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7,761,299 | 1 | 8 | 1. A concatenation cost database stored in a computer-readable medium, the concatenation cost database generated according to a method comprising: synthesizing a body of speech; identifying acoustic unit sequential pairs generated in the body of speech and their respective concatenation costs; and storing the respective concatenation costs in a concatenation cost database. | 1. A concatenation cost database stored in a computer-readable medium, the concatenation cost database generated according to a method comprising: synthesizing a body of speech; identifying acoustic unit sequential pairs generated in the body of speech and their respective concatenation costs; and storing the respective concatenation costs in a concatenation cost database. 8. The concatenation cost database of claim 1 , wherein the identified acoustic unit sequential pairs represent acoustic unit sequential pairs unlikely to occur naturally. | 0.552356 |
8,275,362 | 9 | 10 | 9. A system for presenting information to a user, the system comprising: a processor; and a memory coupled to the processor, the memory storing instructions that, when executed by the processor, cause the system to perform the operations of: receiving one or more ambiguous characters via a reduced-entry keypad of a wireless phone, the one or more ambiguous characters received as a sequence of numbers input through the reduced-entry keypad, each respective ambiguous character being a number that represents one of at least two disambiguated letters; exchanging at least one of the ambiguous characters with a host by transmitting the sequence of numbers to the host across a wireless network, exchanging the at least one of the ambiguous characters including exchanging the sequence of numbers upon receiving an amount of numbers in the sequence that meets an initial predetermined threshold amount of numbers, and exchanging subsequently received numbers, received as part of the sequence of numbers, after receiving an amount of the subsequently received numbers above a second predetermined threshold amount of numbers; receiving, from the host, results that represent disambiguated terms corresponding to the ambiguous characters exchanged with the host; rendering the results in a display of the wireless phone in a manner that enables identification of which of the disambiguated terms will be used upon a received selection of a displayed result; receiving, from the host, updated results that represent disambiguated terms corresponding to the subsequently received numbers exchanged with the host; rendering the updated results in the display of the wireless phone; and in response to receiving a selection of one of the disambiguated terms, displaying information corresponding to the selection. | 9. A system for presenting information to a user, the system comprising: a processor; and a memory coupled to the processor, the memory storing instructions that, when executed by the processor, cause the system to perform the operations of: receiving one or more ambiguous characters via a reduced-entry keypad of a wireless phone, the one or more ambiguous characters received as a sequence of numbers input through the reduced-entry keypad, each respective ambiguous character being a number that represents one of at least two disambiguated letters; exchanging at least one of the ambiguous characters with a host by transmitting the sequence of numbers to the host across a wireless network, exchanging the at least one of the ambiguous characters including exchanging the sequence of numbers upon receiving an amount of numbers in the sequence that meets an initial predetermined threshold amount of numbers, and exchanging subsequently received numbers, received as part of the sequence of numbers, after receiving an amount of the subsequently received numbers above a second predetermined threshold amount of numbers; receiving, from the host, results that represent disambiguated terms corresponding to the ambiguous characters exchanged with the host; rendering the results in a display of the wireless phone in a manner that enables identification of which of the disambiguated terms will be used upon a received selection of a displayed result; receiving, from the host, updated results that represent disambiguated terms corresponding to the subsequently received numbers exchanged with the host; rendering the updated results in the display of the wireless phone; and in response to receiving a selection of one of the disambiguated terms, displaying information corresponding to the selection. 10. The system of claim 9 wherein the memory stores further instructions that, when executed by the processor, cause the system to perform the operations of: determining if an updated threshold of updated ambiguous characters has been received; exchanging the updated ambiguous characters upon receipt of the updated threshold of ambiguous characters; receiving updated results from the host; and rendering the updated results. | 0.5 |
7,831,456 | 9 | 11 | 9. The method of claim 3 , wherein the at least one component model comprises an advertiser class model, the method further comprising: segmenting a plurality of advertisers that own the plurality of respective advertisements into at least one of a plurality of advertiser classes that depend at least on bid price elasticity. | 9. The method of claim 3 , wherein the at least one component model comprises an advertiser class model, the method further comprising: segmenting a plurality of advertisers that own the plurality of respective advertisements into at least one of a plurality of advertiser classes that depend at least on bid price elasticity. 11. The method of claim 9 , further comprising: measuring membership in an advertiser class by bid-click volume elasticity curves that measure willingness of advertisers to pay up to a click share or a volume change. | 0.5 |
9,788,796 | 3 | 4 | 3. The system of claim 1 , further comprising a general interpretation module trained on a general database of existing ECG datasets, wherein the general interpretation module is executable by the processor to process the new ECG waveform and/or the extracted feature to provide a general interpretation output. | 3. The system of claim 1 , further comprising a general interpretation module trained on a general database of existing ECG datasets, wherein the general interpretation module is executable by the processor to process the new ECG waveform and/or the extracted feature to provide a general interpretation output. 4. The system of claim 3 , wherein the system is configured such that if the clinician input received by the cluster training module rejects the cluster interpretation output, then the general interpretation module displays the general interpretation output on the user interface. | 0.5 |
8,612,469 | 1 | 4 | 1. A computer-implemented method comprising: providing a Web page comprising a plurality of content to be displayed on a computer display device using a Web browser; in response to a selection of a portion of a content by a first user using a pointing device, providing a first view of a pop-up toolbox to the first user, wherein the first view of the pop-up toolbox comprises a plurality of user-selectable options; in response to a selection of a first user-selectable option by the first user using the pointing device, providing a second view of the pop-up toolbox to the first user, wherein the second view of the toolbox comprises a suggestion text entry box; receiving at a server input from the first user comprising a first suggestion inputted into the suggestion text entry box; and storing the first suggestion and position information on the first suggestion in a suggestions database at the server, wherein the plurality of content is stored in a separate database and the position information comprises information identifying the content and information identifying a location of the selected portion within the content permitting a second user to select at least a portion of the content selected by the first user; and permitting the second user to input a second suggestion for the at least a portion of the content selected by the first user. | 1. A computer-implemented method comprising: providing a Web page comprising a plurality of content to be displayed on a computer display device using a Web browser; in response to a selection of a portion of a content by a first user using a pointing device, providing a first view of a pop-up toolbox to the first user, wherein the first view of the pop-up toolbox comprises a plurality of user-selectable options; in response to a selection of a first user-selectable option by the first user using the pointing device, providing a second view of the pop-up toolbox to the first user, wherein the second view of the toolbox comprises a suggestion text entry box; receiving at a server input from the first user comprising a first suggestion inputted into the suggestion text entry box; and storing the first suggestion and position information on the first suggestion in a suggestions database at the server, wherein the plurality of content is stored in a separate database and the position information comprises information identifying the content and information identifying a location of the selected portion within the content permitting a second user to select at least a portion of the content selected by the first user; and permitting the second user to input a second suggestion for the at least a portion of the content selected by the first user. 4. The computer-implemented method of claim 1 wherein the storing the first suggestion and position information on the first suggestion in a suggestions database at the server comprises: receiving a first position selected by the first user in a first paragraph; and receiving a second position selected by the first user in the first paragraph. | 0.5 |
8,791,914 | 1 | 7 | 1. An input method applicable for inputting into an electronic device having an image capturing unit, a processing module, a lip-reading analyzing unit, a lip motion code database, a display module, a facial expression analyzing unit and a facial expression code database, and the input method comprising the steps of: capturing a lip motion of a person through the image capturing unit; receiving an image of the lip motion from the image capturing unit; encoding the lip motion image through the lip-reading analyzing unit to obtain a lip motion code; the processing module comparing the lip motion code with a plurality of standard lip motion codes stored in the lip motion code database, to obtain a first text result matching the lip motion code; displaying the first text result through the display module if the first text result is obtained; activating an auxiliary analyzing mode, if the first text result is not obtained, wherein the auxiliary analyzing mode is a facial expression analyzing mode; capturing a facial expression of the person through the image capturing unit; receiving an image of the facial expression from the image capturing unit; encoding the facial expression image through the facial expression analyzing unit to obtain a facial expression code; the processing module comparing the facial expression code with a plurality of standard facial expression codes stored in the facial expression code database, and comparing the lip motion code with the plurality of standard lip motion codes, to obtain a second text result matching the facial expression code and the lip motion code; and displaying the second text result through the display module if the second text result is obtained. | 1. An input method applicable for inputting into an electronic device having an image capturing unit, a processing module, a lip-reading analyzing unit, a lip motion code database, a display module, a facial expression analyzing unit and a facial expression code database, and the input method comprising the steps of: capturing a lip motion of a person through the image capturing unit; receiving an image of the lip motion from the image capturing unit; encoding the lip motion image through the lip-reading analyzing unit to obtain a lip motion code; the processing module comparing the lip motion code with a plurality of standard lip motion codes stored in the lip motion code database, to obtain a first text result matching the lip motion code; displaying the first text result through the display module if the first text result is obtained; activating an auxiliary analyzing mode, if the first text result is not obtained, wherein the auxiliary analyzing mode is a facial expression analyzing mode; capturing a facial expression of the person through the image capturing unit; receiving an image of the facial expression from the image capturing unit; encoding the facial expression image through the facial expression analyzing unit to obtain a facial expression code; the processing module comparing the facial expression code with a plurality of standard facial expression codes stored in the facial expression code database, and comparing the lip motion code with the plurality of standard lip motion codes, to obtain a second text result matching the facial expression code and the lip motion code; and displaying the second text result through the display module if the second text result is obtained. 7. The input method of claim 1 , wherein the step of encoding the facial expression image comprises or follows recognizing the facial expression from the facial expression image. | 0.902838 |
8,280,892 | 1 | 8 | 1. A computer-implemented method comprising: accessing a document stored in one or more tangible media, the document comprising a plurality of text units, a text unit comprising a plurality of words, the plurality of words comprising a plurality of keywords; performing the following for each text unit using a processor: ranking the plurality of words of the each text unit according to a ranking technique; selecting one or more highly ranked words as the keywords of the each text unit; establishing relatedness among the keywords of each text unit; and selecting one or more keywords according to the established relatedness as one or more candidate tags to yield a candidate tag set for the each text unit; using the processor, determining relatedness between the candidate tags of each candidate tag set and the candidate tags of other candidate tag sets; and using the processor, assigning at least one candidate tag to the document according to the determined relatedness. | 1. A computer-implemented method comprising: accessing a document stored in one or more tangible media, the document comprising a plurality of text units, a text unit comprising a plurality of words, the plurality of words comprising a plurality of keywords; performing the following for each text unit using a processor: ranking the plurality of words of the each text unit according to a ranking technique; selecting one or more highly ranked words as the keywords of the each text unit; establishing relatedness among the keywords of each text unit; and selecting one or more keywords according to the established relatedness as one or more candidate tags to yield a candidate tag set for the each text unit; using the processor, determining relatedness between the candidate tags of each candidate tag set and the candidate tags of other candidate tag sets; and using the processor, assigning at least one candidate tag to the document according to the determined relatedness. 8. The method of claim 1 , the determining relatedness between the candidate tags of the each candidate tag set and the candidate tags of the other candidate tag sets further comprising generating a profile for a first candidate tag of the each candidate tag set by: performing the following for each other candidate tag set: for a second candidate tag of the other candidate tag set, establishing an affinity of the second candidate tag, given the first candidate tag, to yield a plurality of affinities; and combining the affinities; and generating the profile from the combined affinities. | 0.601615 |
8,095,870 | 7 | 13 | 7. A data processing system for generating documents in native application formats, the system comprising: a processor; and a memory coupled to the processor, the memory configured to store a plurality of code modules which when executed by the processor cause the processor to: receive a first document file in a predetermined native application format, data stored in the first document file formatted according to the predetermined native application format, the first document file providing an overall document layout for the data stored in the first document file; generate an XDTL template that represents a document template of at least the overall document layout for the data stored in the first document file in response to parsing the first document file according to the predetermined native application format, the XDTL template including one or more tags configured as data placeholders for different data, the one or more tags replicating locations of the data stored in the first document file for the different data; generate an XDTL execution document based on the XDTL template; and render a second document file in the predetermined native application format based on the XDTL document template, data stored in the second document file being different from the data stored in the first document file, the data stored in the second document file formatted according to the predetermined native application format and having the same overall document layout as provided by the first document file for the data stored in the first document file. | 7. A data processing system for generating documents in native application formats, the system comprising: a processor; and a memory coupled to the processor, the memory configured to store a plurality of code modules which when executed by the processor cause the processor to: receive a first document file in a predetermined native application format, data stored in the first document file formatted according to the predetermined native application format, the first document file providing an overall document layout for the data stored in the first document file; generate an XDTL template that represents a document template of at least the overall document layout for the data stored in the first document file in response to parsing the first document file according to the predetermined native application format, the XDTL template including one or more tags configured as data placeholders for different data, the one or more tags replicating locations of the data stored in the first document file for the different data; generate an XDTL execution document based on the XDTL template; and render a second document file in the predetermined native application format based on the XDTL document template, data stored in the second document file being different from the data stored in the first document file, the data stored in the second document file formatted according to the predetermined native application format and having the same overall document layout as provided by the first document file for the data stored in the first document file. 13. The system of claim 7 the processor is configured receive the first document file as an Excel spreadsheet file. | 0.825228 |
10,079,738 | 13 | 15 | 13. A non-transitory computer-readable storage medium comprising instructions that, when executed on a computing system, cause the computing system to perform operations comprising at least: selecting a web crawler from a plurality of web crawlers based at least in part on a test document, the test document specifying a test for an object of a web page, the test document further specifying a user state for browsing the web page, the test identifying an expected outcome associated with performing an action on the object, the test document stored at a network location separately from code of the web crawler, the web crawler configured to access the web page and to perform the test based at least in part on the test document; launching the web crawler based at least in part on the web crawler being selected; providing the network location and an identifier of the web page to the web crawler, wherein the web crawler accesses the test document from the network location, accesses the web page based at least in part on the identifier and the user state, identifies the object from the test document, and performs the action on the object based at least in part on the test document; receiving a result of the test from the web crawler, the result comprising an indication that an outcome different from the expected outcome occurred based at least in part on the action being performed on the object, the result further identifying a second object of the web page not identified in the test document; tracking a quality metric associated with the web page based at least in part on the result; generating a report based at least in part on the result of the test, the report including the quality metric and identifying a correction to the object such that the expected outcome occurs when the action is performed, the report further comprising a metric for the second object based at least in part on the result, wherein the web page is updated by at least updating the object according to the correction; and receiving a second test document for testing the second object based at least in part on the metric. | 13. A non-transitory computer-readable storage medium comprising instructions that, when executed on a computing system, cause the computing system to perform operations comprising at least: selecting a web crawler from a plurality of web crawlers based at least in part on a test document, the test document specifying a test for an object of a web page, the test document further specifying a user state for browsing the web page, the test identifying an expected outcome associated with performing an action on the object, the test document stored at a network location separately from code of the web crawler, the web crawler configured to access the web page and to perform the test based at least in part on the test document; launching the web crawler based at least in part on the web crawler being selected; providing the network location and an identifier of the web page to the web crawler, wherein the web crawler accesses the test document from the network location, accesses the web page based at least in part on the identifier and the user state, identifies the object from the test document, and performs the action on the object based at least in part on the test document; receiving a result of the test from the web crawler, the result comprising an indication that an outcome different from the expected outcome occurred based at least in part on the action being performed on the object, the result further identifying a second object of the web page not identified in the test document; tracking a quality metric associated with the web page based at least in part on the result; generating a report based at least in part on the result of the test, the report including the quality metric and identifying a correction to the object such that the expected outcome occurs when the action is performed, the report further comprising a metric for the second object based at least in part on the result, wherein the web page is updated by at least updating the object according to the correction; and receiving a second test document for testing the second object based at least in part on the metric. 15. The non-transitory computer-readable storage medium of claim 13 , wherein tracking the quality metric comprises: associating the result of the test with the web crawler; associating the web crawler with the web page; identifying, for the web page, test results based at least in part on associations between the test results and web crawlers and between the web crawlers and the web page; and generating the quality metric based at least in part on the test results. | 0.5 |
8,793,757 | 15 | 16 | 15. In an environment including at least one service provider each associated with a respective privacy policy, a non-transitory computer-readable medium having computer-executable instructions for execution by a processor, that, when executed, cause the processor to: manage a plurality of user identities of an individual user, the plurality of user identities pertaining to the individual user and describing different sets of personal information of the individual user, and to select one or more of the user identities of the user that satisfy a set of identity requirements of a security policy obtained from the environment; provide a plurality of privacy preferences relative to at least one user identity of the plurality of user identities of the user; evaluate one or more privacy preferences of the one or more selected user identities of the user against a privacy policy obtained from the environment to determine which of the selected user identities satisfy the at least one privacy preference; present the evaluation of the selected user identities to the user; and process, by a policy editor, a privacy policy from the environment, generate a reduced version thereof, and supply the reduced privacy policy as the privacy policy used by the privacy engine in performing the evaluation. | 15. In an environment including at least one service provider each associated with a respective privacy policy, a non-transitory computer-readable medium having computer-executable instructions for execution by a processor, that, when executed, cause the processor to: manage a plurality of user identities of an individual user, the plurality of user identities pertaining to the individual user and describing different sets of personal information of the individual user, and to select one or more of the user identities of the user that satisfy a set of identity requirements of a security policy obtained from the environment; provide a plurality of privacy preferences relative to at least one user identity of the plurality of user identities of the user; evaluate one or more privacy preferences of the one or more selected user identities of the user against a privacy policy obtained from the environment to determine which of the selected user identities satisfy the at least one privacy preference; present the evaluation of the selected user identities to the user; and process, by a policy editor, a privacy policy from the environment, generate a reduced version thereof, and supply the reduced privacy policy as the privacy policy used by the privacy engine in performing the evaluation. 16. The non-transitory computer-readable medium of claim 15 , wherein the instructions further cause the processor to: receive from the environment a security policy having requirements; process the security policy to determine whether any of the user identities satisfies the security policy requirements; and cause the evaluation operation to use the privacy preference of any user identity determined to satisfy the security policy requirements. | 0.556436 |
7,734,287 | 16 | 27 | 16. A method for facilitating diagnosis and maintenance of one or more control networks, comprising; wirelessly communicating over a wireless channel between a wireless ground station and a wireless interface coupled to an onboard vehicle control network located on a mobile conveyance; coupling the wireless ground station to a local area computer network comprising a server computer, a database comprising diagnostic information relating to said onboard vehicle control network, and a wide area network interface, whereby additional diagnostic information relating to said onboard vehicle control network is obtainable from one or more remote computers; conveying instructions from the handheld wireless diagnostic unit to the onboard vehicle control network in response to inputs entered at a manual input interface of the handheld wireless diagnostic unit; wirelessly communicating between a portable handheld wireless diagnostic unit and said onboard vehicle control network via said wireless interface and with said local area computer network via said ground station thereby receiving the diagnostic information pertaining to the onboard vehicle control network from the local area computer network via said wireless interface, wherein said portable handheld wireless diagnostic unit is not physically connected to said onboard vehicle control network; and displaying communications received by the portable handheld wireless diagnostic unit on a graphical display of the portable handheld wireless diagnostic unit. | 16. A method for facilitating diagnosis and maintenance of one or more control networks, comprising; wirelessly communicating over a wireless channel between a wireless ground station and a wireless interface coupled to an onboard vehicle control network located on a mobile conveyance; coupling the wireless ground station to a local area computer network comprising a server computer, a database comprising diagnostic information relating to said onboard vehicle control network, and a wide area network interface, whereby additional diagnostic information relating to said onboard vehicle control network is obtainable from one or more remote computers; conveying instructions from the handheld wireless diagnostic unit to the onboard vehicle control network in response to inputs entered at a manual input interface of the handheld wireless diagnostic unit; wirelessly communicating between a portable handheld wireless diagnostic unit and said onboard vehicle control network via said wireless interface and with said local area computer network via said ground station thereby receiving the diagnostic information pertaining to the onboard vehicle control network from the local area computer network via said wireless interface, wherein said portable handheld wireless diagnostic unit is not physically connected to said onboard vehicle control network; and displaying communications received by the portable handheld wireless diagnostic unit on a graphical display of the portable handheld wireless diagnostic unit. 27. The method of claim 16 , wherein said instructions conveyed to the onboard vehicle control network allow the onboard vehicle control network to be diagnosed through the graphical display on the portable handheld wireless diagnostic unit. | 0.599668 |
10,044,656 | 15 | 18 | 15. A non-transitory computer-readable storage medium having embodied thereon a program executable by a processor for performing a method for filtering messages, the method comprising: receiving a message over a network communication interface; processing the received message using one or more reliable classifiers that are associated with a higher level of accuracy than at least one other classifier from a plurality of available classifiers, wherein the one or more reliable classifiers are associated with a feature count; classifying the received message using the one or more reliable classifiers and the feature count; tracking a feature of the classified message based on the classification, wherein the tracked feature and one or more other tracked features are stored in a table and the feature count accounts for a number of times the tracked feature appeared in the classified message; processing the received message based on the classification, wherein processing of the received message includes blocking the received message when the received message is classified as spam or allowing the received message to be forwarded to a recipient when the message is classified as a good message; receiving a new indication that the message is spam or good, the new indication regarding a different feature count associated with a different feature; updating the trained classifier by updating the feature count in accordance with the different feature count in the new indication; identifying that a subsequently received message is spam based on the updated feature count and a whitelist count, wherein the whitelist count is associated with a number of times that at least one of the feature or the different feature appears in one or more whitelisted messages; and blocking the subsequently received message based on the subsequently received message being classified as spam in accordance with the updated feature count. | 15. A non-transitory computer-readable storage medium having embodied thereon a program executable by a processor for performing a method for filtering messages, the method comprising: receiving a message over a network communication interface; processing the received message using one or more reliable classifiers that are associated with a higher level of accuracy than at least one other classifier from a plurality of available classifiers, wherein the one or more reliable classifiers are associated with a feature count; classifying the received message using the one or more reliable classifiers and the feature count; tracking a feature of the classified message based on the classification, wherein the tracked feature and one or more other tracked features are stored in a table and the feature count accounts for a number of times the tracked feature appeared in the classified message; processing the received message based on the classification, wherein processing of the received message includes blocking the received message when the received message is classified as spam or allowing the received message to be forwarded to a recipient when the message is classified as a good message; receiving a new indication that the message is spam or good, the new indication regarding a different feature count associated with a different feature; updating the trained classifier by updating the feature count in accordance with the different feature count in the new indication; identifying that a subsequently received message is spam based on the updated feature count and a whitelist count, wherein the whitelist count is associated with a number of times that at least one of the feature or the different feature appears in one or more whitelisted messages; and blocking the subsequently received message based on the subsequently received message being classified as spam in accordance with the updated feature count. 18. The non-transitory computer-readable storage medium of claim 15 , wherein the one or more reliable classifiers include a fingerprinting filter that classifies spam messages. | 0.516393 |
8,145,655 | 17 | 18 | 17. The system of claim 14 , wherein the operations further comprise: modifying the at least one query statement in the source code to produce at least one modified query statement; including the at least one modified query statement in the statement descriptor information; and translating the at least one modified query statement into the executable object code. | 17. The system of claim 14 , wherein the operations further comprise: modifying the at least one query statement in the source code to produce at least one modified query statement; including the at least one modified query statement in the statement descriptor information; and translating the at least one modified query statement into the executable object code. 18. The system of claim 17 , wherein modifying the at least one query statement comprises optimizing the at least one query statement to improve performance of execution of the at least one query statement. | 0.5 |
9,098,570 | 3 | 4 | 3. The method of claim 2 , wherein the paragraph scores are generated by limiting the number of times a paragraph term can be counted to generate a paragraph score. | 3. The method of claim 2 , wherein the paragraph scores are generated by limiting the number of times a paragraph term can be counted to generate a paragraph score. 4. The method of claim 3 , wherein the overall document weights are computed by: W d = ∑ n = 1 k ( W n ) P , where Wd is the overall document score, k is the number of paragraphs in the document, Wn is the paragraph score of the nth paragraph in the document, and P is a number in a range of 2.0 to 3.0. | 0.5 |
8,131,550 | 1 | 6 | 1. A method comprising: extracting a feature indicative of a property of a vocal tract of a speaker from each of training source speech and training target speech; defining sub-feature units with respect to the feature for both the training source speech and the training target speech to generate training source speech sub-feature units and training target speech sub-feature units, respectively; and performing voice conversion of source speech to target speech based on the conversion of the sub-feature units to corresponding target speech sub-feature units using a conversion model trained with respect to converting the training source speech sub-feature units to the training target speech sub-feature units. | 1. A method comprising: extracting a feature indicative of a property of a vocal tract of a speaker from each of training source speech and training target speech; defining sub-feature units with respect to the feature for both the training source speech and the training target speech to generate training source speech sub-feature units and training target speech sub-feature units, respectively; and performing voice conversion of source speech to target speech based on the conversion of the sub-feature units to corresponding target speech sub-feature units using a conversion model trained with respect to converting the training source speech sub-feature units to the training target speech sub-feature units. 6. A method according to claim 1 , further comprising, for a particular training source speech sub-feature sequence, searching a database to identify a corresponding training target speech sub-feature sequence, wherein the conversion model is trained using the corresponding sub-feature sequences. | 0.5 |
9,081,849 | 2 | 3 | 2. A computer-implemented method of processing a multidimensional (MD) data set produced from an execution of a multidimensional query on a MD data source, the MD data set comprising data for a report described by the report specification based on an entity/relationship (ER) schema, the method comprising: producing a result set description matching the semantics of the report specification based on the ER schema from a MD data set description describing the semantics of the MD data set using result processing information; and converting MD data set into a collection of rows of data to generate a result set of the report output as a tabular result set when the ER report specification conforms to a tabular report, wherein converting the MD data set into a collection of rows of data includes, producing respective full stacks of members, each full stack representing a row of data available for inclusion in the collection of rows of data, wherein producing given full stack of members comprises: pushing a highest-level member of a dimension onto a stack, traversing parent/child relationships within a dimension along an edge to push each member at each level onto the stack, popping a top member off the stack, and pushing all siblings of the top member onto the stack; and converting the MD data set into a cross tabulated result set when the report specification conforms to a cross-tabulated report. | 2. A computer-implemented method of processing a multidimensional (MD) data set produced from an execution of a multidimensional query on a MD data source, the MD data set comprising data for a report described by the report specification based on an entity/relationship (ER) schema, the method comprising: producing a result set description matching the semantics of the report specification based on the ER schema from a MD data set description describing the semantics of the MD data set using result processing information; and converting MD data set into a collection of rows of data to generate a result set of the report output as a tabular result set when the ER report specification conforms to a tabular report, wherein converting the MD data set into a collection of rows of data includes, producing respective full stacks of members, each full stack representing a row of data available for inclusion in the collection of rows of data, wherein producing given full stack of members comprises: pushing a highest-level member of a dimension onto a stack, traversing parent/child relationships within a dimension along an edge to push each member at each level onto the stack, popping a top member off the stack, and pushing all siblings of the top member onto the stack; and converting the MD data set into a cross tabulated result set when the report specification conforms to a cross-tabulated report. 3. The method as claimed in claim 2 , further comprising creating a header row, including: setting a state of header to header nested; performing a check header nested; performing a check header current; performing a check header done; performing a check children; performing a check nested; performing a check current; performing a check sibling; and performing a check ancestor. | 0.761606 |
6,023,673 | 20 | 21 | 20. A speech coding method comprising: measuring the value of at least one feature of an utterance during each of a series of successive time intervals to produce a series of feature vector signals representing the feature values; storing a first plurality of prototype vector signals as a first level subset of prototype vectors, each prototype vector signal having at least one parameter vector and a unique identification value; storing a second plurality of prototype vector signals, greater than the first plurality, as a second level subset of prototype vectors; comparing the closeness of the feature vector of the first feature vector signal to the parameter vectors of the prototype vector signals in the first level subset to obtain a ranked list of prototypes most closely matching the first feature vector signal; comparing the closeness of the feature vector of the parameter vectors of the prototype vector signals in the second level subset that are associated with the prototype vectors in the first level subset that most closely match the first feature vector signal to obtain a ranked list of prototypes in the second level subset most closely matching the first feature vector signal; outputting at least the identification value of at least the prototype vector signal in the second level subset, that is associated with a prototype vector in the first level subset, having the best prototype match score as a coded utterance representation signal of the first feature vector signal; and predictive labeling wherein the highest ranking prototype in the lowest level subset is assigned to a second feature vector signal which represents another segment of speech to be recognized if a distance between the second feature vector signal and the first feature vector signal is at least less than a predetermined threshold. | 20. A speech coding method comprising: measuring the value of at least one feature of an utterance during each of a series of successive time intervals to produce a series of feature vector signals representing the feature values; storing a first plurality of prototype vector signals as a first level subset of prototype vectors, each prototype vector signal having at least one parameter vector and a unique identification value; storing a second plurality of prototype vector signals, greater than the first plurality, as a second level subset of prototype vectors; comparing the closeness of the feature vector of the first feature vector signal to the parameter vectors of the prototype vector signals in the first level subset to obtain a ranked list of prototypes most closely matching the first feature vector signal; comparing the closeness of the feature vector of the parameter vectors of the prototype vector signals in the second level subset that are associated with the prototype vectors in the first level subset that most closely match the first feature vector signal to obtain a ranked list of prototypes in the second level subset most closely matching the first feature vector signal; outputting at least the identification value of at least the prototype vector signal in the second level subset, that is associated with a prototype vector in the first level subset, having the best prototype match score as a coded utterance representation signal of the first feature vector signal; and predictive labeling wherein the highest ranking prototype in the lowest level subset is assigned to a second feature vector signal which represents another segment of speech to be recognized if a distance between the second feature vector signal and the first feature vector signal is at least less than a predetermined threshold. 21. A speech coding method as claimed in claim 20, wherein the second level subset includes a number of prototypes greater than the number in the first level subset. | 0.5 |
9,844,873 | 2 | 3 | 2. The method of claim 1 , further comprising performing a learning process that associates the first control signal with the environmental context. | 2. The method of claim 1 , further comprising performing a learning process that associates the first control signal with the environmental context. 3. The method of claim 2 , wherein determining the second control signal further comprises modifying the learning process. | 0.770677 |
9,336,772 | 1 | 2 | 1. A system comprising: a computer-readable memory storing executable instructions; and one or more processors in communication with the computer-readable memory, wherein the one or more processors are programmed by the executable instructions to at least: obtain item information regarding an item expected to be referenced in user utterances in a future period of time more often than the item was referenced in user utterances in a prior period of time; obtain language use prediction data regarding the item, the language use prediction data associated with one or more previously selected features; determine, using the language use prediction data and a machine learning model trained to generate probabilities based on the one or more previously selected features, a probability that the item will be referenced in user utterances in the future period of time; generate a predictive language model comprising a word in a name of the item and a corresponding probability related to the word, the corresponding probability based at least partly on the determined probability; determine a probability, from a general model, that the name of the item is included in a user utterance; and adjust the probability that the name of the item is included in the user utterance based at least on the corresponding probability indicated in the predictive language model. | 1. A system comprising: a computer-readable memory storing executable instructions; and one or more processors in communication with the computer-readable memory, wherein the one or more processors are programmed by the executable instructions to at least: obtain item information regarding an item expected to be referenced in user utterances in a future period of time more often than the item was referenced in user utterances in a prior period of time; obtain language use prediction data regarding the item, the language use prediction data associated with one or more previously selected features; determine, using the language use prediction data and a machine learning model trained to generate probabilities based on the one or more previously selected features, a probability that the item will be referenced in user utterances in the future period of time; generate a predictive language model comprising a word in a name of the item and a corresponding probability related to the word, the corresponding probability based at least partly on the determined probability; determine a probability, from a general model, that the name of the item is included in a user utterance; and adjust the probability that the name of the item is included in the user utterance based at least on the corresponding probability indicated in the predictive language model. 2. The system of claim 1 , wherein the item information comprises information regarding a plurality of items expected to become available in the future period of time, and wherein the plurality of items was not available in the prior period of time. | 0.5 |
7,979,788 | 1 | 3 | 1. A document processing apparatus, including a processor, comprising: an attachment unit that attaches a comment to an electronic document as additional information at a first position in a body of the electronic document and that modifies the electronic document to include a modification at a second position in the body of the electronic document; a processing unit that determines, in response to a user's input indicating that the modification has been made by the user based on a content of the comment, that the electronic document is modified by the user accessing the electronic document to include the modification based on the content of the comment and associates the comment with the modified place information indicating the second position at which the electronic document is modified, a character string at the second position prior to the modification, and a character string at the second position after the modification, in response to determining that the document is modified based on the content of the comment; and a storage unit that stores the associated information in a database. | 1. A document processing apparatus, including a processor, comprising: an attachment unit that attaches a comment to an electronic document as additional information at a first position in a body of the electronic document and that modifies the electronic document to include a modification at a second position in the body of the electronic document; a processing unit that determines, in response to a user's input indicating that the modification has been made by the user based on a content of the comment, that the electronic document is modified by the user accessing the electronic document to include the modification based on the content of the comment and associates the comment with the modified place information indicating the second position at which the electronic document is modified, a character string at the second position prior to the modification, and a character string at the second position after the modification, in response to determining that the document is modified based on the content of the comment; and a storage unit that stores the associated information in a database. 3. The document processing apparatus according to claim 1 , further comprising: a display that displays the electronic document; and a display control unit that controls the display to display the modification at the second position distinguishably. | 0.609718 |
9,122,453 | 8 | 9 | 8. The method of claim 1 , further comprising training the at least one computing device by presenting one or more sample tasks to the crowdworker, wherein the at least one computing device is trained based on an accent of the crowdworker, whereby the training enables the at least one computing device to convert the audio input to the one or more phrases. | 8. The method of claim 1 , further comprising training the at least one computing device by presenting one or more sample tasks to the crowdworker, wherein the at least one computing device is trained based on an accent of the crowdworker, whereby the training enables the at least one computing device to convert the audio input to the one or more phrases. 9. The method of claim 8 , further comprising determining a performance score of the crowdworker based on the training. | 0.5 |
9,810,545 | 1 | 8 | 1. A computer-implemented method for travel time prediction, the method comprising: receiving, by one or more computing devices, a route request associated with a user; determining, by the one or more computing devices, one or more candidate routes responsive to the route request, wherein each of the one or more candidate routes comprises one or more road segments; accessing, by the one or more computing devices, a plurality of different road speed models, wherein each road speed model comprises a model of vehicle speeds on one or more of the one or more road segments during different conditions, each road speed model having been created by a road speed modeler configured to: collect observations of road speed data during a plurality of driving sessions, the road speed data including a set of sensor measurements relevant to road speed; and create the plurality of different road speed models corresponding to different conditions that impact the road speed; selecting, by the one or more computing devices, at least one of the plurality of different road speed models based at least in part on one or more conditions associated with the route request; and employing, by the one or more computing devices, the selected at least one road speed model to predict one or more travel times respectively for the one or more candidate routes. | 1. A computer-implemented method for travel time prediction, the method comprising: receiving, by one or more computing devices, a route request associated with a user; determining, by the one or more computing devices, one or more candidate routes responsive to the route request, wherein each of the one or more candidate routes comprises one or more road segments; accessing, by the one or more computing devices, a plurality of different road speed models, wherein each road speed model comprises a model of vehicle speeds on one or more of the one or more road segments during different conditions, each road speed model having been created by a road speed modeler configured to: collect observations of road speed data during a plurality of driving sessions, the road speed data including a set of sensor measurements relevant to road speed; and create the plurality of different road speed models corresponding to different conditions that impact the road speed; selecting, by the one or more computing devices, at least one of the plurality of different road speed models based at least in part on one or more conditions associated with the route request; and employing, by the one or more computing devices, the selected at least one road speed model to predict one or more travel times respectively for the one or more candidate routes. 8. The computer-implemented method of claim 1 , wherein the plurality of different road speed models are created at least in part from road segment data that includes transition time from one stretch of road to another. | 0.847067 |
8,938,455 | 3 | 4 | 3. The method of claim 1 , further comprising analyzing the URL to determine if the domain name is associated with an ISP. | 3. The method of claim 1 , further comprising analyzing the URL to determine if the domain name is associated with an ISP. 4. The method of claim 3 , wherein determining if the domain name is associated with an ISP comprises determining if multiple IP addresses are associated with the domain name. | 0.619565 |
9,245,004 | 17 | 20 | 17. A non-transitory computer readable storage medium storing one or more programs configured for execution by a computer, the one or more programs comprising instructions for: receiving a search query from a search requestor at a client system that is distinct from the server system; responding to receiving the search query, including: determining whether the search query is a partial search query or a final search query; wherein, when the search query is deemed to be a partial search query: (A) predicting from the search query a plurality of predicted queries based upon the search query, wherein the instructions for predicting include instructions for selecting the predicted queries based, at least in part, on how many times each of the predicted queries has been reused from a cache at the server system; (B) obtaining a first list of documents corresponding to the plurality of predicted queries wherein the first list of documents is obtained by combining respective documents corresponding to individual predicted queries in the plurality of predicted queries prior to receiving a selection of any predicted query in the plurality of predicted queries from the search requester; and (C) transmitting, from the server system, (i) the plurality of-predicted queries, and (ii) the list of documents corresponding to the plurality of predicted queries to the search requestor at the client system; and when the search query is deemed to be a final search query: (i) obtaining a second list of documents corresponding to the final search query, wherein at least a portion of the list of documents is obtained using a server system cache index and associated cache; and (ii) transmitting, from the server system, the second list of documents to the search requestor at the client system; wherein the predicting (A) obtaining (B) and transmitting (C) are executed before obtaining, at the server system, an affirmation, by the search requestor, of a request for executing the search query. | 17. A non-transitory computer readable storage medium storing one or more programs configured for execution by a computer, the one or more programs comprising instructions for: receiving a search query from a search requestor at a client system that is distinct from the server system; responding to receiving the search query, including: determining whether the search query is a partial search query or a final search query; wherein, when the search query is deemed to be a partial search query: (A) predicting from the search query a plurality of predicted queries based upon the search query, wherein the instructions for predicting include instructions for selecting the predicted queries based, at least in part, on how many times each of the predicted queries has been reused from a cache at the server system; (B) obtaining a first list of documents corresponding to the plurality of predicted queries wherein the first list of documents is obtained by combining respective documents corresponding to individual predicted queries in the plurality of predicted queries prior to receiving a selection of any predicted query in the plurality of predicted queries from the search requester; and (C) transmitting, from the server system, (i) the plurality of-predicted queries, and (ii) the list of documents corresponding to the plurality of predicted queries to the search requestor at the client system; and when the search query is deemed to be a final search query: (i) obtaining a second list of documents corresponding to the final search query, wherein at least a portion of the list of documents is obtained using a server system cache index and associated cache; and (ii) transmitting, from the server system, the second list of documents to the search requestor at the client system; wherein the predicting (A) obtaining (B) and transmitting (C) are executed before obtaining, at the server system, an affirmation, by the search requestor, of a request for executing the search query. 20. The non-transitory computer readable storage medium of claim 17 , wherein the search query is deemed to be a partial search query, and wherein the one or more programs further comprise instructions for: comparing one or more characters of the search query to entries in a dictionary; and creating the plurality of predicted queries from one or more of the entries in the dictionary whose entries include the at least one or more characters. | 0.5 |
9,502,039 | 1 | 6 | 1. A computer-implemented method comprising: receiving, by a computing device that uses voice-based speaker identification, audio data corresponding to an utterance by the user of a predefined hotword; in response to a false rejection of the audio data corresponding to the utterance, prompting the user to verify their identification using a technique other than voice-based speaker identification; in response to the user successfully verifying their identification using the technique other than voice-based speaker identification, prompting the user to confirm that the audio data corresponding to the utterance was falsely rejected; receiving data indicating that the user has confirmed that the audio data corresponding to the utterance was falsely rejected; and in response to receiving the data indicating that the user has confirmed that the audio data corresponding to the utterance was falsely rejected, using the audio data in determining whether audio data corresponding to subsequently received utterances by the user of the predefined hotword are to be accepted or rejected. | 1. A computer-implemented method comprising: receiving, by a computing device that uses voice-based speaker identification, audio data corresponding to an utterance by the user of a predefined hotword; in response to a false rejection of the audio data corresponding to the utterance, prompting the user to verify their identification using a technique other than voice-based speaker identification; in response to the user successfully verifying their identification using the technique other than voice-based speaker identification, prompting the user to confirm that the audio data corresponding to the utterance was falsely rejected; receiving data indicating that the user has confirmed that the audio data corresponding to the utterance was falsely rejected; and in response to receiving the data indicating that the user has confirmed that the audio data corresponding to the utterance was falsely rejected, using the audio data in determining whether audio data corresponding to subsequently received utterances by the user of the predefined hotword are to be accepted or rejected. 6. The method of claim 1 , comprising: identifying an environmental context associated with receiving the audio data corresponding to the utterance by the user of the predefined hotword; wherein using the audio data in determining whether audio data corresponding to subsequently received utterances by the user of the predefined hotword are to be accepted or rejected comprises using the environmental context in determining whether the audio data corresponding to the subsequently received utterances by the user of the predefined hotword are to be accepted or rejected. | 0.5 |
8,488,213 | 17 | 18 | 17. A system as described in claim 15 , wherein said first image-capture device comprises at least one of a pan adjustment control, a tilt adjustment control and a zoom adjustment control. | 17. A system as described in claim 15 , wherein said first image-capture device comprises at least one of a pan adjustment control, a tilt adjustment control and a zoom adjustment control. 18. A system as described in claim 17 , wherein said memory stores additional instructions to be executed by said computing system to: analyze said received image frame for content placement; and adjust, prior to said capturing, at least one of said pan adjustment control, said tilt adjustment control and said zoom adjustment control in response to said content placement. | 0.5 |
7,899,657 | 1 | 16 | 1. A computer-implemented method for parameterizing a steady-state model of an in-situ hydrocarbon reservoir, the model having a plurality of model parameters for mapping model input to model output through a stored representation of said reservoir, the method comprising: providing a training data set comprising a plurality of input values and a plurality of target output values, wherein the training data set is representative of production operations for said reservoir; receiving a next at least one input value of the plurality of input values and a next target output value of the plurality of target output values; parameterizing the model with a predetermined algorithm using said next at least one input value and said next target output value, and one or more derivative constraints, wherein the one or more derivative constraints are imposed to constrain relationships between the at least one input value and a resulting model output value, wherein said parameterizing comprises using an optimizer to perform constrained optimization on the plurality of model parameters to satisfy an objective function subject to the derivative constraints; iteratively performing said receiving and said parameterizing using the optimizer to generate a parameterized model, wherein the model comprises a model function, wherein the one or more derivative constraints comprise upper and/or lower bounds on one or more model function derivatives, wherein one or more of the model function derivatives comprise one or more of: a first order derivative of the model function, wherein the first order derivative represents inter-well transmissibilities; a second order derivative of the model function, wherein the second order derivative of the model function represents curvature of the inter-well transmissibilities; and/or a third order derivative of the model function, wherein the third order derivative of the model function represents rate of curvature of the inter-well transmissibilities; and storing the parameterized model in a computer-accessible memory medium, wherein the parameterized model is usable to analyze operations for the reservoir for management of the production operations for the reservoir. | 1. A computer-implemented method for parameterizing a steady-state model of an in-situ hydrocarbon reservoir, the model having a plurality of model parameters for mapping model input to model output through a stored representation of said reservoir, the method comprising: providing a training data set comprising a plurality of input values and a plurality of target output values, wherein the training data set is representative of production operations for said reservoir; receiving a next at least one input value of the plurality of input values and a next target output value of the plurality of target output values; parameterizing the model with a predetermined algorithm using said next at least one input value and said next target output value, and one or more derivative constraints, wherein the one or more derivative constraints are imposed to constrain relationships between the at least one input value and a resulting model output value, wherein said parameterizing comprises using an optimizer to perform constrained optimization on the plurality of model parameters to satisfy an objective function subject to the derivative constraints; iteratively performing said receiving and said parameterizing using the optimizer to generate a parameterized model, wherein the model comprises a model function, wherein the one or more derivative constraints comprise upper and/or lower bounds on one or more model function derivatives, wherein one or more of the model function derivatives comprise one or more of: a first order derivative of the model function, wherein the first order derivative represents inter-well transmissibilities; a second order derivative of the model function, wherein the second order derivative of the model function represents curvature of the inter-well transmissibilities; and/or a third order derivative of the model function, wherein the third order derivative of the model function represents rate of curvature of the inter-well transmissibilities; and storing the parameterized model in a computer-accessible memory medium, wherein the parameterized model is usable to analyze operations for the reservoir for management of the production operations for the reservoir. 16. The method of claim 1 , wherein said providing, said receiving, said parameterizing, and said iteratively performing are performed for each of a plurality of models, wherein said plurality of models compose an aggregate model of the reservoir. | 0.631343 |
8,442,931 | 1 | 5 | 1. A computer-based method for searching a data set for one or more data values, comprising: obtaining a data block of the data set; traversing a graph rule set based at least in part upon a current state of said graph rule set and said data block, wherein a value of said data block falls within a predefined range of values of said graph rule set, and wherein said graph rule set is a graph representation of a set of rules; identifying a rule of said set of rules as a function of traversal of said graph rule set for the data set, wherein said set of rules describes the one or more data values; wherein traversing a link of said graph rule set comprises comparing said data block with a value range not specified in said identified rule; and modifying said data set by attaching a flag to said data set. | 1. A computer-based method for searching a data set for one or more data values, comprising: obtaining a data block of the data set; traversing a graph rule set based at least in part upon a current state of said graph rule set and said data block, wherein a value of said data block falls within a predefined range of values of said graph rule set, and wherein said graph rule set is a graph representation of a set of rules; identifying a rule of said set of rules as a function of traversal of said graph rule set for the data set, wherein said set of rules describes the one or more data values; wherein traversing a link of said graph rule set comprises comparing said data block with a value range not specified in said identified rule; and modifying said data set by attaching a flag to said data set. 5. The method of claim 1 , wherein the step of traversing said graph rule set comprises: evaluating a set of available state transitions of said graph rule set, wherein said available state transitions link said current state to a set of available states; selecting a state transition from said set of available state transitions as a function of a value of said data block; and updating said current state of said graph rule to one of said available states as a function of said selected state transition. | 0.5 |
6,108,632 | 18 | 20 | 18. A transaction support apparatus for use by a plurality of human transaction operators, each provided with a telephone, which apparatus comprises: a speech recognition device having: a speech input coupled to receive a speech signal input to a said telephone by a human transaction operator which is confirmatory of a transaction, a speech recognition processor arranged to recognize predetermined transaction parameters within said speech signal; and a parameter output at which said speech recognition device is arranged to make values of said parameters thus recognized available; and an electronic transaction recording means for recording the results of said recognition together with at least portions of the received speech signal. | 18. A transaction support apparatus for use by a plurality of human transaction operators, each provided with a telephone, which apparatus comprises: a speech recognition device having: a speech input coupled to receive a speech signal input to a said telephone by a human transaction operator which is confirmatory of a transaction, a speech recognition processor arranged to recognize predetermined transaction parameters within said speech signal; and a parameter output at which said speech recognition device is arranged to make values of said parameters thus recognized available; and an electronic transaction recording means for recording the results of said recognition together with at least portions of the received speech signal. 20. Apparatus as in claim 18 which further comprises: a confirmatory output device coupled to said parameter output, to generate a confirmatory indication, recognizable by a said human transaction operator, of values of said parameters thus recognized. | 0.5 |
7,698,639 | 10 | 13 | 10. A computer-implemented method of managing configuration settings, comprising: creating a template of per-user settings for a category of user using one or more processors, the template being associated with a system application; adding new properties to the template; adding new template types into an existing system; instantiating the template into one or more template instances; enabling a definition of the template to be extended by a third-party; applying values to settings of the one or more template instances; and assigning the one or more instances to users. | 10. A computer-implemented method of managing configuration settings, comprising: creating a template of per-user settings for a category of user using one or more processors, the template being associated with a system application; adding new properties to the template; adding new template types into an existing system; instantiating the template into one or more template instances; enabling a definition of the template to be extended by a third-party; applying values to settings of the one or more template instances; and assigning the one or more instances to users. 13. The method of claim 10 , further comprising associating a list of template instance references of the template with a user object. | 0.676329 |
8,527,280 | 1 | 2 | 1. A method of voice communication comprising: providing an earpiece having a housing and a plurality of microphones within the earpiece housing, the earpiece adapted for being worn by a user; selecting at least one microphone within the housing of the earpiece to detect a selected voice communication by a person other than the user; receiving the selected voice communication of a first language from the at least one selected microphone; translating the selected voice communication from the first language to a second language by an intelligent control, the second language different from the first to create a translated voice communication, wherein the translating is performed by a processor within the earpiece; and transducing the translated voice communication at a speaker within the earpiece unit. | 1. A method of voice communication comprising: providing an earpiece having a housing and a plurality of microphones within the earpiece housing, the earpiece adapted for being worn by a user; selecting at least one microphone within the housing of the earpiece to detect a selected voice communication by a person other than the user; receiving the selected voice communication of a first language from the at least one selected microphone; translating the selected voice communication from the first language to a second language by an intelligent control, the second language different from the first to create a translated voice communication, wherein the translating is performed by a processor within the earpiece; and transducing the translated voice communication at a speaker within the earpiece unit. 2. The method of claim 1 wherein at least one microphone is a directional microphone. | 0.700704 |
9,633,082 | 1 | 4 | 1. A search result ranking method, comprising: recording user action information on displayed objects in search results obtained using one or more query words, wherein the displayed objects relate to products or product information; upon receiving a switch-page request or switch-screen request, determining two or more commonality levels of one or more attribute characteristics in objects subjected to user actions, wherein the determining of the two or more commonality levels is based on the user action information on the displayed objects, wherein the one or more attribute characteristics include: title of a product, price of a product, image or image address of a product, number of recent transactions of a product, shipping costs of a product, area where product is located, seller's name of a product, self-defined tags provided by a product publisher, service tags provided by a product publisher, or any combination thereof, and wherein the determining of the two or more commonality levels comprises: calculating first commonality levels of attribute characteristics of objects in a selected set based on the recorded user action information on the displayed objects, wherein the selected set includes user-selected objects of the displayed objects, a first commonality level corresponding to a ratio of a number of objects having the same or similar attribute characteristic of the user-selected objects and a total number of the user-selected objects; and calculating second commonality levels of attribute characteristics of objects in an unselected set, wherein the unselected set includes displayed objects that have not been selected, a second commonality level corresponding to a ratio of a number of objects having the same or similar attribute characteristic of the displayed objects that have not been selected and a total number of the displayed objects that have not been selected; selecting attribute characteristics that comply with predetermined requirements to serve as reference norms for ranking objects that are to be displayed or ranked, wherein the selecting of the attribute characteristics is based on the first commonality level of the calculated first commonality levels and the second commonality level of the calculated second commonality levels; and adjusting rank of objects that are to be displayed or to be ranked, and whose attribute characteristics comply with the reference norms, wherein the objects that are to be displayed or to be ranked have not yet been displayed and are on a separate page from the displayed objects. | 1. A search result ranking method, comprising: recording user action information on displayed objects in search results obtained using one or more query words, wherein the displayed objects relate to products or product information; upon receiving a switch-page request or switch-screen request, determining two or more commonality levels of one or more attribute characteristics in objects subjected to user actions, wherein the determining of the two or more commonality levels is based on the user action information on the displayed objects, wherein the one or more attribute characteristics include: title of a product, price of a product, image or image address of a product, number of recent transactions of a product, shipping costs of a product, area where product is located, seller's name of a product, self-defined tags provided by a product publisher, service tags provided by a product publisher, or any combination thereof, and wherein the determining of the two or more commonality levels comprises: calculating first commonality levels of attribute characteristics of objects in a selected set based on the recorded user action information on the displayed objects, wherein the selected set includes user-selected objects of the displayed objects, a first commonality level corresponding to a ratio of a number of objects having the same or similar attribute characteristic of the user-selected objects and a total number of the user-selected objects; and calculating second commonality levels of attribute characteristics of objects in an unselected set, wherein the unselected set includes displayed objects that have not been selected, a second commonality level corresponding to a ratio of a number of objects having the same or similar attribute characteristic of the displayed objects that have not been selected and a total number of the displayed objects that have not been selected; selecting attribute characteristics that comply with predetermined requirements to serve as reference norms for ranking objects that are to be displayed or ranked, wherein the selecting of the attribute characteristics is based on the first commonality level of the calculated first commonality levels and the second commonality level of the calculated second commonality levels; and adjusting rank of objects that are to be displayed or to be ranked, and whose attribute characteristics comply with the reference norms, wherein the objects that are to be displayed or to be ranked have not yet been displayed and are on a separate page from the displayed objects. 4. The search result ranking method as described in claim 1 , wherein the selecting of the attribute characteristics that comply with the predetermined requirements to serve as the reference norms for ranking objects that are to be displayed or ranked based on the first commonality level of the calculated first commonality levels and the second commonality level of the calculated second commonality levels comprises: calculating differences in commonality levels between various attribute characteristics in the selected set and the unselected set, ranking the various attribute characteristics in an order of large to small differences in the two or more commonality levels between various attribute characteristics in the selected set and the unselected set, and selecting a predetermined quantity of top-ranked attribute characteristics to serve as the reference norms; or regarding attribute characteristics whose the difference in a corresponding commonality level is greater than a set threshold value as the reference norms. | 0.582391 |
8,359,302 | 7 | 21 | 7. A non-transitory computer-readable medium embodying computer program code for displaying search results, the computer program code comprising computer executable instructions, comprising: receiving a query comprising a search term; determining a location on a page that is responsive to the query, wherein the page has a native appearance; determining a contextual area associated with the location on the page, wherein determining a contextual area comprises: determining a plurality of lines of text associated with the location on the page, wherein determining a plurality of lines of text associated with the location on the page comprises: extracting a line of text above the line of text containing the search term; and extracting a line of text below the line of text containing the search term; identifying coordinates of a polygon including the lines of text; rendering the contextual area into an image; and in response to the query, and without requiring any additional user action, causing the image to be output in a hi-fidelity result set displaying one or more results of the query, wherein the image has an appearance the same as the native appearance of the page. | 7. A non-transitory computer-readable medium embodying computer program code for displaying search results, the computer program code comprising computer executable instructions, comprising: receiving a query comprising a search term; determining a location on a page that is responsive to the query, wherein the page has a native appearance; determining a contextual area associated with the location on the page, wherein determining a contextual area comprises: determining a plurality of lines of text associated with the location on the page, wherein determining a plurality of lines of text associated with the location on the page comprises: extracting a line of text above the line of text containing the search term; and extracting a line of text below the line of text containing the search term; identifying coordinates of a polygon including the lines of text; rendering the contextual area into an image; and in response to the query, and without requiring any additional user action, causing the image to be output in a hi-fidelity result set displaying one or more results of the query, wherein the image has an appearance the same as the native appearance of the page. 21. The non-transitory computer-readable medium of claim 7 , wherein the result set comprises a plurality of results, each corresponding to a respective result of the query, and wherein the contextual area is displayed as a portion of one of the results of the query displayed in the result set. | 0.5347 |
8,494,857 | 1 | 14 | 1. A method comprising: receiving, with a speech analysis device, an audio sample that includes speech of a patient; analyzing, with the speech analysis device, the audio sample to identify phonemes from the speech of the patient; analyzing, with the speech analysis device, the identified phonemes to identify prosodic characteristics of the speech of the patient; and automatically measuring, with the speech analysis device, fluency of the speech of the patient based on the prosodic characteristics. | 1. A method comprising: receiving, with a speech analysis device, an audio sample that includes speech of a patient; analyzing, with the speech analysis device, the audio sample to identify phonemes from the speech of the patient; analyzing, with the speech analysis device, the identified phonemes to identify prosodic characteristics of the speech of the patient; and automatically measuring, with the speech analysis device, fluency of the speech of the patient based on the prosodic characteristics. 14. The method of claim 1 , further comprising diagnosing a disorder of the patient according to the fluency of the speech of the patient. | 0.683486 |
7,831,420 | 1 | 2 | 1. A method for modifying a speech signal, the method comprising: receiving, by a formants modifier of a speech converter of a speech processing system, Mth order linear predictive coding (LPC) coefficients representative of an input speech signal; converting the Mth order LPC coefficients to Mth order line spectral pairs (LSPs), by the formants modifier; multiplying, by the formants modifier, the Mth order LSPs by a scale factor to produce scaled Mth order LSPs; removing, by the formants modifier, any pair of scaled LSP with at least one coefficient in the pair above a frequency threshold to produce a Pth order set of LSPs, where P<M; converting the Pth order set of scaled LSPs to a Pth order set of LPCs, by the formants modifier; padding the Pth order set of LPCs with M-P zeros, by the formants modifier; converting the Pth order set of LPCs padded with zeros to a second Mth order set of LSPs, by the formants modifier; processing, by the formants modifier, the second Mth order set of LSPs and at least a third set of Mth order LSPs of another frame; converting the processed LSPs to processed LPCs, by the formants modifier; and re-synthesizing speech, by an LPC synthesizer of a decoder of the speech processing system, using the processed LPCs. | 1. A method for modifying a speech signal, the method comprising: receiving, by a formants modifier of a speech converter of a speech processing system, Mth order linear predictive coding (LPC) coefficients representative of an input speech signal; converting the Mth order LPC coefficients to Mth order line spectral pairs (LSPs), by the formants modifier; multiplying, by the formants modifier, the Mth order LSPs by a scale factor to produce scaled Mth order LSPs; removing, by the formants modifier, any pair of scaled LSP with at least one coefficient in the pair above a frequency threshold to produce a Pth order set of LSPs, where P<M; converting the Pth order set of scaled LSPs to a Pth order set of LPCs, by the formants modifier; padding the Pth order set of LPCs with M-P zeros, by the formants modifier; converting the Pth order set of LPCs padded with zeros to a second Mth order set of LSPs, by the formants modifier; processing, by the formants modifier, the second Mth order set of LSPs and at least a third set of Mth order LSPs of another frame; converting the processed LSPs to processed LPCs, by the formants modifier; and re-synthesizing speech, by an LPC synthesizer of a decoder of the speech processing system, using the processed LPCs. 2. The method of claim 1 , wherein the frequency threshold is a Nyquist rate. | 0.797368 |
9,087,043 | 18 | 19 | 18. The method of claim 17 , wherein the text cluster is a current text cluster, and wherein the method further comprises: determining similarity scores between the current text cluster and the sentences immediately before and immediately after the current text cluster; and merging the current text cluster and the sentence immediately before or immediately after the current text cluster that has the highest similarity relationship to generate an updated current text cluster comprising the current text cluster and the sentence having the highest similarity score. | 18. The method of claim 17 , wherein the text cluster is a current text cluster, and wherein the method further comprises: determining similarity scores between the current text cluster and the sentences immediately before and immediately after the current text cluster; and merging the current text cluster and the sentence immediately before or immediately after the current text cluster that has the highest similarity relationship to generate an updated current text cluster comprising the current text cluster and the sentence having the highest similarity score. 19. The method of claim 18 , further comprising repeatedly implementing the steps of determining similarity scores and merging the current cluster and the sentence until all sentences in the electronic text have been merged with at least one text cluster. | 0.612462 |
9,378,296 | 9 | 15 | 9. A computer program product for generating a customized virtual world, the computer program product comprising: a non-transitory computer readable storage medium having computer readable program code stored thereon, the computer readable program code comprising: computer readable program cod code configured to cause a query server to receive a query from a client computing device comprising a target style, wherein the query requests entry points to virtual worlds having content associated with at least one criterion and wherein the target style is a user selected style for portal representations; computer readable program code configured to cause the query server to identify a set of entities from a virtual world database to be rendered within the customized virtual world, wherein the set of portals are objects representing entry points to alternate virtual worlds that satisfy the query and wherein each portal is an entry point at a location within the customized virtual world; computer readable program code configured to cause a construction server to select a representation associated with the target style for each portal in the set of portals to form a set of selected representations, wherein selecting a representation associated with the target style further comprises: identifying a given portal in the set of portals; searching a set of preferred representations associated with the given portal for a preferred representation matching the target style; and responsive to a failure to identify a matching preferred representation for the given portal matching the target style, selecting a default representation to form the selected representation for the given portal; computer readable program code configured to cause the construction server to construct a virtual world with the set of selected representations to form the customized virtual world, wherein the set of representations are rendered within the customized virtual world; and computer readable program code configured to cause the query server to return the customized virtual world to the client computing device as a response to the to the query. | 9. A computer program product for generating a customized virtual world, the computer program product comprising: a non-transitory computer readable storage medium having computer readable program code stored thereon, the computer readable program code comprising: computer readable program cod code configured to cause a query server to receive a query from a client computing device comprising a target style, wherein the query requests entry points to virtual worlds having content associated with at least one criterion and wherein the target style is a user selected style for portal representations; computer readable program code configured to cause the query server to identify a set of entities from a virtual world database to be rendered within the customized virtual world, wherein the set of portals are objects representing entry points to alternate virtual worlds that satisfy the query and wherein each portal is an entry point at a location within the customized virtual world; computer readable program code configured to cause a construction server to select a representation associated with the target style for each portal in the set of portals to form a set of selected representations, wherein selecting a representation associated with the target style further comprises: identifying a given portal in the set of portals; searching a set of preferred representations associated with the given portal for a preferred representation matching the target style; and responsive to a failure to identify a matching preferred representation for the given portal matching the target style, selecting a default representation to form the selected representation for the given portal; computer readable program code configured to cause the construction server to construct a virtual world with the set of selected representations to form the customized virtual world, wherein the set of representations are rendered within the customized virtual world; and computer readable program code configured to cause the query server to return the customized virtual world to the client computing device as a response to the to the query. 15. The computer program product of claim 9 further comprising: computer readable program code configured to query the virtual world database for a set of virtual worlds responsive to the query; computer readable program code configured to receive a set of entry points, wherein each entry point in the set of entry points is a predetermined location within a virtual world in the set of virtual worlds; computer readable program code configured to obtain a free shard; computer readable program code configured to construct the customized virtual world on the free shard; and computer readable program code configured to return a reference entry point within the customized virtual world to the client computing device. | 0.74359 |
7,835,998 | 1 | 9 | 1. A user-interface method of selecting and presenting a collection of content items of a first content system in which the presentation is ordered at least in part based on content preferences of the user learned from the user selecting content of a second content system, the method comprising: receiving incremental input entered by the user for incrementally identifying desired content items of the second content system, each content item having at least one associated descriptive term to describe the content item; in response to the incremental input entered by the user, presenting a subset of content items of the second content system; receiving selection actions of content items of the subset from the user; determining a user preference signature by analyzing the descriptive terms of the selected content items to learn the content preferences of the user for the content of the second content system; determining a relationship between the content items of the first content system and the content items of the second content system, the relationship defining which learned user content preferences of the user preference signature are relevant to the content items of the first content system; and in response to receiving subsequent incremental input entered by the user for incrementally identifying desired content items of the first content system, selecting and ordering a collection of content items of the first content system based on the learned content preferences of the user determined to be relevant to the content items of the first content system. | 1. A user-interface method of selecting and presenting a collection of content items of a first content system in which the presentation is ordered at least in part based on content preferences of the user learned from the user selecting content of a second content system, the method comprising: receiving incremental input entered by the user for incrementally identifying desired content items of the second content system, each content item having at least one associated descriptive term to describe the content item; in response to the incremental input entered by the user, presenting a subset of content items of the second content system; receiving selection actions of content items of the subset from the user; determining a user preference signature by analyzing the descriptive terms of the selected content items to learn the content preferences of the user for the content of the second content system; determining a relationship between the content items of the first content system and the content items of the second content system, the relationship defining which learned user content preferences of the user preference signature are relevant to the content items of the first content system; and in response to receiving subsequent incremental input entered by the user for incrementally identifying desired content items of the first content system, selecting and ordering a collection of content items of the first content system based on the learned content preferences of the user determined to be relevant to the content items of the first content system. 9. The method of claim 1 , wherein the selecting and ordering the collection of content items is further based on popularity values associated with the content items, each popularity value indicating a relative measure of a likelihood that the corresponding content item is desired by the user. | 0.806579 |
8,533,635 | 10 | 11 | 10. A computer-implemented system for determining a best alias rule in a semiconductor manufacturing process, the system comprising: a memory device; and a processor unit in communication with the memory device, the processor unit performs steps of: obtaining an original rule and candidate alias rules; comparing the original rule to the candidate alias rules; ranking the candidate alias rules according to the comparison; filtering the ranked candidate alias rules; and selecting one rule among the filtered candidate alias rules based on a user's knowledge of the semiconductor manufacturing process, wherein the ranking includes: computing each distance from each candidate alias rule to the original rule; ordering the candidate alias rules in an ascending or descending order of the computed distances; and comparing the computed distance of each candidate rule with at least one threshold; removing one or more of the candidate alias rules if the computed distance of the one or more of the candidate alias rules does not satisfy the at least one threshold, wherein the computing includes: calculating a full-alias value of each candidate alias rule, the full-alias value representing a measured degree of a similarity between a candidate alias rule and the original rule; calculating a used-alias value of each candidate alias rule, the used-alias value representing a measured dependency or correlation between a first tool step included in the original rule and a second tool step included in a candidate alias rule; and calculating a target-alias value of each candidate alias rule, the target-alias value representing a measure of a relative difference between a first target mean associated with the original rule and a second target mean associated with a first candidate alias rule, the first target mean including first measurements associated with the original rule, the second target mean including second measurements associated with the first candidate alias rule, the first candidate alias rule being one or more of the candidate alias rules, the first measurements including one or more of speed, power consumption and yield rate of semiconductor products manufactured according to the original rule, the second measurements including one or more of speed, power consumption and yield rate of semiconductor products manufactured according to the first candidate alias rule. | 10. A computer-implemented system for determining a best alias rule in a semiconductor manufacturing process, the system comprising: a memory device; and a processor unit in communication with the memory device, the processor unit performs steps of: obtaining an original rule and candidate alias rules; comparing the original rule to the candidate alias rules; ranking the candidate alias rules according to the comparison; filtering the ranked candidate alias rules; and selecting one rule among the filtered candidate alias rules based on a user's knowledge of the semiconductor manufacturing process, wherein the ranking includes: computing each distance from each candidate alias rule to the original rule; ordering the candidate alias rules in an ascending or descending order of the computed distances; and comparing the computed distance of each candidate rule with at least one threshold; removing one or more of the candidate alias rules if the computed distance of the one or more of the candidate alias rules does not satisfy the at least one threshold, wherein the computing includes: calculating a full-alias value of each candidate alias rule, the full-alias value representing a measured degree of a similarity between a candidate alias rule and the original rule; calculating a used-alias value of each candidate alias rule, the used-alias value representing a measured dependency or correlation between a first tool step included in the original rule and a second tool step included in a candidate alias rule; and calculating a target-alias value of each candidate alias rule, the target-alias value representing a measure of a relative difference between a first target mean associated with the original rule and a second target mean associated with a first candidate alias rule, the first target mean including first measurements associated with the original rule, the second target mean including second measurements associated with the first candidate alias rule, the first candidate alias rule being one or more of the candidate alias rules, the first measurements including one or more of speed, power consumption and yield rate of semiconductor products manufactured according to the original rule, the second measurements including one or more of speed, power consumption and yield rate of semiconductor products manufactured according to the first candidate alias rule. 11. The computer-implemented system according to claim 10 , wherein the original rule includes a binary decision rule comprising an IF statement, an ELSE statement and a THEN statement. | 0.912156 |
8,577,901 | 15 | 20 | 15. A non-transitory computer-readable memory device, comprising: one or more instructions, which, when executed by one or more processors, cause the one or more processors to: determine, at a first time, a first position of a document with respect to a first set of documents in a first list of search results, the first position being based on a first score of the document with respect to one or more scores associated with the first set of documents in the first list of search results; determine, at a second time, a second position of the document with respect to a second set of documents in a second list of search results, the second position being based on a second score of the document with respect to one or more scores associated with the second set of documents in the second list of search results; determine an amount or rate of change between the first position and the second position; generate a third score for the document based on the determined amount or rate of change between the first position and the second position; and rank the document against at least one other document based on the third score. | 15. A non-transitory computer-readable memory device, comprising: one or more instructions, which, when executed by one or more processors, cause the one or more processors to: determine, at a first time, a first position of a document with respect to a first set of documents in a first list of search results, the first position being based on a first score of the document with respect to one or more scores associated with the first set of documents in the first list of search results; determine, at a second time, a second position of the document with respect to a second set of documents in a second list of search results, the second position being based on a second score of the document with respect to one or more scores associated with the second set of documents in the second list of search results; determine an amount or rate of change between the first position and the second position; generate a third score for the document based on the determined amount or rate of change between the first position and the second position; and rank the document against at least one other document based on the third score. 20. The computer-readable memory device of claim 15 , where the one or more instructions further cause the one or more processors to: receive a search query; and generate a search result document, where the search result document includes an ordered list that includes information identifying the document and information identifying the at least one other document, where the ordered list is based on the ranking. | 0.57582 |
8,060,359 | 1 | 2 | 1. A machine translation apparatus comprising: a central processing unit; an identification information detection unit that detects, from a designated physical object or an attachment thereto, identification information of the designated object; a receiving unit that receives a source language sentence; a word dividing unit that divides the source language sentence into a plurality of first words by morphological analysis; a deixis detection unit that detects, from the first words, a deixis indicating the designated object; a correspondence setting unit that sets a correspondence between the identification information of the designated object and the deixis; a semantic class determining unit executing on the central processing unit that determines a semantic class indicating a semantic attribute of the designated object previously associated with the identification information of the designated object; and a translation unit that translates the source language sentence according to the determined semantic class of the designated object corresponding to the deixis. | 1. A machine translation apparatus comprising: a central processing unit; an identification information detection unit that detects, from a designated physical object or an attachment thereto, identification information of the designated object; a receiving unit that receives a source language sentence; a word dividing unit that divides the source language sentence into a plurality of first words by morphological analysis; a deixis detection unit that detects, from the first words, a deixis indicating the designated object; a correspondence setting unit that sets a correspondence between the identification information of the designated object and the deixis; a semantic class determining unit executing on the central processing unit that determines a semantic class indicating a semantic attribute of the designated object previously associated with the identification information of the designated object; and a translation unit that translates the source language sentence according to the determined semantic class of the designated object corresponding to the deixis. 2. The machine translation apparatus according to claim 1 , wherein the identification information detection unit detects the identification information including the semantic class, and the semantic class determining unit acquires the semantic class included in the identification information and determines the semantic class as the semantic class of the designated object. | 0.783237 |
8,909,591 | 1 | 8 | 1. A computer implemented method for identifying business listings, the method comprising: determining, using one or more processors, a first frequency value of a business listing characteristic within a first plurality of business listings received from a first source, the first plurality of business listings being associated with a particular business listing context; determining, using the one or more processors, a second frequency value of the business listing characteristic within a second plurality of business listings received from a second source, the second plurality of business listings being associated with the particular business listing context; determining, using the one or more processors, a frequency differential between the first frequency value and the second frequency value; in response to the frequency differential exceeding a threshold differential, identifying, using the one or more processors, the business listing characteristic as a differential characteristic; and identifying, using the one or more processors, a particular business listing of the plurality of business listings as a spam listing using the differential characteristic. | 1. A computer implemented method for identifying business listings, the method comprising: determining, using one or more processors, a first frequency value of a business listing characteristic within a first plurality of business listings received from a first source, the first plurality of business listings being associated with a particular business listing context; determining, using the one or more processors, a second frequency value of the business listing characteristic within a second plurality of business listings received from a second source, the second plurality of business listings being associated with the particular business listing context; determining, using the one or more processors, a frequency differential between the first frequency value and the second frequency value; in response to the frequency differential exceeding a threshold differential, identifying, using the one or more processors, the business listing characteristic as a differential characteristic; and identifying, using the one or more processors, a particular business listing of the plurality of business listings as a spam listing using the differential characteristic. 8. The method of claim 1 , wherein the first source is a trusted source and the second source is an untrusted data source. | 0.836022 |
8,214,372 | 13 | 14 | 13. An apparatus comprising: a memory; and at least one processor, coupled to the memory, and operative to: obtain configuration parameter name-value pairs for each of a plurality of component instances, wherein the plurality of configuration parameters are obtained from a deployed software solution; identify a candidate set of configuration dependencies between different ones of the plurality of component instances in the deployed software solution, based on the configuration parameter name-value pairs obtained, wherein the candidate set of configuration dependencies comprise true dependencies and false dependencies; rank-order the candidate set of configuration dependencies to obtain a rank-ordered list, wherein the true dependencies get a higher rank than the false dependencies; and conduct web queries using pairs of the parameter names to compute at least one of a weight and a strength of dependency between members of a given one of the pairs of the parameter names, wherein the rank-ordering step takes into account the computed one of a weight and a strength of dependency. | 13. An apparatus comprising: a memory; and at least one processor, coupled to the memory, and operative to: obtain configuration parameter name-value pairs for each of a plurality of component instances, wherein the plurality of configuration parameters are obtained from a deployed software solution; identify a candidate set of configuration dependencies between different ones of the plurality of component instances in the deployed software solution, based on the configuration parameter name-value pairs obtained, wherein the candidate set of configuration dependencies comprise true dependencies and false dependencies; rank-order the candidate set of configuration dependencies to obtain a rank-ordered list, wherein the true dependencies get a higher rank than the false dependencies; and conduct web queries using pairs of the parameter names to compute at least one of a weight and a strength of dependency between members of a given one of the pairs of the parameter names, wherein the rank-ordering step takes into account the computed one of a weight and a strength of dependency. 14. The apparatus of claim 13 , wherein the at least one processor is operative to identify by accessing the configuration parameter name-value pairs via vendor-specific configuration parameter access application program interfaces. | 0.85335 |
7,984,039 | 8 | 12 | 8. A method of providing a service to a customer over a network comprising: dividing a full query as input by a user into a multiplicity of sub-queries, wherein the sub-queries each comprise a set of keywords of the full query; submitting the full query and said multiplicity of sub-queries to each of a plurality of components, wherein a component comprises a search engine operating on a hardware processor and working on a document collection stored in one or more databases; receiving results of the full query and sub-queries from each component as a list of documents, wherein the results for the full query and the results for the sub-queries from each component have document scores (DS) to which a merit score is applied; estimating a success of a component in handling the full query to generate the merit score for a component per query, wherein estimating the success of a component in handling the full query includes determining an extent of overlap between results for the full query and results for the sub-queries, wherein determining the extent of overlap comprises generating an appearances vector corresponding to a number of times each of the keywords appears in the document collection; and moving through a tree of weights using an overlap vector of the extent of overlap and the appearances vector to generate a query difficulty prediction; applying the merit score to the results of the full query produced by the components, respectively, wherein the merit score is applied if the variance is above a predetermined threshold level; and merging the results for the full query produced by the plurality of components by ranking the results for the full query in order of the applied merit scores. | 8. A method of providing a service to a customer over a network comprising: dividing a full query as input by a user into a multiplicity of sub-queries, wherein the sub-queries each comprise a set of keywords of the full query; submitting the full query and said multiplicity of sub-queries to each of a plurality of components, wherein a component comprises a search engine operating on a hardware processor and working on a document collection stored in one or more databases; receiving results of the full query and sub-queries from each component as a list of documents, wherein the results for the full query and the results for the sub-queries from each component have document scores (DS) to which a merit score is applied; estimating a success of a component in handling the full query to generate the merit score for a component per query, wherein estimating the success of a component in handling the full query includes determining an extent of overlap between results for the full query and results for the sub-queries, wherein determining the extent of overlap comprises generating an appearances vector corresponding to a number of times each of the keywords appears in the document collection; and moving through a tree of weights using an overlap vector of the extent of overlap and the appearances vector to generate a query difficulty prediction; applying the merit score to the results of the full query produced by the components, respectively, wherein the merit score is applied if the variance is above a predetermined threshold level; and merging the results for the full query produced by the plurality of components by ranking the results for the full query in order of the applied merit scores. 12. A method according to claim 8 , wherein the method includes: determining whether or not to apply the merit score to the results based on a variance of merit scores across the components. | 0.5 |
7,899,666 | 28 | 42 | 28. A method for automatically extracting relations between concepts included in electronic text, comprising: accessing, by a program executing on a computer, a semantic network, wherein the semantic network comprises a plurality of lemmas that are grouped into synsets representing concepts, each of the synsets having a corresponding sense, and a plurality of links connected between the synsets that represent semantic relations between the synsets; wherein the semantic network further includes semantic information comprising at least one of: an expanded set of semantic relation links representing: hierarchical semantic relations, synset/corpus semantic relations verb/subject semantic relations, verb/direct object semantic relations, and fine grain/coarse grain semantic relationship; a hierarchical category tree having a plurality of categories, wherein each of the categories contains a group of one or more synsets and a set of attributes, wherein the set of attributes of each of the categories are associated with each of the synsets in the respective category; and a plurality of domains, wherein one or more of the domains is associated with at least a portion of the synsets, wherein each domain adds information regarding a linguistic context in which the corresponding synset is used in a language; and performing, by the program, semantic disambiguation on the electronic text using the semantic network and the at least one of the expanded set of semantic relation links, the hierarchical category tree, and the plurality of domains to assign a respective one of the senses to elements in the electronic text independently from contextual reference of the electronic text. | 28. A method for automatically extracting relations between concepts included in electronic text, comprising: accessing, by a program executing on a computer, a semantic network, wherein the semantic network comprises a plurality of lemmas that are grouped into synsets representing concepts, each of the synsets having a corresponding sense, and a plurality of links connected between the synsets that represent semantic relations between the synsets; wherein the semantic network further includes semantic information comprising at least one of: an expanded set of semantic relation links representing: hierarchical semantic relations, synset/corpus semantic relations verb/subject semantic relations, verb/direct object semantic relations, and fine grain/coarse grain semantic relationship; a hierarchical category tree having a plurality of categories, wherein each of the categories contains a group of one or more synsets and a set of attributes, wherein the set of attributes of each of the categories are associated with each of the synsets in the respective category; and a plurality of domains, wherein one or more of the domains is associated with at least a portion of the synsets, wherein each domain adds information regarding a linguistic context in which the corresponding synset is used in a language; and performing, by the program, semantic disambiguation on the electronic text using the semantic network and the at least one of the expanded set of semantic relation links, the hierarchical category tree, and the plurality of domains to assign a respective one of the senses to elements in the electronic text independently from contextual reference of the electronic text. 42. The method of claim 28 wherein the semantic network includes the hierarchical category tree, the semantic network further includes a set of attributes stored in association with the synsets to limit situations in which one of the synsets is linked to multiple category chains, thereby increasing speed of linguistic analysis. | 0.636865 |
9,202,467 | 23 | 25 | 23. A system for processing a voice request for data specifying a web page, the request including at least a portion of, and invoking, a rule-based grammar statement, the system comprising: means for, responsive to the voice request: identifying which one of a plurality of grammars is associated with the rule-based grammar statement; determining whether a first connection identified as being associated with the grammar is specified in a data structure identifying a plurality of connections and, for each of the plurality of connections, a respective grammar and a respective window in which a web page is presentable, wherein each of the identified grammars is processable by a processor to interpret a received voice request; and if the first connection is specified in the data structure, interpreting the request using the identified grammar, to request the specified webpage and display the specified webpage in at least a portion of the window associated with the first connection. | 23. A system for processing a voice request for data specifying a web page, the request including at least a portion of, and invoking, a rule-based grammar statement, the system comprising: means for, responsive to the voice request: identifying which one of a plurality of grammars is associated with the rule-based grammar statement; determining whether a first connection identified as being associated with the grammar is specified in a data structure identifying a plurality of connections and, for each of the plurality of connections, a respective grammar and a respective window in which a web page is presentable, wherein each of the identified grammars is processable by a processor to interpret a received voice request; and if the first connection is specified in the data structure, interpreting the request using the identified grammar, to request the specified webpage and display the specified webpage in at least a portion of the window associated with the first connection. 25. The system of claim 23 , the system further comprising means for processing the request in at least a portion of a new window capable of presenting the specified web page and associated with a second connection if the first connection identified as being associated with the grammar is not specified in the data structure. | 0.5 |
8,001,179 | 1 | 25 | 1. A computationally-implemented system, comprising: means for acquiring a first inference data indicative of an inferred mental state of a first authoring user in connection with a particular item of an electronic document, wherein said means for acquiring a first inference data indicative of an inferred mental state of a first authoring user in connection with a particular item of an electronic document comprises: means for receiving a first inference data indicative of an inferred mental state of the first authoring user in connection with the particular item, wherein said means for receiving a first inference data indicative of an inferred mental state of the first authoring user in connection with the particular item comprises: means for receiving a first inference data indicative of an inferred mental state of the first authoring user that was obtained based, at least in part, on one or more physical characteristics of the first authoring user sensed during or proximate to an action executed in connection with the particular item and performed, at least in part, by the first authoring user; means for acquiring a second inference data indicative of an inferred mental state of a second authoring user in connection with the particular item of the electronic document; means for comparing the first inference data with the second inference data; and means for presenting data indicative of an extent of congruity between the inferred mental state of the first authoring user and the inferred mental state of the second authoring user based, at least in part, on said comparing. | 1. A computationally-implemented system, comprising: means for acquiring a first inference data indicative of an inferred mental state of a first authoring user in connection with a particular item of an electronic document, wherein said means for acquiring a first inference data indicative of an inferred mental state of a first authoring user in connection with a particular item of an electronic document comprises: means for receiving a first inference data indicative of an inferred mental state of the first authoring user in connection with the particular item, wherein said means for receiving a first inference data indicative of an inferred mental state of the first authoring user in connection with the particular item comprises: means for receiving a first inference data indicative of an inferred mental state of the first authoring user that was obtained based, at least in part, on one or more physical characteristics of the first authoring user sensed during or proximate to an action executed in connection with the particular item and performed, at least in part, by the first authoring user; means for acquiring a second inference data indicative of an inferred mental state of a second authoring user in connection with the particular item of the electronic document; means for comparing the first inference data with the second inference data; and means for presenting data indicative of an extent of congruity between the inferred mental state of the first authoring user and the inferred mental state of the second authoring user based, at least in part, on said comparing. 25. The computationally-implemented system of claim 1 , wherein said means for presenting data indicative of an extent of congruity between the inferred mental state of the first authoring user and the inferred mental state of the second authoring user based, at least in part, on said comparing comprises: means for transmitting via at least one of a wireless network or a wired network an indication of an action executed in connection with the particular item and performed, at least in part, by the first authoring user. | 0.62029 |
9,524,440 | 2 | 4 | 2. The non-transitory computer readable medium according to claim 1 , wherein the input stroke is preprocessed, wherein the preprocessing includes at least the normalization and smoothing of the input stroke. | 2. The non-transitory computer readable medium according to claim 1 , wherein the input stroke is preprocessed, wherein the preprocessing includes at least the normalization and smoothing of the input stroke. 4. The non-transitory computer readable medium according to claim 2 , wherein the assigning of a recognition score comprises a feature extraction stage and a classification of features extracted by neural networks. | 0.5 |
9,182,957 | 1 | 5 | 1. A computer implemented method of program compilation to improve parallelism during the linking of the program by a compiler, the method comprising: converting statements of the program to canonical form; constructing abstract syntax tree (AST) for each procedure in the program; traversing the program to construct a functional dataflow graph, in which an assignment statement or function call is represented as a node, a control flow decision is represented by a first set of nodes, or an array or set is represented as a second set of nodes and in which edges of the functional dataflow graph represent typed data; identifying at least one loop in the functional dataflow graph that can be executed in parallel; transforming the at least one loop to a set operation by retyping connections between nodes of the functional dataflow graph; parsing code of the program to identify control structures that govern alternative statements; and converting each control structure into a sub-graph with conditioning function and with alternative statements represented as separate paths in the graph that later merge and loop. | 1. A computer implemented method of program compilation to improve parallelism during the linking of the program by a compiler, the method comprising: converting statements of the program to canonical form; constructing abstract syntax tree (AST) for each procedure in the program; traversing the program to construct a functional dataflow graph, in which an assignment statement or function call is represented as a node, a control flow decision is represented by a first set of nodes, or an array or set is represented as a second set of nodes and in which edges of the functional dataflow graph represent typed data; identifying at least one loop in the functional dataflow graph that can be executed in parallel; transforming the at least one loop to a set operation by retyping connections between nodes of the functional dataflow graph; parsing code of the program to identify control structures that govern alternative statements; and converting each control structure into a sub-graph with conditioning function and with alternative statements represented as separate paths in the graph that later merge and loop. 5. The method of claim 1 , further comprising: creating a table of initial values for global variables. | 0.778017 |
8,892,550 | 10 | 18 | 10. A system for automatically expanding existing data content that is included in a corpus comprising: memory storage device; a processor in communication with said memory storage device configured to: automatically identify a topic from existing data in said corpus, said existing data comprising one or more seed documents; automatically generate search queries to search for content related to said topic identified from said existing data, the queries being generated based on said topic identified from a seed document in said corpus; using said generated search queries to automatically conduct a search in and retrieve content from one or more other data repositories not including said corpus; automatically extract units of text from the retrieved content; automatically determine a relevance of the extracted units of text and their relatedness to the topic identified from the existing data; and automatically select new sources of content and include them in the corpus based on the determined relevance to said identified topic including compiling a new document from the most relevant extracted text units, said new document being searchable with said existing data content, wherein to automatically identify said topic, said processor is further configured to: generate from said one or more seed documents, a topic name and a topic descriptor corresponding to units extracted from said one or more documents, said generated search queries including one or more: said topic name or words and phrases extracted from said topic descriptor, and wherein to retrieve content, said processor is further configured to: use search engines to run said search queries against the one or more external data repositories, said content retrieved including one or more text passages or documents; extract units of text by splitting the retrieved text passages or documents into smaller text units using structural markup for demarcating text unit boundaries; and, said processor further configured to: determine the relevance of the text units from said retrieved passages or documents by scoring each said text unit using a statistical model based on a lexico-syntactic feature, said lexico-syntactic feature includes a topicality feature, a search feature and a surface feature; wherein to automatically determine a relevance of the extracted units includes fitting a logistic regression (LR) model using said topicality, search and surface features and a generation level to estimate a relevance score of each independent text unit based on their relevance to said topic of the seed document; and compute a score based further on a topicality feature by one of: computing a likelihood ratio of a text unit estimated with a topic model and a background language model, said topic model being estimated from the seed document, and said background language model being estimated from a sample of documents from said corpus. | 10. A system for automatically expanding existing data content that is included in a corpus comprising: memory storage device; a processor in communication with said memory storage device configured to: automatically identify a topic from existing data in said corpus, said existing data comprising one or more seed documents; automatically generate search queries to search for content related to said topic identified from said existing data, the queries being generated based on said topic identified from a seed document in said corpus; using said generated search queries to automatically conduct a search in and retrieve content from one or more other data repositories not including said corpus; automatically extract units of text from the retrieved content; automatically determine a relevance of the extracted units of text and their relatedness to the topic identified from the existing data; and automatically select new sources of content and include them in the corpus based on the determined relevance to said identified topic including compiling a new document from the most relevant extracted text units, said new document being searchable with said existing data content, wherein to automatically identify said topic, said processor is further configured to: generate from said one or more seed documents, a topic name and a topic descriptor corresponding to units extracted from said one or more documents, said generated search queries including one or more: said topic name or words and phrases extracted from said topic descriptor, and wherein to retrieve content, said processor is further configured to: use search engines to run said search queries against the one or more external data repositories, said content retrieved including one or more text passages or documents; extract units of text by splitting the retrieved text passages or documents into smaller text units using structural markup for demarcating text unit boundaries; and, said processor further configured to: determine the relevance of the text units from said retrieved passages or documents by scoring each said text unit using a statistical model based on a lexico-syntactic feature, said lexico-syntactic feature includes a topicality feature, a search feature and a surface feature; wherein to automatically determine a relevance of the extracted units includes fitting a logistic regression (LR) model using said topicality, search and surface features and a generation level to estimate a relevance score of each independent text unit based on their relevance to said topic of the seed document; and compute a score based further on a topicality feature by one of: computing a likelihood ratio of a text unit estimated with a topic model and a background language model, said topic model being estimated from the seed document, and said background language model being estimated from a sample of documents from said corpus. 18. The system as claimed in claim 10 , wherein said topic and background language model is a simple unigram model with Good-Turing discounting. | 0.826087 |
9,405,779 | 13 | 18 | 13. One or more non-transitory storage media embodying logic that is operable when executed by one or more processors to: query the search index and the ontology in parallel, wherein the search index is generated based at least in part upon an unstructured data element by streaming and normalizing received data terms from a data source and the ontology is generated based at least in part upon an structured data element at least one data mitigation and classification rule; receive a first search request relating to information stored in the ontology, wherein the ontology comprises at least one instance and the instance has a name; parse the first search request to determine if the first search request is an instance based search that comprises all or part of a name of at least a first instance in the ontology; perform a first query of the search index associated with the ontology in response to determining that the first search request is an instance based search; receive a second search request relating to information stored in an ontology; parse the second search request to determine if the second search request is an instance based search that comprises all or part of a name of at least a second instance in the ontology; and perform a second query of at least the ontology in response to determining that the second search request is not an instance based search; receive a third search request relating to information not stored in the ontology; parse the third search request to determine that the third search request is an instance based search that comprises all or part of a name of at least a third instance in the ontology; perform a third query of the search index and retrieve metadata associated with the third instance from the search index, wherein the metadata comprises information about a data source associated with the third instance; and retrieve information from the data source that are not stored in the ontology. | 13. One or more non-transitory storage media embodying logic that is operable when executed by one or more processors to: query the search index and the ontology in parallel, wherein the search index is generated based at least in part upon an unstructured data element by streaming and normalizing received data terms from a data source and the ontology is generated based at least in part upon an structured data element at least one data mitigation and classification rule; receive a first search request relating to information stored in the ontology, wherein the ontology comprises at least one instance and the instance has a name; parse the first search request to determine if the first search request is an instance based search that comprises all or part of a name of at least a first instance in the ontology; perform a first query of the search index associated with the ontology in response to determining that the first search request is an instance based search; receive a second search request relating to information stored in an ontology; parse the second search request to determine if the second search request is an instance based search that comprises all or part of a name of at least a second instance in the ontology; and perform a second query of at least the ontology in response to determining that the second search request is not an instance based search; receive a third search request relating to information not stored in the ontology; parse the third search request to determine that the third search request is an instance based search that comprises all or part of a name of at least a third instance in the ontology; perform a third query of the search index and retrieve metadata associated with the third instance from the search index, wherein the metadata comprises information about a data source associated with the third instance; and retrieve information from the data source that are not stored in the ontology. 18. The storage media of claim 13 , wherein the logic is further operable when executed to: receive a plurality of terms, the terms having been generated by processing unstructured data from a data source; and generate the search index at least in part by indexing the plurality of terms. | 0.701863 |
9,086,788 | 9 | 16 | 9. A method for collaborating, the method comprising: modifying, by a computer system, a presentation of a document that includes a plurality of portions by making each portion of the document selectable by a user; responsive to receiving, by the computer system, a selection by the user of a portion of the document, identifying, by the computer system, a context of the user-selected portion of the document; identifying, by the computer system, a set of collaboration channels corresponding to the context of the user-selected portion of the document; determining, by the computer system, whether the set of collaboration channels corresponding to the context of the user-selected portion of the document is empty; responsive to the computer system determining that the set of collaboration channels corresponding to the context of the user-selected portion of the document is empty, creating, by the computer system, a new collaboration channel based on the context of the user-selected portion of the document; responsive to the computer system determining that the set of collaboration channels corresponding to the context of the user-selected portion of the document is not empty, selecting, by the computer system, one or more of the set of collaboration channels corresponding to the context of the user-selected portion of the document; and establishing, by the computer system, a collaboration that communicates information about the user-selected portion of the document between the user and other users by utilizing the one or more of the set of collaboration channels corresponding to the context of the user-selected portion of the document. | 9. A method for collaborating, the method comprising: modifying, by a computer system, a presentation of a document that includes a plurality of portions by making each portion of the document selectable by a user; responsive to receiving, by the computer system, a selection by the user of a portion of the document, identifying, by the computer system, a context of the user-selected portion of the document; identifying, by the computer system, a set of collaboration channels corresponding to the context of the user-selected portion of the document; determining, by the computer system, whether the set of collaboration channels corresponding to the context of the user-selected portion of the document is empty; responsive to the computer system determining that the set of collaboration channels corresponding to the context of the user-selected portion of the document is empty, creating, by the computer system, a new collaboration channel based on the context of the user-selected portion of the document; responsive to the computer system determining that the set of collaboration channels corresponding to the context of the user-selected portion of the document is not empty, selecting, by the computer system, one or more of the set of collaboration channels corresponding to the context of the user-selected portion of the document; and establishing, by the computer system, a collaboration that communicates information about the user-selected portion of the document between the user and other users by utilizing the one or more of the set of collaboration channels corresponding to the context of the user-selected portion of the document. 16. The method of claim 9 , wherein the plurality of portions of the document is arranged in a hierarchy, the context of the user-selected portion of the document is a first context, and the new collaboration channel is a first new collaboration channel, and further comprising: identifying, by the computer system, a second context associated with a parent portion of the user-selected portion of the document; identifying, by the computer system, a second set of collaboration channels corresponding to the second context associated with the parent portion of the user-selected portion of the document; determining, by the computer system, whether the second set of collaboration channels corresponding to the second context associated with the parent portion of the user-selected portion of the document is empty; and responsive to the computer system determining that the second set of collaboration channels corresponding to the second context associated with the parent portion of the user-selected portion of the document is empty, creating, by the computer system, a second new collaboration channel based on the second context associated with the parent portion of the user-selected portion of the document. | 0.5 |
6,065,001 | 19 | 20 | 19. An information associating apparatus according to claim 16 wherein: said association degree dictionary composed of an interval association degree dictionary which stores the degree of interval association found by calculating the association degree between said two queries based on the minimum time interval which is the smallest value among time intervals in which each of said extracted queries for each search user from queries used for searching during a past predetermined time interval, and adding said association degrees calculated for a plurality of each of said search users, and a correlation degree dictionary which stores the degree of correlation of key words found by compiling the queries for each search user in a predetermined time interval from queries used for searching during said past predetermined time interval, calculating for each of said users the number of uses of key words among said queries in each predetermined time interval, calculating the number of uses of each key word for all of said search users, and calculating the coefficient of correlation between two key words based on the number of uses of each key word, and further characterized in said initialization unit generating initial groups for grouping key words according to the interval association degree and the correlation degree stored in said interval association degree dictionary, and said grouping unit grouping associated key words by sequentially making the groups which satisfy predetermined conditions into one group using said initial groups and the interval association degree of key words stored in said interval association degree dictionary and the correlation degree of key words stored in said correlation degree dictionary. | 19. An information associating apparatus according to claim 16 wherein: said association degree dictionary composed of an interval association degree dictionary which stores the degree of interval association found by calculating the association degree between said two queries based on the minimum time interval which is the smallest value among time intervals in which each of said extracted queries for each search user from queries used for searching during a past predetermined time interval, and adding said association degrees calculated for a plurality of each of said search users, and a correlation degree dictionary which stores the degree of correlation of key words found by compiling the queries for each search user in a predetermined time interval from queries used for searching during said past predetermined time interval, calculating for each of said users the number of uses of key words among said queries in each predetermined time interval, calculating the number of uses of each key word for all of said search users, and calculating the coefficient of correlation between two key words based on the number of uses of each key word, and further characterized in said initialization unit generating initial groups for grouping key words according to the interval association degree and the correlation degree stored in said interval association degree dictionary, and said grouping unit grouping associated key words by sequentially making the groups which satisfy predetermined conditions into one group using said initial groups and the interval association degree of key words stored in said interval association degree dictionary and the correlation degree of key words stored in said correlation degree dictionary. 20. An information associating apparatus according to claim 19 wherein: an initialization unit generates groups including one different key word stored in said association degree dictionary, as said initial groups. | 0.87991 |
9,104,968 | 1 | 3 | 1. A method comprising: obtaining a word frequency of one or more words in a product title under a first category and another word frequency of the one or more words in the product title under a second category; calculating a first overall word frequency of the product title under the first category based on the word frequency of the one or more words in the product title under the first category and a second overall word frequency of the product title under the second category based on the word frequency of the one or more words in the product title under the second category; setting a first threshold for the first category and a second threshold for the second category; storing the first threshold and the second threshold in a storage device; and comparing the first overall word frequency of the product title with the first threshold and the second overall word frequency of the product title with the second threshold to determine a category of the product title. | 1. A method comprising: obtaining a word frequency of one or more words in a product title under a first category and another word frequency of the one or more words in the product title under a second category; calculating a first overall word frequency of the product title under the first category based on the word frequency of the one or more words in the product title under the first category and a second overall word frequency of the product title under the second category based on the word frequency of the one or more words in the product title under the second category; setting a first threshold for the first category and a second threshold for the second category; storing the first threshold and the second threshold in a storage device; and comparing the first overall word frequency of the product title with the first threshold and the second overall word frequency of the product title with the second threshold to determine a category of the product title. 3. The method as recited in claim 1 , further comprising: determining one or more stop words from the product title; and filtering the one or more stop words from the product title prior to obtaining the word frequency of the one or more words in the product title under the first category and another word frequency of the one or more words in the product title under the second category, the one or more words in the product title including none of the one or more stop words. | 0.5 |
10,108,603 | 13 | 14 | 13. A method comprising: storing, at a data store, a context-free linguistic model, a first context-specific linguistic model, and a natural language understanding model; training the natural language understanding model using both the context-free linguistic model and the first context-specific linguistic model; receiving input at an input interface of a computing device, wherein the input interface is configured to generate a digital signal corresponding to the input; obtaining text based on the digital signal; retrieving, via a wireless network and using one or more network protocols, a second context-specific linguistic model from a remote server; storing the second context-specific linguistic model at the data store; prior to performing semantic analysis of the text, processing the text using the context-free linguistic model and the second context-specific linguistic model to generate one or more linguistic processing results for the text; and performing a semantic analysis of both the text and at least one of the one or more linguistic processing results using the natural language understanding model to generate a natural language understanding recognition result that comprises at least one of an intent corresponding to the text and a mention corresponding to the text, wherein the one or more linguistic processing results comprise one or more of a tokenization for a portion of the text, a normalization for a portion of the text, a sequence of normalizations for a portion of the text, and combinations thereof. | 13. A method comprising: storing, at a data store, a context-free linguistic model, a first context-specific linguistic model, and a natural language understanding model; training the natural language understanding model using both the context-free linguistic model and the first context-specific linguistic model; receiving input at an input interface of a computing device, wherein the input interface is configured to generate a digital signal corresponding to the input; obtaining text based on the digital signal; retrieving, via a wireless network and using one or more network protocols, a second context-specific linguistic model from a remote server; storing the second context-specific linguistic model at the data store; prior to performing semantic analysis of the text, processing the text using the context-free linguistic model and the second context-specific linguistic model to generate one or more linguistic processing results for the text; and performing a semantic analysis of both the text and at least one of the one or more linguistic processing results using the natural language understanding model to generate a natural language understanding recognition result that comprises at least one of an intent corresponding to the text and a mention corresponding to the text, wherein the one or more linguistic processing results comprise one or more of a tokenization for a portion of the text, a normalization for a portion of the text, a sequence of normalizations for a portion of the text, and combinations thereof. 14. The method of claim 13 , further comprising: training, at the computing device, the natural language understanding model using the text and at least one of the one or more linguistic processing results. | 0.828904 |
9,268,560 | 9 | 15 | 9. A non-transitory computer-readable storage medium comprising instructions for indicating a change to a dependent file, wherein the instructions, when executed, are for controlling a computer system to be configured for: receiving a first change to a program file; performing, via a computing device, a second change to code or program data in a first dependent file on the program file on the program file; wherein the second change is related to the first change; and displaying in a document editor a first identifier for the first dependent file in a first text style, if the first dependent file is changed based on the first change to the program file; displaying in the document editor a second identifier, in a second text style, for a second dependent file, wherein: code of the program file calls code or program data of the first dependent file and the second dependent file, the first text style indicates the first dependent file has been changed based on the first change to the program file, and the first text style and the second text style are different styles. | 9. A non-transitory computer-readable storage medium comprising instructions for indicating a change to a dependent file, wherein the instructions, when executed, are for controlling a computer system to be configured for: receiving a first change to a program file; performing, via a computing device, a second change to code or program data in a first dependent file on the program file on the program file; wherein the second change is related to the first change; and displaying in a document editor a first identifier for the first dependent file in a first text style, if the first dependent file is changed based on the first change to the program file; displaying in the document editor a second identifier, in a second text style, for a second dependent file, wherein: code of the program file calls code or program data of the first dependent file and the second dependent file, the first text style indicates the first dependent file has been changed based on the first change to the program file, and the first text style and the second text style are different styles. 15. The non-transitory computer-readable storage medium of claim 9 , wherein the first identifier includes a non-alphabetic identifier, which indicates the second change to the first dependent file based on the first change to the program file. | 0.619938 |
9,448,978 | 9 | 13 | 9. A computer-implemented web browser-based document editing system, comprising a computing device configured to: display an editing surface defined by an electronic model of the document, wherein the editing surface comprises a visual rendering of the electronic model, wherein a portion of the visual rendering of the electronic model is hidden from the user; receive an entry of a character to the editing surface; determine a location to display the character on the editing surface by determining a size of an off-screen display area including the character; and transfer at least a part of the hidden portion to the displayed editing surface when the user provides a scrolling input wherein the hidden portion is different from the off-screen displayed and the off-screen display is not transferred to the displayed editing surface. | 9. A computer-implemented web browser-based document editing system, comprising a computing device configured to: display an editing surface defined by an electronic model of the document, wherein the editing surface comprises a visual rendering of the electronic model, wherein a portion of the visual rendering of the electronic model is hidden from the user; receive an entry of a character to the editing surface; determine a location to display the character on the editing surface by determining a size of an off-screen display area including the character; and transfer at least a part of the hidden portion to the displayed editing surface when the user provides a scrolling input wherein the hidden portion is different from the off-screen displayed and the off-screen display is not transferred to the displayed editing surface. 13. The system of claim 9 , wherein the computing device is further configured to receive a copy command from the user, and in response: identify one or more user selected items in the editing surface; and populate an element in the off-screen display area with the identified items, wherein the element is not accessible to the user. | 0.644681 |
10,115,394 | 1 | 8 | 1. A voice recognition apparatus which performs recognition of voice to be outputted from an output unit, the voice recognition apparatus comprising: a processor configured to control: first, second and third voice recognizers which each recognize an input voice and obtain a recognition result including a candidate character string corresponding to the input voice, each of said first, second and third voice recognizers include a memory that stores a dictionary; and a controller which, when it is decided based on said recognition result obtained by each of said first and second voice recognizers to cause said third voice recognizer to recognize said input voice, causes said third voice recognizer to recognize said input voice by using the dictionary included in said third voice recognizer including said candidate character string obtained by at least one of said first and second voice recognizers, and causes said output unit to output said recognition result obtained by said third voice recognizer, wherein the recognition results obtained by each of said first and second voice recognizers further include score values indicating accuracy of said candidate character strings, and whether or not to cause the third voice recognizer to recognize said input voice is decided based on an index including at least one of said score values which are obtained by said first and second voice recognizers and are a maximum, a similarity indicating a degree that said candidate character strings obtained by said first and second voice recognizers match each other, and an order distance indicating a degree of difference in an order of said candidate character strings aligned in order of said score values obtained by said first and second voice recognizers. | 1. A voice recognition apparatus which performs recognition of voice to be outputted from an output unit, the voice recognition apparatus comprising: a processor configured to control: first, second and third voice recognizers which each recognize an input voice and obtain a recognition result including a candidate character string corresponding to the input voice, each of said first, second and third voice recognizers include a memory that stores a dictionary; and a controller which, when it is decided based on said recognition result obtained by each of said first and second voice recognizers to cause said third voice recognizer to recognize said input voice, causes said third voice recognizer to recognize said input voice by using the dictionary included in said third voice recognizer including said candidate character string obtained by at least one of said first and second voice recognizers, and causes said output unit to output said recognition result obtained by said third voice recognizer, wherein the recognition results obtained by each of said first and second voice recognizers further include score values indicating accuracy of said candidate character strings, and whether or not to cause the third voice recognizer to recognize said input voice is decided based on an index including at least one of said score values which are obtained by said first and second voice recognizers and are a maximum, a similarity indicating a degree that said candidate character strings obtained by said first and second voice recognizers match each other, and an order distance indicating a degree of difference in an order of said candidate character strings aligned in order of said score values obtained by said first and second voice recognizers. 8. The voice recognition apparatus according to claim 1 , wherein, every time said third voice recognizer recognizes said input voice, said candidate candidate character string from each of the first and second voice recognizers for the recognition is deleted from said dictionary. | 0.803497 |
8,146,127 | 4 | 5 | 4. The broadcast system according to claim 1 wherein: the editor is configured to define a plurality of links for information templates to identify other information templates; the processor is configured to provide, in the corresponding modified information templates, the links and a plurality of tags identifying respective links; and the composition provider apparatus is configured to define presentation templates having corresponding tags associated with a plurality of representations of operating keys such that, for a resulting iTV page, an operation of an operating key of a client receiver is configured to cause movement to another information template according to the link identified by the tag associated with the operating key. | 4. The broadcast system according to claim 1 wherein: the editor is configured to define a plurality of links for information templates to identify other information templates; the processor is configured to provide, in the corresponding modified information templates, the links and a plurality of tags identifying respective links; and the composition provider apparatus is configured to define presentation templates having corresponding tags associated with a plurality of representations of operating keys such that, for a resulting iTV page, an operation of an operating key of a client receiver is configured to cause movement to another information template according to the link identified by the tag associated with the operating key. 5. The broadcast system according to claim 4 wherein, when the editor is configured to define a link for a first information template to a second information template, said second information template is associated with the presentation template of said first information template unless a user of the editor associates the second information template with a different presentation template. | 0.5 |
9,152,617 | 1 | 3 | 1. A system, comprising: a processor coupled to a memory and a graphical user interface for displaying an object; the processor receives an input from a user concerning the object, wherein the input relating to a plurality of parts of at least one portion of the object, wherein each part of the at least one portion is separately identified by the user in the received input; and provides the received input to a keying module, wherein the keying module, based on the received input, a selectable list of object entities corresponding to the displayed object, and a predetermined data model corresponding to the displayed object, determines partial location data for each part of the at least one portion of the object, at least one field value for each part of the at least one portion of the object, and, optionally, at least one other information related to each part of the at least one portion of the object, wherein at least one object entity corresponding to each part of the at least one portion of the object is selected from the selectable list of object entities, wherein the predetermined data model includes at least one field, at least one object entity, at least one object label, and at least one object tag; and provides the received input, the determined partial location data for each part of the at least one portion of the object, the at least one field value for each part of the at least one portion of the object, and, optionally, the at least one other information related to each part of the at least one portion of the object to a recognition engine, the recognition engine is in communication with the keying module; based on the received input, the determined partial location data for each part of the at least one portion of the object, the at least one field value for each part of the at least one portion of the object, and, optionally, the at least one other information related to each part of the at least one portion of the object, the recognition engine generates a first information concerning the at least one portion of the object; and provides the first information to the keying module; the keying module generates an enhanced definition of the at least one portion of the object based on the first information received from the recognition engine and a second information concerning the at least one portion of the object stored by the keying module. | 1. A system, comprising: a processor coupled to a memory and a graphical user interface for displaying an object; the processor receives an input from a user concerning the object, wherein the input relating to a plurality of parts of at least one portion of the object, wherein each part of the at least one portion is separately identified by the user in the received input; and provides the received input to a keying module, wherein the keying module, based on the received input, a selectable list of object entities corresponding to the displayed object, and a predetermined data model corresponding to the displayed object, determines partial location data for each part of the at least one portion of the object, at least one field value for each part of the at least one portion of the object, and, optionally, at least one other information related to each part of the at least one portion of the object, wherein at least one object entity corresponding to each part of the at least one portion of the object is selected from the selectable list of object entities, wherein the predetermined data model includes at least one field, at least one object entity, at least one object label, and at least one object tag; and provides the received input, the determined partial location data for each part of the at least one portion of the object, the at least one field value for each part of the at least one portion of the object, and, optionally, the at least one other information related to each part of the at least one portion of the object to a recognition engine, the recognition engine is in communication with the keying module; based on the received input, the determined partial location data for each part of the at least one portion of the object, the at least one field value for each part of the at least one portion of the object, and, optionally, the at least one other information related to each part of the at least one portion of the object, the recognition engine generates a first information concerning the at least one portion of the object; and provides the first information to the keying module; the keying module generates an enhanced definition of the at least one portion of the object based on the first information received from the recognition engine and a second information concerning the at least one portion of the object stored by the keying module. 3. The system according to claim 1 , wherein the input concerning the object includes an incomplete information about a location of and a field value for the at least the portion of the object. | 0.630268 |
7,869,989 | 1 | 18 | 1. A method for representing text in a language independent format of multiple bits and fields of bits comprising: referencing a word from a set of words into a dictionary of representations of words, in said format of multiple bits and fields of bits, to find a corresponding dictionary term, the set of words derived from a natural language usage defining a natural language context of the words in the set of words; mapping the referenced dictionary term to at least one definition element indicative of usage of the word in at least one context, the definition elements defining a record of fields; comparing the mapped definition element to the corresponding fields in the definition elements of other words in the set of words, the comparison operative to identify similar contexts between the definition elements; disambiguating the referenced words by analyzing each of the definition elements of the referenced words with the definition elements of the other referenced words, the analysis operable to determine a particular definition for each of the referenced words in the context of the set of words, disambiguating including: performing, with a processor, bitwise operations on at least a subset of the fields in the definition elements with corresponding fields in the other definition elements in the set of words, each of the definition elements indicative of a particular context, the operations for identifying a particular definition element based on the context in the set of words, the definition elements including bit fields of class, method, and category in the high bits, the method field determining a structure of fields in lower order bits, wherein disambiguating is performed on definition elements of equal category and method fields; and identifying, from the comparing, a definition element corresponding to the usage of the word in a context of the set of words. | 1. A method for representing text in a language independent format of multiple bits and fields of bits comprising: referencing a word from a set of words into a dictionary of representations of words, in said format of multiple bits and fields of bits, to find a corresponding dictionary term, the set of words derived from a natural language usage defining a natural language context of the words in the set of words; mapping the referenced dictionary term to at least one definition element indicative of usage of the word in at least one context, the definition elements defining a record of fields; comparing the mapped definition element to the corresponding fields in the definition elements of other words in the set of words, the comparison operative to identify similar contexts between the definition elements; disambiguating the referenced words by analyzing each of the definition elements of the referenced words with the definition elements of the other referenced words, the analysis operable to determine a particular definition for each of the referenced words in the context of the set of words, disambiguating including: performing, with a processor, bitwise operations on at least a subset of the fields in the definition elements with corresponding fields in the other definition elements in the set of words, each of the definition elements indicative of a particular context, the operations for identifying a particular definition element based on the context in the set of words, the definition elements including bit fields of class, method, and category in the high bits, the method field determining a structure of fields in lower order bits, wherein disambiguating is performed on definition elements of equal category and method fields; and identifying, from the comparing, a definition element corresponding to the usage of the word in a context of the set of words. 18. The method of claim 1 wherein a result of the bitwise operation equals the definition element of another word describing the usage in context. | 0.878536 |
8,620,022 | 11 | 12 | 11. The method of claim 9 , wherein the eliminating of the unnecessary event comprises: generating all the possible combinations of the event; limiting a temporal interval of the event; comparing a predetermined event rule and an event rule of the event; and eliminating an unnecessary event using event related results computed by the temporal interval constraint of the event and the combination of the event. | 11. The method of claim 9 , wherein the eliminating of the unnecessary event comprises: generating all the possible combinations of the event; limiting a temporal interval of the event; comparing a predetermined event rule and an event rule of the event; and eliminating an unnecessary event using event related results computed by the temporal interval constraint of the event and the combination of the event. 12. The method of claim 11 , wherein the eliminating of the unnecessary event further comprises requiring a set of identifications (IDs) of an event, where the IDs do not overlap each other. | 0.5 |
8,234,118 | 9 | 11 | 9. A speech synthesis method comprising: determining a system speaking style based on a user utterance; generating dialog prosody information including an utterance boundary level indicating a duration of a silent period between each semantic unit by reflecting discourse information between a user and a system when the system speaking style is determined as dialog speech, wherein the utterance boundary level is adjusted based on closeness between semantic units, which is determined by syntax and case; and synthesizing a system utterance based on the generated dialog prosody information using by at least one computer system, wherein the speech act provides a speech act classification of the user utterance, so that even when speech acts are identical, the synthesized system utterance varies according to the speech act classification of the user utterance. | 9. A speech synthesis method comprising: determining a system speaking style based on a user utterance; generating dialog prosody information including an utterance boundary level indicating a duration of a silent period between each semantic unit by reflecting discourse information between a user and a system when the system speaking style is determined as dialog speech, wherein the utterance boundary level is adjusted based on closeness between semantic units, which is determined by syntax and case; and synthesizing a system utterance based on the generated dialog prosody information using by at least one computer system, wherein the speech act provides a speech act classification of the user utterance, so that even when speech acts are identical, the synthesized system utterance varies according to the speech act classification of the user utterance. 11. The method of claim 9 , wherein determining the system speaking style includes: determining a speech act and intention associated with the user utterance by referring to a dialog information database; and determining the system speaking style as one of read speech and dialog speech according to the speech act and intention associated with the user utterance. | 0.607759 |
8,229,932 | 1 | 2 | 1. A computer-implemented method for accessing data in an information hierarchy, comprising the steps of: receiving a query that requests a set of nodes in said information hierarchy, said query including first data that identifies the set of nodes based on a location within the information hierarchy; wherein data for nodes of said information hierarchy are stored in a plurality of rows of a table; wherein a plurality of path signatures are stored in association with said plurality of rows, each row being associated with a path signature of said plurality of path signatures; wherein each path signature of said plurality of path signatures indicates, within the information hierarchy, the location of the node whose data is stored in the row associated with the path signature; generating, based on said first data, data representing a string pattern; and retrieving data from the rows that are associated with path signatures that match said string pattern. | 1. A computer-implemented method for accessing data in an information hierarchy, comprising the steps of: receiving a query that requests a set of nodes in said information hierarchy, said query including first data that identifies the set of nodes based on a location within the information hierarchy; wherein data for nodes of said information hierarchy are stored in a plurality of rows of a table; wherein a plurality of path signatures are stored in association with said plurality of rows, each row being associated with a path signature of said plurality of path signatures; wherein each path signature of said plurality of path signatures indicates, within the information hierarchy, the location of the node whose data is stored in the row associated with the path signature; generating, based on said first data, data representing a string pattern; and retrieving data from the rows that are associated with path signatures that match said string pattern. 2. The method of claim 1 , wherein the first data is a string that conforms to XPATH. | 0.610092 |
8,635,340 | 6 | 8 | 6. The method of claim 5 , further comprising: processing a keyword resolution request from the at least one keyword in response to determining the at least one keyword is resolvable; and determining whether the at least one keyword is available for keyword registration in response to determining the at least one keyword is not resolvable. | 6. The method of claim 5 , further comprising: processing a keyword resolution request from the at least one keyword in response to determining the at least one keyword is resolvable; and determining whether the at least one keyword is available for keyword registration in response to determining the at least one keyword is not resolvable. 8. The method of claim 6 , wherein determining whether the at least one keyword is resolvable comprises querying at least one of a keyword resolver system or file cache. | 0.718333 |
8,122,021 | 15 | 16 | 15. The system of claim 13 , said expertise rating being stored on a remote storage device, said expertise rating is stored without any personally identifiable information. | 15. The system of claim 13 , said expertise rating being stored on a remote storage device, said expertise rating is stored without any personally identifiable information. 16. The system of claim 15 , said expertise rating being stored on a remote storage device, said particular user having given permission for said expertise rating to be stored. | 0.5 |
8,306,977 | 15 | 17 | 15. The method of claim 1 , further comprising: receiving an entry of an alternative user-generated label for tagging the item from the user; and adding the alternative user-generated label to the plurality of user-generated labels in response to determining that the alternative user-generated label is different from the plurality of user-generated labels. | 15. The method of claim 1 , further comprising: receiving an entry of an alternative user-generated label for tagging the item from the user; and adding the alternative user-generated label to the plurality of user-generated labels in response to determining that the alternative user-generated label is different from the plurality of user-generated labels. 17. The method of claim 15 , further comprising: receiving a request from a second user to tag the item; and identifying a set of user-generated labels of the plurality of user-generated labels for display to the second user, wherein the plurality of user-generated labels includes the alternative user-generated label. | 0.5 |
6,031,537 | 6 | 7 | 6. A method for organizing and processing information using a computer, said information comprising a plurality of thoughts, and said method comprising the steps of: defining a matrix comprising the plurality of thoughts and further comprising a plurality of network relationships among the thoughts wherein each thought may be related to at least one other of said thoughts, and wherein at least one of the thoughts is directly related to one of the other thoughts; displaying an indicium of a first thought as a central thought on a display; displaying an indicium of a second thought on the display, wherein the second thought having a direct relation to the first thought; selecting said second thought to be a new central thought, whereby indicia of those thoughts having defined relations with the second thought will be displayed on the display; and creating a file that contains the full location of the computer on which said network is initially defined, said file configured so that said thought documents organized by said network are subsequently accessible from a remote computer having access to the information organized by said network. | 6. A method for organizing and processing information using a computer, said information comprising a plurality of thoughts, and said method comprising the steps of: defining a matrix comprising the plurality of thoughts and further comprising a plurality of network relationships among the thoughts wherein each thought may be related to at least one other of said thoughts, and wherein at least one of the thoughts is directly related to one of the other thoughts; displaying an indicium of a first thought as a central thought on a display; displaying an indicium of a second thought on the display, wherein the second thought having a direct relation to the first thought; selecting said second thought to be a new central thought, whereby indicia of those thoughts having defined relations with the second thought will be displayed on the display; and creating a file that contains the full location of the computer on which said network is initially defined, said file configured so that said thought documents organized by said network are subsequently accessible from a remote computer having access to the information organized by said network. 7. The method of claim 6, further comprising the steps of: identifying at least one thought document that does not reside in the memory or storage of a local computer; copying selected ones of said identified thought documents to a local computer; and changing the recorded location of said copied thought documents to reflect the new local location of said documents. | 0.5 |
8,442,976 | 9 | 12 | 9. A content item retrieval system comprising: a base location extractor module configured to determine multiple base locations, based on GPS information or user entry, each base location being a location from which to apply a corresponding criterion distance-determined granularity thresholding for setting a threshold for location similarity in selecting or rejecting target items for content item retrieval, wherein criterion distance-determined granularity thresholding is applied for each base location of the multiple base locations separately based on differences in distance between farther locations being less important than between equally distant closer locations, further wherein the farther in distance moved from a corresponding base location of the multiple base locations, the less important, in terms of determining similarity, are differences in distance between locations of different content items at the corresponding further distances from the corresponding base location; a location data extractor module configured to extract, as a first anchor item location, location data for a first identified anchor content item and to determine, as a criterion distance, a distance determined between a corresponding base location and the first anchor item location, the first identified content item for designating which candidate content items for which a content type is not known or specified by a user are to be retrieved; a threshold setter module configured to set a first threshold based on the criterion distance that the candidate content items must meet to be selected, wherein the first threshold comprises an assigned value on a scale of 1 to 10, where a value of 1 indicates a very small distance between a corresponding base location and candidate content item and a value of 10 indicates a great distance between the corresponding base location and candidate content item, and wherein the criterion distance is determined, using criterion distance-determined granularity thresholding, as a distance between the corresponding base location of the multiple base locations and the first anchor item location, further wherein the distance from the corresponding base location is ranked on the scale and as the distance from the corresponding base location increases, then longer distances are encompassed by fewer gradations of the scale, such that distance granularity on the scale is higher for locations geographically closer to the corresponding base location than for locations further away from the corresponding base location; said location data extractor module further being configured to extract, as a first candidate location, the location data for a first candidate content item, and to determine, as a first candidate distance, the distance between the corresponding base location of the multiple base locations and the first candidate location; a selector module configured to select the first candidate content item as similar for content item retrieval based on (i) the first candidate distance that corresponds to the distance between the corresponding base location of the multiple base locations and the first candidate location and (ii) the first threshold that is based upon the criterion distance, wherein the first candidate content item is selected as being similar to the first identified content item in response to the determined first candidate distance, when compared to the first threshold, being within or with the first threshold; a result output module configured to output a selection signal for indicating retrieval of the first candidate content item when the first candidate location of the candidate content item is selected as being similar to the first identified content item for content item retrieval; a controller configured to coordinate an overall functioning of respective modules; a user interface; and a storage device, wherein said controller is further configured to interact with the user interface and the storage device, the storage device for storage of content items subject to being retrieved, wherein the controller, the base location extractor, the location extractor, the threshold setter, the selector, and the result output modules, portions thereof, and the retrieval system as a whole, comprise a combination of hardware, software, and firmware configured to perform the corresponding functions of the respective controller and modules. | 9. A content item retrieval system comprising: a base location extractor module configured to determine multiple base locations, based on GPS information or user entry, each base location being a location from which to apply a corresponding criterion distance-determined granularity thresholding for setting a threshold for location similarity in selecting or rejecting target items for content item retrieval, wherein criterion distance-determined granularity thresholding is applied for each base location of the multiple base locations separately based on differences in distance between farther locations being less important than between equally distant closer locations, further wherein the farther in distance moved from a corresponding base location of the multiple base locations, the less important, in terms of determining similarity, are differences in distance between locations of different content items at the corresponding further distances from the corresponding base location; a location data extractor module configured to extract, as a first anchor item location, location data for a first identified anchor content item and to determine, as a criterion distance, a distance determined between a corresponding base location and the first anchor item location, the first identified content item for designating which candidate content items for which a content type is not known or specified by a user are to be retrieved; a threshold setter module configured to set a first threshold based on the criterion distance that the candidate content items must meet to be selected, wherein the first threshold comprises an assigned value on a scale of 1 to 10, where a value of 1 indicates a very small distance between a corresponding base location and candidate content item and a value of 10 indicates a great distance between the corresponding base location and candidate content item, and wherein the criterion distance is determined, using criterion distance-determined granularity thresholding, as a distance between the corresponding base location of the multiple base locations and the first anchor item location, further wherein the distance from the corresponding base location is ranked on the scale and as the distance from the corresponding base location increases, then longer distances are encompassed by fewer gradations of the scale, such that distance granularity on the scale is higher for locations geographically closer to the corresponding base location than for locations further away from the corresponding base location; said location data extractor module further being configured to extract, as a first candidate location, the location data for a first candidate content item, and to determine, as a first candidate distance, the distance between the corresponding base location of the multiple base locations and the first candidate location; a selector module configured to select the first candidate content item as similar for content item retrieval based on (i) the first candidate distance that corresponds to the distance between the corresponding base location of the multiple base locations and the first candidate location and (ii) the first threshold that is based upon the criterion distance, wherein the first candidate content item is selected as being similar to the first identified content item in response to the determined first candidate distance, when compared to the first threshold, being within or with the first threshold; a result output module configured to output a selection signal for indicating retrieval of the first candidate content item when the first candidate location of the candidate content item is selected as being similar to the first identified content item for content item retrieval; a controller configured to coordinate an overall functioning of respective modules; a user interface; and a storage device, wherein said controller is further configured to interact with the user interface and the storage device, the storage device for storage of content items subject to being retrieved, wherein the controller, the base location extractor, the location extractor, the threshold setter, the selector, and the result output modules, portions thereof, and the retrieval system as a whole, comprise a combination of hardware, software, and firmware configured to perform the corresponding functions of the respective controller and modules. 12. The system of claim 9 , wherein at least one of the first location and the first candidate location comprises at least one of a content item current location, a content item most recent modification location, and a content item creation location. | 0.787415 |
7,729,938 | 1 | 14 | 1. A method, comprising: a first party providing an advertisement on a media channel on behalf of an advisor, wherein the advertisement is listed to a user and includes at least a reference to establish a real-time communication connection with the advisor and indicates whether the advisor is currently available to communicate via real-time communication at a time when the user is viewing the advertisement; while the advisor is currently available, receiving a user selection of the reference corresponding to the advisor; and a central controller using the selection from the user to establish a real-time communication connection between the advisor and the user prior to the user submitting a question for the advisor, including the central controller establishing a real-time communication with the user and the central controller establishing a real-time communication with the advisor; and the first party charging an amount for the real-time communication connection established between the advisor and the user according to the advertisement. | 1. A method, comprising: a first party providing an advertisement on a media channel on behalf of an advisor, wherein the advertisement is listed to a user and includes at least a reference to establish a real-time communication connection with the advisor and indicates whether the advisor is currently available to communicate via real-time communication at a time when the user is viewing the advertisement; while the advisor is currently available, receiving a user selection of the reference corresponding to the advisor; and a central controller using the selection from the user to establish a real-time communication connection between the advisor and the user prior to the user submitting a question for the advisor, including the central controller establishing a real-time communication with the user and the central controller establishing a real-time communication with the advisor; and the first party charging an amount for the real-time communication connection established between the advisor and the user according to the advertisement. 14. The method of claim 1 , wherein the first party charging the amount comprises: the first party deducting the amount from an amount received from the user. | 0.795866 |
8,700,996 | 14 | 20 | 14. A method of processing content using a computer, the content including one or more of text, numbers, graphic objects, and tables, the method comprising: storing a version of the content in a memory of the computer; displaying a portion of the content on a display of the computer, the portion having text and an object; providing a display of available commands for processing the content, the available commands including wrapping the text around the object; monitoring user actions associated with the displayed portion of the content, the user actions including identifying but not executing one of the available commands for processing the content; in response to the action of identifying but not executing one of the available commands being performed by the user, updating the display of the portion of the content on the display of the computer in accordance with the identified command. | 14. A method of processing content using a computer, the content including one or more of text, numbers, graphic objects, and tables, the method comprising: storing a version of the content in a memory of the computer; displaying a portion of the content on a display of the computer, the portion having text and an object; providing a display of available commands for processing the content, the available commands including wrapping the text around the object; monitoring user actions associated with the displayed portion of the content, the user actions including identifying but not executing one of the available commands for processing the content; in response to the action of identifying but not executing one of the available commands being performed by the user, updating the display of the portion of the content on the display of the computer in accordance with the identified command. 20. The method of claim 14 , further comprising pushing the one identified command onto an undo stack in response to the user confirming execution of the one identified command. | 0.5 |
8,904,283 | 15 | 20 | 15. A non-transitory computer readable medium embodying programmed instructions for generating an Advanced Function Presentation (AFP) document for output, which, when executed by a processor, direct the processor to: add an AFP component to the AFP document; identify a meta-data object (MDO) for the AFP component; insert a Map Data Resource (MDR) structured field corresponding to the AFP component into the AFP document, wherein the MDR specifies the name of the MDO associating the MDO with a specified scope of objects in the AFP component and further includes a processing mode field indicating whether the MDO is descriptive and does not affect the presentation of the AFP component on an output device or indicating whether the MDO is operational and does affect the presentation of the AFP component on the output device; determine the processing mode field; and based on the determination, if the MDO is descriptive, then the MDO is ignored, and if the MDO is operational, then the instructions further direct the processor to perform at least one of: mask a presentation of the AFP component on the output device; eliminate a presentation of the AFP component on the output device; and partially present the AFP component on the output device. | 15. A non-transitory computer readable medium embodying programmed instructions for generating an Advanced Function Presentation (AFP) document for output, which, when executed by a processor, direct the processor to: add an AFP component to the AFP document; identify a meta-data object (MDO) for the AFP component; insert a Map Data Resource (MDR) structured field corresponding to the AFP component into the AFP document, wherein the MDR specifies the name of the MDO associating the MDO with a specified scope of objects in the AFP component and further includes a processing mode field indicating whether the MDO is descriptive and does not affect the presentation of the AFP component on an output device or indicating whether the MDO is operational and does affect the presentation of the AFP component on the output device; determine the processing mode field; and based on the determination, if the MDO is descriptive, then the MDO is ignored, and if the MDO is operational, then the instructions further direct the processor to perform at least one of: mask a presentation of the AFP component on the output device; eliminate a presentation of the AFP component on the output device; and partially present the AFP component on the output device. 20. The non-transitory computer readable medium of claim 15 wherein instructions directing the processor to perform at least one of: mask a presentation of the AFP component on the output device; eliminate a presentation of the AFP component on the output device; and partially present the AFP component on the output device further comprise instructions directing the processor to: partially present the AFP component on the output device based on the determination. | 0.510482 |
8,615,707 | 26 | 36 | 26. A system comprising: a client device comprising a display screen; and one or more computers programmed to interact with the client device and to perform operations comprising: receiving description data describing a preexisting structured presentation, a visual presentation of the preexisting structured presentation visually presenting information in a systematic arrangement that conforms with a structured design, the preexisting structured presentation including values that each characterize a respective attribute of an instance, the preexisting structured presentation denoting characterization of attributes of a particular instance by particular values by virtue of an arrangement of an identifier of the particular instance and the particular values in a visual presentation of the preexisting structured presentation; conducting, by the machine, a search of an unstructured collection of electronic documents by comparing characteristics of the preexisting structured presentation with content of electronic documents in an unstructured collection of electronic documents to locate electronic documents that identify a new attribute that is relevant to the preexisting structured presentation; adding in response to the locating of the electronic documents an identifier of the new attribute to the preexisting structured presentation to form an expanded structured presentation, wherein adding the identifier of the new attribute comprises: formulating a collection of attribute suggestions, wherein formulating the collection of attribute suggestions comprises: identifying a first document in the electronic document collection that is relevant to one of the instances identified in the preexisting structured presentation and that is arranged in accordance with a template, where the template is a pattern for the arrangement of the content of the first document; and adding an attribute used in the first document to characterize the instance in the attribute suggestion collection; providing the attribute suggestion collection to a user; and receiving a user selection of the new attribute, wherein the new attribute is in the collection of attribute suggestions; and outputting instructions for presenting the expanded structured presentation on the display screen. | 26. A system comprising: a client device comprising a display screen; and one or more computers programmed to interact with the client device and to perform operations comprising: receiving description data describing a preexisting structured presentation, a visual presentation of the preexisting structured presentation visually presenting information in a systematic arrangement that conforms with a structured design, the preexisting structured presentation including values that each characterize a respective attribute of an instance, the preexisting structured presentation denoting characterization of attributes of a particular instance by particular values by virtue of an arrangement of an identifier of the particular instance and the particular values in a visual presentation of the preexisting structured presentation; conducting, by the machine, a search of an unstructured collection of electronic documents by comparing characteristics of the preexisting structured presentation with content of electronic documents in an unstructured collection of electronic documents to locate electronic documents that identify a new attribute that is relevant to the preexisting structured presentation; adding in response to the locating of the electronic documents an identifier of the new attribute to the preexisting structured presentation to form an expanded structured presentation, wherein adding the identifier of the new attribute comprises: formulating a collection of attribute suggestions, wherein formulating the collection of attribute suggestions comprises: identifying a first document in the electronic document collection that is relevant to one of the instances identified in the preexisting structured presentation and that is arranged in accordance with a template, where the template is a pattern for the arrangement of the content of the first document; and adding an attribute used in the first document to characterize the instance in the attribute suggestion collection; providing the attribute suggestion collection to a user; and receiving a user selection of the new attribute, wherein the new attribute is in the collection of attribute suggestions; and outputting instructions for presenting the expanded structured presentation on the display screen. 36. The system of claim 26 , wherein the expanded structured presentation comprises a collection of cards. | 0.842262 |
8,495,559 | 16 | 17 | 16. The method of claim 1 , wherein a dependency between various functional modules is derived from the implementation artifacts and is captured as service dependencies and behavioral model in the PSM which is then further transformed into the PIM. | 16. The method of claim 1 , wherein a dependency between various functional modules is derived from the implementation artifacts and is captured as service dependencies and behavioral model in the PSM which is then further transformed into the PIM. 17. The method of claim 16 , wherein a dependency between the various functional modules is derived manually, automatically or semi-automatically using call-graph hierarchy generation techniques. | 0.5 |
8,214,392 | 1 | 12 | 1. A computer automated method of aggregating and presenting data, said method comprising: inputting a set of user-defined instructions into a remotely located computer database system via a public network connection; inputting a user query into said computer database system via said public network connection, the user query comprising one or more data attributes; mining said computer database system for data relevant to said user query; creating a data set comprising said data relevant to said user query; aggregating data in said data set using domain metrics selected based on any of predefined and configurable rules and past user usage, wherein the aggregation comprises: tagging all data attributes in said data set based on database metadata and inputs from a user, wherein said data attributes comprise any of data identifications (IDs), data grouping attributes, and data measure attributes, wherein the tagging process comprises inputting said user query, database metadata for said data attributes in said user query, and attributes specifications; and reducing the number of the tagged data attributes in said data set by logically eliminating data attributes; selecting at least one presentation report for compiling the aggregated data, wherein the selection is based on any of predefined and configurable rules and past user usage; and displaying said at least one presentation report to said user via said public network, wherein the displaying process comprises graphically arranging said at least one presentation report based on an available viewing area of a device accessing said at least one presentation report; wherein for each of said data attributes in said user query, said tagging process comprises tagging the data attribute as a grouping attribute when said data attribute is to be treated as a grouping attribute based on inputs to any of said computer database system and said database metadata; and wherein when said data attribute comprises a grouping attribute and has a number of unique values less than the maximum numbers of unique values allowed to select a database attribute as a grouping attribute, said tagging process comprises tagging said data attribute as a grouping attribute. | 1. A computer automated method of aggregating and presenting data, said method comprising: inputting a set of user-defined instructions into a remotely located computer database system via a public network connection; inputting a user query into said computer database system via said public network connection, the user query comprising one or more data attributes; mining said computer database system for data relevant to said user query; creating a data set comprising said data relevant to said user query; aggregating data in said data set using domain metrics selected based on any of predefined and configurable rules and past user usage, wherein the aggregation comprises: tagging all data attributes in said data set based on database metadata and inputs from a user, wherein said data attributes comprise any of data identifications (IDs), data grouping attributes, and data measure attributes, wherein the tagging process comprises inputting said user query, database metadata for said data attributes in said user query, and attributes specifications; and reducing the number of the tagged data attributes in said data set by logically eliminating data attributes; selecting at least one presentation report for compiling the aggregated data, wherein the selection is based on any of predefined and configurable rules and past user usage; and displaying said at least one presentation report to said user via said public network, wherein the displaying process comprises graphically arranging said at least one presentation report based on an available viewing area of a device accessing said at least one presentation report; wherein for each of said data attributes in said user query, said tagging process comprises tagging the data attribute as a grouping attribute when said data attribute is to be treated as a grouping attribute based on inputs to any of said computer database system and said database metadata; and wherein when said data attribute comprises a grouping attribute and has a number of unique values less than the maximum numbers of unique values allowed to select a database attribute as a grouping attribute, said tagging process comprises tagging said data attribute as a grouping attribute. 12. The method of claim 1 , all the limitations of which are incorporated herein by reference, wherein for each of said data attributes in said user query, said tagging process comprises applying default statistics when user specified statistics are unavailable and tagging the data attribute as a measure when said data attribute is to be treated as a measure based on inputs to any of said computer database system and said database metadata. | 0.5 |
8,812,474 | 1 | 18 | 1. A method, performed by at least one computer, comprising acts of: (A) receiving a query from a user, the query comprising content including at least a first word and a second word; (B) in response to receiving the query, identifying, based at least in part on the content of the query, a first semantic tag indicating a meaning of the first word and a second semantic tag indicating a meaning of the second word; (C) determining a behavior for the user based on the first and second semantic tags, the behavior comprising an inferred intent of the user; and (D) identifying, based on the behavior, (1) at least one search engine from which information related to the content of the query can be retrieved and (2) an action performable by the user that achieves the behavior. | 1. A method, performed by at least one computer, comprising acts of: (A) receiving a query from a user, the query comprising content including at least a first word and a second word; (B) in response to receiving the query, identifying, based at least in part on the content of the query, a first semantic tag indicating a meaning of the first word and a second semantic tag indicating a meaning of the second word; (C) determining a behavior for the user based on the first and second semantic tags, the behavior comprising an inferred intent of the user; and (D) identifying, based on the behavior, (1) at least one search engine from which information related to the content of the query can be retrieved and (2) an action performable by the user that achieves the behavior. 18. The method of claim 1 , wherein the action performable by the user includes posting on Facebook and/or Twitter information related to the content of the query. | 0.810905 |
5,404,435 | 48 | 49 | 48. In a data processing system, a method for archiving voice objects in a document, comprising the steps of: loading an existing index into a data processing system; inputting a document architecture envelope including a text object and an voice object into said system; generating a first key word for said text object from said text object and adding said first key word to said index; automatically generating a second key word for said voice object from said text object and adding said second key word to said index; storing said document architecture envelope in said system; storing said index including said first and second key words in said system; entering a search term into said data processing system; comparing said search term with candidate key words in said index; and retrieving said voice object if said second key word is found in said comparing step. | 48. In a data processing system, a method for archiving voice objects in a document, comprising the steps of: loading an existing index into a data processing system; inputting a document architecture envelope including a text object and an voice object into said system; generating a first key word for said text object from said text object and adding said first key word to said index; automatically generating a second key word for said voice object from said text object and adding said second key word to said index; storing said document architecture envelope in said system; storing said index including said first and second key words in said system; entering a search term into said data processing system; comparing said search term with candidate key words in said index; and retrieving said voice object if said second key word is found in said comparing step. 49. The method of claim 48, wherein said second key word is generated from a caption word string in said text object. | 0.520492 |
4,516,260 | 23 | 27 | 23. An electronic learning aid for training an operator in spelling, said learning aid comprising: memory means for storing digital data including digitized speech data from which one or more words of human speech and the correct spellings thereof may be respectively derived, speech synthesizer means operably associated with said memory means and including means for converting said digitized speech data into audible human speech, means for receiving inputs from an operator of said learning aid, means for providing said digitized speech data from said memory means to said speech synthesizer means, means for randomly selecting a particular word to be spelled by an operator of said learning aid, said particular word being derived from digitized speech data stored in said memory means and converted to audible human speech by said speech synthesizer means, means for comparing an input entered at said operator input means with said correct spelling stored as digital data in said memory means and for generating a result signal indicative of the results of said comparison, and means for generating a response to said operator in accordance with said result signal. | 23. An electronic learning aid for training an operator in spelling, said learning aid comprising: memory means for storing digital data including digitized speech data from which one or more words of human speech and the correct spellings thereof may be respectively derived, speech synthesizer means operably associated with said memory means and including means for converting said digitized speech data into audible human speech, means for receiving inputs from an operator of said learning aid, means for providing said digitized speech data from said memory means to said speech synthesizer means, means for randomly selecting a particular word to be spelled by an operator of said learning aid, said particular word being derived from digitized speech data stored in said memory means and converted to audible human speech by said speech synthesizer means, means for comparing an input entered at said operator input means with said correct spelling stored as digital data in said memory means and for generating a result signal indicative of the results of said comparison, and means for generating a response to said operator in accordance with said result signal. 27. An electronic learning aid according to claim 23, wherein said response generating means includes means for providing digitized speech data to said speech synthesizer means whereby said operator may be audibly informed in human speech of the results of said comparison. | 0.5 |
8,682,082 | 1 | 6 | 1. A method for determining a meaning of traffic symbols, comprising: capturing an image of a symbol using an imaging device selected from a group consisting essentially of a cell phone camera, digital camera, wi-fi camera, and scanner; transmitting image data to an image database, the image data corresponding to the image of the symbol, and captured image location data, the location data comprising a geographical location of the imaging device determining a meaning of the symbol based on the image data and the location data; comparing the image data with symbol data, the symbol data being associated with location data, for determining whether the symbol data includes the captured symbol of the image data; updating the symbol data to include the image data when the symbol data does not include the symbol image data before the updating; and transmitting to a cell phone of a user of the imaging device the meaning of the symbol. | 1. A method for determining a meaning of traffic symbols, comprising: capturing an image of a symbol using an imaging device selected from a group consisting essentially of a cell phone camera, digital camera, wi-fi camera, and scanner; transmitting image data to an image database, the image data corresponding to the image of the symbol, and captured image location data, the location data comprising a geographical location of the imaging device determining a meaning of the symbol based on the image data and the location data; comparing the image data with symbol data, the symbol data being associated with location data, for determining whether the symbol data includes the captured symbol of the image data; updating the symbol data to include the image data when the symbol data does not include the symbol image data before the updating; and transmitting to a cell phone of a user of the imaging device the meaning of the symbol. 6. The method of claim 1 , comprising: identifying a symbol or meaning stored in the image database that corresponds to the symbol of the image data. | 0.678879 |
7,680,862 | 4 | 5 | 4. The relational database management system set forth in claim 1 wherein: the rewrite method determines whether it is possible to produce the SQL string and provides an indication when it is not possible; and the relational database system responds to the indication by not rewriting the SQL statement. | 4. The relational database management system set forth in claim 1 wherein: the rewrite method determines whether it is possible to produce the SQL string and provides an indication when it is not possible; and the relational database system responds to the indication by not rewriting the SQL statement. 5. The relational database management system set forth in claim 4 further comprising: a runtime execution method that is associated with the table function, the relational database management system executing the runtime execution method when the container is executed if the rewrite method has determined that it is not possible to produce the SQL string. | 0.5 |
8,326,860 | 1 | 2 | 1. A method for processing a search query, comprising: receiving a search query containing one or more terms; processing the query to add one or more bi-words as terms to the query; searching a search index embodied on a non-transitory computer-readable storage medium having product identifiers and logical parts of the product identifiers indexed into different fields in the index; generating a score based on at least some of the terms matching the product identifiers and the individual logical parts of the product identifiers in the different fields in the index, wherein bi-words are weighted higher than the terms having only one word when matching in the index and individual terms are weighted higher when matching in the product identifier fields of the index as compared to matching the fields associated with the individual logical parts of the product identifiers; and selecting and outputting an indicator of product identifiers ranked by their scores. | 1. A method for processing a search query, comprising: receiving a search query containing one or more terms; processing the query to add one or more bi-words as terms to the query; searching a search index embodied on a non-transitory computer-readable storage medium having product identifiers and logical parts of the product identifiers indexed into different fields in the index; generating a score based on at least some of the terms matching the product identifiers and the individual logical parts of the product identifiers in the different fields in the index, wherein bi-words are weighted higher than the terms having only one word when matching in the index and individual terms are weighted higher when matching in the product identifier fields of the index as compared to matching the fields associated with the individual logical parts of the product identifiers; and selecting and outputting an indicator of product identifiers ranked by their scores. 2. The method as recited in claim 1 , further comprising attempting to make a best match between the one or more of the terms and the product identifiers and variations thereof when one or more of the terms does not match a complete product identifier or variation thereof. | 0.527682 |
8,261,200 | 1 | 2 | 1. An interactive system for increasing retrieval performance of images depicting text by allowing users to provide relevance feedback on words contained in the images, the system comprising: a processor; one or more persistent storage devices, wherein at least one persistent storage device is coupled to the processor for storing a program of instructions, wherein the program of instructions are executed by the processor to perform a function to implement the system, the function comprising the steps of: receiving a query input comprising one or more query terms from a user through the user interface to locate one or more images included in the one or more persistent storage devices; determining one or more text suggestions related to the one or more query terms, wherein the one or more text suggestions comprise terms that have been identified as being included in the one or more images; retrieving one or more word images from the one or more images related to the one or more text suggestions, wherein each word image is a graphical rendering of a portion of the one or more images that shows a word; creating one or more word image groups from the retrieved word images using one or more similarity measures; wherein the one or more similarity measures includes a location similarity measure, wherein two word images are similar when their bounding box positions within their different corresponding images overlap by more than a given threshold; determining at least one representative word image for each word image group; displaying the representative word image for each word image group to the user via the user interface; and receiving a selection of one or more of the displayed representative word images from the user via the user interface. | 1. An interactive system for increasing retrieval performance of images depicting text by allowing users to provide relevance feedback on words contained in the images, the system comprising: a processor; one or more persistent storage devices, wherein at least one persistent storage device is coupled to the processor for storing a program of instructions, wherein the program of instructions are executed by the processor to perform a function to implement the system, the function comprising the steps of: receiving a query input comprising one or more query terms from a user through the user interface to locate one or more images included in the one or more persistent storage devices; determining one or more text suggestions related to the one or more query terms, wherein the one or more text suggestions comprise terms that have been identified as being included in the one or more images; retrieving one or more word images from the one or more images related to the one or more text suggestions, wherein each word image is a graphical rendering of a portion of the one or more images that shows a word; creating one or more word image groups from the retrieved word images using one or more similarity measures; wherein the one or more similarity measures includes a location similarity measure, wherein two word images are similar when their bounding box positions within their different corresponding images overlap by more than a given threshold; determining at least one representative word image for each word image group; displaying the representative word image for each word image group to the user via the user interface; and receiving a selection of one or more of the displayed representative word images from the user via the user interface. 2. The system of claim 1 , further comprising exclusion by the user of one or more word images to increase precision of image retrieval results for the one or more query terms. | 0.705686 |
8,036,432 | 3 | 4 | 3. The system of claim 1 , wherein the face descriptor is a feature vector extracted from an image of a person in the digital content. | 3. The system of claim 1 , wherein the face descriptor is a feature vector extracted from an image of a person in the digital content. 4. The system of claim 3 , wherein the cluster classification unit classifies the new digital content and the plurality of digital content by the person-based clustering through comparison of feature vector distances using the feature vectors. | 0.5 |
8,140,326 | 18 | 31 | 18. A system for reducing speech intelligibility while preserving environmental sounds, the system comprising: a receiving module for receiving an audio signal; a voicing detector for processing the audio signal to separate a vocalic region that comprises vowels; a computation module for computing a representation of at least the vocalic regions, the representation including at least a vocal tract transfer function and an excitation; a replacement module for replacing the vocal tract transfer function of the vocalic region with a replacement vocal tract transfer function of a replacement sound to create a modified vocal tract transfer function; and an audio synthesizer for synthesizing a modified audio signal of at least the vocalic region from the modified vocal tract transfer function and the excitation. | 18. A system for reducing speech intelligibility while preserving environmental sounds, the system comprising: a receiving module for receiving an audio signal; a voicing detector for processing the audio signal to separate a vocalic region that comprises vowels; a computation module for computing a representation of at least the vocalic regions, the representation including at least a vocal tract transfer function and an excitation; a replacement module for replacing the vocal tract transfer function of the vocalic region with a replacement vocal tract transfer function of a replacement sound to create a modified vocal tract transfer function; and an audio synthesizer for synthesizing a modified audio signal of at least the vocalic region from the modified vocal tract transfer function and the excitation. 31. The system of claim 18 , wherein the replacement module randomly selects the replacement sound. | 0.756158 |
9,076,459 | 1 | 14 | 1. A method of operation in a speech recognition system, the method comprising: analyzing each of a plurality of frames of audio by a sound classifier; classifying a first number of the frames of audio as speech by the sound classifier; classifying a second number of the frames of audio as non-transient background noise by the sound classifier; classifying a third number of the frames of audio as transient noise events by the sound classifier; and providing signals indicative at least of the classifications of the frames of audio to a speech recognizer. | 1. A method of operation in a speech recognition system, the method comprising: analyzing each of a plurality of frames of audio by a sound classifier; classifying a first number of the frames of audio as speech by the sound classifier; classifying a second number of the frames of audio as non-transient background noise by the sound classifier; classifying a third number of the frames of audio as transient noise events by the sound classifier; and providing signals indicative at least of the classifications of the frames of audio to a speech recognizer. 14. The method of operation of claim 1 , further comprising: generating features based at least in part on the received classifications of the frames of audio. | 0.817661 |
8,239,342 | 5 | 6 | 5. A method as claimed in claim 1 wherein the newly created item in the creation event is a new relationship. | 5. A method as claimed in claim 1 wherein the newly created item in the creation event is a new relationship. 6. A method as claimed in claim 5 further comprising the step of: enabling user modification of default classification of source node and destination node of the new relationship. | 0.5 |
9,104,781 | 12 | 17 | 12. A system, comprising: a processor; and a memory coupled to the processor, the memory having program instructions stored thereon that, upon execution by the processor, cause the system to: store metadata derived from an imperative statement of a program, the metadata computed using runtime state available when the program is executing, the program executable a managed runtime environment, the metadata associated with lookup data, the lookup data derived from an identifier and a parameter that indicates how to obtain the metadata, and the imperative statement including one or more of: the metadata, code that when executed computes the metadata, or a reference to code that when executed computes the metadata, wherein the metadata does not influence the logical flow of the program but influences the behavior of the managed runtime environment, and wherein the metadata is usable by the managed runtime environment to determine whether an exception is to be raised to a debugger; instructions of the program and maintain the runtime state; receive the identifier and a parameter that indicates how to obtain the metadata; and use the identifier and the parameter to obtain the metadata, the metadata manager further operable to provide the metadata to a requestor of the metadata. | 12. A system, comprising: a processor; and a memory coupled to the processor, the memory having program instructions stored thereon that, upon execution by the processor, cause the system to: store metadata derived from an imperative statement of a program, the metadata computed using runtime state available when the program is executing, the program executable a managed runtime environment, the metadata associated with lookup data, the lookup data derived from an identifier and a parameter that indicates how to obtain the metadata, and the imperative statement including one or more of: the metadata, code that when executed computes the metadata, or a reference to code that when executed computes the metadata, wherein the metadata does not influence the logical flow of the program but influences the behavior of the managed runtime environment, and wherein the metadata is usable by the managed runtime environment to determine whether an exception is to be raised to a debugger; instructions of the program and maintain the runtime state; receive the identifier and a parameter that indicates how to obtain the metadata; and use the identifier and the parameter to obtain the metadata, the metadata manager further operable to provide the metadata to a requestor of the metadata. 17. The system of claim 12 , wherein the program instructions, upon execution by the processor, further cause the system to determine a scope in which a requestor requested the metadata and to provide the scope to the metadata manager, wherein the metadata manager is further operable to use the scope to limit the metadata to metadata associated with the scope. | 0.5 |
9,257,115 | 15 | 22 | 15. A computer-based device comprising: at least one microphone; a screen display; at least one data storage unit for storing digital data; a first automatic speech recognition module for automatically recognizing speech input by a first speaker received by the at least one microphone, wherein automatically recognizing the speech input by the first speaker comprises: receiving the speech input from the first speaker; determining a recognized speech result based on the received speech input; an interactive disambiguation module for a determining whether there exists a recognition ambiguity in the recognized speech result of the first speaker, wherein the recognition ambiguity indicates more than one possible match for the recognized speech result, and for determining whether there exists a translation ambiguity for one or more words in the translation of the recognized speech result of the first speaker in the first language into the second language, wherein the translation ambiguity indicates more than one possible translation of the one or more words; a first machine translation module for translating the recognized speech result of the first speaker in the first language into a second language; and wherein the interactive disambiguation module is further configured for, upon a determination that there is either (i) a recognition ambiguity in the recognized speech result of the first speaker or (ii) a translation ambiguity in the translation of the recognized speech result of the first speaker in the first language into the second language, determining a confidence score based on the recognition or translation ambiguity, and responsive to the confidence score being below a threshold, issuing by the computer-based speech translation system a disambiguation query to the first speaker via a user-interface of the speech translation system, wherein a response to the disambiguation query resolves the recognition or translation ambiguity. | 15. A computer-based device comprising: at least one microphone; a screen display; at least one data storage unit for storing digital data; a first automatic speech recognition module for automatically recognizing speech input by a first speaker received by the at least one microphone, wherein automatically recognizing the speech input by the first speaker comprises: receiving the speech input from the first speaker; determining a recognized speech result based on the received speech input; an interactive disambiguation module for a determining whether there exists a recognition ambiguity in the recognized speech result of the first speaker, wherein the recognition ambiguity indicates more than one possible match for the recognized speech result, and for determining whether there exists a translation ambiguity for one or more words in the translation of the recognized speech result of the first speaker in the first language into the second language, wherein the translation ambiguity indicates more than one possible translation of the one or more words; a first machine translation module for translating the recognized speech result of the first speaker in the first language into a second language; and wherein the interactive disambiguation module is further configured for, upon a determination that there is either (i) a recognition ambiguity in the recognized speech result of the first speaker or (ii) a translation ambiguity in the translation of the recognized speech result of the first speaker in the first language into the second language, determining a confidence score based on the recognition or translation ambiguity, and responsive to the confidence score being below a threshold, issuing by the computer-based speech translation system a disambiguation query to the first speaker via a user-interface of the speech translation system, wherein a response to the disambiguation query resolves the recognition or translation ambiguity. 22. The device of claim 15 , further comprising a multimodal interaction interface to solicit feedback from at least one of the first speaker and the second speaker prior to entering of the extracted information in the electronic form. | 0.883433 |
9,516,134 | 10 | 11 | 10. One or more non-transitory computer readable storage media storing computer executable instructions that, when executed, cause a device to: determine potential members associated with a user based on an electronic mailbox associated with the user; determine a plurality of conversion rates respectively for a plurality of invitations based on a respective number of persons that joined a contact information sharing network after being sent a respective one of the plurality of invitations to join the contact information sharing network; determine, based on the plurality of conversion rates, a highest conversion rate invitation of the plurality of invitations; and send, to at least a subset of the potential members, the highest conversion rate invitation. | 10. One or more non-transitory computer readable storage media storing computer executable instructions that, when executed, cause a device to: determine potential members associated with a user based on an electronic mailbox associated with the user; determine a plurality of conversion rates respectively for a plurality of invitations based on a respective number of persons that joined a contact information sharing network after being sent a respective one of the plurality of invitations to join the contact information sharing network; determine, based on the plurality of conversion rates, a highest conversion rate invitation of the plurality of invitations; and send, to at least a subset of the potential members, the highest conversion rate invitation. 11. The one of more non-transitory computer readable storage media of claim 10 , further comprising computer executable instructions that, when executed, cause the device to: select a subset of aesthetic appeal related features from a variety of aesthetic appeal related features to be included in the highest conversion rate invitation based on empirical data showing the subset of the aesthetic appeal related features is statistically determined to prompt a response to the highest conversion rate invitation. | 0.5 |
8,073,701 | 12 | 13 | 12. The system of claim 9 , wherein a second visual representation of frequency relationships within a previously recorded word is generated using said method, said second visual representation being displayed simultaneously on said display with said first visual representation. | 12. The system of claim 9 , wherein a second visual representation of frequency relationships within a previously recorded word is generated using said method, said second visual representation being displayed simultaneously on said display with said first visual representation. 13. The system of claim 12 , wherein the brightness of said first line transitions from a relatively dimmer state to a relatively brighter state on said display when said first visual representation matches said second visual representation. | 0.5 |
7,962,495 | 9 | 10 | 9. A data storage system, comprising: one or more processors; a data store; an ontology coupled to the data store and comprising a plurality of data object types and a plurality of object property types; wherein each object property type, of the plurality of object property types, includes a data type of data that is associated with said each object property type; a parser coupled to the ontology and configured to receive input data and transform the input data into modified data to store in a property specified by one of the property types according to one or more parser definitions; wherein each of the object property types comprises one or more of the parser definitions, wherein each of the parser definitions specifies one or more sub-definitions of how to transform portions of first input data into modified input data that is to be stored in components of one of the object property types of the ontology for the data store. | 9. A data storage system, comprising: one or more processors; a data store; an ontology coupled to the data store and comprising a plurality of data object types and a plurality of object property types; wherein each object property type, of the plurality of object property types, includes a data type of data that is associated with said each object property type; a parser coupled to the ontology and configured to receive input data and transform the input data into modified data to store in a property specified by one of the property types according to one or more parser definitions; wherein each of the object property types comprises one or more of the parser definitions, wherein each of the parser definitions specifies one or more sub-definitions of how to transform portions of first input data into modified input data that is to be stored in components of one of the object property types of the ontology for the data store. 10. The system of claim 9 , wherein the parser further comprises logic which when executed by the one or more processors in the system causes the one or more processors to perform: receiving the first input data; determining whether the first input data matches one of the parser definitions; using the transformation expressed in the matching parser definition to transform portions of the input to components of the object property to create and store the modified input data; storing the modified input data in a property of the property type that is identified in the matching one of the parser definitions. | 0.587162 |
9,223,537 | 1 | 5 | 1. One or more non-transitory computer-readable media storing computer-executable instructions that, when executed on one or more processors, cause the one or more processors of a virtual assistant service to perform acts comprising: generating data for a conversation graphical user interface (GUI) that represents a virtual assistant; causing display of the conversation GUI via a computing device to enable a conversation between the virtual assistant and a user of the computing device; receiving user input that is provided via the conversation GUI, the user input comprising one of audio input, keypad input, or touch input; parsing the user input with a natural language processing system that employs a language model; determining, with the natural language processing system, a response based at least in part on (i) the parsed user input and (ii) at least one of content of a service provider, content of the virtual assistant service, or content of the computing device of the user; identifying an assumption that is used to determine the response, the assumption comprising at least one of the language model that is employed by the natural language processing system, a profile for the user, or a learned behavior of the user; causing display of a dialog representation in the conversation GUI for the user input; causing display of a dialog representation in the conversation GUI for the response; causing display of the assumption in the conversation GUI; enabling the user to interact with the conversation GUI to modify the assumption; receiving a modification to the assumption; determining a revised response based at least in part on the modification to the assumption; and causing display of the revised response in the conversation GUI. | 1. One or more non-transitory computer-readable media storing computer-executable instructions that, when executed on one or more processors, cause the one or more processors of a virtual assistant service to perform acts comprising: generating data for a conversation graphical user interface (GUI) that represents a virtual assistant; causing display of the conversation GUI via a computing device to enable a conversation between the virtual assistant and a user of the computing device; receiving user input that is provided via the conversation GUI, the user input comprising one of audio input, keypad input, or touch input; parsing the user input with a natural language processing system that employs a language model; determining, with the natural language processing system, a response based at least in part on (i) the parsed user input and (ii) at least one of content of a service provider, content of the virtual assistant service, or content of the computing device of the user; identifying an assumption that is used to determine the response, the assumption comprising at least one of the language model that is employed by the natural language processing system, a profile for the user, or a learned behavior of the user; causing display of a dialog representation in the conversation GUI for the user input; causing display of a dialog representation in the conversation GUI for the response; causing display of the assumption in the conversation GUI; enabling the user to interact with the conversation GUI to modify the assumption; receiving a modification to the assumption; determining a revised response based at least in part on the modification to the assumption; and causing display of the revised response in the conversation GUI. 5. One or more non-transitory computer-readable media as recited in claim 1 , wherein the acts further comprise learning, from past user behavior, what assumptions should be used in making the determination of the response. | 0.766247 |
7,996,383 | 5 | 6 | 5. The search engine of claim 3 , wherein the index comprises a matrix of term units, wherein each term unit is a set of characters that is separated by a space from another term unit; and the Duplicate Blocker module operates to locate duplicate term units within the index. | 5. The search engine of claim 3 , wherein the index comprises a matrix of term units, wherein each term unit is a set of characters that is separated by a space from another term unit; and the Duplicate Blocker module operates to locate duplicate term units within the index. 6. The search engine of claim 5 , wherein the Duplicate Blocker module operates to locate duplicate term units without grammatical form. | 0.719008 |
9,934,224 | 1 | 9 | 1. A computer implemented method, comprising: at a server system having one or more processors and memory storing one or more programs executed by the one or more processors, in a document editor application executed by the server system: receiving from a respective client system a subset of an existing document, wherein the subset is identified in accordance with a user action within the existing document and displayed at the respective client system; in response to receiving from the respective client system the subset of the existing document: identifying a most recently edited portion of the document, and a remainder portion of the subset of the document that excludes the most recently edited portion; identifying one or more key words in the received subset of the document as query terms of a search query, wherein the received subset of the document includes additional terms distinct from the identified one or more key words, and wherein: the one or more key words in the received subset of the document correspond to a difference set of words, the difference set of words comprises words included in a first set of words other than words included in a second set of words, the first set of words includes high ranking words among words in a most recently edited paragraph, in the most recently edited portion, ranked in accordance with inverse document frequency values, and the second set of words includes high ranking words among words in the remainder portion of the document ranked in accordance with inverse document frequency values; identifying one or more information items, including initiating a search by sending the search query to a search engine system distinct from the server system, the search query having the one or more key words identified in the subset of the document as the query terms of the search query; and sending to the respective client system, for display at the respective client system, a focus region of each of the one or more identified information items, each focus region comprising a region of a respective identified information item corresponding to at least one of the one or more key words; receiving a selection of an information item in the one or more identified information items, the selection by a user associated with the respective client system; and in response to receiving the selection of the information item, modifying the document by inserting a citation to the selected information item. | 1. A computer implemented method, comprising: at a server system having one or more processors and memory storing one or more programs executed by the one or more processors, in a document editor application executed by the server system: receiving from a respective client system a subset of an existing document, wherein the subset is identified in accordance with a user action within the existing document and displayed at the respective client system; in response to receiving from the respective client system the subset of the existing document: identifying a most recently edited portion of the document, and a remainder portion of the subset of the document that excludes the most recently edited portion; identifying one or more key words in the received subset of the document as query terms of a search query, wherein the received subset of the document includes additional terms distinct from the identified one or more key words, and wherein: the one or more key words in the received subset of the document correspond to a difference set of words, the difference set of words comprises words included in a first set of words other than words included in a second set of words, the first set of words includes high ranking words among words in a most recently edited paragraph, in the most recently edited portion, ranked in accordance with inverse document frequency values, and the second set of words includes high ranking words among words in the remainder portion of the document ranked in accordance with inverse document frequency values; identifying one or more information items, including initiating a search by sending the search query to a search engine system distinct from the server system, the search query having the one or more key words identified in the subset of the document as the query terms of the search query; and sending to the respective client system, for display at the respective client system, a focus region of each of the one or more identified information items, each focus region comprising a region of a respective identified information item corresponding to at least one of the one or more key words; receiving a selection of an information item in the one or more identified information items, the selection by a user associated with the respective client system; and in response to receiving the selection of the information item, modifying the document by inserting a citation to the selected information item. 9. The method of claim 1 , further comprising: retrieving a user profile of the user associated with the respective client system, wherein the user profile includes filtering criteria for one or more of: sources, categories of information, timing criteria, banned keywords, and required keywords, wherein initiating the search to identify the one or more information items includes identifying the one or more information items corresponding to the user profile and the one or more key words. | 0.5 |
8,433,715 | 13 | 14 | 13. A system for ontology driven data mining, comprising: an informatics system coupled to a plurality of data sources, the informatics system comprising a processor and a non-transitory computer readable medium comprising instructions for: receiving a clinical text as input from one or more of the plurality of data sources; creating a graph representation of the input, wherein creating the graph representation of the input comprises parsing the input to create a parse graph; obtaining a graph representation of a semantic ontology, wherein the semantic ontology comprises a set of concepts and a set of relationships; mapping the graph representation of the input to the graph representation of the semantic ontology to create a unified graph comprising the graph representation of the input and the graph of the semantic ontology, wherein mapping the graph representation of the input to the graph representation of the ontology to create a unified graph comprises mapping the parse graph to a domain ontology and using mapping between the parse graph and the domain ontology to map the parse graph to the semantic ontology; constructing a query based on at least one of the set of concepts or at least one of the set of relationships of the semantic ontology; and searching the unified graph based on the query to obtain data of the input associated with the at least one concept or the at least one relationship. | 13. A system for ontology driven data mining, comprising: an informatics system coupled to a plurality of data sources, the informatics system comprising a processor and a non-transitory computer readable medium comprising instructions for: receiving a clinical text as input from one or more of the plurality of data sources; creating a graph representation of the input, wherein creating the graph representation of the input comprises parsing the input to create a parse graph; obtaining a graph representation of a semantic ontology, wherein the semantic ontology comprises a set of concepts and a set of relationships; mapping the graph representation of the input to the graph representation of the semantic ontology to create a unified graph comprising the graph representation of the input and the graph of the semantic ontology, wherein mapping the graph representation of the input to the graph representation of the ontology to create a unified graph comprises mapping the parse graph to a domain ontology and using mapping between the parse graph and the domain ontology to map the parse graph to the semantic ontology; constructing a query based on at least one of the set of concepts or at least one of the set of relationships of the semantic ontology; and searching the unified graph based on the query to obtain data of the input associated with the at least one concept or the at least one relationship. 14. The system of claim 13 , wherein the domain ontology comprises UMLS-SKOS. | 0.5 |
10,083,031 | 18 | 19 | 18. The computer program product of claim 17 , wherein for building a behavior evolution model for a software application, said product further comprising instructions causing the processor to perform: obtaining the application name, historical version labels, release timestamps from each released version, and rating information of each version of the application; and tracking application versions by linking versions with release timestamps and said rating information, said building said behavior evolution model comprising linking features and release versions with change labels, said change labels being labels introduced, deleted or refined. | 18. The computer program product of claim 17 , wherein for building a behavior evolution model for a software application, said product further comprising instructions causing the processor to perform: obtaining the application name, historical version labels, release timestamps from each released version, and rating information of each version of the application; and tracking application versions by linking versions with release timestamps and said rating information, said building said behavior evolution model comprising linking features and release versions with change labels, said change labels being labels introduced, deleted or refined. 19. The computer program product of claim 18 , wherein said product further comprising instructions for configuring said processor to perform: computing an intra-application feature snapshot for each version of each application; computing an inter-application feature snapshot for each category of applications in a certain timestamp; and computing, based on a computed an intra-application feature snapshot and a computed inter-application feature snapshot, an insight extraction rule relating to one or more various feature insights for user preferences to be extracted and generated, said one or more various feature insights for user preferences comprises: a surprising feature, a must-have feature, a failure feature, a co-occurring feature, a continuously-improved feature, a seldom-but-interesting feature. | 0.5 |
9,129,009 | 1 | 13 | 1. A method of providing related links in a web page, comprising: retrieving textual information associated with a web page upon loading of the web page at a client device; extracting, by one or more computers, a set of keywords from the received textual information, wherein the keywords are representative of content of the web page, wherein extracting the set of keywords from the received textual information includes: parsing the textual information associated with the web page to identify a language of the textual information, segmenting each text segment in the textual information into a set of separate words or phrases in accordance with the identified language of the textual information, removing the stop words of the identified language from the set of separate words or phrases, and returning the set of words or phrases as the set of keywords; ranking the extracted set of keywords using a keyword repository, wherein the keyword repository maintains a list of keywords and their respective rankings; selecting one or more representative keywords from the extracted set of keywords based on the ranking; sending the one or more representative keywords as a search query to a search engine to obtain a list of search results ordered by their respective rankings; and returning a specified number of search results with the highest rankings to the client for display, wherein the received search results are responsive to the one or more representative keywords extracted from textual information associated with a web page loading at a client device and wherein the received search results are displayed as related links within a particular designated region of the web page, wherein the related links are links to other web pages related to the loading web page. | 1. A method of providing related links in a web page, comprising: retrieving textual information associated with a web page upon loading of the web page at a client device; extracting, by one or more computers, a set of keywords from the received textual information, wherein the keywords are representative of content of the web page, wherein extracting the set of keywords from the received textual information includes: parsing the textual information associated with the web page to identify a language of the textual information, segmenting each text segment in the textual information into a set of separate words or phrases in accordance with the identified language of the textual information, removing the stop words of the identified language from the set of separate words or phrases, and returning the set of words or phrases as the set of keywords; ranking the extracted set of keywords using a keyword repository, wherein the keyword repository maintains a list of keywords and their respective rankings; selecting one or more representative keywords from the extracted set of keywords based on the ranking; sending the one or more representative keywords as a search query to a search engine to obtain a list of search results ordered by their respective rankings; and returning a specified number of search results with the highest rankings to the client for display, wherein the received search results are responsive to the one or more representative keywords extracted from textual information associated with a web page loading at a client device and wherein the received search results are displayed as related links within a particular designated region of the web page, wherein the related links are links to other web pages related to the loading web page. 13. The method of claim 1 , wherein each returned search result comprises at least the title of the web page of the search result and the URL of the web page of the search result. | 0.752078 |
8,688,602 | 30 | 31 | 30. The computer readable medium of claim 29 , further comprising instructions to: collect feedback relating to the correspondence; and modify the correspondence responsive to the feedback. | 30. The computer readable medium of claim 29 , further comprising instructions to: collect feedback relating to the correspondence; and modify the correspondence responsive to the feedback. 31. The computer readable medium of claim 30 , wherein the feedback is collected from a plurality of end-users. | 0.5 |
6,021,218 | 1 | 9 | 1. A method of formatting handwritten input entered in a pointer-based computer system having a display screen on which the path of the pointer is displayed as ink, the method comprising the following steps: analyzing the handwritten input with a word recognizer to identify some parts of the handwritten input as recognized text words and other, different parts of the handwritten input as unrecognized ink words, the unrecognized ink words being displayed on the display screen in their handwritten input form and the recognized text words appearing in a standard font; grouping the recognized text words and the unrecognized ink words into one or more paragraphs containing both a recognized text word and an unrecognized ink word; formatting the recognized text words and unrecognized ink words by adjusting their positions with respect to one another within the one or more paragraphs so that the paragraphs have one or more lines, at least one of which has a plurality of words, wherein the words in each line are separated from one another by defined word separation distances; and displaying the formatted paragraphs on said display screen such that both unrecognized ink words and recognized text words are contiguously displayed in the same paragraphs, the unrecognized ink words being displayed in their handwritten input form and the recognized text words being displayed in a standard font within the formatted paragraphs, wherein the steps of analyzing, grouping, and formatting are performed by said computer system. | 1. A method of formatting handwritten input entered in a pointer-based computer system having a display screen on which the path of the pointer is displayed as ink, the method comprising the following steps: analyzing the handwritten input with a word recognizer to identify some parts of the handwritten input as recognized text words and other, different parts of the handwritten input as unrecognized ink words, the unrecognized ink words being displayed on the display screen in their handwritten input form and the recognized text words appearing in a standard font; grouping the recognized text words and the unrecognized ink words into one or more paragraphs containing both a recognized text word and an unrecognized ink word; formatting the recognized text words and unrecognized ink words by adjusting their positions with respect to one another within the one or more paragraphs so that the paragraphs have one or more lines, at least one of which has a plurality of words, wherein the words in each line are separated from one another by defined word separation distances; and displaying the formatted paragraphs on said display screen such that both unrecognized ink words and recognized text words are contiguously displayed in the same paragraphs, the unrecognized ink words being displayed in their handwritten input form and the recognized text words being displayed in a standard font within the formatted paragraphs, wherein the steps of analyzing, grouping, and formatting are performed by said computer system. 9. The method of claim 1 wherein the step of grouping the recognized text words and the unrecognized words into one or more paragraphs includes a step of determining whether each recognized text word or unrecognized ink word overlaps an existing paragraph. | 0.735537 |
8,326,343 | 6 | 7 | 6. The mobile communication terminal of claim 1 , wherein the controller obtains information on an attached object, and identifies depths of the activated object and the attached object when the activated object includes an attached object. | 6. The mobile communication terminal of claim 1 , wherein the controller obtains information on an attached object, and identifies depths of the activated object and the attached object when the activated object includes an attached object. 7. The mobile communication terminal of claim 6 , wherein the controller finds speech data sets mapped to the identified depths of the activated and attached objects, and controls output of audible signals corresponding to textual contents of the activated and attached objects using corresponding mapped speech data sets. | 0.5 |
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