiving a selection of a document part category; displaying a gallery of document parts associated with the selected document part category, wherein displaying a gallery of document parts associated with the selected document part category comprises displaying a preview of each document part in the gallery and displaying a description of each document part in the gallery, wherein the document parts include reusable portions of document content; receiving a selection of a document part from the gallery, wherein the document part includes a role identifier that indicates a role of the document part within the electronic document; automatically inserting at least one of author information and current date information in the displayed preview using previously stored document properties associated with the word processing application program; identifying the role indicated by the role identifier; inserting the selected document part in the electronic document in accordance with the identified role; receiving user data; and modifying the selected document part with the received user data, wherein modifying the selected document part with the received user data comprises adding additional data to the selected document part, the additional data comprising at least one document part from one or more alternative galleries of document parts and selecting an option from a menu comprising a plurality of options for modifying the selected document part, wherein selecting the option from the menu for modifying the selected document part comprises generating a submenu displaying thumbnails of additional document parts from the gallery and an option for removing a currently displayed document part, and wherein the submenu is utilized to replace a currently displayed document part with one of the additional document parts from the gallery without returning to the gallery, and wherein the selected document part defines a page layout for the electronic document. 18. The computer-readable storage medium of claim 16 further comprising selecting a new document part from a user interface within the selected document part. | 0.696154 |
8,887,301 | 1 | 10 | 1. A computerized method for classifying and redacting an email message for distributing to multiple recipients having different security levels, the method comprising: using a processor for: selecting a segment of the email message; automatically analyzing contents of the selected segment in real time by using an artificial intelligence (AI) system; automatically classifying the segment, based on results of the analysis performed by the artificial intelligence system, and in accordance with a set of classification options characterizing a type of information contained in the segment; automatically marking the segment in accordance with a respective classification option, producing a marked segment; automatically classifying the email message based on classifications of segments of the email message; and automatically redacting the email message in real time in accordance with a respective clearance level of a recipient of the email message, producing a redacted email message, comprising: (i) arranging recipients of the email message in a hierarchy in accordance with respective clearance levels such that a recipient with a higher clearance level occupies a higher level in the hierarchy in comparison to a recipient with a lower clearance level; and (ii) automatically distributing the redacted email message to the recipients of a particular level in the hierarchy concurrently with the redacting marked segments for the recipients at the immediate lower level in the hierarchy. | 1. A computerized method for classifying and redacting an email message for distributing to multiple recipients having different security levels, the method comprising: using a processor for: selecting a segment of the email message; automatically analyzing contents of the selected segment in real time by using an artificial intelligence (AI) system; automatically classifying the segment, based on results of the analysis performed by the artificial intelligence system, and in accordance with a set of classification options characterizing a type of information contained in the segment; automatically marking the segment in accordance with a respective classification option, producing a marked segment; automatically classifying the email message based on classifications of segments of the email message; and automatically redacting the email message in real time in accordance with a respective clearance level of a recipient of the email message, producing a redacted email message, comprising: (i) arranging recipients of the email message in a hierarchy in accordance with respective clearance levels such that a recipient with a higher clearance level occupies a higher level in the hierarchy in comparison to a recipient with a lower clearance level; and (ii) automatically distributing the redacted email message to the recipients of a particular level in the hierarchy concurrently with the redacting marked segments for the recipients at the immediate lower level in the hierarchy. 10. The method of claim 1 , further comprising redacting marked segments incrementally, comprising redacting the marked segments for the recipients in a particular level in the hierarchy prior to the redacting the marked segments for the recipients at an immediate lower level in the hierarchy. | 0.70122 |
9,202,467 | 47 | 61 | 47. A computer-implemented method for providing web pages, comprising: receiving a first data, the first data including a first web page and a first grammar based on which a voice command is parseable, wherein the first grammar is associated with the first web page; responsive to the receipt of the first data: displaying in a first display window at least a portion of the first web page; storing a reference to the first grammar in a data structure that associates the first grammar with the first display window; responsive to receipt of second data associated with a second web page: displaying in a second display window at least a portion of the second web page in accordance with the second data; and for a second grammar, based on which a voice command is parseable, and that is obtained via the receipt of the second data, storing a reference to the second grammar in the data structure, the data structure associating the second grammar with the second display window; and responsive to an input voice command: determining with which of the first and second grammars the voice command accords; parsing the input voice command according to the determined one of the first and second grammars; accessing the data structure to determine with which of the first and second display windows the determined one of the first and second grammars is associated; and displaying a new data in the determined one of the first and second display windows. | 47. A computer-implemented method for providing web pages, comprising: receiving a first data, the first data including a first web page and a first grammar based on which a voice command is parseable, wherein the first grammar is associated with the first web page; responsive to the receipt of the first data: displaying in a first display window at least a portion of the first web page; storing a reference to the first grammar in a data structure that associates the first grammar with the first display window; responsive to receipt of second data associated with a second web page: displaying in a second display window at least a portion of the second web page in accordance with the second data; and for a second grammar, based on which a voice command is parseable, and that is obtained via the receipt of the second data, storing a reference to the second grammar in the data structure, the data structure associating the second grammar with the second display window; and responsive to an input voice command: determining with which of the first and second grammars the voice command accords; parsing the input voice command according to the determined one of the first and second grammars; accessing the data structure to determine with which of the first and second display windows the determined one of the first and second grammars is associated; and displaying a new data in the determined one of the first and second display windows. 61. The method of claim 47 , wherein: the first web page is a visual web page; the first data includes a first page-markup that includes both first components parseable into the first visual web page and second components parseable into the first grammar irrespective of content of the first components, the second components being specified by a speech markup language and not used for generating the first visual web page; and the second data includes a second page-markup that includes both first components parseable into the second visual web page and second components parseable into the second grammar irrespective of content of the first components of the second page-markup, the second components of the second page-markup being specified by a speech markup language and not used for generating the second visual web page. | 0.500601 |
8,326,826 | 57 | 58 | 57. The computer program product of claim 24 , wherein determining a navigation score for the revised query comprises: determining a click-through rate for each resource identified by a search engine in response to the revised query, the click-through rate being a rate at which search results generated in response to the query and referencing the resource were selected; and wherein the navigation score threshold is a click-through rate threshold. | 57. The computer program product of claim 24 , wherein determining a navigation score for the revised query comprises: determining a click-through rate for each resource identified by a search engine in response to the revised query, the click-through rate being a rate at which search results generated in response to the query and referencing the resource were selected; and wherein the navigation score threshold is a click-through rate threshold. 58. The computer program product of claim 57 , wherein identifying the navigational resource for the revised query comprises identifying as the navigational resource the resource having a click-through rate that exceeds the click-through rate threshold. | 0.940998 |
10,133,736 | 15 | 16 | 15. A computer implemented method executable by a processing unit for providing a contextual analogy response, the method comprising: denoting an analogy phrase within segments of a communication; parsing a set of the segments prior to the denoted analogy phrase; detecting an anaphora within the analogy phrase, including: searching the set of segments for an entity represented by the detected anaphora; and connecting the entity to the detected anaphora; resolving an explanation of the analogy with respect to the set of sentences; creating a sentence structure including an action term from the analogy and a replacement of the anaphora with the entity; populating the created sentence structure with the entity connected with the anaphora; retrieving a contextual response correlating to a sentiment of the analogy phrase; and outputting the response including the retrieved contextual response and the populated sentence structure, wherein the contextual response resolves an explanation of the analogy phrase. | 15. A computer implemented method executable by a processing unit for providing a contextual analogy response, the method comprising: denoting an analogy phrase within segments of a communication; parsing a set of the segments prior to the denoted analogy phrase; detecting an anaphora within the analogy phrase, including: searching the set of segments for an entity represented by the detected anaphora; and connecting the entity to the detected anaphora; resolving an explanation of the analogy with respect to the set of sentences; creating a sentence structure including an action term from the analogy and a replacement of the anaphora with the entity; populating the created sentence structure with the entity connected with the anaphora; retrieving a contextual response correlating to a sentiment of the analogy phrase; and outputting the response including the retrieved contextual response and the populated sentence structure, wherein the contextual response resolves an explanation of the analogy phrase. 16. The method of claim 15 , wherein the sentence parsing further comprises: identifying grammatical sub-components of the segments; identifying grammatical sub-components of the analogy phrase; and matching at least one segment grammatical sob-component corresponding to at least one analogy phrase grammatical sub-component. | 0.729685 |
8,694,491 | 31 | 32 | 31. The method of claim 26 , further comprising: evaluating search results from the rerun query; and selecting search results that meet predefined search result selection criteria; wherein the search results sent to the computer associated with the particular individual computer user correspond to at least some of the selected search results. | 31. The method of claim 26 , further comprising: evaluating search results from the rerun query; and selecting search results that meet predefined search result selection criteria; wherein the search results sent to the computer associated with the particular individual computer user correspond to at least some of the selected search results. 32. The method of claim 31 , wherein at least one of the predefined search result selection criteria used to evaluate a search result from the rerun query is based on the search result not having been previously presented to the particular individual computer user. | 0.911902 |
9,727,639 | 14 | 17 | 14. A query module for performing a name search, comprising: a name search module operative to receive a plurality of identified candidate names from a matching operation between an input name from a query and an index of names of people; a ranking module operative to generate rank values associated with the respective candidate names using a ranking function, each rank value R for a candidate name being generated based on at least a result D+S+N, where D is a dynamic rank score associated with one or more query-dependent factor values, wherein each query-dependent factor value is associated with input information input by a user, N is a nexus rank score associated with one or more nexus factor values, wherein each nexus factor value is associated with an extent of a nexus between the user who inputs the input information and a person associated with the candidate name, and S is a static rank score associated with one or more static factor values, wherein each static factor value is associated with a determination regarding the candidate name that is independent of an identity of the user who inputs the input information, and rank the candidate names based on the rank values; and an output module operative to display on a display device a subset of the ranked candidate names that satisfy a prescribed threshold of appropriateness. | 14. A query module for performing a name search, comprising: a name search module operative to receive a plurality of identified candidate names from a matching operation between an input name from a query and an index of names of people; a ranking module operative to generate rank values associated with the respective candidate names using a ranking function, each rank value R for a candidate name being generated based on at least a result D+S+N, where D is a dynamic rank score associated with one or more query-dependent factor values, wherein each query-dependent factor value is associated with input information input by a user, N is a nexus rank score associated with one or more nexus factor values, wherein each nexus factor value is associated with an extent of a nexus between the user who inputs the input information and a person associated with the candidate name, and S is a static rank score associated with one or more static factor values, wherein each static factor value is associated with a determination regarding the candidate name that is independent of an identity of the user who inputs the input information, and rank the candidate names based on the rank values; and an output module operative to display on a display device a subset of the ranked candidate names that satisfy a prescribed threshold of appropriateness. 17. The query module of claim 14 , wherein the name search module is further configured to: receive input information that includes the input name; parse the input name into component names; for each component name: determine at least one fuzzy match associated with the component name if there is at least one fuzzy match and execute a lookup operation in an index for each fuzzy match to provide at least one lookup result; and provide at least one candidate name based on a scoring analysis of lookup results provided for the component names in the input name, each candidate name having a probability score associated therewith which reflects a level of confidence that the candidate name is an appropriate match for the input name. | 0.500678 |
9,131,045 | 43 | 47 | 43. A system for providing captioned services to an assisted user communicating with a hearing person, the system comprising a relay including a relay computer, a relay input device and a relay display screen; a captioned device that is linkable to at least first and second communication links, the captioned device comprising: a speaker; a microphone; a display within sight of the assisted user; an activation switch that can be selected by the assisted user to invoke a captioning service; and a device processor, each of the display and activation switch linked to the device processor, the device processor also linkable to first and second communication links, the captioned device enabling the assisted user to use the device to facilitate communications via the first communication link between the assisted user and the hearing person and configured to perform the steps of: (i) receiving words spoken by a hearing person on the first communication link and broadcasting the hearing person's words via the speaker upon reception; (ii) receiving words spoken by the assisted user via the microphone and transmitting the words received by the microphone via the first communication link to the device used by the hearing person; (iii) receiving an indication that the activation switch on the assisted user's captioned device has been activated; (iv) upon receiving the indication, providing the voice of the hearing person over the second communication link to the relay so that the relay can convert the words spoken by the hearing person into a text message stream; (v) receiving the text message stream from the relay over the second communication link; and (vi) displaying the received text on the display; the relay configured to perform the steps of: (i) transcribing the words spoken by the hearing person into a text message stream; (ii) displaying the text message stream on the relay display screen used by a call assistant; (iii) receiving corrections to the text message stream entered by a call assistant using the relay input device to generate corrected text; and (iv) transmitting the corrected text to the captioned device. | 43. A system for providing captioned services to an assisted user communicating with a hearing person, the system comprising a relay including a relay computer, a relay input device and a relay display screen; a captioned device that is linkable to at least first and second communication links, the captioned device comprising: a speaker; a microphone; a display within sight of the assisted user; an activation switch that can be selected by the assisted user to invoke a captioning service; and a device processor, each of the display and activation switch linked to the device processor, the device processor also linkable to first and second communication links, the captioned device enabling the assisted user to use the device to facilitate communications via the first communication link between the assisted user and the hearing person and configured to perform the steps of: (i) receiving words spoken by a hearing person on the first communication link and broadcasting the hearing person's words via the speaker upon reception; (ii) receiving words spoken by the assisted user via the microphone and transmitting the words received by the microphone via the first communication link to the device used by the hearing person; (iii) receiving an indication that the activation switch on the assisted user's captioned device has been activated; (iv) upon receiving the indication, providing the voice of the hearing person over the second communication link to the relay so that the relay can convert the words spoken by the hearing person into a text message stream; (v) receiving the text message stream from the relay over the second communication link; and (vi) displaying the received text on the display; the relay configured to perform the steps of: (i) transcribing the words spoken by the hearing person into a text message stream; (ii) displaying the text message stream on the relay display screen used by a call assistant; (iii) receiving corrections to the text message stream entered by a call assistant using the relay input device to generate corrected text; and (iv) transmitting the corrected text to the captioned device. 47. The system of claim 43 wherein the step of receiving the text message stream includes receiving a digital communication stream. | 0.93744 |
9,342,907 | 8 | 13 | 8. A method for analyzing ballistic trajectories comprising: determining, using a preprocessor, invariants for known ballistic objects; defining, using the preprocessor, a reference graph having nodes corresponding to the invariants for the known ballistic objects; defining, using the preprocessor, a query graph having nodes connected to nodes of the reference graph corresponding to anticipated invariant queries to be made using the query graph; inputting into the reference graph, using a runtime processor, one or more sets of invariants corresponding to trajectories of one or more observed objects, each of the one or more sets of invariants traversing through the nodes of the reference graph corresponding to the each of the one or more sets of invariants and leaving a record in the nodes traversed; selecting, using an interface, a query for the query graph corresponding to one or more range of invariants, said query generating a query result identifying the nodes of the reference graph that satisfy the query; and identifying, using the runtime processor, each of the one or more observed objects identified by a record in the identified nodes, thereby determining which of the one or more observed objects satisfy the query. | 8. A method for analyzing ballistic trajectories comprising: determining, using a preprocessor, invariants for known ballistic objects; defining, using the preprocessor, a reference graph having nodes corresponding to the invariants for the known ballistic objects; defining, using the preprocessor, a query graph having nodes connected to nodes of the reference graph corresponding to anticipated invariant queries to be made using the query graph; inputting into the reference graph, using a runtime processor, one or more sets of invariants corresponding to trajectories of one or more observed objects, each of the one or more sets of invariants traversing through the nodes of the reference graph corresponding to the each of the one or more sets of invariants and leaving a record in the nodes traversed; selecting, using an interface, a query for the query graph corresponding to one or more range of invariants, said query generating a query result identifying the nodes of the reference graph that satisfy the query; and identifying, using the runtime processor, each of the one or more observed objects identified by a record in the identified nodes, thereby determining which of the one or more observed objects satisfy the query. 13. The method of claim 8 , wherein connections between nodes of the reference graph and nodes of the query graph comprise the connections between nodes of the query graph corresponding to anticipated invariant queries and nodes of the reference graph that correspond to anticipated invariant queries. | 0.909446 |
9,305,063 | 12 | 14 | 12. The system of claim 11 , wherein selecting one of the catchment areas as a selected catchment area for the query based on the number of catchment area matches comprises: determining, for each catchment area, a catchment area score based on the catchment area matches for the query; and selecting the catchment area with the highest catchment area score and that meets a catchment area score threshold. | 12. The system of claim 11 , wherein selecting one of the catchment areas as a selected catchment area for the query based on the number of catchment area matches comprises: determining, for each catchment area, a catchment area score based on the catchment area matches for the query; and selecting the catchment area with the highest catchment area score and that meets a catchment area score threshold. 14. The system of claim 12 , wherein: determining the catchment area score for each catchment area comprises determining the catchment area score based on constituent catchment area scores determined for catchment areas of the same type and that cover a plurality of different geographic areas. | 0.88587 |
8,150,690 | 1 | 9 | 1. A speech recognition system with cepstral noise subtraction, comprising: a filterbank energy extractor, for obtaining a plurality of first feature vectors according to a voice signal; a cepstral noise subtraction device, for obtaining a first feature vector of a preset voice frame and first feature vectors of a plurality of voice frames before the preset voice frame, so as to calculate a feature mean vector, and calculate a second feature vector of a preset voice frame according to the first feature vector, the feature mean vector, a first scalar coefficient, and a second scalar coefficient of the preset voice frame; a cepstral converter, for converting the second feature vector of the preset voice frame into a cepstral feature vector; a model trainer, for calculating a model parameter according to the cepstral feature vector; and a speech recognizer, for calculating a recognized voice signal according to the cepstral feature vector and the model parameter. | 1. A speech recognition system with cepstral noise subtraction, comprising: a filterbank energy extractor, for obtaining a plurality of first feature vectors according to a voice signal; a cepstral noise subtraction device, for obtaining a first feature vector of a preset voice frame and first feature vectors of a plurality of voice frames before the preset voice frame, so as to calculate a feature mean vector, and calculate a second feature vector of a preset voice frame according to the first feature vector, the feature mean vector, a first scalar coefficient, and a second scalar coefficient of the preset voice frame; a cepstral converter, for converting the second feature vector of the preset voice frame into a cepstral feature vector; a model trainer, for calculating a model parameter according to the cepstral feature vector; and a speech recognizer, for calculating a recognized voice signal according to the cepstral feature vector and the model parameter. 9. The speech recognition system according to claim 1 , wherein the filterbank energy extractor is a log Mel filterbank energy extractor. | 0.941202 |
9,451,050 | 1 | 3 | 1. A method, comprising the steps of: receiving, by a server computer communicatively coupled to a network, a command from a user interface zooming control on a graphical user interface, to display a map on the graphical user interface for a geographic region displaying a plurality of cities, each of the plurality of cities located at a unique horizontal and vertical position on the map; rendering, by the server computer, on the graphical user interface, the map comprising the geographic region; for each city in the plurality of cities displayed on the map: executing, by the server computer, a query to identify a domain name in a plurality of available domain names comprising a name of the city; generating, by the server computer, a user interface control configured to register the domain name; and rendering, by the server computer, the user interface control on the graphical user interface at a position determined by the unique horizontal and vertical position on the map; and transmitting, by the server computer, the graphical user interface to a client computer for display. | 1. A method, comprising the steps of: receiving, by a server computer communicatively coupled to a network, a command from a user interface zooming control on a graphical user interface, to display a map on the graphical user interface for a geographic region displaying a plurality of cities, each of the plurality of cities located at a unique horizontal and vertical position on the map; rendering, by the server computer, on the graphical user interface, the map comprising the geographic region; for each city in the plurality of cities displayed on the map: executing, by the server computer, a query to identify a domain name in a plurality of available domain names comprising a name of the city; generating, by the server computer, a user interface control configured to register the domain name; and rendering, by the server computer, the user interface control on the graphical user interface at a position determined by the unique horizontal and vertical position on the map; and transmitting, by the server computer, the graphical user interface to a client computer for display. 3. The method of claim 1 further comprising the steps of: identifying, by the server computer, a text string associated with the city; searching, by the server computer, a database comprising the a domain name, to determine whether the domain name comprises the text string; and responsive to a determination that the domain name comprises the text string, identifying, by the server computer, the domain name as relevant to the city. | 0.752847 |
8,280,885 | 26 | 27 | 26. A computer-implemented method, using a processor, for generating an opinion summary from a plurality of documents, said method comprising: using at least one of syntactic analysis, semantic analysis and discourse analysis to assist in automatically extracting at least one opinion expression from each of the plurality of documents using the processor, each opinion expression identified by a grammatical element and associated with an opinion source, opinion topic, opinion polarity and opinion strength, wherein for each opinion expression the opinion source is at least one person or entity to which such opinion expression is to be attributed and wherein each document includes opinion expressions from a plurality of opinion sources; identifying those opinion expressions that share a common opinion source and a common opinion topic using the processor; and combining the opinion polarities and opinion strengths of those opinion expressions that share a common opinion source to form an overall opinion summary with one aggregate opinion frame for each common opinion source-topic pairing. | 26. A computer-implemented method, using a processor, for generating an opinion summary from a plurality of documents, said method comprising: using at least one of syntactic analysis, semantic analysis and discourse analysis to assist in automatically extracting at least one opinion expression from each of the plurality of documents using the processor, each opinion expression identified by a grammatical element and associated with an opinion source, opinion topic, opinion polarity and opinion strength, wherein for each opinion expression the opinion source is at least one person or entity to which such opinion expression is to be attributed and wherein each document includes opinion expressions from a plurality of opinion sources; identifying those opinion expressions that share a common opinion source and a common opinion topic using the processor; and combining the opinion polarities and opinion strengths of those opinion expressions that share a common opinion source to form an overall opinion summary with one aggregate opinion frame for each common opinion source-topic pairing. 27. The computer-implemented method of claim 26 , wherein identifying those opinion expressions that share a common opinion source includes identifying those opinion expressions that have a common real-world opinion source expressed in the document with different language. | 0.721429 |
8,787,695 | 1 | 2 | 1. A method for rectifying an input digital image including warped textual lines, the method implemented at least in part by a data processing system and comprising: receiving an input digital image; analyzing the input digital image to determine a plurality of text line traces that track along with the warped textual lines in a substantially parallel fashion; subdividing the input digital image into a plurality of vertical slices, each vertical slice having associated first and second slice edges and an associated slice width; forming vertical slice deformation models for a plurality of the vertical slices by: identifying a plurality of text line traces that cross a particular vertical slice, each of the identified text line traces having a first-edge vertical coordinate corresponding to the location where the text line trace crosses the first slice edge and a second-edge vertical coordinate corresponding to the location where the text line trace crosses the second slice edge of the vertical slice; and forming the vertical slice deformation model for the particular vertical slice by fitting a parametric function that predicts the second-edge vertical coordinates as a function of the first-edge vertical coordinates; forming a plurality of streamlines responsive to the vertical slice deformation models, wherein the streamlines represent a deformation of the warped textual lines in the input digital image; forming a global deformation function by interpolating between the streamlines; forming a rectified image by rectifying the input digital image responsive to the global deformation function; and storing the rectified image in a processor-accessible memory. | 1. A method for rectifying an input digital image including warped textual lines, the method implemented at least in part by a data processing system and comprising: receiving an input digital image; analyzing the input digital image to determine a plurality of text line traces that track along with the warped textual lines in a substantially parallel fashion; subdividing the input digital image into a plurality of vertical slices, each vertical slice having associated first and second slice edges and an associated slice width; forming vertical slice deformation models for a plurality of the vertical slices by: identifying a plurality of text line traces that cross a particular vertical slice, each of the identified text line traces having a first-edge vertical coordinate corresponding to the location where the text line trace crosses the first slice edge and a second-edge vertical coordinate corresponding to the location where the text line trace crosses the second slice edge of the vertical slice; and forming the vertical slice deformation model for the particular vertical slice by fitting a parametric function that predicts the second-edge vertical coordinates as a function of the first-edge vertical coordinates; forming a plurality of streamlines responsive to the vertical slice deformation models, wherein the streamlines represent a deformation of the warped textual lines in the input digital image; forming a global deformation function by interpolating between the streamlines; forming a rectified image by rectifying the input digital image responsive to the global deformation function; and storing the rectified image in a processor-accessible memory. 2. The method of claim 1 wherein the determination of the text line traces includes: determining a filtered image having filtered pixels values, wherein each filtered pixel value is determined by filtering the input image with a plurality of anisotropic Gaussian filters having a variety of orientation angles to provide a corresponding plurality of candidate filtered pixel values and selecting the smallest candidate largest filtered pixel value; applying an edge detection operation to the filtered image to determine an edge trace image including a plurality of edge traces; and designating at least some of the edge traces to be text line traces. | 0.500767 |
6,161,092 | 1 | 40 | 1. A method for reporting traffic information using pre-recorded audio, comprising the steps of: receiving data for a set of traffic incidents, said data including parameters for each of said traffic incidents, one or more of said parameters include at least one code representing a value for said parameter; identifying groups of files that store speech for describing said traffic incidents, each group of files is associated with at least one of said incidents, said step of identifying groups comprises the steps of: for each incident of at least a subset of said traffic incidents, accessing parameters for said incident, and for each parameter of at least a subset of said accessed parameters, identifying one or more files that store speech using a set of information correlating codes for said parameter to references to audio files; and automatically presenting said stored speech from each group of files. | 1. A method for reporting traffic information using pre-recorded audio, comprising the steps of: receiving data for a set of traffic incidents, said data including parameters for each of said traffic incidents, one or more of said parameters include at least one code representing a value for said parameter; identifying groups of files that store speech for describing said traffic incidents, each group of files is associated with at least one of said incidents, said step of identifying groups comprises the steps of: for each incident of at least a subset of said traffic incidents, accessing parameters for said incident, and for each parameter of at least a subset of said accessed parameters, identifying one or more files that store speech using a set of information correlating codes for said parameter to references to audio files; and automatically presenting said stored speech from each group of files. 40. A method according to claim 1, wherein: said step of automatically presenting includes continuously presenting an audio/visual program that includes said stored speech. | 0.882192 |
9,213,768 | 20 | 26 | 20. A tangible, non-transitory storage medium having stored thereon machine executable instructions, the machine executable instructions, when executed by one or more machines, cause the one or more machines to: receive a query in an imprecise syntax, the query including a word, phrase, or group of textual characters; when the word, phrase, or group of textual characters is not recognized by the one or more machines: determine, based at least in part on relative placement of alphabetic characters, numeric characters, and non-alphanumeric characters of the word, phrase, or group of textual characters, a plurality of entities to which the word corresponds, or choose, based at least in part on the relative placement of alphabetic characters, numeric characters, and non-alphanumeric characters of the word, phrase, or group of textual characters, one meaning or sense; when the word, phrase, or group of textual characters is recognized by the one or more machines and the word, phrase, or group of textual characters refers to a plurality of entities, determine the entities to which the word, phrase, or group of textual characters corresponds; when the word, phrase, or group of textual characters corresponds to multiple entities in a same category, rank the multiple entities in the same category to which the word, phrase, or group of textual characters corresponds using a set of attributes common to entities in the category, wherein the set of attributes is different than other sets of attributes common to entities in other categories; when the word, phrase, or group of textual characters is recognized by the one or more machines and the word, phrase, or group of textual characters has multiple meanings or senses, rank the multiple meanings or senses of the word, phrase, or group of textual characters based on attributes of a user; when the word, phrase, or group of textual characters is recognized by the one or more machines and the word, phrase, or group of textual characters has multiple meanings or senses, rank a plurality of meanings or senses of the word, phrase, or group of textual characters, based on a measure of popularity of the plurality of meanings or senses; when the word, phrase, or group of textual characters corresponds to multiple entities in a same category, or the word, phrase, or group of textual characters is recognized by the one or more machines and the word has multiple meanings or senses, choose one meaning or sense based on the rankings; generate an answer to the query based on the one meaning or sense; provide a user interface mechanism to permit a user to select a different one of the plurality of meanings or senses, wherein the user interface mechanism visually presents a list of entities in the same category to which the word, phrase, or group of textual characters corresponds in an order determined according to the set of attributes common to entities in the category; receive an indication of a selected different meaning or sense selected by the user using the user interface mechanism; and generate a different answer based on the selected different meaning or sense. | 20. A tangible, non-transitory storage medium having stored thereon machine executable instructions, the machine executable instructions, when executed by one or more machines, cause the one or more machines to: receive a query in an imprecise syntax, the query including a word, phrase, or group of textual characters; when the word, phrase, or group of textual characters is not recognized by the one or more machines: determine, based at least in part on relative placement of alphabetic characters, numeric characters, and non-alphanumeric characters of the word, phrase, or group of textual characters, a plurality of entities to which the word corresponds, or choose, based at least in part on the relative placement of alphabetic characters, numeric characters, and non-alphanumeric characters of the word, phrase, or group of textual characters, one meaning or sense; when the word, phrase, or group of textual characters is recognized by the one or more machines and the word, phrase, or group of textual characters refers to a plurality of entities, determine the entities to which the word, phrase, or group of textual characters corresponds; when the word, phrase, or group of textual characters corresponds to multiple entities in a same category, rank the multiple entities in the same category to which the word, phrase, or group of textual characters corresponds using a set of attributes common to entities in the category, wherein the set of attributes is different than other sets of attributes common to entities in other categories; when the word, phrase, or group of textual characters is recognized by the one or more machines and the word, phrase, or group of textual characters has multiple meanings or senses, rank the multiple meanings or senses of the word, phrase, or group of textual characters based on attributes of a user; when the word, phrase, or group of textual characters is recognized by the one or more machines and the word, phrase, or group of textual characters has multiple meanings or senses, rank a plurality of meanings or senses of the word, phrase, or group of textual characters, based on a measure of popularity of the plurality of meanings or senses; when the word, phrase, or group of textual characters corresponds to multiple entities in a same category, or the word, phrase, or group of textual characters is recognized by the one or more machines and the word has multiple meanings or senses, choose one meaning or sense based on the rankings; generate an answer to the query based on the one meaning or sense; provide a user interface mechanism to permit a user to select a different one of the plurality of meanings or senses, wherein the user interface mechanism visually presents a list of entities in the same category to which the word, phrase, or group of textual characters corresponds in an order determined according to the set of attributes common to entities in the category; receive an indication of a selected different meaning or sense selected by the user using the user interface mechanism; and generate a different answer based on the selected different meaning or sense. 26. The tangible, non-transitory storage medium according to claim 20 , the machine executable instructions, when executed by the one or more machines, further cause the one or more machines to: when the word, phrase, or group of textual characters is not recognized by the one or more machines, generate a keyword based on an analysis of the relative placement of alphabetic characters, numeric characters, and non-alphanumeric characters of the word, wherein the one or more machines determines the plurality of meanings or senses based on the keyword. | 0.60485 |
8,560,937 | 1 | 22 | 1. A method for segmenting a document comprising: identifying a rectangular page frame using information from multiple pages of a document; matching the page frame to a page of the document; identifying elements within the matched page frame; for a zone of the document page having a zone width and comprising a set of the elements, the zone comprising at least a portion of the page frame width: a) for a first iteration: segmenting the zone regularly into a number of candidate columns, a width of each of the candidate columns being function of the number of the candidate columns and the zone width; for each of the candidate columns, identifying the elements in the set which are within the candidate column; where the candidate columns meet a threshold for identified elements and a gutter is found which spaces the candidate columns, assigning, to a set of segmented columns, those elements in the set which are within the segmented columns, and identifying remaining elements in the set which are not covered by the segmented columns, the segmented columns corresponding in number to the number of candidate columns and each segmented column being spaced by the computed gutter; b) where there are remaining elements after a), performing at least one of: i) at least one subsequent iteration which includes repeating a), wherein in each subsequent iteration, the set of elements is the remaining elements in the set, and wherein the segmenting of the zone regularly into a number of candidate columns segments the zone into a different number of candidate columns from the first iteration and all other subsequent iterations, and ii) considering the zone as a single segmented column only, identifying the elements in the set which are within the single segmented column; and where there are remaining elements in the set after a) and b), providing for a) and b) to be performed for at least one subsequent zone of the page, wherein for each subsequent zone, the set of elements includes remaining elements not covered by the segmented columns identified for any of the preceding zones. | 1. A method for segmenting a document comprising: identifying a rectangular page frame using information from multiple pages of a document; matching the page frame to a page of the document; identifying elements within the matched page frame; for a zone of the document page having a zone width and comprising a set of the elements, the zone comprising at least a portion of the page frame width: a) for a first iteration: segmenting the zone regularly into a number of candidate columns, a width of each of the candidate columns being function of the number of the candidate columns and the zone width; for each of the candidate columns, identifying the elements in the set which are within the candidate column; where the candidate columns meet a threshold for identified elements and a gutter is found which spaces the candidate columns, assigning, to a set of segmented columns, those elements in the set which are within the segmented columns, and identifying remaining elements in the set which are not covered by the segmented columns, the segmented columns corresponding in number to the number of candidate columns and each segmented column being spaced by the computed gutter; b) where there are remaining elements after a), performing at least one of: i) at least one subsequent iteration which includes repeating a), wherein in each subsequent iteration, the set of elements is the remaining elements in the set, and wherein the segmenting of the zone regularly into a number of candidate columns segments the zone into a different number of candidate columns from the first iteration and all other subsequent iterations, and ii) considering the zone as a single segmented column only, identifying the elements in the set which are within the single segmented column; and where there are remaining elements in the set after a) and b), providing for a) and b) to be performed for at least one subsequent zone of the page, wherein for each subsequent zone, the set of elements includes remaining elements not covered by the segmented columns identified for any of the preceding zones. 22. The method of claim 1 , further comprising: assigning a page frame to each of a set of the pages of the input document based on bounding boxes of the detected elements for multiple pages of the document; for each page in the set, identifying a set of elements from the detected elements which are within the assigned page frame the zone having a width which is computed based on the page frame width. | 0.722146 |
8,706,827 | 1 | 6 | 1. A computer-implemented method comprising: under control of one or more computer systems configured with executable instructions, storing dialog patterns for a type of communication between a user and a type of recipient, the dialog patterns including at least one of words or phrases from one or more past communications between the user and one or more recipients of the type of recipient; generating a dialog profile for the type of recipient based at least in part upon the dialog patterns; determining at least one context associated with the user sending a communication to a recipient of the one or more recipients of the type of recipient, the at least one context being associated with at least one behavioral pattern of the user; determining a subsequent occurrence of the at least one context; adjusting the dialog profile associated with the recipient to include dialog patterns associated with the at least one context; generating at least one subsequent communication to be sent to the recipient based at least in part on the dialog patterns associated with the dialog profile of the recipient and the at least one context. | 1. A computer-implemented method comprising: under control of one or more computer systems configured with executable instructions, storing dialog patterns for a type of communication between a user and a type of recipient, the dialog patterns including at least one of words or phrases from one or more past communications between the user and one or more recipients of the type of recipient; generating a dialog profile for the type of recipient based at least in part upon the dialog patterns; determining at least one context associated with the user sending a communication to a recipient of the one or more recipients of the type of recipient, the at least one context being associated with at least one behavioral pattern of the user; determining a subsequent occurrence of the at least one context; adjusting the dialog profile associated with the recipient to include dialog patterns associated with the at least one context; generating at least one subsequent communication to be sent to the recipient based at least in part on the dialog patterns associated with the dialog profile of the recipient and the at least one context. 6. The computer-implemented method of claim 1 , wherein the at least one context is determined by one or more of using at least one Global Positioning System (GPS) sensor, determining an occurrence of an event, determining a time of day, or determining a day of a week. | 0.729376 |
8,229,728 | 18 | 30 | 18. A method for generating a translation model for a statistical machine translation system, comprising the steps of: selecting a plurality of parallel sentences having one or more phrases using at least one of word occurrence frequency information and a minimum BLEU score criterion, each of said parallel sentences having a source language sentence and a target language sentence; manually aligning, via an alignment tool, words and phrases between said source language sentences and said target language sentences of said parallel sentences; extracting alignment patterns from said manually aligned sentences; estimating word alignments from said alignment patterns; extracting source-target phrases using the word alignments; and estimating the one or more translation models from the extracted source-target phrases. | 18. A method for generating a translation model for a statistical machine translation system, comprising the steps of: selecting a plurality of parallel sentences having one or more phrases using at least one of word occurrence frequency information and a minimum BLEU score criterion, each of said parallel sentences having a source language sentence and a target language sentence; manually aligning, via an alignment tool, words and phrases between said source language sentences and said target language sentences of said parallel sentences; extracting alignment patterns from said manually aligned sentences; estimating word alignments from said alignment patterns; extracting source-target phrases using the word alignments; and estimating the one or more translation models from the extracted source-target phrases. 30. The method of claim 18 wherein the translation model is estimated using the word alignment model and a phrase map. | 0.919509 |
9,367,585 | 1 | 9 | 1. A data storage and query method which supports an agile development and horizontal scaling, comprising steps of: transforming data into a 2-tupel (Key, MiniTable), and identifying any MiniTable with a unique Key, wherein, the MiniTable comprises a plurality of data columns; a structure of each data column is limited via a pre-defined mode; and the data columns are sorted according to a primary key defined by the mode; wherein the pre-defined mode is a Key-MiniTable mode having three basic primitives and three physical entities, wherein the three physical entities comprise: a client for initiating a request to a Key server with the three basic primitives and receiving a result of the request; the Key server for receiving the request initiated by the client, searching an IP address and a port number of each MiniTable server where each MiniTable corresponding to the Key is located, and accordingly transferring the request to the corresponding MiniTable server; and the MiniTable servers for receiving the request transferred by the Key server, parsing analogous SQL statements of the request, forming an execution plan, reading and writing the data in a distributed storage system, completing the request and returning a result of the request to the client. | 1. A data storage and query method which supports an agile development and horizontal scaling, comprising steps of: transforming data into a 2-tupel (Key, MiniTable), and identifying any MiniTable with a unique Key, wherein, the MiniTable comprises a plurality of data columns; a structure of each data column is limited via a pre-defined mode; and the data columns are sorted according to a primary key defined by the mode; wherein the pre-defined mode is a Key-MiniTable mode having three basic primitives and three physical entities, wherein the three physical entities comprise: a client for initiating a request to a Key server with the three basic primitives and receiving a result of the request; the Key server for receiving the request initiated by the client, searching an IP address and a port number of each MiniTable server where each MiniTable corresponding to the Key is located, and accordingly transferring the request to the corresponding MiniTable server; and the MiniTable servers for receiving the request transferred by the Key server, parsing analogous SQL statements of the request, forming an execution plan, reading and writing the data in a distributed storage system, completing the request and returning a result of the request to the client. 9. The data storage and query method, as recited in claim 1 , wherein the Key server has three kernel data structures of: (1) a B+ tree, for storing corresponding relations between the Keys and address codes; (2) an address translating table, for storing corresponding relations between the address codes and IP addresses, and between the address codes and the port numbers; and (3) a MiniTable server monitoring table, for storing for storing loading conditions of the MiniTable servers corresponding to each address code; wherein when the Key server receives a primitive request, the Key server checks whether the primitive request is a valid Query primitive; if yes, the Key server queries an address code corresponding to a Key in the B+ tree; if no existing Key, the Key server returns information of no existing Key; if the Key exists, the Key server queries an IP address and a port number corresponding to the address code in the address translating table; if no existing IP address and no existing port number, the Key server returns to error; if the IP address and the port number exist, the Key server transfers the request to the MiniTable server corresponding to the IP address and the port number; if the request is not a valid Query primitive, the Key server checks whether the request is a valid Create primitive; if yes, the Key server queries whether a designated Key exists in the B+ tree; if the designated Key exists, the Key server returns information that the designated Key has existed; if no existing designated Key, the Key server allocates an address code according to a dispatch algorithm and the MiniTable server monitoring table, updates the MiniTable server monitoring table, queries an IP address and a port number corresponding to the address code and transfers the request to the corresponding MiniTable server; if the request is not a valid Create primitive, the Key server checks whether the request is a valid Delete primitive; if yes, the Key server queries whether a designated Key exists in the B+ tree; If no existing designated Key, the Key server returns information of no existing designated Key; if the designated Key exists, the Key server queries an IP address and a port number corresponding to an address code in the address translating table, deletes the corresponding Key in the B+ tree, updates the MiniTable server monitoring table, queries the IP address and the port number and transfers the request to the corresponding MiniTable server. | 0.550487 |
10,055,113 | 11 | 15 | 11. A computer program product encoded on a non-transitory, tangible storage medium, the product comprising computer readable instructions for causing one or more processors to perform operations comprising: identifying an instance of a UI text element within a UI associated with a software application for modification, wherein the UI is displayed to at least one user; retrieving a first set of metadata associated with the identified instance of the UI text element, where each instance in a plurality of instances of the UI text element is associated with the retrieved first set of metadata based on each instance's instantiation from a single UI text model common to each of the plurality of instances, each of the plurality of instances of the UI text element used in different locations, and wherein at least a portion of the retrieved first set of metadata defines the text presented in the identified instance of the UI text element and each of the others of the plurality of instances of the UI text element, where the retrieved first set of metadata associated with each of the plurality of instances of the UI text element is stored in the single UI text model; receiving at least one modification to the retrieved first set of metadata associated with the identified instance of the UI text element, the at least one modification representing a modification to the defined text presented in the identified instance of the UI text element; and persisting the modified first set of metadata associated with the identified instance by associating the modified first set of metadata with the single UI text model, wherein the text presented in each of the plurality of instances of the UI text element is updated based on the modified first set of metadata associated with the single UI text model common to each of the plurality of instances, wherein persisting includes updating the single UI text model with the modified first set of metadata. | 11. A computer program product encoded on a non-transitory, tangible storage medium, the product comprising computer readable instructions for causing one or more processors to perform operations comprising: identifying an instance of a UI text element within a UI associated with a software application for modification, wherein the UI is displayed to at least one user; retrieving a first set of metadata associated with the identified instance of the UI text element, where each instance in a plurality of instances of the UI text element is associated with the retrieved first set of metadata based on each instance's instantiation from a single UI text model common to each of the plurality of instances, each of the plurality of instances of the UI text element used in different locations, and wherein at least a portion of the retrieved first set of metadata defines the text presented in the identified instance of the UI text element and each of the others of the plurality of instances of the UI text element, where the retrieved first set of metadata associated with each of the plurality of instances of the UI text element is stored in the single UI text model; receiving at least one modification to the retrieved first set of metadata associated with the identified instance of the UI text element, the at least one modification representing a modification to the defined text presented in the identified instance of the UI text element; and persisting the modified first set of metadata associated with the identified instance by associating the modified first set of metadata with the single UI text model, wherein the text presented in each of the plurality of instances of the UI text element is updated based on the modified first set of metadata associated with the single UI text model common to each of the plurality of instances, wherein persisting includes updating the single UI text model with the modified first set of metadata. 15. The computer program product of claim 11 , where persisting the modified first set of metadata associated with the UI text element includes storing the modified first set of metadata in a backend database. | 0.80394 |
8,055,674 | 32 | 35 | 32. A computer implemented method of querying a fact repository, performed at a computer system having one or more processors and memory storing one or more programs for execution by the one or more processors, the method comprising: receiving a search query; retrieving at least one fact from the fact repository, the at least one fact corresponding to the received search query and having an attribute and a value, wherein the fact repository includes a plurality of facts associated with objects, wherein a respective fact in the fact repository includes a respective attribute and a respective value, wherein the respective value is a text string, and wherein the plurality of facts are extracted from a plurality of documents; retrieving at least one annotation associated with the at least one fact, the at least one annotation having a value corresponding to the value of the at least one fact, wherein an annotation includes additional information about a fact, and wherein a value of the annotation is indexed to a substring of a fact's value; and sending the attribute and value of the retrieved fact and the retrieved annotation in response to the query. | 32. A computer implemented method of querying a fact repository, performed at a computer system having one or more processors and memory storing one or more programs for execution by the one or more processors, the method comprising: receiving a search query; retrieving at least one fact from the fact repository, the at least one fact corresponding to the received search query and having an attribute and a value, wherein the fact repository includes a plurality of facts associated with objects, wherein a respective fact in the fact repository includes a respective attribute and a respective value, wherein the respective value is a text string, and wherein the plurality of facts are extracted from a plurality of documents; retrieving at least one annotation associated with the at least one fact, the at least one annotation having a value corresponding to the value of the at least one fact, wherein an annotation includes additional information about a fact, and wherein a value of the annotation is indexed to a substring of a fact's value; and sending the attribute and value of the retrieved fact and the retrieved annotation in response to the query. 35. The method of claim 32 , wherein the annotation is retrieved before the at least one fact and the at least one fact is retrieved in accordance with the annotation. | 0.590686 |
9,589,234 | 4 | 5 | 4. The method of claim 3 , further comprising generating a missing-case nogood by negating a missing-case family graph associated with said family of missing cases. | 4. The method of claim 3 , further comprising generating a missing-case nogood by negating a missing-case family graph associated with said family of missing cases. 5. The method of claim 4 , further comprising incorporating said missing-case nogood into the rules inhibition graph. | 0.955138 |
7,596,755 | 1 | 14 | 1. A method of displaying multimedia information stored in a multimedia document on a display, the method comprising: displaying a graphical user interface (GUI) on the display; displaying, in a first area of the GUI, a first visual representation of the multimedia information stored in the multimedia document, the first visual representation including a first representation of information of a first type stored in the multimedia document and a first representation of information of a second type stored in the multimedia document; displaying, in the first area of the GUI, a first lens positionable over a plurality of portions of the first visual representation displayed within the first area of the GUI, the first lens covering a first portion of the first visual representation within the first area; displaying, in a second area of the GUI, a second visual representation of the multimedia information stored in the multimedia document based on the first lens covering the first portion of the first visual representation within the first area, the second visual representation including a second representation of the information of the first type stored in the multimedia document and a second representation of the information of the second type stored in the multimedia document; displaying, in the second area of the GUI, a second lens positionable over a plurality of portions of the second visual representation displayed within the second area of the GUI, the second lens covering a first portion of the second visual representation within the second area; and displaying, in a third area of the GUI, a third visual representation of the multimedia information stored in the multimedia document based on the second lens covering the first portion of the second visual representation within the second area, the third visual representation including a third representation of the information of the first type and a third representation of the information of the second type, wherein displaying the first visual representation of the multimedia information stored in the multimedia document in the first area of the GUI comprises: displaying a first thumbnail image in the first area of the GUI, the first thumbnail image comprising the first representation of the information of the first type; and displaying a second thumbnail image in the first area of the GUI, the second thumbnail image comprising the first representation of the information of the second type, wherein displaying the second visual representation of the multimedia information stored in the multimedia document in the second area of the GUI comprises: displaying, in a first sub-area of the second area of the GUI, the portion of the first representation of the information of the first type covered by the first lens as the second representation of the information of the first type; and displaying, in a second sub-area of the second area of the GUI, the portion of the first representation of the information of the second type covered by the first lens as the second representation of the information of the second type, wherein displaying the third visual representation of the multimedia information stored in the multimedia document in the third area of the GUI comprises: displaying, in a first sub-area of the third area of the GUI, the portion of the second representation of the information of the first type covered by the second lens as the third representation of the information of the first type; and displaying, in a second sub-area of the third area of the GUI, the portion of the second representation of the information of the second type covered by the second lens as the third representation of the information of the first type. | 1. A method of displaying multimedia information stored in a multimedia document on a display, the method comprising: displaying a graphical user interface (GUI) on the display; displaying, in a first area of the GUI, a first visual representation of the multimedia information stored in the multimedia document, the first visual representation including a first representation of information of a first type stored in the multimedia document and a first representation of information of a second type stored in the multimedia document; displaying, in the first area of the GUI, a first lens positionable over a plurality of portions of the first visual representation displayed within the first area of the GUI, the first lens covering a first portion of the first visual representation within the first area; displaying, in a second area of the GUI, a second visual representation of the multimedia information stored in the multimedia document based on the first lens covering the first portion of the first visual representation within the first area, the second visual representation including a second representation of the information of the first type stored in the multimedia document and a second representation of the information of the second type stored in the multimedia document; displaying, in the second area of the GUI, a second lens positionable over a plurality of portions of the second visual representation displayed within the second area of the GUI, the second lens covering a first portion of the second visual representation within the second area; and displaying, in a third area of the GUI, a third visual representation of the multimedia information stored in the multimedia document based on the second lens covering the first portion of the second visual representation within the second area, the third visual representation including a third representation of the information of the first type and a third representation of the information of the second type, wherein displaying the first visual representation of the multimedia information stored in the multimedia document in the first area of the GUI comprises: displaying a first thumbnail image in the first area of the GUI, the first thumbnail image comprising the first representation of the information of the first type; and displaying a second thumbnail image in the first area of the GUI, the second thumbnail image comprising the first representation of the information of the second type, wherein displaying the second visual representation of the multimedia information stored in the multimedia document in the second area of the GUI comprises: displaying, in a first sub-area of the second area of the GUI, the portion of the first representation of the information of the first type covered by the first lens as the second representation of the information of the first type; and displaying, in a second sub-area of the second area of the GUI, the portion of the first representation of the information of the second type covered by the first lens as the second representation of the information of the second type, wherein displaying the third visual representation of the multimedia information stored in the multimedia document in the third area of the GUI comprises: displaying, in a first sub-area of the third area of the GUI, the portion of the second representation of the information of the first type covered by the second lens as the third representation of the information of the first type; and displaying, in a second sub-area of the third area of the GUI, the portion of the second representation of the information of the second type covered by the second lens as the third representation of the information of the first type. 14. The method of claim 1 further comprising: receiving input indicating selection of a portion of the multimedia information occurring between a first time and a second time; and performing a first operation on the portion of the multimedia information occurring between a first time and a second time. | 0.903871 |
8,521,761 | 1 | 9 | 1. A computer-implemented method comprising: identifying, using one or more computers, a plurality of transliterated terms in a target language, where identifying the plurality of transliterated terms in the target language comprises: identifying terms containing only characters of the target language, computing a statistic for each identified term of the terms containing only characters of the target language, where the statistic for each said identified term is based on a ratio of a probability of occurrence of the identified term in resources associated with one or more locales where the source language is spoken to a probability of occurrence of the identified term in resources associated with any locale, comparing the statistic for each said identified term to a specified threshold, and including a particular said identified term in the plurality of transliterated terms in the target language if the statistic for the identified term satisfies the specified threshold; for each transliterated term of the plurality of transliterated terms in the target language, mapping the transliterated term to one or more terms in a source language; and for a first transliterated term of the plurality of transliterated terms in the target language, identifying one or more second transliterated terms of the plurality of transliterated terms in the target language as candidate synonyms of the first transliterated term, where each of the one or more second transliterated terms is mapped to at least one term in the source language that is also mapped from the first transliterated term. | 1. A computer-implemented method comprising: identifying, using one or more computers, a plurality of transliterated terms in a target language, where identifying the plurality of transliterated terms in the target language comprises: identifying terms containing only characters of the target language, computing a statistic for each identified term of the terms containing only characters of the target language, where the statistic for each said identified term is based on a ratio of a probability of occurrence of the identified term in resources associated with one or more locales where the source language is spoken to a probability of occurrence of the identified term in resources associated with any locale, comparing the statistic for each said identified term to a specified threshold, and including a particular said identified term in the plurality of transliterated terms in the target language if the statistic for the identified term satisfies the specified threshold; for each transliterated term of the plurality of transliterated terms in the target language, mapping the transliterated term to one or more terms in a source language; and for a first transliterated term of the plurality of transliterated terms in the target language, identifying one or more second transliterated terms of the plurality of transliterated terms in the target language as candidate synonyms of the first transliterated term, where each of the one or more second transliterated terms is mapped to at least one term in the source language that is also mapped from the first transliterated term. 9. The method of claim 1 , further comprising: for the first transliterated term of the plurality of transliterated terms in the target language, identifying one or more terms in the source language that are mapped from the first transliterated term and from at least one of the one or more second transliterated terms as candidate synonyms of the first transliterated term. | 0.705047 |
9,037,578 | 1 | 3 | 1. A method performed by a computer-implemented content suggestion engine for determining suggested content from a human activity recommendation information system, comprising: obtaining context-sensitive content relevant to attainment of an overall selected goal that is attempted by a human subject, the context-sensitive content produced from content data stored in the human activity recommendation information system, wherein the overall selected goal is attained in connection with changes to human behavior by the human subject in a plurality of real-world activities; determining a set of conditions relevant to the attainment of the overall selected goal to establish a filter and a weight for restricting and prioritizing the context-sensitive content, the set of conditions including one or more conditions obtained from a profile of the human subject, wherein the profile tracks one or more behavior characteristics affecting the attainment of the overall selected goal by the human subject; matching the context-sensitive content to the human subject according to the set of conditions, the matching including applying the filter to exclude content from the context-sensitive content that does not match the set of conditions; prioritizing the context-sensitive content to the human subject according to the set of conditions, the prioritizing including applying the weight to prioritize content in the context-sensitive content that provides a greater match to the profile of the human subject; and selecting suggested content from the filtered and prioritized context-sensitive content for presentation to the human subject. | 1. A method performed by a computer-implemented content suggestion engine for determining suggested content from a human activity recommendation information system, comprising: obtaining context-sensitive content relevant to attainment of an overall selected goal that is attempted by a human subject, the context-sensitive content produced from content data stored in the human activity recommendation information system, wherein the overall selected goal is attained in connection with changes to human behavior by the human subject in a plurality of real-world activities; determining a set of conditions relevant to the attainment of the overall selected goal to establish a filter and a weight for restricting and prioritizing the context-sensitive content, the set of conditions including one or more conditions obtained from a profile of the human subject, wherein the profile tracks one or more behavior characteristics affecting the attainment of the overall selected goal by the human subject; matching the context-sensitive content to the human subject according to the set of conditions, the matching including applying the filter to exclude content from the context-sensitive content that does not match the set of conditions; prioritizing the context-sensitive content to the human subject according to the set of conditions, the prioritizing including applying the weight to prioritize content in the context-sensitive content that provides a greater match to the profile of the human subject; and selecting suggested content from the filtered and prioritized context-sensitive content for presentation to the human subject. 3. The method of claim 1 , wherein the set of conditions relevant to the attainment of the overall selected goal includes a plurality of conditions determined from creation of the profile, the profile being created from one or more of: input collected from the human subject, input collected from a human supporter of the human subject, a psychological model, or a coaching model; and wherein the context-sensitive content is further restricted to activities suggested by the context-sensitive content that match attributes of the profile of the human subject. | 0.795918 |
9,065,914 | 15 | 20 | 15. A computer-readable storage device having instructions stored which, when executed by a processor, cause the processor to perform operations comprising: selecting a spoken dialog application from a plurality of spoken dialog applications; transmitting, over a network, an identification of the selected spoken dialog application, the spoken dialog application having a grammar identifier; selecting a grammar from a plurality of grammars based on the grammar identifier, wherein the grammar is provided by the selected spoken dialog application and chosen from a predetermined group of grammars based upon information provided by the selected spoken dialog application; transmitting digitized user speech over the network while receiving user speech which is digitized into the digitized user speech; receiving partially synthesized speech in response to the digitized user speech, wherein the selected spoken dialog application recognizes the digitized user speech using the grammar; and receiving final synthesized speech in response to the digitized user speech, wherein the receiving of the final synthesized speech occurs after receiving the partially synthesized speech. | 15. A computer-readable storage device having instructions stored which, when executed by a processor, cause the processor to perform operations comprising: selecting a spoken dialog application from a plurality of spoken dialog applications; transmitting, over a network, an identification of the selected spoken dialog application, the spoken dialog application having a grammar identifier; selecting a grammar from a plurality of grammars based on the grammar identifier, wherein the grammar is provided by the selected spoken dialog application and chosen from a predetermined group of grammars based upon information provided by the selected spoken dialog application; transmitting digitized user speech over the network while receiving user speech which is digitized into the digitized user speech; receiving partially synthesized speech in response to the digitized user speech, wherein the selected spoken dialog application recognizes the digitized user speech using the grammar; and receiving final synthesized speech in response to the digitized user speech, wherein the receiving of the final synthesized speech occurs after receiving the partially synthesized speech. 20. The computer-readable storage device of claim 15 , having additional instructions stored which, when executed by the computing device, result in operations comprising: receiving information associated with the final synthesized speech over the network from a client device. | 0.567188 |
8,001,178 | 4 | 5 | 4. A system for providing application content in a variety of languages from a server computing device to a client computing device, comprising: a processor and memory a plurality of language packs residing on the server computing device, each language pack corresponding to a language and comprising unique identifiers and localized strings; and a local string software module configured to execute at the server computing device to determine a language preference specified at the client computing device and, after receiving from the client computing device a HTTP request via an Internet browser for an application, localize strings of the application based on the language preference by providing localized strings from a selected language pack selected using the unique identifiers, and transmit the localized application as the response to the HTTP request. | 4. A system for providing application content in a variety of languages from a server computing device to a client computing device, comprising: a processor and memory a plurality of language packs residing on the server computing device, each language pack corresponding to a language and comprising unique identifiers and localized strings; and a local string software module configured to execute at the server computing device to determine a language preference specified at the client computing device and, after receiving from the client computing device a HTTP request via an Internet browser for an application, localize strings of the application based on the language preference by providing localized strings from a selected language pack selected using the unique identifiers, and transmit the localized application as the response to the HTTP request. 5. The system of claim 4 , wherein the local string software module is configured to determine whether the client computing device has indicated a language preference and if the indicated language preference matches a selected one of the language packs, set a language variable to the indicated language preference. | 0.727509 |
7,809,664 | 12 | 16 | 12. One or more machine-readable storage medium storing instructions which, when executed by one or more processors, cause the performance of: extracting, by a question answering (QA) system, a set of features from a current question; performing, by the QA system, a comparison between (a) said set of features from said current question and (b) a set of features from one or more previously-submitted questions; selecting, based on the comparison, an answer to said current question from a set of answers to said one or more previously-submitted questions; displaying said answer in conjunction with a set of user-submitted answers to said current question; receiving user input that rates at least one user-submitted answer of said user-submitted answers higher than said answer; identifying one or more characteristics of the at least one user-submitted answer that are different from said answer; and based on the one or more characteristics, modifying one or more elements of the QA system. | 12. One or more machine-readable storage medium storing instructions which, when executed by one or more processors, cause the performance of: extracting, by a question answering (QA) system, a set of features from a current question; performing, by the QA system, a comparison between (a) said set of features from said current question and (b) a set of features from one or more previously-submitted questions; selecting, based on the comparison, an answer to said current question from a set of answers to said one or more previously-submitted questions; displaying said answer in conjunction with a set of user-submitted answers to said current question; receiving user input that rates at least one user-submitted answer of said user-submitted answers higher than said answer; identifying one or more characteristics of the at least one user-submitted answer that are different from said answer; and based on the one or more characteristics, modifying one or more elements of the QA system. 16. The one or more machine-readable storage media of claim 12 , wherein selecting an answer to said current question from said set of answers includes: computing a confidence value for the answer; and determining if said confidence value exceeds a specified threshold. | 0.678998 |
7,624,277 | 46 | 49 | 46. A computer-readable storage medium having stored thereon a data structure for use as a test for distinguishing a human from a machine, said data structure comprising: a plurality of human-readable textual characters randomly selected from a predefined set of available characters; said characters being individually altered to inhibit computerized character recognition, said altered characters being concatenated into a character string, said character string being included in an original image wherein each of the characters of said character string have a particular coloring, said original image being subjected to an operation to further alter the character string and to further inhibit computerized character recognition according to a configurable difficulty factor, said operation adding random arcs to the original image, at least one of said random arcs altering the particular coloring of a segment of at least one of the characters of the character string at least one of said random arcs linking a plurality of the characters, and said altered original image to be rendered to a user as a test having a level of difficulty in computerized character recognition represented by the difficulty factor. | 46. A computer-readable storage medium having stored thereon a data structure for use as a test for distinguishing a human from a machine, said data structure comprising: a plurality of human-readable textual characters randomly selected from a predefined set of available characters; said characters being individually altered to inhibit computerized character recognition, said altered characters being concatenated into a character string, said character string being included in an original image wherein each of the characters of said character string have a particular coloring, said original image being subjected to an operation to further alter the character string and to further inhibit computerized character recognition according to a configurable difficulty factor, said operation adding random arcs to the original image, at least one of said random arcs altering the particular coloring of a segment of at least one of the characters of the character string at least one of said random arcs linking a plurality of the characters, and said altered original image to be rendered to a user as a test having a level of difficulty in computerized character recognition represented by the difficulty factor. 49. The computer-readable storage medium of claim 46 wherein segments of the characters in the altered original image have varying line thickness for distorting the character string. | 0.876359 |
9,686,283 | 16 | 20 | 16. A non-transitory computer-readable storage medium storing one or more instructions that, upon execution by one or more processors, causes the one or more processors to: render a document object model (DOM) object of a website using website information; generate a hash signature of the DOM object of the website by: applying a number of hashing functions to each of a plurality of data portions separated from content within the DOM object of the website; and generating a hash signature of the DOM object of the website by selecting a number of hashed data portions of the plurality of hashed data portions; obtain a known hash signature of a DOM object associated with each of a plurality of known websites associated with a classification; compare the hash signature of the DOM object of the website to a known hash signature of the DOM object associated with each of the plurality of known websites, wherein comparing the hash signature of the DOM object of the website to the known hash signature of the DOM object associated with each of the plurality of known websites includes comparing each of the plurality of hashed data portions to a plurality of known hashed data portions of the known hash signature; based on determining that the hash signature of the DOM object of the website does not match the known hash signature of the DOM object associated with each of the plurality of known websites: for each of the plurality of known websites associated with the classification: compute a similarity measurement between the hash signature of the DOM object of the website and the known hash signature of the DOM object associated with the known websites associated with the classification; determine whether a threshold associated with the classification is satisfied based on the similarity measurement computed between the hash signature of the DOM object of the website and the known hash signature of the DOM object for each of the plurality of known websites; and determine whether to classify the website as confirmed for the classification based on determining whether the threshold associated with the classification is satisfied. | 16. A non-transitory computer-readable storage medium storing one or more instructions that, upon execution by one or more processors, causes the one or more processors to: render a document object model (DOM) object of a website using website information; generate a hash signature of the DOM object of the website by: applying a number of hashing functions to each of a plurality of data portions separated from content within the DOM object of the website; and generating a hash signature of the DOM object of the website by selecting a number of hashed data portions of the plurality of hashed data portions; obtain a known hash signature of a DOM object associated with each of a plurality of known websites associated with a classification; compare the hash signature of the DOM object of the website to a known hash signature of the DOM object associated with each of the plurality of known websites, wherein comparing the hash signature of the DOM object of the website to the known hash signature of the DOM object associated with each of the plurality of known websites includes comparing each of the plurality of hashed data portions to a plurality of known hashed data portions of the known hash signature; based on determining that the hash signature of the DOM object of the website does not match the known hash signature of the DOM object associated with each of the plurality of known websites: for each of the plurality of known websites associated with the classification: compute a similarity measurement between the hash signature of the DOM object of the website and the known hash signature of the DOM object associated with the known websites associated with the classification; determine whether a threshold associated with the classification is satisfied based on the similarity measurement computed between the hash signature of the DOM object of the website and the known hash signature of the DOM object for each of the plurality of known websites; and determine whether to classify the website as confirmed for the classification based on determining whether the threshold associated with the classification is satisfied. 20. The non-transitory computer-readable storage medium of claim 16 , wherein the classification is a first classification as a phishing website, a second classification as copyrighted content, or a third classification as unauthorized content. | 0.887142 |
9,646,606 | 1 | 2 | 1. A method of performing speech recognition that is performed by one or more computers of an automated speech recognizer, the method comprising: receiving, by the one or more computers, data that indicates multiple candidate transcriptions for an utterance, wherein the one or more computers are in communication with (i) a first search system that provides a search service of a first domain, and (ii) a second search system that provides a search service for a second domain, the second domain being different from the first domain; for each particular candidate transcription of the candidate transcriptions: receiving, by the one or more computers, data from the first search system that provides the search service for the first domain, the data from the first search system indicating first search results that the search service for the first domain identifies as relevant to the particular candidate transcription; determining, by the one or more computers, a first score based on the first search results that the search service for the first domain identifies as relevant to the particular candidate transcription; receiving, by the one or more computers, data from the second search system that provides the search service for the second domain, the data from the second search system indicating second search results that the search service for the second domain identifies as relevant to the particular candidate transcription; determining, by the one or more computers, a second score based on the second search results that the search service for the second domain identifies as relevant to the particular candidate transcription; providing, by the one or more computers, (i) the first score that is determined based on the first search results and (ii) the second score that is determined based on the second search results as input to a classifier, wherein the classifier has been trained, using scores that represent characteristics of different search results from different domains, to indicate a likelihood that a transcription is correct based on scores for multiple different domains; and receiving, by the one or more computers and from the trained classifier, a classifier output in response to at least the first score and the second score, the classifier output indicating a likelihood that the particular candidate transcription is correct; selecting, by the one or more computers, a transcription for the utterance, from among the multiple candidate transcriptions, based on the classifier outputs; and providing, by the one or more computers, the transcription as output of the automated speech recognizer. | 1. A method of performing speech recognition that is performed by one or more computers of an automated speech recognizer, the method comprising: receiving, by the one or more computers, data that indicates multiple candidate transcriptions for an utterance, wherein the one or more computers are in communication with (i) a first search system that provides a search service of a first domain, and (ii) a second search system that provides a search service for a second domain, the second domain being different from the first domain; for each particular candidate transcription of the candidate transcriptions: receiving, by the one or more computers, data from the first search system that provides the search service for the first domain, the data from the first search system indicating first search results that the search service for the first domain identifies as relevant to the particular candidate transcription; determining, by the one or more computers, a first score based on the first search results that the search service for the first domain identifies as relevant to the particular candidate transcription; receiving, by the one or more computers, data from the second search system that provides the search service for the second domain, the data from the second search system indicating second search results that the search service for the second domain identifies as relevant to the particular candidate transcription; determining, by the one or more computers, a second score based on the second search results that the search service for the second domain identifies as relevant to the particular candidate transcription; providing, by the one or more computers, (i) the first score that is determined based on the first search results and (ii) the second score that is determined based on the second search results as input to a classifier, wherein the classifier has been trained, using scores that represent characteristics of different search results from different domains, to indicate a likelihood that a transcription is correct based on scores for multiple different domains; and receiving, by the one or more computers and from the trained classifier, a classifier output in response to at least the first score and the second score, the classifier output indicating a likelihood that the particular candidate transcription is correct; selecting, by the one or more computers, a transcription for the utterance, from among the multiple candidate transcriptions, based on the classifier outputs; and providing, by the one or more computers, the transcription as output of the automated speech recognizer. 2. The method of claim 1 , further comprising, for each particular candidate transcription of the candidate transcriptions, receiving, by the one or more computers, data indicating a frequency that users have submitted the particular candidate transcription as a search query; and wherein providing, by the one or more computers, (i) the first score that is determined based on the first search results and (ii) the second score that is determined based on the second search results as input to the classifier comprises providing, by the one or more computers, the first score, the second score, and a third score that is indicative of the frequency that users have submitted the particular candidate transcription as a search query as input to the classifier. | 0.802186 |
10,147,038 | 1 | 7 | 1. A computer implemented method of integrating a trained model trained on a training data set into an application, the method comprising: instantiating, by a project engine, a mechanical turk project that includes a plurality of tasks available to project members; receiving, by the project engine, project results data from the project members; generating, by the project engine, a training data set from the project results data; training, by the project engine, a trained model from the training data set; converting, by an application generator module, the project results data in the form of the trained model into a trained application module formatted for integration into an application; and causing, by the application generator module, integration of the trained application module into the application. | 1. A computer implemented method of integrating a trained model trained on a training data set into an application, the method comprising: instantiating, by a project engine, a mechanical turk project that includes a plurality of tasks available to project members; receiving, by the project engine, project results data from the project members; generating, by the project engine, a training data set from the project results data; training, by the project engine, a trained model from the training data set; converting, by an application generator module, the project results data in the form of the trained model into a trained application module formatted for integration into an application; and causing, by the application generator module, integration of the trained application module into the application. 7. The method of claim 1 , wherein the plurality of tasks comprise picture tasks. | 0.864094 |
8,661,331 | 1 | 18 | 1. A computer-implemented method of providing visual access to comment markings that are supplied by a plurality of meeting participants, said method comprising: creating printed meeting documents using a printer having a print driver that automatically includes metadata in said printed meeting documents, each printed meeting document comprising a human-readable content marking related to a subject of a meeting attended by said plurality of meeting participants, a personal marking that identifies a corresponding meeting participant to whom said printed meeting documents is provided, and a storage address marking, said print driver automatically determining a location in said printed meeting documents for said human-readable content marking, said personal marking, and said storage address marking; providing one or more printed meeting documents to each of said plurality of meeting participants; at least one of said plurality of meeting participants, supplying one or more comment markings to said one or more printed meeting documents, thus forming one or more commented meeting documents; scanning, using a scanner, said one or more commented meeting documents, thus forming one or more commented meeting document images; storing said one or more commented meeting document images in a computer storage repository based on said storage address marking; and providing one or more users visual access to said one or more commented meeting document images, thus enabling said one or more users to view said one or more comment markings that are supplied by said at least one of said plurality of meeting participants, said one or more commented meeting document images further comprising said personal marking corresponding to said one or more comment markings allowing said one or more users to identify said one or more meeting participants who supply said one or more comment markings. | 1. A computer-implemented method of providing visual access to comment markings that are supplied by a plurality of meeting participants, said method comprising: creating printed meeting documents using a printer having a print driver that automatically includes metadata in said printed meeting documents, each printed meeting document comprising a human-readable content marking related to a subject of a meeting attended by said plurality of meeting participants, a personal marking that identifies a corresponding meeting participant to whom said printed meeting documents is provided, and a storage address marking, said print driver automatically determining a location in said printed meeting documents for said human-readable content marking, said personal marking, and said storage address marking; providing one or more printed meeting documents to each of said plurality of meeting participants; at least one of said plurality of meeting participants, supplying one or more comment markings to said one or more printed meeting documents, thus forming one or more commented meeting documents; scanning, using a scanner, said one or more commented meeting documents, thus forming one or more commented meeting document images; storing said one or more commented meeting document images in a computer storage repository based on said storage address marking; and providing one or more users visual access to said one or more commented meeting document images, thus enabling said one or more users to view said one or more comment markings that are supplied by said at least one of said plurality of meeting participants, said one or more commented meeting document images further comprising said personal marking corresponding to said one or more comment markings allowing said one or more users to identify said one or more meeting participants who supply said one or more comment markings. 18. The method of claim 1 , each of said one or more printed meeting documents further comprising a meeting marking that identifies or describes said meeting. | 0.598985 |
4,581,601 | 16 | 17 | 16. The apparatus of claim 15 wherein said memory device is a read only memory. | 16. The apparatus of claim 15 wherein said memory device is a read only memory. 17. The apparatus of claim 16 for coding information comprising means for multipling each component of the code words from said read only memory by said expanded and converted second group of signals to derive an encoded four-dimensional symbol for each block of information. | 0.852784 |
8,941,870 | 1 | 2 | 1. A multifunction peripheral comprising: a network interface for accessing a data source including data to be inserted into a plurality of files generated using a template and the data source; a user interface including a display device integral to the multifunction peripheral for receiving user input identifying template elements that act as location placeholders within an electronic document for data from the data source; a controller for generating the template from the electronic document using the identified template elements; the controller further for generating a preview of a file generated using the template and the data source, the preview visible on the display device; the user interface further for receiving selection of an output destination for the plurality of files generated using the template and the data source; the controller further for generating the plurality of files using the template and the data source; and the network interface further for sending the plurality of files to the output destination. | 1. A multifunction peripheral comprising: a network interface for accessing a data source including data to be inserted into a plurality of files generated using a template and the data source; a user interface including a display device integral to the multifunction peripheral for receiving user input identifying template elements that act as location placeholders within an electronic document for data from the data source; a controller for generating the template from the electronic document using the identified template elements; the controller further for generating a preview of a file generated using the template and the data source, the preview visible on the display device; the user interface further for receiving selection of an output destination for the plurality of files generated using the template and the data source; the controller further for generating the plurality of files using the template and the data source; and the network interface further for sending the plurality of files to the output destination. 2. The multifunction peripheral of claim 1 wherein the network interface is further for saving the template for later use after generating the template. | 0.759494 |
9,330,065 | 6 | 7 | 6. The method of claim 1 , wherein the receiving of a specification of the optimization path is performed based on one or more commands received through the graphical user interface from the user that specify a line extending over the template elements of the template element group in the template design area. | 6. The method of claim 1 , wherein the receiving of a specification of the optimization path is performed based on one or more commands received through the graphical user interface from the user that specify a line extending over the template elements of the template element group in the template design area. 7. The method of claim 6 , wherein the specification defines the optimization path in terms of a directed graph of nodes respectively representing the template elements in the template element group, and the generating comprises ordering the nodes of the directed graph in accordance with the relative positions of the template elements along the line in the template design area. | 0.898613 |
9,582,493 | 3 | 4 | 3. The method of claim 1 , wherein the second plurality of lemmas are generated from a version of a web domain in the second language. | 3. The method of claim 1 , wherein the second plurality of lemmas are generated from a version of a web domain in the second language. 4. The method of claim 3 , wherein the first plurality of lemmas are generated from a version of the web domain in the first language. | 0.940338 |
7,694,227 | 1 | 4 | 1. A method of obtaining a list of resource links indexed by categories in a interlinked category structure to be presented to a user via a user interface, the resource links pointing to resources on a network, the method comprising the following steps to be carried out by a computer system: monitoring users' interactions with resource links by: for users' interaction with a category in the interlinked category structure, generating a usage entry in a usage table on a server computer, wherein each usage entry includes a set of activity parameters including a link ID and a user ID; analyzing a user's interaction with the resource links placed in said category, including retrieving, from the usage table, the user's entries for resource links within said category; and calculating a user rating for the user in said category; rating resource links from categories in the category structure, the rating including: retrieving resource links placed within a given category; and rating the retrieved resource links using accumulated sets of activity parameters in the usage table, the resource links' ratings being based on calculated user ratings of a plurality of users who have previously interacted with a resource link within the given category. | 1. A method of obtaining a list of resource links indexed by categories in a interlinked category structure to be presented to a user via a user interface, the resource links pointing to resources on a network, the method comprising the following steps to be carried out by a computer system: monitoring users' interactions with resource links by: for users' interaction with a category in the interlinked category structure, generating a usage entry in a usage table on a server computer, wherein each usage entry includes a set of activity parameters including a link ID and a user ID; analyzing a user's interaction with the resource links placed in said category, including retrieving, from the usage table, the user's entries for resource links within said category; and calculating a user rating for the user in said category; rating resource links from categories in the category structure, the rating including: retrieving resource links placed within a given category; and rating the retrieved resource links using accumulated sets of activity parameters in the usage table, the resource links' ratings being based on calculated user ratings of a plurality of users who have previously interacted with a resource link within the given category. 4. A method according to claim 1 , wherein the resource links ratings are arranged in a rated list of resource links where higher rated resource links are accessed by higher rated users. | 0.749326 |
8,949,263 | 1 | 21 | 1. A method for graphically characterizing statements about an object, comprising: applying, as a result of computing hardware and programmable memory, frame extraction, to a first corpus, in order to attempt to identify, for each statement of the corpus, an object and a sentiment expressed about the object; identifying, as a result of computing hardware and programmable memory, a first object-specific corpus, that is a subset of the first corpus, where all the statements of the first object-specific corpus are about a same first object; categorizing, as a result of computing hardware and programmable memory, a sentiment of each statement, of the first object-specific corpus; categorizing a polarity of each statement, of the first object-specific corpus; categorizing an intensity of each statement, of the first object-specific corpus; determining, as a result of computing hardware and programmable memory, a net polarity measure as a function of the polarity categorization and a net intensity measure as a function of the intensity categorization; producing, as a result of computing hardware and programmable memory, a first graphical representation, of the first object-specific corpus; placing the first graphical representation, relative to a first axis, in accordance with the net polarity measure; and placing the first graphical representation, relative to a second axis, in accordance with the net intensity measure. | 1. A method for graphically characterizing statements about an object, comprising: applying, as a result of computing hardware and programmable memory, frame extraction, to a first corpus, in order to attempt to identify, for each statement of the corpus, an object and a sentiment expressed about the object; identifying, as a result of computing hardware and programmable memory, a first object-specific corpus, that is a subset of the first corpus, where all the statements of the first object-specific corpus are about a same first object; categorizing, as a result of computing hardware and programmable memory, a sentiment of each statement, of the first object-specific corpus; categorizing a polarity of each statement, of the first object-specific corpus; categorizing an intensity of each statement, of the first object-specific corpus; determining, as a result of computing hardware and programmable memory, a net polarity measure as a function of the polarity categorization and a net intensity measure as a function of the intensity categorization; producing, as a result of computing hardware and programmable memory, a first graphical representation, of the first object-specific corpus; placing the first graphical representation, relative to a first axis, in accordance with the net polarity measure; and placing the first graphical representation, relative to a second axis, in accordance with the net intensity measure. 21. The method of claim 1 , wherein the net polarity and intensity measures have a very low correlation. | 0.974129 |
8,681,098 | 44 | 45 | 44. The system of claim 43 , wherein the generating of the at least one data sequence comprises: generating a first respective data set that includes first respective gestural event data; generating a second respective data set that includes second respective state information; and forming a second data sequence to include the first respective data set and the second respective data set. | 44. The system of claim 43 , wherein the generating of the at least one data sequence comprises: generating a first respective data set that includes first respective gestural event data; generating a second respective data set that includes second respective state information; and forming a second data sequence to include the first respective data set and the second respective data set. 45. The system of claim 44 , wherein the generating of the first respective data set includes generating a first respective data set offset, wherein the first respective data set offset points to the first respective data set of the second data sequence. | 0.887411 |
8,564,721 | 1 | 6 | 1. A method for synchronizing text with audio in a preexisting multimedia file, comprising the steps of: receiving the multimedia file and parsing the audio from the multimedia file while maintaining the timeline synchronization between the video portions and audio portions of the multimedia file; receiving closed-captioned data associated with the multimedia file, where the closed-captioned data contains closed-captioned text, each word of which is associated with a corresponding word spoken in the audio portion; generating text representations of parsed audio of the input multimedia file where each word of the text representation is associated approximately with the corresponding words spoken in the video portion; generating a probabilistic model predicting a next item in a sequence to compare each word of the closed-captioned text with a plurality of words of the text representation until a match is found; synchronizing each closed-captioned word with a respective point on the timeline in which each matched word is spoken in the audio and occurs within the video, where each matched word is associated with the accurate point on the timeline; providing the accurate, time-based text output to a database and associating said output with the original multimedia file. | 1. A method for synchronizing text with audio in a preexisting multimedia file, comprising the steps of: receiving the multimedia file and parsing the audio from the multimedia file while maintaining the timeline synchronization between the video portions and audio portions of the multimedia file; receiving closed-captioned data associated with the multimedia file, where the closed-captioned data contains closed-captioned text, each word of which is associated with a corresponding word spoken in the audio portion; generating text representations of parsed audio of the input multimedia file where each word of the text representation is associated approximately with the corresponding words spoken in the video portion; generating a probabilistic model predicting a next item in a sequence to compare each word of the closed-captioned text with a plurality of words of the text representation until a match is found; synchronizing each closed-captioned word with a respective point on the timeline in which each matched word is spoken in the audio and occurs within the video, where each matched word is associated with the accurate point on the timeline; providing the accurate, time-based text output to a database and associating said output with the original multimedia file. 6. The method of claim 1 , where matching strings of characters between the words of the closed-captioned text with the words of the text representation is performed to attempt to find exact or phonetically similar matches. | 0.769628 |
9,239,710 | 8 | 9 | 8. The method of claim 1 , further comprising generating an output based at least on the transformed abstract syntax tree. | 8. The method of claim 1 , further comprising generating an output based at least on the transformed abstract syntax tree. 9. The method of claim 8 , wherein the output is any one of the following: a pretty printing textual report of at least a portion of the transformed abstract syntax tree; a pretty printing graphical of the at least a portion of the transformed abstract syntax tree; and a database file representing the at least a portion of the transformed abstract syntax tree. | 0.952543 |
8,140,549 | 9 | 11 | 9. The computer program product of claim 8 , wherein: the computer product further comprises program instructions to create an array object based upon a set of dimension objects; and the program instructions to create the filter object comprise program instructions to reference one or more elements of the array object by the filter object, wherein: the one or more elements of the filter object refer to one or more elements of the set of dimension objects; and a specification of the one or more elements of the set of dimension objects comprise a reference to the one or more elements of the array object. | 9. The computer program product of claim 8 , wherein: the computer product further comprises program instructions to create an array object based upon a set of dimension objects; and the program instructions to create the filter object comprise program instructions to reference one or more elements of the array object by the filter object, wherein: the one or more elements of the filter object refer to one or more elements of the set of dimension objects; and a specification of the one or more elements of the set of dimension objects comprise a reference to the one or more elements of the array object. 11. The computer program product of claim 9 , wherein the program instructions to create the filter object comprise program instructions to create a filter object containing one element from each dimension of the set of dimensions of the array. | 0.908614 |
8,929,615 | 35 | 39 | 35. A system comprising: one or more processors; and a memory coupled to the processors comprising instructions executable by the processors, the processors being operable when executing the instructions to: extract one or more features from a photo; calculate an engagement metric for the photo based on the one or more extracted features, wherein the engagement metric represents the probability that one or more users will interact with the photo; and apply one or more policies to the photo based on the engagement metric. | 35. A system comprising: one or more processors; and a memory coupled to the processors comprising instructions executable by the processors, the processors being operable when executing the instructions to: extract one or more features from a photo; calculate an engagement metric for the photo based on the one or more extracted features, wherein the engagement metric represents the probability that one or more users will interact with the photo; and apply one or more policies to the photo based on the engagement metric. 39. The system of claim 35 , the instructions to extract one or more features comprising instructions to: apply one or more image object recognition algorithms to the photo; detect one or more image objects via the one or more algorithms; and for each detected object, associate the photo with an object node representing the detected object in a social graph. | 0.501385 |
7,848,995 | 13 | 22 | 13. A computer real-time analysis system, relating to assisting decision making, by at least one trader, related to buying and selling at least one tradable instrument comprising: a) at least one computer processor adapted for receiving, in substantially real-time, historical time-relevant trading data relating to such at least one tradable instrument; b) at least one computer processor adapted for calculating, as at least one first calculation, in substantially real-time, at least one first time-relevant value representing historical collective desire to sell such at least one tradable instrument using such historical time-relevant trading data for at least one plurality of timeframes, wherein such at least one plurality of timeframes comprise discrete periods of time, each of substantially different time lengths than each other, from at least one minute to at least one year; c) at least one computer processor adapted for calculating, as at least one second calculation, in substantially real-time, at least one second time-relevant value representing historical collective desire to buy such at least one tradable instrument using such historical time-relevant trading data for such at least one plurality of timeframes; d) at least one computer processor adapted for comparing, in substantially real-time, such historical collective desire to sell such at least one tradable instrument to such historical collective desire to buy such at least one tradable instrument to make a first determining of at least one “greater-lesser relationship” between such historical collective desire to buy and such historical collective desire to sell for at least one timeframe of such at least one plurality of timeframes; e) at least one computer processor for comparing, in at least one prior timeframe, such historical collective desire to sell such at least one tradable instrument to such historical collective desire to buy such at least one tradable instrument to make a second determining of at least one “greater-lesser relationship” between such historical collective desire to buy and such historical collective desire to sell for at least one timeframe of such at least one plurality of timeframes; f) at least one computer processor adapted for comparing such first determining with such second determining; g) at least one computer processor adapted for identifying any reversal of such “greater-lesser relationship” between such first determining and such second determining; h) at least one computer processor adapted for creating, in substantially real time, at least one set of buy/sell indicators for such at least one tradable instrument for each such indentified reversal; i) at least one computer processor adapted for creating at least one first graphical representation of such at least one first time-relevant value for such at least one timeframe; j) at least one computer processor adapted for creating at least one second graphical representation of such at least one second time-relevant value for such at least one timeframe; k) at least one computer processor adapted for jointly displaying such at least one first graphical representation and such at least one second graphical representation in at least one comparative analysis chart providing at least one system relating to comparative analysis; l) at least one computer processor adapted for automatically comparing such historical collective desire to sell such at least one tradable instrument to such historical collective desire to buy such at least one tradable instrument to determine at least one “greater-lesser relationship” for at least one plurality of such periods of time of such at least one plurality of timeframes; m) at least one computer processor adapted for automatically notifying such at least one trader of such results of such comparison for each of such at least one plurality of such periods of time for such at least one plurality of timeframes; and n) at least one computer processor adapted for automatically notifying such at least one trader when such at least one reversal of such “greater-lesser relationship” occurs in at least two such discrete periods of time. | 13. A computer real-time analysis system, relating to assisting decision making, by at least one trader, related to buying and selling at least one tradable instrument comprising: a) at least one computer processor adapted for receiving, in substantially real-time, historical time-relevant trading data relating to such at least one tradable instrument; b) at least one computer processor adapted for calculating, as at least one first calculation, in substantially real-time, at least one first time-relevant value representing historical collective desire to sell such at least one tradable instrument using such historical time-relevant trading data for at least one plurality of timeframes, wherein such at least one plurality of timeframes comprise discrete periods of time, each of substantially different time lengths than each other, from at least one minute to at least one year; c) at least one computer processor adapted for calculating, as at least one second calculation, in substantially real-time, at least one second time-relevant value representing historical collective desire to buy such at least one tradable instrument using such historical time-relevant trading data for such at least one plurality of timeframes; d) at least one computer processor adapted for comparing, in substantially real-time, such historical collective desire to sell such at least one tradable instrument to such historical collective desire to buy such at least one tradable instrument to make a first determining of at least one “greater-lesser relationship” between such historical collective desire to buy and such historical collective desire to sell for at least one timeframe of such at least one plurality of timeframes; e) at least one computer processor for comparing, in at least one prior timeframe, such historical collective desire to sell such at least one tradable instrument to such historical collective desire to buy such at least one tradable instrument to make a second determining of at least one “greater-lesser relationship” between such historical collective desire to buy and such historical collective desire to sell for at least one timeframe of such at least one plurality of timeframes; f) at least one computer processor adapted for comparing such first determining with such second determining; g) at least one computer processor adapted for identifying any reversal of such “greater-lesser relationship” between such first determining and such second determining; h) at least one computer processor adapted for creating, in substantially real time, at least one set of buy/sell indicators for such at least one tradable instrument for each such indentified reversal; i) at least one computer processor adapted for creating at least one first graphical representation of such at least one first time-relevant value for such at least one timeframe; j) at least one computer processor adapted for creating at least one second graphical representation of such at least one second time-relevant value for such at least one timeframe; k) at least one computer processor adapted for jointly displaying such at least one first graphical representation and such at least one second graphical representation in at least one comparative analysis chart providing at least one system relating to comparative analysis; l) at least one computer processor adapted for automatically comparing such historical collective desire to sell such at least one tradable instrument to such historical collective desire to buy such at least one tradable instrument to determine at least one “greater-lesser relationship” for at least one plurality of such periods of time of such at least one plurality of timeframes; m) at least one computer processor adapted for automatically notifying such at least one trader of such results of such comparison for each of such at least one plurality of such periods of time for such at least one plurality of timeframes; and n) at least one computer processor adapted for automatically notifying such at least one trader when such at least one reversal of such “greater-lesser relationship” occurs in at least two such discrete periods of time. 22. The computer real-time analysis system according to claim 13 further comprising at least one computer processor adapted for automatically notifying such at least one trader when such at least one reversal of such “greater-lesser relationship” occurs in at least three such discrete periods of time. | 0.882031 |
8,635,222 | 17 | 19 | 17. A computer program product comprising a non-transitory computer usable medium having a computer readable program embodied in the non-transitory medium, wherein the computer readable program when executed on a computing device is operable such that the computing device can: store information associated with a web service in a first database of a Universal Description, Discovery, and Integration (UDDI) registry, wherein the first database of the UDDI registry comprises data entries from at least one of white pages, yellow pages, and green pages of the UDDI registry that include the information associated with the web service; store a comment from a first user concerning the web service in a second database, wherein the second database is linked to the first database; determine a rating associated with the first user; store the rating of the first user in the second database; receive a search query from a second user for the information about the web service; retrieve the information about the web service from the first database; retrieve the comment and the rating associated with the web service from the first database; transmit the information about the web service, the comment, and the rating to a second user; receive feedback from the second user regarding the comment from the first user; and determine an updated rating based upon the feedback and the rating, wherein the determination of the rating and the updated rating is performed using a user score manager associated with the UDDI registry. | 17. A computer program product comprising a non-transitory computer usable medium having a computer readable program embodied in the non-transitory medium, wherein the computer readable program when executed on a computing device is operable such that the computing device can: store information associated with a web service in a first database of a Universal Description, Discovery, and Integration (UDDI) registry, wherein the first database of the UDDI registry comprises data entries from at least one of white pages, yellow pages, and green pages of the UDDI registry that include the information associated with the web service; store a comment from a first user concerning the web service in a second database, wherein the second database is linked to the first database; determine a rating associated with the first user; store the rating of the first user in the second database; receive a search query from a second user for the information about the web service; retrieve the information about the web service from the first database; retrieve the comment and the rating associated with the web service from the first database; transmit the information about the web service, the comment, and the rating to a second user; receive feedback from the second user regarding the comment from the first user; and determine an updated rating based upon the feedback and the rating, wherein the determination of the rating and the updated rating is performed using a user score manager associated with the UDDI registry. 19. The computer program product of claim 17 , wherein the computer readable program is operable such that the computing device can store the updated rating in the second database. | 0.88806 |
8,478,766 | 5 | 12 | 5. A computer-implemented method of processing business data, the method comprising: specifying a plurality of ontologies that are based on axioms and rules for processing the axioms, the ontologies written in subject-predicate-object (SPO) triplet format; generating a request to a presentation engine for presenting data to a user; specifying a representation of the SPO triplets in a particular context; wherein the context is specified by a particular ontology and representing an environment surrounding a particular event, object or individual that defines an interpretation of the user data, and any actions or operations on the user data in a particular situation, including a method of processing the user data; using a user-selected ontology, preparing a requested data representation, wherein rules needed to respond to the request from the user, based on one of the elements of the SPO triplet being responsive to the request, are compiled and processed by the engine, without re-compiling previously compiled rules, wherein a particular business application stores its data in multiple databases, and wherein the data in the SPO triplet format is processed and presented to the user in the particular context, including filtering the user data based on connections between objects established by the ontologies and the SPO triplets and adding new ontologies that include new rules, such that the processing includes performing operations on the axioms based on event-defined triggers specified by the rules and generating new axioms in the particular context, and transforming one set of SPO triplets into different set of SPO triplets. | 5. A computer-implemented method of processing business data, the method comprising: specifying a plurality of ontologies that are based on axioms and rules for processing the axioms, the ontologies written in subject-predicate-object (SPO) triplet format; generating a request to a presentation engine for presenting data to a user; specifying a representation of the SPO triplets in a particular context; wherein the context is specified by a particular ontology and representing an environment surrounding a particular event, object or individual that defines an interpretation of the user data, and any actions or operations on the user data in a particular situation, including a method of processing the user data; using a user-selected ontology, preparing a requested data representation, wherein rules needed to respond to the request from the user, based on one of the elements of the SPO triplet being responsive to the request, are compiled and processed by the engine, without re-compiling previously compiled rules, wherein a particular business application stores its data in multiple databases, and wherein the data in the SPO triplet format is processed and presented to the user in the particular context, including filtering the user data based on connections between objects established by the ontologies and the SPO triplets and adding new ontologies that include new rules, such that the processing includes performing operations on the axioms based on event-defined triggers specified by the rules and generating new axioms in the particular context, and transforming one set of SPO triplets into different set of SPO triplets. 12. The method of claim 5 , further comprising generation of a data representation for the same data but in a new context. | 0.810559 |
8,392,825 | 1 | 4 | 1. A method comprising: dividing a first version of a document into one or more sections; generating a condensed version of the document that includes a linkcorresponding to at least one of the one or more sections; transmitting the condensed version of the document to a mobile device for display; receiving a modified version of the document from the mobile device, the modified version including one or more edits to one or more of the sections; and re-aggregating the modified one or more sections with unmodified sections to form a revised document. | 1. A method comprising: dividing a first version of a document into one or more sections; generating a condensed version of the document that includes a linkcorresponding to at least one of the one or more sections; transmitting the condensed version of the document to a mobile device for display; receiving a modified version of the document from the mobile device, the modified version including one or more edits to one or more of the sections; and re-aggregating the modified one or more sections with unmodified sections to form a revised document. 4. The method of claim 1 , wherein the one or more sections correspond to one or more headers in the first version of the document. | 0.774138 |
9,449,220 | 8 | 9 | 8. A system for detecting cookware, the system comprising: a vision sensor positioned so as to collect imagery depicting a cooktop; one or more processors; and one or more non-transitory computer-readable media storing instructions that, when executed by the one or more processors, cause the one or more processors to perform operations, the operations comprising: obtaining a first plurality of images, wherein the first plurality of images depict cookware upon the cooktop; storing the first plurality of images in a memory as a positive image training dataset; obtaining a second plurality of images, wherein the second plurality of images do not depict cookware upon the cooktop; storing the second plurality of images in the memory as a negative image training dataset; training a classifier based on the positive image training dataset and the negative image training dataset; identifying one or more locations respectively associated with one or more burners included in the cooktop, wherein identifying, by one or more computing devices, the one or more locations respectively associated with the one or more burners comprises: obtaining a reference frame of imagery depicting the cooktop without any objects placed thereon; obtaining one or more calibration frames of imagery depicting the cooktop with one or more items of cookware respectively positioned at the one or more locations respectively associated with the one or more burners, wherein the one or more calibration frames of imagery are captured when motion is not detected at the cooktop; performing background subtraction for the one or more calibration frames of imagery with respect to the reference frame of imagery to identify new imagery; and segmenting the new imagery to identify the one or more locations respectively associated with the one or more burners; segmenting a frame of imagery captured by the vision sensor into one or more image segments based at least in part on the one or more locations respectively associated with the one or more burners included in the cooktop; using the classifier to provide an initial classification for each of the one or more image segments, the initial classification for each of the one or more image segments classifying such image segment into either a first class of images depicting cookware or a second class of images not depicting cookware, wherein classification of one or more image segments into first class of images corresponds to detection of cookware on cooktop. | 8. A system for detecting cookware, the system comprising: a vision sensor positioned so as to collect imagery depicting a cooktop; one or more processors; and one or more non-transitory computer-readable media storing instructions that, when executed by the one or more processors, cause the one or more processors to perform operations, the operations comprising: obtaining a first plurality of images, wherein the first plurality of images depict cookware upon the cooktop; storing the first plurality of images in a memory as a positive image training dataset; obtaining a second plurality of images, wherein the second plurality of images do not depict cookware upon the cooktop; storing the second plurality of images in the memory as a negative image training dataset; training a classifier based on the positive image training dataset and the negative image training dataset; identifying one or more locations respectively associated with one or more burners included in the cooktop, wherein identifying, by one or more computing devices, the one or more locations respectively associated with the one or more burners comprises: obtaining a reference frame of imagery depicting the cooktop without any objects placed thereon; obtaining one or more calibration frames of imagery depicting the cooktop with one or more items of cookware respectively positioned at the one or more locations respectively associated with the one or more burners, wherein the one or more calibration frames of imagery are captured when motion is not detected at the cooktop; performing background subtraction for the one or more calibration frames of imagery with respect to the reference frame of imagery to identify new imagery; and segmenting the new imagery to identify the one or more locations respectively associated with the one or more burners; segmenting a frame of imagery captured by the vision sensor into one or more image segments based at least in part on the one or more locations respectively associated with the one or more burners included in the cooktop; using the classifier to provide an initial classification for each of the one or more image segments, the initial classification for each of the one or more image segments classifying such image segment into either a first class of images depicting cookware or a second class of images not depicting cookware, wherein classification of one or more image segments into first class of images corresponds to detection of cookware on cooktop. 9. The system of claim 8 , wherein the operations further comprise: providing an indication to a user of whether the initial classification for at least one of the one or more image segments comprises the first class or the second class; after providing the indication, receiving a user input indicating whether the initial classification is correct; and when the user input indicates that the initial classification is not correct, changing the initial classification for the frame of imagery to a subsequent classification, wherein the subsequent classification comprises the second class when the initial classification comprises the first class, and wherein the subsequent classification comprises the first class when the initial classification comprises the second class. | 0.76806 |
8,495,143 | 1 | 33 | 1. A computer-implemented method comprising: maintaining a user profile for each of a plurality of users of a social networking system, each user profile comprising a set of attributes; selecting a user from the plurality of users; receiving user profile information for at least one user of a set of users in the social networking system who are connected to the selected user in the social networking system; inferring a value of one or more attributes of the user profile for the selected user based on information describing the set of users who are connected to the selected user in the social networking system; comparing a confidence score value for an inferred user profile attribute to a threshold value; storing, responsive to the confidence score being above the threshold value, the inferred value of the user profile attribute with the user profile for the selected user; determining relevant information for the selected user based on the inferred user profile attribute; and sending the relevant information to the selected user. | 1. A computer-implemented method comprising: maintaining a user profile for each of a plurality of users of a social networking system, each user profile comprising a set of attributes; selecting a user from the plurality of users; receiving user profile information for at least one user of a set of users in the social networking system who are connected to the selected user in the social networking system; inferring a value of one or more attributes of the user profile for the selected user based on information describing the set of users who are connected to the selected user in the social networking system; comparing a confidence score value for an inferred user profile attribute to a threshold value; storing, responsive to the confidence score being above the threshold value, the inferred value of the user profile attribute with the user profile for the selected user; determining relevant information for the selected user based on the inferred user profile attribute; and sending the relevant information to the selected user. 33. The computer-implemented method of claim 1 , wherein the inferred attribute comprises one or more interests of the user, and inferring the value of the interests of the selected user further comprises performing sentiment analysis associated with topics identified in interactions of the selected user with the set of users. | 0.598039 |
7,711,581 | 10 | 11 | 10. The software application according to claim 9 , wherein said template manager additionally comprises a plurality of templates for creating said customized template based data entry screens. | 10. The software application according to claim 9 , wherein said template manager additionally comprises a plurality of templates for creating said customized template based data entry screens. 11. The software application according to claim 10 , wherein said template manager additionally comprises means for editing all aspects of said customized template based data entry screens, said natural language report, and said data points in said data point-based searchable database. | 0.877568 |
9,264,545 | 1 | 7 | 1. A computer-implemented system for automating call center phone calls, comprising: a telephony interface to receive a stream of verbal speech utterances from a callee of a call made from a call center; an agent application to process the verbal speech utterances through a customer support scenario controlled by a live agent of the call center; a post-call processor to identify one or more characteristics of the callee based on the verbal speech utterances; a command processor to automate an outgoing call to a different callee with characteristics similar to the characteristics of the callee of the call made from the call center; a script engine to receive a user selection of one or more scripts, each script comprising a grammar that defines a set of executable instructions for a question-and-response dialog and to affect an execution of the selected script; and a performance module comprising at least one of: a start module to begin the execution of the selected script; an adjustment module to adjust a point of the execution within the selected script; and a repeat module to repeat a portion of the selected script. | 1. A computer-implemented system for automating call center phone calls, comprising: a telephony interface to receive a stream of verbal speech utterances from a callee of a call made from a call center; an agent application to process the verbal speech utterances through a customer support scenario controlled by a live agent of the call center; a post-call processor to identify one or more characteristics of the callee based on the verbal speech utterances; a command processor to automate an outgoing call to a different callee with characteristics similar to the characteristics of the callee of the call made from the call center; a script engine to receive a user selection of one or more scripts, each script comprising a grammar that defines a set of executable instructions for a question-and-response dialog and to affect an execution of the selected script; and a performance module comprising at least one of: a start module to begin the execution of the selected script; an adjustment module to adjust a point of the execution within the selected script; and a repeat module to repeat a portion of the selected script. 7. A system according to claim 1 , further comprising: a record of the call made to the callee; and the command processor to manipulate the record comprising at least one of reordering and ranking of the verbal speech utterances. | 0.733721 |
9,756,039 | 4 | 7 | 4. The system of claim 1 , the database system further configurable to cause: generating a renderable web document comprising the markup language content; communicating the document request to a document-rendering service; and communicating the one or more resources to the document-rendering service. | 4. The system of claim 1 , the database system further configurable to cause: generating a renderable web document comprising the markup language content; communicating the document request to a document-rendering service; and communicating the one or more resources to the document-rendering service. 7. The system of claim 4 , the database system further configurable to cause: in response to receiving, from the document-rendering service, an external resource request for an external resource outside of the database system, whitelisting the external resource request. | 0.859813 |
5,558,520 | 33 | 34 | 33. The assembly of claim 31, further comprising a tracing pad comprised of a stiff backing support and a plurality of pieces of tracing paper bound at one edge to one edge of said backing support, said tracing pad being removably attachable to said front or back cover. | 33. The assembly of claim 31, further comprising a tracing pad comprised of a stiff backing support and a plurality of pieces of tracing paper bound at one edge to one edge of said backing support, said tracing pad being removably attachable to said front or back cover. 34. The assembly of claim 33, wherein said tracing pad comprises a first tracing pad removably attachable to said front cover and a second tracing pad being removably attachable to said back cover. | 0.937061 |
8,285,616 | 1 | 2 | 1. A computer-implemented method for causing a computer associated with a database to provide an enhanced credit evaluation report, said method comprising: collecting from a source, data about an entity of interest, for storage in said database; linking said entity of interest to a related entity in a corporate family tree stored in said database; receiving a request for said enhanced credit evaluation report about said entity of interest; obtaining user-specified rules or criteria for evaluating credit of said entity of interest; dynamically selecting from a database of trade experiences stored in said database, based upon said user-specified rules or criteria, (a) trade experiences for said entity of interest and for said related entity, and (b) trade experiences for a peer group; dynamically assessing performance across said trade experiences for said entity of interest; and generating, using said computer, said enhanced credit evaluation report of said entity of interest based upon a comparative analysis of said trade experiences for said entity of interest and for said related entity and said trade experiences for said peer group. | 1. A computer-implemented method for causing a computer associated with a database to provide an enhanced credit evaluation report, said method comprising: collecting from a source, data about an entity of interest, for storage in said database; linking said entity of interest to a related entity in a corporate family tree stored in said database; receiving a request for said enhanced credit evaluation report about said entity of interest; obtaining user-specified rules or criteria for evaluating credit of said entity of interest; dynamically selecting from a database of trade experiences stored in said database, based upon said user-specified rules or criteria, (a) trade experiences for said entity of interest and for said related entity, and (b) trade experiences for a peer group; dynamically assessing performance across said trade experiences for said entity of interest; and generating, using said computer, said enhanced credit evaluation report of said entity of interest based upon a comparative analysis of said trade experiences for said entity of interest and for said related entity and said trade experiences for said peer group. 2. The method according to claim 1 , further comprising classifying trade experiences in said database. | 0.867268 |
7,987,195 | 4 | 5 | 4. The method of claim 2 , wherein determining a location factor for the first phrase based on the responses to the search results includes: determining how often responses to a search result associated with a known location are received relative to how often responses to a search result not associated with a known location are received. | 4. The method of claim 2 , wherein determining a location factor for the first phrase based on the responses to the search results includes: determining how often responses to a search result associated with a known location are received relative to how often responses to a search result not associated with a known location are received. 5. The method of claim 4 , wherein determining a location factor for the first phrase based on the responses to the search results further includes: determining a number of different known locations associated with the search results for which responses are received; and determining a distribution of the responses as a function of the different known locations. | 0.889262 |
8,135,692 | 1 | 4 | 1. A computer-executable information retrieval apparatus for a web page retrieval using a retrieval keyword comprising: at least one processor; a computer storage medium embedded with computer instructions executed by the at least one processor, the executed computer instructions comprising: a word extract portion that extracts a first word from a web page on a display based on a display position of said web page on said display, wherein the displayed position is specified by a user, said word extract portion further extracts a second word placed around said extracted first word, said extracted second word is different from said extracted first word and is determined by an importance; wherein the importance of said extracted second word is calculated by a word importance calculation portion, the word importance calculation portion calculates the importance of said extracted second word based on an importance of said extracted second word itself and related to said extracted first word, wherein the word importance calculation portion further calculating said importance of said extracted second word related to said extracted first word based on a relationship between a ratio of the number of cooccurrences of said extracted second word with said extracted first word within a range of a certain character number in said web page to the total number of occurrences of said extracted second word in said web page, and a distance from said first word to said second word on said display; a retrieval portion that retrieves at least one web page using said extracted first word and second word. | 1. A computer-executable information retrieval apparatus for a web page retrieval using a retrieval keyword comprising: at least one processor; a computer storage medium embedded with computer instructions executed by the at least one processor, the executed computer instructions comprising: a word extract portion that extracts a first word from a web page on a display based on a display position of said web page on said display, wherein the displayed position is specified by a user, said word extract portion further extracts a second word placed around said extracted first word, said extracted second word is different from said extracted first word and is determined by an importance; wherein the importance of said extracted second word is calculated by a word importance calculation portion, the word importance calculation portion calculates the importance of said extracted second word based on an importance of said extracted second word itself and related to said extracted first word, wherein the word importance calculation portion further calculating said importance of said extracted second word related to said extracted first word based on a relationship between a ratio of the number of cooccurrences of said extracted second word with said extracted first word within a range of a certain character number in said web page to the total number of occurrences of said extracted second word in said web page, and a distance from said first word to said second word on said display; a retrieval portion that retrieves at least one web page using said extracted first word and second word. 4. The computer-executable information retrieval apparatus as recited in claim 1 , wherein a ratio of said importance of said extracted second word itself and said importance of said extracted second word related to said extracted first word in said importance of said extracted second word is arbitrary controlled. | 0.504717 |
7,831,437 | 23 | 27 | 23. The method of claim 1 , wherein each categorization entry in the outline further includes a hierarchical framework of information groupings, each information grouping comprising one or more pointer structures corresponding respectively to one or more stored data items. | 23. The method of claim 1 , wherein each categorization entry in the outline further includes a hierarchical framework of information groupings, each information grouping comprising one or more pointer structures corresponding respectively to one or more stored data items. 27. The method of claim 23 , further comprising: storing the outline in a memory associated with the terminal device. | 0.932604 |
7,761,397 | 3 | 4 | 3. The computer-implemented rule processing system of claim 1 , wherein the processor is configured to separately build an autoselect Include ZDD and an autoselect Exclude ZDD to represent the ZDD. | 3. The computer-implemented rule processing system of claim 1 , wherein the processor is configured to separately build an autoselect Include ZDD and an autoselect Exclude ZDD to represent the ZDD. 4. The computer-implemented rule processing system of claim 3 , wherein the processor is configured to reorder one or more nodes of the autoselect Include ZDD or one or more nodes of the autoselect Exclude ZDD to reduce the complexity thereof. | 0.904406 |
7,702,504 | 7 | 8 | 7. The speech signal decoding apparatus of claim 6 , wherein the calculating unit comprises: a first adder adding the decoded fixed codebook gain value output from the gain value decoding unit to the decoded gain difference output from the gain difference decoding unit; a first selector transmitting the decoded fixed codebook gain value output from the gain value decoding unit or a gain value output from the first adder according to operating conditions of the speech signal decoding apparatus; a second adder adding a decoded fixed codebook of the speech quality enhancement layer output from the second fixed codebook decoding unit to a decoded fixed codebook of the base layer output from the first fixed codebook decoding unit; a second selector switch transmitting a signal output from the second adder or the decoded fixed codebook output from the first fixed codebook decoding unit according to the operating conditions of the speech signal decoding apparatus; a first multiplier multiplying a decoded adaptive codebook output from the adaptive codebook decoding unit by a decoded adaptive codebook gain value output from the gain value decoding unit; a second multiplier multiplying a signal output from the first selector switch by a signal output from the second selector switch; and a third adder adding a signal output from the first multiplier to a signal output from the second multiplier. | 7. The speech signal decoding apparatus of claim 6 , wherein the calculating unit comprises: a first adder adding the decoded fixed codebook gain value output from the gain value decoding unit to the decoded gain difference output from the gain difference decoding unit; a first selector transmitting the decoded fixed codebook gain value output from the gain value decoding unit or a gain value output from the first adder according to operating conditions of the speech signal decoding apparatus; a second adder adding a decoded fixed codebook of the speech quality enhancement layer output from the second fixed codebook decoding unit to a decoded fixed codebook of the base layer output from the first fixed codebook decoding unit; a second selector switch transmitting a signal output from the second adder or the decoded fixed codebook output from the first fixed codebook decoding unit according to the operating conditions of the speech signal decoding apparatus; a first multiplier multiplying a decoded adaptive codebook output from the adaptive codebook decoding unit by a decoded adaptive codebook gain value output from the gain value decoding unit; a second multiplier multiplying a signal output from the first selector switch by a signal output from the second selector switch; and a third adder adding a signal output from the first multiplier to a signal output from the second multiplier. 8. The speech signal decoding apparatus of claim 7 , wherein the speech signal restoring unit comprises: a synthesis filter synthesizing a signal output from the third adder using the linear prediction coding coefficient; and a post-processing unit obtaining the restored speech signal using a signal output from the synthesis filter and the linear prediction coding coefficient. | 0.93893 |
8,094,336 | 12 | 13 | 12. A printer comprising: a memory for storing an application program; a processor coupled to the memory, the processor configured to perform the steps comprising: receiving a command to enable or disable an interpreter task; determining if the interpreter task has been enabled or disabled; receiving a data stream; sending the data stream to the interpreter task if enabled to construct therefrom one or more data packets in a predetermined printer control language to be sent to one or more tasks for printing; sending the data stream directly to a PCL task if the interpreter is disabled; and executing the PCL task, bypassing the interpreter. | 12. A printer comprising: a memory for storing an application program; a processor coupled to the memory, the processor configured to perform the steps comprising: receiving a command to enable or disable an interpreter task; determining if the interpreter task has been enabled or disabled; receiving a data stream; sending the data stream to the interpreter task if enabled to construct therefrom one or more data packets in a predetermined printer control language to be sent to one or more tasks for printing; sending the data stream directly to a PCL task if the interpreter is disabled; and executing the PCL task, bypassing the interpreter. 13. The printer as recited in claim 12 , wherein the interpreter manipulates received data in accordance with the application program. | 0.838554 |
9,495,360 | 1 | 2 | 1. A computer program product, the computer program product comprising: a non-transitory computer-readable storage medium having computer-readable program code embodied therewith, the computer-readable program code having instructions for causing a processor to perform an operation, the operation comprising: receiving a recipe request, wherein the recipe request specifies a dish and a set of criteria; retrieving a plurality of recipe texts corresponding to the specified dish; parsing each of the recipe texts to identify one or more ingredients and one or more methods used in preparing the specified dish and to associate metadata to one or more of the identified ingredients and methods; generating, from the associated metadata of the identified ingredients and methods, a statistical model for preparing the specified dish, wherein the statistical model distinguishes between common and uncommon ingredients and methods for preparing the specified dish using a frequency of appearances in the parsed recipe texts; identifying substitutions satisfying the specified set of criteria based on the common and uncommon ingredients and methods; and generating a combination of the identified ingredients and methods for preparing the specified dish based on the specified set of criteria and the statistical model, wherein the combination includes at least one of the identified substitutions. | 1. A computer program product, the computer program product comprising: a non-transitory computer-readable storage medium having computer-readable program code embodied therewith, the computer-readable program code having instructions for causing a processor to perform an operation, the operation comprising: receiving a recipe request, wherein the recipe request specifies a dish and a set of criteria; retrieving a plurality of recipe texts corresponding to the specified dish; parsing each of the recipe texts to identify one or more ingredients and one or more methods used in preparing the specified dish and to associate metadata to one or more of the identified ingredients and methods; generating, from the associated metadata of the identified ingredients and methods, a statistical model for preparing the specified dish, wherein the statistical model distinguishes between common and uncommon ingredients and methods for preparing the specified dish using a frequency of appearances in the parsed recipe texts; identifying substitutions satisfying the specified set of criteria based on the common and uncommon ingredients and methods; and generating a combination of the identified ingredients and methods for preparing the specified dish based on the specified set of criteria and the statistical model, wherein the combination includes at least one of the identified substitutions. 2. The computer program product of claim 1 , wherein the plurality of recipe texts are retrieved from online recipe websites and local databases. | 0.826555 |
6,120,553 | 1 | 2 | 1. A system for modifying job control language (JCL) statements to optimize data storage allocations for datasets comprising: data collection means for collecting historical data concerning actual data storage space requirements of each dataset; parsing means for parsing JCL statements for references to datasets and requested data storage space allocations; and means for generating revised JCL statements containing revised requests for data storage space allocations for said datasets based on said historical data. | 1. A system for modifying job control language (JCL) statements to optimize data storage allocations for datasets comprising: data collection means for collecting historical data concerning actual data storage space requirements of each dataset; parsing means for parsing JCL statements for references to datasets and requested data storage space allocations; and means for generating revised JCL statements containing revised requests for data storage space allocations for said datasets based on said historical data. 2. The system of claim 1 further comprising means for displaying revisions to said JCL statement and allowing a user to accept or reject said revisions. | 0.822844 |
9,697,260 | 1 | 6 | 1. A method comprising, by one or more computing devices: receiving, from a client device of a first user of an online social network, a search query comprising location parameters; identifying one or more locations matching the search query, each location corresponding to a location node within a social graph of the online social network; determining a value for each identified location, wherein the value is based on: a number of edges connected to the location node corresponding to the identified location, each edge having a particular attribute corresponding to a particular action a particular user performed on the online social network with respect to the location node; and the attributes of the edges connected to the location node corresponding to the identified location, wherein a different weight is assigned to each particular attribute based on the particular action performed by the particular user; and sending, to the client device of the first user for display, a search-results page responsive to the search query, the search-results page comprising references to one or more identified locations, each identified location having a determined value greater than a threshold value. | 1. A method comprising, by one or more computing devices: receiving, from a client device of a first user of an online social network, a search query comprising location parameters; identifying one or more locations matching the search query, each location corresponding to a location node within a social graph of the online social network; determining a value for each identified location, wherein the value is based on: a number of edges connected to the location node corresponding to the identified location, each edge having a particular attribute corresponding to a particular action a particular user performed on the online social network with respect to the location node; and the attributes of the edges connected to the location node corresponding to the identified location, wherein a different weight is assigned to each particular attribute based on the particular action performed by the particular user; and sending, to the client device of the first user for display, a search-results page responsive to the search query, the search-results page comprising references to one or more identified locations, each identified location having a determined value greater than a threshold value. 6. The method of claim 1 , wherein the particular attribute is selected from a group comprising a friendship, a business relationship, a fan relationship, a follower relationship, a visitor relationship, a subscriber relationship, a superior/subordinate relationship, a reciprocal relationship, and a non-reciprocal relationship. | 0.70625 |
9,208,435 | 15 | 24 | 15. A system for dynamically generating taxonomies, the system comprising: a processor; a memory coupled to the processor storing components that are executed by the processor; a communication component stored in the memory and configured to receive a topic from a user input in a user interface on a host computer system; a generation component stored in the memory and configured to dynamically generate a plurality of terms associated with the received topic; wherein the generation component is further configured to: communicate a query to a semantic network based on the received topic, and receive the plurality of terms from the semantic network in response to the query; evaluate each of the plurality of terms against the corpus, the evaluating comprising determining that an informativeness measure for the term is within acceptable limits; and wherein the communication component is further configured to communicate to the host computer system only the plurality of terms that are determined to have the informativeness measure within the acceptable limits as a selectable refinement displayed in the user interface in response to receiving the topic from the user in the user interface, the selectable refinement associated with at least one action of a plurality of available associated actions; wherein the displayed selectable refinement comprises displaying automatically to the user, before a further interaction by the user with the user interface after receiving the topic, initial search results from the topic in the user interface, the initial search results comprising links to one or more items of the corpus, and displaying a number of items of the initial search results that correspond to each of the plurality of terms; wherein the generate comprises receiving a plurality of meanings for the topic, and the displaying comprises displaying automatically to the user, before the further interaction by the user with the user interface after receiving the topic, for each of the meanings a set of one or more of the plurality of terms that relate to the meaning; wherein one of the selectable refinements, when selected by the user and associated with an action comprising a text search, generates additional search results that are a subset of the initial search results and that correspond to the term of the selected refinement. | 15. A system for dynamically generating taxonomies, the system comprising: a processor; a memory coupled to the processor storing components that are executed by the processor; a communication component stored in the memory and configured to receive a topic from a user input in a user interface on a host computer system; a generation component stored in the memory and configured to dynamically generate a plurality of terms associated with the received topic; wherein the generation component is further configured to: communicate a query to a semantic network based on the received topic, and receive the plurality of terms from the semantic network in response to the query; evaluate each of the plurality of terms against the corpus, the evaluating comprising determining that an informativeness measure for the term is within acceptable limits; and wherein the communication component is further configured to communicate to the host computer system only the plurality of terms that are determined to have the informativeness measure within the acceptable limits as a selectable refinement displayed in the user interface in response to receiving the topic from the user in the user interface, the selectable refinement associated with at least one action of a plurality of available associated actions; wherein the displayed selectable refinement comprises displaying automatically to the user, before a further interaction by the user with the user interface after receiving the topic, initial search results from the topic in the user interface, the initial search results comprising links to one or more items of the corpus, and displaying a number of items of the initial search results that correspond to each of the plurality of terms; wherein the generate comprises receiving a plurality of meanings for the topic, and the displaying comprises displaying automatically to the user, before the further interaction by the user with the user interface after receiving the topic, for each of the meanings a set of one or more of the plurality of terms that relate to the meaning; wherein one of the selectable refinements, when selected by the user and associated with an action comprising a text search, generates additional search results that are a subset of the initial search results and that correspond to the term of the selected refinement. 24. The system according to claim 15 , wherein the generation component is further configured to receive the plurality of terms including the plurality of terms from the semantic network, and the system further comprises an evaluation component configured to filter, automatically, at least one of the plurality of terms. | 0.518018 |
8,380,870 | 9 | 10 | 9. The method of claim 8 wherein the range of source IP addresses are represented in CIDR notation. | 9. The method of claim 8 wherein the range of source IP addresses are represented in CIDR notation. 10. The method of claim 9 wherein determining that a first field in a portion of the received DNS queries matches the filter criteria comprises matching a source IP address in the portion of the received DNS queries to an IP address in the filter rule. | 0.89385 |
7,849,186 | 22 | 47 | 22. The method according to claim 15 , wherein said evaluating comprises implementing a similarity criterion for determining whether the real-time conversational media session and the reference data item are similar based upon at least data in respect of packet arrival times associated with the real-time conversational media session and a reference data item. | 22. The method according to claim 15 , wherein said evaluating comprises implementing a similarity criterion for determining whether the real-time conversational media session and the reference data item are similar based upon at least data in respect of packet arrival times associated with the real-time conversational media session and a reference data item. 47. The method according to claim 22 , further comprising identifying an originator of the real-time conversational media session, and wherein said evaluating further comprises adjusting the similarity criterion if it is determined that the real-time conversational media session is associated with a certain originator or with a certain group of originators. | 0.890881 |
7,801,881 | 1 | 9 | 1. A method of listing documents performed by a website server system having one or more processors and memory storing one or more programs for execution by the one or more processors, comprising: accessing one or more sources of document information, wherein the one or more sources of document information are associated with a website server; extracting the document information including metadata from the sources; generating a sitemap of a website at the website server, the sitemap including a list of documents and corresponding metadata for each of a plurality of documents in the list of documents based on the document information, wherein the metadata comprises at least one of the group consisting of: document modification date information associated with the plurality of documents, document access frequency information associated with the plurality of documents, document priority information associated with the plurality of documents, and document update rate information associated with the plurality of documents, wherein the document priority information indicates a crawling priority; and storing the sitemap at a location; and transmitting a notification from the website server to a remote computer associated with a web crawler system, the notification including information that identifies the location of the sitemap, the notification functioning as an indication that the sitemap is available for access. | 1. A method of listing documents performed by a website server system having one or more processors and memory storing one or more programs for execution by the one or more processors, comprising: accessing one or more sources of document information, wherein the one or more sources of document information are associated with a website server; extracting the document information including metadata from the sources; generating a sitemap of a website at the website server, the sitemap including a list of documents and corresponding metadata for each of a plurality of documents in the list of documents based on the document information, wherein the metadata comprises at least one of the group consisting of: document modification date information associated with the plurality of documents, document access frequency information associated with the plurality of documents, document priority information associated with the plurality of documents, and document update rate information associated with the plurality of documents, wherein the document priority information indicates a crawling priority; and storing the sitemap at a location; and transmitting a notification from the website server to a remote computer associated with a web crawler system, the notification including information that identifies the location of the sitemap, the notification functioning as an indication that the sitemap is available for access. 9. The method of claim 1 , wherein the sitemap comprises a current sitemap, the method further comprising: determining a difference between the current sitemap and a prior sitemap; and generating a differential sitemap based on the difference. | 0.62844 |
10,134,386 | 10 | 13 | 10. A system for identifying content corresponding to a language, the system comprising: storage circuitry configured to store a first association between a first phoneme sequence and a first language and a second association between a second phoneme sequence and a second language; control circuitry configured to: generate a phoneme sequence based on verbal input received from a first user; determine which one of the first and second phoneme sequences, associated respectively with the first and second languages, corresponds to the generated phoneme sequence; automatically determine, with voice recognition circuitry, that a language spoken by the first user corresponds to the first language based on determining that the first phoneme sequence corresponds to the generated phoneme sequence; measure a first duration of the received first verbal input representing how often the first language is spoken in the household; store the first duration in a database that associates the first duration with the first language; measure a second duration of second verbal input received subsequent to the first verbal input representing how often the second language is spoken in the household, wherein the second verbal input corresponds to the second language; store a second duration in the database that associates the second duration with the second language; compare the first duration to the second duration; in response to determining that the first duration is greater than the second duration, determining that the first language is spoken more often than the second language in the household; search a database of content sources to identify a content source associated with a language field value that corresponds to the first language based on determining that the first language is spoken more often than the second language in the household, wherein the language field in the database identifies the language that the associated content source transmits content to a plurality of users; and generate for display a representation of the identified content source to the first user. | 10. A system for identifying content corresponding to a language, the system comprising: storage circuitry configured to store a first association between a first phoneme sequence and a first language and a second association between a second phoneme sequence and a second language; control circuitry configured to: generate a phoneme sequence based on verbal input received from a first user; determine which one of the first and second phoneme sequences, associated respectively with the first and second languages, corresponds to the generated phoneme sequence; automatically determine, with voice recognition circuitry, that a language spoken by the first user corresponds to the first language based on determining that the first phoneme sequence corresponds to the generated phoneme sequence; measure a first duration of the received first verbal input representing how often the first language is spoken in the household; store the first duration in a database that associates the first duration with the first language; measure a second duration of second verbal input received subsequent to the first verbal input representing how often the second language is spoken in the household, wherein the second verbal input corresponds to the second language; store a second duration in the database that associates the second duration with the second language; compare the first duration to the second duration; in response to determining that the first duration is greater than the second duration, determining that the first language is spoken more often than the second language in the household; search a database of content sources to identify a content source associated with a language field value that corresponds to the first language based on determining that the first language is spoken more often than the second language in the household, wherein the language field in the database identifies the language that the associated content source transmits content to a plurality of users; and generate for display a representation of the identified content source to the first user. 13. The system of claim 10 , wherein the language spoken by the first user is a first language, wherein the control circuitry is further configured to automatically determine, with the voice recognition circuitry, a second language spoken by a second user based on verbal input received from the second user, wherein the second user is in a same household as the first user. | 0.736248 |
7,516,198 | 2 | 3 | 2. The network node of claim 1 , wherein the XML tags within the at least one message are based on a group of predetermined XML tags specifying respective prescribed quality of service attributes identifiable by the application resource, the application resource configured for selecting, for each corresponding predetermined XML tag, a corresponding prescribed network parameter for implementation of the corresponding prescribed quality of service attribute. | 2. The network node of claim 1 , wherein the XML tags within the at least one message are based on a group of predetermined XML tags specifying respective prescribed quality of service attributes identifiable by the application resource, the application resource configured for selecting, for each corresponding predetermined XML tag, a corresponding prescribed network parameter for implementation of the corresponding prescribed quality of service attribute. 3. The network node of claim 2 , wherein the application resource is configured for identifying the flow of data packets for transfer according to the selected network parameters based on flow information specified within the at least one message for the corresponding application service. | 0.897808 |
8,682,646 | 8 | 9 | 8. A system comprising at least one computing device and at least one module that are together configured for performing actions comprising: extracting, based on grammatical rules, location keywords from a location description; and checking for a semantic relationship among the extracted location keywords to derive a valid semantic meaning of the location description, the checking configured for further deriving: a) a spatial part-of relationship between two locations represented by the location keywords extracted from the location description, where a first of the two locations as indicated by a first of the extracted location keywords is a part of a second of the two locations as indicated by a second of the extracted location keywords, b) a spatial near-by relationship between the two locations represented by the location keywords extracted from the location description, where the first of the two locations as indicated by the first of the extracted location keywords is located proximate to the second of the two locations as indicated by the second of the extracted location keywords, and c) a spatial intersects relationship between the two locations represented by the location keywords extracted from the location description, where the first of the two locations as indicated by the first of the extracted location keywords intersects the second of the two locations as indicated by the second of the extracted location keywords. | 8. A system comprising at least one computing device and at least one module that are together configured for performing actions comprising: extracting, based on grammatical rules, location keywords from a location description; and checking for a semantic relationship among the extracted location keywords to derive a valid semantic meaning of the location description, the checking configured for further deriving: a) a spatial part-of relationship between two locations represented by the location keywords extracted from the location description, where a first of the two locations as indicated by a first of the extracted location keywords is a part of a second of the two locations as indicated by a second of the extracted location keywords, b) a spatial near-by relationship between the two locations represented by the location keywords extracted from the location description, where the first of the two locations as indicated by the first of the extracted location keywords is located proximate to the second of the two locations as indicated by the second of the extracted location keywords, and c) a spatial intersects relationship between the two locations represented by the location keywords extracted from the location description, where the first of the two locations as indicated by the first of the extracted location keywords intersects the second of the two locations as indicated by the second of the extracted location keywords. 9. The system of claim 8 where the checking comprises verifying the semantic relationship against semantic relationship attributes associated with each of the location keywords in the location description. | 0.598039 |
8,667,412 | 16 | 17 | 16. The device of claim 10 , wherein the key mapping includes a plurality of characters associated with an alphabet corresponding to the language identifier. | 16. The device of claim 10 , wherein the key mapping includes a plurality of characters associated with an alphabet corresponding to the language identifier. 17. The device of claim 16 , further operable to cause data processing apparatus to perform operations comprising: receiving user input selecting a control included in the virtual input device; and entering a character associated with the selected control in the selected data entry field. | 0.916715 |
9,727,844 | 7 | 12 | 7. An apparatus comprising: a documentation presentation module configured to visually present a list of documents within a documentation package adjacent to content of at least one document selected by a user from the list of documents in an online framework, the online framework facilitating navigation of the list of documents of the documentation package, the online documentation framework generated using an integrated development environment; a documentation review module configured to receive and store comments associated with the selected at least one document in the documentation package, the documentation review application comprising a separate executable application from the online documentation framework, wherein the documentation review application is not natively included with the online documentation framework; and an integration module configured to: integrate the documentation review module into the documentation presentation module such that comments associated with the selected at least one document of the documentation package may be one or more of submitted and viewed from within the online documentation framework, the comments being accessible using a link presented within the online documentation framework for the selected at least one document, the link directing a user to comments maintained for the selected at least one document by the documentation review application; present one or more comments associated with the selected at least one document within the online documentation framework in response to verifying the user is separately logged into both the online documentation framework and the documentation review application, the presented one or more comments being updated in real-time in response to one or more users creating new comments for the selected at least one document using the documentation review application; toggle presentation of the one or more comments in response to the user selecting the link such that the user can switch between displaying an unmarked-up version of the at least document and a marked-up version of the at least one document with comments presented interspersed throughout the document; and search for a document in the documentation package in response to user input, wherein the searching is synchronized with the visually presented list of documents adjacent to the content of the selected document such that documents in the visually presented list that match results of the search are visually highlighted in the list of documents, wherein at least a portion of the documentation presentation module, the documentation review module, and the integration module comprises one or more of hardware and code executable by a processor, the executable code stored on one or more non-transitory computer readable storage media. | 7. An apparatus comprising: a documentation presentation module configured to visually present a list of documents within a documentation package adjacent to content of at least one document selected by a user from the list of documents in an online framework, the online framework facilitating navigation of the list of documents of the documentation package, the online documentation framework generated using an integrated development environment; a documentation review module configured to receive and store comments associated with the selected at least one document in the documentation package, the documentation review application comprising a separate executable application from the online documentation framework, wherein the documentation review application is not natively included with the online documentation framework; and an integration module configured to: integrate the documentation review module into the documentation presentation module such that comments associated with the selected at least one document of the documentation package may be one or more of submitted and viewed from within the online documentation framework, the comments being accessible using a link presented within the online documentation framework for the selected at least one document, the link directing a user to comments maintained for the selected at least one document by the documentation review application; present one or more comments associated with the selected at least one document within the online documentation framework in response to verifying the user is separately logged into both the online documentation framework and the documentation review application, the presented one or more comments being updated in real-time in response to one or more users creating new comments for the selected at least one document using the documentation review application; toggle presentation of the one or more comments in response to the user selecting the link such that the user can switch between displaying an unmarked-up version of the at least document and a marked-up version of the at least one document with comments presented interspersed throughout the document; and search for a document in the documentation package in response to user input, wherein the searching is synchronized with the visually presented list of documents adjacent to the content of the selected document such that documents in the visually presented list that match results of the search are visually highlighted in the list of documents, wherein at least a portion of the documentation presentation module, the documentation review module, and the integration module comprises one or more of hardware and code executable by a processor, the executable code stored on one or more non-transitory computer readable storage media. 12. The apparatus of claim 7 , wherein the integration module receives real-time information from the documentation review module and updates the comments related to a document in real-time. | 0.710366 |
8,365,066 | 17 | 18 | 17. A non-transitory computer-readable memory that stores instructions that when executed by a processor perform a method for storing formatting information for at least one cell in a spreadsheet document described in a markup language, wherein the spreadsheet document includes a plurality of style objects, the method comprising: parsing the spreadsheet document to generate at least one display list of a cell format object for the at least one cell by: obtaining cell formatting information for the at least one cell from a master style object that stores master formatting information for the at least one cell; obtaining named style information for the at least one cell from a style name object that stores named styles for the at least one cell and references the cell master style object; obtaining cell specific formatting information for the at least one cell from a cell-specific style object that includes cell specific formatting information for the at least one cell and references the master style object, wherein the cell specific formatting information overrides master formatting information; generating combined cell formatting information for the at least one cell in the cell format object, wherein the combined cell formatting information in the cell format object comprises named styles for the at least one cell, cell-specific formatting information that has overridden formatting information in the master style object, and master formatting information that has not been overridden by the cell-specific formatting information, wherein the formatting information originally described in the master style object but overridden by the cell-specific information is not included in the combined cell formatting information for the cell format object; and storing the combined cell formatting information as the at least one display list of the cell format object; and rasterizing the at least one cell in a frame buffer using the stored at least one display list of the cell format object. | 17. A non-transitory computer-readable memory that stores instructions that when executed by a processor perform a method for storing formatting information for at least one cell in a spreadsheet document described in a markup language, wherein the spreadsheet document includes a plurality of style objects, the method comprising: parsing the spreadsheet document to generate at least one display list of a cell format object for the at least one cell by: obtaining cell formatting information for the at least one cell from a master style object that stores master formatting information for the at least one cell; obtaining named style information for the at least one cell from a style name object that stores named styles for the at least one cell and references the cell master style object; obtaining cell specific formatting information for the at least one cell from a cell-specific style object that includes cell specific formatting information for the at least one cell and references the master style object, wherein the cell specific formatting information overrides master formatting information; generating combined cell formatting information for the at least one cell in the cell format object, wherein the combined cell formatting information in the cell format object comprises named styles for the at least one cell, cell-specific formatting information that has overridden formatting information in the master style object, and master formatting information that has not been overridden by the cell-specific formatting information, wherein the formatting information originally described in the master style object but overridden by the cell-specific information is not included in the combined cell formatting information for the cell format object; and storing the combined cell formatting information as the at least one display list of the cell format object; and rasterizing the at least one cell in a frame buffer using the stored at least one display list of the cell format object. 18. The computer-readable memory of claim 17 , wherein the spreadsheet document is described in OOXML. | 0.827703 |
6,012,052 | 1 | 10 | 1. A method for generating a resource transition probability model based on resources referenced, the method comprising steps of: a) generating a usage log including information regarding (i) an identification of clients which requested the resources referenced, (ii) an identification of the resources referenced, and (iii) an identification of times when the resources were referenced, b) defining sessions based on the information regarding the identification of clients and the identification of the times; and c) determining resource transition probabilities based on the identification of clients, the identification of resources referenced, and the defined sessions, wherein the resource transition probability model is defined by the determined resource transition probabilities. | 1. A method for generating a resource transition probability model based on resources referenced, the method comprising steps of: a) generating a usage log including information regarding (i) an identification of clients which requested the resources referenced, (ii) an identification of the resources referenced, and (iii) an identification of times when the resources were referenced, b) defining sessions based on the information regarding the identification of clients and the identification of the times; and c) determining resource transition probabilities based on the identification of clients, the identification of resources referenced, and the defined sessions, wherein the resource transition probability model is defined by the determined resource transition probabilities. 10. The method of claim 1 wherein the step of determining resource transition probabilities based on the identification of users, the identification of resources, and the defined sessions includes sub-steps of: i) counting a number of different sessions in which a first resource was referenced to generate a first count; ii) counting a number of different sessions in which a second resource was referenced after the first resource was referenced, to generate a second count; and iii) determining a transition probability from the first resource to the second resource based on the first and second counts. | 0.527994 |
7,853,863 | 17 | 18 | 17. The method as described in claim 16 , wherein said identifying of said first portion of said input audio message further comprises identifying a portion of said input audio message which is at an audibly higher pitch than another portion of said spoken message. | 17. The method as described in claim 16 , wherein said identifying of said first portion of said input audio message further comprises identifying a portion of said input audio message which is at an audibly higher pitch than another portion of said spoken message. 18. The method as described in claim 17 , wherein said identifying of said first portion of said input audio message further comprises identifying a portion of said input audio message which is at an audibly lower pitch than another portion of said spoken message. | 0.827451 |
7,788,582 | 5 | 7 | 5. A computer readable medium including at least computer program code stored thereon for searching through a group of media items, said computer readable medium comprising: computer program code for presenting a search box capable of receiving a user input; computer program code for determining whether a user input is present in the search box; and computer program code for automatically displaying a search assistant when it is determined that a user input is present in the search box, wherein the search assistant facilitates selection of search criteria for use when searching for the text string within the group of media items, and wherein the searching is confined to the search criteria selected using the search assistant, wherein the search assistant includes a category section having a plurality of predetermined categories, and a fields section having a plurality of predetermined fields, and wherein the plurality of predetermined categories and the plurality of predetermined fields are simultaneously displayed in a horizontal row prior to performing a search in accordance with the text string, wherein the predetermined categories horizontally depicted in the search assistant pertain to at least a music category and a video category, when the music category is selected, the one or more fields being horizontally depicted include at least one of artist, album, composer and song, and when the video category is selected, the one or more fields being horizontally depicted include at least one of artist, album and title. | 5. A computer readable medium including at least computer program code stored thereon for searching through a group of media items, said computer readable medium comprising: computer program code for presenting a search box capable of receiving a user input; computer program code for determining whether a user input is present in the search box; and computer program code for automatically displaying a search assistant when it is determined that a user input is present in the search box, wherein the search assistant facilitates selection of search criteria for use when searching for the text string within the group of media items, and wherein the searching is confined to the search criteria selected using the search assistant, wherein the search assistant includes a category section having a plurality of predetermined categories, and a fields section having a plurality of predetermined fields, and wherein the plurality of predetermined categories and the plurality of predetermined fields are simultaneously displayed in a horizontal row prior to performing a search in accordance with the text string, wherein the predetermined categories horizontally depicted in the search assistant pertain to at least a music category and a video category, when the music category is selected, the one or more fields being horizontally depicted include at least one of artist, album, composer and song, and when the video category is selected, the one or more fields being horizontally depicted include at least one of artist, album and title. 7. A computer readable medium as recited in claim 5 , wherein the fields presented in the search assistant are dynamically determined and are different depending on a selection of one of the categories. | 0.679365 |
9,679,251 | 16 | 19 | 16. At least one server, comprising: at least one non-transitory computer readable storage medium configured to store: a mapping of values to sets of evidences U in a knowledge base, and objects in the form E→A, where A is a rule among rules in the knowledge base, and E is a subset of the sets of evidences U from the knowledge base that supports the rule A, so that the rule A is supportable by the subset of evidences E; and at least one hardware processor coupled to the at least one memory to execute instructions stored in the at least one memory, which instructions when executed by the at least one hardware processor, cause the at least one server: determine relationship constraints κ in form of set relations among a plurality of subsets of evidences E; and in response to at least one request, compute for a target rule L, a first composite object with respect to validity (v) ω 1 v =G 1 →L 0 and/or with respect to plausibility (p), ω 1 p =G 1 →L 0 , the first composite object ω 1 v or ω 1 p constructed from a combination of the objects E→A to create a composite sets of evidences G 1 v or G 1 p subject to the relationship constraints κ which support a composite rule L 0 v or L 0 p , the composite rule L 0 v or L 0 p being a combination of the rules implying the target rule L according to deductive reasoning indicated by the mapping of the values to the sets of evidences U, the first composite object ω 1 v or ω 1 p indicative according to the deductive reasoning of a first validity value or a first plausibility value for the target rule L. | 16. At least one server, comprising: at least one non-transitory computer readable storage medium configured to store: a mapping of values to sets of evidences U in a knowledge base, and objects in the form E→A, where A is a rule among rules in the knowledge base, and E is a subset of the sets of evidences U from the knowledge base that supports the rule A, so that the rule A is supportable by the subset of evidences E; and at least one hardware processor coupled to the at least one memory to execute instructions stored in the at least one memory, which instructions when executed by the at least one hardware processor, cause the at least one server: determine relationship constraints κ in form of set relations among a plurality of subsets of evidences E; and in response to at least one request, compute for a target rule L, a first composite object with respect to validity (v) ω 1 v =G 1 →L 0 and/or with respect to plausibility (p), ω 1 p =G 1 →L 0 , the first composite object ω 1 v or ω 1 p constructed from a combination of the objects E→A to create a composite sets of evidences G 1 v or G 1 p subject to the relationship constraints κ which support a composite rule L 0 v or L 0 p , the composite rule L 0 v or L 0 p being a combination of the rules implying the target rule L according to deductive reasoning indicated by the mapping of the values to the sets of evidences U, the first composite object ω 1 v or ω 1 p indicative according to the deductive reasoning of a first validity value or a first plausibility value for the target rule L. 19. The at least one server according to claim 16 , wherein the relationship constraints κ include one or any combination of a subset type relation or a disjoint type relation among the plurality of subsets of evidences E. | 0.89064 |
9,129,029 | 1 | 3 | 1. A method comprising: identifying a region defining an area of interest in response to receiving a viewport from a client device corresponding to the region including identifying a plurality of content items that are associated with the region; evaluating query logs associated with users that submitted queries associated with the region to determine a ranking associated with the plurality of content items, wherein each content item is ranked based on a number of queries in the query logs for which each content item is responsive and a time of occurrence of the number of queries, wherein each content item is ranked higher if the number of queries occurred more recently on average than other queries in the query logs and ranked lower if the number of queries occurred less recently on average than other queries in the query logs; receiving a geographic search query associated with the region; and providing one or more of the content items in response to the geographic search query to be displayed on the viewport of the client device, based at least in part on the ranking associated with each of the one or more contents items, wherein each of the one or more displayed content items are ranked above a predetermined threshold ranking, and wherein the predetermined threshold ranking is based on the viewport. | 1. A method comprising: identifying a region defining an area of interest in response to receiving a viewport from a client device corresponding to the region including identifying a plurality of content items that are associated with the region; evaluating query logs associated with users that submitted queries associated with the region to determine a ranking associated with the plurality of content items, wherein each content item is ranked based on a number of queries in the query logs for which each content item is responsive and a time of occurrence of the number of queries, wherein each content item is ranked higher if the number of queries occurred more recently on average than other queries in the query logs and ranked lower if the number of queries occurred less recently on average than other queries in the query logs; receiving a geographic search query associated with the region; and providing one or more of the content items in response to the geographic search query to be displayed on the viewport of the client device, based at least in part on the ranking associated with each of the one or more contents items, wherein each of the one or more displayed content items are ranked above a predetermined threshold ranking, and wherein the predetermined threshold ranking is based on the viewport. 3. The method of claim 1 where evaluating query log includes evaluating query log data, where each entry in a query log includes query terms submitted, a region as defined by a bounding region that was displayed in a viewport to the user prior to receipt of the query, and where evaluating query log data includes evaluating one or more business listings associated with the bounding region shown in the viewport. | 0.870695 |
9,767,093 | 16 | 19 | 16. The apparatus as recited in claim 12 , wherein generating the one or more annotated alternative versions of the input annotated phrase, the processor and the memory, with the computer code instructions, are further configured to cause the apparatus to apply one or more transformation rules to nodes of the syntactic tree. | 16. The apparatus as recited in claim 12 , wherein generating the one or more annotated alternative versions of the input annotated phrase, the processor and the memory, with the computer code instructions, are further configured to cause the apparatus to apply one or more transformation rules to nodes of the syntactic tree. 19. The apparatus as recited in claim 16 , wherein applying one or more transformation rules to nodes of the syntactic tree, the processor and the memory, with the computer code instructions, are further configured to cause the apparatus to insert an expression within a version of the one or more versions generated. | 0.817606 |
8,010,547 | 4 | 5 | 4. The method of claim 2 , wherein the must-split sub-dictionary contains split candidates with a confidence score above a predetermined high threshold, the must-join sub-dictionary contains join candidates with a confidence score above a second predetermined high threshold, and the normal sub-dictionary contains all other split, join, hyphen, and apostrophe candidates. | 4. The method of claim 2 , wherein the must-split sub-dictionary contains split candidates with a confidence score above a predetermined high threshold, the must-join sub-dictionary contains join candidates with a confidence score above a second predetermined high threshold, and the normal sub-dictionary contains all other split, join, hyphen, and apostrophe candidates. 5. The method of claim 4 , further comprising: comparing the generated candidates of the query with the candidates in the three sub-dictionaries; automatically submitting to the search engine the generated candidates that are found in either the must-split or the must-join sub-dictionaries; and applying the language model to the generated candidates that are found in the normal sub-dictionary. | 0.865854 |
8,082,215 | 13 | 17 | 13. The system of claim 1 , further comprising: a source identity acquisition module configured to acquire source identity data including a first source identity data and a second source identity data, the first source identity data providing one or more identities of one or more sources that provide a basis for the first inference data and the second source identity data providing one or more identities of one or more sources that provide a basis for the second inference data. | 13. The system of claim 1 , further comprising: a source identity acquisition module configured to acquire source identity data including a first source identity data and a second source identity data, the first source identity data providing one or more identities of one or more sources that provide a basis for the first inference data and the second source identity data providing one or more identities of one or more sources that provide a basis for the second inference data. 17. The system of claim 13 , wherein said source identity acquisition module configured to acquire source identity data including a first source identity data and a second source identity data, the first source identity data providing one or more identities of one or more sources that provide a basis for the first inference data and the second source identity data providing one or more identities of one or more sources that provide a basis for the second inference data comprises: a sensor identification (ID) acquisition module configured to acquire one or more identities of one or more sensors used to sense physical characteristics of the first authoring user and the second authoring user, the first inference data and the second inference data being based, at least in part, on the sensed physical characteristics of the first authoring user and the second authoring user, respectively. | 0.629139 |
9,715,491 | 10 | 19 | 10. A non-transitory processor-readable medium storing code representing instructions to be executed by a processor, the code comprising code to cause the processor to: receive a signal associated with a portion of text from a document; associate a document type with the document based at least in part on the signal; select, based on the document type, a document template having a plurality of sections, at least one section from the plurality of sections being associated with at least one policy preference used to analyze a meaning of the portion of text by interpreting a concept represented by text within the portion of text; prepare the portion of text for comparison with the document template by aligning the at least one section with the portion of text; analyze the meaning of the portion of text with respect to a condition associated with the document type based on the at least one policy preference, the at least one policy preference including an indication of the condition and an indication of a recommendation associated with the condition; and send the indication of the recommendation to an entity in response to the meaning satisfying the condition. | 10. A non-transitory processor-readable medium storing code representing instructions to be executed by a processor, the code comprising code to cause the processor to: receive a signal associated with a portion of text from a document; associate a document type with the document based at least in part on the signal; select, based on the document type, a document template having a plurality of sections, at least one section from the plurality of sections being associated with at least one policy preference used to analyze a meaning of the portion of text by interpreting a concept represented by text within the portion of text; prepare the portion of text for comparison with the document template by aligning the at least one section with the portion of text; analyze the meaning of the portion of text with respect to a condition associated with the document type based on the at least one policy preference, the at least one policy preference including an indication of the condition and an indication of a recommendation associated with the condition; and send the indication of the recommendation to an entity in response to the meaning satisfying the condition. 19. The non-transitory processor-readable medium of claim 10 , wherein the recommendation includes a suggestion to modify the portion of text. | 0.862669 |
9,620,128 | 33 | 34 | 33. A computationally-implemented method, comprising: storing a reference to a location of adaptation data, wherein the adaptation data is at least partly based on at least one speech interaction of a particular party; testing an availability of the adaptation data by comparing a property of the adaptation data located at the referenced location with an expected value of the property of the adaptation data; facilitating transmission of the adaptation data to a target device when there is an indication of a speech-facilitated transaction between the target device and the particular party, wherein the adaptation data is configured to be applied to the target device to assist in execution of the speech-facilitated transaction; and facilitating acquisition of adaptation result data that is based on at least one aspect of the speech-facilitated transaction and configured to be used in determining whether to modify the adaptation data. | 33. A computationally-implemented method, comprising: storing a reference to a location of adaptation data, wherein the adaptation data is at least partly based on at least one speech interaction of a particular party; testing an availability of the adaptation data by comparing a property of the adaptation data located at the referenced location with an expected value of the property of the adaptation data; facilitating transmission of the adaptation data to a target device when there is an indication of a speech-facilitated transaction between the target device and the particular party, wherein the adaptation data is configured to be applied to the target device to assist in execution of the speech-facilitated transaction; and facilitating acquisition of adaptation result data that is based on at least one aspect of the speech-facilitated transaction and configured to be used in determining whether to modify the adaptation data. 34. The computationally-implemented method of claim 33 , wherein said storing a reference to a location of adaptation data, wherein the adaptation data is at least partly based on at least one speech interaction of a particular party comprises: storing the reference to the location of adaptation data, wherein the location of adaptation data is one or more of: a network location accessible over the internet; a location on a cloud drive service; a location specified by a stored reference to a cloud drive service; a server picked based on a proximity to a location of a particular user; a location specified by an Internet Protocol (IP) address; a particular page of memory inside a solid state memory; a network address inside an intranet; a MAC address of a physical device; an address of a page on the World Wide Web; and a user account inside a cloud storage device. | 0.847324 |
8,433,696 | 1 | 6 | 1. A method, comprising: associating subsets of content items with corresponding strings of one or more overloaded keys of a keypad so that the subsets of content items are directly mapped to the corresponding strings of one or more overloaded keys by a direct mapping, wherein at least one overloaded key of the one or more overloaded keys is associated with a plurality of alphabetical and/or numerical symbols; ranking content items within at least one of the subsets of content items according to one or more ordering criteria; subsequent to the associating and ranking, receiving entry of a first overloaded key; selecting and presenting a first of the subsets of content items that is associated with the first overloaded key based on the direct mapping; subsequent to receiving entry of the first overloaded key, receiving entry of a second overloaded key the same as or different than the first overloaded key, the second overloaded key forming a string with the first overloaded key; and selecting and presenting a second of the subsets of content items that is associated with the string of overloaded keys formed by the first overloaded key and the second overloaded key based on the direct mapping. | 1. A method, comprising: associating subsets of content items with corresponding strings of one or more overloaded keys of a keypad so that the subsets of content items are directly mapped to the corresponding strings of one or more overloaded keys by a direct mapping, wherein at least one overloaded key of the one or more overloaded keys is associated with a plurality of alphabetical and/or numerical symbols; ranking content items within at least one of the subsets of content items according to one or more ordering criteria; subsequent to the associating and ranking, receiving entry of a first overloaded key; selecting and presenting a first of the subsets of content items that is associated with the first overloaded key based on the direct mapping; subsequent to receiving entry of the first overloaded key, receiving entry of a second overloaded key the same as or different than the first overloaded key, the second overloaded key forming a string with the first overloaded key; and selecting and presenting a second of the subsets of content items that is associated with the string of overloaded keys formed by the first overloaded key and the second overloaded key based on the direct mapping. 6. The method of claim 1 wherein said method comprises receiving entry of a plurality of overloaded keys corresponding to one or more words in an unordered format, the plurality of overloaded keys comprising the string. | 0.829173 |
9,280,534 | 8 | 9 | 8. The method of claim 1 , wherein the determining that the textual term should be added to the social glossary is based on a poll of users. | 8. The method of claim 1 , wherein the determining that the textual term should be added to the social glossary is based on a poll of users. 9. The method of claim 8 , wherein the poll is limited to: users of the social-networking system, users having a relationship with the user according to the social graph, users using the same language as the user, users sharing a demographic category with the user, or users sharing similar profile attributes with the user. | 0.90493 |
9,972,322 | 1 | 5 | 1. A computer-implemented method for speaker recognition comprising: determining a speaker recognition score based on a received audio input; generating a speech to noise ratio based on the received audio input; generating a noise type label corresponding to the received audio input; determining a selected adaptive speaker recognition threshold from a plurality of adaptive speaker recognition thresholds based on the speech to noise ratio, the noise type label, and a target false accept rate corresponding to the received audio input, wherein each of the plurality of adaptive speaker recognition thresholds is associated with a particular noise type label, a particular speech to noise ratio, and a particular target false accept rate, and wherein each of the plurality of adaptive speaker recognition thresholds provides a threshold corresponding to a lowest target false reject rate for the particular noise type label, the particular speech to noise ratio, and the particular target false accept rate; and performing speaker recognition for the received audio input based on a comparison of the speaker recognition score to the selected adaptive speaker recognition threshold. | 1. A computer-implemented method for speaker recognition comprising: determining a speaker recognition score based on a received audio input; generating a speech to noise ratio based on the received audio input; generating a noise type label corresponding to the received audio input; determining a selected adaptive speaker recognition threshold from a plurality of adaptive speaker recognition thresholds based on the speech to noise ratio, the noise type label, and a target false accept rate corresponding to the received audio input, wherein each of the plurality of adaptive speaker recognition thresholds is associated with a particular noise type label, a particular speech to noise ratio, and a particular target false accept rate, and wherein each of the plurality of adaptive speaker recognition thresholds provides a threshold corresponding to a lowest target false reject rate for the particular noise type label, the particular speech to noise ratio, and the particular target false accept rate; and performing speaker recognition for the received audio input based on a comparison of the speaker recognition score to the selected adaptive speaker recognition threshold. 5. The method of claim 1 , further comprising: determining a second selected adaptive speaker recognition threshold from the plurality of adaptive speaker recognition thresholds based on a second speech to noise ratio, a second noise type label, and a second target false accept rate corresponding to a second received audio input; and performing a second speaker recognition for the second received audio input based on a second comparison of a second speaker recognition score to the second selected adaptive speaker recognition threshold, wherein the first and second selected adaptive speaker recognition thresholds are different. | 0.652031 |
10,002,201 | 11 | 12 | 11. A non-transitory computer-readable medium storing software comprising instructions executable by one or more computers which, upon such execution, cause the one or more computers to perform operations comprising: determining that, among a set of search results that include multiple search results and that are each identified as at least potentially relevant by a search engine in response to a search query submitted to the search engine and based on content of a document associated with each search result, one single search result is classified by the search engine as very relevant to the search query based on at least one parameter, calculated by the search engine, that determines relevancy; and in response to determining that, among the set of search results that include multiple search results and are each identified as at least potentially relevant by the search engine, based on the content of the document associated with each search result and in response to the search query submitted to the search engine, one single search result is classified by the search engine as very relevant to the search query, automatically outputting a web page that is referenced by the one single search result that is classified by the search engine as very relevant to the search query, rather than providing a search results page that references a subset of the set of search results that are each identified as at least potentially relevant based on the content of the document associated with each search result and in response to the search query, the one single search result is classified as very relevant based on a relevance score for the result relative to relevance scores for other search results in a ranked list of search results; wherein automatically outputting the web page that is referenced by the one single search result includes providing instructions that cause a client device to provide the web page to the user for display directly after the client device displays a page for the user to submit a search query to the search engine. | 11. A non-transitory computer-readable medium storing software comprising instructions executable by one or more computers which, upon such execution, cause the one or more computers to perform operations comprising: determining that, among a set of search results that include multiple search results and that are each identified as at least potentially relevant by a search engine in response to a search query submitted to the search engine and based on content of a document associated with each search result, one single search result is classified by the search engine as very relevant to the search query based on at least one parameter, calculated by the search engine, that determines relevancy; and in response to determining that, among the set of search results that include multiple search results and are each identified as at least potentially relevant by the search engine, based on the content of the document associated with each search result and in response to the search query submitted to the search engine, one single search result is classified by the search engine as very relevant to the search query, automatically outputting a web page that is referenced by the one single search result that is classified by the search engine as very relevant to the search query, rather than providing a search results page that references a subset of the set of search results that are each identified as at least potentially relevant based on the content of the document associated with each search result and in response to the search query, the one single search result is classified as very relevant based on a relevance score for the result relative to relevance scores for other search results in a ranked list of search results; wherein automatically outputting the web page that is referenced by the one single search result includes providing instructions that cause a client device to provide the web page to the user for display directly after the client device displays a page for the user to submit a search query to the search engine. 12. The medium of claim 11 , the operations comprising classifying the one single search result as very relevant to the search query based on a parameter that is an observed historical click through rate associated with the one single search result, the particular search result being one of the one or more search results that are each classified as at least potentially relevant to the search query. | 0.575212 |
6,154,212 | 14 | 23 | 14. A network interface comprising: a network view portion generated using at least one of a plurality of software components programmed in a first programming language, each of at least a subset of the components programmed in the first programming language including a network base class for managing view operations and interactions with a database, and a display class for managing display operations; and a user interface portion generated using at least one of a plurality of software components programmed in a second programming language at a higher level than the first programming language, each of at least a subset of the components programmed in the second programming language including a standard interface corresponding to a given one of the network base classes, and a special interface associated with a particular type of network view. | 14. A network interface comprising: a network view portion generated using at least one of a plurality of software components programmed in a first programming language, each of at least a subset of the components programmed in the first programming language including a network base class for managing view operations and interactions with a database, and a display class for managing display operations; and a user interface portion generated using at least one of a plurality of software components programmed in a second programming language at a higher level than the first programming language, each of at least a subset of the components programmed in the second programming language including a standard interface corresponding to a given one of the network base classes, and a special interface associated with a particular type of network view. 23. The network interface of claim 14 wherein the network view portion of the network interface includes a view providing a conformal warping of a two-dimensional network map onto a three-dimensional object. | 0.852774 |
8,070,775 | 1 | 2 | 1. A spine implant comprising: an anchor adapted to be inserted into the bone of a patient, the anchor having a longitudinal axis; an anchor head extending from said anchor; a deflection guide cavity in said anchor head, said deflection guide cavity having a deflection guide cavity wall, and an opening at a proximal end of said anchor head; a deflection rod having a distal portion secured within the deflection guide cavity and a proximal portion extending out of the opening of the deflection guide cavity; wherein the spine implant is configured such that, in the absence of a load applied to the proximal portion of the deflection rod, the deflection rod is aligned with the longitudinal axis of the anchor; wherein the spine implant is configured such that a load applied to the proximal portion of the deflection rod causes resilient deflection of the proximal portion of the deflection rod away from alignment with the longitudinal axis of the bone anchor; and wherein resilient deflection of the proximal portion of the deflection rod is limited by contact between the proximal portion of the deflection rod and the deflection guide cavity wall. | 1. A spine implant comprising: an anchor adapted to be inserted into the bone of a patient, the anchor having a longitudinal axis; an anchor head extending from said anchor; a deflection guide cavity in said anchor head, said deflection guide cavity having a deflection guide cavity wall, and an opening at a proximal end of said anchor head; a deflection rod having a distal portion secured within the deflection guide cavity and a proximal portion extending out of the opening of the deflection guide cavity; wherein the spine implant is configured such that, in the absence of a load applied to the proximal portion of the deflection rod, the deflection rod is aligned with the longitudinal axis of the anchor; wherein the spine implant is configured such that a load applied to the proximal portion of the deflection rod causes resilient deflection of the proximal portion of the deflection rod away from alignment with the longitudinal axis of the bone anchor; and wherein resilient deflection of the proximal portion of the deflection rod is limited by contact between the proximal portion of the deflection rod and the deflection guide cavity wall. 2. The implant of claim 1 , wherein said deflection rod comprises an inner metal rod and an outer polymer shell. | 0.849866 |
9,069,757 | 9 | 16 | 9. A communication system comprising: a memory; one or more processors; and one or more modules stored in memory and configured for execution by the one or more processors, the one or more modules comprising: a speech input module configured to receive a first speech signal of a first speaker; an automatic speech recognizer module coupled with said speech input module, said automatic speech recognizer module configured to convert said first speech signal into a text sequence; a speech analyzer module coupled with said speech input module, said speech analyzer module configured to extract paralinguistic characteristics from said first speech signal; a voice analyzer module configured to receive a second speech signal of a second speaker and generate one or more phonemes bases on said second speech signal; and an output speech module coupled with said automatic speech recognizer module, said speech analyzer module, and said voice analyzer module, said output speech module configured to convert said text sequence of said first speech signal into a converted speech signal of said second speaker based on said one or more phonemes of said second speech signal, and convert said converted speech signal into an output speech signal of said second speaker by applying said paralinguistic characteristics to said converted speech signal. | 9. A communication system comprising: a memory; one or more processors; and one or more modules stored in memory and configured for execution by the one or more processors, the one or more modules comprising: a speech input module configured to receive a first speech signal of a first speaker; an automatic speech recognizer module coupled with said speech input module, said automatic speech recognizer module configured to convert said first speech signal into a text sequence; a speech analyzer module coupled with said speech input module, said speech analyzer module configured to extract paralinguistic characteristics from said first speech signal; a voice analyzer module configured to receive a second speech signal of a second speaker and generate one or more phonemes bases on said second speech signal; and an output speech module coupled with said automatic speech recognizer module, said speech analyzer module, and said voice analyzer module, said output speech module configured to convert said text sequence of said first speech signal into a converted speech signal of said second speaker based on said one or more phonemes of said second speech signal, and convert said converted speech signal into an output speech signal of said second speaker by applying said paralinguistic characteristics to said converted speech signal. 16. The communication system of claim 9 , wherein said speech output module converts said text sequence into the converted speech signal using a text-to-speech algorithm. | 0.671815 |
8,019,783 | 10 | 14 | 10. The system of claim 9 , wherein each of said plurality of entity types is defined to include a corresponding set of attributes, wherein said enabling comprises: identifying the attributes associated with said first entity type and said at least one of said second set of entity types; displaying the identified attributes on said display unit; and receiving from said user respective data values associated with corresponding ones of a desired set of attributes. | 10. The system of claim 9 , wherein each of said plurality of entity types is defined to include a corresponding set of attributes, wherein said enabling comprises: identifying the attributes associated with said first entity type and said at least one of said second set of entity types; displaying the identified attributes on said display unit; and receiving from said user respective data values associated with corresponding ones of a desired set of attributes. 14. The system of claim 10 , wherein said set of entity instances of interest are of said first entity type. | 0.967933 |
9,215,243 | 4 | 5 | 4. A method for identifying and ranking URL hyperlinks to possible pirated media content, the method comprising: searching on a computer, by one or more processors, a web page from a first website for one or more indicator keywords, wherein a strength of an indicator keyword is related to a likelihood of pirated media content; responsive to the computer locating a plurality of instances of the one or more indicator keywords, the computer identifying, by one or more processors, a plurality of hyperlinks respectively associated with one or more of the plurality of instances; weighting on the computer, by one or more processors, the identified plurality of hyperlinks based on at least one of a strength of associated indicator keywords, number of associated indicator keywords, number of times each hyperlink was identified, and date of posting; identifying a primary hyperlink for each of the plurality of hyperlinks and determining a number of times respective primary hyperlinks have been identified; ranking on the computer, by one or more processors, the plurality of hyperlinks according to weight indicating a relative likelihood that respective hyperlinks point to pirated media content in a ranked list; determining, by one or more processors on the computer, whether each of the identified plurality of hyperlinks associated with one or more of the plurality of instances has met one or more thresholds, wherein the one or more thresholds are based on at least one or more of: a ratio of strong indicator keywords to weak indicator keywords, a number of strong indicator keywords, and a proximity of each of the plurality of hyperlinks to the one or more indicator keywords; and responsive to determining one or more of the identified plurality of hyperlinks has not met the one or more thresholds, removing, by one or more processors, the one or more of the identified plurality of hyperlinks from the ranked list; displaying on a display screen of said computer a first portion of the rankings of the plurality of hyperlinks according to weight in a first view; receiving, by one or more processors on the computer, an input to display a second portion of the rankings of the plurality of hyperlinks according to weight in a second view; displaying on the display screen of said computer the second portion of the rankings of the plurality of hyperlinks according to weight in the second view; and a user viewing said rankings of the plurality of hyperlinks to direct the user to one or more web pages that may contain pirated media content of copyrighted media and identifying those web pages providing illegal access to said copyrighted media for protection thereof. | 4. A method for identifying and ranking URL hyperlinks to possible pirated media content, the method comprising: searching on a computer, by one or more processors, a web page from a first website for one or more indicator keywords, wherein a strength of an indicator keyword is related to a likelihood of pirated media content; responsive to the computer locating a plurality of instances of the one or more indicator keywords, the computer identifying, by one or more processors, a plurality of hyperlinks respectively associated with one or more of the plurality of instances; weighting on the computer, by one or more processors, the identified plurality of hyperlinks based on at least one of a strength of associated indicator keywords, number of associated indicator keywords, number of times each hyperlink was identified, and date of posting; identifying a primary hyperlink for each of the plurality of hyperlinks and determining a number of times respective primary hyperlinks have been identified; ranking on the computer, by one or more processors, the plurality of hyperlinks according to weight indicating a relative likelihood that respective hyperlinks point to pirated media content in a ranked list; determining, by one or more processors on the computer, whether each of the identified plurality of hyperlinks associated with one or more of the plurality of instances has met one or more thresholds, wherein the one or more thresholds are based on at least one or more of: a ratio of strong indicator keywords to weak indicator keywords, a number of strong indicator keywords, and a proximity of each of the plurality of hyperlinks to the one or more indicator keywords; and responsive to determining one or more of the identified plurality of hyperlinks has not met the one or more thresholds, removing, by one or more processors, the one or more of the identified plurality of hyperlinks from the ranked list; displaying on a display screen of said computer a first portion of the rankings of the plurality of hyperlinks according to weight in a first view; receiving, by one or more processors on the computer, an input to display a second portion of the rankings of the plurality of hyperlinks according to weight in a second view; displaying on the display screen of said computer the second portion of the rankings of the plurality of hyperlinks according to weight in the second view; and a user viewing said rankings of the plurality of hyperlinks to direct the user to one or more web pages that may contain pirated media content of copyrighted media and identifying those web pages providing illegal access to said copyrighted media for protection thereof. 5. The method of claim 4 , further comprising: searching on the computer, by one or more processors, a second website for one or more indicator keywords in text posted to one or more web pages of the second website; responsive to locating a second plurality of instances of the one or more indicator keywords, identifying on the computer, by one or more processors, a second plurality of hyperlinks associated with one or more of the second plurality of instances; weighting on the computer, by one or more processors, the identified the second plurality of hyperlinks based on at least one of: a strength of associated keywords, number of associated keywords, number of times each hyperlink was identified, and date of posting; and ranking on the computer the second plurality of hyperlinks according to weight. | 0.500615 |
9,225,737 | 11 | 13 | 11. The computer-implemented method of claim 1 , further comprising receiving, at the computer server subsystem, data that indicates a context of at least one of (i) the web pages and (ii) the particular client computers, wherein identifying the clusters from the data that characterizes the subsets of the particular document object models comprises correlating features in the subsets of the particular document object models with features indicated by the context. | 11. The computer-implemented method of claim 1 , further comprising receiving, at the computer server subsystem, data that indicates a context of at least one of (i) the web pages and (ii) the particular client computers, wherein identifying the clusters from the data that characterizes the subsets of the particular document object models comprises correlating features in the subsets of the particular document object models with features indicated by the context. 13. The computer-implemented method of claim 11 , wherein the data that indicates the context comprises information that identifies an application that rendered the web page at particular ones of the client computers. | 0.887331 |
9,286,404 | 7 | 9 | 7. A computer-implemented method of displaying information about a document that includes a spatial identifier that identifies a corresponding location within a metric space and wherein that spatial identifier is characterized by a semantic type that is determined by the use of the spatial identifier within the document, said method comprising: displaying at least a portion of content from the document, wherein the at least one portion of content is a natural language; visually identifying the spatial identifier within a displayed visual representation of the content from the document; visually indicating the semantic type of the spatial identifier wherein the semantic type is determined by a path hierarchy for each location; and visually differentiating, by visually promoting and highlighting differently, two or more corresponding locations based on attributes that are defined with reference to the document, wherein the locations that are metonymic are given less prominent visual emphasis than other locations. | 7. A computer-implemented method of displaying information about a document that includes a spatial identifier that identifies a corresponding location within a metric space and wherein that spatial identifier is characterized by a semantic type that is determined by the use of the spatial identifier within the document, said method comprising: displaying at least a portion of content from the document, wherein the at least one portion of content is a natural language; visually identifying the spatial identifier within a displayed visual representation of the content from the document; visually indicating the semantic type of the spatial identifier wherein the semantic type is determined by a path hierarchy for each location; and visually differentiating, by visually promoting and highlighting differently, two or more corresponding locations based on attributes that are defined with reference to the document, wherein the locations that are metonymic are given less prominent visual emphasis than other locations. 9. The computer-implemented method of claim 7 , wherein the semantic type is a context-dependent property of the spatial indicator. | 0.828982 |
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