sentence1
stringlengths 40
15.9k
| sentence2
stringlengths 88
20k
| label
float64 0.5
0.99
|
|---|---|---|
14. The computer program product of claim 13 , wherein the performing the vagueness question analysis further comprises: analyzing the question using natural language processing (NLP) that discovers the set of linguistic features pertaining to the question. | 14. The computer program product of claim 13 , wherein the performing the vagueness question analysis further comprises: analyzing the question using natural language processing (NLP) that discovers the set of linguistic features pertaining to the question. 15. The computer program product of claim 14 , further comprising: providing a set of feedback to a requestor of the question, wherein the set of feedback is based on one or more of the linguistic features discovered in the question. | 0.943519 |
1. A method comprising: identifying, by a computing device, a plurality of email templates, each email template corresponding to characteristics of a received machine-generated email, the characteristics of the received machine-generated email relating to static data of the machine-generated email; and generating, by the computing device, a template causality graph by analyzing the plurality of email templates to determine a statistical causality between templates of the plurality of email templates, the determining of the statistical causality between templates comprising determining that a first received machine-generated email associated with a first template is a result of a second received machine-generated email associated with a second template. | 1. A method comprising: identifying, by a computing device, a plurality of email templates, each email template corresponding to characteristics of a received machine-generated email, the characteristics of the received machine-generated email relating to static data of the machine-generated email; and generating, by the computing device, a template causality graph by analyzing the plurality of email templates to determine a statistical causality between templates of the plurality of email templates, the determining of the statistical causality between templates comprising determining that a first received machine-generated email associated with a first template is a result of a second received machine-generated email associated with a second template. 3. The method of claim 1 , further comprising determining an email template for each of the machine-generated emails. | 0.639754 |
8. A system, comprising: one or more computers; and a storage device coupled to the one or more computers having instructions stored thereon which, when executed by the one or more computers, cause the one or more computers to perform operations comprising: receiving a request for one or more advertisements, wherein the request includes a first term; determining a first location in a semantic space of the first term, wherein the semantic space has a plurality of nodes, each node being associated with a different respective term, and wherein each of the plurality of nodes has a bond with at least one other node in the semantic space, and wherein the bonds between the nodes are assigned respective strengths; determining a semantic distance between the first location in the semantic space of the first term and a second location in the semantic space of a second term associated with an advertisement, including evaluating bonds between a first node associated with the first term and a second node associated with the second term including evaluating a sum of strengths of the bonds between the first node and the second node; obtaining an original cost-per-impression amount provided by an advertiser for the second term associated with the advertisement; modifying the original cost-per-impression amount for the second term provided by the advertiser based on the semantic distance in the semantic space between the first term and the second term, wherein a greater semantic distance results in a lower cost-per-impression amount and wherein a smaller semantic distance results in a higher cost-per-impression amount; providing the advertisement in response to the request; and charging the advertiser the modified cost-per-impression amount for the second term instead of the original cost-per-impression amount provided by the advertiser. | 8. A system, comprising: one or more computers; and a storage device coupled to the one or more computers having instructions stored thereon which, when executed by the one or more computers, cause the one or more computers to perform operations comprising: receiving a request for one or more advertisements, wherein the request includes a first term; determining a first location in a semantic space of the first term, wherein the semantic space has a plurality of nodes, each node being associated with a different respective term, and wherein each of the plurality of nodes has a bond with at least one other node in the semantic space, and wherein the bonds between the nodes are assigned respective strengths; determining a semantic distance between the first location in the semantic space of the first term and a second location in the semantic space of a second term associated with an advertisement, including evaluating bonds between a first node associated with the first term and a second node associated with the second term including evaluating a sum of strengths of the bonds between the first node and the second node; obtaining an original cost-per-impression amount provided by an advertiser for the second term associated with the advertisement; modifying the original cost-per-impression amount for the second term provided by the advertiser based on the semantic distance in the semantic space between the first term and the second term, wherein a greater semantic distance results in a lower cost-per-impression amount and wherein a smaller semantic distance results in a higher cost-per-impression amount; providing the advertisement in response to the request; and charging the advertiser the modified cost-per-impression amount for the second term instead of the original cost-per-impression amount provided by the advertiser. 10. The system of claim 8 , wherein the operations further comprise: traversing multiple bonds in the semantic space between the first node associated with the first term and the second node associated with the second term, wherein the semantic distance is based on respective strengths of bonds traversed between the first node and the second node. | 0.506319 |
21. The apparatus of claim 16 , wherein the website resource selection unit is further configured to determine the plurality of context values associated with the request, including the particular context value, wherein the particular context value identifies an input value received by a server of the referral website from the requesting computing device. | 21. The apparatus of claim 16 , wherein the website resource selection unit is further configured to determine the plurality of context values associated with the request, including the particular context value, wherein the particular context value identifies an input value received by a server of the referral website from the requesting computing device. 23. The apparatus of claim 21 , wherein the input value identifies an item of the referral website selected by the requesting computing device. | 0.892056 |
18. A method comprising: storing a social graph, the social graph comprising a plurality of graph objects and a plurality of graph actions, each graph action having an action type from a plurality of predefined action types and representing a relationship between two or more graph objects; receiving from a third party entity separate from a social networking system a definition of a new action type; responsive to the received definition, adding the new action type to the plurality of predefined action types for use by the social networking system to capture user interactions with graph objects; requesting content from a system outside the social networking system for rendering on a user device, wherein the system hosts the content on a domain separate from the social networking system; receiving the requested content and an executable widget including a first instruction to authenticate the user device with the social networking system; rendering the requested content on the user device, wherein the user device enables a user to interact with the requested content on the system outside the social networking system; executing the widget on the user device, the widget including a second instruction to record a user interaction within the requested content responsive to detecting the user interaction; receiving an authentication of the user from the social networking system, the authentication including a user identifier of the user; detecting the user interaction with the requested content on the user device, the user interaction comprising a graph action performed on the system outside the social networking system, the graph action having an action type and a graph object having an object type; accessing information from the system outside the social networking system to record the graph object and the graph action associated with the user in the social networking system in real-time, the system outside the social networking system providing the information comprising the graph object and the graph action parameterized according to the corresponding object type and the corresponding action type in an action loci generated by the widget; and recording the user interaction as an entry including the graph object corresponding to the object type, the graph action corresponding to the action type, the user identifier of the user performing the user interaction on the system outside the social networking system, and contextual information related to the graph action and the graph object, wherein the recorded graph action in the social graph has the new action type. | 18. A method comprising: storing a social graph, the social graph comprising a plurality of graph objects and a plurality of graph actions, each graph action having an action type from a plurality of predefined action types and representing a relationship between two or more graph objects; receiving from a third party entity separate from a social networking system a definition of a new action type; responsive to the received definition, adding the new action type to the plurality of predefined action types for use by the social networking system to capture user interactions with graph objects; requesting content from a system outside the social networking system for rendering on a user device, wherein the system hosts the content on a domain separate from the social networking system; receiving the requested content and an executable widget including a first instruction to authenticate the user device with the social networking system; rendering the requested content on the user device, wherein the user device enables a user to interact with the requested content on the system outside the social networking system; executing the widget on the user device, the widget including a second instruction to record a user interaction within the requested content responsive to detecting the user interaction; receiving an authentication of the user from the social networking system, the authentication including a user identifier of the user; detecting the user interaction with the requested content on the user device, the user interaction comprising a graph action performed on the system outside the social networking system, the graph action having an action type and a graph object having an object type; accessing information from the system outside the social networking system to record the graph object and the graph action associated with the user in the social networking system in real-time, the system outside the social networking system providing the information comprising the graph object and the graph action parameterized according to the corresponding object type and the corresponding action type in an action loci generated by the widget; and recording the user interaction as an entry including the graph object corresponding to the object type, the graph action corresponding to the action type, the user identifier of the user performing the user interaction on the system outside the social networking system, and contextual information related to the graph action and the graph object, wherein the recorded graph action in the social graph has the new action type. 22. The method of claim 18 , further comprising: communicating the entry to the social networking system. | 0.564585 |
17. The processor-implemented method of claim 1 , wherein ranking the identified results based on a plurality of pre-defined conditions is performed using a sub-process comprising: providing by the processor hierarchy levels to the identified at least one result based on the context through which the result is identified; providing by the processor hierarchy levels to the identified at least one result in which at least one search term appears in the subject line, wherein the at least one result is an e-mail; providing by the processor hierarchy levels to the identified at least one result in which at least one search term appears in a pre-determined range of characters in a body of the at least one result, wherein the at least one result is an e-mail; providing by the processor hierarchy levels to the identified at least one result in which at least one search term appears in the body other than the subject line, the pre-determined range of characters, attachment name and attachment, wherein the at least one result is an e-mail; providing by the processor hierarchy levels to the identified at least one result in which at least one search term appears in a pre-defined format within the content of the attachment; providing by the processor hierarchy levels to the identified at least one result wherein the at least one result is a commercial e-mail; providing by the processor hierarchy levels to the identified at least one result wherein the at least one result is a low-priority e-mail; providing by the processor hierarchy levels to the identified at least one result based on the date of the at least one result; and ranking the e-mails based on the provided hierarchy levels. | 17. The processor-implemented method of claim 1 , wherein ranking the identified results based on a plurality of pre-defined conditions is performed using a sub-process comprising: providing by the processor hierarchy levels to the identified at least one result based on the context through which the result is identified; providing by the processor hierarchy levels to the identified at least one result in which at least one search term appears in the subject line, wherein the at least one result is an e-mail; providing by the processor hierarchy levels to the identified at least one result in which at least one search term appears in a pre-determined range of characters in a body of the at least one result, wherein the at least one result is an e-mail; providing by the processor hierarchy levels to the identified at least one result in which at least one search term appears in the body other than the subject line, the pre-determined range of characters, attachment name and attachment, wherein the at least one result is an e-mail; providing by the processor hierarchy levels to the identified at least one result in which at least one search term appears in a pre-defined format within the content of the attachment; providing by the processor hierarchy levels to the identified at least one result wherein the at least one result is a commercial e-mail; providing by the processor hierarchy levels to the identified at least one result wherein the at least one result is a low-priority e-mail; providing by the processor hierarchy levels to the identified at least one result based on the date of the at least one result; and ranking the e-mails based on the provided hierarchy levels. 20. The processor-implemented method of claim 17 , wherein presenting the results comprises highlighting the at least one search term. | 0.641884 |
17. The at least one hardware computer-readable storage medium of claim 15 where the grouping results in a group that contains the some of the various windows. | 17. The at least one hardware computer-readable storage medium of claim 15 where the grouping results in a group that contains the some of the various windows. 18. The at least one hardware computer-readable storage medium of claim 17 where the windows in the group are related to each other by at least a portion of the switches. | 0.888833 |
1. A computer-implemented method for identifying a regulatory interaction between a transcription factor and a gene target of said transcription factor, the method comprising: a) providing a compendium of biochemical expression measurements reflecting gene expression for a set of biochemical species in an organism wherein at least a subset of said species are transcription factors and a second subset of said species are gene targets of transcription factors; b) in a specifically programmed computer, computing mutual information between members of said set of biochemical species; c) in a specifically programmed computer, applying a background correction to each said mutual information value so as to identify a set of those mutual information values that are significantly higher than background mutual information values, wherein the step of applying a background correction comprises the step of estimating a likelihood of the mutual information score, MI, for each possible pair of genes, by comparing the mutual information score for that pair to a background distribution of mutual information values, and wherein said set of mutual information values identified in step (c) identifies a regulatory interaction between a transcription factor and a gene target of said transcription factor; and d) outputting the identified regulatory interaction to a user interface. | 1. A computer-implemented method for identifying a regulatory interaction between a transcription factor and a gene target of said transcription factor, the method comprising: a) providing a compendium of biochemical expression measurements reflecting gene expression for a set of biochemical species in an organism wherein at least a subset of said species are transcription factors and a second subset of said species are gene targets of transcription factors; b) in a specifically programmed computer, computing mutual information between members of said set of biochemical species; c) in a specifically programmed computer, applying a background correction to each said mutual information value so as to identify a set of those mutual information values that are significantly higher than background mutual information values, wherein the step of applying a background correction comprises the step of estimating a likelihood of the mutual information score, MI, for each possible pair of genes, by comparing the mutual information score for that pair to a background distribution of mutual information values, and wherein said set of mutual information values identified in step (c) identifies a regulatory interaction between a transcription factor and a gene target of said transcription factor; and d) outputting the identified regulatory interaction to a user interface. 27. The method of claim 1 further comprising the step, after step (c), of confirming a physical interaction of a said transcription factor with a said gene target. | 0.64461 |
42. A non-transitory computer readable storage medium storing instructions for processing video data that upon execution by one or more processors cause the one or more processors to: receive a coded video sequence comprising encoded pictures of a video sequence; receive timing parameters for the coded video sequence that include a condition for signaling a number of clock ticks corresponding to a difference of picture order count (POC) values equal to 1 directly in at least one of a video parameter set (VPS) syntax structure referenced by the coded video sequence and a sequence parameter set (SPS) syntax structure referenced by the coded video sequence; and process the coded video sequence according to the timing parameters. | 42. A non-transitory computer readable storage medium storing instructions for processing video data that upon execution by one or more processors cause the one or more processors to: receive a coded video sequence comprising encoded pictures of a video sequence; receive timing parameters for the coded video sequence that include a condition for signaling a number of clock ticks corresponding to a difference of picture order count (POC) values equal to 1 directly in at least one of a video parameter set (VPS) syntax structure referenced by the coded video sequence and a sequence parameter set (SPS) syntax structure referenced by the coded video sequence; and process the coded video sequence according to the timing parameters. 45. The non-transitory computer readable storage medium of claim 42 , wherein the timing parameters comprise timing parameters for hypothetical reference decoding operations. | 0.648981 |
21. A method for training the Mandarin dictation machine to be adapted to a voice and an environment of a user, comprising using a plurality of learning algorithms comprising: a first learning algorithm; a second learning algorithm; a third learning algorithm; and a fourth learning algorithm, wherein (1) the first learning algorithm is automatic learning of a user's voice through "learning sentences" arranged in a plurality of learning stages; (2) the second learning algorithm is automatic "on-line" real-time learning for the user's voice, and the second learning algorithm can be used in conjunction with the first learning algorithm; (3) the third learning algorithm is automatic learning for environmental noise; and (4) the fourth learning algorithm is automatic learning for special words, a wording and a sentence style of the user, wherein: input to the Mandarin dictation machine is in a form comprising continuous speech, the fourth learning algorithm dynamically adjusts statistical parameters and linguistic knowledge in "Chinese Language Models" and can add new words to a global dictionary, while the fourth learning algorithm stores the wording and idioms of the user or the special words which have a plurality of occurrences in a certain input text in a dynamic memory device which will be accessed in first priority, and the wording, the idioms or the special words are stored in different memory areas in accordance with occurrence frequencies of the wording, the idioms or the special words, the "Chinese Language Models" are generated by combining statistical information, resulting from an analysis of probabilities of associativity among "characters", "words" and "word classes" of a Chinese language, with the linguistic knowledge or rules obtained from an analysis of parts-of-speech, syntax and semantics of the Chinese language. | 21. A method for training the Mandarin dictation machine to be adapted to a voice and an environment of a user, comprising using a plurality of learning algorithms comprising: a first learning algorithm; a second learning algorithm; a third learning algorithm; and a fourth learning algorithm, wherein (1) the first learning algorithm is automatic learning of a user's voice through "learning sentences" arranged in a plurality of learning stages; (2) the second learning algorithm is automatic "on-line" real-time learning for the user's voice, and the second learning algorithm can be used in conjunction with the first learning algorithm; (3) the third learning algorithm is automatic learning for environmental noise; and (4) the fourth learning algorithm is automatic learning for special words, a wording and a sentence style of the user, wherein: input to the Mandarin dictation machine is in a form comprising continuous speech, the fourth learning algorithm dynamically adjusts statistical parameters and linguistic knowledge in "Chinese Language Models" and can add new words to a global dictionary, while the fourth learning algorithm stores the wording and idioms of the user or the special words which have a plurality of occurrences in a certain input text in a dynamic memory device which will be accessed in first priority, and the wording, the idioms or the special words are stored in different memory areas in accordance with occurrence frequencies of the wording, the idioms or the special words, the "Chinese Language Models" are generated by combining statistical information, resulting from an analysis of probabilities of associativity among "characters", "words" and "word classes" of a Chinese language, with the linguistic knowledge or rules obtained from an analysis of parts-of-speech, syntax and semantics of the Chinese language. 22. A method as claimed in claim 21, wherien in each of the plurlaity of learning stages of the automatic learning algorithm a new user shall utter a set of specially-designed sentences which include all basic acoustic units of Mandarin speech, including a sub-syllable unit, a phoneme, an "initial", a "final", a mono-syllable, and a tone, in a number of sentences in which certain ones of acoustic units will be present at least a given number of times so that after several utterances a "Hidden Markov Models" can be trained and the Mandarin dictation machine will be adapted to pronouncing styles of the new user; the pronouncing styles of the new user are recorded, the Mandarin dictation machine learning the pronouncing styles of the new user when the new user repeatedly utters the specially-designed sentences, wherein with a different emphasis of the basic acoustic units arranged in the "learning sentences" of each learning stage, a correct recognition rate for recognizing a voice of the new user can be improved in such a manner that a plurality of basic acoustic units are uttered through the number of sentences in the first learning stage; said Mandarin dictation machine will learn the voice of the new user and the correct recognition rate will be improved in successive learning stages. | 0.5 |
14. A non-transitory machine-readable medium comprising instructions that when executed by a data processing device, cause the data processing device to: receive workflow input files comprising workflow files and business process definition file; create a workflow page repository storing workflow pages and metadata for each workflow page including a workflow page description describing one or more steps performed by each workflow page, wherein each workflow page includes reusable code that performs the one or more steps of the workflow page; parse the workflow input files to determine a plurality of feature functionalities of a workflow-based application being generated, and to determine one or more processing steps for each feature functionality; create workflow configuration rules including the plurality of feature functionalities of the workflow-based application being generated, and including the one or more processing steps for each feature functionality, wherein creating the workflow configuration rules further includes defining and editing, by input received via a user interface, at least one of the workflow configuration rules; create routing configuration rules including an order for executing the feature functionalities and dependencies for the feature functionalities; for each feature functionality in the workflow configuration rules, search the workflow page descriptions in the workflow page repository based on the steps for the feature functionality in the workflow configuration rules; identify matching workflow pages from the searching of the workflow page repository for each feature functionality; build workflow pages for any of the feature functionalities that do not have a matching workflow page, and storing the built workflow pages in the workflow page repository; include workflow page identifiers for the matching workflow pages and the built workflow pages in the workflow configuration rules; include an order of executing the matching and built workflow pages and input and output requirements of each of the matching and built workflow pages in the routing configuration rules; generate a workflow context according to the workflow configuration rules, the routing configuration rules, and the matching, built workflow pages, wherein generating the workflow context includes: retrieve a workflow page template; and aggregate the workflow configuration rules, the routing workflow rules, the matching, built workflow pages, and the retrieved workflow page template into the generated workflow context; and generate the workflow-based application based upon the workflow context. | 14. A non-transitory machine-readable medium comprising instructions that when executed by a data processing device, cause the data processing device to: receive workflow input files comprising workflow files and business process definition file; create a workflow page repository storing workflow pages and metadata for each workflow page including a workflow page description describing one or more steps performed by each workflow page, wherein each workflow page includes reusable code that performs the one or more steps of the workflow page; parse the workflow input files to determine a plurality of feature functionalities of a workflow-based application being generated, and to determine one or more processing steps for each feature functionality; create workflow configuration rules including the plurality of feature functionalities of the workflow-based application being generated, and including the one or more processing steps for each feature functionality, wherein creating the workflow configuration rules further includes defining and editing, by input received via a user interface, at least one of the workflow configuration rules; create routing configuration rules including an order for executing the feature functionalities and dependencies for the feature functionalities; for each feature functionality in the workflow configuration rules, search the workflow page descriptions in the workflow page repository based on the steps for the feature functionality in the workflow configuration rules; identify matching workflow pages from the searching of the workflow page repository for each feature functionality; build workflow pages for any of the feature functionalities that do not have a matching workflow page, and storing the built workflow pages in the workflow page repository; include workflow page identifiers for the matching workflow pages and the built workflow pages in the workflow configuration rules; include an order of executing the matching and built workflow pages and input and output requirements of each of the matching and built workflow pages in the routing configuration rules; generate a workflow context according to the workflow configuration rules, the routing configuration rules, and the matching, built workflow pages, wherein generating the workflow context includes: retrieve a workflow page template; and aggregate the workflow configuration rules, the routing workflow rules, the matching, built workflow pages, and the retrieved workflow page template into the generated workflow context; and generate the workflow-based application based upon the workflow context. 15. The non-transitory machine-readable medium of claim 14 , wherein to generate the workflow-based application, said instructions are further to cause the data processing device to: select a target platform configuration; generate the workflow-based application using the workflow context and the selected target platform configuration; and build a deployment package using the generated workflow-based application. | 0.512873 |
10. The integration server of claim 9 , wherein the data structure further comprises: at least one complex data element. | 10. The integration server of claim 9 , wherein the data structure further comprises: at least one complex data element. 11. The integration server of claim 10 , wherein the data structure further comprises: one or more related data elements selected from the group consisting of a related party data element, a related payment method data element, a related payment terms data element, and a related comments data element. | 0.924063 |
3. The computer-implemented method of claim 2 , the generating the second summary comprising: receiving a search query; identifying the document as pertaining to the search query; determining that no summaries indicative of the document are available; and generating the second summary upon determining that no summaries indicative of the document are available. | 3. The computer-implemented method of claim 2 , the generating the second summary comprising: receiving a search query; identifying the document as pertaining to the search query; determining that no summaries indicative of the document are available; and generating the second summary upon determining that no summaries indicative of the document are available. 4. The computer-implemented method of claim 3 , the first summary generated after the second summary. | 0.872584 |
1. An integrated circuit chip comprising programmable intelligent search memory for content search wherein said programmable intelligent search memory performs regular expression based search and signature pattern based search, said programmable intelligent search memory using a plurality of regular expressions and a plurality of signature patterns, and said programmable intelligent search memory comprising a plurality of programmable FSA rule search engines to perform search using a plurality of regular expressions and further comprising one or more programmable signature search engines to perform content search using a plurality of signature patterns, said plurality of regular expressions comprising a plurality of symbols or characters, said plurality of regular expressions converted into a plurality of finite state automata representing the functionality of the said plurality of regular expressions for programming in the said programmable FSA rule search engines, said plurality of finite state automata comprising a plurality of states, said plurality of states derived from the said plurality of symbols or characters of said plurality of regular expressions, said content comprising a plurality of input symbols or characters provided as input to the said programmable intelligent search memory, said plurality of programmable FSA rule search engines comprising at least one of each of: a. a symbol memory circuit to store said plurality of symbols; b. a symbol evaluation circuit coupled to the said symbol memory circuit to evaluate match of the said plurality of symbols stored in the said symbol memory circuit with said plurality of input symbols of said content; c. a state dependent vector (SDV) memory circuit to store state transition controls for said plurality of finite state automata; d. a current state vector (CSV) memory circuit to store said plurality of states; and e. a state transition circuit coupled to the said symbol evaluation circuit, current state vector memory circuit and said state dependent vector memory circuit to perform state transition from one or more first states to one or more second states of said plurality of states of said plurality of finite state automata. | 1. An integrated circuit chip comprising programmable intelligent search memory for content search wherein said programmable intelligent search memory performs regular expression based search and signature pattern based search, said programmable intelligent search memory using a plurality of regular expressions and a plurality of signature patterns, and said programmable intelligent search memory comprising a plurality of programmable FSA rule search engines to perform search using a plurality of regular expressions and further comprising one or more programmable signature search engines to perform content search using a plurality of signature patterns, said plurality of regular expressions comprising a plurality of symbols or characters, said plurality of regular expressions converted into a plurality of finite state automata representing the functionality of the said plurality of regular expressions for programming in the said programmable FSA rule search engines, said plurality of finite state automata comprising a plurality of states, said plurality of states derived from the said plurality of symbols or characters of said plurality of regular expressions, said content comprising a plurality of input symbols or characters provided as input to the said programmable intelligent search memory, said plurality of programmable FSA rule search engines comprising at least one of each of: a. a symbol memory circuit to store said plurality of symbols; b. a symbol evaluation circuit coupled to the said symbol memory circuit to evaluate match of the said plurality of symbols stored in the said symbol memory circuit with said plurality of input symbols of said content; c. a state dependent vector (SDV) memory circuit to store state transition controls for said plurality of finite state automata; d. a current state vector (CSV) memory circuit to store said plurality of states; and e. a state transition circuit coupled to the said symbol evaluation circuit, current state vector memory circuit and said state dependent vector memory circuit to perform state transition from one or more first states to one or more second states of said plurality of states of said plurality of finite state automata. 3. The integrated circuit chip of claim 1 , coupled to a programmable intelligent search memory (PRISM) compiler for the programmable intelligent search memory for compiling content search rules comprising a plurality of regular expression rules and a plurality of signature pattern rules for content search wherein said programmable intelligent search memory performs regular expression based and signature pattern based search. | 0.697249 |
11. A method of performing XBRL extension taxonomy concept replacement comprising: analyzing, by a computer processor, an XBRL document having XBRL tags to identify an XBRL extension taxonomy concept of an XBRL extension taxonomy that is superfluous compared to an XBRL base taxonomy concept of an XBRL base taxonomy; and replacing, by a computer processor, the identified XBRL extension taxonomy concept in the XBRL document with the compared XBRL base taxonomy concept, wherein the identified XBRL extension taxonomy concept has an edit distance of at least one and less than a threshold compared with corresponding information of the compared XBRL base taxonomy concept. | 11. A method of performing XBRL extension taxonomy concept replacement comprising: analyzing, by a computer processor, an XBRL document having XBRL tags to identify an XBRL extension taxonomy concept of an XBRL extension taxonomy that is superfluous compared to an XBRL base taxonomy concept of an XBRL base taxonomy; and replacing, by a computer processor, the identified XBRL extension taxonomy concept in the XBRL document with the compared XBRL base taxonomy concept, wherein the identified XBRL extension taxonomy concept has an edit distance of at least one and less than a threshold compared with corresponding information of the compared XBRL base taxonomy concept. 12. The method of claim 11 , further comprising presenting information of the identified XBRL extension taxonomy concept and corresponding information of the compared XBRL base taxonomy concept to a user and receiving an instruction to perform the replacement of the identified XBRL extension taxonomy concept with the compared XBRL base taxonomy concept in the XBRL document in response to the presenting of the information. | 0.726018 |
1. A method comprising: a) receiving, at a computer, a first set of input data comprising a set of website data; b) defining a grammar, wherein: i) the grammar comprises a plurality of sub-grammars organized according to a hierarchy comprising a plurality of levels; ii) the grammar is defined based on data comprising: 1) the first set of input data; 2) a second set of input data; and 3) a third set of input data; iii) the statements |A B|−|A∩B|≠0 and B C=A C are true where 1) A is a first set of levels from the hierarchy in which at least one sub-grammar is defined based on the first set of input data; 2) B is a second set of levels from the hierarchy in which at least one sub-grammar is defined based on the second set of input data; and 3) C is a third set of levels from the hierarchy in which at least one sub-grammar is defined based on the third set of input data; and c) storing the grammar on a non-transitory computer readable medium. | 1. A method comprising: a) receiving, at a computer, a first set of input data comprising a set of website data; b) defining a grammar, wherein: i) the grammar comprises a plurality of sub-grammars organized according to a hierarchy comprising a plurality of levels; ii) the grammar is defined based on data comprising: 1) the first set of input data; 2) a second set of input data; and 3) a third set of input data; iii) the statements |A B|−|A∩B|≠0 and B C=A C are true where 1) A is a first set of levels from the hierarchy in which at least one sub-grammar is defined based on the first set of input data; 2) B is a second set of levels from the hierarchy in which at least one sub-grammar is defined based on the second set of input data; and 3) C is a third set of levels from the hierarchy in which at least one sub-grammar is defined based on the third set of input data; and c) storing the grammar on a non-transitory computer readable medium. 3. The method of claim 1 wherein the statements A B≠B and A B≠A are true. | 0.887195 |
6. A system comprising: a hardware processor; a data bus coupled to the processor; and a computer-usable medium embodying computer program code, the computer-usable medium being coupled to the data bus, the computer program code used for generating a security analysis effort, cost and process scope estimates within a security intelligence environment, the security intelligence environment comprising a plurality of data sources and a security intelligence platform, the security intelligence platform comprising a security analysis estimation module, the security analysis estimation module executing on a processor of a computer system and comprising instructions executable by the processor and configured for: analyzing a software system, the analyzing the software system utilizing information received from at least one of the plurality of data sources; identifying a complexity level of a security analysis, the complexity level of the security analysis comprising identification of an effort level for the security analysis, the complexity level of the security analysis comprising identification of an effort level for the security analysis, the identifying comprising performing a security analysis estimation operation, the security analysis estimation operation comprising a dynamic analysis performed via a dynamic analysis scanning subsystem and a static analysis performed via a static analysis tool; and, generating the security analysis effort estimate, the security analysis effort estimate comprising an estimate of an effort expenditure to perform a security analysis on the software system at the identified complexity level, the security analysis estimation module providing a quantitative machine learning based analytics driven determination, the quantitative machine learning based analytics driven determination providing an estimation of parameters and correlation of coefficients which can drive price and cost factors for the software security vulnerabilities identification operation. | 6. A system comprising: a hardware processor; a data bus coupled to the processor; and a computer-usable medium embodying computer program code, the computer-usable medium being coupled to the data bus, the computer program code used for generating a security analysis effort, cost and process scope estimates within a security intelligence environment, the security intelligence environment comprising a plurality of data sources and a security intelligence platform, the security intelligence platform comprising a security analysis estimation module, the security analysis estimation module executing on a processor of a computer system and comprising instructions executable by the processor and configured for: analyzing a software system, the analyzing the software system utilizing information received from at least one of the plurality of data sources; identifying a complexity level of a security analysis, the complexity level of the security analysis comprising identification of an effort level for the security analysis, the complexity level of the security analysis comprising identification of an effort level for the security analysis, the identifying comprising performing a security analysis estimation operation, the security analysis estimation operation comprising a dynamic analysis performed via a dynamic analysis scanning subsystem and a static analysis performed via a static analysis tool; and, generating the security analysis effort estimate, the security analysis effort estimate comprising an estimate of an effort expenditure to perform a security analysis on the software system at the identified complexity level, the security analysis estimation module providing a quantitative machine learning based analytics driven determination, the quantitative machine learning based analytics driven determination providing an estimation of parameters and correlation of coefficients which can drive price and cost factors for the software security vulnerabilities identification operation. 7. The system of claim 6 , wherein: the security analysis comprises a software security vulnerabilities identification operation. | 0.541109 |
16. A system, comprising: one or more processors; and memory storing instructions that when executed by the one or more processors cause the one or more processors to effectuate operations comprising: receiving a query from a user via a user device; identifying a geographic area and a category of businesses for the query; identifying, using reviews related to the geographic area and the category of business from a plurality of users, a plurality of experts within the plurality of users based at least on respective numbers of reviews each user submitted, including iteratively modifying the category of business to identify at least a threshold number of experts; ranking local search results responsive to the query based on the expert's respective reviews of the local search results by the plurality of experts; and causing the ranked local search results to be displayed via the user device. | 16. A system, comprising: one or more processors; and memory storing instructions that when executed by the one or more processors cause the one or more processors to effectuate operations comprising: receiving a query from a user via a user device; identifying a geographic area and a category of businesses for the query; identifying, using reviews related to the geographic area and the category of business from a plurality of users, a plurality of experts within the plurality of users based at least on respective numbers of reviews each user submitted, including iteratively modifying the category of business to identify at least a threshold number of experts; ranking local search results responsive to the query based on the expert's respective reviews of the local search results by the plurality of experts; and causing the ranked local search results to be displayed via the user device. 17. The system of claim 16 , the operations further comprising: increasing the geographic area or to a hierarchically higher geographic area to identify at least the threshold number of experts. | 0.579792 |
1. A computer program product comprising a non-transitory computer readable storage medium having a computer readable program stored therein, wherein the computer readable program, when executed on a computing device, causes the computing device to: automatically track language based user activities occurring via the computing device to at least one other computing device via a communication connection; automatically analyze the language based user activities to determine a relative priority ordering of one or more languages used by a user performing the user activities; automatically generate a sequence of preferred language translation substitutions for outputting messages based on results of the analysis, wherein the sequence comprises two or more preferred language translation substitutions for outputting the messages; automatically apply the sequence to a received message from a process associated with the computing device to generate a translated message using one of the preferred language translation substitutions in the sequence of preferred language translation substitutions, wherein the sequence is automatically applied to the received message from the process by overriding a user defined sequence of preferred translation substitutions and giving priority to the automatically sequence and wherein the computer readable program to automatically apply the sequence to the received message further causes the computing device to: traverse, in a sequence order, the preferred language translation substitutions of the sequence; for each preferred language translation substitution in the sequence order: determine whether a source of the received message has a translation catalog file corresponding to the first preferred language translation substitution in the sequence order, wherein each translation catalog file comprises a translation in an associated language; responsive to a failure of the source of the received message having the translation catalog file corresponding to the first preferred language translation substitution in the sequence order, determine whether the source of the received message has a translation catalog file corresponding to the next preferred language translation substitution in the sequence order; and responsive to the source of the received message having the translation catalog file corresponding to the next preferred language translation substitution in the sequence order, select the next preferred language translation substitution as a preferred language translation substitution to use in generating the translated message; and generate the translated message using the selected preferred language translation substitution to translate the received message into a different language from a language in which the received message is received; and output the translated message via an output device of the computing device. | 1. A computer program product comprising a non-transitory computer readable storage medium having a computer readable program stored therein, wherein the computer readable program, when executed on a computing device, causes the computing device to: automatically track language based user activities occurring via the computing device to at least one other computing device via a communication connection; automatically analyze the language based user activities to determine a relative priority ordering of one or more languages used by a user performing the user activities; automatically generate a sequence of preferred language translation substitutions for outputting messages based on results of the analysis, wherein the sequence comprises two or more preferred language translation substitutions for outputting the messages; automatically apply the sequence to a received message from a process associated with the computing device to generate a translated message using one of the preferred language translation substitutions in the sequence of preferred language translation substitutions, wherein the sequence is automatically applied to the received message from the process by overriding a user defined sequence of preferred translation substitutions and giving priority to the automatically sequence and wherein the computer readable program to automatically apply the sequence to the received message further causes the computing device to: traverse, in a sequence order, the preferred language translation substitutions of the sequence; for each preferred language translation substitution in the sequence order: determine whether a source of the received message has a translation catalog file corresponding to the first preferred language translation substitution in the sequence order, wherein each translation catalog file comprises a translation in an associated language; responsive to a failure of the source of the received message having the translation catalog file corresponding to the first preferred language translation substitution in the sequence order, determine whether the source of the received message has a translation catalog file corresponding to the next preferred language translation substitution in the sequence order; and responsive to the source of the received message having the translation catalog file corresponding to the next preferred language translation substitution in the sequence order, select the next preferred language translation substitution as a preferred language translation substitution to use in generating the translated message; and generate the translated message using the selected preferred language translation substitution to translate the received message into a different language from a language in which the received message is received; and output the translated message via an output device of the computing device. 6. The computer program product of claim 1 , wherein the received message is received from one of an operating system of the computing device or an application executing on the computing device. | 0.873868 |
4. The method as described in claim 3 , wherein the predicting further comprising generating the predicted bounding box based on a result of the processing of each of the plurality of cropped portions of the image. | 4. The method as described in claim 3 , wherein the predicting further comprising generating the predicted bounding box based on a result of the processing of each of the plurality of cropped portions of the image. 5. The method as described in claim 4 , wherein the generating is performed by taken an average, a median, or through use of a line fitting algorithm. | 0.90685 |
1. A method for an improved News Meta-Search over a large number of Online news sources on the Internet or similar networks, comprising providing a meta-search system which includes at least one server, and displaying news items to a user through a browser on a computer, wherein the server performs, under software instruction from the meta-search system, at least one of the steps of: i. Switching between news items from the same cluster or sub-cluster which are displayed in a given position in an automatically generated newspaper page, wherein said switching is done automatically or with user intervention; and ii. Switching between news images from the same cluster or sub-cluster which are displayed in a given position in an automatically generated newspaper page, wherein said switching is done automatically or with user intervention, and wherein said images are at least one of still images and streaming data; wherein at least one of the following features exists: a. Recursive sub-clustering is performed and the recursive sub-clustering continues until there are sufficiently few items in the final sub-category or until the items are too different to group further; b. If the user searches for keywords in the News Meta Search, the results are displayed recursively in clusters and sub-cluster in a way similar to the automatically generated newspaper page; c. If the user searches for keywords in the News Meta Search, the results can have all the features that exist in the automatically generated newspaper page; d. The system enables the user to switch between a mode that displays also images and a mode without images; e. The same news item or same sub-cluster can belong to more than one cluster or sub-cluster, and thus it is shown and/or can be reached from all the sufficiently relevant clusters or sub-clusters to which it is related; f. The system enables the user to request to sort a list of related items by relevance and/or by time and date to create order between and/or within the sub-clusters, so that the system performs the sorting without interfering with the cluster structure itself; g. The system enables the user to request to sort the items by at least one of: 1. The country of the source, so that the system orders or clusters the news items in addition or instead also according to the country of the news source, 2. The level of reliability of the source, so that the system orders or clusters the news items in addition or instead also according to the reliability of the news source; h. The system enables the user to view a graphical or textual hierarchical representation which shows simultaneously the multi-level structure of clusters and sub-clusters, showing more than two levels of the hierarchy at the same time, or showing the structure down to the end-nodes; i. The Meta News system automatically chooses only images that are within a certain reasonable range of sizes; j. As additional new related news items come in, the headlines and/or the images can be automatically updated even if the user does not click on any refresh button; k. The user gets a different indication when the items or images themselves have changed or new items or images are brought in (compared to the normal swapping between items), and said indication is at least one of sound indication and visual indication of the item that has changed or the new item that has been inserted; l. The html protocol and/or the html command set is expanded to allow an image to be requested with a given size limit, so that if the original image is bigger it is either truncated automatically to fit in the allowed window, or is automatically downscaled in order to fit completely into the allowed space; m. The html protocol and/or the html command set is expanded to allow an image to be requested with a given size limit, so that if the original image is bigger it is truncated automatically to fit in the allowed window and for said truncation the improved html protocol allows the web programmer to specify for each image the x-y coordinates of its central point of interest, and/or various heuristics are used by the browser or by the server in order to find the central point of interest automatically; n. When switching images contain also streaming data, at least one of the following is done: 1. Automatic switching of images is disabled so that the user has to click on something in order to view related streaming data from a different source or other still images, and 2. Each streaming source remains in the position for a longer time than still images until switching to the next streaming source or to the next still image; o. The system determines which item to use as the main item of the general cluster by at least one of: 1. First picking the sub-cluster that has the largest number of items and/or the most recent cluster that is big enough relative to other sub-clusters, 2. Picking the item within the chosen first sub-cluster which has the highest average similarity to other items in that sub-cluster and/or belongs to the largest sub-cluster of that sub-cluster and/or is most relevant within the cluster or within the sub-cluster and/or is most recent within the cluster or within the sub-cluster; p. When requesting News alerts, instead of being able to request only by specific keywords, the system enables the user to also at least one of: 1. Mark a cluster or a specific sub-cluster, so that he/she is notified automatically on any new items that belong to that cluster or after sufficient changes have accumulated in the cluster, 2. Use semantic qualifiers, 3. Mark words in a way that indicates that synonyms should also be checked for these words, so that he/she will be notified also about items that contain synonyms of these marked words; and wherein at least one of the following features exists: q. In order to improve the clustering ability, the time the items were published is taken into account, with the assumption that the closer the time of publication between them, the higher the chance that two items are dealing with the same event; r. Temporal words or phrases used in the news item are used to decide when the event occurred, and this time is used to separate between news items that occurred before this time and items that occurred after this time and/or to help decide the similarity between items that might be referring to the same event; s. Temporal words or phrases used in the news item are used to decide when the event occurred, and in order to analyze the temporal phrases used in the item, the system is able to perform also at least some minimal type of semantic analysis and/or has at least knowledge of the relevant temporal nouns and relevant verbs; and t. When sorting automatically generated news clusters the number of items in each cluster is normalized by the time factor, since clusters that have exited for a longer time would normally have more items than a newer cluster even if the new cluster is more important. | 1. A method for an improved News Meta-Search over a large number of Online news sources on the Internet or similar networks, comprising providing a meta-search system which includes at least one server, and displaying news items to a user through a browser on a computer, wherein the server performs, under software instruction from the meta-search system, at least one of the steps of: i. Switching between news items from the same cluster or sub-cluster which are displayed in a given position in an automatically generated newspaper page, wherein said switching is done automatically or with user intervention; and ii. Switching between news images from the same cluster or sub-cluster which are displayed in a given position in an automatically generated newspaper page, wherein said switching is done automatically or with user intervention, and wherein said images are at least one of still images and streaming data; wherein at least one of the following features exists: a. Recursive sub-clustering is performed and the recursive sub-clustering continues until there are sufficiently few items in the final sub-category or until the items are too different to group further; b. If the user searches for keywords in the News Meta Search, the results are displayed recursively in clusters and sub-cluster in a way similar to the automatically generated newspaper page; c. If the user searches for keywords in the News Meta Search, the results can have all the features that exist in the automatically generated newspaper page; d. The system enables the user to switch between a mode that displays also images and a mode without images; e. The same news item or same sub-cluster can belong to more than one cluster or sub-cluster, and thus it is shown and/or can be reached from all the sufficiently relevant clusters or sub-clusters to which it is related; f. The system enables the user to request to sort a list of related items by relevance and/or by time and date to create order between and/or within the sub-clusters, so that the system performs the sorting without interfering with the cluster structure itself; g. The system enables the user to request to sort the items by at least one of: 1. The country of the source, so that the system orders or clusters the news items in addition or instead also according to the country of the news source, 2. The level of reliability of the source, so that the system orders or clusters the news items in addition or instead also according to the reliability of the news source; h. The system enables the user to view a graphical or textual hierarchical representation which shows simultaneously the multi-level structure of clusters and sub-clusters, showing more than two levels of the hierarchy at the same time, or showing the structure down to the end-nodes; i. The Meta News system automatically chooses only images that are within a certain reasonable range of sizes; j. As additional new related news items come in, the headlines and/or the images can be automatically updated even if the user does not click on any refresh button; k. The user gets a different indication when the items or images themselves have changed or new items or images are brought in (compared to the normal swapping between items), and said indication is at least one of sound indication and visual indication of the item that has changed or the new item that has been inserted; l. The html protocol and/or the html command set is expanded to allow an image to be requested with a given size limit, so that if the original image is bigger it is either truncated automatically to fit in the allowed window, or is automatically downscaled in order to fit completely into the allowed space; m. The html protocol and/or the html command set is expanded to allow an image to be requested with a given size limit, so that if the original image is bigger it is truncated automatically to fit in the allowed window and for said truncation the improved html protocol allows the web programmer to specify for each image the x-y coordinates of its central point of interest, and/or various heuristics are used by the browser or by the server in order to find the central point of interest automatically; n. When switching images contain also streaming data, at least one of the following is done: 1. Automatic switching of images is disabled so that the user has to click on something in order to view related streaming data from a different source or other still images, and 2. Each streaming source remains in the position for a longer time than still images until switching to the next streaming source or to the next still image; o. The system determines which item to use as the main item of the general cluster by at least one of: 1. First picking the sub-cluster that has the largest number of items and/or the most recent cluster that is big enough relative to other sub-clusters, 2. Picking the item within the chosen first sub-cluster which has the highest average similarity to other items in that sub-cluster and/or belongs to the largest sub-cluster of that sub-cluster and/or is most relevant within the cluster or within the sub-cluster and/or is most recent within the cluster or within the sub-cluster; p. When requesting News alerts, instead of being able to request only by specific keywords, the system enables the user to also at least one of: 1. Mark a cluster or a specific sub-cluster, so that he/she is notified automatically on any new items that belong to that cluster or after sufficient changes have accumulated in the cluster, 2. Use semantic qualifiers, 3. Mark words in a way that indicates that synonyms should also be checked for these words, so that he/she will be notified also about items that contain synonyms of these marked words; and wherein at least one of the following features exists: q. In order to improve the clustering ability, the time the items were published is taken into account, with the assumption that the closer the time of publication between them, the higher the chance that two items are dealing with the same event; r. Temporal words or phrases used in the news item are used to decide when the event occurred, and this time is used to separate between news items that occurred before this time and items that occurred after this time and/or to help decide the similarity between items that might be referring to the same event; s. Temporal words or phrases used in the news item are used to decide when the event occurred, and in order to analyze the temporal phrases used in the item, the system is able to perform also at least some minimal type of semantic analysis and/or has at least knowledge of the relevant temporal nouns and relevant verbs; and t. When sorting automatically generated news clusters the number of items in each cluster is normalized by the time factor, since clusters that have exited for a longer time would normally have more items than a newer cluster even if the new cluster is more important. 5. The method of claim 1 wherein the system has at least one of: a. A knowledge base of at least one of: country names, city names, and other geographical areas; b. A knowledge base of at least the most common or most important verbs that typically appear in headlines and/or in the first one or two sentences of news items and/or in entire news items; c. A knowledge base of verbs that uses semantic trees and/or semantic graphs and/or various rules, so that each verb can be characterized by scores on a number of relevant variables or dimensions; d. A database of synonyms for the comparisons of nouns and/or of verbs, so that the system can know if two words are different or similar even without “understanding” their meaning; e. A knowledge base of major known political names and organizations; f. The ability to take into account also similarity in words at least in the headlines, even if they are not exactly identical. | 0.782303 |
14. A method for verifying an identity of at least one user to a text-based communication with at least a second user, comprising: obtaining a plurality of pair-wise characteristic features of at least one prior pair-wise text-based communication between said at least one user and said same second user; comparing the plurality of obtained pair-wise characteristic features to corresponding pair-wise features of a current session of said pair-wise text-based communication between said at least one user and said same second user; and verifying said identity of said at least one user based on a result of said comparison, wherein at least one of said comparing and verifying steps are performed by at least one hardware device. | 14. A method for verifying an identity of at least one user to a text-based communication with at least a second user, comprising: obtaining a plurality of pair-wise characteristic features of at least one prior pair-wise text-based communication between said at least one user and said same second user; comparing the plurality of obtained pair-wise characteristic features to corresponding pair-wise features of a current session of said pair-wise text-based communication between said at least one user and said same second user; and verifying said identity of said at least one user based on a result of said comparison, wherein at least one of said comparing and verifying steps are performed by at least one hardware device. 20. The method of claim 14 , wherein said plurality of pair-wise characteristic features are recorded in at least one feature vector. | 0.574505 |
13. The computer system of claim 10 , the computer-readable instructions further causing the computer system to: receive a selection of a point in the text transcription of the voicemail message, wherein the selected point is not a first word of the text transcription of the voicemail message; and play the voicemail message from the selected point in the text transcription of the voicemail message. | 13. The computer system of claim 10 , the computer-readable instructions further causing the computer system to: receive a selection of a point in the text transcription of the voicemail message, wherein the selected point is not a first word of the text transcription of the voicemail message; and play the voicemail message from the selected point in the text transcription of the voicemail message. 14. The computer system of claim 13 , wherein an indicator on the progress bar corresponds with the selected point in the text transcription of the voicemail message. | 0.780814 |
22. The method of claim 1 , wherein a said conforming user interface includes a field that is repositioned vis-a-vis the non-conforming user interface which would result from a said rule. | 22. The method of claim 1 , wherein a said conforming user interface includes a field that is repositioned vis-a-vis the non-conforming user interface which would result from a said rule. 23. The method of claim 22 , wherein a location of said repositioned field is based on a location of another field in said user interface. | 0.951445 |
9. The computer storage medium of claim 8 , wherein obtaining the plurality of canonical suffix-rewriting rules comprises: obtaining a first plurality of word-variant pairs, each pair comprising a word and a variant for the word; and associating a canonical suffix-rewriting rule with each of the word-variant pairs, including removing a longest common prefix from the word and the variant, and then generating the canonical suffix-rewriting rule from a remaining suffix of the word and a remaining suffix of the variant. | 9. The computer storage medium of claim 8 , wherein obtaining the plurality of canonical suffix-rewriting rules comprises: obtaining a first plurality of word-variant pairs, each pair comprising a word and a variant for the word; and associating a canonical suffix-rewriting rule with each of the word-variant pairs, including removing a longest common prefix from the word and the variant, and then generating the canonical suffix-rewriting rule from a remaining suffix of the word and a remaining suffix of the variant. 10. The computer storage medium of claim 9 , wherein the variant for each word is a normalized form of the word, and wherein obtaining the first plurality of word-variant pairs comprises: obtaining a second plurality of word-variant pairs, each second pair comprising a word and a variant for the word, each second pair associated with a confidence measure; clustering the words in the second plurality of word-variant pairs according to relationships between words and variants in the word-variant pairs; determining an optimal normalized form for each word in the second plurality of word pairs, the determining including selecting an optimal normalized form for each cluster; and generating the first plurality of word-variant pairs, each pair associating a word from one of the second word-variant pairs with the optimal normalized form for the cluster for the word. | 0.750643 |
10. A method comprising: under control of one or more processors configured with executable instructions, receiving a partial query input comprising voice signals of a user and at least one of text, image or audio input by a user; inferring in real-time, using a classifier, multiple different search goals based on the partial query input, the classifier comprising a support vector machine to find a hyperspace in a space of possible inputs to distinguish triggering input events from non-triggering input events, the classifier explicitly trained using generic training data and implicitly trained by observing user behavior; deriving similar or matching character sets, terms, or phrases to the partial query input by accessing one or more query databases that store query-related information; formulating at least one complete query based on the multiple different search goals; presenting the at least one complete query to the user for editing; processing the at least one complete query to return search results; assigning search results to each of the possible interpretations for selection by the user; outputting a confidence value associated with each of the multiple different search goals; formulating a complete query for each of the multiple different search goals; executing each complete query to return search results; and adjusting a number of the search results to be associated with each of the formal queries based at least in part on the associated confidence value. | 10. A method comprising: under control of one or more processors configured with executable instructions, receiving a partial query input comprising voice signals of a user and at least one of text, image or audio input by a user; inferring in real-time, using a classifier, multiple different search goals based on the partial query input, the classifier comprising a support vector machine to find a hyperspace in a space of possible inputs to distinguish triggering input events from non-triggering input events, the classifier explicitly trained using generic training data and implicitly trained by observing user behavior; deriving similar or matching character sets, terms, or phrases to the partial query input by accessing one or more query databases that store query-related information; formulating at least one complete query based on the multiple different search goals; presenting the at least one complete query to the user for editing; processing the at least one complete query to return search results; assigning search results to each of the possible interpretations for selection by the user; outputting a confidence value associated with each of the multiple different search goals; formulating a complete query for each of the multiple different search goals; executing each complete query to return search results; and adjusting a number of the search results to be associated with each of the formal queries based at least in part on the associated confidence value. 11. The method of claim 10 , further comprising: outputting recognition results based on processing the partial query input; and processing the recognition results in combination with preliminary search results obtained from processing the at least one complete query to arrive at a final set of search results. | 0.568182 |
1. A method, operative within a federated environment in which a token service fulfills requests by executing a module chain comprising a set of modules, comprising: responsive to receipt of a token, initiating processing of the module chain within a data processing system; during processing of the module chain within the data processing system, attempting to validate a value of a name-value pair based on a rule, wherein the rule is determined based on one or more invocation parameters of the module chain; and returning a response. | 1. A method, operative within a federated environment in which a token service fulfills requests by executing a module chain comprising a set of modules, comprising: responsive to receipt of a token, initiating processing of the module chain within a data processing system; during processing of the module chain within the data processing system, attempting to validate a value of a name-value pair based on a rule, wherein the rule is determined based on one or more invocation parameters of the module chain; and returning a response. 6. The method as described in claim 1 wherein, if the value of the name-value pair cannot be validated, the response is an error. | 0.763902 |
17. The system of claim 1 , wherein each type of document action request is processed by a different sub-process, and further wherein each sub-process is associated with a time that the sub-processed last processed a document action request. | 17. The system of claim 1 , wherein each type of document action request is processed by a different sub-process, and further wherein each sub-process is associated with a time that the sub-processed last processed a document action request. 19. The system of claim 17 , wherein each sub-process is associated with a predetermined processing time threshold. | 0.923995 |
1. A method performed by one or more server devices, the method comprising: storing, by a processor associated with the one or more server devices, a user profile that includes an author likelihood score of a particular user, the author likelihood score estimating a likelihood that the particular user will become an author of comments; receiving, by a processor associated with the one or more server devices and from users, one or more explicit requests for comments for a particular document, the one or more explicit requests for comments being associated with the users selecting a visual object to request comments about the particular document when the particular document is a document without comments; receiving, by a processor associated with the one or more server devices, an indication that the particular user has accessed flail the particular document; determining, by a processor associated with the one or more server devices, that the particular document has been identified as needing comments when a quantity of the one or more explicit requests for comments, received for the particular document, exceeds a threshold; retrieving, by a processor associated with the one or more server devices and from the user profile, the author likelihood score for the particular user, based on determining that the particular document has been identified as needing comments; determining, by a processor associated with the one or more server devices, whether the retrieved author likelihood score is greater than a particular threshold; and providing, by a processor associated with the one or more server devices, a suggestion to the particular user to write a comment about the particular document, based on: determining that the retrieved author likelihood score is greater than the particular threshold, and determining that the particular document has been identified as needing comments. | 1. A method performed by one or more server devices, the method comprising: storing, by a processor associated with the one or more server devices, a user profile that includes an author likelihood score of a particular user, the author likelihood score estimating a likelihood that the particular user will become an author of comments; receiving, by a processor associated with the one or more server devices and from users, one or more explicit requests for comments for a particular document, the one or more explicit requests for comments being associated with the users selecting a visual object to request comments about the particular document when the particular document is a document without comments; receiving, by a processor associated with the one or more server devices, an indication that the particular user has accessed flail the particular document; determining, by a processor associated with the one or more server devices, that the particular document has been identified as needing comments when a quantity of the one or more explicit requests for comments, received for the particular document, exceeds a threshold; retrieving, by a processor associated with the one or more server devices and from the user profile, the author likelihood score for the particular user, based on determining that the particular document has been identified as needing comments; determining, by a processor associated with the one or more server devices, whether the retrieved author likelihood score is greater than a particular threshold; and providing, by a processor associated with the one or more server devices, a suggestion to the particular user to write a comment about the particular document, based on: determining that the retrieved author likelihood score is greater than the particular threshold, and determining that the particular document has been identified as needing comments. 5. The method of claim 1 , further comprising: identifying the particular document as a document without comments, where the particular document is associated with at least a particular rank score with respect to a particular topic; and identifying the particular document as needing comments based on: identifying the document as a document without comments, and the particular document being associated with at least the particular rank score with respect to the particular topic. | 0.690955 |
17. A system, comprising: a memory; and a processing device coupled with the memory to: receive from a user a natural language test case for testing a software application, wherein the natural language test case is a test case written in a natural language, the test case comprising at least one of a condition, a variable, or a command that is executed by the software application to determine whether the software application is working according to program specifications, the natural language test case comprising a natural language command, wherein the natural language command is written as a user speaks and is distinct from a computer programming command; parse the received natural language test case to locate one or more search terms used to search for a corresponding term associated with an automated testing script command; cause a search of a testing framework system to be performed for the automated testing script command, wherein the one or more search terms are used to search at least one of an index or a document to locate the corresponding term associated with the automated testing script command, wherein the corresponding term is distinct from the automated testing script command and used to locate the automated testing script command; and generate an automated test case script that corresponds to the natural language test case based on a result of the search, wherein the automated test case script comprises the automated test script command. | 17. A system, comprising: a memory; and a processing device coupled with the memory to: receive from a user a natural language test case for testing a software application, wherein the natural language test case is a test case written in a natural language, the test case comprising at least one of a condition, a variable, or a command that is executed by the software application to determine whether the software application is working according to program specifications, the natural language test case comprising a natural language command, wherein the natural language command is written as a user speaks and is distinct from a computer programming command; parse the received natural language test case to locate one or more search terms used to search for a corresponding term associated with an automated testing script command; cause a search of a testing framework system to be performed for the automated testing script command, wherein the one or more search terms are used to search at least one of an index or a document to locate the corresponding term associated with the automated testing script command, wherein the corresponding term is distinct from the automated testing script command and used to locate the automated testing script command; and generate an automated test case script that corresponds to the natural language test case based on a result of the search, wherein the automated test case script comprises the automated test script command. 20. The system of claim 17 , wherein the processing device is further to: transmit the one or more search terms to the testing framework system; and receive the automated testing script command from the testing framework system, the automated testing script command being located by the testing framework system in a search based on the one or more search terms. | 0.540276 |
13. The method of claim 6 , wherein a plurality of look-up tables is utilized to assign a polarity to said human emotion identified from said one or more keywords, wherein said polarity categorizes said human emotion into one of a positive emotion, a negative emotion, or a neutral emotion. | 13. The method of claim 6 , wherein a plurality of look-up tables is utilized to assign a polarity to said human emotion identified from said one or more keywords, wherein said polarity categorizes said human emotion into one of a positive emotion, a negative emotion, or a neutral emotion. 14. The method of claim 13 , further comprising: determining, by said one or more processors, said positive emotion and said negative emotion simultaneously based on one of said one or more conversations and said plurality of look-up tables; and determining a sarcasm as said human emotion in one of said one or more conversations based on said determination of said positive emotion and said negative emotion. | 0.840885 |
25. A computer system comprising: a non-transitory computer readable storage medium on which is provided a language model database to store a plurality of language models corresponding to a plurality of languages, each language model including information usable to determine a score reflecting a probability that a document is in the language corresponding to that language model, the language model database being further to store an impostor profile associated with each of the plurality of languages, wherein the impostor profile for each of the plurality of languages includes a parameter set comprising values characterizing a score distribution expected for documents in that language when scored using the respective language models of one or more impostor languages in an impostor set associated with that language; and control logic coupled to the language model database to compute, for at least some of the plurality of languages, a document score for a test document, the document score being computed based on at least some of the language models stored in the language model data store, and to select a most likely language for the test document based on the computed document scores, wherein document scores are also computed for the impostor languages in the impostor set associated with the most likely language, the control logic being further to compare the document scores computed for the impostor languages in the impostor set associated with the most likely language to the impostor profile for the most likely language and to determine whether the test document is in the most likely language or in no language based at least in part on a result of comparing the document scores. | 25. A computer system comprising: a non-transitory computer readable storage medium on which is provided a language model database to store a plurality of language models corresponding to a plurality of languages, each language model including information usable to determine a score reflecting a probability that a document is in the language corresponding to that language model, the language model database being further to store an impostor profile associated with each of the plurality of languages, wherein the impostor profile for each of the plurality of languages includes a parameter set comprising values characterizing a score distribution expected for documents in that language when scored using the respective language models of one or more impostor languages in an impostor set associated with that language; and control logic coupled to the language model database to compute, for at least some of the plurality of languages, a document score for a test document, the document score being computed based on at least some of the language models stored in the language model data store, and to select a most likely language for the test document based on the computed document scores, wherein document scores are also computed for the impostor languages in the impostor set associated with the most likely language, the control logic being further to compare the document scores computed for the impostor languages in the impostor set associated with the most likely language to the impostor profile for the most likely language and to determine whether the test document is in the most likely language or in no language based at least in part on a result of comparing the document scores. 31. The computer system of claim 25 wherein the control logic is further configured such that determining whether the test document is in the most likely language or in no language includes applying a similarity test to the computed document score for the most likely language and the respective computed document scores for the languages in the impostor set associated with the most likely language. | 0.501533 |
16. A computer system as in claim 15 wherein the further information is selected from an additional filter condition. | 16. A computer system as in claim 15 wherein the further information is selected from an additional filter condition. 17. A computer system as in claim 16 wherein the structured association type in combination with the further information, amount to a join condition. | 0.946619 |
9. A non-transitory computer-readable storage medium for ranking a plurality of video articles, the non-transitory computer-readable storage medium comprising computer-executable instructions encoded on the medium, comprising: for each of the plurality of video articles, performing the following steps at a server: determining video-oriented characteristic data of a video article, the video-oriented characteristic data describing one or more characteristics of at least one broadcast of the video article, wherein each video article has metadata describing the video article; and determining a rank score based at least in part on the video article-oriented characteristic data and based at least in part on the metadata of the video article; determining an order for transmitting the plurality of video articles to a client, the order of transmission based on the rank score for each of the plurality of video articles. | 9. A non-transitory computer-readable storage medium for ranking a plurality of video articles, the non-transitory computer-readable storage medium comprising computer-executable instructions encoded on the medium, comprising: for each of the plurality of video articles, performing the following steps at a server: determining video-oriented characteristic data of a video article, the video-oriented characteristic data describing one or more characteristics of at least one broadcast of the video article, wherein each video article has metadata describing the video article; and determining a rank score based at least in part on the video article-oriented characteristic data and based at least in part on the metadata of the video article; determining an order for transmitting the plurality of video articles to a client, the order of transmission based on the rank score for each of the plurality of video articles. 14. The computer-readable storage medium of claim 9 , wherein the metadata of the video article is a name of the video article. | 0.66416 |
4. A system for generating answers to questions, comprising: a computer device comprising: at least one distinct software module, each distinct software module being embodied on a tangible computer-readable medium; a memory; and at least one processor coupled to the memory device and operative for: receiving an input query; obtaining, from an unstructured data source, candidate answers to the input query; producing a first score for each of the candidate answers; using a model selection module to select for each of the candidate answers one of a plurality of scoring models based on information about the each candidate answer; sending each of the candidate answers to the one of the scoring models selected for said each candidate answer; using the one of the scoring models selected for each of the candidate answers for weighting the first score for the each candidate answer to determine an answer score for the each candidate answer; and generating at least one answer to the input query based on the answer scores. | 4. A system for generating answers to questions, comprising: a computer device comprising: at least one distinct software module, each distinct software module being embodied on a tangible computer-readable medium; a memory; and at least one processor coupled to the memory device and operative for: receiving an input query; obtaining, from an unstructured data source, candidate answers to the input query; producing a first score for each of the candidate answers; using a model selection module to select for each of the candidate answers one of a plurality of scoring models based on information about the each candidate answer; sending each of the candidate answers to the one of the scoring models selected for said each candidate answer; using the one of the scoring models selected for each of the candidate answers for weighting the first score for the each candidate answer to determine an answer score for the each candidate answer; and generating at least one answer to the input query based on the answer scores. 6. The system according to claim 4 , wherein the information about the candidate answer comprises a part of speech. | 0.531011 |
1. A computer-implemented method of indexing stored information in a query answer system, comprising: receiving, at a processor of the computer, a user input specifying a factoid type; identifying expressions in the stored information on the computer storage device containing a factoid of the user-specified factoid type; constructing, with the processor, a passage corresponding to each expression identified by extracting text from the stored information containing the expression, wherein extracting text includes: determining whether a paragraph containing a given expression has at least a threshold number of words; if the paragraph containing the given expression does not have at least the threshold number of words, extracting the paragraph containing the expression and adding it to the passage; if the paragraph containing the given expression contains only the given expression, then extracting a paragraph preceding the given expression and a paragraph subsequent to the given expression and adding the preceding and subsequent paragraphs to the passage; and repeatedly extracting paragraphs or sentences and adding them to the passage until the passage contains at least the threshold number of words; computing, with the processor, a score corresponding to each passage based on a relationship between the passage and the user-specified factoid type, wherein computing a score corresponding to each passage comprises determining a likelihood that a factoid in an expression corresponding to a given passage answers a request represented by at least one content word, wherein determining a likelihood comprises computing a ranking function for each content word in the given passage; and generating, with the processor, an index of the passages and corresponding scores based on the user-specified factoid type contained in the expression, and storing the index on a computer storage device. | 1. A computer-implemented method of indexing stored information in a query answer system, comprising: receiving, at a processor of the computer, a user input specifying a factoid type; identifying expressions in the stored information on the computer storage device containing a factoid of the user-specified factoid type; constructing, with the processor, a passage corresponding to each expression identified by extracting text from the stored information containing the expression, wherein extracting text includes: determining whether a paragraph containing a given expression has at least a threshold number of words; if the paragraph containing the given expression does not have at least the threshold number of words, extracting the paragraph containing the expression and adding it to the passage; if the paragraph containing the given expression contains only the given expression, then extracting a paragraph preceding the given expression and a paragraph subsequent to the given expression and adding the preceding and subsequent paragraphs to the passage; and repeatedly extracting paragraphs or sentences and adding them to the passage until the passage contains at least the threshold number of words; computing, with the processor, a score corresponding to each passage based on a relationship between the passage and the user-specified factoid type, wherein computing a score corresponding to each passage comprises determining a likelihood that a factoid in an expression corresponding to a given passage answers a request represented by at least one content word, wherein determining a likelihood comprises computing a ranking function for each content word in the given passage; and generating, with the processor, an index of the passages and corresponding scores based on the user-specified factoid type contained in the expression, and storing the index on a computer storage device. 4. The method of claim 1 wherein extracting text further comprises: if the given expression is contained in a table, extracting caption information indicative of a caption of the table and adding the caption information to the passage. | 0.5 |
19. A machine-readable storage device having instructions stored thereon that, when executed by data processing apparatus, cause the data processing apparatus to perform operations comprising: obtaining information regarding selections of search results provided in response to a plurality of search queries, the obtained information for one or more of the selected search results comprising one or more presentation bias features of a presentation of the search result and one or more relevancy features of the search result, wherein at least one of the presentation bias features is a rank of the search result in the search results; training a model using the obtained information, wherein the model is trained to predict a click through rate based on input comprising the one or more presentation bias features and the one or more relevancy features; and providing the model for use with a search engine, wherein the search engine is configured to provide presentation bias and relevancy features of given search results as input to the model and to use predictive outputs of the model to reduce presentation bias in a presentation of the given search results by determining a quality score for each of the given search results and factoring out independent effects of presentation bias from the quality scores using the predictive outputs of the model, wherein the predictive outputs used to reduce the presentation bias in the presentation of the given search results include a predicted click through rate predicted based on the presentation bias and relevancy features of the given search results and the model. | 19. A machine-readable storage device having instructions stored thereon that, when executed by data processing apparatus, cause the data processing apparatus to perform operations comprising: obtaining information regarding selections of search results provided in response to a plurality of search queries, the obtained information for one or more of the selected search results comprising one or more presentation bias features of a presentation of the search result and one or more relevancy features of the search result, wherein at least one of the presentation bias features is a rank of the search result in the search results; training a model using the obtained information, wherein the model is trained to predict a click through rate based on input comprising the one or more presentation bias features and the one or more relevancy features; and providing the model for use with a search engine, wherein the search engine is configured to provide presentation bias and relevancy features of given search results as input to the model and to use predictive outputs of the model to reduce presentation bias in a presentation of the given search results by determining a quality score for each of the given search results and factoring out independent effects of presentation bias from the quality scores using the predictive outputs of the model, wherein the predictive outputs used to reduce the presentation bias in the presentation of the given search results include a predicted click through rate predicted based on the presentation bias and relevancy features of the given search results and the model. 26. The machine-readable storage of claim 19 wherein the search engine is further configured to use comparisons of the predictive outputs of the model with an implicit user feedback model to adjust respective ranking scores of the given search results. | 0.544697 |
1. A computerized method for adapting a baseline language model, comprising: obtaining a textual corpus of documents that comprise textual expressions; incorporating in the baseline language model textual expressions from documents which are determined as relevant to a provided target text based on a plurality of different relevancy determinations between the documents and the provided target text, thereby adapting the baseline language model to form an adapted language model for recognizing terms of a context of the provided target text, wherein a first relevancy determination comprises a determination by sufficiently small evaluated perplexities of the baseline language model with respect to the target text, and wherein a second relevancy determination comprises a determination of matches between stems of words in the textual expressions in the documents and stems of words of the target text, and wherein a third relevancy determination comprises a determination of matches between words in the textual expressions of the documents with words of the target text that for the matching have been converted to synonyms thereof according to a preset dictionary of synonyms, and wherein a fourth relevancy determination comprises a determination of semantic similarities of words in the textual expressions of the documents and words of the target text based on semantic distance and reduction thereof, and wherein the method is automatically performed on an at least one computerized apparatus configured to perform the method. | 1. A computerized method for adapting a baseline language model, comprising: obtaining a textual corpus of documents that comprise textual expressions; incorporating in the baseline language model textual expressions from documents which are determined as relevant to a provided target text based on a plurality of different relevancy determinations between the documents and the provided target text, thereby adapting the baseline language model to form an adapted language model for recognizing terms of a context of the provided target text, wherein a first relevancy determination comprises a determination by sufficiently small evaluated perplexities of the baseline language model with respect to the target text, and wherein a second relevancy determination comprises a determination of matches between stems of words in the textual expressions in the documents and stems of words of the target text, and wherein a third relevancy determination comprises a determination of matches between words in the textual expressions of the documents with words of the target text that for the matching have been converted to synonyms thereof according to a preset dictionary of synonyms, and wherein a fourth relevancy determination comprises a determination of semantic similarities of words in the textual expressions of the documents and words of the target text based on semantic distance and reduction thereof, and wherein the method is automatically performed on an at least one computerized apparatus configured to perform the method. 6. The method according to claim 1 , further comprising evaluating the performance of the adapted language model in recognizing speech related to the provided target text relative to the respective performance of the baseline language model, consequently determining which of the cited language models is more suitable for decoding speech related to the provided target text. | 0.5 |
15. A system, comprising: a memory unit for storing a computer program for enabling attendees of a web conference to view materials of the web conference in their native language; and a processor coupled to the memory unit, wherein the processor is configured to execute the program instructions of the computer program comprising: receiving a request from an attendee to join said web conference; detecting a native language type of said attendee; creating a virtual environment that is a clone of a host environment of a presenter of said web conference that runs a native language pack of a preferred native language of said attendee based on said detected native language type of said attendee or a language preference indicated by said attendee in response to said preferred native language of said attendee being different from a preferred native language of said presenter, wherein said native language pack of said preferred native language of said attendee translates an operating system and an application user interface of said host environment into said preferred native language of said attendee; capturing a shared screen shot of a screen from said host environment of said presenter of said web conference; translating said captured shared screen shot into said preferred native language of said attendee using said native language pack of said preferred native language of said attendee; and sending said translated captured shared sheen shot in said preferred native language of said attendee to said attendee from said virtual environment. | 15. A system, comprising: a memory unit for storing a computer program for enabling attendees of a web conference to view materials of the web conference in their native language; and a processor coupled to the memory unit, wherein the processor is configured to execute the program instructions of the computer program comprising: receiving a request from an attendee to join said web conference; detecting a native language type of said attendee; creating a virtual environment that is a clone of a host environment of a presenter of said web conference that runs a native language pack of a preferred native language of said attendee based on said detected native language type of said attendee or a language preference indicated by said attendee in response to said preferred native language of said attendee being different from a preferred native language of said presenter, wherein said native language pack of said preferred native language of said attendee translates an operating system and an application user interface of said host environment into said preferred native language of said attendee; capturing a shared screen shot of a screen from said host environment of said presenter of said web conference; translating said captured shared screen shot into said preferred native language of said attendee using said native language pack of said preferred native language of said attendee; and sending said translated captured shared sheen shot in said preferred native language of said attendee to said attendee from said virtual environment. 17. The system as recited in claim 15 , wherein the program instructions of the computer program further comprise: capturing an action along with generated dynamic content and associated metadata in response to said presenter performing said action on said screen of said host environment. | 0.500926 |
1. A system comprising: a processor; and a memory communicatively coupled to the processor, the memory storing instructions executable to perform a method, the method including: receiving an image of an identity document, the image being produced using a video stream; recognizing a plurality of text elements in the image using optical character recognition; finding a document template of a plurality of templates having a high degree of coincidence with the image using a substantially rectangular shape of the image overall, at least one of the text elements, and a respective location in the image for the at least one text element; associating each of the text elements with a respective field of the document template using the text elements and a respective location in the image for each of the text elements; placing at least one of the associated text elements in a respective field of a form, the respective field of the form corresponding to the respective associated field of the document template; making the completed form accessible on the system; placing at least one of the associated text elements in a respective field of a second form, the respective field of the second form corresponding to the respective associated field of the document template; and making the second completed form accessible on the system. | 1. A system comprising: a processor; and a memory communicatively coupled to the processor, the memory storing instructions executable to perform a method, the method including: receiving an image of an identity document, the image being produced using a video stream; recognizing a plurality of text elements in the image using optical character recognition; finding a document template of a plurality of templates having a high degree of coincidence with the image using a substantially rectangular shape of the image overall, at least one of the text elements, and a respective location in the image for the at least one text element; associating each of the text elements with a respective field of the document template using the text elements and a respective location in the image for each of the text elements; placing at least one of the associated text elements in a respective field of a form, the respective field of the form corresponding to the respective associated field of the document template; making the completed form accessible on the system; placing at least one of the associated text elements in a respective field of a second form, the respective field of the second form corresponding to the respective associated field of the document template; and making the second completed form accessible on the system. 8. The system of claim 1 wherein the respective location in the image for each of the text elements includes Cartesian coordinates where the origin lies at a corner of the image. | 0.593179 |
27. The system of claim 11 , wherein the suggestion space includes suggestion tables stored in the knowledge base and an in-memory suggestion space stored in memory, the in-memory suggestion space representing a copy of at least a portion of the suggestion tables. | 27. The system of claim 11 , wherein the suggestion space includes suggestion tables stored in the knowledge base and an in-memory suggestion space stored in memory, the in-memory suggestion space representing a copy of at least a portion of the suggestion tables. 28. The system of claim 27 , wherein the suggestion space includes: a suggestion space populator and a suggestion space updater, the suggestion space populator and the suggestion space updater each being coupled between the suggestion tables and the in-memory suggestion space. | 0.806027 |
9. A query system comprising: an interface configured to receive a user input; one or more processors coupled to the interface, configured to: obtain a user characteristic of a user who generated the user input; determine a first set of query keywords based at least in part on the user input; obtain, based on at least some of the first set of query keywords, a user feedback log that includes historical query results; determine at least one category among a plurality of categories of the user feedback log based on the user characteristic of the user; determine second set of query keywords based on the at least one category of the user feedback log, wherein the user feedback log includes selection frequencies, and wherein the determining of the second set of query keywords comprises to: generate the second set of query keywords based on the first set of query keywords and the at least one category, comprising to: determine a first keyword of the second set of query keywords that matches a second keyword of the first set of query keywords according to a selection frequency of the first keyword, comprising to: determine whether the selection frequency of the first keyword falls below or is equal to a threshold; and in the event that the selection frequency falls below or is equal to the threshold, remove the first keyword from the second set of query keywords; and make a query based on at least some of the second set of query keywords; and one or more memories coupled to the one or more processors, configured to provide the processors with instructions. | 9. A query system comprising: an interface configured to receive a user input; one or more processors coupled to the interface, configured to: obtain a user characteristic of a user who generated the user input; determine a first set of query keywords based at least in part on the user input; obtain, based on at least some of the first set of query keywords, a user feedback log that includes historical query results; determine at least one category among a plurality of categories of the user feedback log based on the user characteristic of the user; determine second set of query keywords based on the at least one category of the user feedback log, wherein the user feedback log includes selection frequencies, and wherein the determining of the second set of query keywords comprises to: generate the second set of query keywords based on the first set of query keywords and the at least one category, comprising to: determine a first keyword of the second set of query keywords that matches a second keyword of the first set of query keywords according to a selection frequency of the first keyword, comprising to: determine whether the selection frequency of the first keyword falls below or is equal to a threshold; and in the event that the selection frequency falls below or is equal to the threshold, remove the first keyword from the second set of query keywords; and make a query based on at least some of the second set of query keywords; and one or more memories coupled to the one or more processors, configured to provide the processors with instructions. 14. The system of claim 9 , wherein the selection frequency is determined based on at least one of the following: click frequencies on the historical query results, display frequencies on the historical query results, reading time on the historical query results, or importance of the historical query results. | 0.5 |
11. One or more computer-readable storage media comprising a collection of application program interfaces (APIs) configured for use with a peer identity system, the APIs comprising: a peer identity create function configured to create a new peer identity and return its name; a function configured to retrieve and set a friendly name for use by a user in establishment or management of a peer identity; a get cryptographic key function configured to return a handle to a private/public key air which is associated with an identity; a function configured to delete peer identities; an export function configured to export an identity to a data structure and encrypt the data structure with a supplied password; an import function configured to import identity information in the form of an encrypted data structure; an enumerate function configured to enumerate peer identities; an enumerate function configured to enumerate groups associated with peer identities; a function configured to enable retrieval of security information for an identity in the form of an XML fragment; and a function configured to create a new peer name based on an existing name of an identity and supplied classifier. | 11. One or more computer-readable storage media comprising a collection of application program interfaces (APIs) configured for use with a peer identity system, the APIs comprising: a peer identity create function configured to create a new peer identity and return its name; a function configured to retrieve and set a friendly name for use by a user in establishment or management of a peer identity; a get cryptographic key function configured to return a handle to a private/public key air which is associated with an identity; a function configured to delete peer identities; an export function configured to export an identity to a data structure and encrypt the data structure with a supplied password; an import function configured to import identity information in the form of an encrypted data structure; an enumerate function configured to enumerate peer identities; an enumerate function configured to enumerate groups associated with peer identities; a function configured to enable retrieval of security information for an identity in the form of an XML fragment; and a function configured to create a new peer name based on an existing name of an identity and supplied classifier. 18. The one or more computer-readable storage media of claim 11 , wherein the enumerate function configured to an enumerate peer identities include a parameter comprising a pointer to a location where a handle to an enumeration object is returned; and wherein the enumerate function configured to enumerate groups includes parameters comprising a name of an identity for which groups will be enumerated, and a pointer to the location where a handle to an enumeration object is returned. | 0.687821 |
11. A system comprising: a physical network interface; a set of parameterized models, said set of parameterized models describing mechanisms for gathering data from devices, said set of parameterized models comprising: discovery script templates for a plurality of different devices; for each discovery script template, one or more corresponding parameters defining how said discovery script template is to be customized to monitor a specified device of a specified device type based on corresponding on parameter values for said one or more parameters; and for each discovery script template, corresponding parameter metadata defining restrictions on parameter values for said one or more parameters; a user interface engine, said user interface engine configured to create a user interface for capturing parameter values including for a selected discovery script template being configured to: analyze said discovery script template to identify said one or more corresponding parameters; analyze corresponding parameter metadata to determine a typo parameter value restrictions for each of said one or more corresponding parameters; creates a user interface to capture parameter values for said corresponding one or more parameters, said user interface comprising appropriate user interface controls for receiving parameter values for said corresponding one or more parameters in accordance with restrictions defined in said corresponding parameter metadata; presents said user interface; and receives user input including parameter values for said corresponding one or more parameters through said appropriate user interface controls; and a script engine configured to: create a customized discovery script for monitoring said specified device of said specified device type by customizing said selected discovery script template with said parameter values for said corresponding one or more parameters; launch said customized discovery script; and receives results from said customized discovery script, said results comprising configuration data from said specified device of said specified device type. | 11. A system comprising: a physical network interface; a set of parameterized models, said set of parameterized models describing mechanisms for gathering data from devices, said set of parameterized models comprising: discovery script templates for a plurality of different devices; for each discovery script template, one or more corresponding parameters defining how said discovery script template is to be customized to monitor a specified device of a specified device type based on corresponding on parameter values for said one or more parameters; and for each discovery script template, corresponding parameter metadata defining restrictions on parameter values for said one or more parameters; a user interface engine, said user interface engine configured to create a user interface for capturing parameter values including for a selected discovery script template being configured to: analyze said discovery script template to identify said one or more corresponding parameters; analyze corresponding parameter metadata to determine a typo parameter value restrictions for each of said one or more corresponding parameters; creates a user interface to capture parameter values for said corresponding one or more parameters, said user interface comprising appropriate user interface controls for receiving parameter values for said corresponding one or more parameters in accordance with restrictions defined in said corresponding parameter metadata; presents said user interface; and receives user input including parameter values for said corresponding one or more parameters through said appropriate user interface controls; and a script engine configured to: create a customized discovery script for monitoring said specified device of said specified device type by customizing said selected discovery script template with said parameter values for said corresponding one or more parameters; launch said customized discovery script; and receives results from said customized discovery script, said results comprising configuration data from said specified device of said specified device type. 12. The system of claim 11 further comprising: a data validator engine that: validates said results to create validated output. | 0.540078 |
1. A computer apparatus for interactively developing a graphical control application software program for use in controlling an automation apparatus, the computer apparatus comprising: means for storing an application development program including a first program representing a first set of flow sequences, each flow sequence including at least one transition and at least one step; means for storing a plurality of controls for use in the automation apparatus, the plurality of controls each being an object obeying a standard which defines characteristics of the object as having one of a plurality of methods, one of plurality of properties, and one of a plurality of events; each step in each flow sequence redefined as an object; a display; means for receiving user commands to select from the first program one of the first set of flow sequences, and for selecting one of the objects, the receiving means controlling the display to display a structure wherein the graphical representation of the selected one of the first set of flow sequences is a step in the structure and the selected object structure having at least one transition and at least one event; and means for linking the first program with the possible controls to directly form an automation program in response to user commands. | 1. A computer apparatus for interactively developing a graphical control application software program for use in controlling an automation apparatus, the computer apparatus comprising: means for storing an application development program including a first program representing a first set of flow sequences, each flow sequence including at least one transition and at least one step; means for storing a plurality of controls for use in the automation apparatus, the plurality of controls each being an object obeying a standard which defines characteristics of the object as having one of a plurality of methods, one of plurality of properties, and one of a plurality of events; each step in each flow sequence redefined as an object; a display; means for receiving user commands to select from the first program one of the first set of flow sequences, and for selecting one of the objects, the receiving means controlling the display to display a structure wherein the graphical representation of the selected one of the first set of flow sequences is a step in the structure and the selected object structure having at least one transition and at least one event; and means for linking the first program with the possible controls to directly form an automation program in response to user commands. 4. The apparatus of claim 1 further comprising: means for displaying and enabling the user to select one of the plurality of methods, one of the plurality of properties and one of the plurality of events for each control. | 0.573077 |
1. A generator for generating Chinese character symbols comprising: memory means for storing individual characters at memory locations represented by a two-part computer-readable code, the first part defining a predetermined radical element common to a plurality of characters, and the second part identifying the stroke forms contained at predetermined locations within the balance of the individual character; means for fetching said stored characters from said memory means, said fetching means including means for entering into said character generator said two-part code and means for accessing the memory location within said memory means corresponding to said entered two-part code; input means including a keyboard for controlling said means for fetching in response to manual key-in operations, said input means including means for causing entry of said first part of said two-part code in response to the operation of a key in a first section of said keyboard and means for causing entry of said second part of said two-part code in response to the operation of one or more keys in a second section of said keyboard, the keys in said first section being operated to select one of said predetermined elements common to a plurality of characters and the keys in said second section being operated to indicate the stroke-form content of the balance of a character, excluding said predetermined common element; and wherein said fetching means also includes means for entering a predetermined code in lieu of said first part, said predetermined code indicating the absence of any said predetermined radical element common to a plurality of characters. | 1. A generator for generating Chinese character symbols comprising: memory means for storing individual characters at memory locations represented by a two-part computer-readable code, the first part defining a predetermined radical element common to a plurality of characters, and the second part identifying the stroke forms contained at predetermined locations within the balance of the individual character; means for fetching said stored characters from said memory means, said fetching means including means for entering into said character generator said two-part code and means for accessing the memory location within said memory means corresponding to said entered two-part code; input means including a keyboard for controlling said means for fetching in response to manual key-in operations, said input means including means for causing entry of said first part of said two-part code in response to the operation of a key in a first section of said keyboard and means for causing entry of said second part of said two-part code in response to the operation of one or more keys in a second section of said keyboard, the keys in said first section being operated to select one of said predetermined elements common to a plurality of characters and the keys in said second section being operated to indicate the stroke-form content of the balance of a character, excluding said predetermined common element; and wherein said fetching means also includes means for entering a predetermined code in lieu of said first part, said predetermined code indicating the absence of any said predetermined radical element common to a plurality of characters. 3. The character generator of claim 1 wherein said means for entering said predetermined code includes means responsive to the operation of a key in said second section of said keyboard. | 0.504684 |
14. A method of creating a plurality of different target software development tools, the method comprising: receiving at least one computer-readable specification specifying functionality specific to one or more software development scenarios, wherein the at least one computer-readable specification specifies the following software development scenario functionality of the plurality of different target software development tools: target processor execution architecture; type checking rule set; managed execution environment; input programming language or input binary format; and compilation type; creating at least one software development component for the plurality of different software development tools from the at least one specification; integrating the at least one software development component for the plurality of different software development tools into a software development scenario-independent framework; and compiling, at least in part, the at least one software development component and framework to create the plurality of different target software development tools; wherein the computer-readable specification comprises functionality for processing an intermediate representation format capable of representing a plurality of different programming languages; and wherein the intermediate representation format comprises one or more exception handling models capable of supporting a plurality of programming language-specific exception handling models for the plurality of different programming languages. | 14. A method of creating a plurality of different target software development tools, the method comprising: receiving at least one computer-readable specification specifying functionality specific to one or more software development scenarios, wherein the at least one computer-readable specification specifies the following software development scenario functionality of the plurality of different target software development tools: target processor execution architecture; type checking rule set; managed execution environment; input programming language or input binary format; and compilation type; creating at least one software development component for the plurality of different software development tools from the at least one specification; integrating the at least one software development component for the plurality of different software development tools into a software development scenario-independent framework; and compiling, at least in part, the at least one software development component and framework to create the plurality of different target software development tools; wherein the computer-readable specification comprises functionality for processing an intermediate representation format capable of representing a plurality of different programming languages; and wherein the intermediate representation format comprises one or more exception handling models capable of supporting a plurality of programming language-specific exception handling models for the plurality of different programming languages. 18. The method of claim 14 wherein the intermediate representation comprises type representations capable of representing the type representations of the plurality of different programming languages. | 0.524266 |
1. A system for grouping cluster spines into a two-dimensional visual display space, comprising: a spine generator to obtain clusters of concepts each extracted from one or more documents and to form spines by placing the clusters sharing at least one of the concepts along a vector; a spine ordering module to order the spines based on a length of each spine; a spine placement module to select one or more of the spines, each unique from the other spines, as unique spines and to place the unique spines into a visual display space; a similarity module to determine a similarity between at least one of the spines not placed and each of the placed unique spines and to identify the placed unique spine most similar; an anchor selection module to select at least one anchor cluster on the most similar unique spine that satisfies a threshold similarity with the unplaced spine; a grafting module to identify one of the clusters on the unplaced spine that is most similar to the selected anchor cluster and to graft the most similar cluster to the selected anchor cluster such that the unplaced spine is positioned along a vector extending from a center of the selected anchor cluster to form a group of cluster spines; and a display to display the group of cluster spines in the visual display space. | 1. A system for grouping cluster spines into a two-dimensional visual display space, comprising: a spine generator to obtain clusters of concepts each extracted from one or more documents and to form spines by placing the clusters sharing at least one of the concepts along a vector; a spine ordering module to order the spines based on a length of each spine; a spine placement module to select one or more of the spines, each unique from the other spines, as unique spines and to place the unique spines into a visual display space; a similarity module to determine a similarity between at least one of the spines not placed and each of the placed unique spines and to identify the placed unique spine most similar; an anchor selection module to select at least one anchor cluster on the most similar unique spine that satisfies a threshold similarity with the unplaced spine; a grafting module to identify one of the clusters on the unplaced spine that is most similar to the selected anchor cluster and to graft the most similar cluster to the selected anchor cluster such that the unplaced spine is positioned along a vector extending from a center of the selected anchor cluster to form a group of cluster spines; and a display to display the group of cluster spines in the visual display space. 5. A system according to claim 1 , further comprising: an anchor identification module to identify additional anchor clusters on the unplaced spine by locating an open edge formed by an additional vector extending from a center of one of the clusters along that unplaced spine. | 0.641397 |
10. An apparatus, comprising: a mashup stimulus module that comprises a processor to determine at least one of a role, context, presence, or location of a user, wherein at least one of the role or context is determined based on a telephone call and wherein a specified mashup is determined based on an Instant Message session and the telephone call occurring simultaneously; and a mashup management module that comprises the processor, wherein the mashup management module identifies that the Instant Message session and the telephone call are on different computational devices, in response to identifying that the Instant Message session and the telephone call are on different computational devices, transfers the Instant Message session and the telephone call to a common computational device for displaying the telephone call and the Instant Message session by using the specified mashup for a user interface of the common computational device. | 10. An apparatus, comprising: a mashup stimulus module that comprises a processor to determine at least one of a role, context, presence, or location of a user, wherein at least one of the role or context is determined based on a telephone call and wherein a specified mashup is determined based on an Instant Message session and the telephone call occurring simultaneously; and a mashup management module that comprises the processor, wherein the mashup management module identifies that the Instant Message session and the telephone call are on different computational devices, in response to identifying that the Instant Message session and the telephone call are on different computational devices, transfers the Instant Message session and the telephone call to a common computational device for displaying the telephone call and the Instant Message session by using the specified mashup for a user interface of the common computational device. 14. The apparatus of claim 10 , wherein the specified mashup is associated with a description of the determined at least one of the role, context, presence, or location, wherein the specified mashup is associated with at least one of (a) a description of device capabilities, provisioning and user preferences required by a computational device of the user, (b) a description of an appearance and/or configuration associated with the computational device of the user, or (c) an electronic address or other identifier of the computational device of the user. | 0.762177 |
9. A method comprising: creating a specification for constructing a web display to contain page components that display data from heterogeneous data sources, the specification associating the page components with uniform resource locators assigned to the page components; storing the specification in at least one memory; retrieving data from heterogeneous data sources to produce the web display; controlling display and/or update of the page components using the uniform resource locators, the web display to display at least some of the data from the heterogeneous data sources; associating one or more user-specific changes to the page components, the user-specific changes comprising a layout change to a page layout for a page including the page components; tracking the one or more user-specific changes to the page components to allow users to make changes to the page components; and providing user-selectable options to dynamically undo at least some of the one or more user-specific changes to the page components. | 9. A method comprising: creating a specification for constructing a web display to contain page components that display data from heterogeneous data sources, the specification associating the page components with uniform resource locators assigned to the page components; storing the specification in at least one memory; retrieving data from heterogeneous data sources to produce the web display; controlling display and/or update of the page components using the uniform resource locators, the web display to display at least some of the data from the heterogeneous data sources; associating one or more user-specific changes to the page components, the user-specific changes comprising a layout change to a page layout for a page including the page components; tracking the one or more user-specific changes to the page components to allow users to make changes to the page components; and providing user-selectable options to dynamically undo at least some of the one or more user-specific changes to the page components. 13. The method of claim 9 , wherein versions of the page are time stamped and the one or more user-specific changes can be rolled back up to a period of time. | 0.890041 |
13. The record management system of claim 1 further comprising means for modifying at least a portion of said one or more headings, said selection of available subheadings, or said one or more selected subheadings. | 13. The record management system of claim 1 further comprising means for modifying at least a portion of said one or more headings, said selection of available subheadings, or said one or more selected subheadings. 15. The record management system of claim 13 wherein said means for modifying at least a portion of said one or more headings, said selection of available subheadings, or said one or more selected subheadings comprises means for merging at least a portion of stored electronic documents into the electronic document currently in use. | 0.879558 |
8. A device, comprising: a memory; and one or more processors to: receive a comment related to a first document, identify a plurality of second documents, each of the plurality of second documents being not identical to the first document and including at least a threshold amount of content from the first document, determine information associated with the plurality of second documents, store, in the memory, the comment related to the first document and the information associated with the plurality of second documents, and enable another device to access the stored comment related to the first document and the stored information associated with the plurality of second documents, the processor, when enabling the other device to access the stored comment related to the first document and the stored information associated with the plurality of second documents, being further to: generate, based on the stored information, a web document that, when rendered, includes a first portion to present information associated with the stored comment related to the first document and a second portion to present content associated with one of the plurality of second documents, the first portion and the second portion being different, and provide the other device with access to the generated web document. | 8. A device, comprising: a memory; and one or more processors to: receive a comment related to a first document, identify a plurality of second documents, each of the plurality of second documents being not identical to the first document and including at least a threshold amount of content from the first document, determine information associated with the plurality of second documents, store, in the memory, the comment related to the first document and the information associated with the plurality of second documents, and enable another device to access the stored comment related to the first document and the stored information associated with the plurality of second documents, the processor, when enabling the other device to access the stored comment related to the first document and the stored information associated with the plurality of second documents, being further to: generate, based on the stored information, a web document that, when rendered, includes a first portion to present information associated with the stored comment related to the first document and a second portion to present content associated with one of the plurality of second documents, the first portion and the second portion being different, and provide the other device with access to the generated web document. 13. The device of claim 8 , where the processor, when enabling the other device to access the stored comment related to the first document and the stored information associated with the plurality of second documents, is further to: index at least one of the comment related to the first document or the information associated with the plurality of second documents, receive a query from the other device, determine that the indexed at least one of the comment related to the first document or the information associated with the plurality of second documents is relevant to the query, and identify the indexed at least one of the comment related to the first document and the information associated with the plurality of second documents as part of search results associated with the query. | 0.558352 |
16. The method of claim 12 , further comprising selecting a domain name registration provider from a plurality of domain name registration providers to process the domain name registration request. | 16. The method of claim 12 , further comprising selecting a domain name registration provider from a plurality of domain name registration providers to process the domain name registration request. 18. The method of claim 16 , wherein selecting a domain name registration provider from a plurality of domain name registration providers comprises selecting a domain name registration provider from at least one of a template or modifiable configuration settings. | 0.901756 |
11. The system of claim 1 , wherein at least some of said additional elements comprise one or more elements that describe how drawing is performed and at least a grouping element that groups other elements. | 11. The system of claim 1 , wherein at least some of said additional elements comprise one or more elements that describe how drawing is performed and at least a grouping element that groups other elements. 20. The system of claim 11 , wherein one of said additional elements that describes how drawing is performed comprises an element that describes a geometric region. | 0.926681 |
1. A method of managing relationships between logical fields in a data abstraction model, wherein the logical fields correspond to physical fields in a database, comprising: providing a structure with links between logical branches of the data abstraction model defining logical fields, some of which share a common name, wherein the links allow for the joining of data structures containing the physical fields when executing an abstract query containing a reference to a common name shared by multiple logical fields, and wherein each link defines a path between different data structures of a physical representation of the data in the database; and constructing, by operation of one or more computer processors, an executable query from the abstract query using the provided structure, wherein constructing comprises generating logic to join a plurality of the data structures as defined by the one or more links. | 1. A method of managing relationships between logical fields in a data abstraction model, wherein the logical fields correspond to physical fields in a database, comprising: providing a structure with links between logical branches of the data abstraction model defining logical fields, some of which share a common name, wherein the links allow for the joining of data structures containing the physical fields when executing an abstract query containing a reference to a common name shared by multiple logical fields, and wherein each link defines a path between different data structures of a physical representation of the data in the database; and constructing, by operation of one or more computer processors, an executable query from the abstract query using the provided structure, wherein constructing comprises generating logic to join a plurality of the data structures as defined by the one or more links. 8. The method of claim 1 , comprising: identifying, for each of the plurality of logical branches, a corresponding data structure of a physical representation of the data in the database; and determining whether identified data structures are related to each other. | 0.550372 |
1. A computer-implemented method for verifying data structures, the method comprising: executing, by a processor, a software module to obtain a first reference set of data produced by the software module, wherein the first reference set of data comprising all data produced by the software module at a first time; introducing, by the processor, a change to the software module after the first time to generate a modified software module; executing, by the processor, the modified software module to obtain a second reference set of data produced by the modified software module, wherein the second reference set of data comprising all data including data related to at least one changed portion of the modified software module produced by the modified software module at a second time, and wherein the executing at the second time is response to the introduced change; transforming, by the processor, the first reference set of data produced by the software module and the second reference set of data produced by the modified software module into a first formal text form representation and a second formal text form representation, respectively; determining, by the processor, a plurality of differences between the first reference set of data produced by the software module and the second reference set of data produced by the modified software module by comparing the first formal text form representation and the second formal text form representation to each other; filtering, by the processor, the plurality of differences to obtain a sub-set of the plurality of differences based on at least one filter criteria; mapping, by the processor, each difference in the sub-set of the plurality of differences to a corresponding portion of the modified software module responsible for the difference to determine at which point in execution of the modified software module the difference occurred; generating, by the processor, a report of the sub-set of plurality of differences, the corresponding mapped portions of the modified software module, and root cause of the sub-set of plurality of differences; wherein the second reference set of data is further used, by the processor, to verify whether a functionality of the modified software module is retained after the introduced change; replacing, by the processor, the first reference set of data with the second set of second reference set of data upon verifying that the functionality is retained; and establishing, by the processor, the second reference set of data as a new first reference set of data to use in future software module verification. | 1. A computer-implemented method for verifying data structures, the method comprising: executing, by a processor, a software module to obtain a first reference set of data produced by the software module, wherein the first reference set of data comprising all data produced by the software module at a first time; introducing, by the processor, a change to the software module after the first time to generate a modified software module; executing, by the processor, the modified software module to obtain a second reference set of data produced by the modified software module, wherein the second reference set of data comprising all data including data related to at least one changed portion of the modified software module produced by the modified software module at a second time, and wherein the executing at the second time is response to the introduced change; transforming, by the processor, the first reference set of data produced by the software module and the second reference set of data produced by the modified software module into a first formal text form representation and a second formal text form representation, respectively; determining, by the processor, a plurality of differences between the first reference set of data produced by the software module and the second reference set of data produced by the modified software module by comparing the first formal text form representation and the second formal text form representation to each other; filtering, by the processor, the plurality of differences to obtain a sub-set of the plurality of differences based on at least one filter criteria; mapping, by the processor, each difference in the sub-set of the plurality of differences to a corresponding portion of the modified software module responsible for the difference to determine at which point in execution of the modified software module the difference occurred; generating, by the processor, a report of the sub-set of plurality of differences, the corresponding mapped portions of the modified software module, and root cause of the sub-set of plurality of differences; wherein the second reference set of data is further used, by the processor, to verify whether a functionality of the modified software module is retained after the introduced change; replacing, by the processor, the first reference set of data with the second set of second reference set of data upon verifying that the functionality is retained; and establishing, by the processor, the second reference set of data as a new first reference set of data to use in future software module verification. 3. The method of claim 1 , wherein the at least one filter criteria includes known data deviations. | 0.681953 |
1. A method for hosting a community in multiple languages on a server, the method comprising: receiving a request at the server via a network from a first member of the community to post content in a first language within the community, the content including a text link in the first language; translating the content, including the text link in the first language, into a second language; receiving login information at the server via a network from a second member associated with the second language; displaying the translated content to the second member; providing a link to the content in the first language to the second member; and receiving qualitative and quantitative feedback from the second member relating to the translation of the content, the feedback including a suggested translation, wherein the second member is associated with the second language via a profile. | 1. A method for hosting a community in multiple languages on a server, the method comprising: receiving a request at the server via a network from a first member of the community to post content in a first language within the community, the content including a text link in the first language; translating the content, including the text link in the first language, into a second language; receiving login information at the server via a network from a second member associated with the second language; displaying the translated content to the second member; providing a link to the content in the first language to the second member; and receiving qualitative and quantitative feedback from the second member relating to the translation of the content, the feedback including a suggested translation, wherein the second member is associated with the second language via a profile. 3. The method recited in claim 1 , wherein the content comprises a post in a message board associated with the community. | 0.568385 |
17. The non-transitory computer-readable medium of claim 15 , wherein the actions of the computer program instructions further comprise training the set of initial classifiers, the set of initial classifiers including a first initial classifier trained using a first initial training set comprising videos, and a second initial classifier trained using a second initial training set comprising non-video media. | 17. The non-transitory computer-readable medium of claim 15 , wherein the actions of the computer program instructions further comprise training the set of initial classifiers, the set of initial classifiers including a first initial classifier trained using a first initial training set comprising videos, and a second initial classifier trained using a second initial training set comprising non-video media. 18. The non-transitory computer-readable medium of claim 17 , wherein the non-video media is selected from the group consisting of textual documents, audio, images, and any combination thereof. | 0.900421 |
1. A system, comprising: a text recognition component configured for recognition of text on a sequence of video frames, the text recognition component configured to receive a selected frame of the sequence of video frames and perform text recognition processing of the selected frame to output a selected frame result; a tracker component configured to select a keyframe from the sequence of video frames based on stability criteria applied to incoming frames and to establish a reference coordinate system relative to the selected keyframe, the selected frame result mapped back to the reference coordinate system of the keyframe, the tracker component configured to apply keyframe coordinates to subsequent video frames to enable accumulation of best results for text recognition rendering and viewing; and a microprocessor configured to execute computer-executable instructions associated with at least one of the text recognition component or the tracker component. | 1. A system, comprising: a text recognition component configured for recognition of text on a sequence of video frames, the text recognition component configured to receive a selected frame of the sequence of video frames and perform text recognition processing of the selected frame to output a selected frame result; a tracker component configured to select a keyframe from the sequence of video frames based on stability criteria applied to incoming frames and to establish a reference coordinate system relative to the selected keyframe, the selected frame result mapped back to the reference coordinate system of the keyframe, the tracker component configured to apply keyframe coordinates to subsequent video frames to enable accumulation of best results for text recognition rendering and viewing; and a microprocessor configured to execute computer-executable instructions associated with at least one of the text recognition component or the tracker component. 3. The system of claim 1 , wherein the reference coordinate system relates recognized text coordinates of the text of the selected frame back to the keyframe based on an estimated transformation established between the keyframe and the selected frame. | 0.5 |
15. A method for retrieving answer information from a natural language (NL) query answering system, the method comprising: prompting, in a user interface application generated according to an NL query having first query parameters, using one or more computing devices, a user to provide second query parameters regarding a second query, the second query related to the NL query, and the second query parameters different than the first query parameters; determining one or more respective values of one or more variables using the received second query parameters; and generating a computer-generated query that is based on the NL query, wherein the computer-generated query is generated to include the one or more respective values of the one or more variables; providing the computer-generated query to the NL query answering system; receiving, from the NL query answering system, answer information responsive to the computer-generated query; and causing a display device to display the answer information. | 15. A method for retrieving answer information from a natural language (NL) query answering system, the method comprising: prompting, in a user interface application generated according to an NL query having first query parameters, using one or more computing devices, a user to provide second query parameters regarding a second query, the second query related to the NL query, and the second query parameters different than the first query parameters; determining one or more respective values of one or more variables using the received second query parameters; and generating a computer-generated query that is based on the NL query, wherein the computer-generated query is generated to include the one or more respective values of the one or more variables; providing the computer-generated query to the NL query answering system; receiving, from the NL query answering system, answer information responsive to the computer-generated query; and causing a display device to display the answer information. 17. The method of claim 15 , further comprising: determining types of the answer information that will be displayed in response to receiving the answer information from the NL query answering system, and causing the display device to display the determined types of the answer information received. | 0.710949 |
16. A method as recited in claim 15 , wherein the step for developing code includes: receiving user input selecting one of the one or more code builders from the toolbox; in the code view, receiving user input selecting one of the plurality of available lines for source code for placement of source code generated by the code builder as a desired location for the source code; automatically, in response to receiving the user input selecting the one of the plurality of available lines, displaying the code builder interface and prompting a user for customized input that will be used to determine at least in part the source code that is generated by the code builder; receiving the customized input; applying the customized input to the corresponding document object model to generate customized source code; and inserting the customized source code at the desired location within the code view of the integrated development environment. | 16. A method as recited in claim 15 , wherein the step for developing code includes: receiving user input selecting one of the one or more code builders from the toolbox; in the code view, receiving user input selecting one of the plurality of available lines for source code for placement of source code generated by the code builder as a desired location for the source code; automatically, in response to receiving the user input selecting the one of the plurality of available lines, displaying the code builder interface and prompting a user for customized input that will be used to determine at least in part the source code that is generated by the code builder; receiving the customized input; applying the customized input to the corresponding document object model to generate customized source code; and inserting the customized source code at the desired location within the code view of the integrated development environment. 17. A method as recited in claim 16 , wherein using the code, builder interface to prompt a user for customized input includes querying an IDE service such as for a list of available database connections to provide information that is presented to the user for selection. | 0.875975 |
12. A bone screw comprising: an elongated shaft having a distal end and a proximal end; a post having a distal end and a proximal end; a ball joint which pivotally secures the distal end of the post to the proximal end of the elongated shaft such that the post can pivot relative to the elongated shaft; a tubular extension of the elongated shaft which extends over the ball joint and a distal portion of the post; a compliant member disposed between the post and the tubular extension of the elongated shaft which flexible aligns the post with the elongated shaft; and a screw thread which extends along said elongated shaft and a portion of said tubular extension, said screw thread extending more proximally than the ball joint such that, upon implantation, the elongated shaft and the portion of the tubular extension are adapted to be implanted in a bone and the ball joint is adapted to be positioned within the bone. | 12. A bone screw comprising: an elongated shaft having a distal end and a proximal end; a post having a distal end and a proximal end; a ball joint which pivotally secures the distal end of the post to the proximal end of the elongated shaft such that the post can pivot relative to the elongated shaft; a tubular extension of the elongated shaft which extends over the ball joint and a distal portion of the post; a compliant member disposed between the post and the tubular extension of the elongated shaft which flexible aligns the post with the elongated shaft; and a screw thread which extends along said elongated shaft and a portion of said tubular extension, said screw thread extending more proximally than the ball joint such that, upon implantation, the elongated shaft and the portion of the tubular extension are adapted to be implanted in a bone and the ball joint is adapted to be positioned within the bone. 13. The bone screw of claim 12 , wherein the ball joint is adapted to be positioned in a location adjacent or below the surface of a bone, without obstruction of pivoting of the post. | 0.865889 |
1. A computer program product comprising a tangible computer usable medium having a computer readable program for managing granularity of a computing service infrastructure, wherein the computer readable program when executed on a computer causes the computer to: identify a group having a number of service requestors; identify a set of business functions that may be requested by the group of service requestors by either customized or non-customized service requests; create a value (n1) that represents the smallest number of customized service functions to realize all of the business functions; create a value (n2) that represents the smallest total number of non-customized service functions to realize all of the business functions; and iteratively determine an optimal number L of customized and non-customized service functions to realize the business functions, where L is between n1 and n2 and increases from n2 towards n1 as a number of each requestor is assigned a customized service request for each business function. | 1. A computer program product comprising a tangible computer usable medium having a computer readable program for managing granularity of a computing service infrastructure, wherein the computer readable program when executed on a computer causes the computer to: identify a group having a number of service requestors; identify a set of business functions that may be requested by the group of service requestors by either customized or non-customized service requests; create a value (n1) that represents the smallest number of customized service functions to realize all of the business functions; create a value (n2) that represents the smallest total number of non-customized service functions to realize all of the business functions; and iteratively determine an optimal number L of customized and non-customized service functions to realize the business functions, where L is between n1 and n2 and increases from n2 towards n1 as a number of each requestor is assigned a customized service request for each business function. 6. The computer program product as in claim 1 , wherein the set of service functions comprise at least one of a business function and an output data object. | 0.765672 |
16. A software application, tangibly stored on a storage device medium, the software application comprising instructions operable to cause a programmable processor to: receive a first content in a software application, the software application implementing a first operation that is disabled by default; receive a request to operate on the first content using the first operation; in response to the request, retrieve a first enabler from a database, the first enabler specifying to the software application an enablement of the first operation only with respect to the first content; and as a result of the retrieval of the first enabler, enable the first operation to operate on the first content within an operating context specified in the first enabler. | 16. A software application, tangibly stored on a storage device medium, the software application comprising instructions operable to cause a programmable processor to: receive a first content in a software application, the software application implementing a first operation that is disabled by default; receive a request to operate on the first content using the first operation; in response to the request, retrieve a first enabler from a database, the first enabler specifying to the software application an enablement of the first operation only with respect to the first content; and as a result of the retrieval of the first enabler, enable the first operation to operate on the first content within an operating context specified in the first enabler. 21. The software application of claim 16 , wherein the operating context specified in the first enabler includes one or more of: a particular document, a particular type of document, a particular data set, a particular type of data set, a particular computer, a particular set of computers, a particular user, a particular set of users, a particular session, a particular number of sessions, a particular time period, a particular content provider, and a particular document in a particular state. | 0.538091 |
16. A non-transitory computer readable storage medium storing programmed computer code, which when executed by a computer system having at least one processor and a memory storing computer programs for execution by the processor, causes the computer system to perform operations comprising: receiving inputs from a user interface framework of an application that implements a user interface framework when at least one text string is to be displayed in a display element of the user interface framework, the inputs comprising the text string, an amount of available space in the display element, and an identification of the language of the text string; receiving linguistic pre-analysis results from outside the user interface; executing, by the processor, a text reduction algorithm on the text string based upon the linguistic pre-analysis results, wherein executing the text reduction algorithm comprises calculating one or more of entropy, confusion, and style deviation of the short forms of the text string; identifying one or more short forms of the text string that fit within the available space of the display element based on executing the text reduction algorithm; and communicating the identified short forms of the text string to the application or framework for display in the display element of the user interface framework. | 16. A non-transitory computer readable storage medium storing programmed computer code, which when executed by a computer system having at least one processor and a memory storing computer programs for execution by the processor, causes the computer system to perform operations comprising: receiving inputs from a user interface framework of an application that implements a user interface framework when at least one text string is to be displayed in a display element of the user interface framework, the inputs comprising the text string, an amount of available space in the display element, and an identification of the language of the text string; receiving linguistic pre-analysis results from outside the user interface; executing, by the processor, a text reduction algorithm on the text string based upon the linguistic pre-analysis results, wherein executing the text reduction algorithm comprises calculating one or more of entropy, confusion, and style deviation of the short forms of the text string; identifying one or more short forms of the text string that fit within the available space of the display element based on executing the text reduction algorithm; and communicating the identified short forms of the text string to the application or framework for display in the display element of the user interface framework. 18. The computer-readable storage medium of claim 16 wherein calculating the entropy of the one or more short forms of the text string comprises: assigning a total meaningfulness value to the text string; determining a contribution of each character of the text string to the total meaningfulness value; and calculating how much meaning is subtracted when one or more characters are removed from the text string based on determining the contribution of the removed characters to the total meaningfulness value. | 0.503438 |
298. The system of claim 297 , wherein the required term of experience is rounded up to a unit of time. | 298. The system of claim 297 , wherein the required term of experience is rounded up to a unit of time. 301. The system of claim 298 , wherein the unit of time is not an integer. | 0.981663 |
6. The method according to claim 1 further comprising: performing heuristic examination based on the identification nomenclature and the connectivity to extract and store device lists, the device lists including one or more of: a logic flow list, a finite state machine list, a control register list, and an untested device list. | 6. The method according to claim 1 further comprising: performing heuristic examination based on the identification nomenclature and the connectivity to extract and store device lists, the device lists including one or more of: a logic flow list, a finite state machine list, a control register list, and an untested device list. 9. The method according to claim 6 wherein said connectivity determines how a device is connected to other devices, the network connection identification, and the number and type of connections to be employed on the device. | 0.924617 |
2. The method of claim 1 , wherein scanning for the keyword in the message involves using the content database for guidance and looking for surrounding text which indicates the presence of the activity-related keywords in the message. | 2. The method of claim 1 , wherein scanning for the keyword in the message involves using the content database for guidance and looking for surrounding text which indicates the presence of the activity-related keywords in the message. 3. The method of claim 2 , wherein looking for the surrounding text which indicates the presence of the activity-related keywords in the message involves looking for verbs which indicate specific types of activities in text surrounding prospective activity-related keywords in the message. | 0.856856 |
8. A computer-implemented method for editing, via a Web-based spreadsheet service, a parameter of a list of one or more parameters associated with a model represented by a spreadsheet document, the method comprising: requesting a Web-based spreadsheet server to transmit the spreadsheet document for rendering at a client to display the spreadsheet document on a display device, the spreadsheet document comprising a plurality of cells, wherein a first subset of cells of the plurality of cells comprises cells that are designated as parameters associated with the model and a second subset of cells of the plurality of cells comprises cells that are not designated as parameters associated with the model, and wherein each cell in the first subset of cells is designated to receive input from a user to apply to a calculation of the model, and each cell in the second subset of cells is not designated to receive input from the user; retrieving the list of one or more parameters associated with the model represented by the spreadsheet document, the list of one or more parameters including a name for each parameter and any comments associated with each parameter name, each parameter in the list of one or more parameters corresponding to a cell in the first subset of cells; and via a user interface component, receiving edits to at least one parameter of the list of one or more parameters associated with the model represented by the spreadsheet document, wherein each cell in the first subset of cells and each cell in the second subset of cells are both displayed in the UI component and each cell in the first subset is automatically displayed distinctly from each cell in the second subset of cells to indicate that each cell in the first subset of cells is designated to receive input from the user to apply to the calculation of the model. | 8. A computer-implemented method for editing, via a Web-based spreadsheet service, a parameter of a list of one or more parameters associated with a model represented by a spreadsheet document, the method comprising: requesting a Web-based spreadsheet server to transmit the spreadsheet document for rendering at a client to display the spreadsheet document on a display device, the spreadsheet document comprising a plurality of cells, wherein a first subset of cells of the plurality of cells comprises cells that are designated as parameters associated with the model and a second subset of cells of the plurality of cells comprises cells that are not designated as parameters associated with the model, and wherein each cell in the first subset of cells is designated to receive input from a user to apply to a calculation of the model, and each cell in the second subset of cells is not designated to receive input from the user; retrieving the list of one or more parameters associated with the model represented by the spreadsheet document, the list of one or more parameters including a name for each parameter and any comments associated with each parameter name, each parameter in the list of one or more parameters corresponding to a cell in the first subset of cells; and via a user interface component, receiving edits to at least one parameter of the list of one or more parameters associated with the model represented by the spreadsheet document, wherein each cell in the first subset of cells and each cell in the second subset of cells are both displayed in the UI component and each cell in the first subset is automatically displayed distinctly from each cell in the second subset of cells to indicate that each cell in the first subset of cells is designated to receive input from the user to apply to the calculation of the model. 9. A method according to claim 8 , further comprising: suspending calculation of the model until all information associated with the model is made current by one or more from the group consisting of: automatically obtaining the current information associated with the model and receiving the current information from a user via said edits. | 0.501451 |
14. The method of claim 13 , further comprising: detecting a second gesture; and in response to detecting the second gesture, stopping the translating of the text in the first language into text in the second language. | 14. The method of claim 13 , further comprising: detecting a second gesture; and in response to detecting the second gesture, stopping the translating of the text in the first language into text in the second language. 15. The method of claim 14 , wherein the second gesture is a gesture for changing an exposed surface on which the microphone is provided. | 0.855811 |
1. A method, in a data processing system comprising a processor and a memory, for identifying hidden meaning in a portion of natural language content, wherein the memory comprises instructions executed by the processor to cause the processor to be specifically configured to implement a hidden meaning translation engine, the method comprising: receiving, by the hidden meaning translation engine of the data processing system, a primary portion of natural language content from one or more corpora of electronic documentation; identifying, by the hidden meaning translation engine of data processing system, a secondary portion of natural language content, in the one or more corpora of electronic documentation, that references the primary portion of natural language content; analyzing, by the hidden meaning translation engine of data processing system, the secondary portion of natural language content to identify indications of meaning directed to elements of the primary portion of natural language content; generating, by the hidden meaning translation engine of data processing system, a probabilistic model based on results of the analysis of the secondary portion of natural language content modeling a probability of hidden meaning in the primary portion of natural language content; generating, by the hidden meaning translation engine of data processing system, a hidden meaning statement data structure for the primary portion of natural language content based on the probabilistic model; storing, by the hidden meaning translation engine of the data processing system, the hidden meaning statement data structure in association with the primary portion of natural language content in the one or more corpora of electronic documentation; and performing, by a cognitive system, a cognitive operation at least by performing natural language processing on a combination of the primary portion of natural language content and the hidden meaning statement data structure in the one or more corpora of electronic documentation, wherein analyzing the secondary portion of natural language content further comprises correlating a first temporal characteristic of the secondary portion of natural language content with a second temporal characteristic of the primary portion of natural language content, and wherein generating a probabilistic model further comprises weighting the secondary portion of natural language content based on whether the first temporal characteristic is at a prior time to the second temporal characteristic or at a later time than the second temporal characteristic. | 1. A method, in a data processing system comprising a processor and a memory, for identifying hidden meaning in a portion of natural language content, wherein the memory comprises instructions executed by the processor to cause the processor to be specifically configured to implement a hidden meaning translation engine, the method comprising: receiving, by the hidden meaning translation engine of the data processing system, a primary portion of natural language content from one or more corpora of electronic documentation; identifying, by the hidden meaning translation engine of data processing system, a secondary portion of natural language content, in the one or more corpora of electronic documentation, that references the primary portion of natural language content; analyzing, by the hidden meaning translation engine of data processing system, the secondary portion of natural language content to identify indications of meaning directed to elements of the primary portion of natural language content; generating, by the hidden meaning translation engine of data processing system, a probabilistic model based on results of the analysis of the secondary portion of natural language content modeling a probability of hidden meaning in the primary portion of natural language content; generating, by the hidden meaning translation engine of data processing system, a hidden meaning statement data structure for the primary portion of natural language content based on the probabilistic model; storing, by the hidden meaning translation engine of the data processing system, the hidden meaning statement data structure in association with the primary portion of natural language content in the one or more corpora of electronic documentation; and performing, by a cognitive system, a cognitive operation at least by performing natural language processing on a combination of the primary portion of natural language content and the hidden meaning statement data structure in the one or more corpora of electronic documentation, wherein analyzing the secondary portion of natural language content further comprises correlating a first temporal characteristic of the secondary portion of natural language content with a second temporal characteristic of the primary portion of natural language content, and wherein generating a probabilistic model further comprises weighting the secondary portion of natural language content based on whether the first temporal characteristic is at a prior time to the second temporal characteristic or at a later time than the second temporal characteristic. 4. The method of claim 1 , wherein generating the probabilistic model based on results of the analysis of the secondary portion of natural language content modeling a probability of hidden meaning in the primary portion of natural language content comprises generating one or more pairing data structures that pairs a secondary portion of natural language content with a corresponding primary portion of natural language content, wherein the secondary portion specifies a potential hidden meaning in the corresponding primary portion. | 0.5 |
8. A method comprising steps of: specifying a speech input with a speech-enabled markup; defining within said speech-enabled markup at least one operation of an application that is to be executed upon a detection of said specified speech input; associating said speech-enabled markup with a graphical user interface element of said application; after said defining and associating steps, instantiating said application; monitoring to determine whether said graphical user interface element receives focus; loading said speech-enabled markup into a markup interpreter and activating said speech-enabled markup if said graphical user interface element receives focus; monitoring audible input to determine whether said specified speech input is received when said speech-enabled markup is activated; executing said application operation if said specified speech input is received when said speech-enabled markup is activated; and deactivating said speech-enabled markup so that said application no longer monitors audible input for said specified speech input if said graphical user interface element loses focus. | 8. A method comprising steps of: specifying a speech input with a speech-enabled markup; defining within said speech-enabled markup at least one operation of an application that is to be executed upon a detection of said specified speech input; associating said speech-enabled markup with a graphical user interface element of said application; after said defining and associating steps, instantiating said application; monitoring to determine whether said graphical user interface element receives focus; loading said speech-enabled markup into a markup interpreter and activating said speech-enabled markup if said graphical user interface element receives focus; monitoring audible input to determine whether said specified speech input is received when said speech-enabled markup is activated; executing said application operation if said specified speech input is received when said speech-enabled markup is activated; and deactivating said speech-enabled markup so that said application no longer monitors audible input for said specified speech input if said graphical user interface element loses focus. 9. The method of claim 8 , wherein said application is a multimodal Web browser. | 0.650032 |
17. An apparatus according to claim 16, wherein said means for converting said subsequent element traces through a sub-element linked list containing said first element and a plurality of representations of said subsequent element and chooses said one of the plurality of said second representations of the subsequent element by choosing a first representation of said subsequent element which appears after said first element in said sub-element linked list. | 17. An apparatus according to claim 16, wherein said means for converting said subsequent element traces through a sub-element linked list containing said first element and a plurality of representations of said subsequent element and chooses said one of the plurality of said second representations of the subsequent element by choosing a first representation of said subsequent element which appears after said first element in said sub-element linked list. 18. An apparatus according to claim 17, wherein said subsequent element is a Standard Page Description Language STRCTID element. | 0.937442 |
20. The computer-implemented method of claim 19 , wherein the training comprises: processing each of the reference responses to determine for each reference response a first numerical measure indicative of a number of words and phrases of the reference response that are included verbatim in the source text, a second numerical measure indicative of (i) an amount of the reference response that paraphrases portions of the source text, or (ii) an amount of the reference response that is semantically-similar to portions of the source text, and a third numerical measure indicative of a similarity between sentences of the reference response and sentences of the source text; and conducting a numerical machine-learning analysis based on the first, second, and third numerical measures and classification for each of the plurality of reference responses to determine the first, second, and third weighting factors. | 20. The computer-implemented method of claim 19 , wherein the training comprises: processing each of the reference responses to determine for each reference response a first numerical measure indicative of a number of words and phrases of the reference response that are included verbatim in the source text, a second numerical measure indicative of (i) an amount of the reference response that paraphrases portions of the source text, or (ii) an amount of the reference response that is semantically-similar to portions of the source text, and a third numerical measure indicative of a similarity between sentences of the reference response and sentences of the source text; and conducting a numerical machine-learning analysis based on the first, second, and third numerical measures and classification for each of the plurality of reference responses to determine the first, second, and third weighting factors. 21. The computer-implemented method of claim 20 , wherein the determining of the third numerical measure for each reference response comprises: comparing each sentence of the reference response to each sentence of the source text in a sentence-to-sentence comparison, each of the comparisons generating a value indicative of a degree of similarity between the compared sentences; determining a first metric, the first metric being a maximum value of the generated values; determining a second metric, the second metric being an average of the generated values; determining a third metric, the determining of the third metric including (i) determining, for each sentence of the reference response, a maximum sentence value, wherein the maximum sentence value is a maximum value of a subset of the values, the subset including values generated based on the comparison of the sentence to the sentences of the source text, and (ii) determining an average of the maximum sentence values, the average of the maximum sentence values being the third metric. | 0.81071 |
3. The computer implemented method of claim 2 , wherein determining the feature set comprises: determining structural features of the features based on the structural paths of the structured communications of the cluster, the structural features indicating at least one of: hierarchical structure of the structural paths, and node types of the nodes of the structural paths. | 3. The computer implemented method of claim 2 , wherein determining the feature set comprises: determining structural features of the features based on the structural paths of the structured communications of the cluster, the structural features indicating at least one of: hierarchical structure of the structural paths, and node types of the nodes of the structural paths. 4. The computer implemented method of claim 3 , wherein determining the feature set comprises: determining term features of the features based on communication terms of the structured communications of the cluster; wherein one or more of the communication terms on which the term features are determined are in addition to the classification terms. | 0.884713 |
20. A system for displaying, at a user equipment device, video assets of interest to a user, comprising: a display displaying a mosaic page having a plurality of cells; and user equipment configured to: receive a selection from the user of a first of the plurality of cells; receive an input from the user specifying a criterion for the user selected first cell; for each of a plurality of video assets matching the user specified criterion, determine a score indicative of relevance of the respective video asset to the user by comparing historic or expressed user preferences with data associated with the respective video asset; filter the plurality of video assets to remove video assets having scores below a predetermined threshold value; select from the filtered plurality of video assets, for display in the user selected first cell, a video asset having the greatest score indicative of relevance to the user; and display the selected video asset in the user selected first cell on the display. | 20. A system for displaying, at a user equipment device, video assets of interest to a user, comprising: a display displaying a mosaic page having a plurality of cells; and user equipment configured to: receive a selection from the user of a first of the plurality of cells; receive an input from the user specifying a criterion for the user selected first cell; for each of a plurality of video assets matching the user specified criterion, determine a score indicative of relevance of the respective video asset to the user by comparing historic or expressed user preferences with data associated with the respective video asset; filter the plurality of video assets to remove video assets having scores below a predetermined threshold value; select from the filtered plurality of video assets, for display in the user selected first cell, a video asset having the greatest score indicative of relevance to the user; and display the selected video asset in the user selected first cell on the display. 36. The system of claim 20 , wherein the user equipment is configured to make information about the mosaic page on a first user device available on a second different user device. | 0.584935 |
1. A speech translation system comprising: a first terminal device comprising a first speech input for inputting a first speech of a first language spoken by a first user, and converting the first speech to a first speech signal; a second terminal device comprising a second speech input for inputting a second speech of a second language spoken by a second user, and converting the second speech to a second speech signal; a speech recognition device that receives the first speech signal and the second speech signal, recognizes the first speech signal to a first recognized text, and recognizes the second speech signal to a second recognized text; a machine translation device that receives the first recognized text and the second recognized text, translates the first recognized text to a first translated text of the second language, and translates the second recognized text to a second translated text of the first language; a control device; wherein the first terminal device receives (a) a first text set of the first language being the first recognized text and the second translated text, and (b) a second text set of the second language being the second recognized text and the first translated text, and comprises a first display unit that displays the first text set and the second text set; and the second terminal device receives at least one text of the second text set, and comprises a second display unit that displays the at least one text of the second text set; a third terminal device comprising a third speech input for inputting a third speech of a third language spoken by a third user, and converting the third speech to a third speech signal; the speech recognition device receives the third speech signal, and recognizes the third speech signal to a third recognized text; the machine translation device receives the third recognized text and the first recognized text, further comprises a third machine translation unit that translates the third recognized text to the third translated text of the first language, and translates the first recognized text to the fourth translated text of the third language; the first display unit displays (a) at least one text set of the second text set and a third text set of the third language being the third recognized text and the fourth translated text, and (b) the fourth text set of the first language being the first text set and the third translated text; and the third terminal device further comprises the third display unit that displays at least one text of the third text set. | 1. A speech translation system comprising: a first terminal device comprising a first speech input for inputting a first speech of a first language spoken by a first user, and converting the first speech to a first speech signal; a second terminal device comprising a second speech input for inputting a second speech of a second language spoken by a second user, and converting the second speech to a second speech signal; a speech recognition device that receives the first speech signal and the second speech signal, recognizes the first speech signal to a first recognized text, and recognizes the second speech signal to a second recognized text; a machine translation device that receives the first recognized text and the second recognized text, translates the first recognized text to a first translated text of the second language, and translates the second recognized text to a second translated text of the first language; a control device; wherein the first terminal device receives (a) a first text set of the first language being the first recognized text and the second translated text, and (b) a second text set of the second language being the second recognized text and the first translated text, and comprises a first display unit that displays the first text set and the second text set; and the second terminal device receives at least one text of the second text set, and comprises a second display unit that displays the at least one text of the second text set; a third terminal device comprising a third speech input for inputting a third speech of a third language spoken by a third user, and converting the third speech to a third speech signal; the speech recognition device receives the third speech signal, and recognizes the third speech signal to a third recognized text; the machine translation device receives the third recognized text and the first recognized text, further comprises a third machine translation unit that translates the third recognized text to the third translated text of the first language, and translates the first recognized text to the fourth translated text of the third language; the first display unit displays (a) at least one text set of the second text set and a third text set of the third language being the third recognized text and the fourth translated text, and (b) the fourth text set of the first language being the first text set and the third translated text; and the third terminal device further comprises the third display unit that displays at least one text of the third text set. 4. The system according to claim 1 , wherein the first terminal device further comprises a first display selection unit that receives a selection of text from the first text set and the second text set displayed on the first display unit; the control device comprises a first display control unit that controls displaying at least one text of the second text set on the second display unit, if the first display selection unit receives the selection. | 0.591486 |
5. The method of claim 1 , further comprising: receiving a request to change a font attribute of a selected portion of the second web document; and creating in the web browser a third web document from the second web document, wherein the font attribute, within the third web document, of the selected portion is changed in response to receiving the request to change the font attribute of the selected portion. | 5. The method of claim 1 , further comprising: receiving a request to change a font attribute of a selected portion of the second web document; and creating in the web browser a third web document from the second web document, wherein the font attribute, within the third web document, of the selected portion is changed in response to receiving the request to change the font attribute of the selected portion. 6. The method of claim 5 , further comprising: receiving a request to display page break indicators within the third web document; identifying page break information for the third web document for an output device; and creating in the web browser a fourth web document from the third web document, wherein at least one virtual page break indicator is inserted into the fourth web document, in response to the page break information, to indicate the location of page breaks. | 0.755196 |
1. A computer-implemented method for training a specialized recognition engine to recognize a preselected attribute of a facial image, the specialized recognition engine specialized for a range of head poses, the method comprising: for each of a plurality of facial images of heads that are within the range of head poses for the specialized recognition engine: identifying a pair comprising a known good facial image and a known good specialized recognition metric, wherein the known good facial image is for a same head as said facial image and has the same preselected attribute as said facial image but for a head pose within a range of head poses that is different than the range of head poses for the specialized recognition engine, and the known good specialized recognition metric is indicative of the preselected attribute of the known good facial image; and associating a specialized recognition metric with said facial image, wherein the specialized recognition metric is derived from the known good specialized recognition metric; and training the specialized recognition engine by using pairs comprising the plurality of facial images and the associated specialized recognition metrics as a training set for supervised learning. | 1. A computer-implemented method for training a specialized recognition engine to recognize a preselected attribute of a facial image, the specialized recognition engine specialized for a range of head poses, the method comprising: for each of a plurality of facial images of heads that are within the range of head poses for the specialized recognition engine: identifying a pair comprising a known good facial image and a known good specialized recognition metric, wherein the known good facial image is for a same head as said facial image and has the same preselected attribute as said facial image but for a head pose within a range of head poses that is different than the range of head poses for the specialized recognition engine, and the known good specialized recognition metric is indicative of the preselected attribute of the known good facial image; and associating a specialized recognition metric with said facial image, wherein the specialized recognition metric is derived from the known good specialized recognition metric; and training the specialized recognition engine by using pairs comprising the plurality of facial images and the associated specialized recognition metrics as a training set for supervised learning. 16. The computer-implemented method of claim 1 wherein the specialized recognition metric comprises a confidence level of occurrence of the preselected attribute in said facial image. | 0.57971 |
12. An apparatus for generating a suggested personalized reaction, the apparatus comprising: one or more processors; a collector module, stored on a memory and executable by the one or more processors, for collecting interaction items accessible to a first user from an electronic communication system, the interaction items including an online user post and a user reaction, the collector module coupled to receive interaction items from the electronic communication system; a suggestion analyzer module for processing the collected interaction items to produce one or more labels for the collected interaction items, ranking each collected interaction item based on the labels and the first user's prior reactions to other interaction items and the respective labels of the first user's prior reactions, determining that the online user post satisfies a threshold likelihood of being important or interesting to the first user, and automatically generating a suggested personalized reaction to online user post on behalf of the first user, the suggested personalized reaction based on the one or more labels associated with online user post; and a user interface module for presenting the suggested personalized reaction and related information and for receiving input from the first user, the user interface module coupled to receive the suggested personalized reaction from the suggestion analyzer module, the user interface module configured to receive input from the first user. | 12. An apparatus for generating a suggested personalized reaction, the apparatus comprising: one or more processors; a collector module, stored on a memory and executable by the one or more processors, for collecting interaction items accessible to a first user from an electronic communication system, the interaction items including an online user post and a user reaction, the collector module coupled to receive interaction items from the electronic communication system; a suggestion analyzer module for processing the collected interaction items to produce one or more labels for the collected interaction items, ranking each collected interaction item based on the labels and the first user's prior reactions to other interaction items and the respective labels of the first user's prior reactions, determining that the online user post satisfies a threshold likelihood of being important or interesting to the first user, and automatically generating a suggested personalized reaction to online user post on behalf of the first user, the suggested personalized reaction based on the one or more labels associated with online user post; and a user interface module for presenting the suggested personalized reaction and related information and for receiving input from the first user, the user interface module coupled to receive the suggested personalized reaction from the suggestion analyzer module, the user interface module configured to receive input from the first user. 16. The apparatus of claim 12 further comprising a credentials module for receiving, storing and providing credentials related to the first user's access of the electronic communication system, the credentials module coupled to receive input from the first user and coupled to provide information to the collector module. | 0.50463 |
2. The system of claim 1 , wherein said templates have at least one content marker for locating data within said formatted content. | 2. The system of claim 1 , wherein said templates have at least one content marker for locating data within said formatted content. 3. The system of claim 2 , wherein said content marker has an identifier for identifying data within said formatted content. | 0.980178 |
1. A system, comprising: a citation search engine including a processor, which in operation, retrieves a plurality of citations each composed by one of a plurality of subjects citing one or more of a plurality of objects that fit searching criteria, wherein a citation is an online posting of an opinion of an object by a subject; an object selection engine coupled to the citation search engine and including a processor, which in operation, identifies one or more attributes associated with the citations, determines a selection and ranking of objects cited by the citations, uses one or more attributes as a filter to select objects, identified attributes being transferred from one entity to other search entities, the transferred attributes facilitating a selection and ranking of cited targets for a search result, transfers the identified attributes from the citations where the attributes are available to the one or more objects, and selects the objects as a search result based on the matching of the search criteria with the attributes transferred to the objects from the citations; and an influence evaluation engine that calculates influence scores of entities that determine a ranking of any subset of objects obtained from the plurality of citations, and the influence evaluation engine, which in operation, calculates influence scores of the plurality of subjects that compose the plurality of citations citing the plurality of objects, wherein the citation search engine enables a citation centric search process that focuses on influence of the plurality subjects that cite the plurality of objects. | 1. A system, comprising: a citation search engine including a processor, which in operation, retrieves a plurality of citations each composed by one of a plurality of subjects citing one or more of a plurality of objects that fit searching criteria, wherein a citation is an online posting of an opinion of an object by a subject; an object selection engine coupled to the citation search engine and including a processor, which in operation, identifies one or more attributes associated with the citations, determines a selection and ranking of objects cited by the citations, uses one or more attributes as a filter to select objects, identified attributes being transferred from one entity to other search entities, the transferred attributes facilitating a selection and ranking of cited targets for a search result, transfers the identified attributes from the citations where the attributes are available to the one or more objects, and selects the objects as a search result based on the matching of the search criteria with the attributes transferred to the objects from the citations; and an influence evaluation engine that calculates influence scores of entities that determine a ranking of any subset of objects obtained from the plurality of citations, and the influence evaluation engine, which in operation, calculates influence scores of the plurality of subjects that compose the plurality of citations citing the plurality of objects, wherein the citation search engine enables a citation centric search process that focuses on influence of the plurality subjects that cite the plurality of objects. 2. The system of claim 1 , wherein: each of the plurality of subjects has an opinion wherein expression of the opinion is explicit, expressed, implicit, or imputed through any other technique. | 0.576271 |
18. A computer-implementable method for reconciling names of enterprise computer resources, said computer-implementable method comprising: determining if a resource, which is an enterprise computer resource managed by a configuration management database (CMDB), belongs to a class of resources that comprises multiple prioritized different, valid names, wherein the valid names are assigned by the CMDB to have a validity priority order based upon a prioritized naming rule of multiple prioritized naming rules used to create each valid name in response to determining that more than one set of naming attributes is provided by the multiple prioritized naming rules; and in response to determining that the resource belongs to the class of resources that comprises the multiple prioritized different, valid names, delegating one of the valid names to be a master name for the resource, and delegating any remaining valid names to be alias names for the resource. | 18. A computer-implementable method for reconciling names of enterprise computer resources, said computer-implementable method comprising: determining if a resource, which is an enterprise computer resource managed by a configuration management database (CMDB), belongs to a class of resources that comprises multiple prioritized different, valid names, wherein the valid names are assigned by the CMDB to have a validity priority order based upon a prioritized naming rule of multiple prioritized naming rules used to create each valid name in response to determining that more than one set of naming attributes is provided by the multiple prioritized naming rules; and in response to determining that the resource belongs to the class of resources that comprises the multiple prioritized different, valid names, delegating one of the valid names to be a master name for the resource, and delegating any remaining valid names to be alias names for the resource. 33. The computer-implementable method of claim 18 , where delegating one of the valid names to be the master name for the resource, and delegating any remaining valid names to be alias names for the resource comprises delegating the valid name with a highest priority based upon the validity priority order to be the master name for the resource, and delegating any remaining valid names to be alias names for the resource. | 0.5 |
18. A method for performing speech recognition, the method comprising: (a) providing a vocabulary management software instance for creating, editing, and organizing vocabulary sets for voice recognition, wherein the vocabulary management software instance limits data rendered from a data source to a user; (b) creating a vocabulary set using the software, the vocabulary set containing a portion of available vocabulary words specific to and associated with a data source to be used in dialog creation by the voice application; (c) configuring the voice application to use the created vocabulary set when a speech recognition portion of the application is triggered; (d) configuring the voice application to provide user-specific voice recognition options for each user, wherein the user-specific voice recognition options restrict voice recognition options to options associated with both the user and a specific activity being performed by the user; and (e) deploying the voice application to execution. | 18. A method for performing speech recognition, the method comprising: (a) providing a vocabulary management software instance for creating, editing, and organizing vocabulary sets for voice recognition, wherein the vocabulary management software instance limits data rendered from a data source to a user; (b) creating a vocabulary set using the software, the vocabulary set containing a portion of available vocabulary words specific to and associated with a data source to be used in dialog creation by the voice application; (c) configuring the voice application to use the created vocabulary set when a speech recognition portion of the application is triggered; (d) configuring the voice application to provide user-specific voice recognition options for each user, wherein the user-specific voice recognition options restrict voice recognition options to options associated with both the user and a specific activity being performed by the user; and (e) deploying the voice application to execution. 26. The method of claim 18 wherein in step (e) the voice application is stored for execution in the voice application server. | 0.572218 |
15. A computer program product, comprising: a non-transitory computer-readable storage medium having computer-readable program code embodied therewith, the computer-readable program code executable by one or more computer processors to perform an operation comprising: receiving, by a question answering system, a case from a user; assigning a first level of user sophistication, of a plurality of levels of user sophistication, to the user; determining a level of evidence sophistication, of a plurality of levels of evidence sophistication, associated with each of a plurality of items of supporting evidence in a corpus of information used to process the case; selecting a subset of the plurality of items of supporting evidence based on the determined levels of user sophistication and evidence sophistication; and returning the selected subset to the user as part of a response to the case. | 15. A computer program product, comprising: a non-transitory computer-readable storage medium having computer-readable program code embodied therewith, the computer-readable program code executable by one or more computer processors to perform an operation comprising: receiving, by a question answering system, a case from a user; assigning a first level of user sophistication, of a plurality of levels of user sophistication, to the user; determining a level of evidence sophistication, of a plurality of levels of evidence sophistication, associated with each of a plurality of items of supporting evidence in a corpus of information used to process the case; selecting a subset of the plurality of items of supporting evidence based on the determined levels of user sophistication and evidence sophistication; and returning the selected subset to the user as part of a response to the case. 19. The computer program product of claim 15 , wherein the first level of user sophistication of the user is further assigned based on a role of the user. | 0.739508 |
16. A computer program product, comprising: a non-transitory computer readable storage device storing computer program instructions which, when processed by a computer system including at least one processor and a computer memory, enable the at least one processor to: access the non-transitory computer readable storage in which data are stored, the data including data identifying entities described in a document, wherein the document includes a plurality of tokens appearing in an order in the document, and data defining sentiment values assigned to the tokens in the document, and process, using the at least one processor, the data in the non-transitory computer readable storage to assign a sentiment value to one of the identified entities in the document by applying a filter to a sequence of the sentiment values corresponding to a sequence of the tokens in the order the tokens appear in the document, the filter having a width defined by a number of tokens, the entity having a position in the sequence of tokens, the filter providing a combination of contributions of the sentiment values associated with the tokens surrounding the position of the entity in the document within the width of the filter. | 16. A computer program product, comprising: a non-transitory computer readable storage device storing computer program instructions which, when processed by a computer system including at least one processor and a computer memory, enable the at least one processor to: access the non-transitory computer readable storage in which data are stored, the data including data identifying entities described in a document, wherein the document includes a plurality of tokens appearing in an order in the document, and data defining sentiment values assigned to the tokens in the document, and process, using the at least one processor, the data in the non-transitory computer readable storage to assign a sentiment value to one of the identified entities in the document by applying a filter to a sequence of the sentiment values corresponding to a sequence of the tokens in the order the tokens appear in the document, the filter having a width defined by a number of tokens, the entity having a position in the sequence of tokens, the filter providing a combination of contributions of the sentiment values associated with the tokens surrounding the position of the entity in the document within the width of the filter. 19. The computer program product of claim 16 , wherein the data identifying entities comprises a first ordered array of tokens from the document and data, for each entity, defining boundaries of the entity in the first ordered array, wherein the data defining sentiment values assigned to tokens in the document comprises a second ordered array of sentiment values, and wherein the order of the sentiment values corresponds to the order of the tokens so as to associate the sentiment values with the tokens. | 0.5 |
1. A computer-implemented method for accessing content items in a content store comprising: maintaining a text index of content items in a content store to enable a keyword search on the content items; receiving a query having a keyword and generating a hit list from the text index using the keyword, the hit list comprising two or more content items of the content store; extracting frequent phrases from text within content items of the hit list by estimating an intersection size, wherein the estimating comprises executing an algorithm to intersect a first posting list generated from globally frequent phrases with a second posting list generated from the hit list, wherein the algorithm terminates the executing in response to the earlier of identifying a predetermined M maximum number of comparisons or a predetermined I maximum number of common points; assigning a relative relevance to the frequent phrases wherein frequent phrases having a relatively high relevance are relevant phrases; and grouping content items into topics based on presence of relevant phrases within the content items of the hit list. | 1. A computer-implemented method for accessing content items in a content store comprising: maintaining a text index of content items in a content store to enable a keyword search on the content items; receiving a query having a keyword and generating a hit list from the text index using the keyword, the hit list comprising two or more content items of the content store; extracting frequent phrases from text within content items of the hit list by estimating an intersection size, wherein the estimating comprises executing an algorithm to intersect a first posting list generated from globally frequent phrases with a second posting list generated from the hit list, wherein the algorithm terminates the executing in response to the earlier of identifying a predetermined M maximum number of comparisons or a predetermined I maximum number of common points; assigning a relative relevance to the frequent phrases wherein frequent phrases having a relatively high relevance are relevant phrases; and grouping content items into topics based on presence of relevant phrases within the content items of the hit list. 9. The computer-implemented method of claim 1 , further comprising: maintaining a priority queue of the top-k most frequent phrases while intersecting the hit list with the globally frequent phrases, wherein the estimating comprises: randomizing the globally frequent phrases in the text index to produce the first randomized posting list; and randomizing the hit list to produce the second randomized posting list, wherein the algorithm is a modified zipper algorithm. | 0.541511 |
17. The computer readable storage medium of claim 16 , wherein the one or more processors are further configured to: receive, via the graphical user interface, an indication of a new interval and a mathematical operation; apply the mathematical operation to the determined data objects; re-generate the plurality of two-dimensional graphs such that: at least one of the first common interval or the second common interview corresponds to the new interval; and at least one of the x-axis or the y-axis of each of the two-dimensional graphs represents an output of the applied mathematical operation; and update the graphical user interface to display the single graphical user interface view including the re-generated two-dimensional graphs. | 17. The computer readable storage medium of claim 16 , wherein the one or more processors are further configured to: receive, via the graphical user interface, an indication of a new interval and a mathematical operation; apply the mathematical operation to the determined data objects; re-generate the plurality of two-dimensional graphs such that: at least one of the first common interval or the second common interview corresponds to the new interval; and at least one of the x-axis or the y-axis of each of the two-dimensional graphs represents an output of the applied mathematical operation; and update the graphical user interface to display the single graphical user interface view including the re-generated two-dimensional graphs. 18. The computer readable storage medium of claim 17 , wherein the received mathematical operation includes an indication of a property associated with the determined data objects. | 0.887621 |
1. A computer-implemented method, comprising: receiving, with a processor of a computer, a message before the message is posted to a social media service; analyzing, with the processor of the computer, the message using data analytics to obtain analysis results; comparing, with the processor of the computer, the obtained analysis results to similar analysis results stored for pre-existing messages to identify one or more strong correlations among correlations between the message and the pre-existing messages; for each of the one or more strong correlations, determining, with the processor of the computer, one or more contributing terms that have semantic meaning within a context of the social media service based on translating terms in the message to terms that represent an intended meaning of those terms; based on the one or more contributing terms, generating, with the processor of the computer, one or more suggestions for improving the message; modifying, with the processor of the computer, the message based on the one or more suggestions; and determining, with the processor of the computer, whether to further analyze the modified message based on certain factors. | 1. A computer-implemented method, comprising: receiving, with a processor of a computer, a message before the message is posted to a social media service; analyzing, with the processor of the computer, the message using data analytics to obtain analysis results; comparing, with the processor of the computer, the obtained analysis results to similar analysis results stored for pre-existing messages to identify one or more strong correlations among correlations between the message and the pre-existing messages; for each of the one or more strong correlations, determining, with the processor of the computer, one or more contributing terms that have semantic meaning within a context of the social media service based on translating terms in the message to terms that represent an intended meaning of those terms; based on the one or more contributing terms, generating, with the processor of the computer, one or more suggestions for improving the message; modifying, with the processor of the computer, the message based on the one or more suggestions; and determining, with the processor of the computer, whether to further analyze the modified message based on certain factors. 2. The method of claim 1 , wherein the one or more suggestions are provided as a ranked list of improvements to the message based on strengths of the one or more correlations. | 0.722397 |
1. A method performed by one or more computers, the method comprising: receiving, by the one or more computers, a request from a client device for media content, the request including at least a portion of a first media item or a URL corresponding to the first media item, the first media item including speech of a person; based on the data indicating the first media item, selecting, by the one or more computers, one or more other media items based on one or more representations of acoustic characteristics of the one or more other media items, wherein the one or more representations of acoustic characteristics of the one or more other media items comprise, for each of the one or more other media items, a speaker representation that includes (i) an i-vector or d-vector generated from the other media item, or (ii) a hash of an i-vector or d-vector generated from the other media item; wherein each of the one or more other media items is selected based on a comparison of (i) an i-vector, d-vector or hash determined from speech in the first media item with (ii) the speaker representation for the other media item, wherein: each of the selected one or more other media items is different from the first media item; each of the selected one or more other media items includes speech of the same person whose speech is included in the first media item; and each of the selected one or more other media items is determined, based on the acoustic characteristics of the media item, to include speech demonstrating speaker characteristics that have at least a threshold level of similarity with speaker characteristics determined from speech in the first media item; generating, by the one or more computers, data indicating the selected one or more other media items that are each different from the first media item and that each include speech of the same person whose speech is included in the first media item; and providing, by the one or more computers and to the client device, a response to the request that includes the data indicating the selected one or more other media items that are each different from the first media item and that each include speech of the same person whose speech is included in the first media item. | 1. A method performed by one or more computers, the method comprising: receiving, by the one or more computers, a request from a client device for media content, the request including at least a portion of a first media item or a URL corresponding to the first media item, the first media item including speech of a person; based on the data indicating the first media item, selecting, by the one or more computers, one or more other media items based on one or more representations of acoustic characteristics of the one or more other media items, wherein the one or more representations of acoustic characteristics of the one or more other media items comprise, for each of the one or more other media items, a speaker representation that includes (i) an i-vector or d-vector generated from the other media item, or (ii) a hash of an i-vector or d-vector generated from the other media item; wherein each of the one or more other media items is selected based on a comparison of (i) an i-vector, d-vector or hash determined from speech in the first media item with (ii) the speaker representation for the other media item, wherein: each of the selected one or more other media items is different from the first media item; each of the selected one or more other media items includes speech of the same person whose speech is included in the first media item; and each of the selected one or more other media items is determined, based on the acoustic characteristics of the media item, to include speech demonstrating speaker characteristics that have at least a threshold level of similarity with speaker characteristics determined from speech in the first media item; generating, by the one or more computers, data indicating the selected one or more other media items that are each different from the first media item and that each include speech of the same person whose speech is included in the first media item; and providing, by the one or more computers and to the client device, a response to the request that includes the data indicating the selected one or more other media items that are each different from the first media item and that each include speech of the same person whose speech is included in the first media item. 2. The method of claim 1 , wherein receiving the request comprises receiving a request that includes a URL that corresponds to (i) a video that includes speech of the person, or (ii) an audio recording that includes speech of the person. | 0.550562 |
16. A search module for information searches using a computer device associated with an information presentation area, wherein said search module comprises: a search module GUI client configured to: display a search window on the presentation area, the search window comprising at least one field for: presenting search parameters including gaze search parameters and non gaze search parameters for a user, the gaze search parameters: representing a predefined set of specific mental conditions experienced by the user when the user viewed presented information during a certain period of time prior to displaying the search window; and being based on at least one of a duration of blinks and a pupil size of the user measured during the certain period of time when the user viewed the presented information; and displaying the gaze search parameters as selectable posts in the search window, the selectable posts comprising labels corresponding to the predefined set of specific mental conditions; and provide signals corresponding to specific query searches to a search engine for execution of the specific query searches on the computer device and/or on information hosts connectable to the computer device via networks, by using a selected combination of at least one of the gaze search parameters and at least one of the non gaze search parameters. | 16. A search module for information searches using a computer device associated with an information presentation area, wherein said search module comprises: a search module GUI client configured to: display a search window on the presentation area, the search window comprising at least one field for: presenting search parameters including gaze search parameters and non gaze search parameters for a user, the gaze search parameters: representing a predefined set of specific mental conditions experienced by the user when the user viewed presented information during a certain period of time prior to displaying the search window; and being based on at least one of a duration of blinks and a pupil size of the user measured during the certain period of time when the user viewed the presented information; and displaying the gaze search parameters as selectable posts in the search window, the selectable posts comprising labels corresponding to the predefined set of specific mental conditions; and provide signals corresponding to specific query searches to a search engine for execution of the specific query searches on the computer device and/or on information hosts connectable to the computer device via networks, by using a selected combination of at least one of the gaze search parameters and at least one of the non gaze search parameters. 21. The search module according to claim 16 , wherein the gaze search parameters reflect a reading pattern of the user when reading the presented information, the gaze search parameters allowing the user to define a specific query search by selecting whether to include or exclude a specific gaze search parameter in the specific query search. | 0.621552 |
7. A computer-implemented method for creating a UML model of a user interface environment, comprising: defining use cases within the UML model, wherein the use cases are independent of each other; associating an affinity representing a user-perceived relationship between use cases within the UML model, wherein the affinity is directional from an affinity use case to a target use case; assigning a weight to the affinity within the UML model, wherein the assigning the weight assigns a first weight that dictates a strength of the affinity from a first use case to a second use case and assigns a second, separate weight that dictates a strength of the affinity from the second use case to the first use case; incorporate affinity data into the UML model to influence use cases to be displayed in the user interface environment, wherein the affinity data includes assigned weights; and determine whether the affinity use case should be appeared on a selected display type based on the affinity data. | 7. A computer-implemented method for creating a UML model of a user interface environment, comprising: defining use cases within the UML model, wherein the use cases are independent of each other; associating an affinity representing a user-perceived relationship between use cases within the UML model, wherein the affinity is directional from an affinity use case to a target use case; assigning a weight to the affinity within the UML model, wherein the assigning the weight assigns a first weight that dictates a strength of the affinity from a first use case to a second use case and assigns a second, separate weight that dictates a strength of the affinity from the second use case to the first use case; incorporate affinity data into the UML model to influence use cases to be displayed in the user interface environment, wherein the affinity data includes assigned weights; and determine whether the affinity use case should be appeared on a selected display type based on the affinity data. 9. The computer-implemented method of claim 7 , wherein the affinity data provides a title for a use case when the use case appears as an affinity use case for a target use case. | 0.75 |
2. The method of claim 1 , wherein constructing a statistical classifier comprises applying smoothing to parameters θ ky and θ ky , which comprises calculating an interpolation weight λ for each class y based on sentence count #. | 2. The method of claim 1 , wherein constructing a statistical classifier comprises applying smoothing to parameters θ ky and θ ky , which comprises calculating an interpolation weight λ for each class y based on sentence count #. 4. The method of claim 2 , wherein constructing a statistical classifier further comprises applying convergence speed-up. | 0.932634 |
4. A query processor in accordance with claim 3, further comprising meta-data means for generating seventh signals indicative of the structures of the database engines and the data accessible by them, wherein said translator means further comprises semantic analyzer means for comparing said sixth signals and said seventh signals, and producing therefrom eighth signals indicative of said input query only if the structures of the database engines and the data accessible by them are compatible with the input query, said translator means further processing said eighth signals to produce said second signals. | 4. A query processor in accordance with claim 3, further comprising meta-data means for generating seventh signals indicative of the structures of the database engines and the data accessible by them, wherein said translator means further comprises semantic analyzer means for comparing said sixth signals and said seventh signals, and producing therefrom eighth signals indicative of said input query only if the structures of the database engines and the data accessible by them are compatible with the input query, said translator means further processing said eighth signals to produce said second signals. 5. A query processor in accordance with claim 4, wherein said translator means further comprises normalizer means for receiving said eighth signals and producing therefrom, ninth signals corresponding to said input query cast in terms of base tables and without references to views, said translator means further processing said ninth signals to produce said second signals. | 0.668861 |
7. A computer system for performing rapid, multi-dimensional word searches comprising: storage means for storing one or more objects, the objects comprising a plurality of words; input means for specifying a search query and a search space, the search query comprising a multi-dimensional combination of words and attributes, the search space identifying one or more objects; parser means for creating a data structure based on the search query, the data structure comprising: a lead character table for partially recognizing the words contained in the search query; a word table for storing at least the words contained in the search query; an operator table for storing in post-fix order at least the words contained in the search query and the attributes specifying one or more boolean operators contained in the search query; and a granularity table for storing at least the attributes specifying one or more granularity restrictions contained in the search query, the granularity restrictions requiring the words to appear within one or more granularity boundaries; evaluating means for creating a list of target objects based on the data structure and the search space, the list of target objects consisting of objects from the search space which satisfy the search query; and output means for displaying the list of target objects. | 7. A computer system for performing rapid, multi-dimensional word searches comprising: storage means for storing one or more objects, the objects comprising a plurality of words; input means for specifying a search query and a search space, the search query comprising a multi-dimensional combination of words and attributes, the search space identifying one or more objects; parser means for creating a data structure based on the search query, the data structure comprising: a lead character table for partially recognizing the words contained in the search query; a word table for storing at least the words contained in the search query; an operator table for storing in post-fix order at least the words contained in the search query and the attributes specifying one or more boolean operators contained in the search query; and a granularity table for storing at least the attributes specifying one or more granularity restrictions contained in the search query, the granularity restrictions requiring the words to appear within one or more granularity boundaries; evaluating means for creating a list of target objects based on the data structure and the search space, the list of target objects consisting of objects from the search space which satisfy the search query; and output means for displaying the list of target objects. 8. The computer system of claim 7 wherein the search query limits the word search of the search space to one or more specified fields within the objects in the search space. | 0.5 |
1. A method comprising: analyzing contents of a plurality of documents to identify, for each document, document elements and their respective placements within the document; ascertaining topics of at least some of the document elements based on keyword occurrences in the respective document elements; in an electronic data repository, storing individually addressable database entries for the identified document elements, each database entry comprising a unique document-element identifier, and storing the ascertained topics in association with the respective document elements; and using one or more computer processors, tracking, at sub-document level, user interactions with the document elements and storing, for each of the interactions, at least the document-element identifier of the document element interacted with and an identifier of the interacting user; and determining, for each of at least some of the interacting users, at least one of an interest or a field of expertise based at least in part on the tracked user interactions of that user and the topics associated with the interacted-with document elements, and for at least one of the interacting users, recommending at least one of content or another user to the interacting user based on the determined field of interest or expertise. | 1. A method comprising: analyzing contents of a plurality of documents to identify, for each document, document elements and their respective placements within the document; ascertaining topics of at least some of the document elements based on keyword occurrences in the respective document elements; in an electronic data repository, storing individually addressable database entries for the identified document elements, each database entry comprising a unique document-element identifier, and storing the ascertained topics in association with the respective document elements; and using one or more computer processors, tracking, at sub-document level, user interactions with the document elements and storing, for each of the interactions, at least the document-element identifier of the document element interacted with and an identifier of the interacting user; and determining, for each of at least some of the interacting users, at least one of an interest or a field of expertise based at least in part on the tracked user interactions of that user and the topics associated with the interacted-with document elements, and for at least one of the interacting users, recommending at least one of content or another user to the interacting user based on the determined field of interest or expertise. 8. The method of claim 1 , further comprising further storing, for each of the interactions, at least one of a duration of interaction or a type of interaction, and weighting different types of interaction or different durations of interaction differently in determining the interest or fields of expertise of the at least some of the interacting users. | 0.569454 |
1. A computer readable storage medium encoded with a first data structure and a second data structure, comprising: a first parameter definition for a first input parameter, the first parameter definition to enable identification of an appropriate first input for the first input parameter, wherein the first parameter definition is a declared property of the first data structure; a second parameter definition for a second input parameter, the second parameter definition to enable identification of an appropriate second input for the second input parameter, wherein the second parameter definition is a declared property of the second data structure; and an instruction-based mechanism to use the first parameter definition to identify the appropriate first input for the first input parameter, and use the second parameter definition to identify the appropriate second input for the second input parameter, wherein the instruction-based mechanism is to further enable the first data structure to process the first input parameter based on the appropriate first input identified from an input source to output an object, and provide the object as an input for the second data structure to be processed by the second data structure by passing a reference of the object to the second data structure, and the instruction-based mechanism is to further enable the second data structure to process the second input parameter based on the appropriate second input identified from the input source, when the first and second data structures become instantiated into objects. | 1. A computer readable storage medium encoded with a first data structure and a second data structure, comprising: a first parameter definition for a first input parameter, the first parameter definition to enable identification of an appropriate first input for the first input parameter, wherein the first parameter definition is a declared property of the first data structure; a second parameter definition for a second input parameter, the second parameter definition to enable identification of an appropriate second input for the second input parameter, wherein the second parameter definition is a declared property of the second data structure; and an instruction-based mechanism to use the first parameter definition to identify the appropriate first input for the first input parameter, and use the second parameter definition to identify the appropriate second input for the second input parameter, wherein the instruction-based mechanism is to further enable the first data structure to process the first input parameter based on the appropriate first input identified from an input source to output an object, and provide the object as an input for the second data structure to be processed by the second data structure by passing a reference of the object to the second data structure, and the instruction-based mechanism is to further enable the second data structure to process the second input parameter based on the appropriate second input identified from the input source, when the first and second data structures become instantiated into objects. 16. The computer readable storage medium of claim 1 , wherein at least one of the first and second input parameters is a public parameter. | 0.52781 |
16. The method of claim 14 , wherein the step of generating prescriptions further comprises the step of generating size and conceptual prescriptions for removing size and conceptual defects from software system. | 16. The method of claim 14 , wherein the step of generating prescriptions further comprises the step of generating size and conceptual prescriptions for removing size and conceptual defects from software system. 19. The method of claim 16 , wherein the step of generating size and conceptual prescriptions for removing size and conceptual defects comprises the steps of: i. selecting a conceptually non-cohesive module; ii. determining whether the non-cohesive module has dominant concepts; iii. determining whether the non-cohesive module is a utility module, if non cohesive module does not have dominant concepts; iv. reporting to the user, if the non-cohesive module is not a utility module; v. determining whether the non-cohesive module has size defect, if non-cohesive module has dominant concepts; vi. applying split module strategy, if the non-cohesive module has size defect; vii. determining whether the non-cohesive module has conceptually divergent methods, if the non-cohesive module does not have size defect; viii. selecting conceptually non-cohesive method, if the module has conceptually divergent concepts; ix. applying strategy to move method; and x. generating and filtering size and conceptual prescriptions. | 0.774329 |
13. A computer system executing instructions set forth in a computer program, the computer system comprising: a processor; and a memory coupled to the processor, wherein the computer program includes: program code for receiving an attribute for ranking query results; program code for receiving query results from a query of a data source, each received query result having a respective numeric relevancy score relating to the query; program code for, for each received query result, concatenating with its relevancy score a segment of digits representing a value for the attribute corresponding to the query result to form numeric keys, such that the segment of digits is enabled as a score tie breaking factor among query results; and program code for returning the query results ordered by the numeric keys, wherein the numeric keys take the form of a high segment of digits occupied by a relevancy score and a lower segment of digits representing the value for the attribute of the respective query result. | 13. A computer system executing instructions set forth in a computer program, the computer system comprising: a processor; and a memory coupled to the processor, wherein the computer program includes: program code for receiving an attribute for ranking query results; program code for receiving query results from a query of a data source, each received query result having a respective numeric relevancy score relating to the query; program code for, for each received query result, concatenating with its relevancy score a segment of digits representing a value for the attribute corresponding to the query result to form numeric keys, such that the segment of digits is enabled as a score tie breaking factor among query results; and program code for returning the query results ordered by the numeric keys, wherein the numeric keys take the form of a high segment of digits occupied by a relevancy score and a lower segment of digits representing the value for the attribute of the respective query result. 16. The computer system according to claim 13 , further comprising: program code for storing the query results before the concatenating. | 0.579984 |
10. A method, comprising: receiving, through a communication interface, an access request from a client device, the access request including authentication information corresponding to a user; authenticating the access request based on the authentication information; obtaining, through a database interface, a layout template from a database library, the layout template including a data visualization panel; obtaining, through the database interface, a data visualization template from the database library, the data visualization template identifying a data source server; receiving, through the database interface, updateable data from the data source server; determining a standard data visualization structure for rendering the updateable data; rendering the updateable data into a data visualization according to the determined standard data visualization structure; controlling display of the data visualization in the data visualization panel within the layout template; generating a data visualization modification interface and accepting a client device customization input of data visualization rendering logic implemented by the data visualization; and modifying the data visualization rendering logic responsive to the client device customization. | 10. A method, comprising: receiving, through a communication interface, an access request from a client device, the access request including authentication information corresponding to a user; authenticating the access request based on the authentication information; obtaining, through a database interface, a layout template from a database library, the layout template including a data visualization panel; obtaining, through the database interface, a data visualization template from the database library, the data visualization template identifying a data source server; receiving, through the database interface, updateable data from the data source server; determining a standard data visualization structure for rendering the updateable data; rendering the updateable data into a data visualization according to the determined standard data visualization structure; controlling display of the data visualization in the data visualization panel within the layout template; generating a data visualization modification interface and accepting a client device customization input of data visualization rendering logic implemented by the data visualization; and modifying the data visualization rendering logic responsive to the client device customization. 18. The method of claim 10 , wherein obtaining the data visualization template comprises: receiving, through the communication interface, a data visualization template search query from the client device requesting the data visualization template satisfying a data visualization template attribute identified in the data visualization template search query; parsing, through the database interface, the database library; identifying a set of data visualization templates satisfying the data visualization template attribute based on parsing the database library; presenting, through the communication interface, the set of data visualization templates to the client device; receiving, through the communication interface, a data visualization template selection from the client device identifying the data visualization template from the set of data visualization templates; and retrieving, through the database interface, the data visualization template from the database library based on the data visualization template selection, wherein the data visualization template identifies the standard data visualization structure and the data source server. | 0.526273 |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.