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9,553,922 | 11 | 19 | 11. A non-transitory computer readable storage medium storing program code for presenting social media content items associated with time-based media events, the program when executed by at least one processor causing the processor to: generate a graph interface element including a set of positions along a time axis, where each position is associated with a different portion of a broadcasted media event, the graph interface element depicting a measure of a plurality of content items that are authored by one or more users of a social networking system and that have been determined to be correlated with the portions of the broadcasted media event associated with the set of positions; generate a movable interface element that enables selection among the set of positions included in the graph interface element; populate a content timeline interface element with the plurality of content items arranged in chronological order, each portion of the content timeline interface element including content items correlated with a different portion of the broadcasted media event; provide a concurrent display of the content timeline interface element, the graph interface element, and the movable interface element; determine selection of a first of the set of positions based on the movable interface element having been visually moved to select the first position; and in response to the selection of the first position, cause the provided content timeline interface element to vertically scroll to a first portion of the content timeline interface element that includes content items correlated with a first portion of the broadcasted media event associated with the selected first position; extract non-textual content from a plurality of the content items correlated with the first portion of the broadcasted media event; combine the extracted non-textual content to generate a vignette representing the first portion of the broadcasted media event; and include the vignette in a visually distinct portion of the concurrent display. | 11. A non-transitory computer readable storage medium storing program code for presenting social media content items associated with time-based media events, the program when executed by at least one processor causing the processor to: generate a graph interface element including a set of positions along a time axis, where each position is associated with a different portion of a broadcasted media event, the graph interface element depicting a measure of a plurality of content items that are authored by one or more users of a social networking system and that have been determined to be correlated with the portions of the broadcasted media event associated with the set of positions; generate a movable interface element that enables selection among the set of positions included in the graph interface element; populate a content timeline interface element with the plurality of content items arranged in chronological order, each portion of the content timeline interface element including content items correlated with a different portion of the broadcasted media event; provide a concurrent display of the content timeline interface element, the graph interface element, and the movable interface element; determine selection of a first of the set of positions based on the movable interface element having been visually moved to select the first position; and in response to the selection of the first position, cause the provided content timeline interface element to vertically scroll to a first portion of the content timeline interface element that includes content items correlated with a first portion of the broadcasted media event associated with the selected first position; extract non-textual content from a plurality of the content items correlated with the first portion of the broadcasted media event; combine the extracted non-textual content to generate a vignette representing the first portion of the broadcasted media event; and include the vignette in a visually distinct portion of the concurrent display. 19. The computer readable storage medium of claim 11 , wherein the program when executed by the computer processor further causes the processor to generate a mute interface element that, when selected, prevents the displayed content timeline interface element from being updated with new content items correlated with the broadcasted media event. | 0.795266 |
9,245,523 | 13 | 14 | 13. The method according to claim 12 wherein selecting the words from the list of candidate term expansion words is performed by comparing between the frequencies of the words on the list of term expansion words and the frequency of the search term. | 13. The method according to claim 12 wherein selecting the words from the list of candidate term expansion words is performed by comparing between the frequencies of the words on the list of term expansion words and the frequency of the search term. 14. The method according to claim 13 wherein the frequency of a word on the list of term expansion words is the summation of all the frequencies of keywords within the associated topic that share the same stem form as the word on the list of term expansion words. | 0.829884 |
8,661,407 | 9 | 11 | 9. A method of supporting programming of embedded systems comprising: providing a framework, wherein the framework comprises at least one class library, at least one class, and a runtime environment for executing embedded systems applications; receiving at least one request for a new class relating to an embedded system function, wherein the embedded system function is in a low-level language, wherein the at least one request for a new class includes receiving a request generated from metadata to insert metadata into the native code or operating system of an embedded system; generating a service descriptor from the metadata, wherein the service descriptor comprises a Web Service Description Language (WSDL) description; generating the new class from the WSDL description, wherein the new class is in a high-level language based at least in part on the received request, and the new class does not include the low-level language; and inserting the new class in the framework. | 9. A method of supporting programming of embedded systems comprising: providing a framework, wherein the framework comprises at least one class library, at least one class, and a runtime environment for executing embedded systems applications; receiving at least one request for a new class relating to an embedded system function, wherein the embedded system function is in a low-level language, wherein the at least one request for a new class includes receiving a request generated from metadata to insert metadata into the native code or operating system of an embedded system; generating a service descriptor from the metadata, wherein the service descriptor comprises a Web Service Description Language (WSDL) description; generating the new class from the WSDL description, wherein the new class is in a high-level language based at least in part on the received request, and the new class does not include the low-level language; and inserting the new class in the framework. 11. A method according to claim 9 , which further comprises providing a license to access the framework. | 0.86423 |
5,475,733 | 11 | 13 | 11. An apparatus for relaying a call between a telephone device for the deaf (TDD) and other users, comprising: means for automatically prompting a TDD caller for calling information; means for receiving caller entered prose calling information; means for automatically analyzing the received prose calling information in a language-identifying parsing routine for parsing prose; means for automatically selecting a communication assistant capable of using a language identified in the analyzing means; and automatically routing the call to the selected communication assistant. | 11. An apparatus for relaying a call between a telephone device for the deaf (TDD) and other users, comprising: means for automatically prompting a TDD caller for calling information; means for receiving caller entered prose calling information; means for automatically analyzing the received prose calling information in a language-identifying parsing routine for parsing prose; means for automatically selecting a communication assistant capable of using a language identified in the analyzing means; and automatically routing the call to the selected communication assistant. 13. An apparatus as in claim 11, wherein the means for analyzing includes a plurality of means for parsing the prose calling information each in one of a plurality of languages and selecting a language from the successful one of said parser means. | 0.639942 |
7,617,232 | 13 | 21 | 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. 21. The system of claim 13 wherein the processor is configured to execute computer-executable instructions to allow a user in the organization to approve the term for the project in response to linking the received data representing the term with the received data representing the project in the memory area. | 0.677453 |
4,706,212 | 2 | 3 | 2. A method according to claim 1 including the steps of: storing a dictionary of high frequency source words and associated offset address linkages, the offset address linkages identifying the storage location of grammar and meaning information for the source words; storing a dictionary of low frequency source words in association with grammar code meanings for each word; comparing the source language text words with the high frequency dictionary words and upon detecting an equality with a word, storing the word and associated offset address linkages together in a high frequency file; and comparing the source language text words with the low frequency dictionary words and upon detecting an equality, storing the word and the associated grammar code meanings in a low frequency file. | 2. A method according to claim 1 including the steps of: storing a dictionary of high frequency source words and associated offset address linkages, the offset address linkages identifying the storage location of grammar and meaning information for the source words; storing a dictionary of low frequency source words in association with grammar code meanings for each word; comparing the source language text words with the high frequency dictionary words and upon detecting an equality with a word, storing the word and associated offset address linkages together in a high frequency file; and comparing the source language text words with the low frequency dictionary words and upon detecting an equality, storing the word and the associated grammar code meanings in a low frequency file. 3. A method according to claim 2 including the step of merging the words of the high and low frequency files together. | 0.964734 |
9,141,607 | 13 | 18 | 13. A non-transitory computer-readable storage device having instructions stored thereon that, when executed by a computing device, cause the computing device to perform operations comprising: performing a first optical character recognition process with an optical character recognition engine on one or more pages of a document to generate a first output response for each of multiple writing systems that each comprise a character set that is associated with one or more natural languages, wherein the first optical character recognition process uses a first configuration of the optical character recognition engine, and wherein the first configuration of the optical character recognition engine configures the optical character recognition engine to recognize, for each of the writing systems, a limited subset of characters from the character set of the writing system; using a trained classifier to identify, from among the multiple writing systems, a dominant writing system of the document based on the first output responses generated by the first optical character recognition process; after identifying the dominant writing system of the document and before selecting a dominant natural language of the document, reconfiguring the optical character recognition engine from the first configuration to a second configuration that is different from the first configuration, wherein the second configuration of the optical character recognition engine configures the optical character recognition engine to recognize the full character set that is associated with the one or more natural languages associated with the dominant writing system of the document; performing a second optical character recognition process with the reconfigured optical character recognition engine on one or more pages of the document to generate a second output response, wherein the second optical character recognition process uses the second configuration of the optical character recognition engine; and selecting the dominant natural language from the one or more natural languages associated with the dominant writing system by applying one or more statistical language models to the second output response. | 13. A non-transitory computer-readable storage device having instructions stored thereon that, when executed by a computing device, cause the computing device to perform operations comprising: performing a first optical character recognition process with an optical character recognition engine on one or more pages of a document to generate a first output response for each of multiple writing systems that each comprise a character set that is associated with one or more natural languages, wherein the first optical character recognition process uses a first configuration of the optical character recognition engine, and wherein the first configuration of the optical character recognition engine configures the optical character recognition engine to recognize, for each of the writing systems, a limited subset of characters from the character set of the writing system; using a trained classifier to identify, from among the multiple writing systems, a dominant writing system of the document based on the first output responses generated by the first optical character recognition process; after identifying the dominant writing system of the document and before selecting a dominant natural language of the document, reconfiguring the optical character recognition engine from the first configuration to a second configuration that is different from the first configuration, wherein the second configuration of the optical character recognition engine configures the optical character recognition engine to recognize the full character set that is associated with the one or more natural languages associated with the dominant writing system of the document; performing a second optical character recognition process with the reconfigured optical character recognition engine on one or more pages of the document to generate a second output response, wherein the second optical character recognition process uses the second configuration of the optical character recognition engine; and selecting the dominant natural language from the one or more natural languages associated with the dominant writing system by applying one or more statistical language models to the second output response. 18. The storage device of claim 13 , wherein performing the first optical character recognition process with the optical character recognition engine on one or more pages of the document to generate the multiple first output responses, and performing the second optical character recognition process with the reconfigured optical character recognition engine on one or more pages of the document to generate the second output response comprises: performing the first optical character recognition process and the second optical character recognition process on the same one or more pages of the document. | 0.65991 |
8,024,334 | 12 | 15 | 12. A computer system, relating to creating and maintaining, in at least one database available to a population of users, on a database server computer, information about a plurality of database of subjects, comprising: a) at least one computer processor structured and arranged to associate with each database subject of such plurality of database subjects at least one plurality of natural-language tags potentially descriptive of such each database subject according to an involved subset of such population of database users; said at least one plurality of natural language tags comprising other user chosen and/or other user provided natural language terms potentially descriptive of a subject or subjects of said database; b) at least one computer processor structured and arranged to assess, from input from at least one particular database user, at least one measure of descriptive relevance of each of such at least one plurality of natural-language tags to such each database subject according to each particular database user of such involved subset of such population of database users; c) at least one computer processor structured and arranged to associatively index, in such at least one database, such respective particular database users, such respective natural-language tags, such respective measures of relevance, and such respective database subjects; and d) accumulating and storing such respective measures of relevance. | 12. A computer system, relating to creating and maintaining, in at least one database available to a population of users, on a database server computer, information about a plurality of database of subjects, comprising: a) at least one computer processor structured and arranged to associate with each database subject of such plurality of database subjects at least one plurality of natural-language tags potentially descriptive of such each database subject according to an involved subset of such population of database users; said at least one plurality of natural language tags comprising other user chosen and/or other user provided natural language terms potentially descriptive of a subject or subjects of said database; b) at least one computer processor structured and arranged to assess, from input from at least one particular database user, at least one measure of descriptive relevance of each of such at least one plurality of natural-language tags to such each database subject according to each particular database user of such involved subset of such population of database users; c) at least one computer processor structured and arranged to associatively index, in such at least one database, such respective particular database users, such respective natural-language tags, such respective measures of relevance, and such respective database subjects; and d) accumulating and storing such respective measures of relevance. 15. The computer system, according to claim 12 , further comprising: a) at least one (analyzing) computer processor structured and arranged to accumulate, store, and analyze all associations, including subject categorizations, of such overall measures of relevance of such plurality of natural-language tags associated with such database subjects; and b) at least one (categories) computer processor structured and arranged to determine preferred such natural-language tags, according to such population of users, relating to selected categories of subjects. | 0.500894 |
10,156,965 | 6 | 8 | 6. A system for configuring a data contract definition for universal tag collection using a graphical user interface, comprising: a universal tag configuration subsystem comprising: a console server operable to: generate the graphical user interface for creating and managing the universal tags; display the graphical user interface at a client machine; and receive via the graphical user interface: a selection of a data provider with universal tag availability, and one or more of a plurality of domain names; and an event inspector tool for generating an event inspector panel on the graphical user interface in response to receiving the selection of the one or more domain names, wherein the event inspector tool is configured to receive data contract definitions, each data contract definition specifying: events and corresponding event data to collect from a designated website accessed by a plurality of end users at corresponding end user devices, and transformation rules and taxonomy rules for interpreting the collected event data to generate end user profiles corresponding to the plurality of end users, the end user profiles including key-value pairs and categorizations; wherein the event inspector tool receives event data contract definitions by: receiving a selection of an event bookmarklet to store onto a bookmark bar of a designated website corresponding to the one or more domain names; receiving a URL corresponding to a first page of the designated website for event capture from end users who access such designated website; receiving a selection of the event bookmarklet on the bookmark bar; displaying the event inspector panel in response to the selection of the event bookmarklet, wherein the event inspector panel is overlaid on the first page and displays any previously captured event data for any events that were previously added for such first page; receiving, via the event inspector panel, input for configuring the data contract definition including adding new events for causing event data for each new event to be captured from a plurality of end users who access the first page, wherein the data contract definition is stored as a corresponding updated data contract in a database of the universal tag configuration subsystem; a first presentation server operable to: identify the updated data contract in the database; receive the updated data contract from the database; generate runtime code instructions based on the updated data contract; and a runtime subsystem comprising: a profile server for storing the end user profiles; and a second presentation server operable to: receive the runtime code from the first presentation server to instantiate a runtime endpoint, capture, at runtime, event data from the designated website, the event data specified by the data contract definition, wherein capturing the event data includes providing a universal tag script, via the second presentation server, for running in the context of the designated website to instantiate a universal tag to: collect event data from the designated website, and report the collected event data to the runtime endpoint for applying the transformation and taxonomy rules; apply the transformation and taxonomy rules to the collected event data by performing an iterative loop via the runtime endpoint on the second presentation server, the iterative loop comprising: automatically determining, via a data provider servlet application, a list of runtime transformation applications corresponding to data contracts corresponding to a particular provider ID; performing, via a runtime transform application, the appropriate transformations on event-value pairs; and for each event-value pair, return a key-value pair and appropriate category identification for storage at a runtime user profile application; categorize the transformed event data based on the applied taxonomy rules, and store the transformed event data in the corresponding user profile at the profile server; wherein the system is further configured to display, at the client machine, a data provider configuration page corresponding to the designated website, wherein the data provider configuration page is refreshed with captured event data from the plurality of end users, the event data corresponding to previously specified events. | 6. A system for configuring a data contract definition for universal tag collection using a graphical user interface, comprising: a universal tag configuration subsystem comprising: a console server operable to: generate the graphical user interface for creating and managing the universal tags; display the graphical user interface at a client machine; and receive via the graphical user interface: a selection of a data provider with universal tag availability, and one or more of a plurality of domain names; and an event inspector tool for generating an event inspector panel on the graphical user interface in response to receiving the selection of the one or more domain names, wherein the event inspector tool is configured to receive data contract definitions, each data contract definition specifying: events and corresponding event data to collect from a designated website accessed by a plurality of end users at corresponding end user devices, and transformation rules and taxonomy rules for interpreting the collected event data to generate end user profiles corresponding to the plurality of end users, the end user profiles including key-value pairs and categorizations; wherein the event inspector tool receives event data contract definitions by: receiving a selection of an event bookmarklet to store onto a bookmark bar of a designated website corresponding to the one or more domain names; receiving a URL corresponding to a first page of the designated website for event capture from end users who access such designated website; receiving a selection of the event bookmarklet on the bookmark bar; displaying the event inspector panel in response to the selection of the event bookmarklet, wherein the event inspector panel is overlaid on the first page and displays any previously captured event data for any events that were previously added for such first page; receiving, via the event inspector panel, input for configuring the data contract definition including adding new events for causing event data for each new event to be captured from a plurality of end users who access the first page, wherein the data contract definition is stored as a corresponding updated data contract in a database of the universal tag configuration subsystem; a first presentation server operable to: identify the updated data contract in the database; receive the updated data contract from the database; generate runtime code instructions based on the updated data contract; and a runtime subsystem comprising: a profile server for storing the end user profiles; and a second presentation server operable to: receive the runtime code from the first presentation server to instantiate a runtime endpoint, capture, at runtime, event data from the designated website, the event data specified by the data contract definition, wherein capturing the event data includes providing a universal tag script, via the second presentation server, for running in the context of the designated website to instantiate a universal tag to: collect event data from the designated website, and report the collected event data to the runtime endpoint for applying the transformation and taxonomy rules; apply the transformation and taxonomy rules to the collected event data by performing an iterative loop via the runtime endpoint on the second presentation server, the iterative loop comprising: automatically determining, via a data provider servlet application, a list of runtime transformation applications corresponding to data contracts corresponding to a particular provider ID; performing, via a runtime transform application, the appropriate transformations on event-value pairs; and for each event-value pair, return a key-value pair and appropriate category identification for storage at a runtime user profile application; categorize the transformed event data based on the applied taxonomy rules, and store the transformed event data in the corresponding user profile at the profile server; wherein the system is further configured to display, at the client machine, a data provider configuration page corresponding to the designated website, wherein the data provider configuration page is refreshed with captured event data from the plurality of end users, the event data corresponding to previously specified events. 8. The system of claim 6 , wherein the graphical user interface is further configured to use the at least one processor coupled to the memory for entering a name and notes by the user for a particular universal tag that are entered. | 0.877508 |
7,644,371 | 1 | 4 | 1. A system to facilitate specification of queries or commands, comprising: a user input module that receives a user input; a graphical user interface responsive to the user input, the graphical user interface including a taxonomically organized visualization of a plurality of dimensions that form at least a subset of a taxonomy for an associated information space, the dimensions including headings derived from metadata for data items in the information space; a filter generator that generates a filter based on metadata associated with each heading selected in the visualization; and a results component that presents results items that substantially satisfy the filter. | 1. A system to facilitate specification of queries or commands, comprising: a user input module that receives a user input; a graphical user interface responsive to the user input, the graphical user interface including a taxonomically organized visualization of a plurality of dimensions that form at least a subset of a taxonomy for an associated information space, the dimensions including headings derived from metadata for data items in the information space; a filter generator that generates a filter based on metadata associated with each heading selected in the visualization; and a results component that presents results items that substantially satisfy the filter. 4. The system of claim 1 , further comprising a natural language engine that converts language-based user inputs into corresponding headings that are supplied to the filter generator, the corresponding headings being visualized in the graphical user interface to indicated current filter criteria. | 0.501678 |
8,639,517 | 1 | 8 | 1. A method comprising: generating, via a processor, a set of features characterizing an association between a user input and a conversation context using prior user inputs; determining, by normalizing a length of the user input to a previous input in the prior user inputs and using a data-driven machine learning approach, whether the user input is associated with an existing topic related to a previous conversation context; and when the user input is associated with the existing topic, generating a response to the user input using information associated with the user input and content associated with any previous user input on the existing topic. | 1. A method comprising: generating, via a processor, a set of features characterizing an association between a user input and a conversation context using prior user inputs; determining, by normalizing a length of the user input to a previous input in the prior user inputs and using a data-driven machine learning approach, whether the user input is associated with an existing topic related to a previous conversation context; and when the user input is associated with the existing topic, generating a response to the user input using information associated with the user input and content associated with any previous user input on the existing topic. 8. The method of claim 1 , wherein determining whether the user input is associated with the existing topic related to the previous conversation context further comprises comparing semantic similarity information of a normalized feature and a non-normalized feature. | 0.678744 |
7,676,557 | 4 | 6 | 4. A computer program product for dynamically populating a portlet palette comprising: a computer usable storage medium comprising a physical storage medium having computer usable program code stored therewith, the computer usable program code comprising: computer usable program code configured to associate semantic tags with each of a plurality of stored portlets and with at least one of an open portal or open portlets contained within the open portal, wherein each semantic tag provides semantic information for the portlet or portal for which it is associated, and wherein each semantic tag comprises user entered data; computer usable program code configured to detect an event to initialize a portlet palette within a user interface having the open portal to which the portlet palette is associated, wherein the portlet palette is a user interface control comprising a portlet set of at least one portlet, wherein said portlet palette is configured so that a selection of a portlet from the portlet set causes the portlet to be added to the open portal; computer usable program code configured to compare via the semantic information contained within the semantic tags of the stored portlets against the semantic information contained within the semantic tags of at least one of the open portal and the open portlets; computer usable program code configured to automatically determine a set of portlets from a plurality of stored portlets that are relevant to the open portal based upon results of comparing the semantic information; computer usable program code configured to dynamically populate the portlet palette with the determined set of portlets; and computer usable program code configured to present the populated portlet palette within the user interface. | 4. A computer program product for dynamically populating a portlet palette comprising: a computer usable storage medium comprising a physical storage medium having computer usable program code stored therewith, the computer usable program code comprising: computer usable program code configured to associate semantic tags with each of a plurality of stored portlets and with at least one of an open portal or open portlets contained within the open portal, wherein each semantic tag provides semantic information for the portlet or portal for which it is associated, and wherein each semantic tag comprises user entered data; computer usable program code configured to detect an event to initialize a portlet palette within a user interface having the open portal to which the portlet palette is associated, wherein the portlet palette is a user interface control comprising a portlet set of at least one portlet, wherein said portlet palette is configured so that a selection of a portlet from the portlet set causes the portlet to be added to the open portal; computer usable program code configured to compare via the semantic information contained within the semantic tags of the stored portlets against the semantic information contained within the semantic tags of at least one of the open portal and the open portlets; computer usable program code configured to automatically determine a set of portlets from a plurality of stored portlets that are relevant to the open portal based upon results of comparing the semantic information; computer usable program code configured to dynamically populate the portlet palette with the determined set of portlets; and computer usable program code configured to present the populated portlet palette within the user interface. 6. The computer program product of claim 4 , further comprising: computer usable program code configured to store records to relate user identity to a user specific configuration for a portal, where the user specific configuration comprises a configuration set of portlets; computer usable program code configured to determine an identity of a current user of the open portal; computer usable program code configured to ascertain at least one other user having a relationship strength with the current user over a previously configured threshold, wherein the relationship strength is based upon a social networking relationship existing between the current user and the other user, wherein said social networking relationship is determined from interactions between the current user and the other user occurring through at least one social networking site, said social networking data being stored in a repository of social networking data accessible by a server responsible for dynamically populating said palette utilizing a social networking interface of the server; computer usable program code configured to query the stored records of the at least one other user to determine the configuration set of portlets of the other user; and computer usable program code configured to determine said set of portlets from a plurality of stored portlets that are relevant to the open portal based upon results of comparing the semantic information and based upon portlets of the determined configuration set associated with the other user, wherein the determined set of portlets used to dynamically populate the portlet palette comprise at least one portlet from the results of comparing the semantic information of the semantic tags and comprise at least one portlet from the configuration set of portlets of the other user, wherein the set of relevant portlets comprises the portlets of the determined configuration set associated with each of the at least one other user. | 0.514546 |
10,108,713 | 10 | 12 | 10. An apparatus for analyzing data, the apparatus comprising: a memory; and at least one processor coupled to the memory, the at least one processor being configured: to generate, by an entity, a query based at least in part on a topic of interest; to execute the query on a plurality of data sources, at least one of the plurality of data sources comprising at least one of contact information, device information, contact preferences, geographic data, or a combination thereof; to select, by the entity, a data source from the plurality of data sources for monitoring based on a correlation between the data source and the topic of interest, the correlation determined based on results of the executed query; to monitor, based on a set schedule, the data source or matches to the query to extract data from the data source when at least an update to stored data matches the query, newly added data matches the query, or a combination thereof; to extract data from the data source when at least the update to the stored data matches the query, the newly added data matches the query, or the combination thereof; to determine an extraction rate for extracting the data, the extraction rate indicating an amount of the data that is extracted over a first time period; to determine a first processing rate for processing the extracted data with a number of parallel processors, the first processing rate indicating an amount of extracted data that is processed over a second time period; to dynamically adjust the number of parallel processors for analyzing the extracted data based on the extraction rate to obtain a second processing rate that is greater than the first processing rate; to analyze, with the parallel processors, the extracted data to determine at least one of a sentiment, an index, a pattern, or a combination thereof; to establish a two-way communication channel, between at least the entity that selected the data source for monitoring and a user device of a user that provided the data to the data source, based on the analysis of the extracted data; to transmit, from the entity via the two-way communication channel, a first message directed to the user device based on the analysis of the extracted data; and to receive, from the user device via the two-way communication channel, a second message in response to the first message directed to the user device. | 10. An apparatus for analyzing data, the apparatus comprising: a memory; and at least one processor coupled to the memory, the at least one processor being configured: to generate, by an entity, a query based at least in part on a topic of interest; to execute the query on a plurality of data sources, at least one of the plurality of data sources comprising at least one of contact information, device information, contact preferences, geographic data, or a combination thereof; to select, by the entity, a data source from the plurality of data sources for monitoring based on a correlation between the data source and the topic of interest, the correlation determined based on results of the executed query; to monitor, based on a set schedule, the data source or matches to the query to extract data from the data source when at least an update to stored data matches the query, newly added data matches the query, or a combination thereof; to extract data from the data source when at least the update to the stored data matches the query, the newly added data matches the query, or the combination thereof; to determine an extraction rate for extracting the data, the extraction rate indicating an amount of the data that is extracted over a first time period; to determine a first processing rate for processing the extracted data with a number of parallel processors, the first processing rate indicating an amount of extracted data that is processed over a second time period; to dynamically adjust the number of parallel processors for analyzing the extracted data based on the extraction rate to obtain a second processing rate that is greater than the first processing rate; to analyze, with the parallel processors, the extracted data to determine at least one of a sentiment, an index, a pattern, or a combination thereof; to establish a two-way communication channel, between at least the entity that selected the data source for monitoring and a user device of a user that provided the data to the data source, based on the analysis of the extracted data; to transmit, from the entity via the two-way communication channel, a first message directed to the user device based on the analysis of the extracted data; and to receive, from the user device via the two-way communication channel, a second message in response to the first message directed to the user device. 12. The apparatus of claim 10 , in which the at least one processor is further configured to refine search terms of the query based at least in part on the executed query, and in which the monitoring is performed to monitor for matches to a refined query. | 0.732704 |
10,043,510 | 18 | 19 | 18. The computing device of claim 14 wherein word forms, the word forms having the same ending being the terminal common ending, have at least two different stress positions, and wherein the computer-readable instructions, when executed by the processor, further cause the processor to generate at least two terminal clusters, each of said at least two terminal clusters comprising word forms having: said terminal common ending, and one respective same stress position, and a number of occurrences of said one respective same stress position. | 18. The computing device of claim 14 wherein word forms, the word forms having the same ending being the terminal common ending, have at least two different stress positions, and wherein the computer-readable instructions, when executed by the processor, further cause the processor to generate at least two terminal clusters, each of said at least two terminal clusters comprising word forms having: said terminal common ending, and one respective same stress position, and a number of occurrences of said one respective same stress position. 19. The computing device of claim 18 , wherein the computer-readable instructions, when executed by the processor, further cause the processor to receive a request for defining the stress position of the new word form and, responsive to receiving said request: to use a new ending of the new word form for finding, in the reference system for endings, said at least two terminal clusters, and to apply to the new word form that stress position which corresponds to a stress position of word forms being in that one of said at least two terminal clusters, which terminal cluster has a highest number of occurrences of a particular stress position. | 0.822625 |
9,563,635 | 1 | 3 | 1. A method for eliminating redundant information in a log file having unknown grammar, the method comprising: identifying, by one or more computer processors, an alphanumeric string in a log file, the alphanumeric string comprising a plurality of alphanumeric substrings separated by non-alphanumeric characters, the plurality of alphanumeric substrings including at least two distinct alphanumeric substrings; replacing, by the one or more computer processors, each alphanumeric substring of the plurality of alphanumeric substrings with a first alphanumeric character to generate a first resulting string that includes the non-alphanumeric characters and multiple occurrences of the first alphanumeric character; replacing, by the one or more computer processors, each pair of characters of the first resulting string that is identical to another pair of characters of the first resulting string with a second alphanumeric character to generate a second resulting string, wherein replacing each pair of characters of the first resulting string that is identical to another pair of characters of the first resulting string with a second alphanumeric character to generate a second resulting string comprises: responsive to determining that there are multiple distinct pairs of characters of the first resulting string that are identical to another pair of characters of the first resulting string and that the multiple distinct pairs of characters occur an equal number of times in the first resulting string, selecting, by the one or more computer processors, a pair of the multiple distinct pairs of characters based on a pre-defined hierarchy of characters included in the multiple distinct pairs of characters, and replacing, by the one or more computer processors, the selected pair of characters with the second alphanumeric character to generate the second resulting string; and replacing, by the one or more computer processors, consecutive occurrences of the second alphanumeric character, in the second resulting string, with one occurrence of the second alphanumeric character to generate a compressed string. | 1. A method for eliminating redundant information in a log file having unknown grammar, the method comprising: identifying, by one or more computer processors, an alphanumeric string in a log file, the alphanumeric string comprising a plurality of alphanumeric substrings separated by non-alphanumeric characters, the plurality of alphanumeric substrings including at least two distinct alphanumeric substrings; replacing, by the one or more computer processors, each alphanumeric substring of the plurality of alphanumeric substrings with a first alphanumeric character to generate a first resulting string that includes the non-alphanumeric characters and multiple occurrences of the first alphanumeric character; replacing, by the one or more computer processors, each pair of characters of the first resulting string that is identical to another pair of characters of the first resulting string with a second alphanumeric character to generate a second resulting string, wherein replacing each pair of characters of the first resulting string that is identical to another pair of characters of the first resulting string with a second alphanumeric character to generate a second resulting string comprises: responsive to determining that there are multiple distinct pairs of characters of the first resulting string that are identical to another pair of characters of the first resulting string and that the multiple distinct pairs of characters occur an equal number of times in the first resulting string, selecting, by the one or more computer processors, a pair of the multiple distinct pairs of characters based on a pre-defined hierarchy of characters included in the multiple distinct pairs of characters, and replacing, by the one or more computer processors, the selected pair of characters with the second alphanumeric character to generate the second resulting string; and replacing, by the one or more computer processors, consecutive occurrences of the second alphanumeric character, in the second resulting string, with one occurrence of the second alphanumeric character to generate a compressed string. 3. The method of claim 1 , wherein the replacement of each pair of characters of the first resulting string that is identical to another pair of characters of the first resulting string is achieved by a byte-pair encoding algorithm. | 0.810147 |
7,647,325 | 1 | 13 | 1. A computer-implemented method for updating a computerized catalog of hardware device and software object identifiers installed on a computing device, said method comprising: identifying identifiers associated with at least one of hardware devices and software objects within the computing device, wherein the identity of said identified identifiers is unknown to a collection of information relating to hardware devices and software objects associated with the computing device; categorizing each of the identifiers of unknown identity within the computing device, said categorizing comprising qualifying data associated with the unknown identifiers, said qualified data including a name of an entity associated with the identified identifiers, said qualifying comprising at least normalizing and correcting the data associated with the unknown identifiers, said categorizing comprising at least one of the following: categorizing each of said identified identifiers according to a public categorization scheme and categorizing at least a portion of said identified identifiers according to one or more private categorization schemes; providing, by the computing device, the categorized identifiers with the qualified data to a community of users for review by the community of users when the identity of one or more of the unknown identifiers is not identifiable in response to the categorizing; receiving, by the computing device, comments on the provided categorized identifiers with the qualified data from the community of users; and re-categorizing the identifiers based upon the received comments, said re-categorizing comprising weighing the received comments based upon a reputation of sources of the received comments. | 1. A computer-implemented method for updating a computerized catalog of hardware device and software object identifiers installed on a computing device, said method comprising: identifying identifiers associated with at least one of hardware devices and software objects within the computing device, wherein the identity of said identified identifiers is unknown to a collection of information relating to hardware devices and software objects associated with the computing device; categorizing each of the identifiers of unknown identity within the computing device, said categorizing comprising qualifying data associated with the unknown identifiers, said qualified data including a name of an entity associated with the identified identifiers, said qualifying comprising at least normalizing and correcting the data associated with the unknown identifiers, said categorizing comprising at least one of the following: categorizing each of said identified identifiers according to a public categorization scheme and categorizing at least a portion of said identified identifiers according to one or more private categorization schemes; providing, by the computing device, the categorized identifiers with the qualified data to a community of users for review by the community of users when the identity of one or more of the unknown identifiers is not identifiable in response to the categorizing; receiving, by the computing device, comments on the provided categorized identifiers with the qualified data from the community of users; and re-categorizing the identifiers based upon the received comments, said re-categorizing comprising weighing the received comments based upon a reputation of sources of the received comments. 13. A computer-implemented method as set forth in claim 1 wherein said determining if the categorized identifiers of unknown identity should be recategorized based upon the received comments comprises weighting said received comments based upon a reputation of the sources of the received comments. | 0.666667 |
7,542,979 | 1 | 23 | 1. A computer system for loading data from a spreadsheet dataset, having data in the form of one or more records, into a database comprising: a) a storage device configured to store a control file containing a set of rules, each rule having a condition, wherein the set of rules describe mappings between attributes of the spreadsheet dataset and attributes of a business object; b) a processor configured to execute a spreadsheet loader having as inputs the spreadsheet dataset and the control file, wherein: i) each rule in the control file is evaluated for each record to determine if the condition is true for the record, and the records being parsed into one or more tokens if the condition is true; ii) each of the one or more tokens are assigned values based on a value clause, wherein each of the values is associated with one of the attributes of the business object; and iii) the spreadsheet loader sends the parsed data to the database, wherein the parsed data is stored in the database using a data access layer comprising an entity definition and a persistence map, wherein the entity definition defines the business object based on attributes of the database and the persistence map defines how to store the parsed data in the database. | 1. A computer system for loading data from a spreadsheet dataset, having data in the form of one or more records, into a database comprising: a) a storage device configured to store a control file containing a set of rules, each rule having a condition, wherein the set of rules describe mappings between attributes of the spreadsheet dataset and attributes of a business object; b) a processor configured to execute a spreadsheet loader having as inputs the spreadsheet dataset and the control file, wherein: i) each rule in the control file is evaluated for each record to determine if the condition is true for the record, and the records being parsed into one or more tokens if the condition is true; ii) each of the one or more tokens are assigned values based on a value clause, wherein each of the values is associated with one of the attributes of the business object; and iii) the spreadsheet loader sends the parsed data to the database, wherein the parsed data is stored in the database using a data access layer comprising an entity definition and a persistence map, wherein the entity definition defines the business object based on attributes of the database and the persistence map defines how to store the parsed data in the database. 23. A computer system as in claim 1 , wherein the set of rules within the control file includes a variable rule, wherein the variable rule comprises a condition, a parsedescriptor, and the value clause and an entity rule comprised of a condition and an attributelist. | 0.864604 |
9,002,956 | 19 | 23 | 19. A method for modifying a loudness point total of a first user, the method comprising: retrieving a predefined number of loudness points available to the first user; determining a quality rating of the first user; adjusting the loudness points available based upon the quality rating of the first user; determining whether the first user has sent any messages, a message remaining unsent when unassociated with one or more loudness points and scheduling to automatically send the message at a future time when the first user accumulates the one or more loudness points associated with the message based on the one or more loudness points associated with the message being greater than the loudness points available to the first user; determining loudness points associated with any sent messages, each sent message associated with the one or more loudness points; reducing the loudness points available to the first user by the determined loudness points associated with any sent messages; receiving a reply message to each sent message from a second user, the second user having a predefined number of available loudness points; receiving one or more loudness points associated with the reply message; and modifying the one or more loudness points associated with each sent message by the one or more loudness points associated with the reply message. | 19. A method for modifying a loudness point total of a first user, the method comprising: retrieving a predefined number of loudness points available to the first user; determining a quality rating of the first user; adjusting the loudness points available based upon the quality rating of the first user; determining whether the first user has sent any messages, a message remaining unsent when unassociated with one or more loudness points and scheduling to automatically send the message at a future time when the first user accumulates the one or more loudness points associated with the message based on the one or more loudness points associated with the message being greater than the loudness points available to the first user; determining loudness points associated with any sent messages, each sent message associated with the one or more loudness points; reducing the loudness points available to the first user by the determined loudness points associated with any sent messages; receiving a reply message to each sent message from a second user, the second user having a predefined number of available loudness points; receiving one or more loudness points associated with the reply message; and modifying the one or more loudness points associated with each sent message by the one or more loudness points associated with the reply message. 23. The method of claim 19 , further comprising: determining whether the first user sent any reviews; determining loudness of points associated with any reviews; and reducing the loudness of points available to the first user by the determined loudness points associated with any reviews. | 0.81864 |
8,051,487 | 4 | 5 | 4. A non-transitory computer-readable storage medium structured to store instructions executable by a processor, the instructions when executed causing a processor to: identify a target document and an associated current process activity, wherein the associated current process activity comprises an operation to be performed on the target document; determine whether the target document is an outgoing document which is a document that is exported out of the endpoint; identify a behavior applied to the target document if the target document is determined not to be an outgoing document: determine whether the target document contains sensitive information; and responsive to the target document containing the sensitive information, determining whether the current process activity is to be blocked, allowed, or modified, wherein the instructions when executed by the processor further cause the processor, after the target document and the associated current process activity are identified, to hold the current process activity, notify a behavior analysis engine of the target document and the current process activity, and wait for a signal from the behavior analysis engine indicating whether to continue with the current process activity, and wherein the instructions when executed by the processor further cause the processor to raise an exception and stop the current process activity if the behavior analysis engine provides a signal to block the current process activity. | 4. A non-transitory computer-readable storage medium structured to store instructions executable by a processor, the instructions when executed causing a processor to: identify a target document and an associated current process activity, wherein the associated current process activity comprises an operation to be performed on the target document; determine whether the target document is an outgoing document which is a document that is exported out of the endpoint; identify a behavior applied to the target document if the target document is determined not to be an outgoing document: determine whether the target document contains sensitive information; and responsive to the target document containing the sensitive information, determining whether the current process activity is to be blocked, allowed, or modified, wherein the instructions when executed by the processor further cause the processor, after the target document and the associated current process activity are identified, to hold the current process activity, notify a behavior analysis engine of the target document and the current process activity, and wait for a signal from the behavior analysis engine indicating whether to continue with the current process activity, and wherein the instructions when executed by the processor further cause the processor to raise an exception and stop the current process activity if the behavior analysis engine provides a signal to block the current process activity. 5. The non-transitory computer-readable storage medium of claim 4 , wherein the identification of the behavior applied to the target document involves applying activity-to-behavior patterns to process the current process activity and activities previously applied to the target document, and wherein a behavior comprises one or more process activities which collectively achieve a pre-defined goal. | 0.80336 |
9,390,282 | 12 | 15 | 12. A computing device comprising: a processor; and executable instructions operable by the processor, the executable instructions comprising a method for creating a document in a collaborative manner, the method comprising: providing a non-obfuscated original document (NOD) that is accessible to an outsourcing entity, the NOD having one or more sensitive items contained therein; obfuscating said one or more sensitive items in the NOD, to produce an obfuscated original document (OOD) containing obfuscated items; providing the OOD to plurality of worker entities to make changes to the OOD, the changes producing a plurality of obfuscated transformed document (OTD) parts; receiving the OTD parts from the worker entities, the OTD parts containing the changes made by the worker entities to the OOD; and assembling the OTD parts into an obfuscated transformed document (OTD); de-obfuscating the OTD by restoring the obfuscated items to their corresponding sensitive items, to produce a content-restored transformed document (CTD); sending an instruction from the outsourcing entity to one of the plurality of worker entities via a communication mechanism; and receiving an updated OTD from the worker entity receiving the instruction from the outsourcing entity, the updated OTD containing at least one additional change made by the worker entity to the OOD. | 12. A computing device comprising: a processor; and executable instructions operable by the processor, the executable instructions comprising a method for creating a document in a collaborative manner, the method comprising: providing a non-obfuscated original document (NOD) that is accessible to an outsourcing entity, the NOD having one or more sensitive items contained therein; obfuscating said one or more sensitive items in the NOD, to produce an obfuscated original document (OOD) containing obfuscated items; providing the OOD to plurality of worker entities to make changes to the OOD, the changes producing a plurality of obfuscated transformed document (OTD) parts; receiving the OTD parts from the worker entities, the OTD parts containing the changes made by the worker entities to the OOD; and assembling the OTD parts into an obfuscated transformed document (OTD); de-obfuscating the OTD by restoring the obfuscated items to their corresponding sensitive items, to produce a content-restored transformed document (CTD); sending an instruction from the outsourcing entity to one of the plurality of worker entities via a communication mechanism; and receiving an updated OTD from the worker entity receiving the instruction from the outsourcing entity, the updated OTD containing at least one additional change made by the worker entity to the OOD. 15. The computing device of claim 12 , wherein the computing device represents a remote computing system that is accessible to both the outsourcing entity and the worker entities via respective client computing devices. | 0.582061 |
9,213,766 | 1 | 7 | 1. A method programmed in a non-transitory memory of a device comprising: a. monitoring target information provided by an entity; b. processing the target information provided by the entity including parsing the target information into processed information, wherein processing the target information occurs while the target information is monitored; c. analyzing, with the device, the processed information including: i. detecting one or more keywords in the processed information using keyword detection; ii. analyzing sentence structure of the processed information; and iii. detecting the entity using entity detection; d. providing anticipatory information related to the target information in real-time based on analyzing the processed information, wherein the anticipatory information provides fact checking analysis in anticipation of commentary; and e. providing an alert of questionable information in real-time based on analyzing the processed information, wherein the alert of the questionable information indicates that the processed information is doubtful regarding accuracy, wherein the entity has a validity rating, and if the validity rating of the entity is below a threshold, and a specified keyword is detected, the alert of questionable is provided, wherein the validity rating is based on previous fact checking of comments made by the entity by comparing the comments with source information to generate a fact checking result, wherein comparing includes at least one of: i. searching for an exact match of the comments in the source information and returning the exact match search result of the exact match search if the exact match is found; ii. utilizing pattern matching for fact checking and returning the result of the pattern matching fact check if a pattern matching result confidence score is above a pattern matching result confidence threshold; and iii. utilizing a natural language search for fact checking and returning the result of the natural language fact check if a natural language result confidence score is above a natural language result confidence threshold. | 1. A method programmed in a non-transitory memory of a device comprising: a. monitoring target information provided by an entity; b. processing the target information provided by the entity including parsing the target information into processed information, wherein processing the target information occurs while the target information is monitored; c. analyzing, with the device, the processed information including: i. detecting one or more keywords in the processed information using keyword detection; ii. analyzing sentence structure of the processed information; and iii. detecting the entity using entity detection; d. providing anticipatory information related to the target information in real-time based on analyzing the processed information, wherein the anticipatory information provides fact checking analysis in anticipation of commentary; and e. providing an alert of questionable information in real-time based on analyzing the processed information, wherein the alert of the questionable information indicates that the processed information is doubtful regarding accuracy, wherein the entity has a validity rating, and if the validity rating of the entity is below a threshold, and a specified keyword is detected, the alert of questionable is provided, wherein the validity rating is based on previous fact checking of comments made by the entity by comparing the comments with source information to generate a fact checking result, wherein comparing includes at least one of: i. searching for an exact match of the comments in the source information and returning the exact match search result of the exact match search if the exact match is found; ii. utilizing pattern matching for fact checking and returning the result of the pattern matching fact check if a pattern matching result confidence score is above a pattern matching result confidence threshold; and iii. utilizing a natural language search for fact checking and returning the result of the natural language fact check if a natural language result confidence score is above a natural language result confidence threshold. 7. The method of claim 1 wherein the keyword detection includes comparing the processed information with a keyword database to determine if any keywords in the keyword database are included in the processed information. | 0.898329 |
9,282,076 | 4 | 5 | 4. The method of claim 1 , wherein the source of private information comprises one of: (a) one or more emails sent by the proposed recipient; (b) one or more instant messages sent by the proposed recipient; (c) metadata associated with the proposed recipient; or (d) any combination thereof. | 4. The method of claim 1 , wherein the source of private information comprises one of: (a) one or more emails sent by the proposed recipient; (b) one or more instant messages sent by the proposed recipient; (c) metadata associated with the proposed recipient; or (d) any combination thereof. 5. The method of claim 4 , wherein: (a) the one or more emails had been sent by the proposed recipient to the sender; (b) the one or more instant messages had been sent by the proposed recipient to the sender; (c) the metadata had been sent by the proposed recipient to the sender. | 0.904226 |
9,904,702 | 7 | 8 | 7. The machine readable medium of claim 6 , wherein said forming comprises one or more instructions for including said second comparison predicate in a WHERE clause of said SQL query. | 7. The machine readable medium of claim 6 , wherein said forming comprises one or more instructions for including said second comparison predicate in a WHERE clause of said SQL query. 8. The machine readable medium of claim 7 , wherein said forming further comprises one or more instructions for including a set of columns to be retrieved in a SELECT clause of said SQL query, and a set of tables containing said set of columns in a FROM clause of said SQL query. | 0.964888 |
8,874,430 | 1 | 7 | 1. A method for preparing a multi-lingual personal identification card, comprising: receiving, by a computer processor, a multi-lingual text comprising Latin-based characters in a Latin-based language and non-Latin-based characters in a non-Latin-based language, wherein the multi-lingual text comprises a name of a holder of the personal identification card in the Latin-based language and the non-Latin-based language; converting, by the computer processor, the non-Latin-based characters in the multi-lingual text to index values to produce a pseudo text, wherein each of the non-Latin-based characters has a Unicode value two byte in length, wherein the index values are a single byte in length, wherein the conversion is based on a predefined mapping that converts the Unicode values of the non-Latin-based characters to index values having fewer digits than the corresponding Unicode values of the non-Latin-based characters, wherein the predefined mapping allocates at least 55 consecutive digital numbers for the index values, wherein the pseudo text includes the index values in co-existence with the Latin-based characters in a Latin-based language; receiving vector data for a personal image which includes a facial image, a finger print, or a combination of both of the holder of the personal identification card; and encoding the pseudo text and the vector data in a matrix-code symbol. | 1. A method for preparing a multi-lingual personal identification card, comprising: receiving, by a computer processor, a multi-lingual text comprising Latin-based characters in a Latin-based language and non-Latin-based characters in a non-Latin-based language, wherein the multi-lingual text comprises a name of a holder of the personal identification card in the Latin-based language and the non-Latin-based language; converting, by the computer processor, the non-Latin-based characters in the multi-lingual text to index values to produce a pseudo text, wherein each of the non-Latin-based characters has a Unicode value two byte in length, wherein the index values are a single byte in length, wherein the conversion is based on a predefined mapping that converts the Unicode values of the non-Latin-based characters to index values having fewer digits than the corresponding Unicode values of the non-Latin-based characters, wherein the predefined mapping allocates at least 55 consecutive digital numbers for the index values, wherein the pseudo text includes the index values in co-existence with the Latin-based characters in a Latin-based language; receiving vector data for a personal image which includes a facial image, a finger print, or a combination of both of the holder of the personal identification card; and encoding the pseudo text and the vector data in a matrix-code symbol. 7. The method of claim 1 , wherein the step of encoding comprises: encoding the index values in the matrix-code symbol; and converting the Latin-based characters in the pseudo text to Unicode values and ASCII values, which are encoded in the matrix-code symbol. | 0.574919 |
8,214,734 | 1 | 4 | 1. A method, in a data processing system, for evaluating the performance of a text analysis engine, the method comprising: receiving a plurality of pre-annotated reference documents; receiving a set of annotation types associated with the pre-annotated reference documents; analyzing annotation contexts of reference annotations in the plurality of pre-annotated reference documents using the set of annotation types; identifying similar annotation contexts between the reference annotations and the set of annotation types; responsive to identifying the similar annotation contexts, clustering the similar annotation contexts thereby forming a plurality of reference annotation clusters; computing a set of reference content heterogeneity scores based on the number of reference annotation clusters for each annotation type in the set of annotation types; computing an integral reference content rate for the set of annotation types; outputting the integral reference content rate to a user; receiving standard performance rates for the text analysis engine; applying the integral reference content rate to the standard performance rates; and generating reliable performance rates for the text analysis engine. | 1. A method, in a data processing system, for evaluating the performance of a text analysis engine, the method comprising: receiving a plurality of pre-annotated reference documents; receiving a set of annotation types associated with the pre-annotated reference documents; analyzing annotation contexts of reference annotations in the plurality of pre-annotated reference documents using the set of annotation types; identifying similar annotation contexts between the reference annotations and the set of annotation types; responsive to identifying the similar annotation contexts, clustering the similar annotation contexts thereby forming a plurality of reference annotation clusters; computing a set of reference content heterogeneity scores based on the number of reference annotation clusters for each annotation type in the set of annotation types; computing an integral reference content rate for the set of annotation types; outputting the integral reference content rate to a user; receiving standard performance rates for the text analysis engine; applying the integral reference content rate to the standard performance rates; and generating reliable performance rates for the text analysis engine. 4. The method of claim 1 , wherein the set of reference content heterogeneity scores are computed using the following equation: CH ( T ) = number_of _reference _annotation _clusters _for _type _T number_of _content _units _in _reference _content , wherein the number of context units in the reference content is at least one of an amount of lines or an amount of sentences. | 0.72545 |
9,083,731 | 18 | 20 | 18. A tangible and non-transitory computer program product wherein computer instructions, when executed by a processor in a telecom network element, adapt operation of the telecom network element to provide a method for evaluating a pattern to determine if the pattern should be included within a set of patterns used by a malicious packet detector, the malicious packet detector comparing an input string representing a packet received at a network element to one or more patterns within the set of patterns to identify malicious packets, the method comprising: estimating worst-case time complexity of a regular expression comprising one or more back-references (backref-regex), the regular expression defining a pattern adapted for identifying malicious packets; and if the estimated worst-case time complexity is below a pre-defined threshold, selecting the pattern for inclusion within the set of patterns; wherein said estimating comprises: constructing a non-deterministic finite automaton (NFA) corresponding to the backref-regex (backref-NFA), wherein the backref-NFA comprises a plurality of NFA-states and a respectively labeled edge for each of the one or more back-references of the backref-regex; performing liveness analysis on the backref-NFA to determine for each NFA-state of the backref-NFA a set of back-references alive at the NFA-state; and determining a maximum number of alive back-references over the plurality of NFA-states, wherein the determined maximum number is indicative of the worst-case time complexity of the backref-regex. | 18. A tangible and non-transitory computer program product wherein computer instructions, when executed by a processor in a telecom network element, adapt operation of the telecom network element to provide a method for evaluating a pattern to determine if the pattern should be included within a set of patterns used by a malicious packet detector, the malicious packet detector comparing an input string representing a packet received at a network element to one or more patterns within the set of patterns to identify malicious packets, the method comprising: estimating worst-case time complexity of a regular expression comprising one or more back-references (backref-regex), the regular expression defining a pattern adapted for identifying malicious packets; and if the estimated worst-case time complexity is below a pre-defined threshold, selecting the pattern for inclusion within the set of patterns; wherein said estimating comprises: constructing a non-deterministic finite automaton (NFA) corresponding to the backref-regex (backref-NFA), wherein the backref-NFA comprises a plurality of NFA-states and a respectively labeled edge for each of the one or more back-references of the backref-regex; performing liveness analysis on the backref-NFA to determine for each NFA-state of the backref-NFA a set of back-references alive at the NFA-state; and determining a maximum number of alive back-references over the plurality of NFA-states, wherein the determined maximum number is indicative of the worst-case time complexity of the backref-regex. 20. The computer program product of claim 18 , wherein said method further comprises comparing an input string comprising a plurality of characters representing received packet to a pattern selected for use in identifying malicious packets via a single pass of a non-deterministic finite automation (NFA) corresponding to the backref-regex (backref-NFA) to determine whether the input string matches the pattern. | 0.501211 |
7,702,499 | 29 | 40 | 29. A computer program product that includes a computer usable storage medium, the medium comprising a sequence of instructions which, when executed by a processor, causes a processor to execute a process for preparing software for a performance estimation, the process comprising: obtaining a software assembly code module from a source code module, wherein the software assembly code module is an assembly-language representation; generating a software simulation model in a high level language format, wherein the software assembly code module comprises a binary code, and the act of generating the software simulation model is performed by a processor; annotating the software simulation model with performance information of hardware together with which the software simulation model runs to capture a dynamic interaction between tasks during runtime, wherein the act of annotating the software simulation model is performed during a time of the act of generating the software simulation model; and storing at least the simulation model on a computer usable storage medium or displaying the at least the software simulation model on a display apparatus, wherein the software simulation model is an assembler-level software simulation model, expressed in a high-level programming language. | 29. A computer program product that includes a computer usable storage medium, the medium comprising a sequence of instructions which, when executed by a processor, causes a processor to execute a process for preparing software for a performance estimation, the process comprising: obtaining a software assembly code module from a source code module, wherein the software assembly code module is an assembly-language representation; generating a software simulation model in a high level language format, wherein the software assembly code module comprises a binary code, and the act of generating the software simulation model is performed by a processor; annotating the software simulation model with performance information of hardware together with which the software simulation model runs to capture a dynamic interaction between tasks during runtime, wherein the act of annotating the software simulation model is performed during a time of the act of generating the software simulation model; and storing at least the simulation model on a computer usable storage medium or displaying the at least the software simulation model on a display apparatus, wherein the software simulation model is an assembler-level software simulation model, expressed in a high-level programming language. 40. The computer program product of claim 29 , wherein the performance information is dynamically computed at run-time, using a formula provided during a time of the act of annotating. | 0.901919 |
9,477,652 | 13 | 18 | 13. A non-transitory computer-readable storage medium storing instructions that, when executed by a computing system, cause the computing system to perform operations for creating a dialect-specific training data set, the operations comprising: selecting an initial training data set as a current training data set, wherein the initial training data set is selected by: receiving one or more initial content items; establishing dialect parameters for two or more of the initial content items, wherein the dialect parameters identify a first of the two or more of the initial content items as being composed in a first dialect and identify a second of the two or more of the initial content items as being composed in a second dialect; and sorting each of the initial content items into one or more dialect groups based on the established dialect parameters; generating, based on the initial training data set and corresponding one or more dialect groups, a dialect classifier configured to detect language dialects of content items to be classified as being in one of two or more dialects, the two or more dialects including at least the first dialect and the second dialect; augmenting the current training data set with additional training data by applying the dialect classifier to candidate content items, wherein at least one of the candidate content items that is in the augmented current training data set was not included in the initial training data set; and updating the dialect classifier based on the augmented current training data set; and returning the updated dialect classifier, wherein the updated dialect classifier is configured to identify additional content items that are not in the initial training data and are not in the augmented current training data set as being in one of the two or more dialects. | 13. A non-transitory computer-readable storage medium storing instructions that, when executed by a computing system, cause the computing system to perform operations for creating a dialect-specific training data set, the operations comprising: selecting an initial training data set as a current training data set, wherein the initial training data set is selected by: receiving one or more initial content items; establishing dialect parameters for two or more of the initial content items, wherein the dialect parameters identify a first of the two or more of the initial content items as being composed in a first dialect and identify a second of the two or more of the initial content items as being composed in a second dialect; and sorting each of the initial content items into one or more dialect groups based on the established dialect parameters; generating, based on the initial training data set and corresponding one or more dialect groups, a dialect classifier configured to detect language dialects of content items to be classified as being in one of two or more dialects, the two or more dialects including at least the first dialect and the second dialect; augmenting the current training data set with additional training data by applying the dialect classifier to candidate content items, wherein at least one of the candidate content items that is in the augmented current training data set was not included in the initial training data set; and updating the dialect classifier based on the augmented current training data set; and returning the updated dialect classifier, wherein the updated dialect classifier is configured to identify additional content items that are not in the initial training data and are not in the augmented current training data set as being in one of the two or more dialects. 18. The computer-readable storage medium of claim 13 , wherein establishing the dialect parameters comprises: identifying content items that are correlated to the dialect based on user interaction with the content items. | 0.748858 |
5,438,180 | 13 | 15 | 13. The cooking oven of claim 12 wherein said modifying indicia, said parameter display devices and said parameter indicia are linearly arranged on said panel. | 13. The cooking oven of claim 12 wherein said modifying indicia, said parameter display devices and said parameter indicia are linearly arranged on said panel. 15. The cooking oven of claim 13 wherein said selection means include printed indicia on said panel to define labels for said labeled selection devices and said labeled parameter display devices. | 0.956782 |
9,342,586 | 1 | 10 | 1. A method comprising: generating a search list associated with a first user, wherein said search list comprises an identification of one or more sites pertaining to a given topic; managing said search list in accordance with (i) one or more instructions provided by said first user, and (ii) one or more access control policies associated with one or more additional users, wherein said managing comprises generating a suggestion for inclusion of one or more additional sites to the search list based on (a) sites included in one or more search lists, associated with the one or more additional users, that share a given level of commonality with the search list associated with the first user, and (b) sites that share a given level of commonality with one or more items of content in the one or more sites of the search list associated with the first user; and sharing said search list associated with said first user with the one or more additional users based on the one or more access control policies associated with the one or more additional users; wherein said generating, said managing, and said sharing are carried out by at least one computing device. | 1. A method comprising: generating a search list associated with a first user, wherein said search list comprises an identification of one or more sites pertaining to a given topic; managing said search list in accordance with (i) one or more instructions provided by said first user, and (ii) one or more access control policies associated with one or more additional users, wherein said managing comprises generating a suggestion for inclusion of one or more additional sites to the search list based on (a) sites included in one or more search lists, associated with the one or more additional users, that share a given level of commonality with the search list associated with the first user, and (b) sites that share a given level of commonality with one or more items of content in the one or more sites of the search list associated with the first user; and sharing said search list associated with said first user with the one or more additional users based on the one or more access control policies associated with the one or more additional users; wherein said generating, said managing, and said sharing are carried out by at least one computing device. 10. The method of claim 1 , wherein said managing comprises deleting the identification of the one or more sites pertaining to the given topic. | 0.541667 |
9,031,966 | 1 | 10 | 1. A document editing device comprising: an operation module that receives a character decoration type as a search-target from a user; a display module that displays an editing document which contains character strings; and a control module that searches a character string of the editing document for a character decoration type of the searched character string that is identical to the search-target. | 1. A document editing device comprising: an operation module that receives a character decoration type as a search-target from a user; a display module that displays an editing document which contains character strings; and a control module that searches a character string of the editing document for a character decoration type of the searched character string that is identical to the search-target. 10. The document editing device according to claim 1 , wherein the control module displays, on the display module, a confirmation screen if a display of the confirmation screen for the character decoration type currently specified as the search target is ordered by an operation of the operation module by the user. | 0.691176 |
9,305,307 | 1 | 2 | 1. A computer-implemented method comprising: receiving, from a content sponsor, an indication of a first collection of entities to be used as selection criteria for presenting a first content item of a campaign responsive to received requests, wherein the first collection of entities is a grouping of entities that share at least one common characteristic; storing in inventory a reference to the first content item and the indicated selection criteria; after the storing, receiving a query including one or more terms or phrases, wherein the one or more terms or phrases identifies or is associated with a first entity; determining, using one or more processors, that the first entity is included in the first collection of entities, wherein the one or more terms or phrases does not include the first collection; identifying one or more eligible content items from an inventory of content items, each eligible content item being associated with selection criteria including criteria specifying the first collection of entities, wherein identifying includes identifying the first content item; and providing at least a portion of the first collection of entities for presentation to a user along with search results responsive to the query, wherein providing at least a portion of the first collection of entities includes providing one or more of the eligible content items including the first content item along with the portion of the first collection of entities including dynamically arranging a presentation of the portion of the first collection to position the first content item more prominently or visually emphasize the first content item based on a bid by the content sponsor. | 1. A computer-implemented method comprising: receiving, from a content sponsor, an indication of a first collection of entities to be used as selection criteria for presenting a first content item of a campaign responsive to received requests, wherein the first collection of entities is a grouping of entities that share at least one common characteristic; storing in inventory a reference to the first content item and the indicated selection criteria; after the storing, receiving a query including one or more terms or phrases, wherein the one or more terms or phrases identifies or is associated with a first entity; determining, using one or more processors, that the first entity is included in the first collection of entities, wherein the one or more terms or phrases does not include the first collection; identifying one or more eligible content items from an inventory of content items, each eligible content item being associated with selection criteria including criteria specifying the first collection of entities, wherein identifying includes identifying the first content item; and providing at least a portion of the first collection of entities for presentation to a user along with search results responsive to the query, wherein providing at least a portion of the first collection of entities includes providing one or more of the eligible content items including the first content item along with the portion of the first collection of entities including dynamically arranging a presentation of the portion of the first collection to position the first content item more prominently or visually emphasize the first content item based on a bid by the content sponsor. 2. The method of claim 1 wherein the first collection of entities is named, and wherein the method further comprises providing to the content sponsor an interface for enabling a selection of the first collection of entities from a plurality of available collection of entities, and receiving from content sponsor an explicit designation of the first collection of entities by name to be used as the selection criteria for delivery of the first content item. | 0.811001 |
8,175,876 | 25 | 26 | 25. The system of claim 14 , wherein the processor is further configured to: receive an initial plurality of frames of the speech signal; calculate a silence average background energy parameter using the initial plurality of frames; calculate the silence mean cepstral vector using the initial plurality of frames; calculate a silence cepstral distance of the initial plurality of frames using the silence mean cepstral vector; obtain the first energy threshold and the second energy threshold using the silence average background energy parameter and obtaining the first cepstral distance threshold using the silence cepstral distance. | 25. The system of claim 14 , wherein the processor is further configured to: receive an initial plurality of frames of the speech signal; calculate a silence average background energy parameter using the initial plurality of frames; calculate the silence mean cepstral vector using the initial plurality of frames; calculate a silence cepstral distance of the initial plurality of frames using the silence mean cepstral vector; obtain the first energy threshold and the second energy threshold using the silence average background energy parameter and obtaining the first cepstral distance threshold using the silence cepstral distance. 26. The system of claim 25 , wherein the first energy threshold is obtained from the silence average background energy parameter by a multiplication by a first constant and the second energy threshold is obtained from the silence background energy parameter by a multiplication by a second constant. | 0.838901 |
8,346,536 | 4 | 7 | 4. The system of claim 3 , wherein said translated documents and corresponding target language documents are saved by said one or more local servers in a multi-lingual base. | 4. The system of claim 3 , wherein said translated documents and corresponding target language documents are saved by said one or more local servers in a multi-lingual base. 7. The system of claim 4 , wherein in said multi-lingual base, a target language term in a target language document is associated with one or more source language terms in the corresponding translated document. | 0.950542 |
9,900,271 | 1 | 7 | 1. A method for displaying a plurality of chat threads on a wireless mobile terminal comprising a user input device and a display, the method comprising: receiving a plurality of inbound chat messages corresponding to the plurality of chat threads, each of the plurality of inbound chat messages comprising message content; transmitting a plurality of outbound chat messages from the wireless mobile terminal corresponding to the plurality of chat threads, each of the plurality of outbound chat messages comprising message content and being transmitted to at least one user-selected recipient to thereby become a sent chat message, wherein one or more of the pluralities of inbound and outbound messages further comprise speech content; for each outbound chat message that is a speech chat message, further transmitting a copy of the speech chat message to the wireless mobile terminal as an input chat message; simultaneously displaying the message content of each of the pluralities of inbound and sent chat messages corresponding to the plurality of chat threads in a single content region of a chat history display; receiving at the user input device a user selection of the displayed message content of a user-selected displayed chat message corresponding to one of the displayed pluralities of inbound and sent chat messages; and in response to the user selection of the displayed message content of the user-selected displayed chat message, visually highlighting in the single content region of the chat history display the displayed message content of each of the displayed inbound and sent chat messages associated with a particular chat thread corresponding to the user-selected displayed chat message and further in response to said user selection, displaying in the chat history display a plurality of display identifiers representative of a sender and each of one or more recipients of the user-selected displayed chat message. | 1. A method for displaying a plurality of chat threads on a wireless mobile terminal comprising a user input device and a display, the method comprising: receiving a plurality of inbound chat messages corresponding to the plurality of chat threads, each of the plurality of inbound chat messages comprising message content; transmitting a plurality of outbound chat messages from the wireless mobile terminal corresponding to the plurality of chat threads, each of the plurality of outbound chat messages comprising message content and being transmitted to at least one user-selected recipient to thereby become a sent chat message, wherein one or more of the pluralities of inbound and outbound messages further comprise speech content; for each outbound chat message that is a speech chat message, further transmitting a copy of the speech chat message to the wireless mobile terminal as an input chat message; simultaneously displaying the message content of each of the pluralities of inbound and sent chat messages corresponding to the plurality of chat threads in a single content region of a chat history display; receiving at the user input device a user selection of the displayed message content of a user-selected displayed chat message corresponding to one of the displayed pluralities of inbound and sent chat messages; and in response to the user selection of the displayed message content of the user-selected displayed chat message, visually highlighting in the single content region of the chat history display the displayed message content of each of the displayed inbound and sent chat messages associated with a particular chat thread corresponding to the user-selected displayed chat message and further in response to said user selection, displaying in the chat history display a plurality of display identifiers representative of a sender and each of one or more recipients of the user-selected displayed chat message. 7. The method of claim 1 , further comprising one or more of: displaying at least one public nickname associated with corresponding senders of the plurality of inbound messages; and displaying at least one private nickname associated with corresponding senders of the plurality of inbound messages. | 0.712355 |
7,890,525 | 1 | 2 | 1. A method for automatically providing foreign language abbreviation translation in an instant messaging system, comprising: identifying, by using a computer, at least one foreign language abbreviation translation database in response to a user indicated source culture, wherein said identified foreign abbreviation translation database stores a plurality of abbreviation translations retrievably associated with corresponding ones of a plurality of foreign language abbreviations, wherein said foreign language abbreviations are foreign language abbreviations frequently used by people from said user indicated source culture; locating a candidate term that is possibly a foreign language abbreviation in an instant message input from said user; comparing said candidate term with said plurality of foreign language abbreviations stored in said identified foreign language abbreviation translation database, wherein said comparing said candidate term with said plurality of foreign language abbreviations includes obtaining a transliteration of said candidate term, said obtaining said transliteration including changing individual characters of said candidate term into characters of an alphabet used to represent said plurality of abbreviation translations to provide a phonetic representation of said candidate term, and comparing said transliteration of said candidate term with said plurality of abbreviation translations; in the event that said candidate term matches one of said plurality of foreign language abbreviations stored in said identified foreign language abbreviation translation database, retrieving and displaying one of said plurality of abbreviation translations corresponding to said matching one of said plurality of foreign language abbreviations; adding said candidate term to said instant messaging session, wherein said adding is based on said locating, wherein said locating said candidate term that is possibly a foreign language abbreviation in said instant message input from said user is in response to an indication from said user; and wherein said displaying said one of said plurality of abbreviation translations corresponding to said matching one of said plurality of foreign language abbreviations is within an instant messaging session graphical user interface. | 1. A method for automatically providing foreign language abbreviation translation in an instant messaging system, comprising: identifying, by using a computer, at least one foreign language abbreviation translation database in response to a user indicated source culture, wherein said identified foreign abbreviation translation database stores a plurality of abbreviation translations retrievably associated with corresponding ones of a plurality of foreign language abbreviations, wherein said foreign language abbreviations are foreign language abbreviations frequently used by people from said user indicated source culture; locating a candidate term that is possibly a foreign language abbreviation in an instant message input from said user; comparing said candidate term with said plurality of foreign language abbreviations stored in said identified foreign language abbreviation translation database, wherein said comparing said candidate term with said plurality of foreign language abbreviations includes obtaining a transliteration of said candidate term, said obtaining said transliteration including changing individual characters of said candidate term into characters of an alphabet used to represent said plurality of abbreviation translations to provide a phonetic representation of said candidate term, and comparing said transliteration of said candidate term with said plurality of abbreviation translations; in the event that said candidate term matches one of said plurality of foreign language abbreviations stored in said identified foreign language abbreviation translation database, retrieving and displaying one of said plurality of abbreviation translations corresponding to said matching one of said plurality of foreign language abbreviations; adding said candidate term to said instant messaging session, wherein said adding is based on said locating, wherein said locating said candidate term that is possibly a foreign language abbreviation in said instant message input from said user is in response to an indication from said user; and wherein said displaying said one of said plurality of abbreviation translations corresponding to said matching one of said plurality of foreign language abbreviations is within an instant messaging session graphical user interface. 2. The method of claim 1 , further comprising: generating a graphical user interface for inputting a user indication of said source culture, wherein said identifying said foreign language abbreviation translation database is responsive to said user indication of said source culture. | 0.846861 |
9,916,307 | 2 | 3 | 2. The system of claim 1 , further comprising a primary window to receive and populate the expression. | 2. The system of claim 1 , further comprising a primary window to receive and populate the expression. 3. The system of claim 2 , further comprising the activated application to create a secondary window proximal to the primary window and the application to populate the secondary window with the dynamically translated idiom. | 0.915015 |
10,055,394 | 3 | 4 | 3. The method of claim 2 , further comprising: determining a style of animation to present based on a type of the second user modification; and presenting the animation having the determined style. | 3. The method of claim 2 , further comprising: determining a style of animation to present based on a type of the second user modification; and presenting the animation having the determined style. 4. The method of claim 3 , wherein the style of animation to present is determined based on animation information, the animation information including a mapping of animation types to object types and modification types. | 0.924011 |
9,363,634 | 11 | 14 | 11. A system comprising: one or more computers and one or more storage devices storing instructions that are operable, when executed by the one or more computers, to cause the one or more computers to perform operations comprising: receiving a user context of a user, wherein the user context specifies a location of a user device being used by the user; obtaining user activity data organized into sessions, each session being data representing a plurality of user activities performed by a distinct user during a respective time period, the sessions including sessions for multiple users; obtaining matching sessions for the received user context, each matching session being a distinct session that includes data representing activities performed by respective users having a user context matching the received user context during a time period represented by the matching session; obtaining general sessions, each general session including data representing activities performed by respective users during a time period represented by the general session; determining, from the obtained matching sessions and the obtained general sessions, one or more context-relevant activities that occur in the matching sessions more frequently than the one or more context-relevant activities occur in the general sessions, the one or more context-relevant activities being activities performed by users matching the received user context more frequently than by users in general; and providing information related to the one or more context-relevant activities in response to receiving the user context. | 11. A system comprising: one or more computers and one or more storage devices storing instructions that are operable, when executed by the one or more computers, to cause the one or more computers to perform operations comprising: receiving a user context of a user, wherein the user context specifies a location of a user device being used by the user; obtaining user activity data organized into sessions, each session being data representing a plurality of user activities performed by a distinct user during a respective time period, the sessions including sessions for multiple users; obtaining matching sessions for the received user context, each matching session being a distinct session that includes data representing activities performed by respective users having a user context matching the received user context during a time period represented by the matching session; obtaining general sessions, each general session including data representing activities performed by respective users during a time period represented by the general session; determining, from the obtained matching sessions and the obtained general sessions, one or more context-relevant activities that occur in the matching sessions more frequently than the one or more context-relevant activities occur in the general sessions, the one or more context-relevant activities being activities performed by users matching the received user context more frequently than by users in general; and providing information related to the one or more context-relevant activities in response to receiving the user context. 14. The system of claim 11 , wherein the context-relevant activities comprise users making a purchase at a particular business, and wherein providing information related to the one or more context-relevant activities comprises providing information about the particular business. | 0.709979 |
8,219,904 | 1 | 12 | 1. A document-based system for acquiring information pertaining to a document, comprising: a computer having a memory storing a meta-document including the document, the document including content information, and a set of one or more document service requests based on a personality associated with the document, wherein a personality comprises a theme or context, wherein each document service request in the set comprises a process for using a portion of the document's content information as a starting point to obtain other information from a service provider pertaining to the document's content information, wherein associating a set of one or more document service requests based on a different personality to the document's content information will provide different results; and a scheduler for autonomously activating and managing the document service requests without user intervention by periodically polling the meta-document for document service requests, for selecting a document service request from the set of one or more document service requests, for initiating and managing communication with a selected service provider to satisfy the selected document service request and for integrating any results from the selected document service request into the meta-document, wherein the meta-document includes the document, the set of one or more document service requests and integrated results; wherein the set of one or more document service requests follow a sequence of calls to service providers for extracting information from one or more of other documents, databases and data stores, and for searching for other information responsive to any extracted information from the one or more of other documents, databases and data stores. | 1. A document-based system for acquiring information pertaining to a document, comprising: a computer having a memory storing a meta-document including the document, the document including content information, and a set of one or more document service requests based on a personality associated with the document, wherein a personality comprises a theme or context, wherein each document service request in the set comprises a process for using a portion of the document's content information as a starting point to obtain other information from a service provider pertaining to the document's content information, wherein associating a set of one or more document service requests based on a different personality to the document's content information will provide different results; and a scheduler for autonomously activating and managing the document service requests without user intervention by periodically polling the meta-document for document service requests, for selecting a document service request from the set of one or more document service requests, for initiating and managing communication with a selected service provider to satisfy the selected document service request and for integrating any results from the selected document service request into the meta-document, wherein the meta-document includes the document, the set of one or more document service requests and integrated results; wherein the set of one or more document service requests follow a sequence of calls to service providers for extracting information from one or more of other documents, databases and data stores, and for searching for other information responsive to any extracted information from the one or more of other documents, databases and data stores. 12. The system of claim 1 , wherein the document and the set of one or more document service requests are user-selectable. | 0.742616 |
9,959,862 | 11 | 16 | 11. A speech recognition method based on a deep-neural-network (DNN) sound model, comprising: generating sound-model state sets corresponding to a plurality of pieces of set training speech data included in multi-set training speech data; generating a multi-set state cluster from the sound-model state sets, generating a multi-set state cluster including collecting the sound-model state sets, calculating state log likelihoods of each state of the sound-model state sets, and generating the multi-set state cluster by merging first and second sound-model state sets on the basis of the state log likelihoods and state tying information of the sound-model state sets; learning a DNN structured parameter by setting the multi-set training speech data as an input node, setting the multi-set state cluster as an output node, and disconnecting the output node from a state cluster of the DNN not related to the input node; receiving a user's speech and characteristic information thereof via a user interface; and recognizing the user's speech on the basis of the learned DNN structured parameter by setting a sound-model state set corresponding to the characteristic information of the user's speech as an output node. | 11. A speech recognition method based on a deep-neural-network (DNN) sound model, comprising: generating sound-model state sets corresponding to a plurality of pieces of set training speech data included in multi-set training speech data; generating a multi-set state cluster from the sound-model state sets, generating a multi-set state cluster including collecting the sound-model state sets, calculating state log likelihoods of each state of the sound-model state sets, and generating the multi-set state cluster by merging first and second sound-model state sets on the basis of the state log likelihoods and state tying information of the sound-model state sets; learning a DNN structured parameter by setting the multi-set training speech data as an input node, setting the multi-set state cluster as an output node, and disconnecting the output node from a state cluster of the DNN not related to the input node; receiving a user's speech and characteristic information thereof via a user interface; and recognizing the user's speech on the basis of the learned DNN structured parameter by setting a sound-model state set corresponding to the characteristic information of the user's speech as an output node. 16. The speech recognition method of claim 11 , wherein the learning of the DNN structured parameter comprises setting the plurality of pieces of set training speech data included in the multi-set training speech data as input nodes, and setting the sound-model state sets included in the multi-set state cluster and corresponding to the plurality of pieces of set training speech data as output nodes. | 0.696375 |
9,245,052 | 15 | 16 | 15. A system comprising: at least one computing device; a processor included in the at least one computing device; memory coupled to the processor; an input device; and a video adapter via which the at least one computing device is configured to substantially simultaneously provide, in response to receiving, via the input device, one or more characters that form at least a portion of a query string that does not include an explicit submission of the portion of the query string, both query results and query refinement options, where the one or more received characters match at least one pattern that indicates one or more characters followed by a space character. | 15. A system comprising: at least one computing device; a processor included in the at least one computing device; memory coupled to the processor; an input device; and a video adapter via which the at least one computing device is configured to substantially simultaneously provide, in response to receiving, via the input device, one or more characters that form at least a portion of a query string that does not include an explicit submission of the portion of the query string, both query results and query refinement options, where the one or more received characters match at least one pattern that indicates one or more characters followed by a space character. 16. The system of claim 15 where both the query results and the query refinement options are provided based at least in part on a load. | 0.7 |
6,098,042 | 20 | 21 | 20. The method of claim 19 wherein step B further comprises the step of: B.2 determining from the identified entry of the attribute table which grammatical function of language the homograph can perform. | 20. The method of claim 19 wherein step B further comprises the step of: B.2 determining from the identified entry of the attribute table which grammatical function of language the homograph can perform. 21. The method of claim 20 wherein step B further comprises the step of: B.3 performing a syntactic analysis of the identified homograph within the text. | 0.943626 |
8,560,529 | 17 | 23 | 17. A system for comparing the distinctiveness of a plurality of sets generated through interaction with a collection of information, the system comprising: at least one processor operatively connected to a memory adapted to execute system components; a sampling component configured to sample from the collection of information to generate at least one set, wherein the sampling component is further configured to establish, automatically, at least one identifying characteristic within the at least one set; an analysis component configured to determine a statistical distribution of at least one identifying characteristic associated with the at least one set; a measurement component configured to determine a relative measurement of distinctiveness based on the statistical distributions of the at least one identifying characteristic associated with the at least one set and at least one other set, wherein the measurement component is further configured to account for a set size of a measured set based on a measurement of distinctiveness for a comparison set and a set size for the comparison set, and normalize the relative measurement of distinctiveness based on the set size of the measured set and the size for the comparison set. | 17. A system for comparing the distinctiveness of a plurality of sets generated through interaction with a collection of information, the system comprising: at least one processor operatively connected to a memory adapted to execute system components; a sampling component configured to sample from the collection of information to generate at least one set, wherein the sampling component is further configured to establish, automatically, at least one identifying characteristic within the at least one set; an analysis component configured to determine a statistical distribution of at least one identifying characteristic associated with the at least one set; a measurement component configured to determine a relative measurement of distinctiveness based on the statistical distributions of the at least one identifying characteristic associated with the at least one set and at least one other set, wherein the measurement component is further configured to account for a set size of a measured set based on a measurement of distinctiveness for a comparison set and a set size for the comparison set, and normalize the relative measurement of distinctiveness based on the set size of the measured set and the size for the comparison set. 23. The system according to claim 17 , wherein the analysis component is further configured to determine the statistical distribution against a plurality of identifying characteristics. | 0.792135 |
8,706,729 | 1 | 16 | 1. A distributed data annotation server system, comprising: at least one storage device configured to store source data, one or more annotators, annotation tasks, and a distributed data annotation application; and a processor; wherein the distributed data annotation application configures the processor to: receive source data, where the source data comprises one or more pieces of source data; select one or more annotators for at least one piece of source data; create one or more annotation tasks for the selected annotators and at least one piece of source data; request one or more annotations for at least one piece of source data using the created annotation tasks; receive annotations for at least one piece of source data; determine source data metadata for at least one piece of source data using the received annotations, where the source data metadata includes source data characteristics; generate annotator metadata for at least one annotator using the received annotations and at least one piece of source data, where the annotator metadata includes identified annotator characteristics; and estimate the ground truth for at least one piece of source data using the source data metadata and the annotator metadata. | 1. A distributed data annotation server system, comprising: at least one storage device configured to store source data, one or more annotators, annotation tasks, and a distributed data annotation application; and a processor; wherein the distributed data annotation application configures the processor to: receive source data, where the source data comprises one or more pieces of source data; select one or more annotators for at least one piece of source data; create one or more annotation tasks for the selected annotators and at least one piece of source data; request one or more annotations for at least one piece of source data using the created annotation tasks; receive annotations for at least one piece of source data; determine source data metadata for at least one piece of source data using the received annotations, where the source data metadata includes source data characteristics; generate annotator metadata for at least one annotator using the received annotations and at least one piece of source data, where the annotator metadata includes identified annotator characteristics; and estimate the ground truth for at least one piece of source data using the source data metadata and the annotator metadata. 16. The distributed data annotation server system of claim 1 , wherein selecting one or more annotators for at least one piece of source data comprises selecting one or more annotators based on at least one source data characteristic in the source data metadata. | 0.869652 |
7,623,710 | 10 | 11 | 10. The computer-readable storage media of claim 9 , wherein the structure translator component includes an import component that transfers a subset of the plurality of layout-related characteristics to the second format. | 10. The computer-readable storage media of claim 9 , wherein the structure translator component includes an import component that transfers a subset of the plurality of layout-related characteristics to the second format. 11. The computer-readable storage media of claim 10 , wherein the plurality of layout-related characteristics is at least one of a margin, a bitmap location, a paragraph designator, a column designator, a table and a border. | 0.898734 |
10,146,815 | 1 | 2 | 1. A method, comprising: evaluating a set of queries to identify query information for queries within the set of queries; evaluating the queries as query pairs utilizing a goal classifier to determine common goal probabilities for the query pairs based upon the query information; grouping one or more query pairs associated with common goal probabilities exceeding a goal probability threshold into a plurality of goal clusters; evaluating the plurality of goal clusters as goal cluster pairs utilizing a mission classifier to determine common mission probabilities for the goal cluster pairs, wherein the plurality of goal clusters comprises at least a first goal cluster and a second goal cluster; grouping the first goal cluster and the second goal cluster, of a first goal cluster pair of the goal cluster pairs, into a first mission cluster based upon a first common mission probability, for the first goal cluster pair, exceeding a mission probability threshold, wherein the first mission cluster is associated with two or more query pairs; generating a query-goal-mission structure for the set of queries based upon the plurality of goal clusters and the first mission cluster; receiving a search query from a remote device; evaluating the search query to identify a search query aspect; responsive to the search query aspect corresponding to an aspect of the query-goal-mission structure, using the query-goal-mission structure to identify a query recommendation; and transmitting the query recommendation to the remote device. | 1. A method, comprising: evaluating a set of queries to identify query information for queries within the set of queries; evaluating the queries as query pairs utilizing a goal classifier to determine common goal probabilities for the query pairs based upon the query information; grouping one or more query pairs associated with common goal probabilities exceeding a goal probability threshold into a plurality of goal clusters; evaluating the plurality of goal clusters as goal cluster pairs utilizing a mission classifier to determine common mission probabilities for the goal cluster pairs, wherein the plurality of goal clusters comprises at least a first goal cluster and a second goal cluster; grouping the first goal cluster and the second goal cluster, of a first goal cluster pair of the goal cluster pairs, into a first mission cluster based upon a first common mission probability, for the first goal cluster pair, exceeding a mission probability threshold, wherein the first mission cluster is associated with two or more query pairs; generating a query-goal-mission structure for the set of queries based upon the plurality of goal clusters and the first mission cluster; receiving a search query from a remote device; evaluating the search query to identify a search query aspect; responsive to the search query aspect corresponding to an aspect of the query-goal-mission structure, using the query-goal-mission structure to identify a query recommendation; and transmitting the query recommendation to the remote device. 2. The method of claim 1 , comprising: performing a search assistance task utilizing the query-goal-mission structure. | 0.901667 |
6,161,130 | 2 | 4 | 2. The method in claim 1 wherein the classes comprise first and second classes for first and second predefined categories of messages, respectively. | 2. The method in claim 1 wherein the classes comprise first and second classes for first and second predefined categories of messages, respectively. 4. The method in claim 2 further comprising the steps of: comparing the output confidence level for the incoming message to a predefined probabilistic threshold value so as to yield a comparison result; and distinguishing said incoming message, in a predefined manner associated with the first class, from messages associated with the second class if the comparison result indicates that the output confidence level equals or exceeds the threshold level. | 0.858391 |
10,073,860 | 12 | 17 | 12. A non-transitory computer-readable storage medium storing computer executable instructions that when executed by a processor perform operations comprising: determining media content text data representing a plurality of words output in a subset of media content during presentation of the media content; determining a first color palette based at least in part on a first keyword of the media content text data textually corresponding to a first name of the first color palette, the first color palette comprising a plurality of colors, wherein determining the first color palette based at least in part on the first keyword of the media content text data textually corresponding to the first name of the first color palette further comprises at least one of: determining that the first name of the first color palette includes the first keyword of the media content text data, or determining that the first name of the first color palette is related to the first keyword of the media content text data using natural language processing; retrieving the plurality of colors from the first color palette; determining ranking data, wherein determining the ranking data comprises: calculating a first cumulative score for a first color of the plurality of colors and a second cumulative score for a second color of the plurality of colors, wherein calculating the first cumulative score and the second cumulative score further comprises: aggregating a first weight for each color palette of a plurality of color palettes comprising the first color; and aggregating a second weight for each color palette of the plurality of color palettes comprising the second color; selecting the first color from the plurality of colors based at least in part on the ranking data that includes the first cumulative score and the second cumulative score; and causing display of the first color during presentation of the media content. | 12. A non-transitory computer-readable storage medium storing computer executable instructions that when executed by a processor perform operations comprising: determining media content text data representing a plurality of words output in a subset of media content during presentation of the media content; determining a first color palette based at least in part on a first keyword of the media content text data textually corresponding to a first name of the first color palette, the first color palette comprising a plurality of colors, wherein determining the first color palette based at least in part on the first keyword of the media content text data textually corresponding to the first name of the first color palette further comprises at least one of: determining that the first name of the first color palette includes the first keyword of the media content text data, or determining that the first name of the first color palette is related to the first keyword of the media content text data using natural language processing; retrieving the plurality of colors from the first color palette; determining ranking data, wherein determining the ranking data comprises: calculating a first cumulative score for a first color of the plurality of colors and a second cumulative score for a second color of the plurality of colors, wherein calculating the first cumulative score and the second cumulative score further comprises: aggregating a first weight for each color palette of a plurality of color palettes comprising the first color; and aggregating a second weight for each color palette of the plurality of color palettes comprising the second color; selecting the first color from the plurality of colors based at least in part on the ranking data that includes the first cumulative score and the second cumulative score; and causing display of the first color during presentation of the media content. 17. The non-transitory computer-readable storage medium of claim 12 , wherein the media content text data is determined dynamically through speech recognition. | 0.859292 |
7,752,535 | 1 | 2 | 1. A system tangibly embodied on a computer-readable medium for sorting and reporting transaction information, comprising; a collection function automatically navigating to and retrieving transaction information associated with a specific person or enterprise from third-party Internet-connected web sites and gathering information concerning transactions, the transaction information including at least date, description, and amount of the transactions; an input function enabling a client to provide to the system a request for a summary of transactions over a specific range of dates, according to a definition of purpose of transaction including at least expenditure types; a processing function categorizing individual ones of the collected transactions according to at least part of the transaction description for determining the purpose of transaction using pre-stored description characteristics associated with the purpose; a compilation function summarizing the transactions that meet the purpose and fall into the specific range of dates; a reporting function for providing the summary of transactions to the specific person or enterprise; and a function storing past transaction history associated with the particular person or enterprise, wherein the past transaction history is used to predict future transaction statistical information, and wherein a probability algorithm is used in developing the description characteristics, wherein the description characteristics are periodically amended according to further information that is collected and processed. | 1. A system tangibly embodied on a computer-readable medium for sorting and reporting transaction information, comprising; a collection function automatically navigating to and retrieving transaction information associated with a specific person or enterprise from third-party Internet-connected web sites and gathering information concerning transactions, the transaction information including at least date, description, and amount of the transactions; an input function enabling a client to provide to the system a request for a summary of transactions over a specific range of dates, according to a definition of purpose of transaction including at least expenditure types; a processing function categorizing individual ones of the collected transactions according to at least part of the transaction description for determining the purpose of transaction using pre-stored description characteristics associated with the purpose; a compilation function summarizing the transactions that meet the purpose and fall into the specific range of dates; a reporting function for providing the summary of transactions to the specific person or enterprise; and a function storing past transaction history associated with the particular person or enterprise, wherein the past transaction history is used to predict future transaction statistical information, and wherein a probability algorithm is used in developing the description characteristics, wherein the description characteristics are periodically amended according to further information that is collected and processed. 2. The system of claim 1 wherein the reporting function provides a total transaction expenditure amount with the summary of transactions. | 0.789231 |
7,502,770 | 2 | 26 | 2. A computer database, comprising: a database store for receiving, storing, and allowing access to data concerning a plurality of topics, meta data created at a time of entry of said data, meta data comprising at least one annotation concerning said data, and meta data comprising access statistics concerning said data; a viewing tool for user access to said data in said database, wherein said viewing tool comprises means for choosing topics that a user wants to learn about, viewing explanations provided to said user as a sequence of presentations, and annotating said data in said database; an electronic tutor for maintaining a user learning model, and for finding useful data in said database to present to said user; an authoring tool for enabling an author to add data into said database; said means for choosing further comprising means for naming a topic via entering a word or phrase into a topic-search engine; wherein said viewing tool then displays a map of an area of a topic space said user selects, showing a current user level and attainable user levels; a topic map in which a space of topics and subtopics is illustrated as an n-dimensional landscape, with landmarks and links showing relationships between topics; wherein a coloring scheme shows said user's level and relative importance of said topic; wherein said topic map shows paths that said user has traveled before and paths that others have traveled before; and wherein said viewing tool allows said user to move through topic space by panning, zooming, and leaping from topic to related topic; wherein said viewing tool allows said user to zoom into relevant topics, look at their subtopics and mark things that are of interest, and to mark things that are already known; at least one registry handled by a registration server, wherein a registry comprises one of: a pen name registry, a content registry and a topic registry; wherein said registration server keeps a registry of all content in said database, including any explanations, queries, paths, and annotations; wherein said registration server keeps track of where information is, said author's pen name, and when said information was registered. | 2. A computer database, comprising: a database store for receiving, storing, and allowing access to data concerning a plurality of topics, meta data created at a time of entry of said data, meta data comprising at least one annotation concerning said data, and meta data comprising access statistics concerning said data; a viewing tool for user access to said data in said database, wherein said viewing tool comprises means for choosing topics that a user wants to learn about, viewing explanations provided to said user as a sequence of presentations, and annotating said data in said database; an electronic tutor for maintaining a user learning model, and for finding useful data in said database to present to said user; an authoring tool for enabling an author to add data into said database; said means for choosing further comprising means for naming a topic via entering a word or phrase into a topic-search engine; wherein said viewing tool then displays a map of an area of a topic space said user selects, showing a current user level and attainable user levels; a topic map in which a space of topics and subtopics is illustrated as an n-dimensional landscape, with landmarks and links showing relationships between topics; wherein a coloring scheme shows said user's level and relative importance of said topic; wherein said topic map shows paths that said user has traveled before and paths that others have traveled before; and wherein said viewing tool allows said user to move through topic space by panning, zooming, and leaping from topic to related topic; wherein said viewing tool allows said user to zoom into relevant topics, look at their subtopics and mark things that are of interest, and to mark things that are already known; at least one registry handled by a registration server, wherein a registry comprises one of: a pen name registry, a content registry and a topic registry; wherein said registration server keeps a registry of all content in said database, including any explanations, queries, paths, and annotations; wherein said registration server keeps track of where information is, said author's pen name, and when said information was registered. 26. The user interface of claim 2 , wherein said user interface further comprises: a simulation of a two-dimensional navigational space that said user navigates through by any of moving right/left and up/down; wherein said navigational space comprises a plurality of graphical objects which are any of two-dimensional and animated; and which have sounds associated with them that said user begins to hear as he draws near said object; and wherein there are links between said objects representing relationships between concepts said objects represent; wherein said links are almost transparent; wherein as said user moves near to an object, said links associated with said object become more visible, fading as a chain of connections gets farther from said object; and wherein as the user approaches a link, links of that type become more visible. | 0.516 |
7,809,671 | 27 | 31 | 27. The application home page of claim 26 wherein the tasks area comprises for each particular task a group of clickable links to respective web pages providing additional information about the particular task. | 27. The application home page of claim 26 wherein the tasks area comprises for each particular task a group of clickable links to respective web pages providing additional information about the particular task. 31. The application home page of claim 27 further comprising an issues area including clickable links to web pages with information about problems or topics needing discussion among users involved in the transfer of the knowledge. | 0.912614 |
8,751,957 | 1 | 10 | 1. A method for updating a user profile relating to a television programming recommender, the updating of the user profile being carried out in a system configured for generating recommendations regarding content of programs comprising: obtaining said user profile indicating television program viewing preferences of a user; using an audio/visual device to capture user initiated feedback generated by the user and provided in the form of gestural feedback in the form of video information, and/or auditory sounds in the form of audio information, while the user is watching specific television programs; analyzing at least one of the audio and video information generated by an audio/visual capture device which is focused on said user while said user is viewing or completing viewing of a plurality of specific television programs at different times, to identify whether the said information is predefined behavioral feedback indicating present television program preferences of said user and, if so identified, translating the predefined behavioral feedback into a representation indicating a strength of user's liking or disliking of the specific program being watched; and wherein the updating of said user television program profile is based on processing the representation and the audio and/or video information is in the form of auditory or gestural feedback from the user and said feedback is initiated by the said system or initiated by the user and wherein if the occurrence of a predefined event relating to the television program being watched is detected then the feedback which is received for that program is either of a user response to a query which is generated to the user, in which case the feedback received is explicit feedback from the user which is used to update the user profile, or the feedback received is user initiated feedback which is implicit feedback which is used to update the user profile and the auditory and gestural feedback identified during the watching of the said program and which has been captured by the said audio/visual device is analyzed to validate the user's like or dislike of the said television program said predefined behavioral feedback includes auditory and/or gestural feedback, said feedback mapped to a scale corresponding to respective strengths of said preferences of said user in rating said plurality of television programs viewed. | 1. A method for updating a user profile relating to a television programming recommender, the updating of the user profile being carried out in a system configured for generating recommendations regarding content of programs comprising: obtaining said user profile indicating television program viewing preferences of a user; using an audio/visual device to capture user initiated feedback generated by the user and provided in the form of gestural feedback in the form of video information, and/or auditory sounds in the form of audio information, while the user is watching specific television programs; analyzing at least one of the audio and video information generated by an audio/visual capture device which is focused on said user while said user is viewing or completing viewing of a plurality of specific television programs at different times, to identify whether the said information is predefined behavioral feedback indicating present television program preferences of said user and, if so identified, translating the predefined behavioral feedback into a representation indicating a strength of user's liking or disliking of the specific program being watched; and wherein the updating of said user television program profile is based on processing the representation and the audio and/or video information is in the form of auditory or gestural feedback from the user and said feedback is initiated by the said system or initiated by the user and wherein if the occurrence of a predefined event relating to the television program being watched is detected then the feedback which is received for that program is either of a user response to a query which is generated to the user, in which case the feedback received is explicit feedback from the user which is used to update the user profile, or the feedback received is user initiated feedback which is implicit feedback which is used to update the user profile and the auditory and gestural feedback identified during the watching of the said program and which has been captured by the said audio/visual device is analyzed to validate the user's like or dislike of the said television program said predefined behavioral feedback includes auditory and/or gestural feedback, said feedback mapped to a scale corresponding to respective strengths of said preferences of said user in rating said plurality of television programs viewed. 10. The method of claim 1 wherein said predefined behavioral feedback indicates the relative strengths on a rating basis of said user preferences from amongst said plurality of television programs. | 0.675987 |
6,151,609 | 7 | 8 | 7. A remote system administration method, comprising the steps of: communicating an editor input form from a server through a network to a client in response to receiving a request from the client, the client using a forms-enabled and script-enabled web browser; receiving a server path input at the server from the web browser; communicating a file selection form from the server to the web browser, the file selection form including filenames identifying files included in a server path defined by the server path input; receiving a file selection from the web browser at the server, the file selection identifying one of the files; and communicating a copy of one of the files from the server to the web browser for editing; receiving by the server an updated file for storage, the updated file produced by editing the copy of the one of the files using the web browser without the use of a plug-in to the web browser. | 7. A remote system administration method, comprising the steps of: communicating an editor input form from a server through a network to a client in response to receiving a request from the client, the client using a forms-enabled and script-enabled web browser; receiving a server path input at the server from the web browser; communicating a file selection form from the server to the web browser, the file selection form including filenames identifying files included in a server path defined by the server path input; receiving a file selection from the web browser at the server, the file selection identifying one of the files; and communicating a copy of one of the files from the server to the web browser for editing; receiving by the server an updated file for storage, the updated file produced by editing the copy of the one of the files using the web browser without the use of a plug-in to the web browser. 8. The method of claim 7, further comprising the step of saving the updated file at the server. | 0.894912 |
8,856,638 | 14 | 18 | 14. A method for a multimedia seek sequence using a synchronization index and a mobile computing device, said method comprising the steps: providing a mobile computing device comprising a viewing screen and a touch-sensitive input interface; providing a synchronization index that comprises an electronic transcript that indicates text corresponding to audio from the multimedia and indicates respective times within multimedia corresponding to when a word or range of words is audible in the multimedia; providing a receiving device; displaying on said mobile computing device text from the synchronization index, wherein said text is displayed other than as a web page; receiving, by the mobile computing device, information indicating a user's selected mobile computing device touch-sensitive input interface gesture performed on a portion of said viewing screen corresponding to a word, or range of words, from said synchronization index; wherein said gesture is recognized by said touch-sensitive input interface; performing a timecode lookup using the synchronization index, wherein said synchronization index is referenced to provide data for a time location t1 that corresponds to said word or range of words; seeking on said receiving device multimedia corresponding to said synchronization index, and, if found, accessing multimedia at t1. | 14. A method for a multimedia seek sequence using a synchronization index and a mobile computing device, said method comprising the steps: providing a mobile computing device comprising a viewing screen and a touch-sensitive input interface; providing a synchronization index that comprises an electronic transcript that indicates text corresponding to audio from the multimedia and indicates respective times within multimedia corresponding to when a word or range of words is audible in the multimedia; providing a receiving device; displaying on said mobile computing device text from the synchronization index, wherein said text is displayed other than as a web page; receiving, by the mobile computing device, information indicating a user's selected mobile computing device touch-sensitive input interface gesture performed on a portion of said viewing screen corresponding to a word, or range of words, from said synchronization index; wherein said gesture is recognized by said touch-sensitive input interface; performing a timecode lookup using the synchronization index, wherein said synchronization index is referenced to provide data for a time location t1 that corresponds to said word or range of words; seeking on said receiving device multimedia corresponding to said synchronization index, and, if found, accessing multimedia at t1. 18. The method of claim 14 , wherein the receiving device is other than said mobile computing device and is configured to receive multimedia input from a source selected from the group comprising satellite receiver, internet connection, WiFi, computer network, cable television system, fiber optic cable delivery network for data, cellular communication channel, bluetooth, UPnP, and local wireless connection. | 0.791878 |
8,447,751 | 14 | 23 | 14. A non-transitory computer readable medium storing computer readable instructions that, when executed, cause an apparatus to: receive an identifier for a network document; perform an on-demand analysis of the network document to determine a search engine score for the network document, wherein the on-demand analysis of the network document includes: determining a number of links included in the network document by analyzing a structure of the network document; determining a number of incoming links to the network document; and generating separate specific traffic-independent scoring analyses for each of the links included in the network document, wherein each of the separate specific traffic-independent scoring analyses are visually-navigable; and generate, based on the received identifier and independently of a user-specified search word or phrase, a display of the search engine score along with a first level of scoring detail for the network document, wherein the search engine score is determined by evaluating the network document using one or more traffic-independent scoring factors and wherein the network document is ranked based on the one or more traffic-independent scoring factors, and wherein the ranking is determined by combining the search engine score and a link flow distribution that indicates the likelihood that a user will access the network document relative to a second network document, wherein the network document and the second network document are within the same web site; receive a request to display details of the one or more traffic-independent scoring factors; in response to the request: generate the details of the one or more traffic-independent scoring factors by performing an on-demand analysis of the one or more traffic-independent scoring factors; and generate a display of a second level of scoring detail including the details of the one or more traffic-independent scoring factors, wherein the second level of scoring detail includes a plurality of non-traffic attributes. | 14. A non-transitory computer readable medium storing computer readable instructions that, when executed, cause an apparatus to: receive an identifier for a network document; perform an on-demand analysis of the network document to determine a search engine score for the network document, wherein the on-demand analysis of the network document includes: determining a number of links included in the network document by analyzing a structure of the network document; determining a number of incoming links to the network document; and generating separate specific traffic-independent scoring analyses for each of the links included in the network document, wherein each of the separate specific traffic-independent scoring analyses are visually-navigable; and generate, based on the received identifier and independently of a user-specified search word or phrase, a display of the search engine score along with a first level of scoring detail for the network document, wherein the search engine score is determined by evaluating the network document using one or more traffic-independent scoring factors and wherein the network document is ranked based on the one or more traffic-independent scoring factors, and wherein the ranking is determined by combining the search engine score and a link flow distribution that indicates the likelihood that a user will access the network document relative to a second network document, wherein the network document and the second network document are within the same web site; receive a request to display details of the one or more traffic-independent scoring factors; in response to the request: generate the details of the one or more traffic-independent scoring factors by performing an on-demand analysis of the one or more traffic-independent scoring factors; and generate a display of a second level of scoring detail including the details of the one or more traffic-independent scoring factors, wherein the second level of scoring detail includes a plurality of non-traffic attributes. 23. The non-transitory compute readable medium of claim 14 , wherein the network document and second network document are webpages within the same website having a plurality of webpages, and wherein the link flow distribution of the network document indicates the likelihood that a user will access the network document relative to the plurality of webpages, the plurality of webpages including the second network document. | 0.614051 |
10,102,857 | 1 | 2 | 1. A method, comprising: at a first electronic device of a pluralitv of electronic devices, each electronic device of the plurality of electronic devices comprising one or more microphones, a speaker, one or more processors, and memory storing one or more programs for execution by the one or more processors: detecting a voice input; determining a first quality score for the detected voice input; receiving quality scores generated by the other devices of the plurality of electronic devices for detection of the voice input by the other devices; in accordance with a determination that the first quality score is not the highest amongst the quality scores for the voice input generated by the plurality of electronic devices: identifying a criterion associated with the voice input; and in accordance with a determination that the identified criterion is the most relevant to the first electronic device, responding to the detected input. | 1. A method, comprising: at a first electronic device of a pluralitv of electronic devices, each electronic device of the plurality of electronic devices comprising one or more microphones, a speaker, one or more processors, and memory storing one or more programs for execution by the one or more processors: detecting a voice input; determining a first quality score for the detected voice input; receiving quality scores generated by the other devices of the plurality of electronic devices for detection of the voice input by the other devices; in accordance with a determination that the first quality score is not the highest amongst the quality scores for the voice input generated by the plurality of electronic devices: identifying a criterion associated with the voice input; and in accordance with a determination that the identified criterion is the most relevant to the first electronic device, responding to the detected input. 2. The method of claim 1 , further comprising forgoing outputting an audible response to the detected voice input in accordance with the determination that the identified criterion is not the most relevant to the first electronic device. | 0.611475 |
8,914,722 | 1 | 2 | 1. A method of using a computer having a memory and a processor to prepare a document referencing elements to a drawing and presented in the document with a common noun and further differentially presented with different adjectives identifying the noun in the document, said method comprising the steps of: manually designating ( 22 ) a first element with a common noun preceded by a first primary adjective, associating ( 24 ) a first reference indicia with the common noun preceded by the first primary adjective to reference the first element, storing in the computer memory the first reference indicia with the common noun preceded by the first primary adjective, manually designating ( 26 ) a second element with the common noun preceded by a second primary adjective, associating ( 28 ) a second reference indicia with the common noun preceded by the second primary adjective to reference the second element, storing in the computer memory the second reference indicia with the common noun preceded by the second primary adjective, scanning ( 38 ) the document with the computer for each occurrence of the common noun, inserting ( 40 ) the first reference indicia following the common noun in response to the scanning and each recitation of the common noun preceded by the first primary adjective ( 42 ) to reference the first element throughout the document, inserting ( 44 ) the second reference indicia following the common noun in response to the scanning and each recitation of the common noun preceded by the second primary adjective ( 46 ) to reference the second element throughout the document, and characterized by the computer automatically inserting ( 72 ) the first and second reference indicia following the common noun in response to the scanning and each recitation of the common noun unmodified by an adjective ( 74 ) to reference the unmodified common noun with both reference indicia for the first and second elements throughout the document without attaching the first and second reference indicia to occurrences of the common noun modified by one of the adjectives. | 1. A method of using a computer having a memory and a processor to prepare a document referencing elements to a drawing and presented in the document with a common noun and further differentially presented with different adjectives identifying the noun in the document, said method comprising the steps of: manually designating ( 22 ) a first element with a common noun preceded by a first primary adjective, associating ( 24 ) a first reference indicia with the common noun preceded by the first primary adjective to reference the first element, storing in the computer memory the first reference indicia with the common noun preceded by the first primary adjective, manually designating ( 26 ) a second element with the common noun preceded by a second primary adjective, associating ( 28 ) a second reference indicia with the common noun preceded by the second primary adjective to reference the second element, storing in the computer memory the second reference indicia with the common noun preceded by the second primary adjective, scanning ( 38 ) the document with the computer for each occurrence of the common noun, inserting ( 40 ) the first reference indicia following the common noun in response to the scanning and each recitation of the common noun preceded by the first primary adjective ( 42 ) to reference the first element throughout the document, inserting ( 44 ) the second reference indicia following the common noun in response to the scanning and each recitation of the common noun preceded by the second primary adjective ( 46 ) to reference the second element throughout the document, and characterized by the computer automatically inserting ( 72 ) the first and second reference indicia following the common noun in response to the scanning and each recitation of the common noun unmodified by an adjective ( 74 ) to reference the unmodified common noun with both reference indicia for the first and second elements throughout the document without attaching the first and second reference indicia to occurrences of the common noun modified by one of the adjectives. 2. A method as set forth in claim 1 further comprising the steps of: manually designating ( 122 , 222 ) the first element by adding a first secondary adjective to the common noun preceded by the first primary adjective, storing in the computer memory the designated first element with the common noun preceded by a first primary adjective and a first secondary adjective, manually designating ( 126 , 226 ) the second element by adding a second secondary adjective to the common noun preceded by the second primary adjective, storing in the computer memory the designated second element with the common noun preceded by a second primary adjective and a second secondary adjective, automatically inserting ( 140 , 240 ) the first reference indicia following the common noun in response to the scanning and each recitation of the common noun modified by the first primary adjective and the first secondary adjective ( 142 , 242 ) to reference the common noun with the first reference indicia for the first element throughout the document, and automatically inserting ( 144 , 244 ) the second reference indicia following the common noun in response to the scanning and each recitation of the common noun modified by the second primary adjective and the second secondary adjective to reference the common noun with the second reference indicia for the second element throughout the document ( 146 , 246 ). | 0.671589 |
9,507,695 | 1 | 5 | 1. A method for indicating significance of tested code statements, the method comprising: a processor receiving a rule containing a first set of code statements; the processor comparing the first set of code statements of the rule to a plurality of code statements of a source code; the processor, in response to the first set of code statements of the rule matching a second set of code statements of the plurality of code statements of the source code, applying a weight modifier to the rule, wherein applying the weight modifier to the rule assigns a weighted value to the first set of code statements of the rule; the processor, in response to the first set of code statements of the rule matching a third set of code statements of the plurality of code statements of the source code, applying the weight modifier to the rule a second time, wherein the rule includes a first instance of the weighted value and the weight modifier assigns a second instance of the weighted value to the rule; the processor applying a cumulative weight value of the rule to the second set of code statements and the third set of codes statements of the plurality of code statements of the source code, wherein the cumulative weight value indicates a significance of the second set of code statements and the third set of code statements, and is based on accumulated applications of the weighted value to the rule, by the weight modifier; and the processor, in response to receiving a request for a test coverage report, displaying in the test coverage report, the cumulative weight value of the second set of code statements and the third set of code statements, of the plurality of code statements of the source code. | 1. A method for indicating significance of tested code statements, the method comprising: a processor receiving a rule containing a first set of code statements; the processor comparing the first set of code statements of the rule to a plurality of code statements of a source code; the processor, in response to the first set of code statements of the rule matching a second set of code statements of the plurality of code statements of the source code, applying a weight modifier to the rule, wherein applying the weight modifier to the rule assigns a weighted value to the first set of code statements of the rule; the processor, in response to the first set of code statements of the rule matching a third set of code statements of the plurality of code statements of the source code, applying the weight modifier to the rule a second time, wherein the rule includes a first instance of the weighted value and the weight modifier assigns a second instance of the weighted value to the rule; the processor applying a cumulative weight value of the rule to the second set of code statements and the third set of codes statements of the plurality of code statements of the source code, wherein the cumulative weight value indicates a significance of the second set of code statements and the third set of code statements, and is based on accumulated applications of the weighted value to the rule, by the weight modifier; and the processor, in response to receiving a request for a test coverage report, displaying in the test coverage report, the cumulative weight value of the second set of code statements and the third set of code statements, of the plurality of code statements of the source code. 5. The method of claim 1 , wherein the processor compares the first set of code statements of the rule to the second set of code statements of the plurality of code statements of the source code subsequent to compiling and testing of the source code. | 0.776386 |
9,304,681 | 10 | 11 | 10. A non-transitory storage medium storing instructions that, when executed by a computing system, cause the computing system to perform operations for identifying characters in a handwritten input on a touch-sensitive device, the operations comprising: receiving a handwritten user input via the touch-sensitive device; identifying a set of candidate characters based on the handwritten user input; estimating candidate support lines for each of the candidate characters; associating reference support lines for each candidate character; for each candidate character, measuring a deviation between the estimated support lines and reference support lines to determine one or more deviations from an expectation; ranking each candidate character based on a total deviation measurement for each candidate character; and identifying a best-ranked candidate character based at least in part on a smallest total deviation measurement. | 10. A non-transitory storage medium storing instructions that, when executed by a computing system, cause the computing system to perform operations for identifying characters in a handwritten input on a touch-sensitive device, the operations comprising: receiving a handwritten user input via the touch-sensitive device; identifying a set of candidate characters based on the handwritten user input; estimating candidate support lines for each of the candidate characters; associating reference support lines for each candidate character; for each candidate character, measuring a deviation between the estimated support lines and reference support lines to determine one or more deviations from an expectation; ranking each candidate character based on a total deviation measurement for each candidate character; and identifying a best-ranked candidate character based at least in part on a smallest total deviation measurement. 11. The computer-readable storage medium of claim 10 , wherein each reference support line is associated with a corresponding reference angle around an established anchor point on the touch-sensitive device. | 0.970479 |
8,032,418 | 35 | 36 | 35. The apparatus according to claim 34 , wherein each text item of the database of text items has a bid value associated with a corresponding keyword and wherein each text item is ranked with respect to the bid value. | 35. The apparatus according to claim 34 , wherein each text item of the database of text items has a bid value associated with a corresponding keyword and wherein each text item is ranked with respect to the bid value. 36. The apparatus according to claim 35 , additionally comprising an amendment module in communication with the processor for enabling the commercial suppliers to specify and amend the bid values. | 0.934536 |
8,180,837 | 19 | 21 | 19. A non-transitory computer-readable storage medium having tangibly embodied thereon instructions, which when executed by one or more processors of one or more computer systems cause the one or more processors to perform a method comprising: converting an embedded image of an electronic mail (email) message to a binarized representation by performing thresholding on a grayscale representation of the embedded image; quantifying, by the anti-spam module, a number of text strings that are included in the embedded image by analyzing one or more blocks of the binarized representation with a text string measurement algorithm; classifying, by the anti-spam module, the email message as spam or clean based at least in part on the number of text strings; and wherein the one or more blocks comprise M×N virtual blocks and wherein the text string measurement algorithm employs equations having a general form as follows: T = ∑ m = 0 M ∑ n = 0 N T m , n subject to : T m , n = ∑ y t = y 0 m y max m ∑ y b = y t + 1 y max m T y t , y b m , n y 0 m = y max ∂ 0 ( m - 1 ) , y max m = y 0 m + ∂ 0 T y t , y b m , n = { 1 ∂ 1 > ∑ i = y t y b CB i n > ∂ 2 ∑ k = x 0 n x max n B k , y b + 1 < ∂ 3 , x 0 n = x max ∂ 0 ( n - 1 ) , x max n = x 0 n + ∂ 0 0 Otherwise CB i n = { 1 ∂ 4 > ∑ k = x 0 n x max n B k , i > ∂ 5 Max ( ∑ k = x w x w + ∂ 6 B k , i ) < ∂ 7 , x 0 n ≤ x w ≤ x max n 0 Otherwise where, ∂ 0 . . . ∂ 7 are adjustable parameters; T is the number of text strings; T y t ,y b m,n is a likelihood that a row between y t and y b in virtual block [m,n] represents text; CB i n is a likelihood that a line[i] is a part of text; and B k,i is a value of pixel[k,i] in the binary representation. | 19. A non-transitory computer-readable storage medium having tangibly embodied thereon instructions, which when executed by one or more processors of one or more computer systems cause the one or more processors to perform a method comprising: converting an embedded image of an electronic mail (email) message to a binarized representation by performing thresholding on a grayscale representation of the embedded image; quantifying, by the anti-spam module, a number of text strings that are included in the embedded image by analyzing one or more blocks of the binarized representation with a text string measurement algorithm; classifying, by the anti-spam module, the email message as spam or clean based at least in part on the number of text strings; and wherein the one or more blocks comprise M×N virtual blocks and wherein the text string measurement algorithm employs equations having a general form as follows: T = ∑ m = 0 M ∑ n = 0 N T m , n subject to : T m , n = ∑ y t = y 0 m y max m ∑ y b = y t + 1 y max m T y t , y b m , n y 0 m = y max ∂ 0 ( m - 1 ) , y max m = y 0 m + ∂ 0 T y t , y b m , n = { 1 ∂ 1 > ∑ i = y t y b CB i n > ∂ 2 ∑ k = x 0 n x max n B k , y b + 1 < ∂ 3 , x 0 n = x max ∂ 0 ( n - 1 ) , x max n = x 0 n + ∂ 0 0 Otherwise CB i n = { 1 ∂ 4 > ∑ k = x 0 n x max n B k , i > ∂ 5 Max ( ∑ k = x w x w + ∂ 6 B k , i ) < ∂ 7 , x 0 n ≤ x w ≤ x max n 0 Otherwise where, ∂ 0 . . . ∂ 7 are adjustable parameters; T is the number of text strings; T y t ,y b m,n is a likelihood that a row between y t and y b in virtual block [m,n] represents text; CB i n is a likelihood that a line[i] is a part of text; and B k,i is a value of pixel[k,i] in the binary representation. 21. The computer-readable storage medium of claim 19 , wherein the embedded image comprises an image contained within a file attached to the email message. | 0.91408 |
5,384,702 | 16 | 17 | 16. The method of claim 1, wherein a grammar marker of said plurality of grammar markers includes a comparative mode marker. | 16. The method of claim 1, wherein a grammar marker of said plurality of grammar markers includes a comparative mode marker. 17. The method of claim 16, wherein said first database includes comparative mode rules, comparative conversion rules, and superlative conversion rules. | 0.983449 |
9,978,365 | 17 | 19 | 17. One or more non-transitory computer readable media storing computer-executable instructions which, when executed by a processor, cause the processor to: determine weights for attributes by ranking the attributes based on user interactions with a user terminal; store the weights for the attributes in a memory; process, after the weights are stored in the memory, a voice input in a first analysis, wherein the first analysis includes identifying one of the attributes; identify, as a result of the first analysis, one domain of a plurality of domains wherein the identifying the one domain includes retrieving the stored weight for the identified attribute and identifying the one domain based on the identified attribute and the retrieved weight; process the voice input in a second analysis using specialized information of the one domain, wherein each of the plurality of domains comprises different respective specialized information; and cause a response resulting from the second analysis to be output as synthesized speech. | 17. One or more non-transitory computer readable media storing computer-executable instructions which, when executed by a processor, cause the processor to: determine weights for attributes by ranking the attributes based on user interactions with a user terminal; store the weights for the attributes in a memory; process, after the weights are stored in the memory, a voice input in a first analysis, wherein the first analysis includes identifying one of the attributes; identify, as a result of the first analysis, one domain of a plurality of domains wherein the identifying the one domain includes retrieving the stored weight for the identified attribute and identifying the one domain based on the identified attribute and the retrieved weight; process the voice input in a second analysis using specialized information of the one domain, wherein each of the plurality of domains comprises different respective specialized information; and cause a response resulting from the second analysis to be output as synthesized speech. 19. The one or more non-transitory computer readable media of claim 17 , storing further computer-executable instructions which, when executed by the processor, cause the processor to: identify context information other than the voice input; wherein the one domain is identified based on the context information. | 0.614815 |
9,959,559 | 1 | 2 | 1. A system for ranking search results in an electronic environment, the system comprising: processors; and a memory storing instructions that, when executed by at least one processor among the processors, cause the system to perform operations comprising: receiving a search query from a computing device of a searching party located in a geographic region, wherein the search query is received by an online marketplace visited by the searching party using the computing device; conducting a search and generating search results based on the search query; retrieving an IP address or a browser language setting of the computing device of the searching party; identifying the geographic region of the searching party based at least in part on the retrieved IP address or the retrieved browser language setting of the computing device of the searching party; identifying a language associated with the identified geographic region of the searching party based on the identified geographic region of the searching party; for a seller associated with at least one of the search results, determining a proficiency in the language associated with the geographic region of the searching party; ranking the search results based on at least the identified language and the proficiency, wherein search results associated with a higher proficiency in the identified language are ranked higher relative to search results associated with a lower proficiency in the identified language; and providing the ranked search results to the searching party at the online marketplace. | 1. A system for ranking search results in an electronic environment, the system comprising: processors; and a memory storing instructions that, when executed by at least one processor among the processors, cause the system to perform operations comprising: receiving a search query from a computing device of a searching party located in a geographic region, wherein the search query is received by an online marketplace visited by the searching party using the computing device; conducting a search and generating search results based on the search query; retrieving an IP address or a browser language setting of the computing device of the searching party; identifying the geographic region of the searching party based at least in part on the retrieved IP address or the retrieved browser language setting of the computing device of the searching party; identifying a language associated with the identified geographic region of the searching party based on the identified geographic region of the searching party; for a seller associated with at least one of the search results, determining a proficiency in the language associated with the geographic region of the searching party; ranking the search results based on at least the identified language and the proficiency, wherein search results associated with a higher proficiency in the identified language are ranked higher relative to search results associated with a lower proficiency in the identified language; and providing the ranked search results to the searching party at the online marketplace. 2. The system of claim 1 , further comprising identifying a geographic region of a seller associated with at least one of the search results, identifying a language associated with the geographic region of the seller, and prioritizing the search results based on a matching or similarity between the language of the geographic region of the searching party and the language of the geographic region of the seller. | 0.675824 |
8,355,025 | 1 | 3 | 1. A method comprising: receiving character outline data, wherein the character outline data includes a set of points; determining original interval boundaries and original breakpoints based on the character outline data, wherein the original breakpoints are represented by points on a y-axis, and wherein the original interval boundaries are specified to bound intervals on the y-axis only; creating modified breakpoints and modified interval boundaries to correspond to pixel boundaries, wherein each of the modified interval boundaries is a distance from one of the original interval boundaries and the modified interval boundaries are specified to bound intervals on the y-axis only; and vertically repositioning certain points of the set of points based on the distances without using hinting information and wherein horizontal stems of the character maintain the same thickness through the repositioning. | 1. A method comprising: receiving character outline data, wherein the character outline data includes a set of points; determining original interval boundaries and original breakpoints based on the character outline data, wherein the original breakpoints are represented by points on a y-axis, and wherein the original interval boundaries are specified to bound intervals on the y-axis only; creating modified breakpoints and modified interval boundaries to correspond to pixel boundaries, wherein each of the modified interval boundaries is a distance from one of the original interval boundaries and the modified interval boundaries are specified to bound intervals on the y-axis only; and vertically repositioning certain points of the set of points based on the distances without using hinting information and wherein horizontal stems of the character maintain the same thickness through the repositioning. 3. The method of claim 1 , wherein one of the original interval boundaries corresponds to a distance from a top of a lowercase character to a baseline. | 0.640476 |
8,868,637 | 1 | 7 | 1. A method comprising: by a code segment executing on a client computing device and embedded in a first structured document rendered by the client computing device, detecting an event on the first structured document, the event directing the client application to generate a first request for a second structured document from a remote server; by the code segment, intercepting the first request; by the code segment, identifying one or more resources specified in the first request that are not currently stored on the client computing device; by the code segment, generating a second request for resources to be sent to the remote server, wherein the second request specifies only one or more of the resources specified in the first request that are not currently stored on the client computing device; sending the second request to the remote server; receiving, in response to the second request, one or more of the resources specified in the second request; and rendering the second structured document with: one or more of the resources specified in the first request that are currently stored on the client computing device; and one or more of the resources received in response to the second request. | 1. A method comprising: by a code segment executing on a client computing device and embedded in a first structured document rendered by the client computing device, detecting an event on the first structured document, the event directing the client application to generate a first request for a second structured document from a remote server; by the code segment, intercepting the first request; by the code segment, identifying one or more resources specified in the first request that are not currently stored on the client computing device; by the code segment, generating a second request for resources to be sent to the remote server, wherein the second request specifies only one or more of the resources specified in the first request that are not currently stored on the client computing device; sending the second request to the remote server; receiving, in response to the second request, one or more of the resources specified in the second request; and rendering the second structured document with: one or more of the resources specified in the first request that are currently stored on the client computing device; and one or more of the resources received in response to the second request. 7. The method of claim 1 , wherein the second request comprises an asynchronous request that comprises an XMLHttpRequest (XHR) or JSON request. | 0.872093 |
8,372,122 | 26 | 28 | 26. A spine stabilization device comprising: a bone anchor; a deflectable mount; and a self-centering joint connecting the bone anchor and the deflectable mount; wherein the self-centering joint includes, a housing having a socket; a retainer pivotably received in the socket; and a centering rod having an inner core and an outer sheath, the centering rod received partially within the retainer and partially within the housing; whereby deflection of the retainer bends the centering rod and the centering rod exerts a restoring force on the retainer. | 26. A spine stabilization device comprising: a bone anchor; a deflectable mount; and a self-centering joint connecting the bone anchor and the deflectable mount; wherein the self-centering joint includes, a housing having a socket; a retainer pivotably received in the socket; and a centering rod having an inner core and an outer sheath, the centering rod received partially within the retainer and partially within the housing; whereby deflection of the retainer bends the centering rod and the centering rod exerts a restoring force on the retainer. 28. The spine stabilization device of claim 26 , wherein said inner core of said centering rod is made of nitinol and said outer sheath is made of PEEK. | 0.903919 |
7,868,792 | 13 | 15 | 13. A method for detecting whether an arbitrary-length bit string input matches one of a plurality of known arbitrary-length bit strings, using a memory storing, for each of the plurality of known arbitrary-length bit strings, the known arbitrary-length bit string or a pointer thereto, in an addressed location, and a hierarchical data structure, wherein each level of the hierarchical data structure includes one or more nodes, each node associated with an indication of a hash function and a boundary value, the boundary value partitioning a set of results of the hash function of at least some of the known arbitrary-length bit strings, the method comprising: a) interrogating the hierarchical data structure using hashes of the input arbitrary-length bit string, the indicated hash functions and the boundaries to determine an address of the memory; b) reading the known arbitrary-length bit string or a pointer thereto, from the memory at the determined address; and c) comparing the input arbitrary-length bit string and the known arbitrary-length bit string to determine whether or not a match exists. | 13. A method for detecting whether an arbitrary-length bit string input matches one of a plurality of known arbitrary-length bit strings, using a memory storing, for each of the plurality of known arbitrary-length bit strings, the known arbitrary-length bit string or a pointer thereto, in an addressed location, and a hierarchical data structure, wherein each level of the hierarchical data structure includes one or more nodes, each node associated with an indication of a hash function and a boundary value, the boundary value partitioning a set of results of the hash function of at least some of the known arbitrary-length bit strings, the method comprising: a) interrogating the hierarchical data structure using hashes of the input arbitrary-length bit string, the indicated hash functions and the boundaries to determine an address of the memory; b) reading the known arbitrary-length bit string or a pointer thereto, from the memory at the determined address; and c) comparing the input arbitrary-length bit string and the known arbitrary-length bit string to determine whether or not a match exists. 15. The method of claim 13 wherein the acts of the method include, starting at a first level of the hierarchical data structure, 1) hashing the arbitrary length bit string using the indicated hash function to obtain a value; 2) comparing the obtained value with the boundary value; 3) if the obtained value is less than or equal to the boundary value, defining an address bit as a first bit value, otherwise defining the address bit as a second bit value; 4) determining whether the present level of the hierarchical data structure is a last level; and 5) if it was determined that the present level of the hierarchical data structure is not the last level, then A) concatenating the address bit with any previous address bits, and B) repeating acts (1) through (4) at a next level of the hierarchical data structure, and otherwise, if it was determined that present level of the hierarchical data structure is the last level, then A) concatenating the address bit with any previous address bits, and B) reading the stored arbitrary-length bit string using an addressed memory location at an address defined by the concatenation of the address bits, and C) comparing the read arbitrary-length bit string to the arbitrary-length bit string input to determine whether a match exists. | 0.50039 |
9,110,501 | 1 | 8 | 1. A method for detecting and classifying talking segments of a face in a visual cue in order to infer emotions, the method comprising: normalizing and localizing a face region for each frame of the visual cue; obtaining a histogram of structure descriptive features of the face for the frame in the visual cue; deriving an integrated gradient histogram (IGH) from the descriptive features for the frame in the visual cue; computing entropy of the IGH for the frame in the visual cue; performing segmentation of the IGH to detect talking segments for the face in the visual cues; and analyzing the segments for the frame in the visual cues to infer emotions. | 1. A method for detecting and classifying talking segments of a face in a visual cue in order to infer emotions, the method comprising: normalizing and localizing a face region for each frame of the visual cue; obtaining a histogram of structure descriptive features of the face for the frame in the visual cue; deriving an integrated gradient histogram (IGH) from the descriptive features for the frame in the visual cue; computing entropy of the IGH for the frame in the visual cue; performing segmentation of the IGH to detect talking segments for the face in the visual cues; and analyzing the segments for the frame in the visual cues to infer emotions. 8. The method as in claim 1 , wherein the visual cue is at least one of an image frame and video data comprising a sequence of frames. | 0.85078 |
9,325,508 | 49 | 50 | 49. The method of claim 48 , wherein the registration authority operates under at least one of a plurality of operational policies and procedures of the registration authority. | 49. The method of claim 48 , wherein the registration authority operates under at least one of a plurality of operational policies and procedures of the registration authority. 50. The method of claim 49 , wherein each of the operational policies and procedures under which the registration authority operates has a policy identifier. | 0.97085 |
8,190,618 | 8 | 10 | 8. A computer system for aggregating usage indications for an electronic document, the computer system comprising: one or more processors, one or more computer-readable memories and one or more computer-readable tangible storage devices; program instructions, stored on at least one of the one or more storage devices for execution by at least one of the one or more processors via at least one of the one or more memories, to assign a unique identifier to each segment of a plurality of segments of the electronic document at a time of creation of the electronic document; program instructions, stored on at least one of the one or more storage devices for execution by at least one of the one or more processors via at least one of the one or more memories, to determine usage indication data associated with each segment of the plurality of segments of the electronic document, wherein the usage indication data comprise a measure of time spent using the electronic document; program instructions, stored on at least one of the one or more storage devices for execution by at least one of the one or more processors via at least one of the one or more memories, to aggregate the usage indication data for a plurality of users of the electronic document on a segment by segment basis; and program instructions, stored on at least one of the one or more storage devices for execution by at least one of the one or more processors via at least one of the one or more memories, to communicate to a user of the electronic document the aggregate usage indication data on a segment by segment basis. | 8. A computer system for aggregating usage indications for an electronic document, the computer system comprising: one or more processors, one or more computer-readable memories and one or more computer-readable tangible storage devices; program instructions, stored on at least one of the one or more storage devices for execution by at least one of the one or more processors via at least one of the one or more memories, to assign a unique identifier to each segment of a plurality of segments of the electronic document at a time of creation of the electronic document; program instructions, stored on at least one of the one or more storage devices for execution by at least one of the one or more processors via at least one of the one or more memories, to determine usage indication data associated with each segment of the plurality of segments of the electronic document, wherein the usage indication data comprise a measure of time spent using the electronic document; program instructions, stored on at least one of the one or more storage devices for execution by at least one of the one or more processors via at least one of the one or more memories, to aggregate the usage indication data for a plurality of users of the electronic document on a segment by segment basis; and program instructions, stored on at least one of the one or more storage devices for execution by at least one of the one or more processors via at least one of the one or more memories, to communicate to a user of the electronic document the aggregate usage indication data on a segment by segment basis. 10. The computer system of claim 8 , wherein the program instructions to aggregate the usage indication data for the plurality of users of the electronic document on a segment by segment basis aggregate the usage information for a plurality of versions of the electronic document on a segment by segment basis. | 0.546784 |
8,209,605 | 12 | 13 | 12. A non-transitory digital storage medium storing a computer program for use with a computing system, the computer program, when executed on a the computing system, configured to: identify textual content according to a hierarchy, the hierarchy including by a plurality of nodes that are each respectively associated with a portion of the textual content, the plurality of nodes including a first node associated with a first portion of the textual content and a second node that is associated with a second different portion of the textual content and is also a child of the first node, the second node being a leaf node, assign a visualization form from a plurality of visualization forms to each one of the plurality of nodes, the plurality of visualization forms including at least an open form, a tokenized form, and an invisible form; display the portion of textual content that is associated with the respective node based on the assigned visualization form; and update the visualization form of at least one of the plurality of nodes based on user input, wherein the textual content of the second node is not displayed when the visualization form for the second node includes the invisible form, wherein less than a full amount of the textual content associated with the second node is displayed when the visualization form for the second node includes the tokenized form, and wherein the textual content associated with the second node is displayed when the visualization form for the second node includes the open form. | 12. A non-transitory digital storage medium storing a computer program for use with a computing system, the computer program, when executed on a the computing system, configured to: identify textual content according to a hierarchy, the hierarchy including by a plurality of nodes that are each respectively associated with a portion of the textual content, the plurality of nodes including a first node associated with a first portion of the textual content and a second node that is associated with a second different portion of the textual content and is also a child of the first node, the second node being a leaf node, assign a visualization form from a plurality of visualization forms to each one of the plurality of nodes, the plurality of visualization forms including at least an open form, a tokenized form, and an invisible form; display the portion of textual content that is associated with the respective node based on the assigned visualization form; and update the visualization form of at least one of the plurality of nodes based on user input, wherein the textual content of the second node is not displayed when the visualization form for the second node includes the invisible form, wherein less than a full amount of the textual content associated with the second node is displayed when the visualization form for the second node includes the tokenized form, and wherein the textual content associated with the second node is displayed when the visualization form for the second node includes the open form. 13. The medium of claim 12 , wherein the hierarchy is stored by mark-up within sequential storage of the document contents. | 0.810769 |
8,498,870 | 7 | 8 | 7. A system according to claim 5 , wherein said order related data comprises order related parameters identifying at least one of, (a) quantity, (b) a route of administration of a medical treatment, (c) a frequency of administering a treatment and (d) a form of medical treatment. | 7. A system according to claim 5 , wherein said order related data comprises order related parameters identifying at least one of, (a) quantity, (b) a route of administration of a medical treatment, (c) a frequency of administering a treatment and (d) a form of medical treatment. 8. A system according to claim 7 , wherein said form of medical treatment comprises at least one of, (a) a package type, (b) a strength of a medical treatment and (c) a concentration of a medical treatment. | 0.93481 |
9,223,745 | 2 | 3 | 2. A method according to claim 1 , further comprising: storing a plurality of datasets at the database server, each dataset having an associated node ID; and storing one or more vocabularies at the database server, each vocabulary for use in classifying datasets, and storing attributes associated with a dataset indexed by node ID, wherein each attribute comprises spatial data or references an element within a vocabulary. | 2. A method according to claim 1 , further comprising: storing a plurality of datasets at the database server, each dataset having an associated node ID; and storing one or more vocabularies at the database server, each vocabulary for use in classifying datasets, and storing attributes associated with a dataset indexed by node ID, wherein each attribute comprises spatial data or references an element within a vocabulary. 3. A method according to claim 2 , wherein performing a search of the database server by comparing each temporary table with a pre-existing table stored in the database server to identify any datasets satisfying the input query comprises: joining each temporary table with a pre-existing table stored in the database server to identify node IDs of datasets satisfying a term in the input query; and where there is more than one temporary table, combining the results of the joining operations to identify node IDs of datasets satisfying the complete input query. | 0.888181 |
9,946,511 | 1 | 2 | 1. A method for user training of an information dialogue system being at least partially implemented on a computing device, the method comprising: activating a user input subsystem associated with the computing device, the user input subsystem including at least one of a voice record and recognition component and a keyboard; receiving, by the user input subsystem, a training request, the training request being entered by a user via at least one of the voice record and recognition component and the keyboard associated with the computing device, wherein the training request includes instructions to personalize a response of the information dialog system to a request synonym, wherein the training request further includes a user request and instructions to associate, by the information dialogue system, the user request comprising at least one word with a sequence of actions to be performed by the information dialogue system, wherein at least one of the actions includes accessing a website; converting, by the user input subsystem, the training request of the user into a first text; sending the first text of the training request obtained as a result of the converting to a dialogue module associated with the computing device; processing, by the dialogue module, the first text of the training request; forming and sending, by the dialogue module, a confirmation request to the user; providing the confirmation request to the user, wherein the providing the confirmation request includes displaying the confirmation request or reproducing the confirmation request; receiving, by the user input subsystem, a response to the confirmation request, the response to the confirmation request being entered by the user: converting, by the user input subsystem, the response to the confirmation request into a second text; sending the second text of the response to the confirmation request to the dialogue module; processing, by the dialogue module, the second text of the response to the confirmation request; confirming that the training request and the response to the confirmation request are accepted by the information dialogue system; determining, by the dialogue module, whether the training request conflicts with preliminary settings of the information dialogue system; based on the determining that the training request conflicts with the preliminary settings, modifying, by the dialogue module, the preliminary settings to avoid conflicting the training request; forming, by the dialogue module, a response to the training request, wherein the response to the training request is formed as a command executed by the user input subsystem and one or more of the following: a voice cue and a response text, the command executed by the user input subsystem being based on the instructions and including associating the user request with the sequence of actions, the response being personalized based on the instructions, wherein the personalizing includes establishing the request synonym for the one or more of the voice cue, the response text, and the action; sending the response to the training request to the user; automatic activating the user input subsystem after the response to the training request is sent to the user; receiving, by the user input subsystem, the user request from the user, wherein the user request is entered by the user via at least one of the voice record and recognition component and the keyboard; converting, by the user input subsystem, the user request into a third text and sending the third text to the dialogue module; processing, by the dialogue module, the third text; and based on the processing of the third text, sequentially performing, by the information dialogue system, the sequence of actions based on the instructions of the training request, wherein the at least one of the actions includes accessing, by the computing device the website. | 1. A method for user training of an information dialogue system being at least partially implemented on a computing device, the method comprising: activating a user input subsystem associated with the computing device, the user input subsystem including at least one of a voice record and recognition component and a keyboard; receiving, by the user input subsystem, a training request, the training request being entered by a user via at least one of the voice record and recognition component and the keyboard associated with the computing device, wherein the training request includes instructions to personalize a response of the information dialog system to a request synonym, wherein the training request further includes a user request and instructions to associate, by the information dialogue system, the user request comprising at least one word with a sequence of actions to be performed by the information dialogue system, wherein at least one of the actions includes accessing a website; converting, by the user input subsystem, the training request of the user into a first text; sending the first text of the training request obtained as a result of the converting to a dialogue module associated with the computing device; processing, by the dialogue module, the first text of the training request; forming and sending, by the dialogue module, a confirmation request to the user; providing the confirmation request to the user, wherein the providing the confirmation request includes displaying the confirmation request or reproducing the confirmation request; receiving, by the user input subsystem, a response to the confirmation request, the response to the confirmation request being entered by the user: converting, by the user input subsystem, the response to the confirmation request into a second text; sending the second text of the response to the confirmation request to the dialogue module; processing, by the dialogue module, the second text of the response to the confirmation request; confirming that the training request and the response to the confirmation request are accepted by the information dialogue system; determining, by the dialogue module, whether the training request conflicts with preliminary settings of the information dialogue system; based on the determining that the training request conflicts with the preliminary settings, modifying, by the dialogue module, the preliminary settings to avoid conflicting the training request; forming, by the dialogue module, a response to the training request, wherein the response to the training request is formed as a command executed by the user input subsystem and one or more of the following: a voice cue and a response text, the command executed by the user input subsystem being based on the instructions and including associating the user request with the sequence of actions, the response being personalized based on the instructions, wherein the personalizing includes establishing the request synonym for the one or more of the voice cue, the response text, and the action; sending the response to the training request to the user; automatic activating the user input subsystem after the response to the training request is sent to the user; receiving, by the user input subsystem, the user request from the user, wherein the user request is entered by the user via at least one of the voice record and recognition component and the keyboard; converting, by the user input subsystem, the user request into a third text and sending the third text to the dialogue module; processing, by the dialogue module, the third text; and based on the processing of the third text, sequentially performing, by the information dialogue system, the sequence of actions based on the instructions of the training request, wherein the at least one of the actions includes accessing, by the computing device the website. 2. The method of claim 1 , further comprising, after the sending the response to the training request, providing the response to the training request, wherein the providing the response to the training request includes one or more of the following: displaying the response to the training request and reproducing the response to the training request. | 0.816946 |
10,049,482 | 4 | 5 | 4. The animation server system of claim 3 , wherein instructions, when executed by the at least one processor, cause the system to determine the compatibility score by comparing a similarity between the pose of the 3D character at the end of the first animation and the initial 3D motion model pose at a start of an animation from the one or more additional animations. | 4. The animation server system of claim 3 , wherein instructions, when executed by the at least one processor, cause the system to determine the compatibility score by comparing a similarity between the pose of the 3D character at the end of the first animation and the initial 3D motion model pose at a start of an animation from the one or more additional animations. 5. The animation server system of claim 4 , wherein instructions, when executed by the at least one processor, cause the system to compare the similarity between the pose of the 3D character at the end of the first animation and the initial 3D motion model pose at the start of the animation of the one or more additional animations using a weighted least squares comparison. | 0.887859 |
6,016,470 | 9 | 10 | 9. In a speech recognition system with a process of determining a highest first probability that an utterance is within a rejection grammar and a highest second probability that the utterance is within a main grammar, wherein the utterance is rejected if the highest first probability is higher than the highest second probability, and the utterance is accepted if the highest second probability is higher than the highest first probability, the rejection grammar process comprising the steps of: generating a selected digitized list of phoneme models in a language, said selected digitized list of phoneme models smaller than a digitized list of all phoneme models in the language, presenting a digitized sequential representation of the utterance for processing by the rejection grammar process, and calculating a first set of probabilities representing the match between the sequential representation of the utterance and sequential combinations, or paths, of the phoneme models from the selected digitized list of phoneme models. | 9. In a speech recognition system with a process of determining a highest first probability that an utterance is within a rejection grammar and a highest second probability that the utterance is within a main grammar, wherein the utterance is rejected if the highest first probability is higher than the highest second probability, and the utterance is accepted if the highest second probability is higher than the highest first probability, the rejection grammar process comprising the steps of: generating a selected digitized list of phoneme models in a language, said selected digitized list of phoneme models smaller than a digitized list of all phoneme models in the language, presenting a digitized sequential representation of the utterance for processing by the rejection grammar process, and calculating a first set of probabilities representing the match between the sequential representation of the utterance and sequential combinations, or paths, of the phoneme models from the selected digitized list of phoneme models. 10. The method of claim 9 wherein calculating the first set of probabilities comprises the steps of: comparing the digitized sequential representation of the utterance to all possible sequences of the phoneme models from said selected digitized list of phoneme models, and calculating the probabilities from said comparing step. | 0.811494 |
9,323,739 | 3 | 7 | 3. A method comprising: monitoring, by use of a processor, first communications at a digital processing system; determining usage frequencies of a plurality of words in one or more contexts, the one or more contexts comprising a target audience, a subject, and a location and wherein a combination of the one or more contexts is independently associated with a sub-dictionary of a plurality of sub-dictionaries; identifying a first word in response to a usage frequency for the first word in a first context combination of the one or more contexts exceeding a use threshold; and adding the first word to a first sub-dictionary of the plurality of sub-dictionaries with a greatest number context elements matching the first context combination. | 3. A method comprising: monitoring, by use of a processor, first communications at a digital processing system; determining usage frequencies of a plurality of words in one or more contexts, the one or more contexts comprising a target audience, a subject, and a location and wherein a combination of the one or more contexts is independently associated with a sub-dictionary of a plurality of sub-dictionaries; identifying a first word in response to a usage frequency for the first word in a first context combination of the one or more contexts exceeding a use threshold; and adding the first word to a first sub-dictionary of the plurality of sub-dictionaries with a greatest number context elements matching the first context combination. 7. The method of claim 3 , wherein the first communications comprise one or more of email, text messages, telephone conversations, video conversations, and viewed documents. | 0.78536 |
9,183,199 | 11 | 14 | 11. A communication device for a multiple language translation system comprising: a main housing for holding electrical components and circuitry utilized for operation of the communication device; a wireless transmitter receiver module for communicating with other devices, the wireless transmitter receiver module comprising: a bluetooth transceiver for connecting with other communication devices for the multiple language translation system and allowing the communication device to communicate using the multiple language translation system with the other communication devices; and a wi-fi transceiver for connecting to the Internet; the communication device receiving an original language input from an originating user via the bluetooth transceiver; translating the original language input into base language text; converting the base language text into at least one word code; determining at least one target language word using the at least one word code; searching for the at least one target language word on the Internet via the wi-fi transceiver; ranking search result entries based on user preferred translations submitted by other users; selecting a search result entry from search results based on user preferred translations ranking; performing a reverse translation process on the selected search result entry to translate the selected search result entry back into a language of the original language input; presenting result of the reverse translation process to the originating user in the language of the original language input via the bluetooth transceiver; receiving via the bluetooth transceiver an indication from the originating user that the result of the reverse translation process is correct; selecting another search result entry from the search results if the originating user indicates that the result of the reverse translation process is not correct; performing the reverse translation process and presenting the result of the reverse translation process to the originating user until the originating user indicates that the result of the reverse translation process is correct; and updating a database of the communication device with results of the reverse translation process, search result entry rankings, and indications made by the originating user about the results of the reverse translation process; an earphone for providing audible translations; at least one operation switch for controlling operation settings of the communication device; a detect select switch for detecting and selecting only other communication devices within a set proximity even though other communication devices are available for connection; at least one signal indicator for visually indicating status of the communication device, the at least one signal indicator visually indicating which communication devices are connected together and allowing other communication device users to see the status of the communication device; a camera for capturing video, images, and text; a display for displaying translations, text, and image data; and a microphone for capturing spoken communication. | 11. A communication device for a multiple language translation system comprising: a main housing for holding electrical components and circuitry utilized for operation of the communication device; a wireless transmitter receiver module for communicating with other devices, the wireless transmitter receiver module comprising: a bluetooth transceiver for connecting with other communication devices for the multiple language translation system and allowing the communication device to communicate using the multiple language translation system with the other communication devices; and a wi-fi transceiver for connecting to the Internet; the communication device receiving an original language input from an originating user via the bluetooth transceiver; translating the original language input into base language text; converting the base language text into at least one word code; determining at least one target language word using the at least one word code; searching for the at least one target language word on the Internet via the wi-fi transceiver; ranking search result entries based on user preferred translations submitted by other users; selecting a search result entry from search results based on user preferred translations ranking; performing a reverse translation process on the selected search result entry to translate the selected search result entry back into a language of the original language input; presenting result of the reverse translation process to the originating user in the language of the original language input via the bluetooth transceiver; receiving via the bluetooth transceiver an indication from the originating user that the result of the reverse translation process is correct; selecting another search result entry from the search results if the originating user indicates that the result of the reverse translation process is not correct; performing the reverse translation process and presenting the result of the reverse translation process to the originating user until the originating user indicates that the result of the reverse translation process is correct; and updating a database of the communication device with results of the reverse translation process, search result entry rankings, and indications made by the originating user about the results of the reverse translation process; an earphone for providing audible translations; at least one operation switch for controlling operation settings of the communication device; a detect select switch for detecting and selecting only other communication devices within a set proximity even though other communication devices are available for connection; at least one signal indicator for visually indicating status of the communication device, the at least one signal indicator visually indicating which communication devices are connected together and allowing other communication device users to see the status of the communication device; a camera for capturing video, images, and text; a display for displaying translations, text, and image data; and a microphone for capturing spoken communication. 14. The communication device for a multiple language translation system of claim 11 , further comprising: a remote control located separately from the main housing but a part of the communication device for controlling settings and operations of the communication device, the remote control wirelessly connecting to electrical components in the main housing. | 0.857143 |
8,397,223 | 30 | 31 | 30. An apparatus, comprising: means for receiving input files associated with a graphical user interface code; means for generating an application framework code; means for receiving web application business logic objects; means for organizing the application framework code and the web application business logic objects into web application source code; means for binding the web application source code with the input files; and means for compiling the input files; wherein the application framework code is configured to, at runtime, detect any change to web application screens to re-compile the input files in response to detecting a change. | 30. An apparatus, comprising: means for receiving input files associated with a graphical user interface code; means for generating an application framework code; means for receiving web application business logic objects; means for organizing the application framework code and the web application business logic objects into web application source code; means for binding the web application source code with the input files; and means for compiling the input files; wherein the application framework code is configured to, at runtime, detect any change to web application screens to re-compile the input files in response to detecting a change. 31. The apparatus of claim 30 , wherein the input files are in XML, HTML, cHTML, or WML format. | 0.926698 |
9,794,766 | 4 | 5 | 4. The computer-implemented method of claim 3 , wherein determining, by the one or more processors, a semantic location of a user device based at least in part on the entity associated with the wireless network access point comprises: receiving, by the one or more processors, a signal indicative of a user device connection to the wireless network access point; and determining, by the one or more processors, the semantic location of the user device based at least in part on the entity associated with the wireless network access point. | 4. The computer-implemented method of claim 3 , wherein determining, by the one or more processors, a semantic location of a user device based at least in part on the entity associated with the wireless network access point comprises: receiving, by the one or more processors, a signal indicative of a user device connection to the wireless network access point; and determining, by the one or more processors, the semantic location of the user device based at least in part on the entity associated with the wireless network access point. 5. The computer-implemented method of claim 4 , wherein the connection is an authenticated connection. | 0.970332 |
8,250,118 | 12 | 14 | 12. The method of claim 5 , wherein the step of displaying the legal case history further includes automatically positioning the graphical representation of the parent case and the graphical representations of the related cases in the graphical flow-chart format according to a set of rules. | 12. The method of claim 5 , wherein the step of displaying the legal case history further includes automatically positioning the graphical representation of the parent case and the graphical representations of the related cases in the graphical flow-chart format according to a set of rules. 14. The method of claim 12 , wherein the set of rules includes the following rule: when the parent case has one or more related cases that are children to the parent case, and where the parent and child cases were decided in different courts, the graphical representation of the parent case is positioned below the graphical representations of the child cases. | 0.883041 |
9,489,381 | 1 | 3 | 1. One or more non-transitory computer-readable media storing computer-executable instructions for comparing two structured documents that, when executed by one or more processors, configure the one or more processors to perform operations comprising: identifying, by performing a traversal of a first structure in a first document and a second structure in a second document, one or more potential matches between elements in the first and second documents; obtaining, from a user, specified custom rules defining expected differences between the first and second documents, the expected differences indicating a positional change between at least one actual element positioned within a first hierarchical arrangement of the first document and at least one expected element positioned within a second hierarchical arrangement of the second document; determining when differences between the identified potential matches are significant based at least in part on the custom rules, wherein significant differences are determined to be significant as a result of being differences, other than expected differences, that vary from the expected differences; and effecting data storage for the at least one difference that is determined to be significant. | 1. One or more non-transitory computer-readable media storing computer-executable instructions for comparing two structured documents that, when executed by one or more processors, configure the one or more processors to perform operations comprising: identifying, by performing a traversal of a first structure in a first document and a second structure in a second document, one or more potential matches between elements in the first and second documents; obtaining, from a user, specified custom rules defining expected differences between the first and second documents, the expected differences indicating a positional change between at least one actual element positioned within a first hierarchical arrangement of the first document and at least one expected element positioned within a second hierarchical arrangement of the second document; determining when differences between the identified potential matches are significant based at least in part on the custom rules, wherein significant differences are determined to be significant as a result of being differences, other than expected differences, that vary from the expected differences; and effecting data storage for the at least one difference that is determined to be significant. 3. The one or more computer-readable media of claim 1 , wherein the instructions, when executed, further configure the one or more processors to perform operations comprising identifying transient problems as insignificant problems. | 0.884116 |
8,016,678 | 11 | 12 | 11. The method of providing the game as in claim 8 further comprising providing character enhancements with variable performance characteristics in first group activities where the activity module also requires a predetermined performance characteristic character enhancement produced by first group activities to successfully complete a second group activity. | 11. The method of providing the game as in claim 8 further comprising providing character enhancements with variable performance characteristics in first group activities where the activity module also requires a predetermined performance characteristic character enhancement produced by first group activities to successfully complete a second group activity. 12. The method of providing the game as in claim 11 further comprising enabling a character object exchange arranged such that characters exchange PGO's, PGO enhancements, character enhancements, PGO enhancements with variable performance characteristics, and character enhancements with variable performance characteristics whereby the required object is obtained by exchange. | 0.904412 |
6,084,595 | 1 | 18 | 1. A method of feature vector indexing, comprising the steps of: providing a plurality of feature vectors, each feature vector indicative of one of a plurality of objects, wherein each feature vector comprises at least one primitive, each primitive being associated with an attribute of the object and identifying a plurality of features, each feature having an associated feature coefficient; using a distance metric to select index values which are indicative of features of the feature vector; providing a target feature vector and a plurality of user weights; generating a constraint based on the target feature vector and the plurality of user weights; and applying the constraint to the index values so as to select a subset of the feature vectors. | 1. A method of feature vector indexing, comprising the steps of: providing a plurality of feature vectors, each feature vector indicative of one of a plurality of objects, wherein each feature vector comprises at least one primitive, each primitive being associated with an attribute of the object and identifying a plurality of features, each feature having an associated feature coefficient; using a distance metric to select index values which are indicative of features of the feature vector; providing a target feature vector and a plurality of user weights; generating a constraint based on the target feature vector and the plurality of user weights; and applying the constraint to the index values so as to select a subset of the feature vectors. 18. The method of claim 1, additionally comprising the steps of: providing a primitive function to extract an attribute from each object; and adding a new primitive function, wherein the new primitive function comprises an indexing step for a selected attribute. | 0.527076 |
10,162,609 | 6 | 15 | 6. An integrated development environment comprising: a processor; a metadata store coupled to the processor and configured to store object metadata; a metadata object modeler configured to allow creation of an object for data access; a code editor configured to receive user input object oriented source code that creates a function-expression that is displayed as a menu element in a graphical user interface of the integrated development environment; and wherein the displayed function-expression is selectable for inclusion in the object for data access. | 6. An integrated development environment comprising: a processor; a metadata store coupled to the processor and configured to store object metadata; a metadata object modeler configured to allow creation of an object for data access; a code editor configured to receive user input object oriented source code that creates a function-expression that is displayed as a menu element in a graphical user interface of the integrated development environment; and wherein the displayed function-expression is selectable for inclusion in the object for data access. 15. The integrated development environment of claim 6 , wherein the integrated development environment is embodied in a cloud computing architecture. | 0.824706 |
9,535,906 | 10 | 11 | 10. A mobile electronic device comprising: a touch sensitive screen; a detection component for detecting a change in physical orientation of the mobile electronic device; and a translator application capable of translating a word or phrase from a first language entered via a first virtual keyboard on the touch sensitive screen into a second language, wherein in response to the detection component detecting a change in the physical orientation of the mobile electronic device from a first orientation to a second orientation, the translator application: causing a translation of a word or phrase from a first language entered via the first virtual keyboard into a second language to obtain a first translation, and causing a display of the first translation in the second language and a second virtual keyboard having characters or symbols from the second language on the touch sensitive screen, wherein in response to the detection component detecting a change in the physical orientation of the mobile electronic device from the second orientation back to the first orientation, the translator application: causing a translation of a word or phrase entered via the second virtual keyboard from the second language on the touch sensitive screen into the first language to obtain a second translation, and causing a display of the second translation and the first virtual keyboard, wherein the first language is a default language or is selected by the first user, and wherein the second language is selected by a first user, selected by a second user, or determined by the mobile electronic device. | 10. A mobile electronic device comprising: a touch sensitive screen; a detection component for detecting a change in physical orientation of the mobile electronic device; and a translator application capable of translating a word or phrase from a first language entered via a first virtual keyboard on the touch sensitive screen into a second language, wherein in response to the detection component detecting a change in the physical orientation of the mobile electronic device from a first orientation to a second orientation, the translator application: causing a translation of a word or phrase from a first language entered via the first virtual keyboard into a second language to obtain a first translation, and causing a display of the first translation in the second language and a second virtual keyboard having characters or symbols from the second language on the touch sensitive screen, wherein in response to the detection component detecting a change in the physical orientation of the mobile electronic device from the second orientation back to the first orientation, the translator application: causing a translation of a word or phrase entered via the second virtual keyboard from the second language on the touch sensitive screen into the first language to obtain a second translation, and causing a display of the second translation and the first virtual keyboard, wherein the first language is a default language or is selected by the first user, and wherein the second language is selected by a first user, selected by a second user, or determined by the mobile electronic device. 11. The device of claim 10 , wherein the second virtual keyboard replaces the first virtual keyboard. | 0.941211 |
9,853,876 | 3 | 4 | 3. The method of claim 1 , wherein extracting the plurality of source code tokens comprises: extracting, from the source code of the network application, a plurality of universal resource locator (URL) strings and a plurality of key declaration strings; and further extracting a plurality of domain host names, a plurality of universal resource identifier (URI) path strings, and a first plurality of keys from the plurality of URL strings, as well as a second plurality of keys from the plurality of key declaration strings; wherein the plurality of source code tokens includes the plurality of domain host names, the plurality of URI path strings, the first plurality of keys, and the second plurality of keys. | 3. The method of claim 1 , wherein extracting the plurality of source code tokens comprises: extracting, from the source code of the network application, a plurality of universal resource locator (URL) strings and a plurality of key declaration strings; and further extracting a plurality of domain host names, a plurality of universal resource identifier (URI) path strings, and a first plurality of keys from the plurality of URL strings, as well as a second plurality of keys from the plurality of key declaration strings; wherein the plurality of source code tokens includes the plurality of domain host names, the plurality of URI path strings, the first plurality of keys, and the second plurality of keys. 4. The method of claim 3 , further comprising: obtaining, from a network application distribution platform, an executable binary data package of the network application, wherein the executable binary data package comprises an executable binary file and metadata associated with the executable binary file; and further extracting a network application download package name of the executable binary data package from the metadata, wherein the index document is generated further based on the network application download package name. | 0.821381 |
9,454,760 | 1 | 3 | 1. A method, comprising: accessing a message, by a computer, of a contact center from a sender; formulating, by the computer, a portion of a response to the message; storing, by the computer, the portion of the response in a memory; accessing, by the computer, a user context of the sender; selecting, by the computer, an embellishment in accord with the user context; retrieving, by the computer, the stored portion of the response from the memory; updating, by the computer, the retrieved portion of the response to include banter associated with the embellishment thereby creating an updated response; and sending, via a communications network, the updated response to the sender. | 1. A method, comprising: accessing a message, by a computer, of a contact center from a sender; formulating, by the computer, a portion of a response to the message; storing, by the computer, the portion of the response in a memory; accessing, by the computer, a user context of the sender; selecting, by the computer, an embellishment in accord with the user context; retrieving, by the computer, the stored portion of the response from the memory; updating, by the computer, the retrieved portion of the response to include banter associated with the embellishment thereby creating an updated response; and sending, via a communications network, the updated response to the sender. 3. The method of claim 1 , wherein the user context comprises a punctuation usage style associated at least one social media post of the sender. | 0.783784 |
9,804,687 | 2 | 3 | 2. The digital television of claim 1 further comprising a memory, wherein the second and third alphabet characters are extracted from the memory. | 2. The digital television of claim 1 further comprising a memory, wherein the second and third alphabet characters are extracted from the memory. 3. The digital television of claim 2 , wherein the second alphabet character is extracted from the memory based on a first word related to the first alphabet character. | 0.944954 |
7,904,595 | 6 | 9 | 6. A method of managing resources of a multiplicity of interrelated data sources corresponding to a plurality of sites accessed through a communications network, comprising the steps of: analyzing the multiplicity of interrelated data sources to identify architecture, protocol, language and localization requirements; establishing at least one target application interface for transferring data to and from said multiplicity of interrelated data sources; establishing a site-to-site interrelationship model identifying provider and subscriber relationships between said multiplicity of interrelated data sources, said model identifying in said multiplicity of interrelated data sources a plurality of data sources which are site content providers and at least one data source which is both a site content subscribed and a site content provider; periodically reading via one or more processors data representing site content from said multiplicity of interrelated data sources identified as site content providers in said model; comparing said periodically read data with data representing predetermined site content to identify data representing content changes; and, transferring said identified data representing changed content to at least one of said multiplicity of interrelated data sources identified as a site content subscriber in said model and at least one data source identified as both a site content subscriber and a site content provider in said model. | 6. A method of managing resources of a multiplicity of interrelated data sources corresponding to a plurality of sites accessed through a communications network, comprising the steps of: analyzing the multiplicity of interrelated data sources to identify architecture, protocol, language and localization requirements; establishing at least one target application interface for transferring data to and from said multiplicity of interrelated data sources; establishing a site-to-site interrelationship model identifying provider and subscriber relationships between said multiplicity of interrelated data sources, said model identifying in said multiplicity of interrelated data sources a plurality of data sources which are site content providers and at least one data source which is both a site content subscribed and a site content provider; periodically reading via one or more processors data representing site content from said multiplicity of interrelated data sources identified as site content providers in said model; comparing said periodically read data with data representing predetermined site content to identify data representing content changes; and, transferring said identified data representing changed content to at least one of said multiplicity of interrelated data sources identified as a site content subscriber in said model and at least one data source identified as both a site content subscriber and a site content provider in said model. 9. The method as recited in claim 6 where said step of transferring said identified data is preceded by the step of processing said identified data representing changed content by localizing said changed content for consistency with said localization requirements. | 0.908587 |
9,865,029 | 8 | 9 | 8. A method of contextually rendering graphics, the method comprising: parsing at least one graphics file into a plurality of graphics objects; determining whether one or more dynamic behavior attributes are present for each graphics object; extracting at least one tag name for each graphics object having the one or more dynamic behavior attributes; assigning an attribute weight to each of the dynamic behavior attributes; computing a sum of the attribute weights for each tag name-graphics object combination as Score_OT; sorting the plurality of graphics objects based on their respective location and respective Score_OT for each tag name; computing a combined score for each tag name-graphics file combination as a summation of all Score_OTs for an associated tag name; ranking, using circuitry, each tag name-graphics file combination according to the respective combined score; and displaying a portion of a graphics view of one or more graphics objects for a first-ranked tag name-graphics file combination in context with other graphics objects. | 8. A method of contextually rendering graphics, the method comprising: parsing at least one graphics file into a plurality of graphics objects; determining whether one or more dynamic behavior attributes are present for each graphics object; extracting at least one tag name for each graphics object having the one or more dynamic behavior attributes; assigning an attribute weight to each of the dynamic behavior attributes; computing a sum of the attribute weights for each tag name-graphics object combination as Score_OT; sorting the plurality of graphics objects based on their respective location and respective Score_OT for each tag name; computing a combined score for each tag name-graphics file combination as a summation of all Score_OTs for an associated tag name; ranking, using circuitry, each tag name-graphics file combination according to the respective combined score; and displaying a portion of a graphics view of one or more graphics objects for a first-ranked tag name-graphics file combination in context with other graphics objects. 9. The method of claim 8 , wherein the displaying includes identifying coordinates of a user's point of interest in proximity to the one or more graphics objects, and displaying the one or more graphics objects in context with other graphics objects associated with one or more of the identified coordinates. | 0.533333 |
9,965,610 | 1 | 6 | 1. A machine access control system, comprising: a camera configured to capture an input image of a subject purported to be a person associated with operating a particular workplace machine; a memory storing a deep learning model configured to perform joint multi-task learning for a pair of tasks including a liveness detection task and a face recognition task; and a processor configured to apply the deep learning model to the input image to recognize an identity of the subject in the input image regarding being authorized to use the particular workplace machine and a liveness of the subject, and wherein the liveness detection task is configured to evaluate a plurality of different distractor modalities corresponding to different physical spoofing materials to prevent face spoofing for the face recognition task. | 1. A machine access control system, comprising: a camera configured to capture an input image of a subject purported to be a person associated with operating a particular workplace machine; a memory storing a deep learning model configured to perform joint multi-task learning for a pair of tasks including a liveness detection task and a face recognition task; and a processor configured to apply the deep learning model to the input image to recognize an identity of the subject in the input image regarding being authorized to use the particular workplace machine and a liveness of the subject, and wherein the liveness detection task is configured to evaluate a plurality of different distractor modalities corresponding to different physical spoofing materials to prevent face spoofing for the face recognition task. 6. The face recognition system of claim 1 , wherein the processor is further configured to perform data preprocessing on the plurality of input images selected from the group consisting of image contrast enhancements, data augmentation, and cropping. | 0.741201 |
9,275,022 | 11 | 17 | 11. A method for providing a document stored on a cloud computing service to a client computer for rendering, the method comprising: storing a document on the cloud computing service; storing a rendering function for rendering the document, wherein the rendering function comprises instructions to: determine a maximum height of a portion of text in the document; insert into the portion of text a spacer element with a height greater than the maximum height of the portion of text; adjust, by an offset, a vertical position of the portion of text and the spacer element, wherein a baseline of the portion of text is determined from the height of the spacer element and the offset; and render the portion of text on the web browser based at least in part on the baseline; and sending the document and the rendering function to a client computer. | 11. A method for providing a document stored on a cloud computing service to a client computer for rendering, the method comprising: storing a document on the cloud computing service; storing a rendering function for rendering the document, wherein the rendering function comprises instructions to: determine a maximum height of a portion of text in the document; insert into the portion of text a spacer element with a height greater than the maximum height of the portion of text; adjust, by an offset, a vertical position of the portion of text and the spacer element, wherein a baseline of the portion of text is determined from the height of the spacer element and the offset; and render the portion of text on the web browser based at least in part on the baseline; and sending the document and the rendering function to a client computer. 17. The method of claim 11 , wherein the vertical position of the portion of text and the spacer element is defined by a top margin. | 0.794393 |
8,296,123 | 53 | 55 | 53. A system comprising: a translation server operable to perform machine translation obtaining translation model data from a translation model for translation between a source language and a target language and language model data from a language model for the target language, the translation server further operable to translate a source text in the source language into the target language using the obtained translation model data and language model data, wherein the translation model is divided into a plurality of translation model partitions, each translation model partition being less than the entire translation model and being stored on a different translation model server of a plurality of translation model servers, and the respective translation model partitions together constituting the entire translation model, and wherein language model is divided into a plurality of language model partitions, each language model partition being less than the entire language model and the respective language model partitions together constituting the entire language model; the translation server comprising: a request queue operable to store requests for language model data to be obtained for translating a segment of the source text in the source language, and a segment translation server cache operable to store language model data obtained by the requests by the translation server, wherein the translation server is configured to: i) obtain translation model data from at least one of the translation model partitions based on the segment of the source text, ii) translate the segment of the source text into a set of possible translations based on the translation model data, iii) obtain the language model data from at least one of the partitions of the language model based on the set of possible translations, the language model data matching at least one token in at least one possible translation of the set of possible translations, and iv) determine a translation of the segment based on the obtained language model data and the set of possible translations. | 53. A system comprising: a translation server operable to perform machine translation obtaining translation model data from a translation model for translation between a source language and a target language and language model data from a language model for the target language, the translation server further operable to translate a source text in the source language into the target language using the obtained translation model data and language model data, wherein the translation model is divided into a plurality of translation model partitions, each translation model partition being less than the entire translation model and being stored on a different translation model server of a plurality of translation model servers, and the respective translation model partitions together constituting the entire translation model, and wherein language model is divided into a plurality of language model partitions, each language model partition being less than the entire language model and the respective language model partitions together constituting the entire language model; the translation server comprising: a request queue operable to store requests for language model data to be obtained for translating a segment of the source text in the source language, and a segment translation server cache operable to store language model data obtained by the requests by the translation server, wherein the translation server is configured to: i) obtain translation model data from at least one of the translation model partitions based on the segment of the source text, ii) translate the segment of the source text into a set of possible translations based on the translation model data, iii) obtain the language model data from at least one of the partitions of the language model based on the set of possible translations, the language model data matching at least one token in at least one possible translation of the set of possible translations, and iv) determine a translation of the segment based on the obtained language model data and the set of possible translations. 55. The system of claim 53 , wherein: the segment translation server cache is operable to delete the obtained language model data periodically. | 0.961518 |
10,089,295 | 10 | 14 | 10. A computer program product comprising a non-transitory computer-readable storage medium having instructions encoded thereon that, when executed by a processor, cause the processor to: store a plurality of page templates, each page template including one or more regions, each region configured to present one or more content items, one or more of the plurality of page templates including one or more regions, each region associated with a height that is based on a width of a display area; receive a request from a client device to present one or more content items from one or more sources in the digital magazine to a user; retrieve information describing content items associated with the digital magazine; retrieve information describing user interaction with one or more content items associated with the digital magazine; identify one or more page templates previously associated with the digital magazine from the one or more page templates; determine weights associated with characteristics of page templates based at least in part on characteristics of the identified one or more page templates previously associated with the digital magazine; select one or more candidate page templates by applying the determined weights to one or more selected from a group consisting of: the identified one or more page templates previously associated with the digital magazine, one or more characteristics of the content items associated with the digital magazine, the user interaction with the one or more content items associated with the digital magazine, and any combination thereof; generate a score associated with each of the one or more candidate page templates, where a score associated with a candidate page template is based on a number of the content items, characteristics of the one or more content items, and a number of regions in the page template; select a display page template based on the scores associated with the one or more candidate page templates; and generate a section of the digital magazine for presentation via the client device, the section including one or more regions each presenting one or more content items placed in positions specified by the one or more regions of the display page template. | 10. A computer program product comprising a non-transitory computer-readable storage medium having instructions encoded thereon that, when executed by a processor, cause the processor to: store a plurality of page templates, each page template including one or more regions, each region configured to present one or more content items, one or more of the plurality of page templates including one or more regions, each region associated with a height that is based on a width of a display area; receive a request from a client device to present one or more content items from one or more sources in the digital magazine to a user; retrieve information describing content items associated with the digital magazine; retrieve information describing user interaction with one or more content items associated with the digital magazine; identify one or more page templates previously associated with the digital magazine from the one or more page templates; determine weights associated with characteristics of page templates based at least in part on characteristics of the identified one or more page templates previously associated with the digital magazine; select one or more candidate page templates by applying the determined weights to one or more selected from a group consisting of: the identified one or more page templates previously associated with the digital magazine, one or more characteristics of the content items associated with the digital magazine, the user interaction with the one or more content items associated with the digital magazine, and any combination thereof; generate a score associated with each of the one or more candidate page templates, where a score associated with a candidate page template is based on a number of the content items, characteristics of the one or more content items, and a number of regions in the page template; select a display page template based on the scores associated with the one or more candidate page templates; and generate a section of the digital magazine for presentation via the client device, the section including one or more regions each presenting one or more content items placed in positions specified by the one or more regions of the display page template. 14. The computer program product of claim 10 , wherein the user interaction with the one or more content items associated with the digital magazine includes a length of time to interact with a content item based at least in part on prior interactions between the user and content items associated with the digital magazine previously presented to the user. | 0.800895 |
7,752,501 | 11 | 16 | 11. An apparatus for performing dynamic globalization verification testing of a software user interface, comprising: one or more machine readable storage media, said one or more machine readable storage media comprising: a user interface control identifier adapted to identify one or more user interface controls in said software user interface having text strings that have been pseudo translated; a test case generator adapted to generate one or more applicable test cases that test for display defects stemming from said pseudo translations; a test case executor adapted to execute said test cases; and a defect logger adapted to log defects discovered by executing said test cases. | 11. An apparatus for performing dynamic globalization verification testing of a software user interface, comprising: one or more machine readable storage media, said one or more machine readable storage media comprising: a user interface control identifier adapted to identify one or more user interface controls in said software user interface having text strings that have been pseudo translated; a test case generator adapted to generate one or more applicable test cases that test for display defects stemming from said pseudo translations; a test case executor adapted to execute said test cases; and a defect logger adapted to log defects discovered by executing said test cases. 16. An apparatus in accordance with claim 11 wherein said test case generator is adapted to generate said one or more applicable test cases by categorizing said one or more user interface controls by type. | 0.891189 |
10,108,712 | 9 | 16 | 9. A method comprising: receiving at an input module of a query rewrite input language (QRIL) processor device, a one or more QRIL records, each QRIL record comprising a trigger value, a query rewrite value, and one or more metaflag elements comprising a query rewrite type metaflag that identifies each QRIL record as associated with a query rewrite type, wherein the QRIL processor device comprises a memory and one or more processors coupled to the memory; identifying, by a rewrite resolver module, a first query rewrite type for a first QRIL record of the one or more QRIL records; processing, by the rewrite resolver module, using the first query rewrite type, the first QRIL record to identify a set of precedence issues between the first QRIL record and at least one overlapping or conflicting QRIL record; identifying, by a search engine rewrite customization module, a first search engine and a first rewrite semantic structure associated with the first search engine; generating, by the search engine rewrite customization module, a first standardized rewrite from the first QRIL record, the set of precedence issues, and the first rewrite semantic structure, wherein the first standardized rewrite comprises a standardized trigger value, a standardized rewrite expression for rewriting an input query for the first search engine, and a bag of words dictionary; and providing, by the QRIL processor device, the first standardized rewrite to facilitate executing a user query using the first standardized rewrite. | 9. A method comprising: receiving at an input module of a query rewrite input language (QRIL) processor device, a one or more QRIL records, each QRIL record comprising a trigger value, a query rewrite value, and one or more metaflag elements comprising a query rewrite type metaflag that identifies each QRIL record as associated with a query rewrite type, wherein the QRIL processor device comprises a memory and one or more processors coupled to the memory; identifying, by a rewrite resolver module, a first query rewrite type for a first QRIL record of the one or more QRIL records; processing, by the rewrite resolver module, using the first query rewrite type, the first QRIL record to identify a set of precedence issues between the first QRIL record and at least one overlapping or conflicting QRIL record; identifying, by a search engine rewrite customization module, a first search engine and a first rewrite semantic structure associated with the first search engine; generating, by the search engine rewrite customization module, a first standardized rewrite from the first QRIL record, the set of precedence issues, and the first rewrite semantic structure, wherein the first standardized rewrite comprises a standardized trigger value, a standardized rewrite expression for rewriting an input query for the first search engine, and a bag of words dictionary; and providing, by the QRIL processor device, the first standardized rewrite to facilitate executing a user query using the first standardized rewrite. 16. The method of claim 9 further comprising: receiving, at a query factorization module of a search engine, an updated set of standardized rewrites comprising the first standardized rewrite; receiving, at the search engine from a first client device, a first search engine user query; rewriting the first search engine user query using the first standardized rewrite and the query factorization module; generating a first set of search results for the first search engine user query using the first standardized rewrite; and communicating the first set of search results for the first search engine user query from the search engine to the first client device. | 0.500755 |
9,810,544 | 1 | 9 | 1. A non-transitory machine-readable storage medium encoded with instructions that, when executed by one or more processors, cause the processor to carry out a process for generating one or more attribute models learned from a user's driving preferences, the process comprising: receiving attribute data for a set of driving sessions for a user, wherein attribute data for each driving session includes measurements relevant to one or more target attributes, wherein each driving session is defined in terms of one or more road segments of one or more roads traversed by the user during the set of driving sessions; applying attribute estimation rules to the attribute data to compute an attribute value for each target attribute along each road segment traversed at least once in the driving sessions; assigning a default attribute value for one or more unseen road segments of the one or more roads identified in each driving session, wherein unseen road segments correspond to road segments not yet traversed by the user during any one of the driving sessions; determining and storing an attribute model comprising attribute values computed or assigned for each road segment of the one or more roads traversed by the user during the set of driving sessions; and accessing the attribute model to generate directions for use in navigation. | 1. A non-transitory machine-readable storage medium encoded with instructions that, when executed by one or more processors, cause the processor to carry out a process for generating one or more attribute models learned from a user's driving preferences, the process comprising: receiving attribute data for a set of driving sessions for a user, wherein attribute data for each driving session includes measurements relevant to one or more target attributes, wherein each driving session is defined in terms of one or more road segments of one or more roads traversed by the user during the set of driving sessions; applying attribute estimation rules to the attribute data to compute an attribute value for each target attribute along each road segment traversed at least once in the driving sessions; assigning a default attribute value for one or more unseen road segments of the one or more roads identified in each driving session, wherein unseen road segments correspond to road segments not yet traversed by the user during any one of the driving sessions; determining and storing an attribute model comprising attribute values computed or assigned for each road segment of the one or more roads traversed by the user during the set of driving sessions; and accessing the attribute model to generate directions for use in navigation. 9. The non-transitory machine-readable medium of claim 1 , wherein receiving attribute data for a set of driving sessions for a user comprises receiving sensor data. | 0.911765 |
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