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7,934,660 | 4 | 5 | 4. A data collection system comprising: a hand held portable data collection terminal having a bar code reader device for decoding bar code symbols, a manual trigger for actuation of bar code decoding, and a radio transceiver; a computer spaced apart from said hand held portable data collection terminal, said computer having a display, said hand held portable data collection terminal and said computer being configured as part of an IP network including both of said hand held portable data collection terminal and said computer; said computer being configured to display a graphical user interface prompting an operator of said data collection system to select data for inclusion in a data package, said computer building a data package in accordance with at least one selection of said operator; wherein said data collection system is configured so that said data package built by said computer can be transferred from said computer to said hand held portable data collection terminal by either of (i) encoding data of said data package and then decoding encoded data utilizing said bar code reader device of said portable data collection terminal or (ii) transmitting said data package from said computer to said portable data collection terminal utilizing a data communication protocol supported by said IP network. | 4. A data collection system comprising: a hand held portable data collection terminal having a bar code reader device for decoding bar code symbols, a manual trigger for actuation of bar code decoding, and a radio transceiver; a computer spaced apart from said hand held portable data collection terminal, said computer having a display, said hand held portable data collection terminal and said computer being configured as part of an IP network including both of said hand held portable data collection terminal and said computer; said computer being configured to display a graphical user interface prompting an operator of said data collection system to select data for inclusion in a data package, said computer building a data package in accordance with at least one selection of said operator; wherein said data collection system is configured so that said data package built by said computer can be transferred from said computer to said hand held portable data collection terminal by either of (i) encoding data of said data package and then decoding encoded data utilizing said bar code reader device of said portable data collection terminal or (ii) transmitting said data package from said computer to said portable data collection terminal utilizing a data communication protocol supported by said IP network. 5. The data collection system of claim 4 , wherein said data communication protocol is the File Transfer Protocol (FTP). | 0.693878 |
4,516,260 | 50 | 55 | 50. A talking electronic apparatus comprising: memory means for storing digital speech data and digital control data from which a plurality of requests in synthesized human speech for respective operator responses and appropriate operator responses corresponding to each of said plurality of requests may be respectively derived, speech synthesizer means operably associated with said memory means for converting said digital speech data into audible human speech, means for selectively transferring said digital speech data to said speech synthesizer means to produce a selected audible request in human speech, means responsive to said digital control data for producing a visual display corresponding to said selected audible request, operator input means for receiving an operator response to said selected audible request, and means responsive to said digital control data and said operator response to said selected audible request for responding in a manner producing an output indicative of the appropriateness of said operator response with respect to the appropriate operator response corresponding to said selected audible request. | 50. A talking electronic apparatus comprising: memory means for storing digital speech data and digital control data from which a plurality of requests in synthesized human speech for respective operator responses and appropriate operator responses corresponding to each of said plurality of requests may be respectively derived, speech synthesizer means operably associated with said memory means for converting said digital speech data into audible human speech, means for selectively transferring said digital speech data to said speech synthesizer means to produce a selected audible request in human speech, means responsive to said digital control data for producing a visual display corresponding to said selected audible request, operator input means for receiving an operator response to said selected audible request, and means responsive to said digital control data and said operator response to said selected audible request for responding in a manner producing an output indicative of the appropriateness of said operator response with respect to the appropriate operator response corresponding to said selected audible request. 55. A talking electronic apparatus according to claim 50, further including battery receiving means for holding a battery power source to provide electrical power to said apparatus. | 0.672101 |
8,312,056 | 1 | 4 | 1. A method for identifying a key influencer in a social media, said method comprising: compiling a user interest profile by analyzing a historical message stored in a database utilizing a topic modeling approach to thereafter generate social graph data; performing an influence measuring process based on said social graph data utilizing an influence measuring module and a data intensive distributed application module to identify a set of key influencers in a particular topic area by considering time stamp information; and assessing an impact of user communication with respect to growth of a conversation within a predefined time interval in order to predict a message propagation speed and coverage in a social network and permit efficient targeting of said message to said key influencer of a targeted community. | 1. A method for identifying a key influencer in a social media, said method comprising: compiling a user interest profile by analyzing a historical message stored in a database utilizing a topic modeling approach to thereafter generate social graph data; performing an influence measuring process based on said social graph data utilizing an influence measuring module and a data intensive distributed application module to identify a set of key influencers in a particular topic area by considering time stamp information; and assessing an impact of user communication with respect to growth of a conversation within a predefined time interval in order to predict a message propagation speed and coverage in a social network and permit efficient targeting of said message to said key influencer of a targeted community. 4. The method of claim 1 further comprising generating said social graph utilizing said user as a node and a social relationship between said users as an edge wherein said edge weight is defined based on a strength of relationship. | 0.5 |
7,617,232 | 13 | 18 | 13. A system for developing terminology for use within an organization, said system comprising: a memory area for storing terminology data related to the organization; and a processor configured to execute computer-executable instructions to: receive data representing a term for building a glossary of terms from a user, receive data representing a project to be associated with the term in the organization from the user, said term representing a terminology used in association with the one or more projects, said terminology associating with at least a definition included in the terminology data stored in the memory area, define a relationship between the received data representing the term and the received data representing the one or more projects, said relationship defining at least one of the following: a project may include zero to many terms, a term may appear in zero to many projects, and a term may not appear in the same project more than once, link the received data representing the term and the received data representing the project in the memory area, automatically extract the definition associated with the data representing the term from the terminology data in the memory area; and automatically generate a glossary including the term for the project, said generated glossary including the term having the extracted definition linked to the one or more projects provided from the user. | 13. A system for developing terminology for use within an organization, said system comprising: a memory area for storing terminology data related to the organization; and a processor configured to execute computer-executable instructions to: receive data representing a term for building a glossary of terms from a user, receive data representing a project to be associated with the term in the organization from the user, said term representing a terminology used in association with the one or more projects, said terminology associating with at least a definition included in the terminology data stored in the memory area, define a relationship between the received data representing the term and the received data representing the one or more projects, said relationship defining at least one of the following: a project may include zero to many terms, a term may appear in zero to many projects, and a term may not appear in the same project more than once, link the received data representing the term and the received data representing the project in the memory area, automatically extract the definition associated with the data representing the term from the terminology data in the memory area; and automatically generate a glossary including the term for the project, said generated glossary including the term having the extracted definition linked to the one or more projects provided from the user. 18. The system of claim 13 wherein the processor is configured to execute computer-executable instructions to generate a help file based on the received data representing the term and the received data representing the project. | 0.738479 |
8,572,511 | 1 | 2 | 1. A non-transitory computer readable medium including a sequence of instructions stored thereon for causing a computer to execute a method, comprising: generating a search term entry area operable to allow a user to enter text as a search term; generating a hierarchical tree area operable to display data elements in a multi-level hierarchical tree structure, wherein the data elements are representative of searchable data in a database; generating a search result area operable to display a result of a search query; and generating a search criteria tree area operable to allow a user to enter a new search query of the searchable data in response to the user's selection of one or more of the search term from the search term entry area, the data elements from the hierarchical tree area, and the result from the search result area, wherein the search criteria tree area enables the user to select the search term from the search term entry area, the data elements from the hierarchical tree area, and the result from the search result area for the new search query, and wherein the search term entry area, hierarchical tree area, search results area, and search criteria tree area are displayed together in a single window on a graphical user interface. | 1. A non-transitory computer readable medium including a sequence of instructions stored thereon for causing a computer to execute a method, comprising: generating a search term entry area operable to allow a user to enter text as a search term; generating a hierarchical tree area operable to display data elements in a multi-level hierarchical tree structure, wherein the data elements are representative of searchable data in a database; generating a search result area operable to display a result of a search query; and generating a search criteria tree area operable to allow a user to enter a new search query of the searchable data in response to the user's selection of one or more of the search term from the search term entry area, the data elements from the hierarchical tree area, and the result from the search result area, wherein the search criteria tree area enables the user to select the search term from the search term entry area, the data elements from the hierarchical tree area, and the result from the search result area for the new search query, and wherein the search term entry area, hierarchical tree area, search results area, and search criteria tree area are displayed together in a single window on a graphical user interface. 2. The non-transitory computer readable medium of claim 1 , wherein the method further comprises generating a window that appears in response to a user's selection of one of the search term, data elements, and result in the search criteria tree area, wherein the window is operable to allow the user to modify a scope of the new search query by providing the user with selectable options to further define the one of the search term, data elements, and result. | 0.5 |
8,024,280 | 16 | 20 | 16. A non-transitory computer-readable storage medium storing one or more sequences of instructions which, when executed by one or more processors, causes the one or more processors to perform the steps of: a website sending a webpage that includes content which, when rendered at a client, causes the client to display a question; receiving from the client on which the web page was rendered, input that was provided by a user of the client through one or more controls on the webpage, wherein the input comprises text that indicates an answer to the question; automatically determining whether the answer is likely to contain useful information responsive to the question on the webpage, wherein determining whether the answer is likely to contain useful information comprises: generating a first numerical value based on a first analysis of the text; generating a second numerical value based on a second analysis of the text; generating a score for the text based at least in part on the first and second numerical values; and based on the score for the text, performing at least one of: a) determining, based on the first and second analysis of the text, whether to display the answer on subsequent pages of the website, or b) determining, based on the first and second analysis of the text, how to display the answer on subsequent pages of the website; wherein the second analysis is different than the first analysis; wherein each of the first analysis and the second analysis is one of: determining whether proper punctuation is used in said text; determining whether correct spelling is used in said text; determining whether slang words are used in said text; determining whether said text contains specialized words; determining whether said text contains words with three or more syllables; determining whether grammar is properly used in said text; or determining whether said text contains rare words. | 16. A non-transitory computer-readable storage medium storing one or more sequences of instructions which, when executed by one or more processors, causes the one or more processors to perform the steps of: a website sending a webpage that includes content which, when rendered at a client, causes the client to display a question; receiving from the client on which the web page was rendered, input that was provided by a user of the client through one or more controls on the webpage, wherein the input comprises text that indicates an answer to the question; automatically determining whether the answer is likely to contain useful information responsive to the question on the webpage, wherein determining whether the answer is likely to contain useful information comprises: generating a first numerical value based on a first analysis of the text; generating a second numerical value based on a second analysis of the text; generating a score for the text based at least in part on the first and second numerical values; and based on the score for the text, performing at least one of: a) determining, based on the first and second analysis of the text, whether to display the answer on subsequent pages of the website, or b) determining, based on the first and second analysis of the text, how to display the answer on subsequent pages of the website; wherein the second analysis is different than the first analysis; wherein each of the first analysis and the second analysis is one of: determining whether proper punctuation is used in said text; determining whether correct spelling is used in said text; determining whether slang words are used in said text; determining whether said text contains specialized words; determining whether said text contains words with three or more syllables; determining whether grammar is properly used in said text; or determining whether said text contains rare words. 20. The computer-readable storage medium of claim 16 : wherein the text comprises an answer to a question; wherein the first analysis involves causing the text to be processed through a first filter that is based on a first selected set of rules; wherein the second analysis involves causing the text to be processed through a second filter that is based on a second selected set of rules. | 0.5 |
8,983,839 | 20 | 25 | 20. A system for facilitating dynamic-recognition-grammar-based interpretation of one or more natural language utterance, the system comprising: one or more physical processors programmed with computer program instructions which, when executed, cause the one or more physical processors to: receive a natural language utterance relating to a navigation context; determine one or more similarities between a user associated with the natural language utterance and one or more other users; determine a dynamic recognition grammar based on the one or more determined similarities; and generate one or more interpretations associated with the natural language utterance based on the dynamic recognition grammar. | 20. A system for facilitating dynamic-recognition-grammar-based interpretation of one or more natural language utterance, the system comprising: one or more physical processors programmed with computer program instructions which, when executed, cause the one or more physical processors to: receive a natural language utterance relating to a navigation context; determine one or more similarities between a user associated with the natural language utterance and one or more other users; determine a dynamic recognition grammar based on the one or more determined similarities; and generate one or more interpretations associated with the natural language utterance based on the dynamic recognition grammar. 25. The system of claim 20 , wherein the one or more physical processors are further caused to: receive a subsequent natural language utterance; update the dynamic recognition grammar based on the subsequent natural language utterance; and refine the one or more interpretations associated with the natural language utterance based on the updated dynamic recognition grammar. | 0.748996 |
8,145,623 | 1 | 7 | 1. A computer-implemented method, comprising: selecting a plurality of search queries; grouping the plurality of search queries into one or more clusters, wherein grouping further comprises: assigning each of the plurality of search queries to a cluster in a total number of clusters; designating one of the search queries assigned to each cluster as a cluster center for the each cluster; and adjusting one or more of (i) the total number of clusters, (ii) an assignment of search queries to the clusters, and (iii) a designation of cluster centers for the clusters, to minimize an aggregated metric of all search queries, where a metric of a search query is between the search query and the cluster center of the cluster comprising the search query; selecting a representative query for each cluster; associating each cluster with a respective representative category; assigning a respective rank to each of the clusters, the assigning being based on a cluster popularity score of each cluster and a category popularity score of each cluster's respective representative category; and presenting the selected representative queries in order according to the ranks of their respective clusters, wherein assigning a respective rank to each of the clusters is performed on one or more processors. | 1. A computer-implemented method, comprising: selecting a plurality of search queries; grouping the plurality of search queries into one or more clusters, wherein grouping further comprises: assigning each of the plurality of search queries to a cluster in a total number of clusters; designating one of the search queries assigned to each cluster as a cluster center for the each cluster; and adjusting one or more of (i) the total number of clusters, (ii) an assignment of search queries to the clusters, and (iii) a designation of cluster centers for the clusters, to minimize an aggregated metric of all search queries, where a metric of a search query is between the search query and the cluster center of the cluster comprising the search query; selecting a representative query for each cluster; associating each cluster with a respective representative category; assigning a respective rank to each of the clusters, the assigning being based on a cluster popularity score of each cluster and a category popularity score of each cluster's respective representative category; and presenting the selected representative queries in order according to the ranks of their respective clusters, wherein assigning a respective rank to each of the clusters is performed on one or more processors. 7. The method of claim 1 wherein presenting representative queries further comprises: presenting one or more representative queries in order according to the ranks of their respective clusters, where the one or more representative queries are associated with a common representative category. | 0.764895 |
8,448,218 | 1 | 9 | 1. A security method, comprising: (a) providing a repository which is able to store initial cryptographic certificates and policies for resources including, but not limited to, executable files, whereby the resource's author can be authenticated, and system calls that are necessary for malicious behaviour are identified, (b) providing a repository which is able to store initial security policies, (c) providing a repository which is able to store loaded files and processes state information, (d) providing a memory which is able to store executable code, (e) intercepting a call, (f) determining whether the call is a request to load an executable file into said memory, (g) when it is determined that the call is a request to load an executable file into said memory, analysing the cryptographic compliance as per initially determined policies and determining whether it is compliant, (h) when it is determined that the file is compliant with said cryptographic policies, loading said file into said memory, assigning it full rights, updating state information related to the call, the associated file including, but not limited to, the unequivocal identification of the resource's author, and the newly loaded process into said memory, (i) when it is determined that the file is not compliant with cryptographic policies, loading said file into memory, assigning it limited rights, updating state information related to the call, the associated file, and the newly loaded process into said memory, (j) when it is determined that the call is not a request to load an executable file into memory, determining whether the call is a restricted call as per the initially determined security policies, (k) when it is determined that the call is restricted, determining the calling process rights based on the state machine information of the calling process hierarchy, (l) when it is determined that the process is not authorised, updating the state machine information, reacting to the unauthorised call, (m) when it is determined that the process is authorised, updating the state machine information, returning control to the operating system, repeating (c)-(m); wherein an interceptor intercepts the call and forwards the call to a detector, wherein the detector includes an infrastructure for providing a state machine; whereby executable files requiring full rights will need to comply with said initial cryptographic certificates and policies, including but not limited to unequivocal identification of the resource's author, whereby executable files with limited rights will not be able to perform activities, including, but not limited to, system calls, necessary for malware's malicious behaviour as defined in the initial policies; whereby the revocation of the cryptographic certificates of the resources, including, but not limited to, executable files, will prevent the propagation of malware without the need for distribution of updates for the security method here described; whereby the post-mortem analysis of the cryptographic certificates of malware allows for the legal prosecution and accountability of the malware's authors. | 1. A security method, comprising: (a) providing a repository which is able to store initial cryptographic certificates and policies for resources including, but not limited to, executable files, whereby the resource's author can be authenticated, and system calls that are necessary for malicious behaviour are identified, (b) providing a repository which is able to store initial security policies, (c) providing a repository which is able to store loaded files and processes state information, (d) providing a memory which is able to store executable code, (e) intercepting a call, (f) determining whether the call is a request to load an executable file into said memory, (g) when it is determined that the call is a request to load an executable file into said memory, analysing the cryptographic compliance as per initially determined policies and determining whether it is compliant, (h) when it is determined that the file is compliant with said cryptographic policies, loading said file into said memory, assigning it full rights, updating state information related to the call, the associated file including, but not limited to, the unequivocal identification of the resource's author, and the newly loaded process into said memory, (i) when it is determined that the file is not compliant with cryptographic policies, loading said file into memory, assigning it limited rights, updating state information related to the call, the associated file, and the newly loaded process into said memory, (j) when it is determined that the call is not a request to load an executable file into memory, determining whether the call is a restricted call as per the initially determined security policies, (k) when it is determined that the call is restricted, determining the calling process rights based on the state machine information of the calling process hierarchy, (l) when it is determined that the process is not authorised, updating the state machine information, reacting to the unauthorised call, (m) when it is determined that the process is authorised, updating the state machine information, returning control to the operating system, repeating (c)-(m); wherein an interceptor intercepts the call and forwards the call to a detector, wherein the detector includes an infrastructure for providing a state machine; whereby executable files requiring full rights will need to comply with said initial cryptographic certificates and policies, including but not limited to unequivocal identification of the resource's author, whereby executable files with limited rights will not be able to perform activities, including, but not limited to, system calls, necessary for malware's malicious behaviour as defined in the initial policies; whereby the revocation of the cryptographic certificates of the resources, including, but not limited to, executable files, will prevent the propagation of malware without the need for distribution of updates for the security method here described; whereby the post-mortem analysis of the cryptographic certificates of malware allows for the legal prosecution and accountability of the malware's authors. 9. The method as recited in claim 1 , wherein the reacting includes terminating the unwanted process. | 0.889738 |
9,400,827 | 7 | 14 | 7. An apparatus comprising: means for synchronizing search results from at least two data sources in response to a user search query, the data sources comprising a central database comprising an asset table for a plurality of external databases storing media assets, and at least one of a file repository and another site, wherein an asset comprises an aggregation of information regarding a media essence; means for establishing a search configuration in response to the user search query means for aggregating the synchronized search results from the at least two data sources, said aggregating including assigning an identifier for each application corresponding to a respective asset; and means for presenting the aggregated search results to the user as one search result. | 7. An apparatus comprising: means for synchronizing search results from at least two data sources in response to a user search query, the data sources comprising a central database comprising an asset table for a plurality of external databases storing media assets, and at least one of a file repository and another site, wherein an asset comprises an aggregation of information regarding a media essence; means for establishing a search configuration in response to the user search query means for aggregating the synchronized search results from the at least two data sources, said aggregating including assigning an identifier for each application corresponding to a respective asset; and means for presenting the aggregated search results to the user as one search result. 14. The apparatus according to claim 7 , wherein said means for establishing defines search environment parameters involved in the search. | 0.601156 |
9,305,113 | 9 | 15 | 9. A system comprising: one or more data stores storing a query log that includes search queries for a plurality of different search sessions; and data processing apparatus including one or more processors executing instructions that cause the one or more processors to interact with the data store and to perform actions including: receiving a current search query during a current search session; determining, based on a difference between terms of the current search query and terms of a previous search query received during the current search session, that the current search query is an attempt to refine the previous search query; identifying, based on the determination that the current search query is an attempt to refine the previous search query, a set of related terms based on a given term that is included in the previous search query, but not included in the current search query; determining, based on search log data for previous search sessions, that the given term was replaced with a different term from the set of related terms in at least a specified portion of the previous search sessions; in response to the determination that the given term was replaced with the different term from the set of related terms, generating a modified search query that includes the different term; and providing the modified search query for presentation in a display of a user device corresponding to the current search session. | 9. A system comprising: one or more data stores storing a query log that includes search queries for a plurality of different search sessions; and data processing apparatus including one or more processors executing instructions that cause the one or more processors to interact with the data store and to perform actions including: receiving a current search query during a current search session; determining, based on a difference between terms of the current search query and terms of a previous search query received during the current search session, that the current search query is an attempt to refine the previous search query; identifying, based on the determination that the current search query is an attempt to refine the previous search query, a set of related terms based on a given term that is included in the previous search query, but not included in the current search query; determining, based on search log data for previous search sessions, that the given term was replaced with a different term from the set of related terms in at least a specified portion of the previous search sessions; in response to the determination that the given term was replaced with the different term from the set of related terms, generating a modified search query that includes the different term; and providing the modified search query for presentation in a display of a user device corresponding to the current search session. 15. The system of claim 9 , wherein identifying a set of related tokens comprises selecting, as the set of related tokens, tokens that have at least a specified level of similarity to the subject context of the current search session. | 0.508403 |
9,430,738 | 4 | 14 | 4. A social media intelligence platform comprising: a. a processor providing an analyst application comprising: i. a first software module obtaining real-time social media conversations; ii. a second software module automatically classifying, categorizing and summarizing expressed emotions in said real-time social media conversations by using a knowledge base of emotional words, or phrases, or both words and phrases as an input, wherein the knowledge base comprises a list of emotional tokens and pairwise token distance using a degree of similarity, each pair associated with a valence and arousal score expressed on a scale; iii. a third software module defining a continuous distance metric between said real-time social media conversations comprising same or different number of the emotional tokens utilizing an expand-align-compare (EAC) algorithm; and iv. a fourth software module conducting clustering based on that distance metric; b. the processor further providing a customer dashboard application comprising: i. a fifth software module providing an interface allowing the customer to input a topic; and ii. a sixth software module providing a graphic visualization of the sentiment clusters for the topic. | 4. A social media intelligence platform comprising: a. a processor providing an analyst application comprising: i. a first software module obtaining real-time social media conversations; ii. a second software module automatically classifying, categorizing and summarizing expressed emotions in said real-time social media conversations by using a knowledge base of emotional words, or phrases, or both words and phrases as an input, wherein the knowledge base comprises a list of emotional tokens and pairwise token distance using a degree of similarity, each pair associated with a valence and arousal score expressed on a scale; iii. a third software module defining a continuous distance metric between said real-time social media conversations comprising same or different number of the emotional tokens utilizing an expand-align-compare (EAC) algorithm; and iv. a fourth software module conducting clustering based on that distance metric; b. the processor further providing a customer dashboard application comprising: i. a fifth software module providing an interface allowing the customer to input a topic; and ii. a sixth software module providing a graphic visualization of the sentiment clusters for the topic. 14. The platform of claim 4 , wherein the graphic visualization of sentiment clusters comprises one or more prototypical communications associated with each cluster. | 0.523121 |
9,237,211 | 1 | 11 | 1. An energy harvesting communication device configured with signal booster apparatus, comprising: at least a communication apparatus; at least an antenna apparatus communicatively coupled to the communication apparatus and in association with at least an input output (IO) device; at least a microprocessor configured with a software for controlling communications via the communication apparatus and for processing data associated with said IO device; said at least an antenna apparatus in communication with said at least a microprocessor; and at least a sensor apparatus embedded in silicon substrate and embedded in a microfiber material to provide at least one of a communication medium, communication clarity, a detection platform, detection selectivity, and detection sensitivity. | 1. An energy harvesting communication device configured with signal booster apparatus, comprising: at least a communication apparatus; at least an antenna apparatus communicatively coupled to the communication apparatus and in association with at least an input output (IO) device; at least a microprocessor configured with a software for controlling communications via the communication apparatus and for processing data associated with said IO device; said at least an antenna apparatus in communication with said at least a microprocessor; and at least a sensor apparatus embedded in silicon substrate and embedded in a microfiber material to provide at least one of a communication medium, communication clarity, a detection platform, detection selectivity, and detection sensitivity. 11. The energy harvesting communication device of claim 1 , wherein said detection platform further comprises at least one of: a mobile phone case; a mobile phone housing; a mobile phone circuitry; a housing for an electronic device; a case for an electronic device; a housing for said communication apparatus; a circuit board for said communication apparatus; each said detection platform further operable for generating electrical energy. | 0.849315 |
7,933,771 | 13 | 18 | 13. The method as claimed in claim 12 , wherein said at least one environment parameter in said step (a) further includes signal-to-noise ratio (SNR) of said input signal, a probability of said input signal being speech or any combination of the environment parameters, and said verification training is trained with environment parameters in advance using multi-layer perception (MLP) method of pattern classification. | 13. The method as claimed in claim 12 , wherein said at least one environment parameter in said step (a) further includes signal-to-noise ratio (SNR) of said input signal, a probability of said input signal being speech or any combination of the environment parameters, and said verification training is trained with environment parameters in advance using multi-layer perception (MLP) method of pattern classification. 18. The method as claimed in claim 13 , wherein one of said plurality of strategies of said step (c) is to inform a user of environment conditions and signal quality, and provide said user with corresponding solutions. | 0.762527 |
9,251,292 | 1 | 5 | 1. A method for searching, the method comprising: receiving, by a computer system, first queries, from a user; selecting, by the computer system, a plurality of head queries from among the first queries; clustering, by the computer system, the first queries, exclusive of the plurality of head queries, to the plurality of head queries by: calculating similarity scores for at least a portion of the first queries relative to the plurality of head queries; and clustering the at least the portion of the first queries to the plurality of head queries according to the similarity scores; associating, by the computer system, one or more categories with each head query of the plurality of head queries; receiving, by the computer system, a second query; determining a similarity between the second query and at least one of a selected head query of the plurality of head queries; associating, by the computer system, the second query with the selected head query of the plurality of head queries according to the similarity between the second query and the at least one of the selected head query; and identifying, by the computer system, one or more documents relevant to the second query using the one or more categories associated with the selected head query of the plurality of head queries; wherein: calculating the similarity scores for the at least the portion of the first queries relative to the plurality of head queries further comprises: evaluating response similarity between user selections of search results for the at least the portion of the first queries and user selections of search results for the plurality of head queries by evaluating an equation: Sim ( q 1 , q 2 ) = P 1 · P 2 P 1 2 P 2 2 where Sim (q 1 ,q 2 ) is a similarity score of a first query a 1 of the at least the portion of the first queries, q 2 is a head query of the plurality of head queries, P 1 is a vector of user selection counts for search results of q 1 , and P 2 is a vector of user selection counts for search results of q 2 . | 1. A method for searching, the method comprising: receiving, by a computer system, first queries, from a user; selecting, by the computer system, a plurality of head queries from among the first queries; clustering, by the computer system, the first queries, exclusive of the plurality of head queries, to the plurality of head queries by: calculating similarity scores for at least a portion of the first queries relative to the plurality of head queries; and clustering the at least the portion of the first queries to the plurality of head queries according to the similarity scores; associating, by the computer system, one or more categories with each head query of the plurality of head queries; receiving, by the computer system, a second query; determining a similarity between the second query and at least one of a selected head query of the plurality of head queries; associating, by the computer system, the second query with the selected head query of the plurality of head queries according to the similarity between the second query and the at least one of the selected head query; and identifying, by the computer system, one or more documents relevant to the second query using the one or more categories associated with the selected head query of the plurality of head queries; wherein: calculating the similarity scores for the at least the portion of the first queries relative to the plurality of head queries further comprises: evaluating response similarity between user selections of search results for the at least the portion of the first queries and user selections of search results for the plurality of head queries by evaluating an equation: Sim ( q 1 , q 2 ) = P 1 · P 2 P 1 2 P 2 2 where Sim (q 1 ,q 2 ) is a similarity score of a first query a 1 of the at least the portion of the first queries, q 2 is a head query of the plurality of head queries, P 1 is a vector of user selection counts for search results of q 1 , and P 2 is a vector of user selection counts for search results of q 2 . 5. The method of claim 1 , wherein selecting, by the computer system, the plurality of head queries from among the first queries further comprises: selecting, as the plurality of head queries, those queries of the first queries having highest click-through rates for search results associated therewith. | 0.826062 |
7,664,641 | 32 | 35 | 32. A method of performing quality analysis on a plurality of interactions, each one of the interactions involving at least one agent, the method comprising at least the following: obtaining data representing at least a given one of the interactions, each one of the interactions having a respective actual duration parameter associated therewith; obtaining data representing at least one expected duration parameter evaluated by an automatic recognition component having a log record module that is applicable to at least the given one of the interactions; for at least the given one of the interactions, comparing the actual duration of the given one interaction to the expected duration parameter and comparing a plurality of duration parameters to respective portions of the actual duration of the given one interaction; dispositioning at least the given one interaction based on the comparing; wherein dispositioning at least the given transaction including assigning the given interaction for evaluation because the actual duration of the given interaction falls outside of a pre-defined range applicable to the given interaction. | 32. A method of performing quality analysis on a plurality of interactions, each one of the interactions involving at least one agent, the method comprising at least the following: obtaining data representing at least a given one of the interactions, each one of the interactions having a respective actual duration parameter associated therewith; obtaining data representing at least one expected duration parameter evaluated by an automatic recognition component having a log record module that is applicable to at least the given one of the interactions; for at least the given one of the interactions, comparing the actual duration of the given one interaction to the expected duration parameter and comparing a plurality of duration parameters to respective portions of the actual duration of the given one interaction; dispositioning at least the given one interaction based on the comparing; wherein dispositioning at least the given transaction including assigning the given interaction for evaluation because the actual duration of the given interaction falls outside of a pre-defined range applicable to the given interaction. 35. The method of claim 32 , wherein obtaining data representing the given one of the interactions includes receiving a respective voice record of the given one of the interactions involving an agent physically located remotely from a call center. | 0.666216 |
7,677,967 | 16 | 17 | 16. A computer program product as recited in claim 15 , wherein the input received from the first human participant is received at the computing system through a network connection from a remote computing system where the input is entered. | 16. A computer program product as recited in claim 15 , wherein the input received from the first human participant is received at the computing system through a network connection from a remote computing system where the input is entered. 17. A computer program product as recited in claim 16 , wherein the network connection includes the Internet. | 0.5 |
8,793,229 | 13 | 18 | 13. A computer system for determining a set of legal documents to present to a user for acceptance as part of a transaction, the system comprising: a computer processor; and a non-transitory computer-readable storage medium storing computer program module configured to execute on the computer processor, the computer program modules comprising: a communications module configured to receive informational data describing a transaction; a documents module configured to identify a set of hierarchical electronic documents pertinent to the transaction based at least in part on the received informational data, the set including a root electronic document and one or more dependency electronic documents of the root electronic document, the root electronic document specifying a transaction identifier of the transaction and metadata identifying the one or more dependency electronic documents; a verification module configured to: select a subset of electronic documents from the set of hierarchical electronic documents based at least in part on data describing electronic documents that a user involved in the transaction has previously accepted; identify, from the selected subset of electronic documents, a current version of an electronic document that has not been accepted by the user; determine whether acceptance of the current version is not required responsive to the user having accepted a prior version of the electronic document; responsive to determining that acceptance of the current version is not required and that the user has accepted the prior version, remove the current version of the electronic document from the selected subset of electronic documents; and output informational data pertaining to the selected subset of electronic documents for presenting the selected subset of electronic documents to the user involved in the transaction for acceptance as part of the transaction. | 13. A computer system for determining a set of legal documents to present to a user for acceptance as part of a transaction, the system comprising: a computer processor; and a non-transitory computer-readable storage medium storing computer program module configured to execute on the computer processor, the computer program modules comprising: a communications module configured to receive informational data describing a transaction; a documents module configured to identify a set of hierarchical electronic documents pertinent to the transaction based at least in part on the received informational data, the set including a root electronic document and one or more dependency electronic documents of the root electronic document, the root electronic document specifying a transaction identifier of the transaction and metadata identifying the one or more dependency electronic documents; a verification module configured to: select a subset of electronic documents from the set of hierarchical electronic documents based at least in part on data describing electronic documents that a user involved in the transaction has previously accepted; identify, from the selected subset of electronic documents, a current version of an electronic document that has not been accepted by the user; determine whether acceptance of the current version is not required responsive to the user having accepted a prior version of the electronic document; responsive to determining that acceptance of the current version is not required and that the user has accepted the prior version, remove the current version of the electronic document from the selected subset of electronic documents; and output informational data pertaining to the selected subset of electronic documents for presenting the selected subset of electronic documents to the user involved in the transaction for acceptance as part of the transaction. 18. The computer system of claim 13 , wherein the verification module is further configured to: remove an electronic document from the set of hierarchical electronic documents, responsive to the document in the set of hierarchical electronic documents being outside of a validity period where the document is valid. | 0.5 |
7,548,895 | 1 | 7 | 1. A computer-implemented system that responds to human communications, comprising: a recognition component that dynamically monitors human communications for an apparent intent related to a task discussed by a user during a communication session with a human second party; a task component that receives, at least in part, an apparent intent from the recognition component and associates it with a task to form a candidate task for prompting a user; and a computer readable storage medium comprising data structures and sets of codes for causing a computer to execute the recognition and task components. | 1. A computer-implemented system that responds to human communications, comprising: a recognition component that dynamically monitors human communications for an apparent intent related to a task discussed by a user during a communication session with a human second party; a task component that receives, at least in part, an apparent intent from the recognition component and associates it with a task to form a candidate task for prompting a user; and a computer readable storage medium comprising data structures and sets of codes for causing a computer to execute the recognition and task components. 7. The computer-implemented system of claim 1 further comprising: an action manager component that receives a candidate task directly or indirectly from the task component and prompts a user about the candidate task. | 0.648208 |
8,090,724 | 1 | 12 | 1. A method comprising: receiving an ordered collection of text-based terms; analyzing groupings of consecutive text-based terms in the ordered collection to identify occurrences of different combinations of consecutive text-based terms in the ordered collection; and maintaining frequency information representing the occurrences of the different combinations of consecutive text-based terms in the collection. | 1. A method comprising: receiving an ordered collection of text-based terms; analyzing groupings of consecutive text-based terms in the ordered collection to identify occurrences of different combinations of consecutive text-based terms in the ordered collection; and maintaining frequency information representing the occurrences of the different combinations of consecutive text-based terms in the collection. 12. The method of claim 1 , wherein analyzing groupings of consecutive text-based terms in the ordered collection comprises: generating a hierarchical tree of the text-based terms in the collection, the hierarchical tree including a parent level and a child level, the parent level including a parent node representing a first unique text-based term in the ordered collection, the child level including at least one child node representing a second unique text-based term in the ordered collection. document. | 0.74676 |
9,535,945 | 1 | 16 | 1. A system comprising: network communications circuitry, configured to: receive a search query from a client device, over a network; communicate an entity search result to the client device over the network; search engine circuitry communicatively coupled to the network communications circuitry, the search engine circuitry comprising a processor, the processor configured to: execute the search query on an entity search database, wherein the entity search database comprises a plurality of entity circuitries, wherein individual ones of the entity circuitries comprises a single root object for a single person entity, a single place entity, or a single thing entity that is different from other individual ones of the entity circuitries; identify an entity indicator in the search query, according to the execution of the search query on the entity search database; identify the entity search result, according to the entity indicator; identify an additional query part besides the entity indicator in the search query, according to the execution of the search query on the entity search database; execute a non-entity query using the additional query part on a non-entity search database with respect to the entity search result, wherein the non-entity search database comprises multiple root objects for a single person entity, a single place entity, or a single thing entity; identify one or more non-entity search results, according to the execution of the non-entity query; alter a display of the entity search result to include the one or more non-entity search results; and emphasize the one or more non-entity search results in the entity search result. | 1. A system comprising: network communications circuitry, configured to: receive a search query from a client device, over a network; communicate an entity search result to the client device over the network; search engine circuitry communicatively coupled to the network communications circuitry, the search engine circuitry comprising a processor, the processor configured to: execute the search query on an entity search database, wherein the entity search database comprises a plurality of entity circuitries, wherein individual ones of the entity circuitries comprises a single root object for a single person entity, a single place entity, or a single thing entity that is different from other individual ones of the entity circuitries; identify an entity indicator in the search query, according to the execution of the search query on the entity search database; identify the entity search result, according to the entity indicator; identify an additional query part besides the entity indicator in the search query, according to the execution of the search query on the entity search database; execute a non-entity query using the additional query part on a non-entity search database with respect to the entity search result, wherein the non-entity search database comprises multiple root objects for a single person entity, a single place entity, or a single thing entity; identify one or more non-entity search results, according to the execution of the non-entity query; alter a display of the entity search result to include the one or more non-entity search results; and emphasize the one or more non-entity search results in the entity search result. 16. The system of claim 1 , wherein the processor is configured to reduce sizes of at least a majority of visual objects in a first GUI to appear after a user selects the entity search result on the client device, the at least a majority of visual objects excluding a visual representation of the one or more additional search results and a background object of the first GUI. | 0.541463 |
9,519,871 | 8 | 12 | 8. A computer-implemented method of contextual text adaptation, the method performed by one or more hardware processors, comprising: receiving a corpus of documents in context of a target user; receiving a dictionary of words; receiving a dictionary of synonyms; generating a topic model algorithm based on the corpus of documents and the dictionary of words by machine learning, the topic model algorithm comprising a first function that predicts probability distribution of a plurality of topics in a given document, and a second function that predicts probability of a given word occurring in a document associated with a given topic; and storing the first function and the second function of the topic model algorithm in a storage device, receiving an input document; determining input document topics associated with the input document and a normalized weight associated with each of the input document topics by executing the first function; determining an aggregate probability indicating relevance of an input document word to the input document topics based on executing the second function; determining a synonym of the input document word based on the dictionary of synonyms; determining an aggregate probability for the synonym based on executing the second function; comparing the aggregate probability for the synonym and the aggregate probability for the input document word; and responsive to determining that the aggregate probability for the synonym is greater than the aggregate probability for the input document word, replacing the input document word with the synonym; and generating an output document comprising content of the input document with replaced word. | 8. A computer-implemented method of contextual text adaptation, the method performed by one or more hardware processors, comprising: receiving a corpus of documents in context of a target user; receiving a dictionary of words; receiving a dictionary of synonyms; generating a topic model algorithm based on the corpus of documents and the dictionary of words by machine learning, the topic model algorithm comprising a first function that predicts probability distribution of a plurality of topics in a given document, and a second function that predicts probability of a given word occurring in a document associated with a given topic; and storing the first function and the second function of the topic model algorithm in a storage device, receiving an input document; determining input document topics associated with the input document and a normalized weight associated with each of the input document topics by executing the first function; determining an aggregate probability indicating relevance of an input document word to the input document topics based on executing the second function; determining a synonym of the input document word based on the dictionary of synonyms; determining an aggregate probability for the synonym based on executing the second function; comparing the aggregate probability for the synonym and the aggregate probability for the input document word; and responsive to determining that the aggregate probability for the synonym is greater than the aggregate probability for the input document word, replacing the input document word with the synonym; and generating an output document comprising content of the input document with replaced word. 12. The method of claim 8 , wherein the corpus of documents are received over a communication network from a social media server. | 0.895462 |
9,196,248 | 1 | 3 | 1. A method for providing voice interaction in a vehicle, the method comprising the acts of: receiving, by a voice interface server, a voice-based query from a user in the vehicle; determining, by the voice interface server, an emotional state for the user based on a detected valence and arousal level associated with the voice-based query; deriving, by the voice interface server, a text-based query from the voice-based query; searching, by the voice interface server using the text-based query, a help database for at least one response to the voice-based query; and providing, by a voice interface server, the at least one response to the user in the form of voice-based assistance in accordance with the emotional state of the user. | 1. A method for providing voice interaction in a vehicle, the method comprising the acts of: receiving, by a voice interface server, a voice-based query from a user in the vehicle; determining, by the voice interface server, an emotional state for the user based on a detected valence and arousal level associated with the voice-based query; deriving, by the voice interface server, a text-based query from the voice-based query; searching, by the voice interface server using the text-based query, a help database for at least one response to the voice-based query; and providing, by a voice interface server, the at least one response to the user in the form of voice-based assistance in accordance with the emotional state of the user. 3. The method of claim 1 , wherein the determined emotion state is selected from a predetermined emotional taxonomy. | 0.839779 |
9,971,976 | 10 | 12 | 10. A computer program product comprising: a non-transitory machine readable storage device; and computer code stored on the non-transitory machine readable storage device, with the computer code including instructions for causing a set of one or more hardware processors to perform operations including the following: receiving a first set of input parameters about a first aspect of the candidates in a set of candidates; applying multiple scoring methods to the first set of input parameters to compute, for each scoring method, a score for the first aspect of each candidate; evaluating an agreement between or among the multiple scoring methods by comparing the computed scores of the multiple scoring methods; responsive to the evaluated agreement not meeting or exceeding a threshold level, (i) updating the first set of input parameters by dropping one or more parameters from the first set of input parameters, and (ii) repeating application of the multiple scoring methods with the updated first set of input parameters until the agreement meets the threshold level; and selecting a subset of one or more candidates from the set of candidates by applying one or more selection criteria to a set of the computed scores corresponding to the agreement meeting the threshold for the first aspect of each candidate; wherein: each input parameter in the first set of input parameters is associated with zero or more values for each candidate. | 10. A computer program product comprising: a non-transitory machine readable storage device; and computer code stored on the non-transitory machine readable storage device, with the computer code including instructions for causing a set of one or more hardware processors to perform operations including the following: receiving a first set of input parameters about a first aspect of the candidates in a set of candidates; applying multiple scoring methods to the first set of input parameters to compute, for each scoring method, a score for the first aspect of each candidate; evaluating an agreement between or among the multiple scoring methods by comparing the computed scores of the multiple scoring methods; responsive to the evaluated agreement not meeting or exceeding a threshold level, (i) updating the first set of input parameters by dropping one or more parameters from the first set of input parameters, and (ii) repeating application of the multiple scoring methods with the updated first set of input parameters until the agreement meets the threshold level; and selecting a subset of one or more candidates from the set of candidates by applying one or more selection criteria to a set of the computed scores corresponding to the agreement meeting the threshold for the first aspect of each candidate; wherein: each input parameter in the first set of input parameters is associated with zero or more values for each candidate. 12. The product of claim 10 , further comprising: computing a score for a second aspect of each candidate using a second set of input parameters; wherein: each input parameter in the second set of input parameters is associated with zero or more values for each candidate; at least one input parameter in either the first set of input parameters or the second set of input parameters is not common to both sets of input parameters; and the selection of the subset of candidates includes simultaneous evaluation of at least one first aspect score and one second aspect score. | 0.5 |
10,073,956 | 10 | 11 | 10. The computer program product of claim 7 , wherein the application is further configured to add a CMIS item object type. | 10. The computer program product of claim 7 , wherein the application is further configured to add a CMIS item object type. 11. The computer program product of claim 10 , wherein the secondary type object type and the CMIS item object type for the application are primary object types such that CMIS secondary types are attachable to the secondary type object type and the CMIS item object type for the application. | 0.5 |
8,543,592 | 10 | 12 | 10. The computerized method of claim 7 , wherein determining, utilizing the second computing device, that the input search query is a task-oriented search query comprises determining that the input search query is a task-oriented search query utilizing at least one query log comprising at least one of aggregate past user session data and data associated with the first user and the first search session. | 10. The computerized method of claim 7 , wherein determining, utilizing the second computing device, that the input search query is a task-oriented search query comprises determining that the input search query is a task-oriented search query utilizing at least one query log comprising at least one of aggregate past user session data and data associated with the first user and the first search session. 12. The computerized method of claim 10 , wherein determining, utilizing the second computing device, that the input search query is a task-oriented search query comprises determining that the input search query is a categorical search query utilizing the at least one query log. | 0.501786 |
9,852,233 | 1 | 7 | 1. A computer-implemented method comprising: accessing a plurality of social activity signals associated with a user and indicative of actions that are performed by the user and viewable by other users; receiving, from the user, user-entered text in a search field for a search engine; determining, by a machine having a memory and at least one processor, predicted queries based on the user-entered text and the plurality of social activity signals, each one of the predicted queries comprising predicted text and at least a portion of the user-entered text, the predicted text being absent from the user-entered text, the determining comprising: determining potential predicted queries based on the user-entered text; and assigning a corresponding predicted query value to each one of the potential predicted queries based on a determination for each potential predicted query of whether the potential predicted query corresponds to one of the social activity signals indicative of an action performed by the user that is viewable by other users, the assigning including: for each potential predicted query determined to correspond to one of the plurality of social activity signals indicative of an action performed by the user that is viewable by other users, determining a corresponding social activity type of the one of the plurality of social activity signals indicative of an action performed by the user that is viewable by other users; and for each potential predicted query determined to correspond to the one of the plurality of social activity signals, calculating the corresponding predicted query value based on a corresponding weight of the corresponding social activity type; and causing the predicted queries to be displayed, to the user, in an autocomplete user interface element of the search field. | 1. A computer-implemented method comprising: accessing a plurality of social activity signals associated with a user and indicative of actions that are performed by the user and viewable by other users; receiving, from the user, user-entered text in a search field for a search engine; determining, by a machine having a memory and at least one processor, predicted queries based on the user-entered text and the plurality of social activity signals, each one of the predicted queries comprising predicted text and at least a portion of the user-entered text, the predicted text being absent from the user-entered text, the determining comprising: determining potential predicted queries based on the user-entered text; and assigning a corresponding predicted query value to each one of the potential predicted queries based on a determination for each potential predicted query of whether the potential predicted query corresponds to one of the social activity signals indicative of an action performed by the user that is viewable by other users, the assigning including: for each potential predicted query determined to correspond to one of the plurality of social activity signals indicative of an action performed by the user that is viewable by other users, determining a corresponding social activity type of the one of the plurality of social activity signals indicative of an action performed by the user that is viewable by other users; and for each potential predicted query determined to correspond to the one of the plurality of social activity signals, calculating the corresponding predicted query value based on a corresponding weight of the corresponding social activity type; and causing the predicted queries to be displayed, to the user, in an autocomplete user interface element of the search field. 7. The computer-implemented method of claim 1 , wherein accessing the plurality of social activity signals comprises receiving the plurality of social activity signals from at least one social networking service. | 0.59387 |
8,705,705 | 6 | 7 | 6. The method of claim 1 , further comprising: after receiving said voice memo, prompting said recipient to indicate whether to continue with the rendering of said email message as speech. | 6. The method of claim 1 , further comprising: after receiving said voice memo, prompting said recipient to indicate whether to continue with the rendering of said email message as speech. 7. The method of claim 6 , further comprising: after prompting said recipient to indicate whether to continue with the rendering of said email message as speech, receiving an indication from said recipient to continue with the rendering of said email message as speech; and continuing with the rendering of said email as speech. | 0.5 |
8,527,279 | 1 | 4 | 1. A computer-implemented method comprising: accessing, by a computer system, a search history that identifies one or more search queries that were previously submitted to one or more search services by a mobile computing device that is associated with a user; accessing information that identifies one or more web pages that were previously displayed on the mobile computing device; identifying, based at least in part on i) the search history of the mobile computing device, ii) search results associated with the one or more search queries in the search history, and iii) content included in the one or more web pages that were previously displayed on the mobile computing device, a geographic location to which future voice input from the user is likely to relate; selecting, by the computer system and based at least in part on the identified geographic location, a first grammar from among a plurality of grammars, wherein the first grammar includes a vocabulary that is relevant to the identified geographic location; and outputting, by the computer system, information that identifies the first grammar, wherein the outputted information causes a grammar used to analyze voice input from the mobile computing device to be changed to the first grammar. | 1. A computer-implemented method comprising: accessing, by a computer system, a search history that identifies one or more search queries that were previously submitted to one or more search services by a mobile computing device that is associated with a user; accessing information that identifies one or more web pages that were previously displayed on the mobile computing device; identifying, based at least in part on i) the search history of the mobile computing device, ii) search results associated with the one or more search queries in the search history, and iii) content included in the one or more web pages that were previously displayed on the mobile computing device, a geographic location to which future voice input from the user is likely to relate; selecting, by the computer system and based at least in part on the identified geographic location, a first grammar from among a plurality of grammars, wherein the first grammar includes a vocabulary that is relevant to the identified geographic location; and outputting, by the computer system, information that identifies the first grammar, wherein the outputted information causes a grammar used to analyze voice input from the mobile computing device to be changed to the first grammar. 4. The computer-implemented method of claim 1 , wherein the geographic location is identified independent of a current geographic location of the mobile computing device. | 0.880282 |
9,058,588 | 1 | 6 | 1. A computer-implemented system for managing a context-sensitive sidebar window, comprising: contextual information relevant to an electronic document displayed on an electronic desktop; a presentation module to present a portion of the contextual information in a sidebar window; a window management module to manage a display of the context-sensitive sidebar window within the electronic desktop adjacent to the electronic document by determining a location of one or more icons on the electronic desktop, assigning an importance value to each of the one or more icons, assigning an importance value to each pixel of the icons in the electronic desktop, adjusting at least one of a vertical and horizontal positioning of the context-sensitive sidebar within the electronic desktop based on the importance of the icons and the importance of the icon pixels within the electronic desktop such that coverage of the pixels of the icons, associated with a higher importance, by the context-sensitive sidebar is minimized, automatically opening the context-sensitive sidebar window when the electronic document is opened, and automatically closing the context-sensitive sidebar window when the document is closed; and a processor to execute the modules. | 1. A computer-implemented system for managing a context-sensitive sidebar window, comprising: contextual information relevant to an electronic document displayed on an electronic desktop; a presentation module to present a portion of the contextual information in a sidebar window; a window management module to manage a display of the context-sensitive sidebar window within the electronic desktop adjacent to the electronic document by determining a location of one or more icons on the electronic desktop, assigning an importance value to each of the one or more icons, assigning an importance value to each pixel of the icons in the electronic desktop, adjusting at least one of a vertical and horizontal positioning of the context-sensitive sidebar within the electronic desktop based on the importance of the icons and the importance of the icon pixels within the electronic desktop such that coverage of the pixels of the icons, associated with a higher importance, by the context-sensitive sidebar is minimized, automatically opening the context-sensitive sidebar window when the electronic document is opened, and automatically closing the context-sensitive sidebar window when the document is closed; and a processor to execute the modules. 6. A system according to claim 1 , wherein the management module further manages the context-sensitive sidebar window based on an active window for the electronic document by at least one of moving the context-sensitive sidebar window with the active window, shrinking the context-sensitive sidebar window with the active window, and resizing the active window based on a size of the context-sensitive sidebar window. | 0.5 |
8,380,753 | 12 | 14 | 12. A method for analyzing a document comprising a plurality of primitive elements, the method comprising: identifying aligned gaps in a plurality of text lines in a column of the document; determining which of the aligned gaps are indicative of spacing between a list item label and a list item in order to identify text lines that linclude the aligned gaps as list items; identifying hierarchical levels for the list items based on alignment, spacing, and content of the list items; and defining a hierarchically-organized set of lists for the column in which list items with the same hierarchical level are in the same list. | 12. A method for analyzing a document comprising a plurality of primitive elements, the method comprising: identifying aligned gaps in a plurality of text lines in a column of the document; determining which of the aligned gaps are indicative of spacing between a list item label and a list item in order to identify text lines that linclude the aligned gaps as list items; identifying hierarchical levels for the list items based on alignment, spacing, and content of the list items; and defining a hierarchically-organized set of lists for the column in which list items with the same hierarchical level are in the same list. 14. The method of claim 12 , determining which of the aligned gaps are indicative of spacing comprises identifying gaps that have a single short word to the left and left-aligned text to the right. | 0.751263 |
8,249,858 | 17 | 21 | 17. A computer program product for multilingual administration of enterprise data, the computer program product comprising: non-transitory machine-readable medium having computer usable program code embodied therewith, the computer usable program code comprising a computer usable program code configured to: retrieve enterprise data; extract text from the enterprise data for rendering from a digital media file, the extracted text being in a source language; select a predetermined default target language from among a plurality of target languages based on a data type for the enterprise data; identify that the source language is not the predetermined default target language for rendering the enterprise data; translate the extracted text in the source language to translated text in the predetermined default target language; convert the translated text to synthesized speech in the predetermined default target language; and record the synthesized speech in the predetermined default target language in a digital media file. | 17. A computer program product for multilingual administration of enterprise data, the computer program product comprising: non-transitory machine-readable medium having computer usable program code embodied therewith, the computer usable program code comprising a computer usable program code configured to: retrieve enterprise data; extract text from the enterprise data for rendering from a digital media file, the extracted text being in a source language; select a predetermined default target language from among a plurality of target languages based on a data type for the enterprise data; identify that the source language is not the predetermined default target language for rendering the enterprise data; translate the extracted text in the source language to translated text in the predetermined default target language; convert the translated text to synthesized speech in the predetermined default target language; and record the synthesized speech in the predetermined default target language in a digital media file. 21. The computer program product of claim 17 , wherein the computer usable program code comprises computer usable program code configured to receive from the user a selection of a predetermined default target language including computer program instructions for receiving through a GUI selection screen a selection of an identification of one of a plurality of available predetermined default target languages. | 0.5 |
8,126,718 | 7 | 8 | 7. The method of claim 3 wherein said calculating comprises breaking said portion of said username into letter pairs or letter triplets and determining a frequency of occurrence of said letter pairs or letter triplets in a spoken language. | 7. The method of claim 3 wherein said calculating comprises breaking said portion of said username into letter pairs or letter triplets and determining a frequency of occurrence of said letter pairs or letter triplets in a spoken language. 8. The method of claim 7 wherein said calculating calculates a high likelihood of pronounceability when said frequency of occurrence of said letter pairs or letter triplets in said spoken language exceeds a threshold. | 0.5 |
8,135,712 | 12 | 14 | 12. The software of claim 11 , wherein the plurality of different previously-submitted search queries include a plurality of previously-searched questions with each previously-searched question including a word indicating a question. | 12. The software of claim 11 , wherein the plurality of different previously-submitted search queries include a plurality of previously-searched questions with each previously-searched question including a word indicating a question. 14. The software of claim 12 , wherein the word indicating a question includes one or more words indicating an interrogative sentence. | 0.5 |
9,934,465 | 13 | 15 | 13. Apparatus comprising: at least one processor; and at least one storage medium storing processor-executable instructions that, when executed by the at least one processor, perform a method for synthesizing a complex knowledge representation, the method comprising: receiving a context from a data consumer; identifying, in accordance with the context, one or more elemental components, including a first concept, in an elemental knowledge representation; and generating a complex knowledge representation by applying one or more rules to the one or more elemental components, wherein generating the complex knowledge representation comprises synthesizing a complex concept that was not present in the elemental knowledge representation, and including the synthesized complex concept in the complex knowledge representation, wherein synthesizing the complex concept comprises joining the first concept with an elemental concept that is not hierarchically related to the first concept, to form the synthesized complex concept, and wherein generating the complex knowledge representation comprises including in the complex knowledge representation an intrinsic relationship between the first concept and the complex concept. | 13. Apparatus comprising: at least one processor; and at least one storage medium storing processor-executable instructions that, when executed by the at least one processor, perform a method for synthesizing a complex knowledge representation, the method comprising: receiving a context from a data consumer; identifying, in accordance with the context, one or more elemental components, including a first concept, in an elemental knowledge representation; and generating a complex knowledge representation by applying one or more rules to the one or more elemental components, wherein generating the complex knowledge representation comprises synthesizing a complex concept that was not present in the elemental knowledge representation, and including the synthesized complex concept in the complex knowledge representation, wherein synthesizing the complex concept comprises joining the first concept with an elemental concept that is not hierarchically related to the first concept, to form the synthesized complex concept, and wherein generating the complex knowledge representation comprises including in the complex knowledge representation an intrinsic relationship between the first concept and the complex concept. 15. The apparatus of claim 13 , wherein the first concept and the elemental concept joined with the first concept to synthesize the complex concept form a concept definition for the complex concept. | 0.676471 |
7,644,091 | 1 | 3 | 1. A computer-implemented method for handling Health Level Seven (HL7) electronic medical data, comprising the steps of: receiving HL7 electronic medical data; wherein the HL7 electronic medical data includes data segments, wherein a segment has a three character name and a pre-defined format of specific fields; creating an electronic indexing medical record based upon the received HL7 electronic medical data; creating a medically-related document containing data from the received HL7 electronic medical data; providing the indexing medical record and the medically-related document to a document management system; wherein the document management system is configured to store the medically-related document and to use the provided indexing medical record in order to index the medically-related document. | 1. A computer-implemented method for handling Health Level Seven (HL7) electronic medical data, comprising the steps of: receiving HL7 electronic medical data; wherein the HL7 electronic medical data includes data segments, wherein a segment has a three character name and a pre-defined format of specific fields; creating an electronic indexing medical record based upon the received HL7 electronic medical data; creating a medically-related document containing data from the received HL7 electronic medical data; providing the indexing medical record and the medically-related document to a document management system; wherein the document management system is configured to store the medically-related document and to use the provided indexing medical record in order to index the medically-related document. 3. The method of claim 1 , wherein HL7 is directed to level seven of the ISO (International Standards Organization) communications model. | 0.708511 |
9,223,758 | 1 | 15 | 1. A computer implemented method, comprising: receiving a request to load a web page; determining a language encoding data setting for the web page based on the language encoding data setting provided by a language encoding database, wherein the language encoding data setting received from the language encoding database is a language encoding data setting most frequently selected by viewers of the web page, wherein the language encoding database maintains a count of a number of correct times the language encoding data setting has been used for the webpage and provides the language encoding data setting if the count exceeds a first threshold; applying the language encoding data setting provided by the language encoding database to the web page; and rendering the web page based on the language encoding data setting applied to the web page. | 1. A computer implemented method, comprising: receiving a request to load a web page; determining a language encoding data setting for the web page based on the language encoding data setting provided by a language encoding database, wherein the language encoding data setting received from the language encoding database is a language encoding data setting most frequently selected by viewers of the web page, wherein the language encoding database maintains a count of a number of correct times the language encoding data setting has been used for the webpage and provides the language encoding data setting if the count exceeds a first threshold; applying the language encoding data setting provided by the language encoding database to the web page; and rendering the web page based on the language encoding data setting applied to the web page. 15. The method of claim 1 , wherein if the count does not exceed the first threshold, further comprising providing a user-selected language encoding data setting. | 0.823913 |
8,484,193 | 6 | 20 | 6. The method of claim 1 wherein an initial transition matrix is calculated according to the following:
P (N) =( D (N) ) −1 AD (N−1) where P (N) represents the initial transition matrix based on a look-ahead distance of N−1, A represents an adjacency matrix indicating links between documents, and D (N) represents a diagonal matrix with diagonal elements set to d (N) , where d (N) is calculated according to the following:
d (N) =Ad (N−1) where d (0) =(1, 1, . . . , 1) n T . | 6. The method of claim 1 wherein an initial transition matrix is calculated according to the following:
P (N) =( D (N) ) −1 AD (N−1) where P (N) represents the initial transition matrix based on a look-ahead distance of N−1, A represents an adjacency matrix indicating links between documents, and D (N) represents a diagonal matrix with diagonal elements set to d (N) , where d (N) is calculated according to the following:
d (N) =Ad (N−1) where d (0) =(1, 1, . . . , 1) n T . 20. The method of claim 6 including converting the initial transition matrix into a transition probability matrix by normalizing elements of each row by the sum of the elements in the row. | 0.5 |
8,195,655 | 4 | 5 | 4. The system of claim 1 , wherein the document-based search component is configured to return the individual document identifiers corresponding to the individual matching documents according to rank. | 4. The system of claim 1 , wherein the document-based search component is configured to return the individual document identifiers corresponding to the individual matching documents according to rank. 5. The system of claim 4 , wherein the retrieval component is configured to retrieve a number of the co-occurring related named entities in the returned individual matching documents. | 0.5 |
8,869,072 | 1 | 2 | 1. A method for providing gesture input to a plurality of applications, comprising: receiving data indicative of a user motion or pose, the data being captured by a camera; determining a result of processing the data, the result comprising a three-dimensional model of at least part of the user; sending the result to a first gesture filter of a first application of the plurality of applications, the first application being configured to process the result with the first gesture filter to determine a first output indicative of whether the result is indicative of the user performing a gesture represented by the first gesture filter; and sending the result to a second gesture filter of a second application of the plurality of applications, the second application being configured to process the result with the second gesture filter to determine a second output indicative of whether the result is indicative of the user performing a gesture represented by the second gesture filter. | 1. A method for providing gesture input to a plurality of applications, comprising: receiving data indicative of a user motion or pose, the data being captured by a camera; determining a result of processing the data, the result comprising a three-dimensional model of at least part of the user; sending the result to a first gesture filter of a first application of the plurality of applications, the first application being configured to process the result with the first gesture filter to determine a first output indicative of whether the result is indicative of the user performing a gesture represented by the first gesture filter; and sending the result to a second gesture filter of a second application of the plurality of applications, the second application being configured to process the result with the second gesture filter to determine a second output indicative of whether the result is indicative of the user performing a gesture represented by the second gesture filter. 2. The method of claim 1 , wherein determining the result of processing the data comprises: determining at least a partial skeletal model of the user from the data. | 0.915638 |
9,286,886 | 2 | 4 | 2. The method of claim 1 , further comprising selecting a second corresponding text fragment for a second portion of the input text, wherein selecting the second corresponding text fragment comprises: identifying a first marker included in the second portion of the input text; identifying a class of the first marker; and selecting the second corresponding text fragment based at least in part on the second corresponding text fragment comprising a second marker of the same class as the first marker. | 2. The method of claim 1 , further comprising selecting a second corresponding text fragment for a second portion of the input text, wherein selecting the second corresponding text fragment comprises: identifying a first marker included in the second portion of the input text; identifying a class of the first marker; and selecting the second corresponding text fragment based at least in part on the second corresponding text fragment comprising a second marker of the same class as the first marker. 4. The method of claim 2 , wherein determining the alignment comprises aligning the second marker with the first marker. | 0.707317 |
9,348,872 | 2 | 3 | 2. The method of claim 1 , wherein the first magnitude is determined based on a stylistic attribute associated with the first plurality of text items. | 2. The method of claim 1 , wherein the first magnitude is determined based on a stylistic attribute associated with the first plurality of text items. 3. The method of claim 2 , wherein the stylistic attribute includes at least one of font style, line height, font size, and associated hyperlink. | 0.620419 |
8,645,390 | 23 | 24 | 23. The system of claim 14 , wherein: the set of search results has a preliminary search result order; and ordering the portion of the search results in accordance with the identified predicted performance function includes: comparing predicted click through rates of a plurality search results in multiple different search result orders; selecting a respective search result order that increases a predicted click through rate of a plurality of the results over the preliminary search result order; and ordering the portion of the search results in the respective search result order. | 23. The system of claim 14 , wherein: the set of search results has a preliminary search result order; and ordering the portion of the search results in accordance with the identified predicted performance function includes: comparing predicted click through rates of a plurality search results in multiple different search result orders; selecting a respective search result order that increases a predicted click through rate of a plurality of the results over the preliminary search result order; and ordering the portion of the search results in the respective search result order. 24. The system of claim 23 , wherein: the preliminary sort order is a user-independent sort order based on relevance of the search results to the search query; and the respective sort order is a user-dependent sort order based on a user profile of the user. | 0.5 |
8,239,334 | 9 | 12 | 9. A memory having computer-executable instructions embodied thereon, the computer-executable instructions to configure a computer to perform acts comprising: subspace learning for ranking; and returning a search based at least in part on the subspace learning for ranking. | 9. A memory having computer-executable instructions embodied thereon, the computer-executable instructions to configure a computer to perform acts comprising: subspace learning for ranking; and returning a search based at least in part on the subspace learning for ranking. 12. The memory as recited in claim 9 wherein the acts further comprise: obtaining a training query and documents to be processed as ranked query-document pairs; indexing the training query and documents as training data in a vector space model having a dimension; producing a training database via the indexing; applying a learning latent semantic space for ranking algorithm; receiving ordinal information of indexed documents; integrating the ordinal information of the indexed documents into ranking in a learned subspace for ranking; projecting data from the learned subspace for ranking to a document database; and reporting the learned subspace including unranked documents. | 0.5 |
6,012,027 | 4 | 5 | 4. The method of claim 1, wherein step (c) further includes the steps of: (c1) determining a duration of the second utterance; (c2) when the duration is greater than a maximum duration, disregarding the second utterance. | 4. The method of claim 1, wherein step (c) further includes the steps of: (c1) determining a duration of the second utterance; (c2) when the duration is greater than a maximum duration, disregarding the second utterance. 5. The method of claim 4, wherein step (c1) further includes the steps of: (i) setting an amplitude threshold; (ii) determining a start time when an input signal exceeds the amplitude threshold; (iii) determining an end time, after the start time, when the input signal is less than the amplitude threshold; (iv) calculating the duration as a difference between the end time and the start time. | 0.5 |
9,904,521 | 12 | 20 | 12. An apparatus for enforcing usage of a canonical model, the apparatus comprising at least one processor and at least one memory including program code, the at least one memory and the program code configured to, with the processor, cause the apparatus to at least: receive machine-automatable artifacts from a canonical model artifact repository, the machine-automatable artifacts expressing the canonical model using a set of metadata constraints and a set of transformation rules; convert the received machine-automatable artifacts into language-specific bindings; and program an application using the language-specific bindings to automatically enforce conformity of the application to the canonical model and to enable the application to communicate with one or more other applications according to the canonical model even in an instance in which the application obtains first inbound data that is in non-canonical form from at least one of the other applications in response to utilizing one or more transformation rules of the set of transformation rules expressed by the machine-automatable artifacts to canonicalize the first inbound data, which was initially obtained by the at least one application in non-canonical form. | 12. An apparatus for enforcing usage of a canonical model, the apparatus comprising at least one processor and at least one memory including program code, the at least one memory and the program code configured to, with the processor, cause the apparatus to at least: receive machine-automatable artifacts from a canonical model artifact repository, the machine-automatable artifacts expressing the canonical model using a set of metadata constraints and a set of transformation rules; convert the received machine-automatable artifacts into language-specific bindings; and program an application using the language-specific bindings to automatically enforce conformity of the application to the canonical model and to enable the application to communicate with one or more other applications according to the canonical model even in an instance in which the application obtains first inbound data that is in non-canonical form from at least one of the other applications in response to utilizing one or more transformation rules of the set of transformation rules expressed by the machine-automatable artifacts to canonicalize the first inbound data, which was initially obtained by the at least one application in non-canonical form. 20. The apparatus of claim 12 , wherein the machine-automatable artifacts include a set of extensible markup language schema definitions (XSDs) that express the set of metadata constraints and a set of canonical extensible stylesheet language transformations (XSLTs) that express the set of transformation rules. | 0.671579 |
10,038,786 | 3 | 5 | 3. The method of claim 1 , further comprising: displaying in a user interface a visual representation of the one or more mood metrics determined in each of the two or more chat stages for tracking the changes in the one or mood metrics. | 3. The method of claim 1 , further comprising: displaying in a user interface a visual representation of the one or more mood metrics determined in each of the two or more chat stages for tracking the changes in the one or mood metrics. 5. The method of claim 3 , wherein the visual representation of the one or mood metrics comprises one or more color coded representations in each of the two or more chat stages. | 0.613537 |
8,200,640 | 15 | 19 | 15. A computer-implemented method of deduplicating data records, the method, performed by a processor and memory of one or more computers, comprising: executing an implementation of a deduplication language, the deduplication language not comprising a Structured Query Language, the implementation executing arbitrary strings in the deduplication language using a clustering algorithm, the implementation: accessing stored data records in one or more relational tables, the data records representing respective real world entities, wherein some of the data records comprise duplicates that mutually represent same respective real world entities; receiving strings, in electronic form, constructed by one or more users, each string forming a valid program of the deduplication language, the strings specifying, in accordance with the deduplication language, entity references that are to be deduplicated and specifying constraints that corresponding data records, when deduplicated, must or should satisfy; executing one of the strings to generate a deduplication of the data records, the deduplication comprising deduplication relations that identify pairs of entity references among the data records that satisfy the constraints of the executed string; and storing in electronic form indicia of the deduplication. | 15. A computer-implemented method of deduplicating data records, the method, performed by a processor and memory of one or more computers, comprising: executing an implementation of a deduplication language, the deduplication language not comprising a Structured Query Language, the implementation executing arbitrary strings in the deduplication language using a clustering algorithm, the implementation: accessing stored data records in one or more relational tables, the data records representing respective real world entities, wherein some of the data records comprise duplicates that mutually represent same respective real world entities; receiving strings, in electronic form, constructed by one or more users, each string forming a valid program of the deduplication language, the strings specifying, in accordance with the deduplication language, entity references that are to be deduplicated and specifying constraints that corresponding data records, when deduplicated, must or should satisfy; executing one of the strings to generate a deduplication of the data records, the deduplication comprising deduplication relations that identify pairs of entity references among the data records that satisfy the constraints of the executed string; and storing in electronic form indicia of the deduplication. 19. A computer-implemented method according to claim 15 , wherein the string is executed by minimizing the number of soft constraints that are violated by deduplicate match clusters. | 0.874136 |
9,971,893 | 1 | 2 | 1. A method, said method comprising: a first computer executing a plurality of text blocks of code derived from a script from a web page in response to a request for the web page from a client computer, said text blocks executed sequentially in a sequential order, wherein the script is a first text block of the plurality of text blocks, the execution of one text block of the plurality of text blocks by the first computer generating a new text block of code; and said first computer determining that the new text block includes malicious code and in response, said first computer preventing transmission of the web page to the client computer. | 1. A method, said method comprising: a first computer executing a plurality of text blocks of code derived from a script from a web page in response to a request for the web page from a client computer, said text blocks executed sequentially in a sequential order, wherein the script is a first text block of the plurality of text blocks, the execution of one text block of the plurality of text blocks by the first computer generating a new text block of code; and said first computer determining that the new text block includes malicious code and in response, said first computer preventing transmission of the web page to the client computer. 2. The method of claim 1 , said method comprising: said first computer copying each text block to an output file in a data storage area of the first computer, wherein the first text block is copied before another text block of the plurality of text blocks is copied. | 0.5 |
9,692,851 | 1 | 8 | 1. A database system implemented using a server system comprising at least one hardware processor, the at least one hardware processor executing instructions to perform: designating a first user as a proxy user of a second user in a social networking system with respect to with respect to an entity in the social networking system, the proxy user having an authorization to publish feed content attributed to the second user to feeds associated with the entity; processing feed content received from a device associated with the proxy user, the feed content to be published in one or more feeds associated with the entity; associating the feed content with the second user; generating data indicating the association of the feed content with the second user; providing the generated data to a display device configured to display a presentation of the one or more feeds in a user interface, the presentation including the feed content and an indication of the association of the feed content with the second user; automatically determining, absent user input and after expiration of a time period specifiable by the second user, that a de-designation condition has been met, the de-designation condition being controllable by the second user; and automatically de-designating, responsive to determining that the de-designation condition has been met, the first user as the proxy user of the second user. | 1. A database system implemented using a server system comprising at least one hardware processor, the at least one hardware processor executing instructions to perform: designating a first user as a proxy user of a second user in a social networking system with respect to with respect to an entity in the social networking system, the proxy user having an authorization to publish feed content attributed to the second user to feeds associated with the entity; processing feed content received from a device associated with the proxy user, the feed content to be published in one or more feeds associated with the entity; associating the feed content with the second user; generating data indicating the association of the feed content with the second user; providing the generated data to a display device configured to display a presentation of the one or more feeds in a user interface, the presentation including the feed content and an indication of the association of the feed content with the second user; automatically determining, absent user input and after expiration of a time period specifiable by the second user, that a de-designation condition has been met, the de-designation condition being controllable by the second user; and automatically de-designating, responsive to determining that the de-designation condition has been met, the first user as the proxy user of the second user. 8. The database system of claim 1 , wherein the presentation conceals the identity of the proxy user. | 0.876225 |
8,487,942 | 1 | 41 | 1. A system for processing an action script for a graphical image for visual display, the system comprising: a network input and output interface to receive data; a first memory to store data; a frame buffer to store pixel data; and a plurality of processors to parse the action script into a plurality of descriptive elements and a corresponding plurality of variable length operand data sets, the plurality of descriptive elements specifying the graphical image in a non-pixel-by-pixel form; to directly convert each descriptive element of the plurality of descriptive elements of the action script into a corresponding operational code of a plurality of operational codes, each corresponding operational code comprising at least one graphical primitive instruction for native execution by at least one processor of the plurality of processors or comprising a memory pointer to an address in the first memory having a sequence of graphical primitive instructions for native execution by at the least one processor of the plurality of processors; to directly convert each variable length operand data set of the corresponding plurality of variable length operand data sets into one or more control words and store the one or more control words in the first memory, each control word comprising operand data and one or more control bits in predetermined fields for the native execution of the one or more graphical primitive instructions by the at least one processor of the plurality of processors; at least one processor of the plurality of processors to directly execute the one or more graphical primitive instructions using the one or more control words to generate pixel data for the graphical image, and to transfer the pixel data to the frame buffer. | 1. A system for processing an action script for a graphical image for visual display, the system comprising: a network input and output interface to receive data; a first memory to store data; a frame buffer to store pixel data; and a plurality of processors to parse the action script into a plurality of descriptive elements and a corresponding plurality of variable length operand data sets, the plurality of descriptive elements specifying the graphical image in a non-pixel-by-pixel form; to directly convert each descriptive element of the plurality of descriptive elements of the action script into a corresponding operational code of a plurality of operational codes, each corresponding operational code comprising at least one graphical primitive instruction for native execution by at least one processor of the plurality of processors or comprising a memory pointer to an address in the first memory having a sequence of graphical primitive instructions for native execution by at the least one processor of the plurality of processors; to directly convert each variable length operand data set of the corresponding plurality of variable length operand data sets into one or more control words and store the one or more control words in the first memory, each control word comprising operand data and one or more control bits in predetermined fields for the native execution of the one or more graphical primitive instructions by the at least one processor of the plurality of processors; at least one processor of the plurality of processors to directly execute the one or more graphical primitive instructions using the one or more control words to generate pixel data for the graphical image, and to transfer the pixel data to the frame buffer. 41. The system of claim 1 , wherein the action script is a data file specifying the graphical image at least partially using non-pixel data and which comprises an ASCII-encoded scripting language or bytecode. | 0.869511 |
9,015,134 | 40 | 41 | 40. The method of claim 27 , wherein relation of said at least one representation of a document to said one of said stored queries is stored in said database. | 40. The method of claim 27 , wherein relation of said at least one representation of a document to said one of said stored queries is stored in said database. 41. The method of claim 40 , wherein information on at least one user who selected said one of said related stored queries is stored in said database in relation to said one of said related stored queries. | 0.594862 |
9,747,897 | 17 | 18 | 17. The computer-implemented method of claim 16 , wherein the text-based transcription is a text-based transcription of the updated phonetic transcription of the additional audio data corresponding to the particular user speaking the one or more terms in the natural language. | 17. The computer-implemented method of claim 16 , wherein the text-based transcription is a text-based transcription of the updated phonetic transcription of the additional audio data corresponding to the particular user speaking the one or more terms in the natural language. 18. The computer-implemented method of claim 17 , further comprising providing the text-based transcription of the updated phonetic transcription of the additional audio data corresponding to the particular user speaking the one or more terms in the natural language to a user interface manager. | 0.514803 |
9,471,567 | 5 | 6 | 5. The method of claim 1 , wherein filtering further includes controlling a decibel level from the detected audio. | 5. The method of claim 1 , wherein filtering further includes controlling a decibel level from the detected audio. 6. The method of claim 5 , wherein controlling further includes removing noise identified in the detected audio. | 0.5 |
8,626,862 | 1 | 17 | 1. A method comprising: accessing, by one or more computers of a first person, information for a graphical user interface that when rendered by the one or more computers displays an identifying characteristic associated with a second person's contact information; detecting, by the one or more computers, the first's person selection of a hotkey combination that specifies that the first user has selected textual information in the graphical user interface; identifying, based on detection of the hotkey combination, that the selected textual information is the identifying characteristic displayed in the graphical user interface; determining, by the one or more computers, a type of the identifying characteristic that is selected in the graphical user interface and that is identified by the selection of the hotkey combination, with the type of the identifying characteristic comprising one or more of a telephone number for the second person, a name of the second person, and an image associated with the second person; determining, based on the identifying characteristic that is selected in the graphical user interface and that is identified by the selection of the hotkey combination and the type of the identifying characteristic that is selected in the graphical user interface and that is identified by the selection of the hotkey combination, contact information for the second person; and launching a communication mode, with the communication mode using the contact information for the second person to establish a communication with the second person. | 1. A method comprising: accessing, by one or more computers of a first person, information for a graphical user interface that when rendered by the one or more computers displays an identifying characteristic associated with a second person's contact information; detecting, by the one or more computers, the first's person selection of a hotkey combination that specifies that the first user has selected textual information in the graphical user interface; identifying, based on detection of the hotkey combination, that the selected textual information is the identifying characteristic displayed in the graphical user interface; determining, by the one or more computers, a type of the identifying characteristic that is selected in the graphical user interface and that is identified by the selection of the hotkey combination, with the type of the identifying characteristic comprising one or more of a telephone number for the second person, a name of the second person, and an image associated with the second person; determining, based on the identifying characteristic that is selected in the graphical user interface and that is identified by the selection of the hotkey combination and the type of the identifying characteristic that is selected in the graphical user interface and that is identified by the selection of the hotkey combination, contact information for the second person; and launching a communication mode, with the communication mode using the contact information for the second person to establish a communication with the second person. 17. The method of claim 1 further comprising enabling the first person to communicate with the second person via an e-mail message. | 0.882616 |
9,569,417 | 2 | 3 | 2. The method of claim 1 , wherein the natural language document is an original document of a corpus of information, and wherein the modified tabular data structure is part of a modified document that replaces the original document in the corpus of information. | 2. The method of claim 1 , wherein the natural language document is an original document of a corpus of information, and wherein the modified tabular data structure is part of a modified document that replaces the original document in the corpus of information. 3. The method of claim 2 , wherein the processing operation is a natural language processing operation that is applied to the modified document. | 0.5 |
9,489,171 | 8 | 9 | 8. The method of claim 1 , wherein the voice command includes a parameterized voice command including a root operation and a parameter that modifies the root operation, and wherein the method further comprises: selecting a personalized value of the parameter based on the user identity; and presenting via the display a voice-command suggestion with the personalized value of the parameter. | 8. The method of claim 1 , wherein the voice command includes a parameterized voice command including a root operation and a parameter that modifies the root operation, and wherein the method further comprises: selecting a personalized value of the parameter based on the user identity; and presenting via the display a voice-command suggestion with the personalized value of the parameter. 9. The method of claim 8 , wherein the personalized value of the parameter is a first personalized value, and wherein the method further comprises: in response to exceeding a duration, selecting a second personalized value of the parameter based on the user identity, the second personalized value differing from the first personalized value; and presenting the parameterized voice-command suggestion with the second personalized value. | 0.5 |
9,348,815 | 8 | 15 | 8. A system, comprising: one or more processors; a memory device coupled to the one or more processors and storing instructions which, when executed by the one or more processors, cause the system to perform functions that include: reading text data corresponding to one or more messages; creating one or more semantic annotations to the text data to generate one or more annotated messages, wherein creating the one or more semantic annotations comprises generating, at least in part by a trained statistical language model, one or more predictive labels as annotations corresponding to language patterns associated with the text data; aggregating the one or more annotated messages and storing information associated with the aggregated one or more annotated messages in a message store; and performing, based on information from the message store and associated with the one or more messages, global analytics functions that include: identifying an annotation error in the created semantic annotations, updating the respective semantic annotation to correct the annotation error, and back-propagating the updated semantic annotation into training data for further language model training, wherein aggregating the one or more annotated messages and storing the information associated with the aggregated one or more annotated messages comprises constructing a global knowledge graph representation corresponding to the aggregated one or more annotated messages, and wherein identifying the annotation error, updating the respective semantic annotation, and back-propagating the updated semantic annotation comprises: (a) identifying the annotation error from the knowledge graph representation, (b) updating the respective semantic annotation in the knowledge graph representation to correct the annotation error, (c) back-propagating the updated semantic annotation into the training data for the further language model training, and (d) performing steps (a)-(c) repeatedly until a predetermined level of accuracy of the annotations has been reached or a predetermined number of iterations have been performed. | 8. A system, comprising: one or more processors; a memory device coupled to the one or more processors and storing instructions which, when executed by the one or more processors, cause the system to perform functions that include: reading text data corresponding to one or more messages; creating one or more semantic annotations to the text data to generate one or more annotated messages, wherein creating the one or more semantic annotations comprises generating, at least in part by a trained statistical language model, one or more predictive labels as annotations corresponding to language patterns associated with the text data; aggregating the one or more annotated messages and storing information associated with the aggregated one or more annotated messages in a message store; and performing, based on information from the message store and associated with the one or more messages, global analytics functions that include: identifying an annotation error in the created semantic annotations, updating the respective semantic annotation to correct the annotation error, and back-propagating the updated semantic annotation into training data for further language model training, wherein aggregating the one or more annotated messages and storing the information associated with the aggregated one or more annotated messages comprises constructing a global knowledge graph representation corresponding to the aggregated one or more annotated messages, and wherein identifying the annotation error, updating the respective semantic annotation, and back-propagating the updated semantic annotation comprises: (a) identifying the annotation error from the knowledge graph representation, (b) updating the respective semantic annotation in the knowledge graph representation to correct the annotation error, (c) back-propagating the updated semantic annotation into the training data for the further language model training, and (d) performing steps (a)-(c) repeatedly until a predetermined level of accuracy of the annotations has been reached or a predetermined number of iterations have been performed. 15. The system of claim 8 , wherein identifying the annotation error comprises identifying a categorization error from a named entity recognition (NER) model. | 0.673554 |
9,020,941 | 11 | 13 | 11. The system of claim 8 , wherein the geocoder generates geographical coordinate information that includes latitude and longitude values. | 11. The system of claim 8 , wherein the geocoder generates geographical coordinate information that includes latitude and longitude values. 13. The system of claim 11 , further comprising: a publicly available user created geocode database, wherein the geocoder selects the geographical coordinate information from the geocode database. | 0.5 |
9,202,460 | 1 | 6 | 1. A device, comprising: a memory to store instructions; and a processor coupled to the memory, wherein responsive to executing the instructions, the processor performs operations comprising: receiving video media content, wherein the video media content comprises images, audio content, and closed captioning of text from the audio content; detecting an occurrence of a textual phrase in the closed captioning of the video media content as a detected occurrence; selecting an audio segment from the audio content of the media content as a selected audio segment, wherein the selected audio segment corresponds to the detected occurrence of the textual phrase in the closed captioning; selecting from a speech recognition library an audio pronunciation associated with the textual phrase, wherein the speech recognition library comprises a group of identified audio segments, wherein the group of identified audio segments comprises a baseline audio pronunciation and collected audio pronunciations of the textual phrase; comparing the selected audio segment with the group of identified audio segments from the speech recognition library; determining if an audio pronunciation of the selected audio segment differs from the baseline audio pronunciation from the speech recognition library; responsive to determining that the audio pronunciation of the selected audio segment differs from the baseline audio pronunciation, generating a phonetic transcription of the audio pronunciation of the selected audio segment; and adding the phonetic transcription and the textual phrase to the group of identified audio segments in the speech recognition library to populate the collected audio pronunciations of the selected audio segment. | 1. A device, comprising: a memory to store instructions; and a processor coupled to the memory, wherein responsive to executing the instructions, the processor performs operations comprising: receiving video media content, wherein the video media content comprises images, audio content, and closed captioning of text from the audio content; detecting an occurrence of a textual phrase in the closed captioning of the video media content as a detected occurrence; selecting an audio segment from the audio content of the media content as a selected audio segment, wherein the selected audio segment corresponds to the detected occurrence of the textual phrase in the closed captioning; selecting from a speech recognition library an audio pronunciation associated with the textual phrase, wherein the speech recognition library comprises a group of identified audio segments, wherein the group of identified audio segments comprises a baseline audio pronunciation and collected audio pronunciations of the textual phrase; comparing the selected audio segment with the group of identified audio segments from the speech recognition library; determining if an audio pronunciation of the selected audio segment differs from the baseline audio pronunciation from the speech recognition library; responsive to determining that the audio pronunciation of the selected audio segment differs from the baseline audio pronunciation, generating a phonetic transcription of the audio pronunciation of the selected audio segment; and adding the phonetic transcription and the textual phrase to the group of identified audio segments in the speech recognition library to populate the collected audio pronunciations of the selected audio segment. 6. The device as defined in claim 1 , wherein the operations comprise comparing the selected audio segment to a second baseline audio pronunciation associated with the textual phrase from the speech recognition library. | 0.908598 |
9,063,990 | 1 | 2 | 1. A method of searching messages, comprising: at one or more servers: receiving a search query; in response to receiving the search query: obtaining, from a message repository, conversations relevant to the search query; creating a list of conversations representing at least a subset of the obtained conversations, wherein each conversation in the list of conversations is represented as a single item, and at least one of the conversations in the list of conversations comprises two or more electronic messages from distinct senders; identifying, for each conversation in the list of conversations, a portion of conversation content relevant to the search query; and producing, for concurrent display at a client, a search result including at least the list of conversations, and the identified portion of conversation content for each conversation in the list of conversations. | 1. A method of searching messages, comprising: at one or more servers: receiving a search query; in response to receiving the search query: obtaining, from a message repository, conversations relevant to the search query; creating a list of conversations representing at least a subset of the obtained conversations, wherein each conversation in the list of conversations is represented as a single item, and at least one of the conversations in the list of conversations comprises two or more electronic messages from distinct senders; identifying, for each conversation in the list of conversations, a portion of conversation content relevant to the search query; and producing, for concurrent display at a client, a search result including at least the list of conversations, and the identified portion of conversation content for each conversation in the list of conversations. 2. The method of claim 1 , wherein each obtained conversation is associated with a unique numeric conversation identifier. | 0.865044 |
8,356,044 | 11 | 15 | 11. A computer-implemented system for providing default hierarchical training for social indexing, comprising: an electronic database, comprising: articles of digital information maintained for social indexing; and a hierarchically-structured tree of topics, which each comprise a label comprising one or more words; a processor and memory within which code for execution by the processor is stored, further comprising: an electronically-stored rules set identifying hard constraints based on the labels comprised in the topic tree and the topic tree's hierarchical structure, wherein the hard constraints are defined to include required immutable rules comprising at least one of: that a topic model comprises a single term comprised from a label that is duplicated within the topic tree; that a topic model includes no term from the label for the topic to which the topic model belongs; and when the label is duplicated within the topic tree, that a topic model includes no term from the label of a parent topic for the topic to which the topic model belongs; a topic builder module that, for each topic in the topic tree, creates a topic model subject to the hard constraints, the topic model comprising a finite state pattern that comprises a pattern evaluable against the articles; and an evaluator module evaluating the topic models for the topic tree against the hard constraints, and disfavoring those topic models that violate one or more of the immutable rules; and a user interface visually identifying for each topic, the topic model, which best satisfies the constraints. | 11. A computer-implemented system for providing default hierarchical training for social indexing, comprising: an electronic database, comprising: articles of digital information maintained for social indexing; and a hierarchically-structured tree of topics, which each comprise a label comprising one or more words; a processor and memory within which code for execution by the processor is stored, further comprising: an electronically-stored rules set identifying hard constraints based on the labels comprised in the topic tree and the topic tree's hierarchical structure, wherein the hard constraints are defined to include required immutable rules comprising at least one of: that a topic model comprises a single term comprised from a label that is duplicated within the topic tree; that a topic model includes no term from the label for the topic to which the topic model belongs; and when the label is duplicated within the topic tree, that a topic model includes no term from the label of a parent topic for the topic to which the topic model belongs; a topic builder module that, for each topic in the topic tree, creates a topic model subject to the hard constraints, the topic model comprising a finite state pattern that comprises a pattern evaluable against the articles; and an evaluator module evaluating the topic models for the topic tree against the hard constraints, and disfavoring those topic models that violate one or more of the immutable rules; and a user interface visually identifying for each topic, the topic model, which best satisfies the constraints. 15. A system according to claim 11 , wherein the processor and memory further comprise: a structural complexity evaluation module evaluating structural complexity for each of the topic models, comprising one or more of favoring those topic models that include at least one n-gram, favoring those topic models that include one or more non-duplicated terms, and favoring those topic models that include at least one group of the terms in the labels. | 0.574286 |
8,868,529 | 13 | 15 | 13. An apparatus comprising: a processor configured to: divide a plurality of ride intent objects into candidate sets, wherein: each ride intent object defines ride preferences of a respective car pool user; and each candidate set is associated with a respective ride matcher object that specifies a plurality of ride preferences that ride intent objects in the candidate set must include, the plurality of ride preferences forming a subset of less than all the ride preferences of any particular ride intent object in the candidate set; lock the ride intent objects such that only a ride matcher object associated with a candidate set containing a particular ride intent object can perform matching on the particular ride intent object while the particular ride intent object remains locked, wherein unlocked ride intent objects are available for matching by any ride matcher object, and wherein the same ride preference is specified by at least some of the ride matcher objects; match, by each ride matcher object and based on ride preference values, ride intent objects in a respective candidate set to other ride intent objects in the same candidate set; identify, based on ride preference value, a plurality of ride preferences in a first ride intent object that match a corresponding plurality of ride preferences in a second ride intent object, wherein ride preferences are determined to match when: there is an exact match between respective values of a first of at least two ride preferences for the first ride intent object and the second ride intent object; and respective values of a second of the at least two ride preferences for the first and the second ride intent objects are within a predetermined threshold of similarity; assign different weights to corresponding ride preferences in each ride intent object; calculate a sum of the weights associated with the matching ride preferences; determine that the first ride intent object matches the second ride intent object when the sum of the weights exceeds a predetermined weight threshold; and group the plurality of ride intent objects into a plurality of ride intent sets based on the matching, wherein each ride intent set is a subset of a respective candidate set that contains the ride intent objects of the ride intent set. | 13. An apparatus comprising: a processor configured to: divide a plurality of ride intent objects into candidate sets, wherein: each ride intent object defines ride preferences of a respective car pool user; and each candidate set is associated with a respective ride matcher object that specifies a plurality of ride preferences that ride intent objects in the candidate set must include, the plurality of ride preferences forming a subset of less than all the ride preferences of any particular ride intent object in the candidate set; lock the ride intent objects such that only a ride matcher object associated with a candidate set containing a particular ride intent object can perform matching on the particular ride intent object while the particular ride intent object remains locked, wherein unlocked ride intent objects are available for matching by any ride matcher object, and wherein the same ride preference is specified by at least some of the ride matcher objects; match, by each ride matcher object and based on ride preference values, ride intent objects in a respective candidate set to other ride intent objects in the same candidate set; identify, based on ride preference value, a plurality of ride preferences in a first ride intent object that match a corresponding plurality of ride preferences in a second ride intent object, wherein ride preferences are determined to match when: there is an exact match between respective values of a first of at least two ride preferences for the first ride intent object and the second ride intent object; and respective values of a second of the at least two ride preferences for the first and the second ride intent objects are within a predetermined threshold of similarity; assign different weights to corresponding ride preferences in each ride intent object; calculate a sum of the weights associated with the matching ride preferences; determine that the first ride intent object matches the second ride intent object when the sum of the weights exceeds a predetermined weight threshold; and group the plurality of ride intent objects into a plurality of ride intent sets based on the matching, wherein each ride intent set is a subset of a respective candidate set that contains the ride intent objects of the ride intent set. 15. The apparatus of claim 13 , wherein preferences of each ride intent object include at least one of smoking, music, sex, gender, origin of ride, destination of ride, time window of ride, driving style, conversation style, area of occupation, vehicle type, and temperature inside vehicle. | 0.5 |
5,515,490 | 19 | 22 | 19. A method of temporally formatting a plurality of media items included in a time-dependent document in an information presentation system; the information presentation system including memory for storing data, a processor connected for accessing the data stored in the memory, and a plurality of media presentation devices; the data stored in the memory including instruction data indicating instructions the processor executes; the method comprising: operating the processor to obtain, for each media item, at least one pair of temporally adjacent media item event data items, referred to as a pair of temporally adjacent events, identifying a media item segment; each event in a pair of temporally adjacent events marking a point in time in the respective media item segment such that a second event in the pair of events follows a first event in time with no intervening media item events specified between the pair of temporally adjacent events; each media item segment indicating whether occurrence of the media item segment in the time-dependent document is predictable or unpredictable; operating the processor to obtain a durational time data item, hereafter referred to as a duration, for each respective media item segment; each durational time data item indicating an elapsed time for presentation of the media item segment by a respective one of the media presentation devices; each durational time data item further indicating whether the duration is predictable or unpredictable; each predictable duration including a range of predictable elapsed presentation durations including a minimum duration, an optimum duration, and a maximum duration for presenting the respective media item segment; the optimum duration indicating a durational time value that produces a preferred presentation quality for the respective media item segment when the respective media item segment is presented by a respective one of the media presentation devices for the optimum duration; each predictable duration further indicating flexibility metric data measuring a deviation from the preferred presentation quality of the respective media item segment at each respective duration within the range of durations when the media item segment is presented by the at least one media presentation device for the respective duration; the flexibility metric data indicating a penalty value for adjusting the predictable elapsed presentation duration of a respective media item segment to an adjusted duration different from the optimum duration; operating the processor to obtain temporal constraint data indicating a time ordering relation value specified between first and second temporally related event data items, referred to hereafter as a pair of temporally related events, identified from among the temporally adjacent events; a first one of the temporally related events being an event included in a first media item segment and a second one of the temporally related events being an event included in a second media item segment; operating the processor to identify media item segments indicating a predictable occurrence and a predictable media segment duration as having predictable behavior, and to identify media item segments indicating an unpredictable occurrence or an unpredictable media segment duration as having unpredictable behavior; for each respective media item segment having predictable behavior, operating the processor to assign a document presentation time value to each event included in the respective media item segment; each document presentation time value assigned producing a computed duration within the range of durations indicated for the respective media item segment, and satisfying the temporal constraint data specified between the respective media item segment and a second media item segment; the computed duration being an adjusted duration when document presentation time values cannot be assigned that are consistent with the optimum duration for the respective media item segment and still satisfy the temporal constraint data; the adjusted duration being determined using the flexibility metric data and producing assigned document presentation time values satisfying the temporal constraint data specified between the respective media item segment and a second media item segment while producing a presentation quality that deviates by an acceptable amount from the preferred presentation quality of the respective media item segment, as measured by an acceptably small penalty value indicated by the flexibility metric data; and for each respective media item segment having unpredictable behavior, operating the processor to assign an unresolved document presentation time to a starting event in a media item segment having an unpredictable occurrence, and to assign an unresolved document presentation time assigned to an ending event in a media item segment having an unpredictable duration. | 19. A method of temporally formatting a plurality of media items included in a time-dependent document in an information presentation system; the information presentation system including memory for storing data, a processor connected for accessing the data stored in the memory, and a plurality of media presentation devices; the data stored in the memory including instruction data indicating instructions the processor executes; the method comprising: operating the processor to obtain, for each media item, at least one pair of temporally adjacent media item event data items, referred to as a pair of temporally adjacent events, identifying a media item segment; each event in a pair of temporally adjacent events marking a point in time in the respective media item segment such that a second event in the pair of events follows a first event in time with no intervening media item events specified between the pair of temporally adjacent events; each media item segment indicating whether occurrence of the media item segment in the time-dependent document is predictable or unpredictable; operating the processor to obtain a durational time data item, hereafter referred to as a duration, for each respective media item segment; each durational time data item indicating an elapsed time for presentation of the media item segment by a respective one of the media presentation devices; each durational time data item further indicating whether the duration is predictable or unpredictable; each predictable duration including a range of predictable elapsed presentation durations including a minimum duration, an optimum duration, and a maximum duration for presenting the respective media item segment; the optimum duration indicating a durational time value that produces a preferred presentation quality for the respective media item segment when the respective media item segment is presented by a respective one of the media presentation devices for the optimum duration; each predictable duration further indicating flexibility metric data measuring a deviation from the preferred presentation quality of the respective media item segment at each respective duration within the range of durations when the media item segment is presented by the at least one media presentation device for the respective duration; the flexibility metric data indicating a penalty value for adjusting the predictable elapsed presentation duration of a respective media item segment to an adjusted duration different from the optimum duration; operating the processor to obtain temporal constraint data indicating a time ordering relation value specified between first and second temporally related event data items, referred to hereafter as a pair of temporally related events, identified from among the temporally adjacent events; a first one of the temporally related events being an event included in a first media item segment and a second one of the temporally related events being an event included in a second media item segment; operating the processor to identify media item segments indicating a predictable occurrence and a predictable media segment duration as having predictable behavior, and to identify media item segments indicating an unpredictable occurrence or an unpredictable media segment duration as having unpredictable behavior; for each respective media item segment having predictable behavior, operating the processor to assign a document presentation time value to each event included in the respective media item segment; each document presentation time value assigned producing a computed duration within the range of durations indicated for the respective media item segment, and satisfying the temporal constraint data specified between the respective media item segment and a second media item segment; the computed duration being an adjusted duration when document presentation time values cannot be assigned that are consistent with the optimum duration for the respective media item segment and still satisfy the temporal constraint data; the adjusted duration being determined using the flexibility metric data and producing assigned document presentation time values satisfying the temporal constraint data specified between the respective media item segment and a second media item segment while producing a presentation quality that deviates by an acceptable amount from the preferred presentation quality of the respective media item segment, as measured by an acceptably small penalty value indicated by the flexibility metric data; and for each respective media item segment having unpredictable behavior, operating the processor to assign an unresolved document presentation time to a starting event in a media item segment having an unpredictable occurrence, and to assign an unresolved document presentation time assigned to an ending event in a media item segment having an unpredictable duration. 22. The temporal formatting method of claim 19 wherein the time ordering relation specified between temporally related events specifies a time ordering relation between media item segments included in the same media item. | 0.932622 |
7,987,169 | 26 | 37 | 26. The method of claim 25 , wherein the generating of a score for a structure having an aggregate comprises calculating (a) a deviation score of the search expression, and (b) for each sub-expression of the search expression, a density and a relevance center of the sub-expression, for the aggregate, the calculating being performed using at least relevance geometry of the aggregate, one or more deviation scores of the search expression of each child of the aggregate, and a density of each sub-expression of the search expression for each child of the aggregate. | 26. The method of claim 25 , wherein the generating of a score for a structure having an aggregate comprises calculating (a) a deviation score of the search expression, and (b) for each sub-expression of the search expression, a density and a relevance center of the sub-expression, for the aggregate, the calculating being performed using at least relevance geometry of the aggregate, one or more deviation scores of the search expression of each child of the aggregate, and a density of each sub-expression of the search expression for each child of the aggregate. 37. The method of claim 26 , wherein the generating of a score for a structure having an aggregate comprises assigning a relevance value for a child of the aggregate for a plurality of disjointed sub-expressions of the search expression, to a maximum of a number of relevance values previously calculated or assigned to a child of the aggregate for the sub-expressions. | 0.823445 |
7,831,432 | 2 | 3 | 2. The method of claim 1 wherein retrieving metadata further comprises: retrieving from each of the media files managed by the media player metadata describing the media file; identifying in dependence upon a file system in which the media files are stored an organization of the media files managed by the media player; and wherein saving the speech in the audio portion of the one or more media files for the audio menu further comprises: saving the speech according to the organization of the media files managed by the media player. | 2. The method of claim 1 wherein retrieving metadata further comprises: retrieving from each of the media files managed by the media player metadata describing the media file; identifying in dependence upon a file system in which the media files are stored an organization of the media files managed by the media player; and wherein saving the speech in the audio portion of the one or more media files for the audio menu further comprises: saving the speech according to the organization of the media files managed by the media player. 3. The method of claim 2 further comprising prepending speech converted from the metadata of a media file managed by the media player to the audio portion of the media file. | 0.5 |
8,649,776 | 12 | 13 | 12. A non-transitory machine readable medium storing instructions that, when executed by a processor, cause the processor to perform operations comprising: receiving user identification information associated with a first user, the user identification information comprising a name of the first user and a photograph of the first user, wherein the photograph is captured by a mobile device associated with a second user, and the photograph comprises identifying characteristics of the first user; causing contact information of the first user to be stored in association with the user identification information; receiving current user identification information through the mobile device, the current user identification information comprising a current photograph of the first user, wherein the current photograph is captured by the mobile device, and the current photograph comprises current identifying characteristics of the first user; matching the current user identification information with the user identification information; in response to matching the current user identification information with the first user identification information, retrieving social network information of the first user, the social network information comprising friend information associated with a friend of the first user, activity information associated with an activity of the first user, and web content associated with the first user; and causing the mobile device to present the social network information to the second user so that the second user can utilize the social network information during a conversation with the first user. | 12. A non-transitory machine readable medium storing instructions that, when executed by a processor, cause the processor to perform operations comprising: receiving user identification information associated with a first user, the user identification information comprising a name of the first user and a photograph of the first user, wherein the photograph is captured by a mobile device associated with a second user, and the photograph comprises identifying characteristics of the first user; causing contact information of the first user to be stored in association with the user identification information; receiving current user identification information through the mobile device, the current user identification information comprising a current photograph of the first user, wherein the current photograph is captured by the mobile device, and the current photograph comprises current identifying characteristics of the first user; matching the current user identification information with the user identification information; in response to matching the current user identification information with the first user identification information, retrieving social network information of the first user, the social network information comprising friend information associated with a friend of the first user, activity information associated with an activity of the first user, and web content associated with the first user; and causing the mobile device to present the social network information to the second user so that the second user can utilize the social network information during a conversation with the first user. 13. The non-transitory machine readable medium of claim 12 , wherein matching the current user identification information with the user identification information comprises matching the current user identification information with the user identification information utilizing face recognition. | 0.5 |
8,583,632 | 13 | 22 | 13. A computer system that processes a search query result, the computer system comprising: a network interface for communicating with a network through which access to a collection of pages is obtained, a processor that identifies a plurality of result pages in response to a search query submitted from a computing device that is associated with a subscriber, wherein the search query is directed to the collection of pages, determines a relevancy ranking for each of the result pages in accordance with a parameter set that includes metrics relating to the search query itself and also includes metrics unique to the subscriber associated with the computing device, and includes metrics related to the computing device from which the search query was submitted, wherein each of the parameter set metrics, when applied to the result pages, provides a re-ordering of the result pages, wherein the parameter set metrics are applied according to a tunable priority received from an administrative console input, and the determined relevancy ranking comprises a single merged ordering of the respective re-orderings and provides result pages in accordance with the determined relevancy ranking; wherein the administrative console input specifies parameter set processing for a plurality of ranking operations, and the administrative console input is used to select or deselect each of the ranking operations and specify an order of operation for the selected ranking operations, wherein determining a relevancy ranking includes: associating each result page with a relevancy ranking value; and ordering the plurality of result pages in accordance with the associated relevancy ranking values of the result pages; and wherein the relevancy ranking value is adjusted with a tunable parameter value, and wherein the relevancy ranking value AR is calculated according to ∀ u AR k ( u ) = c [ α ∑ i ( tf i * log ( D df ) ) + β ∑ v ∈ ⋃ u P ( v ) + λ ∑ v ∈ ⋃ u DSI ( v ) + γ ( 1 - ( u x - P ( V x ) ) 2 + ( u y - P ( V y ) ) 2 ) ] + ( 1 - c ) where the terms are defined by the following: AR=Active Rank matrix (sorted order of vectors) u=set of total search results v=set of metadata attributes associated with each search result item k=a given Active Rank row (value for a specific search result) c=normalization coefficient ≦1 α=bias to weight keyword matching effects (0 ≦α≦1) β=bias to weight Personalization profiles (0 ≦β≦1) λ=bias to weight Device Specificity effects (0 ≦λ≦1) γ=bias to weight LBS geometric distance effects (0 ≦γ≦1) tf i =term frequency (keyword counts) or number of times a term i occurs in a search result page df i =document frequency or number of pages in the search result pages containing term i D=number of documents in the database P=Personalization profile vector DSI=Device Specific Index vector (u x , u y )=each search result's geocoded location, if any (v x , v y )=cellular user's actual physical location (stored in vector P) provided by the cellular network. | 13. A computer system that processes a search query result, the computer system comprising: a network interface for communicating with a network through which access to a collection of pages is obtained, a processor that identifies a plurality of result pages in response to a search query submitted from a computing device that is associated with a subscriber, wherein the search query is directed to the collection of pages, determines a relevancy ranking for each of the result pages in accordance with a parameter set that includes metrics relating to the search query itself and also includes metrics unique to the subscriber associated with the computing device, and includes metrics related to the computing device from which the search query was submitted, wherein each of the parameter set metrics, when applied to the result pages, provides a re-ordering of the result pages, wherein the parameter set metrics are applied according to a tunable priority received from an administrative console input, and the determined relevancy ranking comprises a single merged ordering of the respective re-orderings and provides result pages in accordance with the determined relevancy ranking; wherein the administrative console input specifies parameter set processing for a plurality of ranking operations, and the administrative console input is used to select or deselect each of the ranking operations and specify an order of operation for the selected ranking operations, wherein determining a relevancy ranking includes: associating each result page with a relevancy ranking value; and ordering the plurality of result pages in accordance with the associated relevancy ranking values of the result pages; and wherein the relevancy ranking value is adjusted with a tunable parameter value, and wherein the relevancy ranking value AR is calculated according to ∀ u AR k ( u ) = c [ α ∑ i ( tf i * log ( D df ) ) + β ∑ v ∈ ⋃ u P ( v ) + λ ∑ v ∈ ⋃ u DSI ( v ) + γ ( 1 - ( u x - P ( V x ) ) 2 + ( u y - P ( V y ) ) 2 ) ] + ( 1 - c ) where the terms are defined by the following: AR=Active Rank matrix (sorted order of vectors) u=set of total search results v=set of metadata attributes associated with each search result item k=a given Active Rank row (value for a specific search result) c=normalization coefficient ≦1 α=bias to weight keyword matching effects (0 ≦α≦1) β=bias to weight Personalization profiles (0 ≦β≦1) λ=bias to weight Device Specificity effects (0 ≦λ≦1) γ=bias to weight LBS geometric distance effects (0 ≦γ≦1) tf i =term frequency (keyword counts) or number of times a term i occurs in a search result page df i =document frequency or number of pages in the search result pages containing term i D=number of documents in the database P=Personalization profile vector DSI=Device Specific Index vector (u x , u y )=each search result's geocoded location, if any (v x , v y )=cellular user's actual physical location (stored in vector P) provided by the cellular network. 22. A computer system as defined in claim 13 , wherein the multiple dimension parameter set includes metrics relating to the search query itself, to the subscriber associated with the search query, to capabilities of the computing device, and to geographic location of the computing device. | 0.671946 |
7,684,546 | 12 | 14 | 12. A device for controlling operation of an operational line in a DSL system, the device comprising: means for collecting operational data from the operational line; means coupled to the collecting means for analyzing the collected operational data, the analyzing means further comprising: means for estimating the observation probability, the state-transition probability matrix, and the initial state distribution of a Hidden Markov Model (HMM) based on the collected update operational data; means for estimating a likelihood of at least one state of the HMM based on the collected update operational data; means for controlling operation of the operational line based on: the collected operational data; and the HMM modeling the internal states of the DSL system, the states characterizing at least one of data activity, impulse noise, crosstalk, noise margin, maximum attainable data rate or bit distributions. | 12. A device for controlling operation of an operational line in a DSL system, the device comprising: means for collecting operational data from the operational line; means coupled to the collecting means for analyzing the collected operational data, the analyzing means further comprising: means for estimating the observation probability, the state-transition probability matrix, and the initial state distribution of a Hidden Markov Model (HMM) based on the collected update operational data; means for estimating a likelihood of at least one state of the HMM based on the collected update operational data; means for controlling operation of the operational line based on: the collected operational data; and the HMM modeling the internal states of the DSL system, the states characterizing at least one of data activity, impulse noise, crosstalk, noise margin, maximum attainable data rate or bit distributions. 14. The device of claim 12 wherein the device is configured to construct and update the HMM by: using the collecting means to collect operational data from the operational line; and using the analyzing means to analyze the collected operational data. | 0.725275 |
7,565,632 | 9 | 11 | 9. A computer readable storage device having a program stored thereon for causing a computer to execute a behavioral synthesizing method for generating a circuit description at low abstractness from a behavioral-level description, said stored program comprising: processing for analyzing the behavioral-level description entered thereinto for conversion into an internal representation for behavioral synthesis, and generating an internal representation indicative of a correspondence relationship between a pointer variable and a specific circuit entity when the pointer variable is converted into a specific circuit entity, based on a pointer type specification within the behavioral-level description; processing for converting a pointer variable in the internal representation into a set of a terminal and a condition section, based on a conversion rule; and processing for performing behavioral synthesis processing for the internal representation from which the pointer variable has been removed to generate and supply a circuit description at low abstractness; wherein the behavioral synthesis processing includes providing a design flow which allows a caller function to be completely independent of the implementation of a callee function upon synthesis of the caller function. | 9. A computer readable storage device having a program stored thereon for causing a computer to execute a behavioral synthesizing method for generating a circuit description at low abstractness from a behavioral-level description, said stored program comprising: processing for analyzing the behavioral-level description entered thereinto for conversion into an internal representation for behavioral synthesis, and generating an internal representation indicative of a correspondence relationship between a pointer variable and a specific circuit entity when the pointer variable is converted into a specific circuit entity, based on a pointer type specification within the behavioral-level description; processing for converting a pointer variable in the internal representation into a set of a terminal and a condition section, based on a conversion rule; and processing for performing behavioral synthesis processing for the internal representation from which the pointer variable has been removed to generate and supply a circuit description at low abstractness; wherein the behavioral synthesis processing includes providing a design flow which allows a caller function to be completely independent of the implementation of a callee function upon synthesis of the caller function. 11. The computer readable storage device having a program stored thereon according to claim 9 , wherein said stored program further comprises processing for determining a method to convert a pointer variable into a specific circuit entity based on the result of the analysis. | 0.723896 |
9,830,311 | 7 | 10 | 7. A computing device comprising: at least one processor; and memory configured to store instructions that, when executed, cause the at least one processor to: output, for display, a graphical keyboard comprising a plurality of keys; receive a plurality of indications of input, each respective indication of input from the plurality of indications of input corresponding to a respective location of the graphical keyboard; and for each respective indication of input from the plurality of indications of input, incrementally: determine, based at least in part on both physical cost values from a spatial model, and lexical cost values from a language model at least one predicted current word based on a set of characters that correspond to the plurality of indications of input, wherein the spatial model comprises at least one respective distribution of touch points that corresponds to at least one respective key of the graphical keyboard, and wherein the at least one predicted current word is determined based on a physical cost value from the spatial model that is modified by a lexical cost value from the language model, the physical cost value representing a first likelihood that the plurality of indications of input correspond to the set of characters, and the lexical cost value representing a second likelihood that the set of characters are included in any word in a lexicon of the language model; determine, based at least in part on the at least one predicted current word that is the previous word, at least one predicted next word that follows the at least one predicted current word; and output, for display, the at least one predicted current word and the at least one predicted next word as a soft commit word in a text entry area of a graphical user interface by at least: outputting, for display in a first visual style, characters of the at least one predicted current word and the at least one predicted next word that are from the set of characters that correspond to the plurality of indications of input; and outputting, for display in a second visual style that is different than the first visual style, characters of the at least one predicted current word and the at least one predicted next word that are not from the set of characters that correspond to the plurality of indications of input. | 7. A computing device comprising: at least one processor; and memory configured to store instructions that, when executed, cause the at least one processor to: output, for display, a graphical keyboard comprising a plurality of keys; receive a plurality of indications of input, each respective indication of input from the plurality of indications of input corresponding to a respective location of the graphical keyboard; and for each respective indication of input from the plurality of indications of input, incrementally: determine, based at least in part on both physical cost values from a spatial model, and lexical cost values from a language model at least one predicted current word based on a set of characters that correspond to the plurality of indications of input, wherein the spatial model comprises at least one respective distribution of touch points that corresponds to at least one respective key of the graphical keyboard, and wherein the at least one predicted current word is determined based on a physical cost value from the spatial model that is modified by a lexical cost value from the language model, the physical cost value representing a first likelihood that the plurality of indications of input correspond to the set of characters, and the lexical cost value representing a second likelihood that the set of characters are included in any word in a lexicon of the language model; determine, based at least in part on the at least one predicted current word that is the previous word, at least one predicted next word that follows the at least one predicted current word; and output, for display, the at least one predicted current word and the at least one predicted next word as a soft commit word in a text entry area of a graphical user interface by at least: outputting, for display in a first visual style, characters of the at least one predicted current word and the at least one predicted next word that are from the set of characters that correspond to the plurality of indications of input; and outputting, for display in a second visual style that is different than the first visual style, characters of the at least one predicted current word and the at least one predicted next word that are not from the set of characters that correspond to the plurality of indications of input. 10. The computing device of claim 7 , wherein the instructions, when executed, further cause the at least one processor to: determine, based at least in part on both a lexicon and a word-level N-gram, a frequency value associated with the set of characters, wherein the frequency value represents a frequency of occurrence of the set of characters in the lexicon; and determine, based at least in part on the frequency value, the at least one predicted current word. | 0.5 |
7,693,829 | 4 | 6 | 4. The method of claim 2 , further comprising determining document scores for the set of documents, wherein a respective document score is based on a highest match score and a total number of matches between the search pattern and the respective document in the set of documents. | 4. The method of claim 2 , further comprising determining document scores for the set of documents, wherein a respective document score is based on a highest match score and a total number of matches between the search pattern and the respective document in the set of documents. 6. The method of claim 4 , wherein the respective document score is a weighted summation of the highest match score, the total number of matches between the search pattern and the respective document, and a quality of document metric. | 0.753684 |
9,514,108 | 1 | 9 | 1. A method for reference note generation, comprising: receiving a first user input that identifies a designated insertion point in a destination document; subsequent to receiving the first user input, receiving a second user input that causes an information element to be copied to a transfer buffer from a source application; collecting source reference information associated with the information element, wherein the source reference information includes a source identifier indicative of an origin of the information element; generating a reference note based on the source reference information and a reference note format specification; inserting the information element into the destination document, wherein the information element is inserted automatically at the designated insertion point without receiving a further user input from a user interface that is associated with the destination document; and inserting the reference note into the destination document, wherein the reference note is associated with the information element and the reference note is inserted without receiving a user input from a user interface that is associated with the destination document. | 1. A method for reference note generation, comprising: receiving a first user input that identifies a designated insertion point in a destination document; subsequent to receiving the first user input, receiving a second user input that causes an information element to be copied to a transfer buffer from a source application; collecting source reference information associated with the information element, wherein the source reference information includes a source identifier indicative of an origin of the information element; generating a reference note based on the source reference information and a reference note format specification; inserting the information element into the destination document, wherein the information element is inserted automatically at the designated insertion point without receiving a further user input from a user interface that is associated with the destination document; and inserting the reference note into the destination document, wherein the reference note is associated with the information element and the reference note is inserted without receiving a user input from a user interface that is associated with the destination document. 9. The method of claim 1 , wherein the reference note is inserted into the destination document in a different content field than the information element. | 0.70155 |
9,349,132 | 11 | 12 | 11. The method of claim 1 , wherein exposing the database system of the host organization comprises exposing a Predictive Query Language Application Programming Interface (PreQL API) directly to authenticated users, wherein the PreQL API is accessible to the authenticated users via a public Internet. | 11. The method of claim 1 , wherein exposing the database system of the host organization comprises exposing a Predictive Query Language Application Programming Interface (PreQL API) directly to authenticated users, wherein the PreQL API is accessible to the authenticated users via a public Internet. 12. The method of claim 11 , wherein querying the database system using the GROUP command term comprises passing a PreQL query to the database system, the PreQL query having a query syntax of: the GROUP command term as a required term; a COLUMN term as a required term, the COLUMN term specifying the column to be passed with the GROUP command term; an optional FROM term specifying one or more tables, datasets, data sources, or indices, or any combination thereof, to be queried when the optional FROM term is specified; and wherein a default value is used when the optional FROM term is not specified. | 0.5 |
7,661,060 | 1 | 2 | 1. A mobile communication terminal to reproduce multimedia, the terminal comprising: an input unit that receives a Synchronized Multimedia Integration Language (SMIL) document at the mobile communication terminal; a SMIL analyzer that generates a Document Object Model (DOM) tree from the SMIL document; a control table generator that generates a predetermined control table based on the DOM tree; a media reproducing unit that reproduces media data of the SMIL document on the mobile communication terminal; and a controller that controls the media reproducing unit based on the predetermined control table, wherein the predetermined control table comprises a reproduction control table and a stop control table, the reproduction control table including a first plurality of time sections and a plurality of kinds or names of media to be reproduced at the corresponding first plurality of time sections, the stop control table including a second plurality of time sections and a plurality of kinds or names of media to be stopped from being reproduced at the corresponding second plurality of time sections, wherein each media specified in the predetermined control table has a connection structure of a linked list, wherein when there is a plurality of media items to be reproduced, the media reproducing unit aligns the media items according to a z-index alignment method and reproduces the media items starting from a media item having a lowest order under control of the controller, wherein the stop control table and the reproduction control table are separately operated, and wherein the controller arbitrarily adjusts a stop time of media being reproduced according to a user's input. | 1. A mobile communication terminal to reproduce multimedia, the terminal comprising: an input unit that receives a Synchronized Multimedia Integration Language (SMIL) document at the mobile communication terminal; a SMIL analyzer that generates a Document Object Model (DOM) tree from the SMIL document; a control table generator that generates a predetermined control table based on the DOM tree; a media reproducing unit that reproduces media data of the SMIL document on the mobile communication terminal; and a controller that controls the media reproducing unit based on the predetermined control table, wherein the predetermined control table comprises a reproduction control table and a stop control table, the reproduction control table including a first plurality of time sections and a plurality of kinds or names of media to be reproduced at the corresponding first plurality of time sections, the stop control table including a second plurality of time sections and a plurality of kinds or names of media to be stopped from being reproduced at the corresponding second plurality of time sections, wherein each media specified in the predetermined control table has a connection structure of a linked list, wherein when there is a plurality of media items to be reproduced, the media reproducing unit aligns the media items according to a z-index alignment method and reproduces the media items starting from a media item having a lowest order under control of the controller, wherein the stop control table and the reproduction control table are separately operated, and wherein the controller arbitrarily adjusts a stop time of media being reproduced according to a user's input. 2. The terminal of claim 1 , wherein the controller drives a timer and checks the control table at each of the first plurality of time sections and the second plurality of time sections, and wherein when there is media to be reproduced at a first time section specified in the reproduction control table, the controller reproduces the corresponding media and when there is media to be stopped from reproduction at a second time section specified in the stop control table, the controller stops reproducing of the corresponding media. | 0.5 |
9,715,497 | 14 | 16 | 14. One or more non-transitory computer-readable media storing instructions which, when executed by at least one processor, instruct the at least one processor to perform actions comprising: accessing a framework from at least one previously published work, the framework comprising a first set of entities; accessing one or more rules that constrain a first set of actions associated with the first set of entities within the framework, the first set of actions including one or more of a verb performed by or on at least one of the first set of entities in the framework or a phrase performed by or on the at least one of the first set of entities in the manuscript; accessing a manuscript submitted for publication, the manuscript being associated with the framework; performing natural language analysis of the manuscript submitted for publication to identify a set of nouns described in the manuscript as a second set of entities described in the manuscript, and to identify a second set of actions associated with at least one of conveying an action associated with the first set of entities in the manuscript, the second set of actions including the one or more of a verb performed by or on at least one of the second set of entities in the manuscript or a phrase performed by or on the at least one of the second set of entities in the manuscript; generating a set of relationships in the manuscript between the second set of entities and the second set of actions, such that the set of relationships further include one or more additional actions that are synonymous to at least one action associated with at least one entity in the second set of actions; comparing the set of relationships between the second set of entities and the second set of actions associated with the second set of entities with the one or more rules that constrain the first set of actions associated with the first set of entities in the framework; determining an amount of compliancy for each specific entity in the second set of entities by locating the one or more rules that reference the specific entity and determining whether the actions that correspond to the specific entity in the set of relationships comply or do not comply with the actions for the specific entity specified in the located one or more rules; and identifying the manuscript as compliant with the one or more rules based on determining that a number of actions of the second set of entities in the set of relationships that comply with the one or more rules is greater than a threshold proportion of a total number of the second set of entities; and generating result data that indicates the manuscript complies with the rules. | 14. One or more non-transitory computer-readable media storing instructions which, when executed by at least one processor, instruct the at least one processor to perform actions comprising: accessing a framework from at least one previously published work, the framework comprising a first set of entities; accessing one or more rules that constrain a first set of actions associated with the first set of entities within the framework, the first set of actions including one or more of a verb performed by or on at least one of the first set of entities in the framework or a phrase performed by or on the at least one of the first set of entities in the manuscript; accessing a manuscript submitted for publication, the manuscript being associated with the framework; performing natural language analysis of the manuscript submitted for publication to identify a set of nouns described in the manuscript as a second set of entities described in the manuscript, and to identify a second set of actions associated with at least one of conveying an action associated with the first set of entities in the manuscript, the second set of actions including the one or more of a verb performed by or on at least one of the second set of entities in the manuscript or a phrase performed by or on the at least one of the second set of entities in the manuscript; generating a set of relationships in the manuscript between the second set of entities and the second set of actions, such that the set of relationships further include one or more additional actions that are synonymous to at least one action associated with at least one entity in the second set of actions; comparing the set of relationships between the second set of entities and the second set of actions associated with the second set of entities with the one or more rules that constrain the first set of actions associated with the first set of entities in the framework; determining an amount of compliancy for each specific entity in the second set of entities by locating the one or more rules that reference the specific entity and determining whether the actions that correspond to the specific entity in the set of relationships comply or do not comply with the actions for the specific entity specified in the located one or more rules; and identifying the manuscript as compliant with the one or more rules based on determining that a number of actions of the second set of entities in the set of relationships that comply with the one or more rules is greater than a threshold proportion of a total number of the second set of entities; and generating result data that indicates the manuscript complies with the rules. 16. The one or more computer-readable media of claim 14 , wherein: the first set of entities includes one or more of a character, a location, or an object described in the manuscript. | 0.774631 |
7,698,328 | 15 | 19 | 15. A system, comprising: one or more computers configured to perform operations including: receiving a first search query including one or more search terms; providing a first set of documents responsive to the first query; determining one or more collocations from the first set of documents that include at least one of the search terms, each collocation including at least one other term that is semantically related to the at least one search term; scoring the collocations from the first set of documents, including determining a mutual information score for each collocation using a mutual information test; multiplying at least some collocation scores by frequency counts, a frequency count for a given collocation representing a number of times the collocation occurs in a document of the first set of documents; determining a subset of the first set of documents to present to a user based on the scored collocations; providing one or more user interface elements to be used by a user to include and exclude documents from the first set of documents that contain at least one specified collocation of the collocations; receiving user input specifying inclusion or exclusion of documents from the first set of documents that contain at least one of the collocations; refining the first search query to produce a second query based on the user input; and providing a second set of documents responsive to the second query, where the second set of documents includes or excludes documents containing the specified collocation. | 15. A system, comprising: one or more computers configured to perform operations including: receiving a first search query including one or more search terms; providing a first set of documents responsive to the first query; determining one or more collocations from the first set of documents that include at least one of the search terms, each collocation including at least one other term that is semantically related to the at least one search term; scoring the collocations from the first set of documents, including determining a mutual information score for each collocation using a mutual information test; multiplying at least some collocation scores by frequency counts, a frequency count for a given collocation representing a number of times the collocation occurs in a document of the first set of documents; determining a subset of the first set of documents to present to a user based on the scored collocations; providing one or more user interface elements to be used by a user to include and exclude documents from the first set of documents that contain at least one specified collocation of the collocations; receiving user input specifying inclusion or exclusion of documents from the first set of documents that contain at least one of the collocations; refining the first search query to produce a second query based on the user input; and providing a second set of documents responsive to the second query, where the second set of documents includes or excludes documents containing the specified collocation. 19. The system of claim 15 , where the terms of at least some of the collocations are non-adjacent in at least one document in the first set of documents. | 0.654709 |
8,386,470 | 5 | 7 | 5. The information acquiring apparatus comprising: a display part configured to display an electronic document; a selection accepting part configured to accept a first character string from characters or a character string in a reading or inspecting document that is displayed on the display part; an index information acquiring part configured to acquire a second character string to be used as index information for searching the reading or inspecting document, based on identification information of the reading or inspecting document, and to delete the second character string that overlaps with the first character string from the index information; and a search control part configured to execute a search using the first character string and the second character string as search keywords, wherein the index information acquiring part extracts each word having an occurrence that is greater than a predetermined value with respect to the first character string from the index information as the second character string, and wherein: the index information acquiring part extracts at least one of the words having a co-occurrence that is greater than the predetermined value with respect to the first character string from a plurality of second character strings based on a co-occurrence management table that manages the co-occurrence for each combination of words in the index information as a third character string, and the search control part executes the search based on the first character string and the third character string. | 5. The information acquiring apparatus comprising: a display part configured to display an electronic document; a selection accepting part configured to accept a first character string from characters or a character string in a reading or inspecting document that is displayed on the display part; an index information acquiring part configured to acquire a second character string to be used as index information for searching the reading or inspecting document, based on identification information of the reading or inspecting document, and to delete the second character string that overlaps with the first character string from the index information; and a search control part configured to execute a search using the first character string and the second character string as search keywords, wherein the index information acquiring part extracts each word having an occurrence that is greater than a predetermined value with respect to the first character string from the index information as the second character string, and wherein: the index information acquiring part extracts at least one of the words having a co-occurrence that is greater than the predetermined value with respect to the first character string from a plurality of second character strings based on a co-occurrence management table that manages the co-occurrence for each combination of words in the index information as a third character string, and the search control part executes the search based on the first character string and the third character string. 7. The information acquiring apparatus as claimed in claim 5 , comprising: an advertising content searching part configured to search an advertising content based on at least one of the second and the third character strings, wherein the advertising content is displayed together with a search result the searching part. | 0.71223 |
9,507,576 | 3 | 4 | 3. The non-transitory computer readable storage media of claim 2 , wherein determining the cost of execution of the program with the conditional expression moved to the move destination comprises: determining a first provisional cost corresponding to the conditional expression being positive; and determining a second provisional cost corresponding to the conditional expression being negative, wherein the cost is a sum of the first provisional cost and the second provisional cost. | 3. The non-transitory computer readable storage media of claim 2 , wherein determining the cost of execution of the program with the conditional expression moved to the move destination comprises: determining a first provisional cost corresponding to the conditional expression being positive; and determining a second provisional cost corresponding to the conditional expression being negative, wherein the cost is a sum of the first provisional cost and the second provisional cost. 4. The non-transitory computer readable storage media of claim 3 , wherein the first provisional cost is based on a number of conditional expressions being true in response to the conditional expression being positive, and the second provisional cost is based on a number of conditional expressions being true in response to the conditional expression being negative. | 0.671147 |
7,797,638 | 1 | 7 | 1. A method for associating metadata to a document via flags, the method comprising: receiving a first document via a first software application user interface; providing at least one flag type for application to the first document, wherein the at least one flag type is independent of any file type; receiving a selection of a first flag for application to the first document, wherein the first flag is independent of a file type of the first document; saving metadata associated with the first flag to the first document, wherein the metadata points to the first flag that is independent of the file type of the first document in order to establish a peer reference relationship between the first document and the first flag; receiving a selection of an object that forms a portion of the first document; receiving a selection of a second flag for application to the object in the first document, wherein the second flag is independent of a file type of the embedded object; applying the second flag to the object; in response to applying the second flag to the object, indicating, with an icon in the document, that the object is an embedded flagged document object; saving metadata associated with the second flag to the embedded flagged document object of the first document, wherein the metadata points to the second flag that is independent of the file type of the embedded flagged document object in order to establish a peer reference relationship between the embedded flagged document object and the second flag; accessing a second document via a second software application user interface, wherein the second software application user interface is different than the first software application user interface; receiving a selection of a flag type via the second software application user interface; when the metadata associated with the first flag of the first document is of the selected flag type, displaying, on the second software application user interface, the metadata associated with the first flag of the first document; and when the metadata associated with the second flag of the first document is of the selected flag type, displaying, on the second software application user interface, the metadata associated with the second flag of the first document. | 1. A method for associating metadata to a document via flags, the method comprising: receiving a first document via a first software application user interface; providing at least one flag type for application to the first document, wherein the at least one flag type is independent of any file type; receiving a selection of a first flag for application to the first document, wherein the first flag is independent of a file type of the first document; saving metadata associated with the first flag to the first document, wherein the metadata points to the first flag that is independent of the file type of the first document in order to establish a peer reference relationship between the first document and the first flag; receiving a selection of an object that forms a portion of the first document; receiving a selection of a second flag for application to the object in the first document, wherein the second flag is independent of a file type of the embedded object; applying the second flag to the object; in response to applying the second flag to the object, indicating, with an icon in the document, that the object is an embedded flagged document object; saving metadata associated with the second flag to the embedded flagged document object of the first document, wherein the metadata points to the second flag that is independent of the file type of the embedded flagged document object in order to establish a peer reference relationship between the embedded flagged document object and the second flag; accessing a second document via a second software application user interface, wherein the second software application user interface is different than the first software application user interface; receiving a selection of a flag type via the second software application user interface; when the metadata associated with the first flag of the first document is of the selected flag type, displaying, on the second software application user interface, the metadata associated with the first flag of the first document; and when the metadata associated with the second flag of the first document is of the selected flag type, displaying, on the second software application user interface, the metadata associated with the second flag of the first document. 7. The method of claim 1 , wherein the first software application user interface is associated with a first software application, wherein the second software application user interface is association with a second software application, wherein the first software application and the second software application are disparate. | 0.6881 |
6,034,689 | 3 | 4 | 3. In a client system in communication with at least one remote server system, the client system being coupled to a display device. a method of navigating through an interactive display environment including a plurality of hypertext objects, the method comprising: receiving information corresponding to an image map from one of the server systems. The image map including at least one hypertext object having an address stored in one of the server systems and not in the client system. The address corresponding to one of the server systems and for accessing information stored in one of the server systems, causing the image map to be displayed on the display device, receiving a first user input that selects the image map, displaying a selection icon on the display device in response to the image map being selected according to the first user input; receiving a second user input entered from the remote input device specifying a movement of the selection icon; receiving a third user input entered from the remote input device specifying coordinates within the image map, the coordinates corresponding to a current position of the selection icon; and transmitting the coordinates specified by the third user input to one of the server systems in order to access information associated with the address. | 3. In a client system in communication with at least one remote server system, the client system being coupled to a display device. a method of navigating through an interactive display environment including a plurality of hypertext objects, the method comprising: receiving information corresponding to an image map from one of the server systems. The image map including at least one hypertext object having an address stored in one of the server systems and not in the client system. The address corresponding to one of the server systems and for accessing information stored in one of the server systems, causing the image map to be displayed on the display device, receiving a first user input that selects the image map, displaying a selection icon on the display device in response to the image map being selected according to the first user input; receiving a second user input entered from the remote input device specifying a movement of the selection icon; receiving a third user input entered from the remote input device specifying coordinates within the image map, the coordinates corresponding to a current position of the selection icon; and transmitting the coordinates specified by the third user input to one of the server systems in order to access information associated with the address. 4. A method according to claim 3, further comprising the steps of: scaling the image map down in size before causing the image map to be displayed, to format the image map for the display device; and scaling the coordinates specified by the third user input up before transmitting the coordinates. | 0.5 |
9,418,056 | 1 | 4 | 1. An authoring tool, embedded in a non-transitory tangible computer readable medium, the authoring tool comprising tools for: enabling an author to create and define a presentation of a wrap package by: (a) selecting a card type among a plurality of card types; (b) selecting a card template from one or more card templates of the selected card type; (c) creating a new card by authoring a copy of the selected card template; (d) creating a plurality of cards by repeating (a) through (c); and (e) defining a sequence order for viewing the plurality of cards, the presentation of the wrap package defined by (i) the plurality of cards as created and authored and (ii) the defined sequence order for viewing the plurality of cards; the authoring tool further comprising: generating a plurality of JSON card descriptors, each JSON card descriptor defining content, a structure and a layout of an associated one of the plurality of cards of the wrap package respectively; and generating a JSON wrap descriptor including the plurality of JSON card descriptors, wherein the JSON wrap descriptor is used by a runtime viewer at a consuming device to create a runtime instance of the wrap package having the same presentation as defined by the author, the runtime instance of the wrap package including the plurality of cards arranged to be viewed in the sequence order, wherein the presentation of the wrap package includes a set of cards, among the plurality of cards, each characterized by: a same size; a first aspect ratio; and content where the relative position of the content of each card in the set remains fixed, regardless of the size and/or type of display, associated with the consuming device. | 1. An authoring tool, embedded in a non-transitory tangible computer readable medium, the authoring tool comprising tools for: enabling an author to create and define a presentation of a wrap package by: (a) selecting a card type among a plurality of card types; (b) selecting a card template from one or more card templates of the selected card type; (c) creating a new card by authoring a copy of the selected card template; (d) creating a plurality of cards by repeating (a) through (c); and (e) defining a sequence order for viewing the plurality of cards, the presentation of the wrap package defined by (i) the plurality of cards as created and authored and (ii) the defined sequence order for viewing the plurality of cards; the authoring tool further comprising: generating a plurality of JSON card descriptors, each JSON card descriptor defining content, a structure and a layout of an associated one of the plurality of cards of the wrap package respectively; and generating a JSON wrap descriptor including the plurality of JSON card descriptors, wherein the JSON wrap descriptor is used by a runtime viewer at a consuming device to create a runtime instance of the wrap package having the same presentation as defined by the author, the runtime instance of the wrap package including the plurality of cards arranged to be viewed in the sequence order, wherein the presentation of the wrap package includes a set of cards, among the plurality of cards, each characterized by: a same size; a first aspect ratio; and content where the relative position of the content of each card in the set remains fixed, regardless of the size and/or type of display, associated with the consuming device. 4. The authoring tool of claim 1 , further comprising copying component(s) and attribute(s) of the selected card template when the new card is created. | 0.855364 |
8,886,011 | 3 | 4 | 3. The method of claim 1 , further comprising: receiving the question and a corresponding answer from a user interaction. | 3. The method of claim 1 , further comprising: receiving the question and a corresponding answer from a user interaction. 4. The method of claim 3 , further comprising: attaching at least one of an audio file and a video file to the video bitstream at the location of the question, wherein the audio file and the video file are associated with the corresponding answer. | 0.5 |
9,286,370 | 11 | 15 | 11. A computer-readable storage medium containing a program which, when executed, performs an operation to interleave dimensional and relational query constructs in a single, dimensional query, based on a report specification and a predetermined sequence and without introducing semantic inconsistencies, the operation comprising: receiving user indication of a plurality of query constructs to include in the report specification to retrieve a set of query results from a dimensional data model, wherein the report specification is expressed in a predefined reporting language of a higher level of abstraction than both a relational query language and a dimensional query language, wherein the dimensional data model includes a cube having a plurality of dimensions, at least one dimension including a hierarchy of members, wherein the plurality of query constructs includes the dimensional and relational query constructs; generating the single, dimensional query from the report specification by operation of the one or more computer processors when executing the program and based on the predetermined sequence of applying the plurality of query constructs in the single, dimensional query and based further on a plurality of mapping rules specifying how to map between the dimensional data model and a corresponding relational data model, in order to prevent one or more semantic inconsistencies in the set of query results when interleaving the dimensional and relational query constructs in the single, dimensional query; wherein the predetermined sequence specifies to arrange the plurality of query constructs in an order of application of: a dimensional slicer, a dimensional pre-aggregation detail filter, a relational post-aggregation detail filter, a dimensional set filtering operator, a dimensional suppression, a relational summary filter, a relational sort, and a relational summary operator; wherein the plurality of mapping rules includes a model mapping rule, a level mapping rule, a leaf mapping rule, a cell mapping rule, a ragged mapping rule, a fact mapping rule, and a child mapping rule; wherein the single, dimensional query is executed in order to generate the set of query results; and outputting the set of query results responsive to the report specification. | 11. A computer-readable storage medium containing a program which, when executed, performs an operation to interleave dimensional and relational query constructs in a single, dimensional query, based on a report specification and a predetermined sequence and without introducing semantic inconsistencies, the operation comprising: receiving user indication of a plurality of query constructs to include in the report specification to retrieve a set of query results from a dimensional data model, wherein the report specification is expressed in a predefined reporting language of a higher level of abstraction than both a relational query language and a dimensional query language, wherein the dimensional data model includes a cube having a plurality of dimensions, at least one dimension including a hierarchy of members, wherein the plurality of query constructs includes the dimensional and relational query constructs; generating the single, dimensional query from the report specification by operation of the one or more computer processors when executing the program and based on the predetermined sequence of applying the plurality of query constructs in the single, dimensional query and based further on a plurality of mapping rules specifying how to map between the dimensional data model and a corresponding relational data model, in order to prevent one or more semantic inconsistencies in the set of query results when interleaving the dimensional and relational query constructs in the single, dimensional query; wherein the predetermined sequence specifies to arrange the plurality of query constructs in an order of application of: a dimensional slicer, a dimensional pre-aggregation detail filter, a relational post-aggregation detail filter, a dimensional set filtering operator, a dimensional suppression, a relational summary filter, a relational sort, and a relational summary operator; wherein the plurality of mapping rules includes a model mapping rule, a level mapping rule, a leaf mapping rule, a cell mapping rule, a ragged mapping rule, a fact mapping rule, and a child mapping rule; wherein the single, dimensional query is executed in order to generate the set of query results; and outputting the set of query results responsive to the report specification. 15. The computer-readable storage medium of claim 11 , wherein the leaf mapping rule specifies to enforce referential integrity by verifying that each hierarchy leaf member has at least one corresponding record in a fact table. | 0.5 |
10,140,323 | 10 | 11 | 10. A computer program product comprising one or more hardware storage devices having thereon computer-executable instructions that are structured such that, when executed by one or more processors of a computing system, cause the computing system to: identify a plurality of logical data models that each corresponds to a physical data model, wherein each given logical data model of the plurality of logical data models includes a logical data model index corresponding to the given logical data model that is configured to index a plurality of queries and at least partial query results corresponding to each of the plurality of queries, the indexed queries comprising queries issued to the given logical data model, and wherein each logical data model of the plurality of logical data models includes a different semantic mapping set that maps at least one logical data model entity to at least one entity of the physical data model; receive a model query that identifies a particular logical data model of the plurality of logical data models; and in response to the received model query, access the logical data model index corresponding to the particular logical data model to determine whether results of the model query have been previously returned. | 10. A computer program product comprising one or more hardware storage devices having thereon computer-executable instructions that are structured such that, when executed by one or more processors of a computing system, cause the computing system to: identify a plurality of logical data models that each corresponds to a physical data model, wherein each given logical data model of the plurality of logical data models includes a logical data model index corresponding to the given logical data model that is configured to index a plurality of queries and at least partial query results corresponding to each of the plurality of queries, the indexed queries comprising queries issued to the given logical data model, and wherein each logical data model of the plurality of logical data models includes a different semantic mapping set that maps at least one logical data model entity to at least one entity of the physical data model; receive a model query that identifies a particular logical data model of the plurality of logical data models; and in response to the received model query, access the logical data model index corresponding to the particular logical data model to determine whether results of the model query have been previously returned. 11. The computer program product in accordance with claim 10 , wherein the computing system includes a cache configured to cache results of at least some model queries previously made to any of the plurality of logical data models. | 0.5 |
9,633,115 | 8 | 12 | 8. A computer program product to analyze a query and provisioning data to analytics, the computer program product including a computer readable storage medium having program instructions embodied therewith, wherein the computer readable storage medium is not a transitory signal per se, the program instructions executable by a processing circuit to cause the processing circuit to perform a method comprising: generating a user interface that displays a set of selectable terms from a glossary of business terms and generates, in response to selection of terms, a business metadata query that identifies at least one forum with a plurality of member profiles; generating from the business metadata query at least one module that identifies the at least one forum and an analytical processing environment; moving data from the at least one forum into the analytical processing environment by deploying the at least one module; performing, using the analytical processing environment, analytical operations on the data from the at least one forum; identifying metadata from a result of the analytical operations; and updating the glossary of business terms using the identified metadata. | 8. A computer program product to analyze a query and provisioning data to analytics, the computer program product including a computer readable storage medium having program instructions embodied therewith, wherein the computer readable storage medium is not a transitory signal per se, the program instructions executable by a processing circuit to cause the processing circuit to perform a method comprising: generating a user interface that displays a set of selectable terms from a glossary of business terms and generates, in response to selection of terms, a business metadata query that identifies at least one forum with a plurality of member profiles; generating from the business metadata query at least one module that identifies the at least one forum and an analytical processing environment; moving data from the at least one forum into the analytical processing environment by deploying the at least one module; performing, using the analytical processing environment, analytical operations on the data from the at least one forum; identifying metadata from a result of the analytical operations; and updating the glossary of business terms using the identified metadata. 12. The computer program product of claim 8 , wherein the method further comprises: receiving results in response to the performance of the analytical operations on the data; and sending the results to an analytical user interface. | 0.678273 |
8,161,066 | 2 | 18 | 2. A method for creating a semantic object to represent a target referent of an object type, the semantic object being stored on a computer readable medium, the method, comprising, creating the semantic object of a semantic object type to represent the target referent of the object type, the semantic object having multiple meta-tags that are each associable with metadata; wherein, the semantic object of the semantic object type is suitable to represent the object type of the target referent; associating a meta-tag of the multiple meta-tags with the metadata; wherein the meta-tag or the metadata is definable using an ontology; and extracting a portion of the content from the target referent for inclusion in the semantic object; subsequently determining that the target referent has been revised, updating metadata associated with one or more meta-taps of the multiple meta-taps of the semantic object based on the revision; wherein the extraction is part of a data mining performed on selected resources including the ontology or the Internet. sharing, with another user, the semantic object having included therein the portion of the content extracted from the target referent. | 2. A method for creating a semantic object to represent a target referent of an object type, the semantic object being stored on a computer readable medium, the method, comprising, creating the semantic object of a semantic object type to represent the target referent of the object type, the semantic object having multiple meta-tags that are each associable with metadata; wherein, the semantic object of the semantic object type is suitable to represent the object type of the target referent; associating a meta-tag of the multiple meta-tags with the metadata; wherein the meta-tag or the metadata is definable using an ontology; and extracting a portion of the content from the target referent for inclusion in the semantic object; subsequently determining that the target referent has been revised, updating metadata associated with one or more meta-taps of the multiple meta-taps of the semantic object based on the revision; wherein the extraction is part of a data mining performed on selected resources including the ontology or the Internet. sharing, with another user, the semantic object having included therein the portion of the content extracted from the target referent. 18. The method of claim 2 , wherein, the semantic object is stored on the computer readable medium as an XML object using RDF or another binary storage format. | 0.851955 |
8,843,466 | 9 | 11 | 9. The method of claim 1 , further comprising: generating one or more attribute suggestions for the search query, each attribute suggestion identifying an additional attribute associated with first entity type. | 9. The method of claim 1 , further comprising: generating one or more attribute suggestions for the search query, each attribute suggestion identifying an additional attribute associated with first entity type. 11. The method of claim 9 , further comprising: analyzing contents of each resource of a plurality of resources identified by the search results to identify references to attributes associated with entities of the particular type in the contents of the resource. | 0.700913 |
8,468,160 | 18 | 19 | 18. The computer readable storage medium of claim 17 , wherein the method further comprises extending the first set of tokens to create an extended first set of tokens and the second set of tokens to create an extended first set of tokens based on the received semantic knowledge. | 18. The computer readable storage medium of claim 17 , wherein the method further comprises extending the first set of tokens to create an extended first set of tokens and the second set of tokens to create an extended first set of tokens based on the received semantic knowledge. 19. The computer readable storage medium of claim 18 , wherein the method further comprises receiving a set of weight values related to the extended first and second sets of extended tokens and calculating a similarity score for the extended first and second sets of extended tokens based on the received weight values. | 0.5 |
7,873,223 | 34 | 44 | 34. A method comprising: specifying a class network having a class, wherein a membership function defines whether an object of a data network belongs to the class; specifying a process step having a domain and an algorithm, wherein the domain designates the class, and wherein the process step is part of a process hierarchy; receiving pixel values obtained from a digital image; receiving metadata relating to the digital image; and executing the class network and the process hierarchy on a computer that implements the data network by selectively linking a plurality of objects to the pixel values and to the metadata according to the class network and the process hierarchy, wherein the process step is linked to the metadata. | 34. A method comprising: specifying a class network having a class, wherein a membership function defines whether an object of a data network belongs to the class; specifying a process step having a domain and an algorithm, wherein the domain designates the class, and wherein the process step is part of a process hierarchy; receiving pixel values obtained from a digital image; receiving metadata relating to the digital image; and executing the class network and the process hierarchy on a computer that implements the data network by selectively linking a plurality of objects to the pixel values and to the metadata according to the class network and the process hierarchy, wherein the process step is linked to the metadata. 44. The method of claim 34 , further comprising: determining whether objects belonging to the class depict a target region on the digital image, wherein the digital image is a satellite image, and wherein the target region shows a ship. | 0.822021 |
8,775,844 | 1 | 6 | 1. A method comprising: detecting, by a computing device, a change to a power mode of the computing device; responsive to detecting the change to the power mode, processing, by the computing device and from among a set of elements within a page of content that each specify a respective portion of the content in accordance with a markup language, the page of content to identify one or more elements of the set of elements that each have at least one respective attribute designated to be modified in response to the change to the power mode; modifying, by the computing device and based on the change to the power mode, at least a portion of the at least one respective attribute of each of the identified one or more elements to associate the respective portion of the content specified by each of the identified one or more elements with a set of presentation properties; and rendering, by the computing device and for display in accordance with the set of presentation properties, the respective portion of the content specified by each of the identified one or more elements. | 1. A method comprising: detecting, by a computing device, a change to a power mode of the computing device; responsive to detecting the change to the power mode, processing, by the computing device and from among a set of elements within a page of content that each specify a respective portion of the content in accordance with a markup language, the page of content to identify one or more elements of the set of elements that each have at least one respective attribute designated to be modified in response to the change to the power mode; modifying, by the computing device and based on the change to the power mode, at least a portion of the at least one respective attribute of each of the identified one or more elements to associate the respective portion of the content specified by each of the identified one or more elements with a set of presentation properties; and rendering, by the computing device and for display in accordance with the set of presentation properties, the respective portion of the content specified by each of the identified one or more elements. 6. The method of claim 1 , wherein the change to the power mode is detected in response to the computing device transitioning from a full-power mode to a low-power mode. | 0.833004 |
9,786,277 | 6 | 7 | 6. The method of claim 1 , wherein the command review instructions instruct the second plurality of users to compare the first user-defined variant with model text language variants for the computer recognized command. | 6. The method of claim 1 , wherein the command review instructions instruct the second plurality of users to compare the first user-defined variant with model text language variants for the computer recognized command. 7. The method of claim 6 , wherein the command review instructions further includes the first user-defined variant and the computer recognized command alongside the model text language variants, the method further comprising: receiving an indication from each of the second plurality of users of whether the first user-defined variant is similar to one of the model text language variants. | 0.5 |
9,870,554 | 1 | 3 | 1. A method for managing computer-based documents, comprising: identifying, by a computing device using calendar information from a calendar program associated with a first participant, related events in the calendar program associated with the first participant, wherein the related events include a first event and a second event, wherein the first event is associated with a first time period on a specified day, wherein the first time period occurs in the present or in the future, wherein the second event is associated with a second time period, wherein the second time period occurred in the past, wherein the calendar program includes, for the first participant and for the specified day, first participant events including the first event, wherein the calendar information includes at least one of event title, event participant list, event tag, or event topic, and wherein the identification of the related events is made when at least some of the calendar information associated with the second event matches at least some of the calendar information associated with the first event; identifying a first document associated with the second event, wherein the first document was created, accessed, or modified by the first participant during the second time period, and wherein the first document is inaccessible by a second participant of the first event; creating, in a folder of a directory, a link to the first document, wherein the folder is a folder of the first participant and the folder is inaccessible to the second participant of the first event, wherein the folder is associated with the first event, and wherein the directory is part of a program other than the calendar program, is associated with the specified day, and includes respective folders for some of the first participant events including the folder associated with the first event; responsive to a selection of the specified day in the program, displaying the directory, the respective folders including the folder associated with the first event, and the link to the first document; and sharing, with a permission of the first participant, the folder and the link with the second participant of the first event. | 1. A method for managing computer-based documents, comprising: identifying, by a computing device using calendar information from a calendar program associated with a first participant, related events in the calendar program associated with the first participant, wherein the related events include a first event and a second event, wherein the first event is associated with a first time period on a specified day, wherein the first time period occurs in the present or in the future, wherein the second event is associated with a second time period, wherein the second time period occurred in the past, wherein the calendar program includes, for the first participant and for the specified day, first participant events including the first event, wherein the calendar information includes at least one of event title, event participant list, event tag, or event topic, and wherein the identification of the related events is made when at least some of the calendar information associated with the second event matches at least some of the calendar information associated with the first event; identifying a first document associated with the second event, wherein the first document was created, accessed, or modified by the first participant during the second time period, and wherein the first document is inaccessible by a second participant of the first event; creating, in a folder of a directory, a link to the first document, wherein the folder is a folder of the first participant and the folder is inaccessible to the second participant of the first event, wherein the folder is associated with the first event, and wherein the directory is part of a program other than the calendar program, is associated with the specified day, and includes respective folders for some of the first participant events including the folder associated with the first event; responsive to a selection of the specified day in the program, displaying the directory, the respective folders including the folder associated with the first event, and the link to the first document; and sharing, with a permission of the first participant, the folder and the link with the second participant of the first event. 3. The method of claim 1 wherein identifying the first document further comprises: comparing text included in the first document with an event title of the second event. | 0.793399 |
8,359,285 | 15 | 16 | 15. The method of claim 9 , further comprising the step of rendering for display at least one of the subset of user submitted queries to a user seeking an item from the item category. | 15. The method of claim 9 , further comprising the step of rendering for display at least one of the subset of user submitted queries to a user seeking an item from the item category. 16. The method of claim 15 , further comprising the step of rendering for display at least one item review relevant to the displayed at least one user submitted query. | 0.638528 |
10,049,668 | 1 | 2 | 1. A non-transitory computer-readable medium having instructions stored thereon, the instructions, when executed by one or more processors, cause the one or more processors to: receive speech input; traverse, based on the speech input, a sequence of states and arcs of a weighted finite state transducer (WFST), wherein: the sequence of states and arcs represents one or more history candidate words and a current candidate word; and a first probability of the candidate word given the one or more history candidate words is determined by traversing the sequence of states and arcs of the WFST; traverse a negating finite state transducer (FST), wherein traversing the negating FST negates the first probability of the candidate word given the one or more history candidate words; compose a virtual FST using a neural network language model and based on the sequence of states and arcs of the WFST, wherein one or more virtual states of the virtual FST represent the current candidate word; traverse the one or more virtual states of the virtual FST, wherein a second probability of the candidate word given the one or more history candidate words is determined by traversing the one or more virtual states of the virtual FST; determine, based on the second probability of the candidate word given the one or more history candidate words, text corresponding to the speech input; based on the determined text, perform one or more tasks to obtain a result; and cause the result to be presented in spoken or visual form. | 1. A non-transitory computer-readable medium having instructions stored thereon, the instructions, when executed by one or more processors, cause the one or more processors to: receive speech input; traverse, based on the speech input, a sequence of states and arcs of a weighted finite state transducer (WFST), wherein: the sequence of states and arcs represents one or more history candidate words and a current candidate word; and a first probability of the candidate word given the one or more history candidate words is determined by traversing the sequence of states and arcs of the WFST; traverse a negating finite state transducer (FST), wherein traversing the negating FST negates the first probability of the candidate word given the one or more history candidate words; compose a virtual FST using a neural network language model and based on the sequence of states and arcs of the WFST, wherein one or more virtual states of the virtual FST represent the current candidate word; traverse the one or more virtual states of the virtual FST, wherein a second probability of the candidate word given the one or more history candidate words is determined by traversing the one or more virtual states of the virtual FST; determine, based on the second probability of the candidate word given the one or more history candidate words, text corresponding to the speech input; based on the determined text, perform one or more tasks to obtain a result; and cause the result to be presented in spoken or visual form. 2. The non-transitory computer-readable medium of claim 1 , wherein the virtual FST is composed after traversing the sequence of states and arcs of the WFST. | 0.896438 |
8,315,484 | 1 | 27 | 1. A method for resolving contradicting output data from an Optical Character Recognition (OCR) system, wherein the output data comprises at least one word with at least one uncertainly recognized character, wherein the at least one uncertainly recognized character is reported in the output data together with probable alternatives for the at least one uncertainly recognized character, and the words wherein the at least one uncertainly recognized character has been encountered in an image of a text being processed by the OCR system, the method comprises the steps of: using an Internet search engine with search arguments established according to a search strategy comprising: a) providing initial search arguments by forming spelling alternatives for the words comprising the at least one uncertainly recognized character by substituting the at least one uncertainly recognized character with the reported probable alternatives for the at least one character, one by one, and in possible combinations in each encountered word, or by removing a character, thereby forming a plurality of spelling alternatives, and then measuring and recording number of hits for search results of each respective spelling alternative that has been formed in this manner, b) comparing the measured number of hits for each of the spelling alternatives with an upper predefined relative threshold level and a lower predefined relative threshold level, wherein each of the respective comparisons of the plurality of measurements falls into one of three possible outcomes: i) if the measurement of a spelling alternative is above the predefined relative upper threshold level, the corresponding spelling alternative for this measurement is the correct spelling alternative for the word, and terminating the Internet search, ii) if the measurement of a spelling alternative is below the lower predefined relative threshold level, the corresponding spelling alternative for this measurement is deemed non- existing, and the word with this spelling alternative is discarded from further investigations, and continuing with other spelling alternatives that has been formed as search arguments for the Internet search engine, iii) if the measurement of a spelling alternative falls between the upper relative threshold level and the lower relative threshold level, exit the Internet search engine and modifying the search strategy providing further search arguments as a combination of members of the remaining spelling alternatives and other words encountered in the document, other character alternatives for the at least one uncertainly recognized character, phrases, adapting the upper relative threshold level, adapting the lower relative threshold level, and/or other information related to the output data from the OCR system, before continuing using the search strategy providing further measurements and comparisons for resolving the contradicting output data, c) continuing processing step b) a number of predefined times, or until there is only one spelling alternative left, whatever occurs first, providing an iteration amongst a plurality of different search arguments used in the search strategy before terminating step b), and using the remaining spelling alternative having the highest measurement above the upper relative threshold level as the correct spelling alternative. | 1. A method for resolving contradicting output data from an Optical Character Recognition (OCR) system, wherein the output data comprises at least one word with at least one uncertainly recognized character, wherein the at least one uncertainly recognized character is reported in the output data together with probable alternatives for the at least one uncertainly recognized character, and the words wherein the at least one uncertainly recognized character has been encountered in an image of a text being processed by the OCR system, the method comprises the steps of: using an Internet search engine with search arguments established according to a search strategy comprising: a) providing initial search arguments by forming spelling alternatives for the words comprising the at least one uncertainly recognized character by substituting the at least one uncertainly recognized character with the reported probable alternatives for the at least one character, one by one, and in possible combinations in each encountered word, or by removing a character, thereby forming a plurality of spelling alternatives, and then measuring and recording number of hits for search results of each respective spelling alternative that has been formed in this manner, b) comparing the measured number of hits for each of the spelling alternatives with an upper predefined relative threshold level and a lower predefined relative threshold level, wherein each of the respective comparisons of the plurality of measurements falls into one of three possible outcomes: i) if the measurement of a spelling alternative is above the predefined relative upper threshold level, the corresponding spelling alternative for this measurement is the correct spelling alternative for the word, and terminating the Internet search, ii) if the measurement of a spelling alternative is below the lower predefined relative threshold level, the corresponding spelling alternative for this measurement is deemed non- existing, and the word with this spelling alternative is discarded from further investigations, and continuing with other spelling alternatives that has been formed as search arguments for the Internet search engine, iii) if the measurement of a spelling alternative falls between the upper relative threshold level and the lower relative threshold level, exit the Internet search engine and modifying the search strategy providing further search arguments as a combination of members of the remaining spelling alternatives and other words encountered in the document, other character alternatives for the at least one uncertainly recognized character, phrases, adapting the upper relative threshold level, adapting the lower relative threshold level, and/or other information related to the output data from the OCR system, before continuing using the search strategy providing further measurements and comparisons for resolving the contradicting output data, c) continuing processing step b) a number of predefined times, or until there is only one spelling alternative left, whatever occurs first, providing an iteration amongst a plurality of different search arguments used in the search strategy before terminating step b), and using the remaining spelling alternative having the highest measurement above the upper relative threshold level as the correct spelling alternative. 27. The method according to claim 1 , wherein a merit function is used to define a measurement for the number of hits as: totscore ( i ) = a ′ CRS word ( i ) + b ′ ( 1 - min ( CRS i ) ) - c ′ 1 - ∑ k = 1 nchar Δ CRS i , k nchar + d ′ f ( rBest ( i ) phrase , rBest ( i ) single word , rBest ( i ) mult word ) wherein a′+b′+c′+d′=1, CRS word (i) is a character score value from the OCR process related to the spelling alternative i, the second term is the minimum CRS for all the characters in the word, the third term is the sum of the CRS difference between the highest CRS for each character and the CRS using word(i), f is a minimum or maximum function of the upper threshold or lower threshold values as defined: acceptance ( i ) ⇔ # hits i ∑ i = 1 n # hits i ≥ γ ( # hits ) wherein i denotes one of the spelling alternatives, #hits i is the measured number of hits for spelling alternative i, the denominator is the total measured number of hits for all spelling alternatives, and γ(#hits) is a threshold level that is a function of the number hits; and nchar is the number of characters in the word i. | 0.5 |
8,135,125 | 7 | 13 | 7. A method executing on a processor of a computing device for aggregating contextual information relating to several clients and analyzing the aggregation, comprising: initializing a communication channel between a service provider and at least one client; wherein the communication channel is used to transmit contextual data packets and conversational data packets; establishing between the service provider and the at least one client a predefined structured hierarchy to use to transmit contextual information; wherein the predefined structured hierarchy is used to transmit the contextual information; receiving multiple sets of contextual information from the at least one client and other clients; aggregating the received contextual information; determining when the aggregated contextual information meets a threshold and based on the determination determining when to receive and aggregate more contextual information and when to generate an event; during the aggregating, identifying levels of relevancy of the received contextual information; upon detecting that the aggregated contextual information meets its corresponding threshold, generating an event and clearing the aggregated contextual information and the threshold for a new analysis; and providing the generated event. | 7. A method executing on a processor of a computing device for aggregating contextual information relating to several clients and analyzing the aggregation, comprising: initializing a communication channel between a service provider and at least one client; wherein the communication channel is used to transmit contextual data packets and conversational data packets; establishing between the service provider and the at least one client a predefined structured hierarchy to use to transmit contextual information; wherein the predefined structured hierarchy is used to transmit the contextual information; receiving multiple sets of contextual information from the at least one client and other clients; aggregating the received contextual information; determining when the aggregated contextual information meets a threshold and based on the determination determining when to receive and aggregate more contextual information and when to generate an event; during the aggregating, identifying levels of relevancy of the received contextual information; upon detecting that the aggregated contextual information meets its corresponding threshold, generating an event and clearing the aggregated contextual information and the threshold for a new analysis; and providing the generated event. 13. The method of claim 7 , wherein the threshold corresponds to a predetermined period. | 0.747126 |
9,805,023 | 1 | 2 | 1. A device comprising: at least one processor; a display accessible to the at least one processor; and storage accessible to the at least one processor and bearing instructions executable by the at least one processor to: store a first phrase from a sent message for presentation of the first phrase again during a subsequent composition of a second message, wherein the first phrase from the sent message that is stored comprises a variable when stored that will be replaced in the second message with at least one character for a particular recipient during composition of the second message; and identify the first phrase for presentation during composition of the second message; and present, on the display and during composition of the second message, the first phrase. | 1. A device comprising: at least one processor; a display accessible to the at least one processor; and storage accessible to the at least one processor and bearing instructions executable by the at least one processor to: store a first phrase from a sent message for presentation of the first phrase again during a subsequent composition of a second message, wherein the first phrase from the sent message that is stored comprises a variable when stored that will be replaced in the second message with at least one character for a particular recipient during composition of the second message; and identify the first phrase for presentation during composition of the second message; and present, on the display and during composition of the second message, the first phrase. 2. The device of claim 1 , wherein the instructions are executable by the at least one processor to: present, on the display, a settings user interface (UI) that comprises an option selectable to edit phrases which are to be presented in the future during composition of messages that will be composed in the future. | 0.522659 |
9,836,508 | 10 | 12 | 10. A system comprising: a memory for storing data and computer-executable instructions; and at least one processor configured to access the memory, wherein the at least one processor is further configured to execute the computer-executable instructions to cause the system to perform a method comprising: associating external query data having one or more query field values with a record in a linked hierarchical database, the linked hierarchical database comprising a plurality of records, each record having a record identifier and representing an entity in a hierarchy, each record associated with a hierarchy level, each record comprising one or more fields, each field configured to contain a field value, the associating comprising: receiving the external query data, wherein the external query data comprises one or more search values; and identifying, from the plurality of records in the linked hierarchical database, one or more matched fields having field values that at least partially match the one or more search values; scoring, with zero or more match weights, each of the one or more matched fields; determining an aggregate weight for each matched field based at least in part on the scoring with the zero or more match weights; merging, based at least in part on determining the aggregate weights, the one or more matched fields to form a merged table having records with matched fields; scoring the merged table based at least in part on the aggregate weights; and outputting, based at least in part on the scoring of the merged table, a record identifier corresponding to a matching entity in the hierarchy. | 10. A system comprising: a memory for storing data and computer-executable instructions; and at least one processor configured to access the memory, wherein the at least one processor is further configured to execute the computer-executable instructions to cause the system to perform a method comprising: associating external query data having one or more query field values with a record in a linked hierarchical database, the linked hierarchical database comprising a plurality of records, each record having a record identifier and representing an entity in a hierarchy, each record associated with a hierarchy level, each record comprising one or more fields, each field configured to contain a field value, the associating comprising: receiving the external query data, wherein the external query data comprises one or more search values; and identifying, from the plurality of records in the linked hierarchical database, one or more matched fields having field values that at least partially match the one or more search values; scoring, with zero or more match weights, each of the one or more matched fields; determining an aggregate weight for each matched field based at least in part on the scoring with the zero or more match weights; merging, based at least in part on determining the aggregate weights, the one or more matched fields to form a merged table having records with matched fields; scoring the merged table based at least in part on the aggregate weights; and outputting, based at least in part on the scoring of the merged table, a record identifier corresponding to a matching entity in the hierarchy. 12. The system of claim 10 , wherein the at least one processor is further configured to execute the computer-executable instructions to cause the system to perform the method further comprising: sorting the one or more matched fields according to the determined aggregate weights; at least partially forming one or more search tables corresponding to the one or more search values; and at least partially forming one or more base tables corresponding to the one or more fields of the plurality of records of the linked hierarchical database; and wherein the merging, based at least in part on determining the aggregate weights, comprises combining at least a portion of the one or more search tables and the one or more base tables to form the merged table; and wherein the one or more search tables comprise zero or more common fields, and wherein the one or more base tables comprise zero or more common fields, and wherein the one or more base tables comprise record identifiers for each entity in the hierarchy. | 0.589992 |
8,150,676 | 13 | 18 | 13. A computer system comprising: at least one memory; and at least one controller, coupled to the at least one memory, that: accesses, from the at least one memory, human-language text automatically generated using at least one template that includes at least some fixed text and at least one tag that serves as a placeholder to be filled in with automatically generated text; identifies instances of at least one portion of the human-language text appearing multiple times in the human language text; and automatically generates output text in a human-readable language at least in part by substituting one or more synonyms of the at least one portion for one or more of the identified instances of the at least one portion in the human-language text; wherein the one or more synonyms comprises a first synonym; wherein the at least one controller identifies instances of the at least one portion at least in part by identifying two instances of the at least one portion that appear in close proximity to each other in the human-language text; wherein substituting the one or more synonyms comprises substituting the first synonym for one of the two identified instances of the at least one portion in the human-language text; and wherein identifying the two instances of the at least one portion comprises identifying two instances that appear within a threshold number of characters or words of one another in the human-language text. | 13. A computer system comprising: at least one memory; and at least one controller, coupled to the at least one memory, that: accesses, from the at least one memory, human-language text automatically generated using at least one template that includes at least some fixed text and at least one tag that serves as a placeholder to be filled in with automatically generated text; identifies instances of at least one portion of the human-language text appearing multiple times in the human language text; and automatically generates output text in a human-readable language at least in part by substituting one or more synonyms of the at least one portion for one or more of the identified instances of the at least one portion in the human-language text; wherein the one or more synonyms comprises a first synonym; wherein the at least one controller identifies instances of the at least one portion at least in part by identifying two instances of the at least one portion that appear in close proximity to each other in the human-language text; wherein substituting the one or more synonyms comprises substituting the first synonym for one of the two identified instances of the at least one portion in the human-language text; and wherein identifying the two instances of the at least one portion comprises identifying two instances that appear within a threshold number of characters or words of one another in the human-language text. 18. The computer system of claim 13 , wherein the at least one template comprises the one or more synonyms. | 0.773305 |
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