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8,677,377 | 14 | 25 | 14. A computer readable storage medium containing an executable program for building an automated assistant, where the program is configured to cause a processor to perform a method comprising: interfacing a service-oriented architecture comprising a plurality of services to an execution environment comprising an active ontology, wherein the active ontology models a domain and comprises a logical arrangement of a plurality of active processing elements, wherein each active processing element is configured to receive at least one fact relating to the modeled domain and to perform at least one action responsive to at least one received fact; and registering at least one of the plurality of services for use in the domain, by specifying at least one of: one or more active processing elements that the at least one of the plurality of services can accept; and one or more active processing elements that the at least one of the plurality of services cannot accept; wherein the active ontology filters requests for services to the at least one of the plurality of services in accordance with the one or more active processing elements specified by the at least one of the plurality of services. | 14. A computer readable storage medium containing an executable program for building an automated assistant, where the program is configured to cause a processor to perform a method comprising: interfacing a service-oriented architecture comprising a plurality of services to an execution environment comprising an active ontology, wherein the active ontology models a domain and comprises a logical arrangement of a plurality of active processing elements, wherein each active processing element is configured to receive at least one fact relating to the modeled domain and to perform at least one action responsive to at least one received fact; and registering at least one of the plurality of services for use in the domain, by specifying at least one of: one or more active processing elements that the at least one of the plurality of services can accept; and one or more active processing elements that the at least one of the plurality of services cannot accept; wherein the active ontology filters requests for services to the at least one of the plurality of services in accordance with the one or more active processing elements specified by the at least one of the plurality of services. 25. The computer readable storage medium of claim 14 , wherein at least one of the active processing elements is configured to send at least one fact relating to the modeled domain to at least one other active processing element. | 0.512766 |
7,904,808 | 1 | 2 | 1. A non-transitory computer-readable recording medium on which a document management program for managing a correction history of a document is recorded, the program making a computer function as: a document store section for storing the document; a correction history table store section for storing a correction history table; a document input section for accepting input of the document which is original and for storing the document inputted in the document store section; a document correction section for correcting a character string of the document stored in the document store section in response to operation input, for registering a correction history including a number of characters deleted by a character string deletion process and a correction history including a number of characters before replacement by a replacement process in the correction history table, and for storing the corrected document in the document store section; and a correction history analysis section for referring to the correction history table to make a decision table including an opacity rate, the opacity rate obtained by dividing a total of the number of the characters deleted by the character string deletion process and the number of the characters before the replacement by the replacement process by a number of characters included in the original document. | 1. A non-transitory computer-readable recording medium on which a document management program for managing a correction history of a document is recorded, the program making a computer function as: a document store section for storing the document; a correction history table store section for storing a correction history table; a document input section for accepting input of the document which is original and for storing the document inputted in the document store section; a document correction section for correcting a character string of the document stored in the document store section in response to operation input, for registering a correction history including a number of characters deleted by a character string deletion process and a correction history including a number of characters before replacement by a replacement process in the correction history table, and for storing the corrected document in the document store section; and a correction history analysis section for referring to the correction history table to make a decision table including an opacity rate, the opacity rate obtained by dividing a total of the number of the characters deleted by the character string deletion process and the number of the characters before the replacement by the replacement process by a number of characters included in the original document. 2. The non-transitory computer-readable recording medium according to claim 1 , wherein: the document correction section registers a correction history indicative of a character string deletion process, a character string addition process, and a character string replacement process performed on the document in the correction history table; and if a character string is added at a place where a character string is deleted, the document correction section recognizes that character string replacement is performed, and registers a correction history in the correction history table. | 0.757689 |
9,069,557 | 7 | 10 | 7. A computer-readable storage memory storing a data structure, the data structure comprising: a set of pipeline-connected entities defining a business intelligence document, the business intelligence document being defined and used at a local computing device to define a business intelligence application that runs on the local computing device, the set including: a first entity including one or more expressions and designating data of a remote data source, data of a local computing device, and a computation identifier for evaluation of the one or more expressions of the first entity, wherein the one or more expressions of the first entity are evaluated, based on the computation identifier, by transforming the data of the remote data source and data of the local computing device by the remote data source to yield a remotely computed result, a second entity including one or more expressions and designating data of a local computing device against which the one or more expressions of the second entity are to be locally evaluated to yield a locally computed result, and a visualization entity including one or more expressions defining a user interface, wherein the data of the local computing device and the remotely computed result are transformed to yield the locally computed result, at least one of the remotely computed result of the first entity and the locally computed result are presentable via the user interface defined by the visualization entity; wherein the set of pipeline-connected entities forms a directed acyclic graph and wherein independent parts of the business intelligence application are executed in parallel. | 7. A computer-readable storage memory storing a data structure, the data structure comprising: a set of pipeline-connected entities defining a business intelligence document, the business intelligence document being defined and used at a local computing device to define a business intelligence application that runs on the local computing device, the set including: a first entity including one or more expressions and designating data of a remote data source, data of a local computing device, and a computation identifier for evaluation of the one or more expressions of the first entity, wherein the one or more expressions of the first entity are evaluated, based on the computation identifier, by transforming the data of the remote data source and data of the local computing device by the remote data source to yield a remotely computed result, a second entity including one or more expressions and designating data of a local computing device against which the one or more expressions of the second entity are to be locally evaluated to yield a locally computed result, and a visualization entity including one or more expressions defining a user interface, wherein the data of the local computing device and the remotely computed result are transformed to yield the locally computed result, at least one of the remotely computed result of the first entity and the locally computed result are presentable via the user interface defined by the visualization entity; wherein the set of pipeline-connected entities forms a directed acyclic graph and wherein independent parts of the business intelligence application are executed in parallel. 10. The one or more computer-readable storage memory of claim 7 wherein the one or more expressions of the first entity are capable of communication to the remote data source. | 0.811828 |
9,799,375 | 11 | 12 | 11. The device according to claim 10 , wherein the first processing component comprises: a decoding element, configured to perform decoding processing on the audio data in the video file; and a converting element, configured to convert the decoded audio data into the caption file. | 11. The device according to claim 10 , wherein the first processing component comprises: a decoding element, configured to perform decoding processing on the audio data in the video file; and a converting element, configured to convert the decoded audio data into the caption file. 12. The device according to claim 11 , wherein the receiving component comprises: a first receiving element, configured to receive input text information; and a second receiving component, configured to receive audio data, and convert the audio data into the text information. | 0.900072 |
9,965,562 | 10 | 11 | 10. A method for provisioning industrial applications, comprising: receiving, by a system comprising a processor, a functional module and associated metadata from a first client device, wherein the metadata specifies at least an industry type and an industrial device to which the functional module pertains, and the functional module comprises at least one of an add-on functional module for an industrial application or an application upgrade module for the industrial application; indexing, by the system, the functional module in a cloud platform device based on the metadata, wherein the cloud platform device classifies the functional module according to hierarchical categories of a storage schema, and the hierarchical categories comprise at least an industry type category specifying an industry and an industrial device category specifying an industrial device; receiving, by the system, browsing data from a second client device; selecting, by the system in response to the receiving the browsing data, a subset of functional modules stored on the cloud platform device based on the browsing data, wherein the browsing data progressively narrows the subset of the functional modules based on a selected industry type and a selected industrial device identified by the browsing data; rendering, by the system, identification information for the subset of the functional modules; and delivering, by the system, a selected functional module of the subset of the functional modules to a memory location associated with the second client device. | 10. A method for provisioning industrial applications, comprising: receiving, by a system comprising a processor, a functional module and associated metadata from a first client device, wherein the metadata specifies at least an industry type and an industrial device to which the functional module pertains, and the functional module comprises at least one of an add-on functional module for an industrial application or an application upgrade module for the industrial application; indexing, by the system, the functional module in a cloud platform device based on the metadata, wherein the cloud platform device classifies the functional module according to hierarchical categories of a storage schema, and the hierarchical categories comprise at least an industry type category specifying an industry and an industrial device category specifying an industrial device; receiving, by the system, browsing data from a second client device; selecting, by the system in response to the receiving the browsing data, a subset of functional modules stored on the cloud platform device based on the browsing data, wherein the browsing data progressively narrows the subset of the functional modules based on a selected industry type and a selected industrial device identified by the browsing data; rendering, by the system, identification information for the subset of the functional modules; and delivering, by the system, a selected functional module of the subset of the functional modules to a memory location associated with the second client device. 11. The method of claim 10 , wherein the indexing the functional modules comprises indexing, as one of the functional modules, at least one of a code block, an extension pack, industrial controller code, or a human-machine interface graphic. | 0.790435 |
9,807,093 | 5 | 6 | 5. The computer-based system of claim 1 , wherein the pre-determined type of metadata comprises a portion of the metadata in the electronic document. | 5. The computer-based system of claim 1 , wherein the pre-determined type of metadata comprises a portion of the metadata in the electronic document. 6. The computer-based system of claim 5 , wherein the processor is further configured to execute the instructions to generate a request, to the user of the electronic device, for a selection of the metadata to be removed from the electronic document. | 0.871531 |
7,814,092 | 5 | 6 | 5. The computer-implemented method of claim 1 wherein receiving named entity recognition client results comprises receiving named entity recognition client results identifying named entities known to the one or more client machines, but not known to the server. | 5. The computer-implemented method of claim 1 wherein receiving named entity recognition client results comprises receiving named entity recognition client results identifying named entities known to the one or more client machines, but not known to the server. 6. The computer-implemented method of claim 5 wherein performing named entity recognition on the server comprises identifying named entities known to the server, but not known to the one or more client machines. | 0.970473 |
9,659,067 | 15 | 16 | 15. The computer-readable medium of claim 11 , wherein the graphical user interface includes multiple graphical user interface elements. | 15. The computer-readable medium of claim 11 , wherein the graphical user interface includes multiple graphical user interface elements. 16. The computer-readable medium of claim 15 , wherein obtaining, by one or more of the first servers, the graphical user interface from the index entry comprises: identifying a subset of the graphical user interface elements from the multiple graphical user interface elements based on a graphical user interface rule; and retrieving the subset of graphical user interface elements that satisfy the graphical user interface rule. | 0.930331 |
8,290,924 | 4 | 5 | 4. The method of claim 1 , wherein said determining specifications of the query comprises extracting semantics from the keywords to determine the query. | 4. The method of claim 1 , wherein said determining specifications of the query comprises extracting semantics from the keywords to determine the query. 5. The method of claim 4 , wherein said determining specifications of the query further comprises prompting and receiving at least one question type. | 0.936811 |
8,024,408 | 17 | 23 | 17. A non-transitory computer-readable storage media comprising information that, when executed by a computer, cause the computer to perform a method comprising: monitoring one or more email documents in an information stream associated with a first electronic forum; comparing information about the one or more email documents to two or more rules, wherein the comparison is between newer of the one or more email documents and older of the one or more email documents to determine when a new topic of conversation has begun; querying a set consisting of users participating in the first electronic forum when at least two of the two or more rules are satisfied; creating a new electronic forum based on one or more replies from the set of users; and subscribing each queried user of the set indicating interest in the new electronic forum to the new electronic forum, but not subscribing to the new electronic forum users of the set who do not indicate interest, wherein the two or more rules comprise at least two of the following: how long the electronic forum has been in use; how many email messages have been exchanged on the electronic forum; whether there has been a suggestion to create a new discussion forum; whether a certain number of email messages on a particular topic have been received within a predetermined time period; whether a rate of email messages exchanged on a particular topic is statistically greater than normal; or whether a certain number of forum members exchanged email messages on a particular topic within a predetermined time period. | 17. A non-transitory computer-readable storage media comprising information that, when executed by a computer, cause the computer to perform a method comprising: monitoring one or more email documents in an information stream associated with a first electronic forum; comparing information about the one or more email documents to two or more rules, wherein the comparison is between newer of the one or more email documents and older of the one or more email documents to determine when a new topic of conversation has begun; querying a set consisting of users participating in the first electronic forum when at least two of the two or more rules are satisfied; creating a new electronic forum based on one or more replies from the set of users; and subscribing each queried user of the set indicating interest in the new electronic forum to the new electronic forum, but not subscribing to the new electronic forum users of the set who do not indicate interest, wherein the two or more rules comprise at least two of the following: how long the electronic forum has been in use; how many email messages have been exchanged on the electronic forum; whether there has been a suggestion to create a new discussion forum; whether a certain number of email messages on a particular topic have been received within a predetermined time period; whether a rate of email messages exchanged on a particular topic is statistically greater than normal; or whether a certain number of forum members exchanged email messages on a particular topic within a predetermined time period. 23. The non-transitory computer-readable storage media of claim 17 , wherein the information stream comprises one or more email messages flowing between two or more of the set of users. | 0.770471 |
9,536,001 | 8 | 15 | 8. A computer-readable medium bearing computer-executable instructions which, when executed on a computing system comprising at least a processor, carry out a method for responding to a search query from a user, the method comprising: obtaining a plurality of search results from a content store in response to a search query received from a computer user, wherein each of the obtained search results is associated with a score; identifying a plurality of user intents according to the obtained search results; grouping the obtained search results into a plurality of groups, each of the plurality of groups corresponding to one of the identified plurality of user intents; selecting a first user intent from the plurality of user intents based on the search query, wherein the first user intent is selected according to the group of search results of the plurality of groups having the highest scoring search results; generating one or more search results pages from the group of search results corresponding to the selected first user intent in response to the received search query from the computer user, wherein each search results page is generated such that the groups of search results are aligned with search results pages such that each generated search results page comprises only search results of a single user intent; and providing the generated search results page to the computer user in response to the search query. | 8. A computer-readable medium bearing computer-executable instructions which, when executed on a computing system comprising at least a processor, carry out a method for responding to a search query from a user, the method comprising: obtaining a plurality of search results from a content store in response to a search query received from a computer user, wherein each of the obtained search results is associated with a score; identifying a plurality of user intents according to the obtained search results; grouping the obtained search results into a plurality of groups, each of the plurality of groups corresponding to one of the identified plurality of user intents; selecting a first user intent from the plurality of user intents based on the search query, wherein the first user intent is selected according to the group of search results of the plurality of groups having the highest scoring search results; generating one or more search results pages from the group of search results corresponding to the selected first user intent in response to the received search query from the computer user, wherein each search results page is generated such that the groups of search results are aligned with search results pages such that each generated search results page comprises only search results of a single user intent; and providing the generated search results page to the computer user in response to the search query. 15. The computer-readable medium of claim 8 , wherein each group of the search results is presented on the search results page as a tabbed view of search results. | 0.915537 |
8,032,860 | 1 | 8 | 1. A method for editing a source code file, comprising: modifying the source code file using a language-independent source code editor, wherein the language-independent source code editor does not include a language-specific lexical analyzer or parser; sending a change notification to an extensible multi-language compiler framework identifying a changed file, changed text, and type of change, wherein the editor communicates to the compiler framework using language-independent metadata, and wherein the compiler framework provides a stream of token nodes, supports mixing and nesting of languages within a source file, and provides the editor with information about the source file, comprising signatures of classes defined by the source file, errors found in the source file, stacks of nested languages at any point in the source file, and information exposed by any language; retokenizing the source code file and updating token and node information; enqueueing a task for the extensible multi-language compiler framework to complete compilation in a background thread; repainting a screen giving immediate feedback to a user; and emptying enqueued tasks and completing remaining steps in the background thread; wherein the extensible multi-language compiler framework has error correction in code-generation, permitting the user to run code even if there is an error in the code; wherein a thread pool allows compilation of multiple files to be performed in parallel; wherein a type cache contains signatures for classes. | 1. A method for editing a source code file, comprising: modifying the source code file using a language-independent source code editor, wherein the language-independent source code editor does not include a language-specific lexical analyzer or parser; sending a change notification to an extensible multi-language compiler framework identifying a changed file, changed text, and type of change, wherein the editor communicates to the compiler framework using language-independent metadata, and wherein the compiler framework provides a stream of token nodes, supports mixing and nesting of languages within a source file, and provides the editor with information about the source file, comprising signatures of classes defined by the source file, errors found in the source file, stacks of nested languages at any point in the source file, and information exposed by any language; retokenizing the source code file and updating token and node information; enqueueing a task for the extensible multi-language compiler framework to complete compilation in a background thread; repainting a screen giving immediate feedback to a user; and emptying enqueued tasks and completing remaining steps in the background thread; wherein the extensible multi-language compiler framework has error correction in code-generation, permitting the user to run code even if there is an error in the code; wherein a thread pool allows compilation of multiple files to be performed in parallel; wherein a type cache contains signatures for classes. 8. The method of claim 1 , wherein the compiler framework keeps track of errors in all source files in a project so that the user can have a complete list of all errors in opened and unopened source code files in a project. | 0.764768 |
8,744,861 | 13 | 17 | 13. A system for invoking a tapered prompt comprising a plurality of prompt elements, each prompt element comprising a voice component and a non-voice component, the system comprising at least one processor programmed to: select a first voice style for the voice component of a first prompt element in the plurality of prompt elements of the tapered prompt, wherein the voice component of the first prompt element solicits requested information from a user; select, in conjunction with selecting the first voice style, a first non-voice style for the non-voice component of the first prompt element, wherein the non-voice component of the first prompt element solicits the same requested information as the voice component of the first prompt element; receive voice input provided by the user in response to the first prompt element; process the voice input to determine whether the user provided the requested information; and in response to determining that at least some of the requested information was not provided by the user, select a second voice style for the voice component of a second prompt element of the tapered prompt, and select, in conjunction with selecting the second voice style, a second non-voice style for the non-voice component of the second prompt element, wherein: both the voice component and non-voice component of the second prompt element further solicit the at least some of the requested information from the user, the second voice style is different from the first voice style, and the second non-voice style is different from the first non-voice style. | 13. A system for invoking a tapered prompt comprising a plurality of prompt elements, each prompt element comprising a voice component and a non-voice component, the system comprising at least one processor programmed to: select a first voice style for the voice component of a first prompt element in the plurality of prompt elements of the tapered prompt, wherein the voice component of the first prompt element solicits requested information from a user; select, in conjunction with selecting the first voice style, a first non-voice style for the non-voice component of the first prompt element, wherein the non-voice component of the first prompt element solicits the same requested information as the voice component of the first prompt element; receive voice input provided by the user in response to the first prompt element; process the voice input to determine whether the user provided the requested information; and in response to determining that at least some of the requested information was not provided by the user, select a second voice style for the voice component of a second prompt element of the tapered prompt, and select, in conjunction with selecting the second voice style, a second non-voice style for the non-voice component of the second prompt element, wherein: both the voice component and non-voice component of the second prompt element further solicit the at least some of the requested information from the user, the second voice style is different from the first voice style, and the second non-voice style is different from the first non-voice style. 17. The system of claim 13 , wherein the non-voice component of the second prompt element is a textual component, and wherein the second non-voice style is a textual style having an intensity that matches an intensity of the second voice style. | 0.700246 |
7,788,594 | 1 | 3 | 1. A method of presenting a data input interface, the method comprising: displaying a single text input field which, through a first input to the text input field itself, can select between at least a first operation and a second operation; displaying, by a data processing system, a separator within the text input field, wherein a first portion and a second portion are separated by the separator; receiving the first input to the single text input field to determine a selected operation which includes one of the first operation or the second operation, wherein the first input comprises receiving a user input in either the first portion or the second portion of the text input field, wherein the first operation is selected if the user input is positioned in the first portion when the user input is received and wherein the second operation is selected if the user input is positioned in the second portion when the user input is received, wherein the first operation is a text search through a first source of data and wherein the second operation is either a file operation or a search operation that is different than the first operation, and wherein in response to the first input, the separator automatically disappears from the text input field and the first portion dominates the entire area of the text input field if the first operation is selected and the second portion dominates the entire area of the text input field if the second operation is selected; receiving a text input in the single text input field, the text input being displayable in the entire single text input field and performing the selected operation on the text input. | 1. A method of presenting a data input interface, the method comprising: displaying a single text input field which, through a first input to the text input field itself, can select between at least a first operation and a second operation; displaying, by a data processing system, a separator within the text input field, wherein a first portion and a second portion are separated by the separator; receiving the first input to the single text input field to determine a selected operation which includes one of the first operation or the second operation, wherein the first input comprises receiving a user input in either the first portion or the second portion of the text input field, wherein the first operation is selected if the user input is positioned in the first portion when the user input is received and wherein the second operation is selected if the user input is positioned in the second portion when the user input is received, wherein the first operation is a text search through a first source of data and wherein the second operation is either a file operation or a search operation that is different than the first operation, and wherein in response to the first input, the separator automatically disappears from the text input field and the first portion dominates the entire area of the text input field if the first operation is selected and the second portion dominates the entire area of the text input field if the second operation is selected; receiving a text input in the single text input field, the text input being displayable in the entire single text input field and performing the selected operation on the text input. 3. A method as in claim 1 wherein the first input comprises: receiving a mouse button input while a cursor is positioned in either the first portion or the second portion of the text input field, wherein the first operation is selected if the cursor is positioned in the first portion when the mouse button input is received and wherein the second operation is selected if the cursor is positioned in the second portion when the mouse button input is received. | 0.743875 |
7,809,714 | 10 | 11 | 10. A system for enhancing information search queries for information retrieval by computer, comprising a browser program; information pages served to the browser program; a plurality of established term usage subject areas (TUSAs) wherein each TUSA comprises a predetermined subject area; an identified corpus of documents, messages, expositions, or communications exemplifying patterns of term usage specific to each TUSA wherein the corpus for each TUSA includes documents, messages, expositions, or communications disparate from information search queries; means for analyzing documents, messages, expositions, or communications within each corpus of each TUSA to extract term co-occurrence and usage patterns and statistics; means for receiving an information search query relative to the browser program wherein the information search query includes one or more search terms; means for identifying and assigning a primary TUSA corresponding to the information search query; means for locating alternative or additional query terms or query phrases within the primary TUSA based on the term co-occurrence and usage patterns extracted through the analysis of the documents, messages, expositions, or communications within the corpus of the primary TUSA; means for presenting the located alternative or additional query terms or phrases within the primary TUSA to the user via an interface for use in refining the information search query; means for permitting a selection and de-selection of alternative or additional query terms or phrases from among the located alternative or additional query terms or phrases presented by an executive action that does not necessarily require typing individual characters; a mechanism to combine alternative or additional query terms or phrases selected from among the located alternative or additional query terms or phrases presented with the information search query received to create a new, enhanced information search query; and a mechanism to submit the new, enhanced information search query to a search engine to generate information search query results. | 10. A system for enhancing information search queries for information retrieval by computer, comprising a browser program; information pages served to the browser program; a plurality of established term usage subject areas (TUSAs) wherein each TUSA comprises a predetermined subject area; an identified corpus of documents, messages, expositions, or communications exemplifying patterns of term usage specific to each TUSA wherein the corpus for each TUSA includes documents, messages, expositions, or communications disparate from information search queries; means for analyzing documents, messages, expositions, or communications within each corpus of each TUSA to extract term co-occurrence and usage patterns and statistics; means for receiving an information search query relative to the browser program wherein the information search query includes one or more search terms; means for identifying and assigning a primary TUSA corresponding to the information search query; means for locating alternative or additional query terms or query phrases within the primary TUSA based on the term co-occurrence and usage patterns extracted through the analysis of the documents, messages, expositions, or communications within the corpus of the primary TUSA; means for presenting the located alternative or additional query terms or phrases within the primary TUSA to the user via an interface for use in refining the information search query; means for permitting a selection and de-selection of alternative or additional query terms or phrases from among the located alternative or additional query terms or phrases presented by an executive action that does not necessarily require typing individual characters; a mechanism to combine alternative or additional query terms or phrases selected from among the located alternative or additional query terms or phrases presented with the information search query received to create a new, enhanced information search query; and a mechanism to submit the new, enhanced information search query to a search engine to generate information search query results. 11. A system for enhancing information search queries for information retrieval by computer in claim 10 , further comprising a mechanism for selection and pricing of advertising and ancillary materials based on degree of match with the primary TUSA or the located alternative or additional query terms or phrases within the primary TUSA presented. | 0.82332 |
7,474,654 | 9 | 14 | 9. An apparatus, comprising: means for receiving a packet having a plurality of fields in a header of the packet; means for defining at least one packet classification rule using a command-line interface (CLI), wherein the at least one packet classification rule comprises a structured part and an unstructured part, the structured part having a predetermined logical operator relation between at least two of the plurality of fields, the unstructured part having a user configurable relation among the plurality of fields; means for performing a first classification of the packet based on the structured part of at least one packet classification rule; means for using the predetermined logical operator relation between the at least two of the plurality of fields for the structured part in the first classification to provide a first classification result; means for performing a second classification of the packet based on the unstructured part of the at least one packet classification rule and the first classification result; and means for using the user configurable relation among the plurality of fields with keywords identifying values in the plurality of fields for the unstructured part in the second classification, wherein the first and second classifications form a classification of the packet. | 9. An apparatus, comprising: means for receiving a packet having a plurality of fields in a header of the packet; means for defining at least one packet classification rule using a command-line interface (CLI), wherein the at least one packet classification rule comprises a structured part and an unstructured part, the structured part having a predetermined logical operator relation between at least two of the plurality of fields, the unstructured part having a user configurable relation among the plurality of fields; means for performing a first classification of the packet based on the structured part of at least one packet classification rule; means for using the predetermined logical operator relation between the at least two of the plurality of fields for the structured part in the first classification to provide a first classification result; means for performing a second classification of the packet based on the unstructured part of the at least one packet classification rule and the first classification result; and means for using the user configurable relation among the plurality of fields with keywords identifying values in the plurality of fields for the unstructured part in the second classification, wherein the first and second classifications form a classification of the packet. 14. The apparatus of claim 9 , wherein the structured part of the at least one packet classification rule is in Access Control List (ACL) format. | 0.854418 |
7,783,668 | 27 | 28 | 27. The method of claim 26 , wherein performing the first level of indexing further comprises identifying one or more keywords for each piece of content in the corpus of content and identifying one of one or more synsets and one or more entities for each piece of content in the corpus of content to generate the one or more features for each piece of content in the corpus of content. | 27. The method of claim 26 , wherein performing the first level of indexing further comprises identifying one or more keywords for each piece of content in the corpus of content and identifying one of one or more synsets and one or more entities for each piece of content in the corpus of content to generate the one or more features for each piece of content in the corpus of content. 28. The method of claim 27 , wherein performing the first level of indexing further comprises identifying one or more orphan words in each piece of content in the corpus of content. | 0.943046 |
6,047,255 | 5 | 7 | 5. A system for producing a speech signal for generating a voice message comprising words in a dictionary having n words, said system comprising: a processor; a memory device interconnected to said processor; said memory device comprising: n first memory portions each storing a signal segment for generating a beginning portion of a unique word in said dictionary; n second memory portions each storing a signal segment for generating an end portion of a unique word in said dictionary; n.times.n third memory portions, each storing a signal segment corresponding to a unique word pair in said dictionary and for generating an end portion of an initial word in said pair, a smooth transition to a final word in said pair, and a beginning portion of said final word; an output device connected to said processor; wherein said processor is adapted to select and provide said output device signal segments selected from said first, second and third memory portions to produce said speech signal and wherein any first and second word in said dictionary may be generated from a signal segment selected from one of said first memory portions; a signal segment selected from one of said third memory portions; and a signal segment selected from one of said second memory portions. | 5. A system for producing a speech signal for generating a voice message comprising words in a dictionary having n words, said system comprising: a processor; a memory device interconnected to said processor; said memory device comprising: n first memory portions each storing a signal segment for generating a beginning portion of a unique word in said dictionary; n second memory portions each storing a signal segment for generating an end portion of a unique word in said dictionary; n.times.n third memory portions, each storing a signal segment corresponding to a unique word pair in said dictionary and for generating an end portion of an initial word in said pair, a smooth transition to a final word in said pair, and a beginning portion of said final word; an output device connected to said processor; wherein said processor is adapted to select and provide said output device signal segments selected from said first, second and third memory portions to produce said speech signal and wherein any first and second word in said dictionary may be generated from a signal segment selected from one of said first memory portions; a signal segment selected from one of said third memory portions; and a signal segment selected from one of said second memory portions. 7. The system of claim 5, further comprising a plurality of fourth memory portions, each fourth memory portion storing a speech signal segment for generating a system announcement message. | 0.572727 |
8,060,511 | 1 | 11 | 1. A method of information searching in a document image derived from a scanner, the method comprising: defining a key type of a referential key based on at least one type of contextual indicator of a plurality of contextual indicator types that is present in the document image; parsing successive portions of the document image to locate a first type of contextual indicator of the plurality of contextual indicator types, wherein locating the first type of contextual indicator identifies a referential key within the document image; identifying at least one portion of the document image that includes the located first type of contextual indicator; determining if the located first type of contextual indicator is determinative of the defined key type of the referential key, without knowledge of text contained within the portion of the document image that includes the located first type of contextual indicator; extracting characters from the referential key if the located first type of contextual indicator is determinative of the defined key type of the referential key; parsing the portion of the document image that includes the located first type of contextual indicator to locate a second type of contextual indicator of the plurality of contextual indicator types if the located first type of contextual indicator is not determinative of the defined key type of the referential key; determining that a combination of the located first type of contextual indicator and the located second type of contextual indicator located in the document image is determinative of the defined key type of the referential key; and extracting characters from the referential key in response to the determining that the combination of the located first type of contextual indicator and the located second type of contextual indicator located in the document image is determinative of the defined key type of the referential key. | 1. A method of information searching in a document image derived from a scanner, the method comprising: defining a key type of a referential key based on at least one type of contextual indicator of a plurality of contextual indicator types that is present in the document image; parsing successive portions of the document image to locate a first type of contextual indicator of the plurality of contextual indicator types, wherein locating the first type of contextual indicator identifies a referential key within the document image; identifying at least one portion of the document image that includes the located first type of contextual indicator; determining if the located first type of contextual indicator is determinative of the defined key type of the referential key, without knowledge of text contained within the portion of the document image that includes the located first type of contextual indicator; extracting characters from the referential key if the located first type of contextual indicator is determinative of the defined key type of the referential key; parsing the portion of the document image that includes the located first type of contextual indicator to locate a second type of contextual indicator of the plurality of contextual indicator types if the located first type of contextual indicator is not determinative of the defined key type of the referential key; determining that a combination of the located first type of contextual indicator and the located second type of contextual indicator located in the document image is determinative of the defined key type of the referential key; and extracting characters from the referential key in response to the determining that the combination of the located first type of contextual indicator and the located second type of contextual indicator located in the document image is determinative of the defined key type of the referential key. 11. The method of claim 1 , wherein the defining the key type of the referential key based on the at least one type of contextual indicator comprises defining the key type of the referential key based on the at least one type of contextual indicator derived from knowledge including at least one of a general knowledge, a tribal knowledge, and a specific document format rule. | 0.613169 |
8,312,376 | 1 | 10 | 1. A method, comprising: maintaining a user profile of a user to track user requests for media content; receiving a bookmark save event from a media device when a bookmark is initiated by the user while a video stream of media content is rendered by the media device; interpreting the bookmark to determine one or more bookmark representations based on a context interpretation of the bookmark with respect to the media content and based on the user requests that are tracked in the user profile for different types of the media content, the one or more bookmark representations derived from metadata that accompanies the media content; maintaining the bookmark for selection; and providing one or more of the bookmark representations that correspond to the bookmark when a request for the bookmark is received. | 1. A method, comprising: maintaining a user profile of a user to track user requests for media content; receiving a bookmark save event from a media device when a bookmark is initiated by the user while a video stream of media content is rendered by the media device; interpreting the bookmark to determine one or more bookmark representations based on a context interpretation of the bookmark with respect to the media content and based on the user requests that are tracked in the user profile for different types of the media content, the one or more bookmark representations derived from metadata that accompanies the media content; maintaining the bookmark for selection; and providing one or more of the bookmark representations that correspond to the bookmark when a request for the bookmark is received. 10. A method as recited in claim 1 , further comprising determining a person that is associated with the media content, and wherein a bookmark representation corresponds to the person. | 0.862275 |
8,744,839 | 12 | 16 | 12. A target word recognition system, comprising: one or more processors configured to: obtain a candidate word set and corresponding characteristic computation data, the candidate word set comprising text data, and characteristic computation data being associated with the candidate word set; perform segmentation of the characteristic computation data to generate a plurality of text segments; combine the plurality of text segments to form a text data combination set; determine an intersection of the candidate word set and the text data combination set, the intersection comprising a plurality of text data combinations; determine a plurality of designated characteristic values for the plurality of text data combinations; determine a criterion, including: obtain a training sample word set and sample characteristic computation data, the sample characteristic computation data comprising a plurality of sample words and designated characteristic values of the plurality of sample words; obtain a sample text data combination set based on the plurality of sample words; determine a plurality of designated characteristic values of sample text data combinations in an intersection of the sample text data combination set and the training sample word set; and set a threshold value of a designated characteristic value of a sample text data combination in the intersection as a part of the criterion; and based at least in part on the plurality of designated characteristic values for the plurality of text data combinations and according to at least the criterion, recognize among the plurality of text data combinations, target words whose characteristic values fulfill the criterion; and one or more memories coupled to the one or more processors, configured to provide the one or more processors with instructions. | 12. A target word recognition system, comprising: one or more processors configured to: obtain a candidate word set and corresponding characteristic computation data, the candidate word set comprising text data, and characteristic computation data being associated with the candidate word set; perform segmentation of the characteristic computation data to generate a plurality of text segments; combine the plurality of text segments to form a text data combination set; determine an intersection of the candidate word set and the text data combination set, the intersection comprising a plurality of text data combinations; determine a plurality of designated characteristic values for the plurality of text data combinations; determine a criterion, including: obtain a training sample word set and sample characteristic computation data, the sample characteristic computation data comprising a plurality of sample words and designated characteristic values of the plurality of sample words; obtain a sample text data combination set based on the plurality of sample words; determine a plurality of designated characteristic values of sample text data combinations in an intersection of the sample text data combination set and the training sample word set; and set a threshold value of a designated characteristic value of a sample text data combination in the intersection as a part of the criterion; and based at least in part on the plurality of designated characteristic values for the plurality of text data combinations and according to at least the criterion, recognize among the plurality of text data combinations, target words whose characteristic values fulfill the criterion; and one or more memories coupled to the one or more processors, configured to provide the one or more processors with instructions. 16. The system of claim 12 , wherein setting the threshold value includes: sorting a training sample word in the intersection using the threshold value to reach a determination of whether the training sample word in the intersection is a target word; comparing the determination with a known result; and adjusting the threshold value if the determination does not match the known result. | 0.505115 |
8,185,553 | 5 | 6 | 5. The at least one computer-readable storage medium of claim 1 , wherein the act of obtaining the information corresponding to at least one of the data fields specified by the activated template comprises prompting a user for the information. | 5. The at least one computer-readable storage medium of claim 1 , wherein the act of obtaining the information corresponding to at least one of the data fields specified by the activated template comprises prompting a user for the information. 6. The at least one computer-readable storage medium of claim 5 , wherein the user is the physician. | 0.957519 |
9,912,669 | 1 | 3 | 1. A computer-implemented method for facilitating a conversation amongst a plurality of user devices communicating over a digital communication network, the method comprising: receiving a request to initiate a conversation from a user device associated with an opening user, the request comprising, substantive content provided by the opening user and designation of one or more users or user groups as being members of the conversation, at least some of the conversation members being explicitly authorized by the opening user to subsequently designate additional users as members of that specific conversation; receiving a request to view at least some portion of the conversation from a querying user device; determining whether the querying user device is associated with an authorized conversation member; if the querying user device is associated with an authorized conversation member, publishing to the querying user device an authorized member conversation view for rendering on a display screen of the querying user device, the authorized member conversation view comprising, conversation substantive content and a user interface element enabling a user to add a new member to the conversation; and if the querying user device is associated with a conversation member not being an authorized conversation member, publishing to the querying user device an unauthorized conversation view for rendering on a display screen of the querying user device, the unauthorized conversation view comprising conversation substantive content and precluding a user from adding a new member to the conversation. | 1. A computer-implemented method for facilitating a conversation amongst a plurality of user devices communicating over a digital communication network, the method comprising: receiving a request to initiate a conversation from a user device associated with an opening user, the request comprising, substantive content provided by the opening user and designation of one or more users or user groups as being members of the conversation, at least some of the conversation members being explicitly authorized by the opening user to subsequently designate additional users as members of that specific conversation; receiving a request to view at least some portion of the conversation from a querying user device; determining whether the querying user device is associated with an authorized conversation member; if the querying user device is associated with an authorized conversation member, publishing to the querying user device an authorized member conversation view for rendering on a display screen of the querying user device, the authorized member conversation view comprising, conversation substantive content and a user interface element enabling a user to add a new member to the conversation; and if the querying user device is associated with a conversation member not being an authorized conversation member, publishing to the querying user device an unauthorized conversation view for rendering on a display screen of the querying user device, the unauthorized conversation view comprising conversation substantive content and precluding a user from adding a new member to the conversation. 3. The method of claim 1 , further comprising: receiving a request from a user device associated with an authorized conversation member to add a new member to the conversation, the request comprising specification of an electronic contact address associated with the new member; transmitting a notification to the electronic contact address associated with the new member; and conveying conversation-level privileges upon the new member. | 0.501142 |
9,275,023 | 13 | 22 | 13. A non-transitory computer readable medium having stored thereon instructions for further adapting eXtensible Stylesheet Language (XSL) to HyperText Markup Language (HTML) document transformations comprising machine executable code which when executed by at least one processor, causes the processor to perform steps comprising: identifying a plurality of rules matching one or more elements in an HTML document; identifying a plurality of actions associated with each of the identified plurality of rules; grouping each of the matching identified plurality of actions together into one or more corresponding groups; filtering the grouped plurality of actions based on one or more filtering rules when two or more of the grouped plurality of actions match; removing one or more of the plurality of actions in each of the one or more corresponding groups based on the one or more filtering rules; applying the remaining grouped plurality of actions that match after the filtering to transform the matching one or more elements in the HTML document; and providing the transformed HTML document. | 13. A non-transitory computer readable medium having stored thereon instructions for further adapting eXtensible Stylesheet Language (XSL) to HyperText Markup Language (HTML) document transformations comprising machine executable code which when executed by at least one processor, causes the processor to perform steps comprising: identifying a plurality of rules matching one or more elements in an HTML document; identifying a plurality of actions associated with each of the identified plurality of rules; grouping each of the matching identified plurality of actions together into one or more corresponding groups; filtering the grouped plurality of actions based on one or more filtering rules when two or more of the grouped plurality of actions match; removing one or more of the plurality of actions in each of the one or more corresponding groups based on the one or more filtering rules; applying the remaining grouped plurality of actions that match after the filtering to transform the matching one or more elements in the HTML document; and providing the transformed HTML document. 22. The medium as set forth in claim 13 , wherein the one or more filtering rules comprises removing remove-element, set-content, or append-content when the identified plurality of actions in the one or more corresponding groups comprises set-content. | 0.748497 |
8,312,102 | 3 | 4 | 3. The method according to claim 1 further comprising: determining whether the first level content files contain references to second level content files. | 3. The method according to claim 1 further comprising: determining whether the first level content files contain references to second level content files. 4. The method according to claim 3 further comprising: if the first level content files contains references to second level content files, retrieving the second level content files; extracting content from the second level content files and replacing the references with content from the second level content files. | 0.874302 |
9,444,772 | 7 | 8 | 7. A non-transitory computer-readable memory having instructions stored thereon, which, when executed by a processor, cause the processor to perform operations comprising: receiving a question from an asker in which the question is associated with one or more topics; selecting a plurality of candidate answerers based at least partly on each candidate answerer's respective social relationship to the asker within a computer-implemented social network; determining a respective wait time for each candidate answerer in the plurality of candidate answerers, where the respective wait time is based on one or more of a respective communication channel used by the candidate answerer and a historical responsiveness of the candidate answerer for the respective communication channel, wherein the respective communication channel comprising one of an instant message, an electronic mail, a blog post, and a short message service message; selecting a first candidate answerer based on a ranking of the plurality of candidate answerers; sending the question to the first candidate answerer of the plurality of candidate answerers through the respective communication channel of the first candidate answerer; determining that the respective wait time of the first candidate answerer for a first answer from the first candidate answerer has expired without receiving the first answer, and in response: selecting a second candidate answerer based on the ranking of the plurality of candidate answerers, and sending the question to the second candidate answerer of the plurality of candidate answerers through the respective communication channel of the second candidate answerer; receiving a second answer to the question from the second candidate answerer; and sending the second answer to the asker and information that identifies the second answerer. | 7. A non-transitory computer-readable memory having instructions stored thereon, which, when executed by a processor, cause the processor to perform operations comprising: receiving a question from an asker in which the question is associated with one or more topics; selecting a plurality of candidate answerers based at least partly on each candidate answerer's respective social relationship to the asker within a computer-implemented social network; determining a respective wait time for each candidate answerer in the plurality of candidate answerers, where the respective wait time is based on one or more of a respective communication channel used by the candidate answerer and a historical responsiveness of the candidate answerer for the respective communication channel, wherein the respective communication channel comprising one of an instant message, an electronic mail, a blog post, and a short message service message; selecting a first candidate answerer based on a ranking of the plurality of candidate answerers; sending the question to the first candidate answerer of the plurality of candidate answerers through the respective communication channel of the first candidate answerer; determining that the respective wait time of the first candidate answerer for a first answer from the first candidate answerer has expired without receiving the first answer, and in response: selecting a second candidate answerer based on the ranking of the plurality of candidate answerers, and sending the question to the second candidate answerer of the plurality of candidate answerers through the respective communication channel of the second candidate answerer; receiving a second answer to the question from the second candidate answerer; and sending the second answer to the asker and information that identifies the second answerer. 8. The computer-readable medium of claim 7 , where selecting the plurality of candidate answerers comprises selecting candidate answerers that communicate using a communication channel of the asker. | 0.878378 |
7,941,313 | 20 | 21 | 20. The method of claim 15 , further comprising: receiving from the voice recognition device in the distributed voice recognition system at least one word or command estimated based on the indication of detected voice activity and the plurality of features. | 20. The method of claim 15 , further comprising: receiving from the voice recognition device in the distributed voice recognition system at least one word or command estimated based on the indication of detected voice activity and the plurality of features. 21. The method of claim 20 , further comprising: initiating an action at a subscriber unit based on the at least one word or command. | 0.943162 |
8,676,800 | 28 | 29 | 28. A system for generating information from a plurality of data items, the system comprising: a computing device; (a) a preprocessor executable in the computing device, the preprocessor being configured for: i. populating an aggregate data item with at least one of the plurality of data items; wherein each individual data item comprises original information including an attribute and a value, wherein the attribute of the individual data item is an identifier for the individual data item, wherein the aggregate data item is a form of derived attribute, wherein the derived attribute represents a transformation of a collection of individual data items into a single data item with a value, wherein said value of the derived attribute is an aggregate value comprising a map of attribute to value for each said individual data item within said collection of individual data items such that a derived attribute forms a single data item suitable for inferencing by a knowledge base, said single data item retaining the original information relating to each of the plurality of individual data items yet queried by the knowledge base as a whole to extract information regarding said individual data items; and ii. for constructing one or more other derived attributes from the plurality of data items; and (b) an information generator executable in the computing device, the information generator configured for generating the information using the derived attributes, wherein the information generator forms at least part of a decision support system, and wherein the information so generated falls into one or more of the following groups: i. textual information; ii. a machine instruction. | 28. A system for generating information from a plurality of data items, the system comprising: a computing device; (a) a preprocessor executable in the computing device, the preprocessor being configured for: i. populating an aggregate data item with at least one of the plurality of data items; wherein each individual data item comprises original information including an attribute and a value, wherein the attribute of the individual data item is an identifier for the individual data item, wherein the aggregate data item is a form of derived attribute, wherein the derived attribute represents a transformation of a collection of individual data items into a single data item with a value, wherein said value of the derived attribute is an aggregate value comprising a map of attribute to value for each said individual data item within said collection of individual data items such that a derived attribute forms a single data item suitable for inferencing by a knowledge base, said single data item retaining the original information relating to each of the plurality of individual data items yet queried by the knowledge base as a whole to extract information regarding said individual data items; and ii. for constructing one or more other derived attributes from the plurality of data items; and (b) an information generator executable in the computing device, the information generator configured for generating the information using the derived attributes, wherein the information generator forms at least part of a decision support system, and wherein the information so generated falls into one or more of the following groups: i. textual information; ii. a machine instruction. 29. A system defined by claim 28 wherein the preprocessor is able to iteratively construct derived attributes which use derived defined earlier in the iterative process. | 0.82173 |
7,805,310 | 6 | 8 | 6. A method of implementing voice-enabled applications in a converged voice and data network IP environment that supports and implements VoIP connections, protocols and traffic, comprising: a. entering human voice data as data packets from a speaker into a converged VoIP voice and data packet-switched IP based network for later processing and acoustic matching; b. non-intrusively processing the voice data from an end user biometrically while the end user is speaking into the converged VoIP voice and data packet-switched IP based network; c. preparing the voice data for VoIP speech processing function with a front-end processing module to separate the pauses in the speech from the voice data and utilizing a voice feature extraction module to ready the speech for a processing algorithm from a speech engine; d. synchronizing generated control information with a data exchange between a data preparation module and the speech engine through a speech application interface; e. processing the voice features by the speech engine to perform at least one combination of the speech processing and pattern recognition algorithms implemented by the speech engine; f. providing feedback to the end user to communicate the result from the speech processing; and g. taking an action responsive to the result from the processing of the voice. | 6. A method of implementing voice-enabled applications in a converged voice and data network IP environment that supports and implements VoIP connections, protocols and traffic, comprising: a. entering human voice data as data packets from a speaker into a converged VoIP voice and data packet-switched IP based network for later processing and acoustic matching; b. non-intrusively processing the voice data from an end user biometrically while the end user is speaking into the converged VoIP voice and data packet-switched IP based network; c. preparing the voice data for VoIP speech processing function with a front-end processing module to separate the pauses in the speech from the voice data and utilizing a voice feature extraction module to ready the speech for a processing algorithm from a speech engine; d. synchronizing generated control information with a data exchange between a data preparation module and the speech engine through a speech application interface; e. processing the voice features by the speech engine to perform at least one combination of the speech processing and pattern recognition algorithms implemented by the speech engine; f. providing feedback to the end user to communicate the result from the speech processing; and g. taking an action responsive to the result from the processing of the voice. 8. The method of claim 6 , further comprising the implementation of a network speech appliance on the buffering device with the speech application interface communicating with the voice-enabled application on the packet-switched IP based VoIP network using a message-based mechanism. | 0.815274 |
8,896,633 | 1 | 4 | 1. A method comprising: displaying text in a display region using an initial display size; detecting a selection of a desired text collection; receiving an instruction to increase a display size of the desired text collection, wherein the instruction is provided by an input detected within the display region; determining a sequence of display sizes based on the desired text collection; detecting a selection of an increased display size larger than the initial display size from the sequence of display sizes; and displaying the desired text collection in the display region using the increased display size. | 1. A method comprising: displaying text in a display region using an initial display size; detecting a selection of a desired text collection; receiving an instruction to increase a display size of the desired text collection, wherein the instruction is provided by an input detected within the display region; determining a sequence of display sizes based on the desired text collection; detecting a selection of an increased display size larger than the initial display size from the sequence of display sizes; and displaying the desired text collection in the display region using the increased display size. 4. The method of claim 1 , further comprising: increasing a size of the display region to accommodate the text displayed using the increased display size. | 0.611111 |
9,087,046 | 12 | 15 | 12. The method of claim 11 , wherein the manual correction of the translation comprises: detecting a first touch on the touch screen when the translation is displayed; identifying a portion of the translation corresponding to the first touch; displaying one or more alternative variants of translation in the target language of the identified portion of the translation; detecting a second touch on the touch screen indicating one of the alternative variants of translation in the target language; and substituting the indicated alternative variant of translation for the identified portion of the translation for displaying. | 12. The method of claim 11 , wherein the manual correction of the translation comprises: detecting a first touch on the touch screen when the translation is displayed; identifying a portion of the translation corresponding to the first touch; displaying one or more alternative variants of translation in the target language of the identified portion of the translation; detecting a second touch on the touch screen indicating one of the alternative variants of translation in the target language; and substituting the indicated alternative variant of translation for the identified portion of the translation for displaying. 15. The method of claim 12 , wherein word forms of the one or more alternative variants of translation are consistent with a word form of the identified portion of the translation. | 0.673913 |
8,645,832 | 4 | 5 | 4. The method of claim 1 , wherein said method is performed using a graphical user interface, said graphical user interface comprising a plurality of computer display regions including a map region displaying the abstract map and plotted markers, and a playback region for playing back one of the plurality of traversal records associated with one of the plurality of markers in response to interactive selection of the one of the plurality of markers. | 4. The method of claim 1 , wherein said method is performed using a graphical user interface, said graphical user interface comprising a plurality of computer display regions including a map region displaying the abstract map and plotted markers, and a playback region for playing back one of the plurality of traversal records associated with one of the plurality of markers in response to interactive selection of the one of the plurality of markers. 5. The method of claim 4 , wherein the graphical user interface further includes a worksheet region displaying a list of the plurality of traversal records and associated annotations. | 0.946176 |
9,658,746 | 14 | 15 | 14. A non-transitory computer program product comprising a plurality of instructions encoded thereon that, when executed by a processor, cause a process to be carried out, the process comprising: receiving at a touch sensitive surface an accessible automatic reading mode activation gesture, the accessible automatic reading mode facilitating use of the touch sensitive surface by a visually impaired user by configuring an entire surface of the touch sensitive surface as a single control feature for receiving touch gestures, and the touch gestures include at least one of one or more taps, one or more presses, one or more press and holds, and one or more swipes in any direction, the accessible automatic reading mode comprising: automatically and continuously aurally presenting textual content from a predetermined point with a selected voice font, volume, and rate in response to the accessible automatic reading mode activation gesture; disregarding all contacts on the touch sensitive surface other than touch gestures received anywhere on the touch sensitive surface to transition out of the automatic reading mode, and touch gestures received anywhere on the touch sensitive surface to adjust at least one of reading rate, scroll by sentence, scroll by page, and scroll by chapter; and creating a virtual bookmark on a currently displayed page if a chapter scrolling gesture is received, the currently displayed page is not at the beginning of a chapter, and making an additional stop on the corresponding bookmarked page in response to a subsequent chapter scrolling gesture prompting the process to proceed over the bookmarked page; and receiving at a touch sensitive surface an accessible manual reading mode activation gesture, the manual reading mode performing an action including at least one of: aurally presenting textual content at a current read point or that is selected, navigating menu options, sharing content, selecting content, adding notes to content, adjusting reading rate, adjusting voice font, and adjust volume in response to the one or more corresponding touch gestures received anywhere on the touch sensitive surface; and transitioning between the automatic reading mode and the manual reading mode in response to a transition gesture received anywhere on the touch sensitive surface. | 14. A non-transitory computer program product comprising a plurality of instructions encoded thereon that, when executed by a processor, cause a process to be carried out, the process comprising: receiving at a touch sensitive surface an accessible automatic reading mode activation gesture, the accessible automatic reading mode facilitating use of the touch sensitive surface by a visually impaired user by configuring an entire surface of the touch sensitive surface as a single control feature for receiving touch gestures, and the touch gestures include at least one of one or more taps, one or more presses, one or more press and holds, and one or more swipes in any direction, the accessible automatic reading mode comprising: automatically and continuously aurally presenting textual content from a predetermined point with a selected voice font, volume, and rate in response to the accessible automatic reading mode activation gesture; disregarding all contacts on the touch sensitive surface other than touch gestures received anywhere on the touch sensitive surface to transition out of the automatic reading mode, and touch gestures received anywhere on the touch sensitive surface to adjust at least one of reading rate, scroll by sentence, scroll by page, and scroll by chapter; and creating a virtual bookmark on a currently displayed page if a chapter scrolling gesture is received, the currently displayed page is not at the beginning of a chapter, and making an additional stop on the corresponding bookmarked page in response to a subsequent chapter scrolling gesture prompting the process to proceed over the bookmarked page; and receiving at a touch sensitive surface an accessible manual reading mode activation gesture, the manual reading mode performing an action including at least one of: aurally presenting textual content at a current read point or that is selected, navigating menu options, sharing content, selecting content, adding notes to content, adjusting reading rate, adjusting voice font, and adjust volume in response to the one or more corresponding touch gestures received anywhere on the touch sensitive surface; and transitioning between the automatic reading mode and the manual reading mode in response to a transition gesture received anywhere on the touch sensitive surface. 15. The non-transitory computer program product of claim 14 wherein the touch sensitive surface is a touch screen display and wherein the process further comprises: receiving at the touch screen display a short press gesture performed over a first word; and aurally presenting the first word to a user. | 0.50165 |
10,097,483 | 6 | 9 | 6. A client computer configured for messaging integration of a business object comprising: at least one hardware processor configured to initiate the following executable operations: embedding, in a message session provided by a messenger, the business object into message text; applying, from within the message session, an action to the business object; forwarding, by the client and based upon the applied action, a copy of the message text to a backend business component separate from the client computer, indexing tags for the business object when indexing the message text for a message session in a message transcript; and searching the business object along with the message text of the message session in the message transcript with contextual relevance, wherein the business object encapsulates lower-level objects that implement a business process. | 6. A client computer configured for messaging integration of a business object comprising: at least one hardware processor configured to initiate the following executable operations: embedding, in a message session provided by a messenger, the business object into message text; applying, from within the message session, an action to the business object; forwarding, by the client and based upon the applied action, a copy of the message text to a backend business component separate from the client computer, indexing tags for the business object when indexing the message text for a message session in a message transcript; and searching the business object along with the message text of the message session in the message transcript with contextual relevance, wherein the business object encapsulates lower-level objects that implement a business process. 9. The client computer of claim 6 , wherein the messenger is a discussion forum environment, the message text is discussion forum text and the messaging session is a threaded discussion forum. | 0.737705 |
9,032,366 | 6 | 8 | 6. An apparatus for performing a configuration of an aeronautical system, comprising: a display configured to display a user interface for receiving aeronautical system setting information in compliance with an ARINC (Aeronautical Radio, Incorporated) 653 standard; and at least one processor configured to: generate an intermediate model of source code based on the setting information received via the user interface; create an XML document by performing XML conversion on the generated intermediate model; and generate a source code file in compliance with the ARINC 653 standard by converting the generated XML document. | 6. An apparatus for performing a configuration of an aeronautical system, comprising: a display configured to display a user interface for receiving aeronautical system setting information in compliance with an ARINC (Aeronautical Radio, Incorporated) 653 standard; and at least one processor configured to: generate an intermediate model of source code based on the setting information received via the user interface; create an XML document by performing XML conversion on the generated intermediate model; and generate a source code file in compliance with the ARINC 653 standard by converting the generated XML document. 8. The apparatus of claim 6 , wherein an extended ARINC 653 XML schema standard that enables a shared input/output (IO) function to be set is used to create the XML document is used to create the XML document. | 0.626786 |
5,583,921 | 1 | 2 | 1. A data processing apparatus comprising: inputting means for inputting alphanumeric character data representing a message to be transmitted; converting means for converting said alphanumeric character data input by said inputting means into first information indicating a series of key operations of a push-button telephone which must be operated by a user when inputting a message corresponding to said alphanumeric character data by said key operations of said push-button telephone connected to a public telephone network; and displaying means for displaying said first information indicating said series of key operations converted by said converting means. | 1. A data processing apparatus comprising: inputting means for inputting alphanumeric character data representing a message to be transmitted; converting means for converting said alphanumeric character data input by said inputting means into first information indicating a series of key operations of a push-button telephone which must be operated by a user when inputting a message corresponding to said alphanumeric character data by said key operations of said push-button telephone connected to a public telephone network; and displaying means for displaying said first information indicating said series of key operations converted by said converting means. 2. A data processing apparatus according to claim 1, wherein said displaying means displays said first information while dividing a data display range into a plurality of preset data widths. | 0.88125 |
8,560,456 | 27 | 29 | 27. A computer-implemented method for exchanging consumer information, comprising the steps of: registering a plurality of data providers and a plurality of data buyers, the registration of each data buyer of the plurality of data buyers comprising receiving a legal representation from the data buyer that the data buyer will use any consumer information requested only in accordance with stated permissible uses; building, by the computer, a searchable index for each of the data buyers based on at least one index of consumer information for sale provided from one or more of the data providers; for each searchable index of each of the data buyers, encrypting and decrypting the searchable index by a public key unique to a respective one of the data buyers, when building the searchable indexes; receiving an encrypted query that identifies a data buyer of the plurality of data buyers and defines a purchase request for consumer information; retrieving the searchable index associated with the data buyer; determining, by the computer, whether at least one of the data providers maintains the consumer information requested by the data buyer by comparing the purchase request to the searchable index associated with the data buyer; encrypting and decrypting the searchable index associated with the data buyer by a private key unique to the data buyer, when determining whether at least one of the data providers maintains the consumer information requested; and in response to determining that at least one of the data providers maintains the consumer information requested, transmitting a message to the data buyer comprising information about the consumer information requested, the cost of purchasing the consumer information requested, and an anonymous exchange identifier code for uniquely identifying the consumer information requested. | 27. A computer-implemented method for exchanging consumer information, comprising the steps of: registering a plurality of data providers and a plurality of data buyers, the registration of each data buyer of the plurality of data buyers comprising receiving a legal representation from the data buyer that the data buyer will use any consumer information requested only in accordance with stated permissible uses; building, by the computer, a searchable index for each of the data buyers based on at least one index of consumer information for sale provided from one or more of the data providers; for each searchable index of each of the data buyers, encrypting and decrypting the searchable index by a public key unique to a respective one of the data buyers, when building the searchable indexes; receiving an encrypted query that identifies a data buyer of the plurality of data buyers and defines a purchase request for consumer information; retrieving the searchable index associated with the data buyer; determining, by the computer, whether at least one of the data providers maintains the consumer information requested by the data buyer by comparing the purchase request to the searchable index associated with the data buyer; encrypting and decrypting the searchable index associated with the data buyer by a private key unique to the data buyer, when determining whether at least one of the data providers maintains the consumer information requested; and in response to determining that at least one of the data providers maintains the consumer information requested, transmitting a message to the data buyer comprising information about the consumer information requested, the cost of purchasing the consumer information requested, and an anonymous exchange identifier code for uniquely identifying the consumer information requested. 29. The computer-implemented method recited by claim 27 , wherein the consumer information requested comprises law enforcement information regarding an individual, the law enforcement information comprising at least one of a driver's license number of the individual and information regarding a criminal history of the individual. | 0.769231 |
10,019,226 | 13 | 24 | 13. An apparatus, comprising: a subsystem, on a first device, implemented at least partially in hardware, that organizes machine data into a plurality of events, each event in the plurality of events being associated with a timestamp and including a portion of machine data that reflects activity in an information technology environment and that is produced by a component of that information technology environment; a subsystem, implemented at least partially in hardware, that receives, via a user interface, a user selection of a text value from displayed machine data associated with an event among the plurality of events, and automatically generates at least one extraction rule in response to the selection of the text value from machine data associated with the event; and a subsystem, implemented at least partially in hardware, that extracts at least one text value from at least one event in the plurality of events using the at least one extraction rule. | 13. An apparatus, comprising: a subsystem, on a first device, implemented at least partially in hardware, that organizes machine data into a plurality of events, each event in the plurality of events being associated with a timestamp and including a portion of machine data that reflects activity in an information technology environment and that is produced by a component of that information technology environment; a subsystem, implemented at least partially in hardware, that receives, via a user interface, a user selection of a text value from displayed machine data associated with an event among the plurality of events, and automatically generates at least one extraction rule in response to the selection of the text value from machine data associated with the event; and a subsystem, implemented at least partially in hardware, that extracts at least one text value from at least one event in the plurality of events using the at least one extraction rule. 24. The apparatus as recited in claim 13 , further comprising: a subsystem, implemented at least partially in hardware, that causes highlighting of the text value in the user interface that displays one or more of the plurality of events. | 0.694872 |
7,752,193 | 11 | 12 | 11. The method of claim 8 further comprising: generating one or more tables storing information on the one or more variations for each of the normalized words, wherein, the query engine is configured to search the one or more tables for information on the one or more variations matching the input query word responsive to a command to consider the one or more variations. | 11. The method of claim 8 further comprising: generating one or more tables storing information on the one or more variations for each of the normalized words, wherein, the query engine is configured to search the one or more tables for information on the one or more variations matching the input query word responsive to a command to consider the one or more variations. 12. The method of claim 11 , wherein the variation of one of the normalized words includes a diacritic symbol, and the table stores information on the diacritic symbol. | 0.948276 |
8,824,548 | 1 | 14 | 1. A method for classifying an object in a scene, comprising the steps of: preprocessing a sequence of images, wherein each image is acquired of the object in the scene by a scanner, wherein the scanner includes a 1D laser line sensor, and each image includes columns of pixels, and each pixel has an associated depth value such that each image is a range image, wherein the preprocessing further comprises; denoising each image in the sequence; removing background pixels from each image; projecting, in 3D, each image to a 3D world coordinate system; correcting depth values; extracting features; and classifying the sequence of images, wherein the classifying further comprises: applying an appearance classifier to the features to obtain labels; applying a sequence classifier to smooth the labels; and enforcing a structure of the object to determine a class of the object, wherein the steps are performed in a processor. | 1. A method for classifying an object in a scene, comprising the steps of: preprocessing a sequence of images, wherein each image is acquired of the object in the scene by a scanner, wherein the scanner includes a 1D laser line sensor, and each image includes columns of pixels, and each pixel has an associated depth value such that each image is a range image, wherein the preprocessing further comprises; denoising each image in the sequence; removing background pixels from each image; projecting, in 3D, each image to a 3D world coordinate system; correcting depth values; extracting features; and classifying the sequence of images, wherein the classifying further comprises: applying an appearance classifier to the features to obtain labels; applying a sequence classifier to smooth the labels; and enforcing a structure of the object to determine a class of the object, wherein the steps are performed in a processor. 14. The method of claim 1 , wherein the structure enforcing converts the labels to labels of a most similar valid object model defined in a object grammar. | 0.503205 |
9,779,136 | 15 | 20 | 15. A non-transitory machine-readable medium embodying a set of instructions that, when executed by a processor, cause the processor to perform operations, the operations comprising: receiving a first initial search query from a first user, the first initial search query comprising at least one search operator and at least one search term; generating a first rewritten search query based on the first initial search query, the generating the first rewritten search query comprising rewriting at least one optional search operator in the first initial search query using at least one required search operator and at least one exclusion search operator in response to a determination that the first initial search query comprises the at least one optional search operator and does not comprise any required search operators; generating a first set of search results for the first rewritten search query; and causing the first set of search results to be presented to the first user. | 15. A non-transitory machine-readable medium embodying a set of instructions that, when executed by a processor, cause the processor to perform operations, the operations comprising: receiving a first initial search query from a first user, the first initial search query comprising at least one search operator and at least one search term; generating a first rewritten search query based on the first initial search query, the generating the first rewritten search query comprising rewriting at least one optional search operator in the first initial search query using at least one required search operator and at least one exclusion search operator in response to a determination that the first initial search query comprises the at least one optional search operator and does not comprise any required search operators; generating a first set of search results for the first rewritten search query; and causing the first set of search results to be presented to the first user. 20. The non-transitory machine-readable medium of claim 15 , wherein the first rewritten search query is generated in response to a user-generated interrupt, the user generated interrupt comprising a submission by the first user of the first initial search query. | 0.857838 |
10,163,439 | 3 | 4 | 3. The computer-implemented method of claim 1 , further comprising, for each frame in the received first audio signal: identifying, by speech recognition-enabled electronic device, audio characteristics of the user speaking the trigger phrase and audio characteristics of background noise for the corresponding frame in the received first audio signal; comparing, by the speech recognition-enabled electronic device, the identified audio characteristics of the user speaking the trigger phrase to predetermined threshold values associated with one or more values for trigger phrase model training; and determining, by the speech recognition-enabled electronic device, a voice activity detection flag for the corresponding frame in the received first audio signal in response to comparing the identified audio characteristics of the user speaking the trigger phrase to the predetermined threshold values. | 3. The computer-implemented method of claim 1 , further comprising, for each frame in the received first audio signal: identifying, by speech recognition-enabled electronic device, audio characteristics of the user speaking the trigger phrase and audio characteristics of background noise for the corresponding frame in the received first audio signal; comparing, by the speech recognition-enabled electronic device, the identified audio characteristics of the user speaking the trigger phrase to predetermined threshold values associated with one or more values for trigger phrase model training; and determining, by the speech recognition-enabled electronic device, a voice activity detection flag for the corresponding frame in the received first audio signal in response to comparing the identified audio characteristics of the user speaking the trigger phrase to the predetermined threshold values. 4. The computer-implemented method of claim 3 , wherein determining the voice activity detection flag for the corresponding frame in the received first audio signal comprises: generating an accept enrollment flag in response to the identified audio characteristics of the user speaking the trigger phrase being less than the predetermined threshold values; and generating a reject enrollment flag in response to the identified audio characteristics of the user speaking the trigger phrase being greater than the predetermined threshold values. | 0.863978 |
9,519,642 | 1 | 5 | 1. A system, comprising: at least one processor; at least one non-transitory computer readable medium storing instructions translatable by the at least one processor, the instructions when translated by the at least one processor cause the system to provide content management and locale-specific delivery of managed linguistic translations of web site content by: responsive to a request for content from a client device communicatively connected to a web server in an enterprise computing environment, dynamically resolving the request for content by: determining an exemplar linguistic translation reference, the exemplar linguistic translation reference identifying a managed web site content object associated with the content requested by the client device, the web site content object having a multilingual attribute indicating that the managed web site content object is multilingual, the managed web site content object being stored in a repository residing in the enterprise computing environment; determining a linguistic translation group utilizing the exemplar linguistic translation reference, the linguistic translation group including translation group content items representing same content translated into different languages; determining, from the determined linguistic translation group, one or more human languages associated with the managed web site content object; determining an effective locale for the request for content; determining, from the one or more human languages in the linguistic translation group and based on the effective locale, a language that is appropriate for the effective locale; retrieving a managed content item from the repository, wherein the managed content item is part of the linguistic translation group and represents a linguistic translation for the managed web site content object in the language that is appropriate for the effective locale; and responding to the request for content by dynamically rendering and delivering the managed content item that is in the language appropriate for the effective locale. | 1. A system, comprising: at least one processor; at least one non-transitory computer readable medium storing instructions translatable by the at least one processor, the instructions when translated by the at least one processor cause the system to provide content management and locale-specific delivery of managed linguistic translations of web site content by: responsive to a request for content from a client device communicatively connected to a web server in an enterprise computing environment, dynamically resolving the request for content by: determining an exemplar linguistic translation reference, the exemplar linguistic translation reference identifying a managed web site content object associated with the content requested by the client device, the web site content object having a multilingual attribute indicating that the managed web site content object is multilingual, the managed web site content object being stored in a repository residing in the enterprise computing environment; determining a linguistic translation group utilizing the exemplar linguistic translation reference, the linguistic translation group including translation group content items representing same content translated into different languages; determining, from the determined linguistic translation group, one or more human languages associated with the managed web site content object; determining an effective locale for the request for content; determining, from the one or more human languages in the linguistic translation group and based on the effective locale, a language that is appropriate for the effective locale; retrieving a managed content item from the repository, wherein the managed content item is part of the linguistic translation group and represents a linguistic translation for the managed web site content object in the language that is appropriate for the effective locale; and responding to the request for content by dynamically rendering and delivering the managed content item that is in the language appropriate for the effective locale. 5. The system of claim 1 , wherein the effective locale is determined by parsing locale information contained in the request for content. | 0.789877 |
9,619,450 | 6 | 10 | 6. A computer program product comprising a non-transitory computer usable medium including a computer readable program, wherein the computer readable program when executed on a computer causes the computer to: learn sets of equivalent syntactic patterns from a corpus of documents; map the sets of equivalent syntactic patterns to corresponding items in a knowledge graph; receive a set of one or more input documents; process the set of one or more input documents for one or more expressions matching a first set of equivalent syntactic patterns from among the sets of equivalent syntactic patterns; process the one or more expressions to determine one or more entities; determine a set of entities that are relevant to a main event described by the set of one or more input documents from the one or more entities; identify entity types for the set of entities; generate a refined set of equivalent syntactic patterns by excluding the equivalent syntactic patterns with a relevance score below a predefined threshold; select an equivalent syntactic pattern from among the refined set of equivalent syntactic patterns for a headline, the selected equivalent syntactic pattern reflecting the main event described by the set of one or more input documents; generate the headline by populating the selected equivalent syntactic pattern with the one or more entities, wherein an order of entities in the headline is based on the entity types of the one or more entities; determine one or more entries in the knowledge graph corresponding to the one or more entities described by the one or more expressions; and update the one or more entries in the knowledge graph to reflect the main event using the headline. | 6. A computer program product comprising a non-transitory computer usable medium including a computer readable program, wherein the computer readable program when executed on a computer causes the computer to: learn sets of equivalent syntactic patterns from a corpus of documents; map the sets of equivalent syntactic patterns to corresponding items in a knowledge graph; receive a set of one or more input documents; process the set of one or more input documents for one or more expressions matching a first set of equivalent syntactic patterns from among the sets of equivalent syntactic patterns; process the one or more expressions to determine one or more entities; determine a set of entities that are relevant to a main event described by the set of one or more input documents from the one or more entities; identify entity types for the set of entities; generate a refined set of equivalent syntactic patterns by excluding the equivalent syntactic patterns with a relevance score below a predefined threshold; select an equivalent syntactic pattern from among the refined set of equivalent syntactic patterns for a headline, the selected equivalent syntactic pattern reflecting the main event described by the set of one or more input documents; generate the headline by populating the selected equivalent syntactic pattern with the one or more entities, wherein an order of entities in the headline is based on the entity types of the one or more entities; determine one or more entries in the knowledge graph corresponding to the one or more entities described by the one or more expressions; and update the one or more entries in the knowledge graph to reflect the main event using the headline. 10. The computer program product of claim 6 , wherein to process the set of one or more input documents includes: determining that a number of expressions processed from the one or more input documents meets a pre-determined evidence threshold; and determining the set of equivalent syntactic patterns to be relevant to the set of one or more input documents based on the evidence threshold being met. | 0.512165 |
7,827,028 | 4 | 5 | 4. The method of claim 3 , wherein said plurality of nodes comprises: a plurality of labeled nodes including the syntactic labels and the role labels; a plurality of pre-terminal nodes coupled downstream of the labeled nodes, the pre-terminal nodes respectively including the destination language words; and the plurality of terminal nodes coupled to the pre-terminal nodes, the terminal nodes respectively including the words of the source language sentence. | 4. The method of claim 3 , wherein said plurality of nodes comprises: a plurality of labeled nodes including the syntactic labels and the role labels; a plurality of pre-terminal nodes coupled downstream of the labeled nodes, the pre-terminal nodes respectively including the destination language words; and the plurality of terminal nodes coupled to the pre-terminal nodes, the terminal nodes respectively including the words of the source language sentence. 5. The method of claim 4 , wherein said rearranging (f) comprises placing the pre-terminal nodes into a word order associated with the destination language. | 0.955147 |
7,577,644 | 10 | 13 | 10. One or more storage media having logic encoded thereon for execution on a data processing system, wherein the logic when executed is operable to: receive a query from the user comprising one or more search terms; obtain a context corresponding to the query, the context being representative of a currently viewed content or a history of viewed content; execute a first algorithmic search using at least one of the one or more search terms in the query; execute a second contextual search using the context and the at least one of the one or more search terms in the query; obtain a first search result set from the executed first search; obtain a second search result set from the executed second search; and merge the first and second search result sets into a merged result set, wherein in order to merge the first and second search result sets, the logic is further operable to conditionally exclude results in the first result set from the merged result set based on a threshold similarity to the context such that results in the first result set that are not within the threshold similarity to the context are excluded from the merged result set; and transmit the merged result set as a response to the query. | 10. One or more storage media having logic encoded thereon for execution on a data processing system, wherein the logic when executed is operable to: receive a query from the user comprising one or more search terms; obtain a context corresponding to the query, the context being representative of a currently viewed content or a history of viewed content; execute a first algorithmic search using at least one of the one or more search terms in the query; execute a second contextual search using the context and the at least one of the one or more search terms in the query; obtain a first search result set from the executed first search; obtain a second search result set from the executed second search; and merge the first and second search result sets into a merged result set, wherein in order to merge the first and second search result sets, the logic is further operable to conditionally exclude results in the first result set from the merged result set based on a threshold similarity to the context such that results in the first result set that are not within the threshold similarity to the context are excluded from the merged result set; and transmit the merged result set as a response to the query. 13. The storage media according to claim 10 , wherein the logic when executed is further operable to order the results sets based upon a value of a ranking parameter. | 0.597087 |
7,631,301 | 1 | 10 | 1. A computer program product for implementing a method for controlling a computing system, the computer program product comprising physical computer storage media containing computer-executable instructions for implementing a method for customizing a binary content file stored at the computing system without recompiling source code associated with the binary content file so as to modify the behavior of the binary content file when the binary content file is executed at a destination computing system, and wherein the method comprises: at a computing system performing an act of translating an object file compiled from source code into one or more compiled binary content files; an act of receiving at a computing system for storage one or more compiled binary content files that each includes one or more variables that are assigned current values; an act of preparing at a computing system one or more non-binary script files that each include one or more references to updated values for one or more of the variables in one or more of the compiled binary content files; inputting for storage at the computing system at which the one or more compiled binary content files are stored the prepared script files, and then performing at a variable initialization module of the computing system an act of processing the one or more non-binary script files to change the current values of one or more variables to updated values for the one or more variables in one or more of the compiled binary content files; and at the computing system where the one or more compiles binary content files are stored, using the variable initialization module to update the one or more compiled binary content files with the change to current values of the one or more variables obtained from the one or more script files without having to recompile the updated binary content files. | 1. A computer program product for implementing a method for controlling a computing system, the computer program product comprising physical computer storage media containing computer-executable instructions for implementing a method for customizing a binary content file stored at the computing system without recompiling source code associated with the binary content file so as to modify the behavior of the binary content file when the binary content file is executed at a destination computing system, and wherein the method comprises: at a computing system performing an act of translating an object file compiled from source code into one or more compiled binary content files; an act of receiving at a computing system for storage one or more compiled binary content files that each includes one or more variables that are assigned current values; an act of preparing at a computing system one or more non-binary script files that each include one or more references to updated values for one or more of the variables in one or more of the compiled binary content files; inputting for storage at the computing system at which the one or more compiled binary content files are stored the prepared script files, and then performing at a variable initialization module of the computing system an act of processing the one or more non-binary script files to change the current values of one or more variables to updated values for the one or more variables in one or more of the compiled binary content files; and at the computing system where the one or more compiles binary content files are stored, using the variable initialization module to update the one or more compiled binary content files with the change to current values of the one or more variables obtained from the one or more script files without having to recompile the updated binary content files. 10. The computer program product as recited in claim 1 , wherein the act of processing the one or more non-binary script files to change the current values of one or more variables to updated values for the one or more variables in one or more of the compiled binary content files comprises the following: an act of directly overwriting the current values of the one or more variables included in the one or more compiled binary content files with the updated values of the one or more variables included in at least one non-binary script file. | 0.531842 |
7,853,546 | 6 | 9 | 6. The method of claim 2 , wherein extracting the data comprises: obtaining the predefined rules from a second storage; and extracting information of interest from the data based on the predefined rules. | 6. The method of claim 2 , wherein extracting the data comprises: obtaining the predefined rules from a second storage; and extracting information of interest from the data based on the predefined rules. 9. The method of claim 6 , further comprising storing the processed data in a third storage. | 0.964479 |
8,386,568 | 1 | 2 | 1. A method of communicating during an instant messaging (“IM”) session, comprising: creating, by a message author participating in the IM session, a first message to be sent to each of at least one other participants in the IM session; designating in the first message, by the message author, at least one portion of the first message for sending to a non-participant in the IM session; annotating the first message, by the message author, with at least one messaging identifier associated with the non-participant and, for each of the at least one messaging identifiers, a corresponding routing method; sending a query to each of the at least one other participants to determine if they approve sending the at least one designated portion to the non-participant, and if a response to each sent query indicates that the at least one other participants approve the sending, then: programmatically generating a second message that comprises each of the at least one designated portions of the first message and excludes other portions of the first message; and sending the second message to the non-participant using at least one of the messaging identifiers with which the first message is annotated and the corresponding routing method; and sending the first message to each of the at least one other participants in the IM session using the IM session, wherein at least one of the corresponding routing methods used for sending the second message to the non-participant is different from the IM session used for sending the first message to each of the at least one other participants. | 1. A method of communicating during an instant messaging (“IM”) session, comprising: creating, by a message author participating in the IM session, a first message to be sent to each of at least one other participants in the IM session; designating in the first message, by the message author, at least one portion of the first message for sending to a non-participant in the IM session; annotating the first message, by the message author, with at least one messaging identifier associated with the non-participant and, for each of the at least one messaging identifiers, a corresponding routing method; sending a query to each of the at least one other participants to determine if they approve sending the at least one designated portion to the non-participant, and if a response to each sent query indicates that the at least one other participants approve the sending, then: programmatically generating a second message that comprises each of the at least one designated portions of the first message and excludes other portions of the first message; and sending the second message to the non-participant using at least one of the messaging identifiers with which the first message is annotated and the corresponding routing method; and sending the first message to each of the at least one other participants in the IM session using the IM session, wherein at least one of the corresponding routing methods used for sending the second message to the non-participant is different from the IM session used for sending the first message to each of the at least one other participants. 2. The method according to claim 1 , wherein at least one of the corresponding routing methods comprises sending the second message as an instant message from the message author to the non-participant. | 0.773649 |
9,185,081 | 1 | 4 | 1. A method for encrypting a first application data file, the method comprising: determining, by operation of a processor, a file format of the first application data file; encrypting the first application data file; selecting a second application data file template having a file format matching the file format of the first application data file, wherein a placeholder image is embedded in the second application data file template; storing the first application data file as encrypted content in an image file container, wherein storing the first application data file as the encrypted content in the image file container comprises: generating the image file container having a first image format, and embedding the encrypted content, as image data, in the image file container; replacing the placeholder image in the second application data file template with the image file container storing the first application data file as encrypted content; embedding, in the second application data file template, textual instructions for accessing the encrypted content; and generating a second application data file from the second application data file template, wherein the textual instructions are presented to users when accessing the second application data file. | 1. A method for encrypting a first application data file, the method comprising: determining, by operation of a processor, a file format of the first application data file; encrypting the first application data file; selecting a second application data file template having a file format matching the file format of the first application data file, wherein a placeholder image is embedded in the second application data file template; storing the first application data file as encrypted content in an image file container, wherein storing the first application data file as the encrypted content in the image file container comprises: generating the image file container having a first image format, and embedding the encrypted content, as image data, in the image file container; replacing the placeholder image in the second application data file template with the image file container storing the first application data file as encrypted content; embedding, in the second application data file template, textual instructions for accessing the encrypted content; and generating a second application data file from the second application data file template, wherein the textual instructions are presented to users when accessing the second application data file. 4. The method of claim 1 , wherein the first image format comprises the Portable Network Graphics (PNG) format. | 0.877212 |
8,412,628 | 1 | 6 | 1. A method for receiving and processing a claim file and authoring and electronically filing a legal document for a legal action in a court, comprising the steps of: (A) electronically receiving the claim file in electronic form wherein the claim file includes a plurality of data fields in a native format; (B) mapping, using an electronic processor, one or more of the data fields from the native format to a desired format different from the native format to form a modified claim file; (C) selecting a court, using the processor, at least in part on data included in the modified claim file and predetermined court selection criteria; (D) generating, using the processor, a legal document in electronic form configured for electronic filing in the selected court and which is compliant with requirements of the selected court, using data in the modified claim file and predetermined filing requirements data associated with the selected court; and (E) electronically filing the generated legal document in the selected court. | 1. A method for receiving and processing a claim file and authoring and electronically filing a legal document for a legal action in a court, comprising the steps of: (A) electronically receiving the claim file in electronic form wherein the claim file includes a plurality of data fields in a native format; (B) mapping, using an electronic processor, one or more of the data fields from the native format to a desired format different from the native format to form a modified claim file; (C) selecting a court, using the processor, at least in part on data included in the modified claim file and predetermined court selection criteria; (D) generating, using the processor, a legal document in electronic form configured for electronic filing in the selected court and which is compliant with requirements of the selected court, using data in the modified claim file and predetermined filing requirements data associated with the selected court; and (E) electronically filing the generated legal document in the selected court. 6. The method of claim 1 further including the step of: validating a legal claim based on at least on data in the modified claim file and predetermined rules and documentation requirements associated with the selected court. | 0.916168 |
8,788,566 | 27 | 29 | 27. The policy engine according to claim 16 , where the policy applying module comprises: a document validating unit that validates whether any instance document in the instantiated context model is matched using each of the policies; a validation report generating unit that generates a validation report for the matched policy; an action enforcing unit that enforces an action part of the matched policy according to the validation report. | 27. The policy engine according to claim 16 , where the policy applying module comprises: a document validating unit that validates whether any instance document in the instantiated context model is matched using each of the policies; a validation report generating unit that generates a validation report for the matched policy; an action enforcing unit that enforces an action part of the matched policy according to the validation report. 29. The policy engine according to claim 27 , where the action enforcing unit comprises: a loading unit that loads an action semantic module in the action part; a parameter setting unit that sets parameters in the action semantic module; and an executing unit that executes the action semantic module. | 0.927119 |
9,965,569 | 10 | 14 | 10. A computer-implemented method for reducing user error when constructing a search query, comprising: receiving, by a computing device, a search query without launching a web search for the search query; obtaining, by the computing device, autosuggest candidates having the search query as a common prefix wherein the autosuggest candidates are based, at least in part, on received user preference information corresponding to the search query; generating, by the computing device, truncated autosuggest candidates by removing the search query from the autosuggest candidates; and providing the truncated autosuggest candidates for display. | 10. A computer-implemented method for reducing user error when constructing a search query, comprising: receiving, by a computing device, a search query without launching a web search for the search query; obtaining, by the computing device, autosuggest candidates having the search query as a common prefix wherein the autosuggest candidates are based, at least in part, on received user preference information corresponding to the search query; generating, by the computing device, truncated autosuggest candidates by removing the search query from the autosuggest candidates; and providing the truncated autosuggest candidates for display. 14. The computer-implemented method of claim 10 , wherein the received information is received from a suggestion dictionary. | 0.931943 |
9,691,391 | 15 | 17 | 15. One or more non-transitory computer-readable media comprising computer executable instructions that, when executed, perform a method for clustering audio segments, the method comprising: obtaining a plurality of audio segments, wherein each audio segment of the plurality of audio segments includes a representation of speech generated by a speaker of a plurality of speakers; computing a speaker model for each audio segment of the plurality of audio segments; computing a plurality of scores, wherein each score of the plurality of scores corresponds to a pair of speaker models, the plurality of scores comprising a first score and a second score, wherein: the first score is computed using a first speaker model corresponding to a first audio segment and a second speaker model corresponding to a second audio segment, and the second score is computed using a third speaker model corresponding to a third audio segment and a fourth speaker model corresponding to a fourth audio segment; generating a graph, wherein each audio segment of the plurality of audio segments corresponds to a node in the graph; determining to include an edge between a first node of the graph and a second node of the graph using the first score, wherein the first node corresponds to the first audio segment and the second node corresponds to the second audio segment; determining to not include an edge between a third node of the graph and a fourth node of the graph using the second score, wherein the third node corresponds to the third audio segment and the fourth node corresponds to the fourth audio segment; determining that the first node corresponds to a first community of nodes using edges connected to the first node, wherein the first community of nodes corresponds to a first speaker of the plurality of speakers; and determining that the second node corresponds to a second community of nodes using edges connected to the second node, wherein the second community of nodes corresponds to a second speaker of the plurality of speakers. | 15. One or more non-transitory computer-readable media comprising computer executable instructions that, when executed, perform a method for clustering audio segments, the method comprising: obtaining a plurality of audio segments, wherein each audio segment of the plurality of audio segments includes a representation of speech generated by a speaker of a plurality of speakers; computing a speaker model for each audio segment of the plurality of audio segments; computing a plurality of scores, wherein each score of the plurality of scores corresponds to a pair of speaker models, the plurality of scores comprising a first score and a second score, wherein: the first score is computed using a first speaker model corresponding to a first audio segment and a second speaker model corresponding to a second audio segment, and the second score is computed using a third speaker model corresponding to a third audio segment and a fourth speaker model corresponding to a fourth audio segment; generating a graph, wherein each audio segment of the plurality of audio segments corresponds to a node in the graph; determining to include an edge between a first node of the graph and a second node of the graph using the first score, wherein the first node corresponds to the first audio segment and the second node corresponds to the second audio segment; determining to not include an edge between a third node of the graph and a fourth node of the graph using the second score, wherein the third node corresponds to the third audio segment and the fourth node corresponds to the fourth audio segment; determining that the first node corresponds to a first community of nodes using edges connected to the first node, wherein the first community of nodes corresponds to a first speaker of the plurality of speakers; and determining that the second node corresponds to a second community of nodes using edges connected to the second node, wherein the second community of nodes corresponds to a second speaker of the plurality of speakers. 17. The one or more non-transitory computer-readable media of claim 15 , wherein the first score is score is computed using a cosine similarity metric. | 0.815854 |
7,689,033 | 1 | 9 | 1. A method for use in detecting faces within a digital image, the method comprising: processing via a processor, in a pre-filter stage, a set of digital image data to produce a set of initial candidate portions using at least one feature algorithm, the pre-filter stage including a linear filter based on a decision function having coefficients that are determined during a learning procedure; processing via the processor, in a boosting filter stage, the set of initial candidate portions to produce a set of intermediate candidate portions, the boosting filter stage including: a boosting chain having a plurality of boosting chain nodes to identify candidate portions and a boot strap function following each of the plurality of boosting chain nodes, the boot strap function to use a weak learner of a previous boosting chain node in training another boosting chain node of the boosting chain, wherein the weak learner includes building a simple decision stump on a histogram of a Haar-like feature on a training set; and processing via the processor, the set of intermediate candidate portions in a post-filter stage to produce a set of final candidate portions, wherein the post-filter stage includes an image pre-processing process, a color-filter process, and a support vector machine (SVM) filter process. | 1. A method for use in detecting faces within a digital image, the method comprising: processing via a processor, in a pre-filter stage, a set of digital image data to produce a set of initial candidate portions using at least one feature algorithm, the pre-filter stage including a linear filter based on a decision function having coefficients that are determined during a learning procedure; processing via the processor, in a boosting filter stage, the set of initial candidate portions to produce a set of intermediate candidate portions, the boosting filter stage including: a boosting chain having a plurality of boosting chain nodes to identify candidate portions and a boot strap function following each of the plurality of boosting chain nodes, the boot strap function to use a weak learner of a previous boosting chain node in training another boosting chain node of the boosting chain, wherein the weak learner includes building a simple decision stump on a histogram of a Haar-like feature on a training set; and processing via the processor, the set of intermediate candidate portions in a post-filter stage to produce a set of final candidate portions, wherein the post-filter stage includes an image pre-processing process, a color-filter process, and a support vector machine (SVM) filter process. 9. The method as recited in claim 1 , further comprising training the boosting chain using face images, non-face images, and weak classifiers. | 0.653659 |
8,032,375 | 6 | 7 | 6. The system of claim 1 , wherein the argument model comprises a generative model. | 6. The system of claim 1 , wherein the argument model comprises a generative model. 7. The system of claim 6 , wherein the generative model is a naïve-Bayes model. | 0.967964 |
9,606,986 | 15 | 16 | 15. The method of claim 11 , wherein the weight comprises the conditional probability of the candidate word given the one or more classes divided by the probability of the candidate word within the corpus. | 15. The method of claim 11 , wherein the weight comprises the conditional probability of the candidate word given the one or more classes divided by the probability of the candidate word within the corpus. 16. The method of claim 15 , wherein the weighted conditional probability of the candidate word comprises a dot product of the weight and the conditional probability of the candidate word given the one or more words. | 0.922469 |
10,140,017 | 1 | 15 | 1. A method comprising: outputting, by a first application executing at a computing device, a graphical user interface including a text edit region that includes uncommitted text input, and an output region that includes committed text input: invoking, by the first application, a keyboard application executing at the computing device to provide a graphical keyboard within the graphical user interface; outputting, by the keyboard application, for display adjacent to the text edit and output regions of the graphical user interface, the graphical keyboard, wherein the graphical keyboard includes a plurality of character keys, a word suggestion region and a search element, wherein the word suggestion region and the search element are each positioned above the plurality of character keys and below the text edit and output regions, wherein the word suggestion region includes a plurality of word suggestions based on the uncommitted text input displayed by the text edit region; receiving, by the keyboard application, an indication of a selection of the search element; responsive to receiving the indication of the selection of the search element, outputting, by the keyboard application, for display within the graphical keyboard, adjacent to the text edit and output regions of the graphical user interface, and in place of the word suggestion region, a query suggestion region including one or more suggested search queries; while outputting the query suggestion region for display, receiving, by the keyboard application, an indication of a selection of one or more character keys from the plurality of character keys; outputting, by the keyboard application, for display within the graphical keyboard, adjacent to the text edit and output regions of the graphical user interface, and in place of the query suggestion region, an updated query suggestion region including one or more characters selected in response to the selection of the one or more character keys; determining, by the keyboard application, based on the one or more characters, one or more updated suggested search queries; outputting, by the keyboard application, for display, the one or more updated suggested search queries in the updated query suggestion region; receiving, by the keyboard application, an indication of a selection of one of one or more updated suggested search queries, the one of the one or more updated suggested search queries being a selected search query; invoking, by the keyboard application and based on the selected search query, a search; responsive to invoking the search, receiving, by the keyboard application, search results; and outputting, by the keyboard application, for display within the graphical keyboard, adjacent to the text edit and output regions of the graphical user interface, and in place of a portion, but not all, of the plurality of character keys, a graphical indication of at least a portion of the search results. | 1. A method comprising: outputting, by a first application executing at a computing device, a graphical user interface including a text edit region that includes uncommitted text input, and an output region that includes committed text input: invoking, by the first application, a keyboard application executing at the computing device to provide a graphical keyboard within the graphical user interface; outputting, by the keyboard application, for display adjacent to the text edit and output regions of the graphical user interface, the graphical keyboard, wherein the graphical keyboard includes a plurality of character keys, a word suggestion region and a search element, wherein the word suggestion region and the search element are each positioned above the plurality of character keys and below the text edit and output regions, wherein the word suggestion region includes a plurality of word suggestions based on the uncommitted text input displayed by the text edit region; receiving, by the keyboard application, an indication of a selection of the search element; responsive to receiving the indication of the selection of the search element, outputting, by the keyboard application, for display within the graphical keyboard, adjacent to the text edit and output regions of the graphical user interface, and in place of the word suggestion region, a query suggestion region including one or more suggested search queries; while outputting the query suggestion region for display, receiving, by the keyboard application, an indication of a selection of one or more character keys from the plurality of character keys; outputting, by the keyboard application, for display within the graphical keyboard, adjacent to the text edit and output regions of the graphical user interface, and in place of the query suggestion region, an updated query suggestion region including one or more characters selected in response to the selection of the one or more character keys; determining, by the keyboard application, based on the one or more characters, one or more updated suggested search queries; outputting, by the keyboard application, for display, the one or more updated suggested search queries in the updated query suggestion region; receiving, by the keyboard application, an indication of a selection of one of one or more updated suggested search queries, the one of the one or more updated suggested search queries being a selected search query; invoking, by the keyboard application and based on the selected search query, a search; responsive to invoking the search, receiving, by the keyboard application, search results; and outputting, by the keyboard application, for display within the graphical keyboard, adjacent to the text edit and output regions of the graphical user interface, and in place of a portion, but not all, of the plurality of character keys, a graphical indication of at least a portion of the search results. 15. The method of claim 1 , wherein: the keyboard application executes as an extension to the first application. | 0.898917 |
4,724,523 | 67 | 68 | 67. A method according to claim 66 which said second coding step comprises storing a signal representative of at least one of a partial verbal paradigm and a partial nominal paradigm. | 67. A method according to claim 66 which said second coding step comprises storing a signal representative of at least one of a partial verbal paradigm and a partial nominal paradigm. 68. A method according to claim 67 in which said second coding step comprises storing a signal representative of an exceptional inflectional form expression corresponding to at least one said partial paradigm-representative signal. | 0.934635 |
9,152,388 | 6 | 9 | 6. A system comprising: at least one programmable processor; and a machine-readable medium storing instructions that, when executed by the at least one programmable processor, cause the at least one programmable processor to perform operations comprising: receiving a user scripting input via a script editor displayed to a user on a displayed of a computing device, the user scripting input comprising a script using defining a subset language of a standardized scripting language, the subset language being simplified relative to the standardized scripting language while retaining a syntax of the standardized scripting language and comprising a tailored grammar matching features of the subset language without being a subset of a grammar of the standardized scripting language, each of the subset language features being defined within the tailored grammar of the subset to be compatible with a specification of the standardized scripting language, the user scripting input creating a user interface feature accessing data in one or more objects; determining a type for a variable entered as part of the scripting input during input of a character string of the scripting input, the determining comprising use of a subset-specific type system for the subset of the standardized scripting language, the subset-specific type system providing a type inference capability that accesses information about an underlying data structure of the one or more objects, the subset-specific type system adding to a defined type system for the standardized scripting language; and querying a type library to display to the user assistance information for resolving the character string to a correct type and description compatible with the underlying data structure. | 6. A system comprising: at least one programmable processor; and a machine-readable medium storing instructions that, when executed by the at least one programmable processor, cause the at least one programmable processor to perform operations comprising: receiving a user scripting input via a script editor displayed to a user on a displayed of a computing device, the user scripting input comprising a script using defining a subset language of a standardized scripting language, the subset language being simplified relative to the standardized scripting language while retaining a syntax of the standardized scripting language and comprising a tailored grammar matching features of the subset language without being a subset of a grammar of the standardized scripting language, each of the subset language features being defined within the tailored grammar of the subset to be compatible with a specification of the standardized scripting language, the user scripting input creating a user interface feature accessing data in one or more objects; determining a type for a variable entered as part of the scripting input during input of a character string of the scripting input, the determining comprising use of a subset-specific type system for the subset of the standardized scripting language, the subset-specific type system providing a type inference capability that accesses information about an underlying data structure of the one or more objects, the subset-specific type system adding to a defined type system for the standardized scripting language; and querying a type library to display to the user assistance information for resolving the character string to a correct type and description compatible with the underlying data structure. 9. A system as in claim 6 , wherein the user interface feature comprises one or more of a chart and a table. | 0.725888 |
9,190,049 | 6 | 13 | 6. A computer-implemented method comprising: retrieving a first content item from a first content source and a second content item from a second content source, wherein the first content source is different from the second content source; identifying first text-to-speech voice data based at least in part on a characteristic of the first content item; determining that the second content item comprises a first portion and a second portion; identifying second text-to-speech voice data and third text-to-speech voice data based at least in part on a characteristic of the second content item, wherein the first text-to-speech voice data is different from the second text-to-speech voice data; generating a first audio presentation of the first content item utilizing the first text-to-speech voice data; generating a second audio presentation of the second content item utilizing the second text-to-speech voice data with the first portion, and using the third text-to-speech voice data with the second portion; and assembling an audio program comprising the first audio presentation and the second audio presentation. | 6. A computer-implemented method comprising: retrieving a first content item from a first content source and a second content item from a second content source, wherein the first content source is different from the second content source; identifying first text-to-speech voice data based at least in part on a characteristic of the first content item; determining that the second content item comprises a first portion and a second portion; identifying second text-to-speech voice data and third text-to-speech voice data based at least in part on a characteristic of the second content item, wherein the first text-to-speech voice data is different from the second text-to-speech voice data; generating a first audio presentation of the first content item utilizing the first text-to-speech voice data; generating a second audio presentation of the second content item utilizing the second text-to-speech voice data with the first portion, and using the third text-to-speech voice data with the second portion; and assembling an audio program comprising the first audio presentation and the second audio presentation. 13. The computer-implemented method of claim 6 , further comprising: receiving, from a client device, authentication information associated with the first content source, wherein retrieving the first content item comprises presenting the authentication information to the first content source. | 0.80068 |
8,031,204 | 9 | 17 | 9. A system for filtering a font character bitmap represented as a texture map, comprising: a texture read request unit configured to read a coarsely aligned region of the font character bitmap; a font alignment engine configured to align the coarsely aligned region of the texture map with a font filter footprint and produce a finely aligned region of the font character bitmap; a font sample unit configured to compute font samples for portions of the finely aligned region of the font character bitmap, wherein the font samples indicate a percentage of texels that are within a font character represented by the font character bitmap; a bilinear filter engine configured to bilinearly interpolate the font samples to produce a bilinearly filtered font sample value for the finely aligned region of the font character bitmap; and computing a font coverage value for the finely aligned region of the font character bitmap by scaling the bilinearly filtered font sample value by a normalization factor. | 9. A system for filtering a font character bitmap represented as a texture map, comprising: a texture read request unit configured to read a coarsely aligned region of the font character bitmap; a font alignment engine configured to align the coarsely aligned region of the texture map with a font filter footprint and produce a finely aligned region of the font character bitmap; a font sample unit configured to compute font samples for portions of the finely aligned region of the font character bitmap, wherein the font samples indicate a percentage of texels that are within a font character represented by the font character bitmap; a bilinear filter engine configured to bilinearly interpolate the font samples to produce a bilinearly filtered font sample value for the finely aligned region of the font character bitmap; and computing a font coverage value for the finely aligned region of the font character bitmap by scaling the bilinearly filtered font sample value by a normalization factor. 17. The system of claim 9 , wherein the bilinear filter unit is further configured to bilinearly interpolate the font samples using fractional portions of texture coordinates corresponding to a position of the font filter footprint relative to the font character bitmap. | 0.685315 |
8,478,903 | 11 | 20 | 11. The content delivery system as recited in claim 1 further comprising: a set of shared repeater servers that comprises the at least one repeater server; and a repeater selector mechanism constructed and adapted to associate the first resource with the first alias name after selecting the at least one shared repeater server from the set of shared repeater servers in response to a request for the first resource issued by a particular client machine. | 11. The content delivery system as recited in claim 1 further comprising: a set of shared repeater servers that comprises the at least one repeater server; and a repeater selector mechanism constructed and adapted to associate the first resource with the first alias name after selecting the at least one shared repeater server from the set of shared repeater servers in response to a request for the first resource issued by a particular client machine. 20. The content delivery system as recited in claim 11 , wherein the repeater selector mechanism is part of a reflector. | 0.969574 |
10,019,477 | 6 | 9 | 6. A computer system for query processing, the computer system comprising: one or more computer processors, one or more computer readable storage media, and program instructions stored on the computer readable storage media for execution by at least one of the one or more processors, the program instructions comprising: program instructions to receive a query; program instructions to determine the received query does not correspond to a previously executed query; program instructions to parse the received query to identify input literals that include one or more of: data values, tables, fields, records, and a parameter included in the received query; program instructions to determine whether a pattern is associated with the input literals included in the received query; responsive to determining a pattern is associated with the input literals included in the received query, program instructions to identify one or more indices that include the pattern; program instructions to retrieve one or more adjacent index keys from the identified one or more indices corresponding to the pattern; program instructions to determine one or more pattern hits within the retrieved one or more adjacent index keys, wherein the one or more pattern hits are matches between the parameter of the received query and the retrieved one or more adjacent index keys; program instructions to store a total number of executions of comparisons of the parameter of the received query to the retrieved one or more adjacent index keys and a total number of the one or more pattern hits; program instructions to calculate a ratio of the total number of the one or more pattern hits to the total number of executions; program instructions to determine whether the one or more indices include the pattern based on the calculated ratio at least meeting a predetermined value; responsive to determining the one or more indices include the pattern based on the calculated ratio at least meeting a predetermined value, program instructions to determine a future parameter based on the pattern associated with the input literals, wherein the future parameter is a subsequent instance of a parameter of the received query that corresponds to the pattern; and program instructions to automatically create a future query by incorporating the determined future parameter into the received query. | 6. A computer system for query processing, the computer system comprising: one or more computer processors, one or more computer readable storage media, and program instructions stored on the computer readable storage media for execution by at least one of the one or more processors, the program instructions comprising: program instructions to receive a query; program instructions to determine the received query does not correspond to a previously executed query; program instructions to parse the received query to identify input literals that include one or more of: data values, tables, fields, records, and a parameter included in the received query; program instructions to determine whether a pattern is associated with the input literals included in the received query; responsive to determining a pattern is associated with the input literals included in the received query, program instructions to identify one or more indices that include the pattern; program instructions to retrieve one or more adjacent index keys from the identified one or more indices corresponding to the pattern; program instructions to determine one or more pattern hits within the retrieved one or more adjacent index keys, wherein the one or more pattern hits are matches between the parameter of the received query and the retrieved one or more adjacent index keys; program instructions to store a total number of executions of comparisons of the parameter of the received query to the retrieved one or more adjacent index keys and a total number of the one or more pattern hits; program instructions to calculate a ratio of the total number of the one or more pattern hits to the total number of executions; program instructions to determine whether the one or more indices include the pattern based on the calculated ratio at least meeting a predetermined value; responsive to determining the one or more indices include the pattern based on the calculated ratio at least meeting a predetermined value, program instructions to determine a future parameter based on the pattern associated with the input literals, wherein the future parameter is a subsequent instance of a parameter of the received query that corresponds to the pattern; and program instructions to automatically create a future query by incorporating the determined future parameter into the received query. 9. The computer system of claim 6 , further comprising program instructions, stored on the one or more computer readable storage media, to: receive an another query; determine the received another query correspond to the automatically performed future query; retrieve the stored results of the automatically performed future query corresponding to the received another query; and display the retrieved stored results of the automatically performed future query. | 0.680748 |
6,038,574 | 5 | 6 | 5. The method as recited in claim 1 wherein said method is further comprised of the steps of: f) determining if said generated document clusters provides acceptable clustering results; g) if said generated document clusters does not provide acceptable clustering results, varying the value of said link frequency threshold; and h) repeating steps b)-e). | 5. The method as recited in claim 1 wherein said method is further comprised of the steps of: f) determining if said generated document clusters provides acceptable clustering results; g) if said generated document clusters does not provide acceptable clustering results, varying the value of said link frequency threshold; and h) repeating steps b)-e). 6. The method as recited in claim 5 wherein an unacceptable clustering results is a combination of few large clusters and many small clusters, said step of varying the value of said link frequency threshold causes said link frequency threshold to decrease. | 0.864263 |
9,134,811 | 1 | 3 | 1. A device comprising: a processor; and a memory that stores instructions that, when executed by the processor, cause the processor to perform operations comprising: receiving a selection of a key of a plurality of keys, wherein the key is associated with a question and wherein the selection of the key indicates an answer to the question, after receiving the selection of the key of the plurality of keys, assigning a prediction value to at least a portion of the plurality of keys based on the answer to the question associated with the key selected; and adjusting an acceptable angle for one of the at least a portion of the plurality of keys relative to the prediction value assigned to the one of the at least a portion of the plurality of keys, the acceptable angle being measured by a plurality of electrical contacts arranged around a center of the one of the at least a portion of the plurality of keys, the plurality of electrical contacts comprising a plurality of upper electrical contacts and a plurality of lower electrical contacts, wherein adjusting the acceptable angle comprises: in response to the one of the at least a portion of the plurality of keys being assigned a lower prediction value, increasing a number of the plurality of upper electrical contacts of the one of the at least a portion of the plurality of keys required to contact a number of the plurality of lower electrical contacts of the one of the at least a portion of the plurality of keys to constitute an entry of the one of the at least a portion of the plurality of keys, and in response to the one of the at least a portion of the plurality of keys being assigned a higher prediction value, decreasing the number of the plurality of upper electrical contacts of the one of the at least a portion of the plurality of keys required to contact the number of the plurality of lower electrical contacts of the one of the at least a portion of the plurality of keys to constitute the entry of the one of the at least a portion of the plurality of keys. | 1. A device comprising: a processor; and a memory that stores instructions that, when executed by the processor, cause the processor to perform operations comprising: receiving a selection of a key of a plurality of keys, wherein the key is associated with a question and wherein the selection of the key indicates an answer to the question, after receiving the selection of the key of the plurality of keys, assigning a prediction value to at least a portion of the plurality of keys based on the answer to the question associated with the key selected; and adjusting an acceptable angle for one of the at least a portion of the plurality of keys relative to the prediction value assigned to the one of the at least a portion of the plurality of keys, the acceptable angle being measured by a plurality of electrical contacts arranged around a center of the one of the at least a portion of the plurality of keys, the plurality of electrical contacts comprising a plurality of upper electrical contacts and a plurality of lower electrical contacts, wherein adjusting the acceptable angle comprises: in response to the one of the at least a portion of the plurality of keys being assigned a lower prediction value, increasing a number of the plurality of upper electrical contacts of the one of the at least a portion of the plurality of keys required to contact a number of the plurality of lower electrical contacts of the one of the at least a portion of the plurality of keys to constitute an entry of the one of the at least a portion of the plurality of keys, and in response to the one of the at least a portion of the plurality of keys being assigned a higher prediction value, decreasing the number of the plurality of upper electrical contacts of the one of the at least a portion of the plurality of keys required to contact the number of the plurality of lower electrical contacts of the one of the at least a portion of the plurality of keys to constitute the entry of the one of the at least a portion of the plurality of keys. 3. The device of claim 1 , wherein the operations further comprise illuminating an indicator associated with the question based on the selection of the key associated with the question. | 0.656134 |
7,941,746 | 1 | 3 | 1. A method for creating a CSS (cascading style sheet) file from a CSSX (Extended Cascading Style Sheets) file including CSSX extensions for defining a variable, said CSS file intended for execution by a web browser that does not execute CSSX extensions wherein the web browser would not execute the variables of the CSSX file including the CSSX extensions, said method comprising: creating the CSSX file including CSSX extensions for defining a variable and CSSX extensions for referencing said variable, wherein said creating comprises: defining a left variable with a value of left and a right variable with a value of right; referencing at least the left variable or the right variable in the CSSX file; and specifying a language within the CSSX file; determining a value of the defined variable in the CSSX file; modifying the CSSX file by replacing all references to the defined variable with the determined value; and generating from the modified CSSX file the CSS file not including the variable and including the replaced variable value wherein the CSS file contains only CSS compatible commands and wherein the CSS file contains no CSSX extensions, wherein said generating comprises: determining if the specified language reads left-to-right or right-to-left; if the specified language reads right-to-left, redefining the right variable with a value of left and the left variable with a value of right; and generating from the specified CSSX file the CSS file not including the variable definition and including the replaced variable value wherein the CSS file contains only CSS compatible commands and wherein the CSS file contains no CSS extensions whereby the CSS file will automatically render a right-to-left layout in the web browser when the language reads right-to-left. | 1. A method for creating a CSS (cascading style sheet) file from a CSSX (Extended Cascading Style Sheets) file including CSSX extensions for defining a variable, said CSS file intended for execution by a web browser that does not execute CSSX extensions wherein the web browser would not execute the variables of the CSSX file including the CSSX extensions, said method comprising: creating the CSSX file including CSSX extensions for defining a variable and CSSX extensions for referencing said variable, wherein said creating comprises: defining a left variable with a value of left and a right variable with a value of right; referencing at least the left variable or the right variable in the CSSX file; and specifying a language within the CSSX file; determining a value of the defined variable in the CSSX file; modifying the CSSX file by replacing all references to the defined variable with the determined value; and generating from the modified CSSX file the CSS file not including the variable and including the replaced variable value wherein the CSS file contains only CSS compatible commands and wherein the CSS file contains no CSSX extensions, wherein said generating comprises: determining if the specified language reads left-to-right or right-to-left; if the specified language reads right-to-left, redefining the right variable with a value of left and the left variable with a value of right; and generating from the specified CSSX file the CSS file not including the variable definition and including the replaced variable value wherein the CSS file contains only CSS compatible commands and wherein the CSS file contains no CSS extensions whereby the CSS file will automatically render a right-to-left layout in the web browser when the language reads right-to-left. 3. The method of claim 1 , wherein a whole CSS term or part of a CSS term may be replaced by a reference to the variable. | 0.727477 |
8,606,728 | 9 | 10 | 9. A system comprising: one or more data processing apparatus; and a computer-readable storage device having stored thereon instructions that, when executed by the one or more data processing apparatus, cause the one or more data processing apparatus to perform operations comprising: calculating one or more types of suggestion scores for each of a plurality of training examples wherein each type of suggestion score is based at least in part on a plurality of computed predictions for each training example generated by a plurality of different trained models, including weighting each type of suggestion score by an accuracy of the trained model that generated the prediction; calculating an overall suggestion score for each training example based at least in part on a combination of the one or more types of suggestion scores for each training example; ranking the training examples by the corresponding overall suggestion scores; and providing one or more highest-ranked training examples as a set of suggested training examples. | 9. A system comprising: one or more data processing apparatus; and a computer-readable storage device having stored thereon instructions that, when executed by the one or more data processing apparatus, cause the one or more data processing apparatus to perform operations comprising: calculating one or more types of suggestion scores for each of a plurality of training examples wherein each type of suggestion score is based at least in part on a plurality of computed predictions for each training example generated by a plurality of different trained models, including weighting each type of suggestion score by an accuracy of the trained model that generated the prediction; calculating an overall suggestion score for each training example based at least in part on a combination of the one or more types of suggestion scores for each training example; ranking the training examples by the corresponding overall suggestion scores; and providing one or more highest-ranked training examples as a set of suggested training examples. 10. The system of claim 9 , wherein the operations further comprise providing one or more of highest-ranked training examples in response to a request. | 0.873534 |
9,697,239 | 20 | 21 | 20. The system of claim 19 , wherein the operations further comprise determining the visibility of a token being queried. | 20. The system of claim 19 , wherein the operations further comprise determining the visibility of a token being queried. 21. The system of claim 20 , wherein operations determining visibility further comprise testing one or more of whether the token is not marked as deleted, a version of the token is smaller than the current version identifier of the execution tree, and the version of the token matches a visible version range that is associated with the execution tree. | 0.918481 |
10,072,941 | 14 | 15 | 14. A mobile device comprising: an input operative to receive at least a portion of a conversational narrative comprising at least one non-verbal physical movement of a portion of a human body of a provider and descriptive of a route to a destination expressed by the provider thereof to a receiver not connected to the mobile device, wherein the conversational narrative includes a plurality elements, the plurality of elements including a plurality of navigation oriented elements and at least one descriptive element characterizing another of the plurality of elements; a converter coupled with the input and operative to convert the received portion of the expressed conversational narrative to data representative thereof; a parser coupled with the converter and operative to identify the plurality of navigation oriented conversational elements represented within the data, as well as any descriptive elements associated therewith; a navigation processor coupled with the parser and operative to convert each of the plurality of navigation oriented conversational elements into an associated navigation data element representative thereof based on the identified descriptive elements associated therewith, if any; a route generator coupled with the navigation processor and operative to compile the navigation elements into a navigation route; and an output coupled with the route generator and operative to present the navigation route. | 14. A mobile device comprising: an input operative to receive at least a portion of a conversational narrative comprising at least one non-verbal physical movement of a portion of a human body of a provider and descriptive of a route to a destination expressed by the provider thereof to a receiver not connected to the mobile device, wherein the conversational narrative includes a plurality elements, the plurality of elements including a plurality of navigation oriented elements and at least one descriptive element characterizing another of the plurality of elements; a converter coupled with the input and operative to convert the received portion of the expressed conversational narrative to data representative thereof; a parser coupled with the converter and operative to identify the plurality of navigation oriented conversational elements represented within the data, as well as any descriptive elements associated therewith; a navigation processor coupled with the parser and operative to convert each of the plurality of navigation oriented conversational elements into an associated navigation data element representative thereof based on the identified descriptive elements associated therewith, if any; a route generator coupled with the navigation processor and operative to compile the navigation elements into a navigation route; and an output coupled with the route generator and operative to present the navigation route. 15. The mobile device of claim 14 wherein the navigation processor is further coupled with a navigation database operative to relate one or more navigation oriented conversational elements to one or more navigation data elements. | 0.811987 |
8,825,447 | 15 | 16 | 15. The automatic correlation accelerator tool of claim 14 , wherein the operations further comprise generating, based on filtering lines of the first and second recordings of the base script, a first temporary recording of the base script and a second temporary recording of the base script. | 15. The automatic correlation accelerator tool of claim 14 , wherein the operations further comprise generating, based on filtering lines of the first and second recordings of the base script, a first temporary recording of the base script and a second temporary recording of the base script. 16. The automatic correlation accelerator tool of claim 15 , wherein the operations further comprise generating correlation logs using the first temporary recording of the base script and the second temporary recording of the base script. | 0.903331 |
6,137,863 | 7 | 8 | 7. A method of recognizing an identifier entered by a user, the identifier including a first plurality of predetermined characters, the method comprising the steps of: a) providing a recognized identifier based on the entered identifier, the recognized identifier comprising a second plurality of predetermined characters; b) providing a plurality of reference identifiers, each one of the plurality of reference identifiers comprising a different plurality of predetermined characters; c) obtaining from a stored data structure, for each character position in at least one of the reference identifiers and each character position in the recognized identifier, a previously determined probability that a character in the at least one reference identifier is recognized as a character found in the corresponding character position in the recognized identifier, each probability in the stored data structure representing a quantification of a tendency of one predetermined character to be recognized as one of the predetermined character and another predetermined character; d) determining an identifier recognition probability based on the obtained probabilities; e) repeating steps c) and d) for every reference identifier in the plurality of reference identifiers, each one of the plurality of reference identifiers being associated with a corresponding identifier recognition probability; and f) selecting the reference identifier most likely matching the entered identifier based on the plurality of obtained recognition probabilities, wherein the entered identifier is entered by the user speaking the identifier into a voice input device. | 7. A method of recognizing an identifier entered by a user, the identifier including a first plurality of predetermined characters, the method comprising the steps of: a) providing a recognized identifier based on the entered identifier, the recognized identifier comprising a second plurality of predetermined characters; b) providing a plurality of reference identifiers, each one of the plurality of reference identifiers comprising a different plurality of predetermined characters; c) obtaining from a stored data structure, for each character position in at least one of the reference identifiers and each character position in the recognized identifier, a previously determined probability that a character in the at least one reference identifier is recognized as a character found in the corresponding character position in the recognized identifier, each probability in the stored data structure representing a quantification of a tendency of one predetermined character to be recognized as one of the predetermined character and another predetermined character; d) determining an identifier recognition probability based on the obtained probabilities; e) repeating steps c) and d) for every reference identifier in the plurality of reference identifiers, each one of the plurality of reference identifiers being associated with a corresponding identifier recognition probability; and f) selecting the reference identifier most likely matching the entered identifier based on the plurality of obtained recognition probabilities, wherein the entered identifier is entered by the user speaking the identifier into a voice input device. 8. The method according to claim 7, wherein the recognized identifier is provided by a speech recognizer. | 0.972163 |
8,745,581 | 12 | 17 | 12. A system for automatically identifying and filling in source code snippets based upon a context of a user in a development environment, the system comprising: one or more processors configured to provide: a code editor that accepts user input comprising source code; a code modification command set that: identifies an existing code snippet associated with the user's current context within the development environment; duplicates and inserts the code snippet into the code editor and automatically customizes the code snippet based upon the code modification command set used by replacing one or more characters in the snippet with user indicated characters; electronic memory that stores textual information including existing code snippets and transformed code snippets; and an electronic display that displays textual information including existing code snippets and transformed code snippets, the electronic display comprising a plurality of light emitting circuits; wherein said code modification command set transforms a portion of said plurality of light emitting circuits to display customized code snippets. | 12. A system for automatically identifying and filling in source code snippets based upon a context of a user in a development environment, the system comprising: one or more processors configured to provide: a code editor that accepts user input comprising source code; a code modification command set that: identifies an existing code snippet associated with the user's current context within the development environment; duplicates and inserts the code snippet into the code editor and automatically customizes the code snippet based upon the code modification command set used by replacing one or more characters in the snippet with user indicated characters; electronic memory that stores textual information including existing code snippets and transformed code snippets; and an electronic display that displays textual information including existing code snippets and transformed code snippets, the electronic display comprising a plurality of light emitting circuits; wherein said code modification command set transforms a portion of said plurality of light emitting circuits to display customized code snippets. 17. The system of claim 12 , wherein use of the code modification command set opens a new window that contains multiple panels, wherein the panels contain a copy of the code snippet, a display of the customized code snippet, and a place to enter or modify the command set. | 0.847534 |
7,774,193 | 1 | 3 | 1. A method, implemented by a computing system comprising one or more processors, the method comprising: comparing, using one or more of the processors, one or more collocations from a text sample with a corpus; identifying, using one or more of the processors, whether the collocations are disfavored in the corpus; and providing indications of whether the collocations are disfavored via an output device; in which comparing the collocations with the corpus comprises performing one or more searches of the World Wide Web using one or more query terms that comprise each of one or more of the collocations; and in which for each of one or more of the collocations for which searches are performed, a search is performed for each of the one or more query terms that comprise the collocation until either one of the query terms provides search results that meet a preselected threshold for matching the collocation, or all the query terms that comprise the collocation are used without meeting the preselected threshold, and further comprising: composing one or more query terms with a wild card replacing a word in one of the disfavored collocations; searching a word collocation reference for the query terms; identifying results of the search having a relatively high proportion of a candidate word replacing the wild card; and providing the results of the search having the candidate word via the output device as potentially proper word collocations. | 1. A method, implemented by a computing system comprising one or more processors, the method comprising: comparing, using one or more of the processors, one or more collocations from a text sample with a corpus; identifying, using one or more of the processors, whether the collocations are disfavored in the corpus; and providing indications of whether the collocations are disfavored via an output device; in which comparing the collocations with the corpus comprises performing one or more searches of the World Wide Web using one or more query terms that comprise each of one or more of the collocations; and in which for each of one or more of the collocations for which searches are performed, a search is performed for each of the one or more query terms that comprise the collocation until either one of the query terms provides search results that meet a preselected threshold for matching the collocation, or all the query terms that comprise the collocation are used without meeting the preselected threshold, and further comprising: composing one or more query terms with a wild card replacing a word in one of the disfavored collocations; searching a word collocation reference for the query terms; identifying results of the search having a relatively high proportion of a candidate word replacing the wild card; and providing the results of the search having the candidate word via the output device as potentially proper word collocations. 3. The method of claim 1 , wherein a collocation is disfavored if either it is not found in the corpus, or it does not score above a preselected threshold matching score indicating a significant presence of fuzzy matches of the collocation in the corpus. | 0.73922 |
8,082,242 | 21 | 22 | 21. A memory device to store instructions that are executable by a processor of a network device, the instructions comprising: one or more instructions to receive, independent of any search query and from a first user, a selection of one or more documents, where the one or more documents are used to form a plurality of custom content groups; one or more instructions to index the one or more documents to form a custom search index for each of the plurality of custom content groups, where each custom search index is different from a web search index and any other custom search index associated with the plurality of content groups; one or more instructions to receive, from a second, different user, a selection of one or more of the plurality of custom content groups; one or more instructions to receive, from a client device associated with the second user, a search query; one or more instructions to perform, based on the search query, a search of the web search index to identify web search results; one or more instructions to perform, based on the search query, a search of one or more of the custom search indexes associated with the selected one or more custom content groups to identify custom search results; one or more instructions to generate a search result document that includes the web search results, the custom search results, and a plurality of advertisements presented within at least a first area and a second area of the search result document, where the first area is distinct from the second area within the search result document, where the web search results and one or more of the custom search results are included within the first area, and where the advertisements and another one or more of the custom search results are included within the second area; and one or more instructions to provide, to the client device, the search result document. | 21. A memory device to store instructions that are executable by a processor of a network device, the instructions comprising: one or more instructions to receive, independent of any search query and from a first user, a selection of one or more documents, where the one or more documents are used to form a plurality of custom content groups; one or more instructions to index the one or more documents to form a custom search index for each of the plurality of custom content groups, where each custom search index is different from a web search index and any other custom search index associated with the plurality of content groups; one or more instructions to receive, from a second, different user, a selection of one or more of the plurality of custom content groups; one or more instructions to receive, from a client device associated with the second user, a search query; one or more instructions to perform, based on the search query, a search of the web search index to identify web search results; one or more instructions to perform, based on the search query, a search of one or more of the custom search indexes associated with the selected one or more custom content groups to identify custom search results; one or more instructions to generate a search result document that includes the web search results, the custom search results, and a plurality of advertisements presented within at least a first area and a second area of the search result document, where the first area is distinct from the second area within the search result document, where the web search results and one or more of the custom search results are included within the first area, and where the advertisements and another one or more of the custom search results are included within the second area; and one or more instructions to provide, to the client device, the search result document. 22. The device of claim 21 , where the one or more instructions to receive the selection of the one or more custom content groups further include: one or more instructions to determine at least one of the plurality of custom content groups that the second user is permitted to access, and one or more instructions to automatically select the at least one custom content group that the second user is permitted to access. | 0.730077 |
8,700,619 | 1 | 14 | 1. A computer-implemented method for providing search results to a user, the method comprising: receiving a search query from the user, the search query being associated with a particular date and comprising a plurality of search terms; forming, using a processor, a query feature vector for the search query, the query feature vector comprising a set of numerical values associated with the search terms; accessing news feature vectors associated with documents related to current events, the current events documents having publication dates that are temporally proximate to the particular date, and the news feature vectors comprising sets of numerical values associated with terms in corresponding ones of the current events documents; generating an augmented query feature vector based on the query feature vector and at least one of the news feature vectors, the generating comprising: identifying a subset of the news feature vectors associated with at least one of the search terms and at least one of the terms within the current events documents; generating a centroid feature vector for the subset of the news feature vectors, based on the sets of numerical values of the subset of the news feature vectors; forming the augmented query feature vector, based on a comparison of the query feature vector and the centroid feature vector, accessing target feature vectors associated with target documents, each the target feature vectors comprising sets of numerical values associated with terms in corresponding ones of the target documents; computing first metrics of similarity between the augmented query feature vector and the target feature vectors, the first similarity metrics comprising at least one of distances or angles between the augmented query feature vector and the target feature vectors; identifying search results based on the computed first similarity metrics, the search results comprising information associated with at least a portion of the target documents; and enabling the user to perceive at least one of the identified search results. | 1. A computer-implemented method for providing search results to a user, the method comprising: receiving a search query from the user, the search query being associated with a particular date and comprising a plurality of search terms; forming, using a processor, a query feature vector for the search query, the query feature vector comprising a set of numerical values associated with the search terms; accessing news feature vectors associated with documents related to current events, the current events documents having publication dates that are temporally proximate to the particular date, and the news feature vectors comprising sets of numerical values associated with terms in corresponding ones of the current events documents; generating an augmented query feature vector based on the query feature vector and at least one of the news feature vectors, the generating comprising: identifying a subset of the news feature vectors associated with at least one of the search terms and at least one of the terms within the current events documents; generating a centroid feature vector for the subset of the news feature vectors, based on the sets of numerical values of the subset of the news feature vectors; forming the augmented query feature vector, based on a comparison of the query feature vector and the centroid feature vector, accessing target feature vectors associated with target documents, each the target feature vectors comprising sets of numerical values associated with terms in corresponding ones of the target documents; computing first metrics of similarity between the augmented query feature vector and the target feature vectors, the first similarity metrics comprising at least one of distances or angles between the augmented query feature vector and the target feature vectors; identifying search results based on the computed first similarity metrics, the search results comprising information associated with at least a portion of the target documents; and enabling the user to perceive at least one of the identified search results. 14. The method of claim 1 , wherein at least one of the current events documents or target documents are web pages. | 0.901372 |
7,584,120 | 1 | 2 | 1. A method of extracting data of interest from at least one web site of a plurality of web sites, wherein the data of interest is information associated with a product, the method comprising: (A) for each respective web site W in said plurality of web sites, (i) creating a respective description of data of interest that identifies the web site W; (ii) developing an extraction pattern from a web page output from the respective web site W using a graphical user interface tool, the extraction pattern being adapted to identify at least a portion of an output of a web site and to extract information from a plurality of web pages of the respective web site W, wherein the extraction pattern comprises a regular expression; and (iii) associating the developed extraction pattern with the respective description of data of interest for the respective web site W; (B) receiving a value for use as an extraction parameter for the developed extraction patterns; and (C) obtaining said data of interest by querying the at least one web site of the plurality of web sites using the value and the extraction patterns associated with the respective descriptions of data of interest; and (D) extracting said data of interest from the at least one web site of the plurality of web sites and storing said extracted data of interest. | 1. A method of extracting data of interest from at least one web site of a plurality of web sites, wherein the data of interest is information associated with a product, the method comprising: (A) for each respective web site W in said plurality of web sites, (i) creating a respective description of data of interest that identifies the web site W; (ii) developing an extraction pattern from a web page output from the respective web site W using a graphical user interface tool, the extraction pattern being adapted to identify at least a portion of an output of a web site and to extract information from a plurality of web pages of the respective web site W, wherein the extraction pattern comprises a regular expression; and (iii) associating the developed extraction pattern with the respective description of data of interest for the respective web site W; (B) receiving a value for use as an extraction parameter for the developed extraction patterns; and (C) obtaining said data of interest by querying the at least one web site of the plurality of web sites using the value and the extraction patterns associated with the respective descriptions of data of interest; and (D) extracting said data of interest from the at least one web site of the plurality of web sites and storing said extracted data of interest. 2. The method of claim 1 , wherein the graphical user interface tool includes a web browser. | 0.911708 |
7,765,200 | 3 | 4 | 3. The computer-implemented method of claim 1 , wherein performing the debugging operations further comprises: skipping at least an unmodified portion of the query execution plan. | 3. The computer-implemented method of claim 1 , wherein performing the debugging operations further comprises: skipping at least an unmodified portion of the query execution plan. 4. The computer-implemented method of claim 3 , wherein performing the debugging operations further comprises: modifying a portion of the query execution plan, and skipping at least an unmodified portion of the query execution plan. | 0.949145 |
9,031,840 | 1 | 2 | 1. A computer-implemented method comprising: receiving, by one or more processors, audio data that encodes (i) a spoken natural language query, and (ii) music; determining, by the one or more processors, that one or more keywords in a transcription of the spoken natural language query are associated with a movie content type; and based on determining that the one or more keywords in the transcription of the spoken natural query are associated with the movie content type, identifying, by the one or more processors, a movie content item that is recognized using the music. | 1. A computer-implemented method comprising: receiving, by one or more processors, audio data that encodes (i) a spoken natural language query, and (ii) music; determining, by the one or more processors, that one or more keywords in a transcription of the spoken natural language query are associated with a movie content type; and based on determining that the one or more keywords in the transcription of the spoken natural query are associated with the movie content type, identifying, by the one or more processors, a movie content item that is recognized using the music. 2. The computer-implemented method of claim 1 , wherein receiving the audio data further comprises receiving the audio data from a mobile computing device. | 0.852662 |
9,237,291 | 15 | 16 | 15. The television of claim 14 , wherein, in a social volume visualization, selected contents of each linked social network profile of a social contact and/or inbound messages and/or outbound messages from or to a linked social media contact and/or current activity of the social media contact is presented in a displayed object on the television screen, the displayed object comprising at least one tile. | 15. The television of claim 14 , wherein, in a social volume visualization, selected contents of each linked social network profile of a social contact and/or inbound messages and/or outbound messages from or to a linked social media contact and/or current activity of the social media contact is presented in a displayed object on the television screen, the displayed object comprising at least one tile. 16. The television of claim 15 , wherein a size of the at least one tile is related to one or more of a relative degree of importance of the linked social contact to the user, a type of relationship of user to the linked social contact, a degree of influence of the linked social contact to the user, a geographic proximity of the linked social contact to the user, a degree to which the currently provided media content is of interest both to the user and linked social contact, an assigned ranking of the linked social contact by the user, a type of social network type linking the user with the linked social contact, a current activity of the linked social contact, a current online or offline status of the linked social contact, and a social network grouping type or category to which both the user and linked social contact belong. | 0.858398 |
8,612,746 | 2 | 3 | 2. The device of claim 1 , where the web feed includes at least one of a Really Simple Syndication (RSS) feed or an Atom feed, where the link is provided at a particular location in the document, and where the received secure content replaces the link at the particular location in the document. | 2. The device of claim 1 , where the web feed includes at least one of a Really Simple Syndication (RSS) feed or an Atom feed, where the link is provided at a particular location in the document, and where the received secure content replaces the link at the particular location in the document. 3. The device of claim 2 , where the processor is further to: provide, in the document, another entry that includes another link that is associated with other secure content. | 0.962805 |
5,418,942 | 12 | 15 | 12. The method of claim 11, wherein the information being stored includes both data and procedure information, and wherein data and procedure are arranged in a structure called a Context, wherein every Context contains both data and procedure, and wherein all procedure information is stored in the same manner as any other information in the computer memory. | 12. The method of claim 11, wherein the information being stored includes both data and procedure information, and wherein data and procedure are arranged in a structure called a Context, wherein every Context contains both data and procedure, and wherein all procedure information is stored in the same manner as any other information in the computer memory. 15. The method of claim 12, wherein the computer intrinsically comprises means for performing the pointer storing step. | 0.941838 |
5,558,520 | 1 | 3 | 1. An interactive coordinated book assembly useful for teaching in a parent/child, teacher/student or self study environment, comprising: a plurality of left and right main pages, each containing textual material and at least one key word; a plurality of left and fight activity pages, each of said activity pages containing an activity area and a direction text area; said main pages and said activity pages being alternately interleaved and bound along one edge to form a book; said direction text areas on said activity pages containing at least one activity to be read, said direction text area on said fight activity page being reverse coordinated with said key word appearing on said left main page and said direction text area on said left activity page being reverse coordinated with said key word appearing on said right main page; wherein at least one of said activities is coordinated with said key word appearing on said fight main page; and wherein said left activity page contains said key word present in said adjacent fight main page, and said right activity page contains said key word present in said adjacent left main page. | 1. An interactive coordinated book assembly useful for teaching in a parent/child, teacher/student or self study environment, comprising: a plurality of left and right main pages, each containing textual material and at least one key word; a plurality of left and fight activity pages, each of said activity pages containing an activity area and a direction text area; said main pages and said activity pages being alternately interleaved and bound along one edge to form a book; said direction text areas on said activity pages containing at least one activity to be read, said direction text area on said fight activity page being reverse coordinated with said key word appearing on said left main page and said direction text area on said left activity page being reverse coordinated with said key word appearing on said right main page; wherein at least one of said activities is coordinated with said key word appearing on said fight main page; and wherein said left activity page contains said key word present in said adjacent fight main page, and said right activity page contains said key word present in said adjacent left main page. 3. The assembly of claim 1, wherein said key word is presented in a form which is visually distinguishable from the surrounding text on said main page. | 0.890896 |
9,823,824 | 2 | 14 | 2. A method of placing text and/or graphic elements in a digital image product comprising: providing a context and content sensitive adaptable user interface for the text and/or graphic element placement in a digital image product; analyzing the context and content of the digital image product and recognizing a plurality of objects within the digital image product; allowing a user to link the text and/or graphic elements with at least one of the recognized objects within the digital image product; in response to dragging the text and/or graphic elements within a predetermined distance to any of the plurality of recognized objects, dynamically suggesting to the user modifications to at least one attribute of a color, font, size, shape, surround, or background of the text and/or graphic elements in the digital image product based on the analysis of the context and content of the digital image product by the user interface; and as the user drags the text and/or graphic elements, dynamically indicating by the user interface to the user via visual, haptic, or audio feedback text placement options that are available on any given area of the digital image product, wherein the image product areas includes recognized objects and open spaces including template surround areas for composite images, collages, or album pages, or folds, gutters, or borders for post printing converting, folding, trimming, and binding operations. | 2. A method of placing text and/or graphic elements in a digital image product comprising: providing a context and content sensitive adaptable user interface for the text and/or graphic element placement in a digital image product; analyzing the context and content of the digital image product and recognizing a plurality of objects within the digital image product; allowing a user to link the text and/or graphic elements with at least one of the recognized objects within the digital image product; in response to dragging the text and/or graphic elements within a predetermined distance to any of the plurality of recognized objects, dynamically suggesting to the user modifications to at least one attribute of a color, font, size, shape, surround, or background of the text and/or graphic elements in the digital image product based on the analysis of the context and content of the digital image product by the user interface; and as the user drags the text and/or graphic elements, dynamically indicating by the user interface to the user via visual, haptic, or audio feedback text placement options that are available on any given area of the digital image product, wherein the image product areas includes recognized objects and open spaces including template surround areas for composite images, collages, or album pages, or folds, gutters, or borders for post printing converting, folding, trimming, and binding operations. 14. The method of claim 2 wherein touching a linked text in a defined manner allows the user to modify the text and element linkage. | 0.741176 |
9,262,938 | 20 | 21 | 20. A computer program product for determining a confidence score for candidate answers to questions in a question-answering system, said computer program product comprising a non-transitory computer readable storage medium having program code embodied therewith, said program code being readable and executable by a computer to perform a method comprising: receiving a question into a computerized device; determining a question LAT, said question LAT being a lexical answer type associated with said question; identifying a candidate answer to said question; automatically determining preliminary types for said candidate answer using first components of said computerized device, said first components using different methods to produce said preliminary types, and each of said first components producing a preliminary type; automatically scoring a match between said preliminary type and said question LAT, each of said first components producing a first type-score, said first type-score representing a degree of match between said preliminary type and said question LAT, said scoring being differentiated based on which of said first components produced said preliminary type; automatically evaluating each said preliminary type and each said first type-score using second components of said computerized device, each of said second components producing a second score based on a combination of said first type-score and a measure of degree that said preliminary type matches said question LAT, said second components using different methods to produce said second score; automatically calculating a final score based on said second score from each of said second components; and automatically outputting said final score representing a degree of confidence that said candidate answer is a type that matches said question LAT. | 20. A computer program product for determining a confidence score for candidate answers to questions in a question-answering system, said computer program product comprising a non-transitory computer readable storage medium having program code embodied therewith, said program code being readable and executable by a computer to perform a method comprising: receiving a question into a computerized device; determining a question LAT, said question LAT being a lexical answer type associated with said question; identifying a candidate answer to said question; automatically determining preliminary types for said candidate answer using first components of said computerized device, said first components using different methods to produce said preliminary types, and each of said first components producing a preliminary type; automatically scoring a match between said preliminary type and said question LAT, each of said first components producing a first type-score, said first type-score representing a degree of match between said preliminary type and said question LAT, said scoring being differentiated based on which of said first components produced said preliminary type; automatically evaluating each said preliminary type and each said first type-score using second components of said computerized device, each of said second components producing a second score based on a combination of said first type-score and a measure of degree that said preliminary type matches said question LAT, said second components using different methods to produce said second score; automatically calculating a final score based on said second score from each of said second components; and automatically outputting said final score representing a degree of confidence that said candidate answer is a type that matches said question LAT. 21. The computer program product according to claim 20 , said method further comprising: performing automated query analysis to determine said question LAT. | 0.908558 |
10,095,769 | 1 | 5 | 1. A method for dynamically clustering data items, the method comprising: receiving (a) a plurality of data items originating from at least two sources; (b) a plurality of distinct metadata details; (c) data indicative of associations between said data items and said metadata details, wherein each data item is associated with at least one metadata detail indicative of the respective data items owner, and wherein at least a first data item originating from a first source and a second data item originating from a second source are related data items associated with at least one shared metadata detail; grading strengths of relationships between at least one of said data items and at least one of said metadata details, wherein said grading comprises applying weighting functions; and clustering said data items into one or more clusters, based on the calculated strengths of a relationship between various data items wherein at least one of said clusters comprises related data items originating from more than one source. | 1. A method for dynamically clustering data items, the method comprising: receiving (a) a plurality of data items originating from at least two sources; (b) a plurality of distinct metadata details; (c) data indicative of associations between said data items and said metadata details, wherein each data item is associated with at least one metadata detail indicative of the respective data items owner, and wherein at least a first data item originating from a first source and a second data item originating from a second source are related data items associated with at least one shared metadata detail; grading strengths of relationships between at least one of said data items and at least one of said metadata details, wherein said grading comprises applying weighting functions; and clustering said data items into one or more clusters, based on the calculated strengths of a relationship between various data items wherein at least one of said clusters comprises related data items originating from more than one source. 5. The method of claim 1 wherein said clustering is based on a heuristic clustering algorithm. | 0.866477 |
9,269,024 | 1 | 3 | 1. A method for signal processing, comprising: obtaining a plurality of signals related to a plurality of subjects; extracting, using at least one processor, one or more generic features of the subjects based on the signals; training, based on the one or more generic features, a first dictionary used to recognize the subjects, wherein the first dictionary is applied in an initial level of reconstruction of the signals; removing, using the at least one processor, the generic features from the plurality of signals to obtain one or more updated patterns for each subject; obtaining a set of discriminative features for each subject based on the updated patterns; and adding, based on the set of discriminative features, one or more second dictionaries used to recognize the subjects, wherein the one or more second dictionaries are applied at a level of reconstruction of the signals subsequent to the initial level. | 1. A method for signal processing, comprising: obtaining a plurality of signals related to a plurality of subjects; extracting, using at least one processor, one or more generic features of the subjects based on the signals; training, based on the one or more generic features, a first dictionary used to recognize the subjects, wherein the first dictionary is applied in an initial level of reconstruction of the signals; removing, using the at least one processor, the generic features from the plurality of signals to obtain one or more updated patterns for each subject; obtaining a set of discriminative features for each subject based on the updated patterns; and adding, based on the set of discriminative features, one or more second dictionaries used to recognize the subjects, wherein the one or more second dictionaries are applied at a level of reconstruction of the signals subsequent to the initial level. 3. The method of claim 1 , further comprising: training, based on the one or more generic features, another dictionary of the one or more second dictionaries used to recognize the subjects, wherein the other dictionary is applied at a level of reconstruction of the signals subsequent to the initial level but before a final level. | 0.656639 |
8,732,636 | 22 | 24 | 22. A computer program product comprising a non-transitory computer readable storage medium having a sequence of instructions stored thereupon which, when executed by a computer system, causes the computer system to perform a method for implementing multi-power domain digital or mixed-signal verification and low power simulation of an electronic circuit design, the method comprising: using the computer system which comprises at least one processor and is programmed for performing a process, the process comprising: identifying a first hierarchical level and a second hierarchical level in the hierarchical electronic circuit design; referencing a power data file, which includes power specific data for at least a portion of a transistor level netlist in a digital or mixed-signal block of the hierarchical electronic circuit design, to obtain a first connectivity information; determining or identifying power intent data or information, which includes data or information for power intent for the at least the portion of the transistor level netlist, in a schematic of the hierarchical electronic circuit design based at least in part upon one or more criteria to infer a second connectivity information for at least a part of the schematic; and performing schematic level verification or simulation by using at least the schematic modified by using at least some of the power intent data or information and the second connectivity information, instead of the transistor level netlist. | 22. A computer program product comprising a non-transitory computer readable storage medium having a sequence of instructions stored thereupon which, when executed by a computer system, causes the computer system to perform a method for implementing multi-power domain digital or mixed-signal verification and low power simulation of an electronic circuit design, the method comprising: using the computer system which comprises at least one processor and is programmed for performing a process, the process comprising: identifying a first hierarchical level and a second hierarchical level in the hierarchical electronic circuit design; referencing a power data file, which includes power specific data for at least a portion of a transistor level netlist in a digital or mixed-signal block of the hierarchical electronic circuit design, to obtain a first connectivity information; determining or identifying power intent data or information, which includes data or information for power intent for the at least the portion of the transistor level netlist, in a schematic of the hierarchical electronic circuit design based at least in part upon one or more criteria to infer a second connectivity information for at least a part of the schematic; and performing schematic level verification or simulation by using at least the schematic modified by using at least some of the power intent data or information and the second connectivity information, instead of the transistor level netlist. 24. The computer program product of claim 22 , wherein the act of referencing the power data file comprises: creating nets or the multiple power domains; and associating respective instances, ports, or pins with the nets or the multiple power domains. | 0.634111 |
6,014,428 | 5 | 8 | 5. The voice response system comprising: a first window field configured to accept a text entry representative of a desired voice prompt, wherein said text entry includes at least one word which is to be included in the voice prompt; a window activation field used to accept a user input which initiates a search that attempts to match said at least one word of said text entry with at least one word of an existing voice prompt; and a window output area configured to display at least a matching existing voice prompt portion. | 5. The voice response system comprising: a first window field configured to accept a text entry representative of a desired voice prompt, wherein said text entry includes at least one word which is to be included in the voice prompt; a window activation field used to accept a user input which initiates a search that attempts to match said at least one word of said text entry with at least one word of an existing voice prompt; and a window output area configured to display at least a matching existing voice prompt portion. 8. The voice response system as defined in claim 5, further comprising a display used to display said window. | 0.889452 |
9,606,987 | 1 | 4 | 1. A method, comprising: providing a developer interface for a developer account to define an internationalized sentence syntax to associate with an application on a social networking system that has multiple applications, the internationalized sentence syntax for rendering a natural language expression based on at least a social graph edge in a social graph of the social networking system on behalf of the application, wherein the social graph includes two or more social network nodes interconnected by one or more social graph edges; generating a token structure to define the internationalized sentence syntax, wherein the token structure includes a customizable language token to designate the internationalized sentence syntax as a language-specific syntax to translate into a preferred language indicated by the customizable language token, the token structure customizable via the developer interface to configure translation options of the internationalized sentence syntax; providing, via the social networking system, a sentence option on the developer interface for selection to define grammar of the internationalized sentence syntax, wherein defining the grammar includes inserting one or more tokens representing an actor, a target, an edge, or any combination thereof, into the token structure of the internationalized sentence syntax; associating a social graph attribute with a first token of the token structure; storing the sentence option and the token structure with the internationalized sentence syntax to facilitate run-time translation by the application of a natural language expression in a primary language into the natural language expression in the preferred language; and performing, by a computer system of the social networking system, application-specific run-time translation of a user activity from the primary language to the preferred language by configuring the application to express the user activity through the application according to the internationalized sentence syntax, wherein said performing the application-specific run-time translation includes fitting grammatical elements of the user activity according to the token structure associated with the application, further wherein the fitting is based on attributes indicated by the social graph. | 1. A method, comprising: providing a developer interface for a developer account to define an internationalized sentence syntax to associate with an application on a social networking system that has multiple applications, the internationalized sentence syntax for rendering a natural language expression based on at least a social graph edge in a social graph of the social networking system on behalf of the application, wherein the social graph includes two or more social network nodes interconnected by one or more social graph edges; generating a token structure to define the internationalized sentence syntax, wherein the token structure includes a customizable language token to designate the internationalized sentence syntax as a language-specific syntax to translate into a preferred language indicated by the customizable language token, the token structure customizable via the developer interface to configure translation options of the internationalized sentence syntax; providing, via the social networking system, a sentence option on the developer interface for selection to define grammar of the internationalized sentence syntax, wherein defining the grammar includes inserting one or more tokens representing an actor, a target, an edge, or any combination thereof, into the token structure of the internationalized sentence syntax; associating a social graph attribute with a first token of the token structure; storing the sentence option and the token structure with the internationalized sentence syntax to facilitate run-time translation by the application of a natural language expression in a primary language into the natural language expression in the preferred language; and performing, by a computer system of the social networking system, application-specific run-time translation of a user activity from the primary language to the preferred language by configuring the application to express the user activity through the application according to the internationalized sentence syntax, wherein said performing the application-specific run-time translation includes fitting grammatical elements of the user activity according to the token structure associated with the application, further wherein the fitting is based on attributes indicated by the social graph. 4. The method of claim 1 , wherein associating the social graph attribute includes associating a numeric attribute with the first token, the numeric attribute being whether a target or an actor of the internationalized sentence syntax is singular or plural. | 0.779588 |
8,762,365 | 15 | 19 | 15. A system, comprising: at least one computing device; and a network site classification engine in the at least one computing device, the network site classification engine comprising: logic that computes a plurality of similarities between a first plurality of search queries and individual ones of a second plurality of search queries, the first plurality of search queries returning an unclassified network site and the second plurality of search queries returning a plurality of classified network sites, individual ones of the classified network sites having a respective category, wherein the plurality of similarities are based at least on a query importance comprising a click through and the query importance is associated with a search query in the first plurality of search queries and the second plurality of search queries; and logic that classifies the unclassified network site into the respective category of one of the classified network sites based at least in part on the plurality of similarities. | 15. A system, comprising: at least one computing device; and a network site classification engine in the at least one computing device, the network site classification engine comprising: logic that computes a plurality of similarities between a first plurality of search queries and individual ones of a second plurality of search queries, the first plurality of search queries returning an unclassified network site and the second plurality of search queries returning a plurality of classified network sites, individual ones of the classified network sites having a respective category, wherein the plurality of similarities are based at least on a query importance comprising a click through and the query importance is associated with a search query in the first plurality of search queries and the second plurality of search queries; and logic that classifies the unclassified network site into the respective category of one of the classified network sites based at least in part on the plurality of similarities. 19. The system of claim 15 , wherein the computing of similarities uses vector space calculations. | 0.932692 |
9,275,272 | 1 | 18 | 1. A method comprising, by a computing device: receiving an image associated with an online social network, wherein the image portrays at least a first person; determining a social-graph affinity for one or more users of the online social network; determining, for each of the one or more users, a facial-recognition score with respect to the first person portrayed in the image, wherein the facial-recognition score is based at least in part on: the social-graph affinity determined for each user; and a facial-representation associated with each user, wherein the facial-representation associated with each user is compared with the image; sending, to a client system, one or more tag suggestions for the first person portrayed in the image based on the determined facial-recognition scores, wherein each tag suggestion corresponds to a particular user of the one or more users; and tagging the image with a particular user corresponding to a particular tag suggestion responsive to receiving a selection of the particular tag suggestion from the client system. | 1. A method comprising, by a computing device: receiving an image associated with an online social network, wherein the image portrays at least a first person; determining a social-graph affinity for one or more users of the online social network; determining, for each of the one or more users, a facial-recognition score with respect to the first person portrayed in the image, wherein the facial-recognition score is based at least in part on: the social-graph affinity determined for each user; and a facial-representation associated with each user, wherein the facial-representation associated with each user is compared with the image; sending, to a client system, one or more tag suggestions for the first person portrayed in the image based on the determined facial-recognition scores, wherein each tag suggestion corresponds to a particular user of the one or more users; and tagging the image with a particular user corresponding to a particular tag suggestion responsive to receiving a selection of the particular tag suggestion from the client system. 18. The method of claim 1 , wherein the social-graph affinity for each user is based at least in part on time-decay information associated with the image. | 0.825397 |
10,031,953 | 1 | 6 | 1. A non-transitory computer-readable medium storing instructions executable by one or more computers which, upon such execution, cause the one or more computers to perform operations comprising: receiving, at a server, a query identifying one or more attributes of an entity; accessing, at the server, a set of candidate templates for answering the query based on the one or more attributes of the entity, each candidate template having one or more fields, wherein each field is associated with at least one constraint; obtaining, at the server, a set of information that answers the query; selecting, at the server and from among the set of candidate templates, a template from which to generate a phrase that comprises an answer to the query, the selected template selected based on a determination that the selected template has a maximum number of fields with constraints that are satisfied by the set of information, in that no other template in the set of candidate templates has more fields with constraints that are satisfied by the set of information than the maximum number of fields of the selected template; generating, at the server, the phrase by adding the set of information to the one or more fields of the selected template, such that the phrase comprises an answer to the query; and communicating, from the server, the phrase to a client device. | 1. A non-transitory computer-readable medium storing instructions executable by one or more computers which, upon such execution, cause the one or more computers to perform operations comprising: receiving, at a server, a query identifying one or more attributes of an entity; accessing, at the server, a set of candidate templates for answering the query based on the one or more attributes of the entity, each candidate template having one or more fields, wherein each field is associated with at least one constraint; obtaining, at the server, a set of information that answers the query; selecting, at the server and from among the set of candidate templates, a template from which to generate a phrase that comprises an answer to the query, the selected template selected based on a determination that the selected template has a maximum number of fields with constraints that are satisfied by the set of information, in that no other template in the set of candidate templates has more fields with constraints that are satisfied by the set of information than the maximum number of fields of the selected template; generating, at the server, the phrase by adding the set of information to the one or more fields of the selected template, such that the phrase comprises an answer to the query; and communicating, from the server, the phrase to a client device. 6. The computer-readable medium of claim 1 , wherein receiving, at a server, a query identifying one or more attributes of an entity comprises receiving, at the server, a query identifying a plurality of attributes of an entity; wherein accessing, at the server, a set of candidate templates for answering the query based on the one or more attributes of the entity comprises accessing at the server, for each of the plurality of attributes of the entity, a set of candidate templates for answering the query based on the respective attribute of the entity; wherein obtaining, at the server, a set of information that answers the query comprises obtaining at the server, for each of the plurality of attributes of the entity, a set of information that answers a respective portion of the query; wherein selecting, at the server, the template from which to generate the phrase that comprises an answer to the query comprises selecting at the server, for each of the plurality of attributes of the entity, a template from the respective set of candidate templates; wherein generating, at the server, the phrase by adding the set of information to the one or more fields of the selected template, such that the phrase comprises an answer to the query comprises generating at the server, for each of the plurality of attributes of the entity, a phrase by adding the respective set of information to the one or more fields of the selected template; and wherein communicating, from the server, the phrase for output by a client device comprises communicating from the server, a sentence including the phrases to a client device, wherein the operations further comprise, obtaining, at the server, a sentence template based on a type of the entity, wherein the sentence template includes a plurality of fields for phrases; and adding the phrases to the fields of the sentence template to form the sentence. | 0.500263 |
8,086,697 | 1 | 7 | 1. A method comprising: (A) receiving, from a client computer, a request for an impression to be displayed in a placement of a web page, the request being made by the client computer as a result of said client computer receiving the web page; (B) receiving from the client computer a placement identifier particularly identifying a placement for the impression in the web page, the placement identifier having been embedded in the web page received at the client computer; (C) receiving behavioral data from the client computer, the behavioral data being indicative of client actions taken on multiple websites previously visited by the client computer and indicative of impressions previously received at the client computer; (D) determining a plurality of candidate impressions that may be displayed in the placement of the web page, based, at least in part, on the behavioral data; (E) determining a learning mode of each impression in the plurality of candidate impressions, the learning mode of each said impression being indicative of a number of times said each impression in the plurality of candidate impressions has been served to web pages in client computers on the Internet, wherein said learning mode is one of a plurality of learning modes, said plurality of learning modes comprising at least a first learning mode, a second learning mode, and a third learning mode, wherein, impressions that have been served less than a first predetermined threshold number of times are in said first learning mode, and wherein impressions that have been served more than said first predetermined number of times and less than a second predetermined threshold number of times are in said second learning mode, and wherein impressions that have been served more than a third predetermined threshold number of times are in a third learning mode, said second predetermined threshold being greater than said first predetermined threshold, and said third predetermined threshold being greater than said second predetermined threshold; (F) selecting a selected impression from the plurality of candidate impressions based at least in part on the learning mode of each of the impressions; and (G) serving the selected impression to the client computer, wherein selecting the selected impression from the plurality of candidate impressions in (F) comprises: (f1) if all impressions in the plurality of candidate impressions are in said first learning mode, then randomly selecting the selected impression from the plurality of candidate impressions; and (f2) if all impressions in the plurality of candidate impressions are in said second learning mode, then selecting a highest revenue generating impression in the plurality of candidate impressions as the selected impression; and (f3) if all of the impressions in the plurality of candidate impressions are in said third learning mode, then selecting a highest revenue generating impression in the plurality of candidate impressions as the selected impression; and (f4) if at least some impressions in the plurality of candidate impressions are in different learning modes, then selecting, as a final set of candidate impressions, impressions in the plurality of candidate impressions that are either; (i) all in the first learning mode, or (ii) all in the second learning mode, or (iii) all in the third learning mode, and then selecting the selected impression from the final set of candidate impressions. | 1. A method comprising: (A) receiving, from a client computer, a request for an impression to be displayed in a placement of a web page, the request being made by the client computer as a result of said client computer receiving the web page; (B) receiving from the client computer a placement identifier particularly identifying a placement for the impression in the web page, the placement identifier having been embedded in the web page received at the client computer; (C) receiving behavioral data from the client computer, the behavioral data being indicative of client actions taken on multiple websites previously visited by the client computer and indicative of impressions previously received at the client computer; (D) determining a plurality of candidate impressions that may be displayed in the placement of the web page, based, at least in part, on the behavioral data; (E) determining a learning mode of each impression in the plurality of candidate impressions, the learning mode of each said impression being indicative of a number of times said each impression in the plurality of candidate impressions has been served to web pages in client computers on the Internet, wherein said learning mode is one of a plurality of learning modes, said plurality of learning modes comprising at least a first learning mode, a second learning mode, and a third learning mode, wherein, impressions that have been served less than a first predetermined threshold number of times are in said first learning mode, and wherein impressions that have been served more than said first predetermined number of times and less than a second predetermined threshold number of times are in said second learning mode, and wherein impressions that have been served more than a third predetermined threshold number of times are in a third learning mode, said second predetermined threshold being greater than said first predetermined threshold, and said third predetermined threshold being greater than said second predetermined threshold; (F) selecting a selected impression from the plurality of candidate impressions based at least in part on the learning mode of each of the impressions; and (G) serving the selected impression to the client computer, wherein selecting the selected impression from the plurality of candidate impressions in (F) comprises: (f1) if all impressions in the plurality of candidate impressions are in said first learning mode, then randomly selecting the selected impression from the plurality of candidate impressions; and (f2) if all impressions in the plurality of candidate impressions are in said second learning mode, then selecting a highest revenue generating impression in the plurality of candidate impressions as the selected impression; and (f3) if all of the impressions in the plurality of candidate impressions are in said third learning mode, then selecting a highest revenue generating impression in the plurality of candidate impressions as the selected impression; and (f4) if at least some impressions in the plurality of candidate impressions are in different learning modes, then selecting, as a final set of candidate impressions, impressions in the plurality of candidate impressions that are either; (i) all in the first learning mode, or (ii) all in the second learning mode, or (iii) all in the third learning mode, and then selecting the selected impression from the final set of candidate impressions. 7. The method of claim 1 wherein: said first learning mode is a non-scaled learning mode; said second learning mode is a globally scaled learning mode; and said third learning mode is a fully scaled learning mode. | 0.812169 |
8,433,708 | 1 | 8 | 1. A non-transitory computer readable medium encoded with program instructions which are executed by a computer to provide a method of generating internal citations for a formatted document, the instructions comprising the steps of: a) obtaining graphic representations of each page of the formatted document, b) optically recognizing characters on each page of the formatted document, and determining the position of the characters on each page, c) obtaining a separate and distinct text version of the formatted document, d) parsing text from the text version, the parsed text being separate and distinct from the recognized characters, e) correlating the recognized characters with the parsed text to determine an internal citation for each sentence, wherein the internal citation identifies the document and a citation location inside the document where the corresponding sentence is found, wherein the citation location comprises one or more of: i) an internal citation page number; ii) an internal citation column number; iii) an internal citation line number; iv) an internal citation paragraph number; and v) an internal citation sentence number, and f) creating a data structure storing data determined in the correlating step. | 1. A non-transitory computer readable medium encoded with program instructions which are executed by a computer to provide a method of generating internal citations for a formatted document, the instructions comprising the steps of: a) obtaining graphic representations of each page of the formatted document, b) optically recognizing characters on each page of the formatted document, and determining the position of the characters on each page, c) obtaining a separate and distinct text version of the formatted document, d) parsing text from the text version, the parsed text being separate and distinct from the recognized characters, e) correlating the recognized characters with the parsed text to determine an internal citation for each sentence, wherein the internal citation identifies the document and a citation location inside the document where the corresponding sentence is found, wherein the citation location comprises one or more of: i) an internal citation page number; ii) an internal citation column number; iii) an internal citation line number; iv) an internal citation paragraph number; and v) an internal citation sentence number, and f) creating a data structure storing data determined in the correlating step. 8. The computer readable medium of claim 1 wherein the data structure comprises at least one of the group of: a) internal citation page number, b) internal citation paragraph number, and c) internal citation sentence number. | 0.764211 |
9,607,101 | 4 | 5 | 4. The medium of claim 3 , wherein the entity comprises one of a plurality of contact descriptors. | 4. The medium of claim 3 , wherein the entity comprises one of a plurality of contact descriptors. 5. The medium of claim 4 , the instructions causing additional operations comprising: performing a first search using a first search query generated using the first tokenized search suggestion; receiving an indication to change the default suggestion scope to a second suggestion scope; and displaying a graphical representation of an updated first tokenized search suggestion generated using the selected suggestion and the second suggestion scope. | 0.867708 |
8,326,605 | 1 | 10 | 1. A system comprising: a storage device storing first textual data, uncompressed second textual data, compressed third textual data, and a dictionary, the dictionary having a plurality of keys, each key associated with an identifier, the keys comprising: a plurality of static word or phrase keys, each static word or phrase key listing one or more unchanging words in a particular order; and, a plurality of dynamic phrase keys, each dynamic phrase key listing a plurality of words and one or more placeholders in a particular order, each placeholder denoting a place where a word or phrase other than the words of the dynamic phrase key is to be inserted; a dictionary-constructing mechanism to generate the dictionary from the first textual data; a compression mechanism to compress the uncompressed second textual data to yield the compressed third textual data using the dictionary; and, a decompression mechanism to decompress the compressed third textual data to yield the uncompressed second textual data using the dictionary. | 1. A system comprising: a storage device storing first textual data, uncompressed second textual data, compressed third textual data, and a dictionary, the dictionary having a plurality of keys, each key associated with an identifier, the keys comprising: a plurality of static word or phrase keys, each static word or phrase key listing one or more unchanging words in a particular order; and, a plurality of dynamic phrase keys, each dynamic phrase key listing a plurality of words and one or more placeholders in a particular order, each placeholder denoting a place where a word or phrase other than the words of the dynamic phrase key is to be inserted; a dictionary-constructing mechanism to generate the dictionary from the first textual data; a compression mechanism to compress the uncompressed second textual data to yield the compressed third textual data using the dictionary; and, a decompression mechanism to decompress the compressed third textual data to yield the uncompressed second textual data using the dictionary. 10. A system of claim 1 , wherein the compression mechanism to compress the uncompressed second textual data to yield the compressed third textual data using the dictionary comprises: receiving the dictionary, the dictionary having a plurality of keys, each key associated with an identifier, the keys comprising: a plurality of static word or phrase keys, each static word or phrase key listing one or more unchanging words in a particular order; and, a plurality of dynamic phrase keys, each dynamic phrase key listing a plurality of words and one or more placeholders in a particular order, each placeholder denoting a place where a word or phrase other than the words of the dynamic phrase key is to be inserted; wherein words and phrases within the textual data with the keys of the dictionary are matched and the words and phrases within the textual data that match the keys of the dictionary with the identifiers of the keys are replaced, and the textual data within which the words and phrases that match the keys have been replaced with the identifiers of the keys are stored on the storage device. | 0.508873 |
9,244,968 | 2 | 5 | 2. The method of claim 1 wherein step (d) is performed by analyzing a prevalence of selected content from said first electronic document within a first domain. | 2. The method of claim 1 wherein step (d) is performed by analyzing a prevalence of selected content from said first electronic document within a first domain. 5. The method of claim 2 wherein a rate of change of said prevalence is considered as well. | 0.961078 |
8,949,261 | 10 | 11 | 10. The system of claim 8 , wherein the third users are identified based at least in part on one or more second user attributes of the first user. | 10. The system of claim 8 , wherein the third users are identified based at least in part on one or more second user attributes of the first user. 11. The system of claim 10 , wherein a second user attribute is a user identifier and each user identifier is unique within the social-networking system. | 0.953888 |
8,244,719 | 9 | 10 | 9. Computer apparatus for social tagging, comprising: a data store holding social tagging data from system user inquiries; a tag previewer executable by a processor, the tag previewer being coupled to the data store and responsive to an end-user commencing input of a tag candidate, the end-user commencing input of the tag candidate and in response the tag previewer retrieving social tagging data about system user inquiries that have involved the tag candidate, wherein said social tagging data about system user inquiries include indications of how many and which system users have previously searched for the tag candidate and thus are interested in said tag candidate; during the end-user input of the tag candidate, the tag previewer forming a display of the retrieved social tagging data; and a display monitor coupled to receive the formed display and rendering the formed display to the end-user in a manner enabling a preview of the retrieved social tagging data during the end-user input of the tag candidate and prior to the end-user committing to the tag candidate; wherein the formed display includes indications to the end-user of: number of users who have inquired about the tag candidate, and how the users have inquired about the tag candidate; and wherein the formed display indications of how the users have inquired about the tag candidate includes indicating: names or numbers of users that have subscriptions to the tag candidate, names or numbers of users that have searched using the tag candidate and names or numbers of users that have browsed using the tag candidate. | 9. Computer apparatus for social tagging, comprising: a data store holding social tagging data from system user inquiries; a tag previewer executable by a processor, the tag previewer being coupled to the data store and responsive to an end-user commencing input of a tag candidate, the end-user commencing input of the tag candidate and in response the tag previewer retrieving social tagging data about system user inquiries that have involved the tag candidate, wherein said social tagging data about system user inquiries include indications of how many and which system users have previously searched for the tag candidate and thus are interested in said tag candidate; during the end-user input of the tag candidate, the tag previewer forming a display of the retrieved social tagging data; and a display monitor coupled to receive the formed display and rendering the formed display to the end-user in a manner enabling a preview of the retrieved social tagging data during the end-user input of the tag candidate and prior to the end-user committing to the tag candidate; wherein the formed display includes indications to the end-user of: number of users who have inquired about the tag candidate, and how the users have inquired about the tag candidate; and wherein the formed display indications of how the users have inquired about the tag candidate includes indicating: names or numbers of users that have subscriptions to the tag candidate, names or numbers of users that have searched using the tag candidate and names or numbers of users that have browsed using the tag candidate. 10. A computer method as claimed in claim 9 wherein the system user inquiries include browses, searches and subscription such that the data store holds social tagging data about browsed tags, searched tags and tags subscribed to. | 0.702597 |
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