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7,801,942 | 11 | 12 | 11. A method for enabling search results including screen snapshots, the method comprising: visiting a web site on a network; collecting search terms from the web site; taking a screen snapshot of the web site; storing the search terms and screen snapshot in a database; receiving a search query from a user; searching the database to respond to the search query, thereby locating the web site; providing the user with search results based on the search terms, wherein the search results include: a link to the web site; and the screen snapshot of the web site; collecting demographic information of the user, the demographic information including age, income level, and employment history; and targeting an ad placement and targeting the search results to the user responsive to the demographic information. | 11. A method for enabling search results including screen snapshots, the method comprising: visiting a web site on a network; collecting search terms from the web site; taking a screen snapshot of the web site; storing the search terms and screen snapshot in a database; receiving a search query from a user; searching the database to respond to the search query, thereby locating the web site; providing the user with search results based on the search terms, wherein the search results include: a link to the web site; and the screen snapshot of the web site; collecting demographic information of the user, the demographic information including age, income level, and employment history; and targeting an ad placement and targeting the search results to the user responsive to the demographic information. 12. A method for enabling search results according to claim 11 , wherein collecting the search terms from the web site includes resolving at least one uniform resource locator (URL), and wherein taking the screen snapshot includes queuing a request to an imager to take the screen snapshot responsive to the resolving. | 0.5 |
8,930,372 | 14 | 15 | 14. A computer-executable program product stored in at least one non-transitory storage medium that causes a computer to execute a set of programmatic instructions, said computer-executable program product comprising: computer program code, which is stored in at least one non-transitory storage medium, configured to extract a character string from each of a plurality of documents of information stored in a computer-accessible form; computer program code, which is stored in at least one non-transitory storage medium, configured to execute a combination of at least two different types of character string analyses and assign a plurality of different kinds of tokens to each document with each kind of token obtained by applying a corresponding character string analysis to the character string extracted from that document; computer program code, which is stored in at least one non-transitory storage medium, configured to receive a search word used upon referencing the information, and extract a plurality of kinds of search tokens from the search word by applying the different types of character string analyses to the search word; link the plurality of kinds of search tokens extracted from the search word in parallel to issue a search command to inquire the information in parallel; computer program code, which is stored in at least one non-transitory storage medium, configured to send the search command to an index list that registers the tokens, a plurality of token types identifying a corresponding type of the character string analysis used, an information identification value for identifying the registered information, and a score for each of the plurality of kinds of tokens; computer program code, which is stored in at least one non-transitory storage medium, configured to search the index list based on the search tokens in the search command and determine a total score for each of one or more documents of the information by identifying one or more of the plurality of kinds of tokens assigned to that document matching the search tokens of the search word and combining the scores of each of the identified plurality of kinds of tokens; and computer program code, which is stored in at least one non-transitory storage medium, configured to display results of the searching of the index list as a search result and ordering the results based on the total scores for the one or more documents. | 14. A computer-executable program product stored in at least one non-transitory storage medium that causes a computer to execute a set of programmatic instructions, said computer-executable program product comprising: computer program code, which is stored in at least one non-transitory storage medium, configured to extract a character string from each of a plurality of documents of information stored in a computer-accessible form; computer program code, which is stored in at least one non-transitory storage medium, configured to execute a combination of at least two different types of character string analyses and assign a plurality of different kinds of tokens to each document with each kind of token obtained by applying a corresponding character string analysis to the character string extracted from that document; computer program code, which is stored in at least one non-transitory storage medium, configured to receive a search word used upon referencing the information, and extract a plurality of kinds of search tokens from the search word by applying the different types of character string analyses to the search word; link the plurality of kinds of search tokens extracted from the search word in parallel to issue a search command to inquire the information in parallel; computer program code, which is stored in at least one non-transitory storage medium, configured to send the search command to an index list that registers the tokens, a plurality of token types identifying a corresponding type of the character string analysis used, an information identification value for identifying the registered information, and a score for each of the plurality of kinds of tokens; computer program code, which is stored in at least one non-transitory storage medium, configured to search the index list based on the search tokens in the search command and determine a total score for each of one or more documents of the information by identifying one or more of the plurality of kinds of tokens assigned to that document matching the search tokens of the search word and combining the scores of each of the identified plurality of kinds of tokens; and computer program code, which is stored in at least one non-transitory storage medium, configured to display results of the searching of the index list as a search result and ordering the results based on the total scores for the one or more documents. 15. The computer-executable program product according to claim 14 , further comprising: computer program code, which is stored in at least one non-transitory storage medium, configured to order the results in descending order of the total scores. | 0.5 |
9,014,762 | 3 | 10 | 3. A character input device, comprising: a display unit; a touch sensor for detecting a contact with a surface thereof; a character recognition processing unit for performing a first character recognition process for recognizing a character used for a first function and a second character recognition process for recognizing a character used for a second function, on the basis of a locus connecting positions where the contact is detected by the touch sensor; and an input control unit for displaying, on the display unit, a first input screen for the first function onto which the character recognized by the first character recognition process is input and/or a second input screen for the second function onto which the character recognized by the second character recognition process is input, wherein the input control unit is configured to display the first input screen and/or the second input screen on the display unit, on the basis of a recognition accuracy of the character by the first character recognition process and a recognition accuracy of the character by the second character recognition process. | 3. A character input device, comprising: a display unit; a touch sensor for detecting a contact with a surface thereof; a character recognition processing unit for performing a first character recognition process for recognizing a character used for a first function and a second character recognition process for recognizing a character used for a second function, on the basis of a locus connecting positions where the contact is detected by the touch sensor; and an input control unit for displaying, on the display unit, a first input screen for the first function onto which the character recognized by the first character recognition process is input and/or a second input screen for the second function onto which the character recognized by the second character recognition process is input, wherein the input control unit is configured to display the first input screen and/or the second input screen on the display unit, on the basis of a recognition accuracy of the character by the first character recognition process and a recognition accuracy of the character by the second character recognition process. 10. The character input device according to claim 3 , wherein the input control unit is configured to process a cumulative total value or a representative value of the recognition accuracy of the character recognized by the first character recognition process as the recognition accuracy of the character by the first character recognition process, and process a cumulative total value or a representative value of the recognition accuracy of the character recognized by the second character recognition process as the recognition accuracy of the character by the second character recognition process. | 0.646054 |
9,553,842 | 1 | 2 | 1. A method, comprising: detecting, via a processor, a message posted on a website data source from an end user, the message posting being related to a predefined monitored entity; performing via the processor, a natural language interpretation of the message contents responsive to identifying the message posting being related to the predefined monitored entity; processing via the processor, the message to determine the user's topic of interest; generating via a processor, a response to the message responsive to the user's topic of interest; and sending, via a transmitter, the response to the end user; wherein the end user is identified by matching user specific information included in the message to pre-stored user specific information stored in a database. | 1. A method, comprising: detecting, via a processor, a message posted on a website data source from an end user, the message posting being related to a predefined monitored entity; performing via the processor, a natural language interpretation of the message contents responsive to identifying the message posting being related to the predefined monitored entity; processing via the processor, the message to determine the user's topic of interest; generating via a processor, a response to the message responsive to the user's topic of interest; and sending, via a transmitter, the response to the end user; wherein the end user is identified by matching user specific information included in the message to pre-stored user specific information stored in a database. 2. The method of claim 1 , further comprising calculating a confidence score representing a likelihood that the response is accurate prior to sending the response to the end user. | 0.587558 |
8,140,547 | 1 | 5 | 1. A computer-implemented method for generating calculation context classes from a relationship between structured data and a calculation procedure, the context classes having parent-child relationships, the method comprising: searching the calculation procedure for at least one of a first data definition and an operation, wherein the calculation procedure is configured to derive Key Performance Indicators from a business operation, and wherein the context classes having the parent-child relationships are from the Key Performance Indicators; in response to identifying the operation, registering the operation for the first data definition that is an input of the operation and registering the operation for the first data definition that is an output of the operation; generating a first context from a first scope applied to the first data definition; tracing back the calculation procedure to obtain a second data definition for calculating the first data definition and to which the first scope is applied; copying the calculation procedure into the first context until the second data definition is obtained; obtaining a second scope applied to the second data definition; obtaining a second context generated from the second scope; determining an existence of an order comparison of the first scope with the second scope; obtaining an order from the structured data; in response to the second scope being less than the first scope, registering the first context as a parent and the second context as a child; in response to the second scope being greater than the first scope, registering the second context as a parent and the first context as a child; and in response to the second scope being equal to the first scope, registering both the first and second contexts as a single context class, and registering both the first and second scopes as a single scope of the single context class, wherein in response to an inability to compare an order of the first scope with an order of the second scope, the first and second contexts exist independently without a parent-child relationship, wherein the first and second scopes each describe a level of business operations at which the Key Performance Indicators are to be monitored, the first and second scopes each holding a name, a level name of structured data concerning the operation, and an event mapping rule for deriving an identifier for each of the first and second scopes. | 1. A computer-implemented method for generating calculation context classes from a relationship between structured data and a calculation procedure, the context classes having parent-child relationships, the method comprising: searching the calculation procedure for at least one of a first data definition and an operation, wherein the calculation procedure is configured to derive Key Performance Indicators from a business operation, and wherein the context classes having the parent-child relationships are from the Key Performance Indicators; in response to identifying the operation, registering the operation for the first data definition that is an input of the operation and registering the operation for the first data definition that is an output of the operation; generating a first context from a first scope applied to the first data definition; tracing back the calculation procedure to obtain a second data definition for calculating the first data definition and to which the first scope is applied; copying the calculation procedure into the first context until the second data definition is obtained; obtaining a second scope applied to the second data definition; obtaining a second context generated from the second scope; determining an existence of an order comparison of the first scope with the second scope; obtaining an order from the structured data; in response to the second scope being less than the first scope, registering the first context as a parent and the second context as a child; in response to the second scope being greater than the first scope, registering the second context as a parent and the first context as a child; and in response to the second scope being equal to the first scope, registering both the first and second contexts as a single context class, and registering both the first and second scopes as a single scope of the single context class, wherein in response to an inability to compare an order of the first scope with an order of the second scope, the first and second contexts exist independently without a parent-child relationship, wherein the first and second scopes each describe a level of business operations at which the Key Performance Indicators are to be monitored, the first and second scopes each holding a name, a level name of structured data concerning the operation, and an event mapping rule for deriving an identifier for each of the first and second scopes. 5. The method as claimed in claim 1 , further comprising: in response to an order of the first scope and an order of the second scope being equal, performing: merging the first context into the second context; and replacing a name of the first data definition to generate a first variable of the second context. | 0.628878 |
8,065,609 | 6 | 7 | 6. A computer program product comprising a computer readable storage device storing executable instructions for generating a survey, the executable instructions comprising: instructions for storing an XML survey document in a memory of a first computer system, wherein the XML survey document comprises a plurality of questions and corresponding answer options, a root node and a plurality of sub-nodes branching from the root node, wherein each question and corresponding answer options are defined as XML data elements, wherein attributes define the associations among the XML data elements and define question branches; instructions for sending programming instructions to a second computer system for execution as an applet in a browser of the second computer system and a document type definition file, wherein the execution of the programming instructions as an applet causes the second computer system to parse the data elements into a plurality of data arrays using the document type definition file, wherein each data array in the plurality of data arrays comprises a hash table and cross-references defining associations among each question and corresponding answer options in the plurality of questions and corresponding answer options and identifying additional questions and corresponding answer options; instructions for providing a question and corresponding answer options, from the plurality of questions and corresponding answer options, to a user on the second computer system; instructions for receiving a user input comprising user selected answer options responsive to the provided question; instructions for traversing the each data array to determine whether the user selected answer options identifies additional questions and corresponding answer options; and instructions for presenting the additional questions and corresponding answer options to the user on the second computer system responsive to determining that the user selected answer options identifies the additional questions and corresponding answer options. | 6. A computer program product comprising a computer readable storage device storing executable instructions for generating a survey, the executable instructions comprising: instructions for storing an XML survey document in a memory of a first computer system, wherein the XML survey document comprises a plurality of questions and corresponding answer options, a root node and a plurality of sub-nodes branching from the root node, wherein each question and corresponding answer options are defined as XML data elements, wherein attributes define the associations among the XML data elements and define question branches; instructions for sending programming instructions to a second computer system for execution as an applet in a browser of the second computer system and a document type definition file, wherein the execution of the programming instructions as an applet causes the second computer system to parse the data elements into a plurality of data arrays using the document type definition file, wherein each data array in the plurality of data arrays comprises a hash table and cross-references defining associations among each question and corresponding answer options in the plurality of questions and corresponding answer options and identifying additional questions and corresponding answer options; instructions for providing a question and corresponding answer options, from the plurality of questions and corresponding answer options, to a user on the second computer system; instructions for receiving a user input comprising user selected answer options responsive to the provided question; instructions for traversing the each data array to determine whether the user selected answer options identifies additional questions and corresponding answer options; and instructions for presenting the additional questions and corresponding answer options to the user on the second computer system responsive to determining that the user selected answer options identifies the additional questions and corresponding answer options. 7. The computer program product of claim 6 wherein each sub-node in the plurality of the sub-nodes comprises attributes defining categories for each question and corresponding answer options in the plurality of questions and corresponding answer options. | 0.799051 |
9,807,216 | 1 | 5 | 1. A phone device comprising: a storage configured to store a registration table, in which phone numbers are associated with names of parties that own the phone numbers, and a language-specific name table, in which a plurality of names are registered for each of multiple languages; and one or more processors coupled to the storage and configured to: in response to receiving a phone number, read a name of a party associated with the received phone number from the storage; select a language for which the name of the party is registered in the language-specific name table; select a default language when the name is not registered in the language-specific name table; and convert the name of the party into voice data in the selected language and output the voice data. | 1. A phone device comprising: a storage configured to store a registration table, in which phone numbers are associated with names of parties that own the phone numbers, and a language-specific name table, in which a plurality of names are registered for each of multiple languages; and one or more processors coupled to the storage and configured to: in response to receiving a phone number, read a name of a party associated with the received phone number from the storage; select a language for which the name of the party is registered in the language-specific name table; select a default language when the name is not registered in the language-specific name table; and convert the name of the party into voice data in the selected language and output the voice data. 5. The phone device of claim 1 , wherein the multiple languages include English. | 0.898219 |
8,745,075 | 8 | 11 | 8. A method of creating an electronic document, comprising: maintaining, in a processor-readable storage medium, a dynamic document template containing a plurality of queries, wherein each query includes a query scope and a context element, wherein the query scope refers to one or more source documents maintained in a document collection and the context element refers to content of the one or more source documents referred to by the query scope; defining, based upon a request received from a first user, a first content rule and a second content rule; applying the first content rule to monitor the document template and trigger an action if a second user changes the document template; applying the second content rule to monitor the document collection and trigger an action if a second user changes any of the source documents referred to by the query scope; in response to both the first content rule and the second content rule triggering an action indicating a change occurred to the document template and at least one of the source documents, determining whether the query scope and context element of each of the queries in the document template are valid; indicating, in response to determining a valid query scope and context element, a query to be valid; if any of the queries are invalid after the change, issuing a notification to the first user indicating an invalid query; determining whether the change satisfies a predetermined condition; if the change satisfies a predetermined condition, triggering a second notification event; receiving a change to one of the queries to result in a modified query; automatically accessing the document collection to determine whether the modified query is valid; and if the modified query is valid, automatically refreshing the document template, wherein refreshing the document template comprises displaying a dynamic document comprising at least a portion of the dynamic document template with the content of the one or more source documents, including the changed source document. | 8. A method of creating an electronic document, comprising: maintaining, in a processor-readable storage medium, a dynamic document template containing a plurality of queries, wherein each query includes a query scope and a context element, wherein the query scope refers to one or more source documents maintained in a document collection and the context element refers to content of the one or more source documents referred to by the query scope; defining, based upon a request received from a first user, a first content rule and a second content rule; applying the first content rule to monitor the document template and trigger an action if a second user changes the document template; applying the second content rule to monitor the document collection and trigger an action if a second user changes any of the source documents referred to by the query scope; in response to both the first content rule and the second content rule triggering an action indicating a change occurred to the document template and at least one of the source documents, determining whether the query scope and context element of each of the queries in the document template are valid; indicating, in response to determining a valid query scope and context element, a query to be valid; if any of the queries are invalid after the change, issuing a notification to the first user indicating an invalid query; determining whether the change satisfies a predetermined condition; if the change satisfies a predetermined condition, triggering a second notification event; receiving a change to one of the queries to result in a modified query; automatically accessing the document collection to determine whether the modified query is valid; and if the modified query is valid, automatically refreshing the document template, wherein refreshing the document template comprises displaying a dynamic document comprising at least a portion of the dynamic document template with the content of the one or more source documents, including the changed source document. 11. The method of claim 8 , further comprising: displaying a dynamic document comprising at least a portion of the dynamic document template with the content of the one or more source documents. | 0.746073 |
8,880,402 | 1 | 5 | 1. A speech recognition method comprising the steps of: (a) receiving input speech from a user; (b) processing said input speech to obtain at least one parameter value; and (c) determining the user's level of experience with using automatic speech recognition, using the at least one parameter value. | 1. A speech recognition method comprising the steps of: (a) receiving input speech from a user; (b) processing said input speech to obtain at least one parameter value; and (c) determining the user's level of experience with using automatic speech recognition, using the at least one parameter value. 5. The speech recognition method of claim 1 , wherein step (c) further comprises comparing said at least one parameter value to at least one threshold value. | 0.814858 |
8,005,850 | 6 | 7 | 6. The method of claim 1 wherein generating the search report further includes: generating a separate listing including only annotated hits. | 6. The method of claim 1 wherein generating the search report further includes: generating a separate listing including only annotated hits. 7. The method of claim 6 wherein the user-specific metadata included in each annotation includes a rating of one of the plurality of documents belonging to the corpus and wherein the separate listing includes only annotated hits for which the matching annotation includes a favorable rating. | 0.5 |
9,478,146 | 1 | 20 | 1. A student reading performance assessment system, comprising: a worksheet having a position-identifying pattern configured to be read by an image-capturing device printed thereon, the worksheet comprising: a plurality of indicator regions, each comprising at least one indicator portion of the position-identifying pattern; a plurality of words each associated with at least one of the indicator regions; and a note region, comprising a note portion of the position-identifying pattern; and a digital pen capable of both writing on a substrate and capturing data corresponding to a user's handwriting, the digital pen comprising an image-capturing sensor, a processor, and a tangible, computer-readable memory with instructions that, when executed, cause the processor to: associate a first mark and a first notation on a worksheet comprising a position-identifying pattern with a first word by: detecting, by the image-capturing sensor, a first indicator portion of the position-identifying pattern corresponding to a first mark in a first one of the indicator regions that is associated with a first word, after detecting the first indicator portion, detecting, by the image-capturing device, a first note portion of the position-identifying pattern corresponding to a first notation in the note region, and after the first indicator portion of the position-identifying pattern is detected by the image-capturing sensor, associating all subsequently detected portions of the position-identifying pattern in the first indicator region and the note region of the worksheet and the corresponding marks and notations with the first word until another indicator portion of the position-identifying pattern that corresponds to another word is detected by the image-capturing sensor; based on whether the first mark indicates that the first word was read incorrectly or correctly, determine a first reading assessment result for the first word, and store, in a memory, a digital document file comprising the first reading assessment result, the marks and notations associated with the first word, and information identifying where on the worksheet the markings and notations associated with the first word are located. | 1. A student reading performance assessment system, comprising: a worksheet having a position-identifying pattern configured to be read by an image-capturing device printed thereon, the worksheet comprising: a plurality of indicator regions, each comprising at least one indicator portion of the position-identifying pattern; a plurality of words each associated with at least one of the indicator regions; and a note region, comprising a note portion of the position-identifying pattern; and a digital pen capable of both writing on a substrate and capturing data corresponding to a user's handwriting, the digital pen comprising an image-capturing sensor, a processor, and a tangible, computer-readable memory with instructions that, when executed, cause the processor to: associate a first mark and a first notation on a worksheet comprising a position-identifying pattern with a first word by: detecting, by the image-capturing sensor, a first indicator portion of the position-identifying pattern corresponding to a first mark in a first one of the indicator regions that is associated with a first word, after detecting the first indicator portion, detecting, by the image-capturing device, a first note portion of the position-identifying pattern corresponding to a first notation in the note region, and after the first indicator portion of the position-identifying pattern is detected by the image-capturing sensor, associating all subsequently detected portions of the position-identifying pattern in the first indicator region and the note region of the worksheet and the corresponding marks and notations with the first word until another indicator portion of the position-identifying pattern that corresponds to another word is detected by the image-capturing sensor; based on whether the first mark indicates that the first word was read incorrectly or correctly, determine a first reading assessment result for the first word, and store, in a memory, a digital document file comprising the first reading assessment result, the marks and notations associated with the first word, and information identifying where on the worksheet the markings and notations associated with the first word are located. 20. The system of claim 1 wherein the position-identifying pattern covers the entire worksheet. | 0.951826 |
9,311,568 | 11 | 15 | 11. A non-transitory, computer-readable storage medium comprising instructions for selecting a representative image for a recipe from among a plurality of recipe images, the instructions when executed by a processor cause the processor to: receive a recipe comprising classified recipe text and a plurality of candidate images; generate image features for the plurality of candidate images, features of a candidate image representative of at least one of: classified recipe text proximate to the candidate image and position of the candidate image within the recipe; determine image probabilities of the plurality of candidate images depicting a finished food product described by the recipe after preparation is complete, the image probabilities determined using an image model, image feature weights, and the generated image features, the image feature weights computed based on training recipes comprising classified training recipe text and training recipe images, the training recipe images including representative training images corresponding to the training recipes; rank the plurality of candidate images according to the determined image probabilities; select a representative image from the candidate images according to the ranking of the candidate images, the selected representative image having a highest image probability of the determined image probabilities; and store the selected representative image in association with the retrieved recipe. | 11. A non-transitory, computer-readable storage medium comprising instructions for selecting a representative image for a recipe from among a plurality of recipe images, the instructions when executed by a processor cause the processor to: receive a recipe comprising classified recipe text and a plurality of candidate images; generate image features for the plurality of candidate images, features of a candidate image representative of at least one of: classified recipe text proximate to the candidate image and position of the candidate image within the recipe; determine image probabilities of the plurality of candidate images depicting a finished food product described by the recipe after preparation is complete, the image probabilities determined using an image model, image feature weights, and the generated image features, the image feature weights computed based on training recipes comprising classified training recipe text and training recipe images, the training recipe images including representative training images corresponding to the training recipes; rank the plurality of candidate images according to the determined image probabilities; select a representative image from the candidate images according to the ranking of the candidate images, the selected representative image having a highest image probability of the determined image probabilities; and store the selected representative image in association with the retrieved recipe. 15. The non-transitory, computer-readable storage medium of claim 11 , wherein the generated features of the candidate image are further representative of image metadata selected from at least one of: an image title, an image alternative text, and an image filename. | 0.882923 |
9,171,096 | 1 | 10 | 1. A method comprising: receiving a source artifact from a process, wherein the source artifact is one of a Web Service Definition Language (WSDL) format file, a Business Process Execution Language (BPEL) format file, an XML Schema Definition (XSD) format file, and an Extensible Stylesheet Language Transformation (XLST) format file; introspecting said source artifact to identify a plurality of service metadata artifact entities based on a model of the format of said source artifact; processing a first service metadata artifact entity of said plurality of service metadata artifact entities to generate a processed service metadata artifact entity, wherein said processing includes canonicalizing said first service metadata artifact entity; wherein said processed service metadata artifact entity is not required to be schema-valid; applying a hashing function to said processed service metadata artifact entity to generate a fingerprint of said processed service metadata artifact entity; searching a service metadata repository, using said fingerprint of said processed service metadata artifact entity, to identify a preexisting service metadata asset having a fingerprint attribute matching said fingerprint of said processed service metadata artifact entity; if the fingerprint of said processed service metadata artifact entity matches a fingerprint attribute of a preexisting service metadata asset in the service metadata repository, returning to said process a service metadata repository reference to said matching preexisting service metadata asset; if the fingerprint of said processed service metadata artifact entity does not match a fingerprint attribute of a preexisting service metadata asset in the service metadata repository, storing said first service metadata artifact entity in said service metadata repository as a new service metadata asset, storing said fingerprint of said processed service metadata artifact entity as an attribute of said new service metadata asset, and returning to said process a service metadata repository reference to said new service metadata asset. | 1. A method comprising: receiving a source artifact from a process, wherein the source artifact is one of a Web Service Definition Language (WSDL) format file, a Business Process Execution Language (BPEL) format file, an XML Schema Definition (XSD) format file, and an Extensible Stylesheet Language Transformation (XLST) format file; introspecting said source artifact to identify a plurality of service metadata artifact entities based on a model of the format of said source artifact; processing a first service metadata artifact entity of said plurality of service metadata artifact entities to generate a processed service metadata artifact entity, wherein said processing includes canonicalizing said first service metadata artifact entity; wherein said processed service metadata artifact entity is not required to be schema-valid; applying a hashing function to said processed service metadata artifact entity to generate a fingerprint of said processed service metadata artifact entity; searching a service metadata repository, using said fingerprint of said processed service metadata artifact entity, to identify a preexisting service metadata asset having a fingerprint attribute matching said fingerprint of said processed service metadata artifact entity; if the fingerprint of said processed service metadata artifact entity matches a fingerprint attribute of a preexisting service metadata asset in the service metadata repository, returning to said process a service metadata repository reference to said matching preexisting service metadata asset; if the fingerprint of said processed service metadata artifact entity does not match a fingerprint attribute of a preexisting service metadata asset in the service metadata repository, storing said first service metadata artifact entity in said service metadata repository as a new service metadata asset, storing said fingerprint of said processed service metadata artifact entity as an attribute of said new service metadata asset, and returning to said process a service metadata repository reference to said new service metadata asset. 10. The method of claim 1 , wherein said source artifact comprises a transformation. | 0.850534 |
6,151,574 | 30 | 38 | 30. A method for use in a system for recognizing selected speech based on acoustic models, which are characterized by a plurality of parameters, the method comprising: providing selected data representing a sample of the selected speech; defining a structure which includes a plurality of levels, each level including one or more nodes, each node being associated with a respective probability measure, which is derived from at least the selected data; identifying at least one sequence of nodes from different levels; and modifying at least one of the parameters based on at least the probability measure associated with a selected node in the sequence, the probability measure associated with the selected node being a function of the probability measure associated with every other node in the sequence. | 30. A method for use in a system for recognizing selected speech based on acoustic models, which are characterized by a plurality of parameters, the method comprising: providing selected data representing a sample of the selected speech; defining a structure which includes a plurality of levels, each level including one or more nodes, each node being associated with a respective probability measure, which is derived from at least the selected data; identifying at least one sequence of nodes from different levels; and modifying at least one of the parameters based on at least the probability measure associated with a selected node in the sequence, the probability measure associated with the selected node being a function of the probability measure associated with every other node in the sequence. 38. The method of claim 30 wherein the acoustic models are modified based also on a recognized version of the sample of the speech. | 0.81392 |
7,519,822 | 12 | 14 | 12. A method of processing data representing a graph, the graph being stored on machine-readable media, said method comprising: determining a first hash value representing the graph; using a digital processor to compute a second hash value that represents an additional statement; and computing an aggregate hash value that is a function of each of the first hash value and the second hash value, where the function is commutative. | 12. A method of processing data representing a graph, the graph being stored on machine-readable media, said method comprising: determining a first hash value representing the graph; using a digital processor to compute a second hash value that represents an additional statement; and computing an aggregate hash value that is a function of each of the first hash value and the second hash value, where the function is commutative. 14. A method according to claim 12 , further comprising: retrieving the first hash value from remote machine-readable media; adding the statement by causing the remote machine-readable media to store the additional statement in association with the graph; computing as the second hash value an incremental hash value representing the additional statement; and digitally signing the aggregate hash value and causing the remote machine-readable media to store the digitally signed aggregate hash value in association with the data representing the graph. | 0.724 |
8,181,163 | 11 | 13 | 11. At a computer system, a method for automatically resolving semantic errors in a software routine using one or more known inputs and corresponding expected outputs for portions of the software routine that are known to have errors, the method comprising: an act of providing the software routine with one or more known inputs and corresponding one or more expected outputs for portions of a program fragment where an error has been localized; an act of learning a correctly functioning program fragment from pairs of input-output descriptions of the program fragment; an act of determining the program statements that can transform one or more given input states into one or more given output states after execution of those program statements; and an act of altering portions of the software routine with the learned program fragments. | 11. At a computer system, a method for automatically resolving semantic errors in a software routine using one or more known inputs and corresponding expected outputs for portions of the software routine that are known to have errors, the method comprising: an act of providing the software routine with one or more known inputs and corresponding one or more expected outputs for portions of a program fragment where an error has been localized; an act of learning a correctly functioning program fragment from pairs of input-output descriptions of the program fragment; an act of determining the program statements that can transform one or more given input states into one or more given output states after execution of those program statements; and an act of altering portions of the software routine with the learned program fragments. 13. The method of claim 11 , wherein the act of determining the program statements that can transform one or more given input states into one or more given output states after execution of those program statements comprises using belief propagation to determine the program statements. | 0.5 |
9,870,655 | 5 | 6 | 5. The apparatus according to claim 4 , wherein the logging policy includes policy profile information, variable information used to determine an application timing of the policy, and policy information used to log the vehicle data. | 5. The apparatus according to claim 4 , wherein the logging policy includes policy profile information, variable information used to determine an application timing of the policy, and policy information used to log the vehicle data. 6. The apparatus according to claim 5 , wherein the policy profile information includes at least one of a car model, a development stage, and a software version. | 0.653017 |
8,813,007 | 1 | 2 | 1. A method to formally verify a circuit design, the method comprising: simplifying a first set of assumptions to obtain a second set of assumptions, wherein the second set of assumptions is logically equivalent to the first set of assumptions, and wherein the first set of assumptions and the second set of assumptions correspond to allowable input assignments for the circuit design; associating, by computer, a first subset of assumptions with an assertion in a set of assertions, wherein the first subset of assumptions is a subset of the second set of assumptions, and wherein satisfying the assertion corresponds to a desired behavior of circuit design; modifying the first subset of assumptions to obtain a second subset of assumptions which is not logically equivalent to the first subset of assumptions; and proving that the circuit design satisfies the assertion when the second subset of assumptions is satisfied. | 1. A method to formally verify a circuit design, the method comprising: simplifying a first set of assumptions to obtain a second set of assumptions, wherein the second set of assumptions is logically equivalent to the first set of assumptions, and wherein the first set of assumptions and the second set of assumptions correspond to allowable input assignments for the circuit design; associating, by computer, a first subset of assumptions with an assertion in a set of assertions, wherein the first subset of assumptions is a subset of the second set of assumptions, and wherein satisfying the assertion corresponds to a desired behavior of circuit design; modifying the first subset of assumptions to obtain a second subset of assumptions which is not logically equivalent to the first subset of assumptions; and proving that the circuit design satisfies the assertion when the second subset of assumptions is satisfied. 2. The method of claim 1 , wherein associating the first subset of assumptions with the assertion in the set of assertions involves: associating an initial subset of assumptions with the assertion, wherein an assumption is associated with an assertion if the assumption, either directly or indirectly, shares logic with the assertion; and removing at least a first assumption from the initial subset of assumptions if the assertion is satisfiable regardless of whether the first assumption is satisfied or not. | 0.5 |
8,103,609 | 5 | 6 | 5. The method of claim 1 , wherein the identifying act further comprises selecting best-matching voxels based on a pre-determined distance measurement between a voxel and the computed TAC. | 5. The method of claim 1 , wherein the identifying act further comprises selecting best-matching voxels based on a pre-determined distance measurement between a voxel and the computed TAC. 6. The method of claim 5 , wherein the a priori data comprises at least one item selected from the group consisting of a set of tracer characteristics and administered dose, patient weight and blood volume, and a set of medical-imaging-device characteristics. | 0.5 |
9,454,621 | 10 | 14 | 10. The computer-implemented method of claim 1 , wherein the one or more signals include one or more characteristics of the candidate navigational search results. | 10. The computer-implemented method of claim 1 , wherein the one or more signals include one or more characteristics of the candidate navigational search results. 14. The computer-implemented method of claim 10 , wherein the one or more characteristics of the candidate navigational search results includes document types of the candidate navigational search results. | 0.58871 |
9,448,702 | 11 | 12 | 11. A method for a display system to display a selected graphical procedure depiction on a display, comprising: displaying a plurality of graphical procedure depictions on a lateral view of a moving map, each graphical procedure depiction of the plurality of graphical procedure depictions corresponding to a respective procedure of a plurality of procedures, and each respective procedure of the plurality of procedures being selected from one of the group consisting of standard terminal arrival routes, standard terminal arrival route transitions, approaches, approach transitions, standard instrument departures, and standard instrument departure transitions, each of the standard terminal arrival routes, standard terminal arrival route transitions, approaches, approach transitions, standard instrument departures, and standard instrument departure transitions; displaying a list including one or more of a plurality of textual procedure identifications, each textual procedure identification of the plurality of textual procedure identifications corresponding to a respective procedure of the plurality of procedures and having a respective graphical procedure depiction of the plurality of graphical procedure depictions on the lateral view of the moving map associated therewith; when a first graphical procedure depiction of the plurality of graphical procedure depictions on the lateral view of the moving map is identified, highlighting both the first textual procedure identification displayed in the list to distinguish from other textual procedure identifications of the plurality of textual procedures in the list and the first graphical procedure depiction displayed on the lateral view of the moving map to distinguish from other graphical procedure depictions of the plurality of graphical procedure depictions on the lateral view of the moving map, the first textual procedure identification being associated with the first graphical procedure depiction; characterizing the identified first textual procedure identification and the identified first graphical procedure depiction as selected; and removing the other textual procedure identifications from the list and the other graphical procedure depictions from the lateral view other than the selected first textual procedure identification and first graphical procedure depiction. | 11. A method for a display system to display a selected graphical procedure depiction on a display, comprising: displaying a plurality of graphical procedure depictions on a lateral view of a moving map, each graphical procedure depiction of the plurality of graphical procedure depictions corresponding to a respective procedure of a plurality of procedures, and each respective procedure of the plurality of procedures being selected from one of the group consisting of standard terminal arrival routes, standard terminal arrival route transitions, approaches, approach transitions, standard instrument departures, and standard instrument departure transitions, each of the standard terminal arrival routes, standard terminal arrival route transitions, approaches, approach transitions, standard instrument departures, and standard instrument departure transitions; displaying a list including one or more of a plurality of textual procedure identifications, each textual procedure identification of the plurality of textual procedure identifications corresponding to a respective procedure of the plurality of procedures and having a respective graphical procedure depiction of the plurality of graphical procedure depictions on the lateral view of the moving map associated therewith; when a first graphical procedure depiction of the plurality of graphical procedure depictions on the lateral view of the moving map is identified, highlighting both the first textual procedure identification displayed in the list to distinguish from other textual procedure identifications of the plurality of textual procedures in the list and the first graphical procedure depiction displayed on the lateral view of the moving map to distinguish from other graphical procedure depictions of the plurality of graphical procedure depictions on the lateral view of the moving map, the first textual procedure identification being associated with the first graphical procedure depiction; characterizing the identified first textual procedure identification and the identified first graphical procedure depiction as selected; and removing the other textual procedure identifications from the list and the other graphical procedure depictions from the lateral view other than the selected first textual procedure identification and first graphical procedure depiction. 12. The method of claim 11 wherein the highlighting comprises moving a cursor over either the first textual procedure identification or the first graphical procedure depiction. | 0.689046 |
9,697,099 | 9 | 10 | 9. The method of claim 1 , wherein providing access to the one or more intermediate output objects comprises mapping the new content being ingested to the one or more intermediate output objects. | 9. The method of claim 1 , wherein providing access to the one or more intermediate output objects comprises mapping the new content being ingested to the one or more intermediate output objects. 10. The method of claim 9 , further comprising: responsive to receiving an input question in a question answering system, running a question answering pipeline of software engines against available partially and fully ingested content according to the mapping; generating one or more candidate answers for the input question; ranking the one or more candidate answers; and presenting the ranked one or more candidate answers. | 0.5 |
8,078,598 | 10 | 17 | 10. A non-transitory computer readable medium storing computer-executable program code, the program code comprising: code to receive a structured query language query; code to determine at least one point data query and at least one relational data query based on the structured query language query; code to transmit the at least one point data query to at least one point data server; code to transmit the at least one relational data query to at least one relational data server; code to receive point data and relational data in response to the point data query and the relational data query; and code to join the received point data and the received relational data into a result rowset; wherein the code to receive point data and relational data in response to the point data query and the relational data query comprises: code to receive, from the at least one point data server in response to the at least one point data query that is based on the structured query language query, point data that has been collected from multiple heterogeneous sources based on components defined according to a class-based object model and encapsulated as object instantiations of the components; and wherein the at least one point data server is to receive the object instantiations of the components defined according to the class-based object model; and wherein the point data is current, real-time or value data associated with one or more instruments, components, or portions of a manufacturing, industrial, commercial, or other system. | 10. A non-transitory computer readable medium storing computer-executable program code, the program code comprising: code to receive a structured query language query; code to determine at least one point data query and at least one relational data query based on the structured query language query; code to transmit the at least one point data query to at least one point data server; code to transmit the at least one relational data query to at least one relational data server; code to receive point data and relational data in response to the point data query and the relational data query; and code to join the received point data and the received relational data into a result rowset; wherein the code to receive point data and relational data in response to the point data query and the relational data query comprises: code to receive, from the at least one point data server in response to the at least one point data query that is based on the structured query language query, point data that has been collected from multiple heterogeneous sources based on components defined according to a class-based object model and encapsulated as object instantiations of the components; and wherein the at least one point data server is to receive the object instantiations of the components defined according to the class-based object model; and wherein the point data is current, real-time or value data associated with one or more instruments, components, or portions of a manufacturing, industrial, commercial, or other system. 17. The non-transitory computer readable medium according to claim 10 , wherein the code to join the received point data and the received relational data into a result rowset comprises: code to synthesize a first rowset based on the received point data; code to synthesize a second rowset based on the received relational data; and code to combine the first rowset and the second rowset into the result rowset based on columns specified in the structured query language query. | 0.564103 |
9,740,928 | 21 | 23 | 21. The system of claim 14 , wherein a distance is calculated by: calculating a plurality of distances, each being the difference between the value of one feature of the one of the word images and a corresponding feature of the other one of the multiple word images; and summing together the plurality of distances. | 21. The system of claim 14 , wherein a distance is calculated by: calculating a plurality of distances, each being the difference between the value of one feature of the one of the word images and a corresponding feature of the other one of the multiple word images; and summing together the plurality of distances. 23. The system of claim 21 , wherein the created feature vector further comprises a weight assigned to each of the multiple word features, and wherein the method further comprises using the weight when summing together the plurality of distances in order to calculate a distance between each one of the multiple word images and every other one of the multiple word images. | 0.5 |
9,788,179 | 16 | 18 | 16. A mobile device comprising: at least one processor; and memory storing: a plurality of images of screens captured on the mobile device, each of the plurality of images having an associated timestamp, and instructions that, when executed by the at least one processor, cause the mobile device to: receive an image captured from a mobile device display for a first mobile application, determine a window that includes a chronological set of the plurality of images, identify entities appearing in images in a first portion of the window using text for images in a remaining portion of the window as context to disambiguate ambiguous entity references, and using the identified entities for customizing mobile applications executing on the mobile device. | 16. A mobile device comprising: at least one processor; and memory storing: a plurality of images of screens captured on the mobile device, each of the plurality of images having an associated timestamp, and instructions that, when executed by the at least one processor, cause the mobile device to: receive an image captured from a mobile device display for a first mobile application, determine a window that includes a chronological set of the plurality of images, identify entities appearing in images in a first portion of the window using text for images in a remaining portion of the window as context to disambiguate ambiguous entity references, and using the identified entities for customizing mobile applications executing on the mobile device. 18. The mobile device of claim 16 , wherein each of the plurality of images has an associated mobile application and determining the set of images in the window includes: using the associated mobile applications to determine the window. | 0.763052 |
7,958,107 | 20 | 22 | 20. A user device comprising: a) a user interface for receiving input from a user and displaying information to the user; and b) a control system, associated with the user interface, adapted to: i) receive input from the user that corresponds to a keyword search term for a search of content; ii) adjust a logical fuzziness of the keyword search term based on input from the user, the logical fuzziness of the keyword search term corresponding to an extent to which a plurality of associated keywords for the keyword search term are utilized for the search of the content; iii) perform the search of the content based on the keyword search term and the logical fuzziness of the keyword search term; and iv) present results of the search to the user via the user interface; wherein performing the search of the content comprises performing the search of the content based on the keyword search term and a number of keywords selected from the plurality of associated keywords based on the logical fuzziness of the keyword search term; and wherein the number of keywords selected from the plurality of associated keywords increases if the logical fuzziness of the keyword search term is increased by the user and decreases if the logical fuzziness of the keyword search term is decreased by the user. | 20. A user device comprising: a) a user interface for receiving input from a user and displaying information to the user; and b) a control system, associated with the user interface, adapted to: i) receive input from the user that corresponds to a keyword search term for a search of content; ii) adjust a logical fuzziness of the keyword search term based on input from the user, the logical fuzziness of the keyword search term corresponding to an extent to which a plurality of associated keywords for the keyword search term are utilized for the search of the content; iii) perform the search of the content based on the keyword search term and the logical fuzziness of the keyword search term; and iv) present results of the search to the user via the user interface; wherein performing the search of the content comprises performing the search of the content based on the keyword search term and a number of keywords selected from the plurality of associated keywords based on the logical fuzziness of the keyword search term; and wherein the number of keywords selected from the plurality of associated keywords increases if the logical fuzziness of the keyword search term is increased by the user and decreases if the logical fuzziness of the keyword search term is decreased by the user. 22. The user device of claim 20 wherein the user device is one of a plurality of peer devices forming a Peer-to-Peer (P2P) network, and the content searched comprises content stored by at least one other device from the plurality of peer devices. | 0.5 |
8,949,377 | 8 | 13 | 8. A computer program storage product for managing a conversational system on a server, the computer program storage product comprising: a non-transitory storage medium readable by a computer and storing instructions for execution by the computer for performing: presenting on a user system of a first party, each of at least one chatbot as part of at least one messaging window forming a chat window hosted by a third party, the chatbot adapted to act as a customer service agent for at least one of a good and a service; and a web page document hosted by a second party, the web page document including code to launch the chat window hosted by the third party, and the second party and the third party being independent business entities; displaying a message to the first party through the messaging window; reviewing a response from the first party using a combination of keyword/response pair scripting and artificial intelligence; and wherein the keyword/response pair scripting, the messaging window and the artificial intelligence are all managed via a web-based management console hosted by the third party, the web-based management console includes components selectable by the second party for managing the messaging window of the chatbot, separate from a window of the web page document hosted by the second party for display on the user system of the first party, the components including at least one event to launch the messaging window of the chatbot in response to code scripting at the web page document hosted by the second party. | 8. A computer program storage product for managing a conversational system on a server, the computer program storage product comprising: a non-transitory storage medium readable by a computer and storing instructions for execution by the computer for performing: presenting on a user system of a first party, each of at least one chatbot as part of at least one messaging window forming a chat window hosted by a third party, the chatbot adapted to act as a customer service agent for at least one of a good and a service; and a web page document hosted by a second party, the web page document including code to launch the chat window hosted by the third party, and the second party and the third party being independent business entities; displaying a message to the first party through the messaging window; reviewing a response from the first party using a combination of keyword/response pair scripting and artificial intelligence; and wherein the keyword/response pair scripting, the messaging window and the artificial intelligence are all managed via a web-based management console hosted by the third party, the web-based management console includes components selectable by the second party for managing the messaging window of the chatbot, separate from a window of the web page document hosted by the second party for display on the user system of the first party, the components including at least one event to launch the messaging window of the chatbot in response to code scripting at the web page document hosted by the second party. 13. The computer program storage product of claim 8 , further comprising: generating a report on activities of the chatbot. | 0.900162 |
8,185,606 | 2 | 3 | 2. The computer implemented method of claim 1 , wherein parsing the received email with a second parser comprises: selectively and programmatically enabling the capability of the second parser to parse the annotated portion. | 2. The computer implemented method of claim 1 , wherein parsing the received email with a second parser comprises: selectively and programmatically enabling the capability of the second parser to parse the annotated portion. 3. The computer implemented method of claim 2 , wherein selectively and programmatically enabling further comprises: selection through a set of controls, the controls managing selective and programmatic enablement according to a set of criteria comprising sending user, email topic, email priority and receiving user. | 0.5 |
9,052,755 | 7 | 10 | 7. An overlapped handwriting input method, comprising: Step S 111 : touching a touch screen through a touch unit, and starting to input a stroke; Step S 112 : moving the touch unit on the touch screen, recording and displaying the track of a stroke on a handwriting area of the touch screen, and drawing the track of the current stroke using a given color A; Step S 113 : moving the touch unit away from the touch screen, and ending the input of the current stroke; Step S 114 : determining whether the stroke being currently written and all previously input strokes having a color A belong to the same character; if yes, keeping the color of the current stroke unchanged; otherwise, going to Step S 115 ; Step S 115 : determining whether an inactive visual layer character is present on the screen, wherein the inactive visual layer character refers to the last completely written character that has undergone recognition and color transformation, and the character is defined in Step S 117 ; if yes, going to Step S 116 ; otherwise, going to Step S 117 ; Step S 116 : clearing an image of the inactive visual layer character and related stroke information; Step S 117 : defining a character constituted by all strokes having the color value A, except for the current stroke, as the inactive visual layer character; going to Step S 118 ; and Step S 118 : submitting data of the current inactive visual layer character to a recognition engine for recognition, and outputting a recognition result. | 7. An overlapped handwriting input method, comprising: Step S 111 : touching a touch screen through a touch unit, and starting to input a stroke; Step S 112 : moving the touch unit on the touch screen, recording and displaying the track of a stroke on a handwriting area of the touch screen, and drawing the track of the current stroke using a given color A; Step S 113 : moving the touch unit away from the touch screen, and ending the input of the current stroke; Step S 114 : determining whether the stroke being currently written and all previously input strokes having a color A belong to the same character; if yes, keeping the color of the current stroke unchanged; otherwise, going to Step S 115 ; Step S 115 : determining whether an inactive visual layer character is present on the screen, wherein the inactive visual layer character refers to the last completely written character that has undergone recognition and color transformation, and the character is defined in Step S 117 ; if yes, going to Step S 116 ; otherwise, going to Step S 117 ; Step S 116 : clearing an image of the inactive visual layer character and related stroke information; Step S 117 : defining a character constituted by all strokes having the color value A, except for the current stroke, as the inactive visual layer character; going to Step S 118 ; and Step S 118 : submitting data of the current inactive visual layer character to a recognition engine for recognition, and outputting a recognition result. 10. The overlapped handwriting input method according to claim 7 , wherein: in Step S 114 , whether the stroke being currently written and the previously input strokes belong to a same character is determined according to a relationship between geometric position information of the stroke being currently written and geometric position information of a character constituted by all the previously input strokes; assistant determination is performed in combination with the recognition result, which specifically comprises: performing recognition on the character constituted by all the previously written strokes having the color A except for the current stroke, and if the recognition reliability is high, determining that the current stroke and the previous strokes do not belong to the same character the method of determining the recognition reliability of the recognition engine recognizing a certain handwritten character comprises: calculating a difference between a probability of the character to be recognized belonging to a first candidate character and a probability of the character to be recognized belonging to a second candidate character, and if the difference is greater than a certain set threshold, determining that the reliability of the recognition result provided by the recognition engine is high; the method of calculating the probability of the character to be recognized belonging to a certain candidate recognition result character is provided by a recognition classifier; a quadratic discriminant function classifier is used as the classifier, and the probability is approximate to a negative exponent of a recognition distance provided by the quadratic discriminant function classifier; in Step S 114 , the method of determining whether the stroke being currently written and all the previously input strokes having the color A belong to the same character comprises: Step 141 : determining whether the current stroke is a first stroke input by the user; if yes, going to Step 146 ; otherwise, going to Step 142 ; Step 142 : determining whether the current stroke is a stroke of a character being newly written at the right of the previously stroke; if yes, going to Step 145 ; otherwise, going to Step 143 ; Step 143 : determining whether the current stroke overlaps another stroke having been written; if yes, going to Step 144 ; otherwise, going to Step 145 ; Step 144 : determining whether the overlapping degree of the current stroke and the stroke having been written is greater than a certain given threshold; if yes, going to Step 146 ; otherwise, going to Step 145 ; Step 145 : returning a determination result that the currently input stroke and the previously input stroke may belong to a same character; and Step 146 : returning a determination result that the currently input stroke and the previously input stroke do not belong to the same character. | 0.5 |
10,083,690 | 1 | 3 | 1. A method for operating a digital assistant, the method comprising: at an electronic device having one or more processors and memory: receiving user speech input; generating a textual representation of the user speech input; parsing the textual representation to determine a primary domain representing a user intent for the textual representation; identifying a first substring from the textual representation that corresponds to a first attribute of the primary domain; parsing the identified first substring to determine a secondary domain representing a user intent for the first sub string; performing a task flow comprising one or more tasks based on the primary domain and the secondary domain; and outputting a response in accordance with the performed task flow. | 1. A method for operating a digital assistant, the method comprising: at an electronic device having one or more processors and memory: receiving user speech input; generating a textual representation of the user speech input; parsing the textual representation to determine a primary domain representing a user intent for the textual representation; identifying a first substring from the textual representation that corresponds to a first attribute of the primary domain; parsing the identified first substring to determine a secondary domain representing a user intent for the first sub string; performing a task flow comprising one or more tasks based on the primary domain and the secondary domain; and outputting a response in accordance with the performed task flow. 3. The method of claim 1 , wherein the first attribute comprises a place, a time, an event, or a person. | 0.902804 |
8,977,949 | 2 | 6 | 2. An equivalence determination system comprising: a processor; an object extracting unit, executed on the processor, that extracts, from respective electronic documents in a set of electronic documents, at least one object which forms the electronic document and includes at least one of a text, a figure, and an equation; a specifying unit that specifies predetermined number of objects in the respective electronic documents based on density calculated by referring to the extracted objects; a judging unit that judges that plural electronic documents are similar based on the specified objects; a hash value calculation unit that calculates hash values of the objects specified by said specifying unit; and a feature word extraction unit that extracts a feature character string from the objects specified by said specifying unit, wherein said hash value calculation unit calculates a hash value based on the feature character string extracted by said feature word extraction unit, wherein said judging unit determines, by using the hash values calculated by said hash value calculation unit, whether the objects specified by said specifying unit match each other, wherein said specifying unit calculates, based on a density of the at least one object extracted by the object extracting unit, an improbability of modifying the at least one object, and specifies objects based on a calculation result, said feature word extraction unit extracts at least one feature word as the feature character string from the specified object by said specifying unit, said hash value calculation unit calculates a hash value of a character string obtained by concatenating feature words extracted by said feature word extraction unit, and registers identification information of corresponding electronic documents in a hash table, and said judging unit judges, based on a match between hash values, that the corresponding electronic documents are equivalent. | 2. An equivalence determination system comprising: a processor; an object extracting unit, executed on the processor, that extracts, from respective electronic documents in a set of electronic documents, at least one object which forms the electronic document and includes at least one of a text, a figure, and an equation; a specifying unit that specifies predetermined number of objects in the respective electronic documents based on density calculated by referring to the extracted objects; a judging unit that judges that plural electronic documents are similar based on the specified objects; a hash value calculation unit that calculates hash values of the objects specified by said specifying unit; and a feature word extraction unit that extracts a feature character string from the objects specified by said specifying unit, wherein said hash value calculation unit calculates a hash value based on the feature character string extracted by said feature word extraction unit, wherein said judging unit determines, by using the hash values calculated by said hash value calculation unit, whether the objects specified by said specifying unit match each other, wherein said specifying unit calculates, based on a density of the at least one object extracted by the object extracting unit, an improbability of modifying the at least one object, and specifies objects based on a calculation result, said feature word extraction unit extracts at least one feature word as the feature character string from the specified object by said specifying unit, said hash value calculation unit calculates a hash value of a character string obtained by concatenating feature words extracted by said feature word extraction unit, and registers identification information of corresponding electronic documents in a hash table, and said judging unit judges, based on a match between hash values, that the corresponding electronic documents are equivalent. 6. An equivalence determination system according to claim 2 , wherein said hash value calculation unit calculates a hash value for each feature word, and registers identification information of one of corresponding electronic documents and partial documents in the hash table, and said judging unit determines, based on a match between at least a predetermined number of hash values out of hash values of respective feature words that are calculated by said hash value calculation unit, that the corresponding electronic documents are equivalent. | 0.72 |
9,514,218 | 1 | 12 | 1. A method comprising, by a computing device: receiving, from a client device of a first user of an online social network, an unstructured text query comprising an ambiguous n-gram, the online social network being associated with a plurality of objects; identifying one or more objects corresponding to the ambiguous n-gram based on a calculated probability that the n-gram correspond to the identified objects; generating a first set of structured queries, each structured query from the first set of structured queries corresponding to an identified object, the structured query comprising a reference to the corresponding identified object; receiving, from the client device of the first user, a selection of a structured query corresponding to a first object of the identified objects; and generating a second set of structured queries, each structured query of the second set of structured queries comprising a reference to the first object. | 1. A method comprising, by a computing device: receiving, from a client device of a first user of an online social network, an unstructured text query comprising an ambiguous n-gram, the online social network being associated with a plurality of objects; identifying one or more objects corresponding to the ambiguous n-gram based on a calculated probability that the n-gram correspond to the identified objects; generating a first set of structured queries, each structured query from the first set of structured queries corresponding to an identified object, the structured query comprising a reference to the corresponding identified object; receiving, from the client device of the first user, a selection of a structured query corresponding to a first object of the identified objects; and generating a second set of structured queries, each structured query of the second set of structured queries comprising a reference to the first object. 12. The method of claim 1 , further comprising sending the first set of structured queries for display to the first user as the first user enters the unstructured text query into a graphical user interface, the display of the first set of structured queries to the first user enabling the first user to select the first structured query from the first set of structured queries. | 0.584615 |
8,595,246 | 6 | 7 | 6. The method of claim 5 , wherein the keywords of the service metadata assets comprise terms in the service metadata asset's metadata. | 6. The method of claim 5 , wherein the keywords of the service metadata assets comprise terms in the service metadata asset's metadata. 7. The method of claim 6 , wherein the keywords of the service metadata assets further comprise terms that appear in documents and links associated with the service metadata asset. | 0.5 |
9,911,143 | 2 | 12 | 2. An event-collection-and-event-processing system comprising: one or more computer systems, each having one or more processors, one or more memories, and one or more mass-storage devices; an event-collection subsystem, operating within one or more of the one or more computer systems, which: receives encoded data from one or more browser applications, executing on one or more remote user computers, the encoded data event generated by instrumentation within one or more instrumented web pages processed and rendered for display by the one or more browser applications; processes the received encoded data to produce a set of initially processed events, each of the set of initially processed events having an initial number of data entities; and stores the set of initially processed events in one or more of the one or more memories; an abstraction layer, operating within one or more of the one or more computer systems, that: receives the set of initially processed events from the event-collection subsystem; further processes the set of initially processed events to generate a corresponding set of processed events, each processed event in the set of processed events having a data entity that represents a topic assignment output assigned to the processed event, the further processing including: accessing a set of current distributions, the set of current distributions including: a regular-word distribution associated with a global topic; a seed-word distribution associated with the global topic; for each of a set of topics, a regular-word distribution associated with the topic; and for each of the set of topics, a seed-word distribution associated with the topic, the seed-word distribution associated with the topic including, for each seed word a plurality of seed words, a quantity indicating a number of observations where the seed word was included in an event and was associated with the topic; performing a set of iteration operations that include: for each word of a plurality of words in the set of initially processed events: determining, based on the set of current distributions, whether the word corresponds to a regular word or a seed word; determining, based on the set of current distributions, whether the word corresponds to a global topic or a discovered topic; and updating the set of current distributions based on, for each word of the plurality of words, the determination as to whether the word corresponds to a regular word or a seed word and the determination as to whether the word corresponds to a global topic or a discovered topic; and based on one or more iterations of the set of iteration operations, identifying, for each initially processed event in the set of initially processed events, the topic-assignment output to be represented in a processed event in the set of processed events corresponding to the initially processed event, and an event-consuming application, operating within one or more of the one or more computer systems, that receives the topic-assignment outputs of the set of initially processed events from the abstraction layer and uses the topic-assignment outputs processed events to produce one or more results. | 2. An event-collection-and-event-processing system comprising: one or more computer systems, each having one or more processors, one or more memories, and one or more mass-storage devices; an event-collection subsystem, operating within one or more of the one or more computer systems, which: receives encoded data from one or more browser applications, executing on one or more remote user computers, the encoded data event generated by instrumentation within one or more instrumented web pages processed and rendered for display by the one or more browser applications; processes the received encoded data to produce a set of initially processed events, each of the set of initially processed events having an initial number of data entities; and stores the set of initially processed events in one or more of the one or more memories; an abstraction layer, operating within one or more of the one or more computer systems, that: receives the set of initially processed events from the event-collection subsystem; further processes the set of initially processed events to generate a corresponding set of processed events, each processed event in the set of processed events having a data entity that represents a topic assignment output assigned to the processed event, the further processing including: accessing a set of current distributions, the set of current distributions including: a regular-word distribution associated with a global topic; a seed-word distribution associated with the global topic; for each of a set of topics, a regular-word distribution associated with the topic; and for each of the set of topics, a seed-word distribution associated with the topic, the seed-word distribution associated with the topic including, for each seed word a plurality of seed words, a quantity indicating a number of observations where the seed word was included in an event and was associated with the topic; performing a set of iteration operations that include: for each word of a plurality of words in the set of initially processed events: determining, based on the set of current distributions, whether the word corresponds to a regular word or a seed word; determining, based on the set of current distributions, whether the word corresponds to a global topic or a discovered topic; and updating the set of current distributions based on, for each word of the plurality of words, the determination as to whether the word corresponds to a regular word or a seed word and the determination as to whether the word corresponds to a global topic or a discovered topic; and based on one or more iterations of the set of iteration operations, identifying, for each initially processed event in the set of initially processed events, the topic-assignment output to be represented in a processed event in the set of processed events corresponding to the initially processed event, and an event-consuming application, operating within one or more of the one or more computer systems, that receives the topic-assignment outputs of the set of initially processed events from the abstraction layer and uses the topic-assignment outputs processed events to produce one or more results. 12. The event-collection-and-event-processing system of claim 2 , wherein the topic-assignment output includes an indication of a topic to which the initially processed event is to be defined or an error indication. | 0.908198 |
9,881,066 | 1 | 8 | 1. A system configured to provide an interactive user interface and process one or more data sets in response to inputs received via the interactive user interface in order to search and analyze transaction data within at least two databases, the system comprising: one or more hardware computer processors configured to execute software code stored in at least one tangible storage device in order to cause the system to: process data involving a user interface that is configured to process information between a user and the databases, the databases containing organized information including object oriented and relationally-structured information associated with the transaction data, wherein at least a portion of the information is only semi-structured and not organized in a hierarchical structure or directory of folders and subfolders, and wherein at least one of the databases is configured to be accessed via technical queries using a technical search language, and wherein the information is organized in accordance with a data model with initial objects as nodes which may be linked to other second objects having a relationship with the initial objects, the second objects defining properties or attributes of the initial objects; provide interactive user interface tools in the user interface including at least one of graphical input fields or indicia to perform at least one of predefined or customizable searches of the transaction data as a function of one or more search queries, the graphical input fields or indicia comprising query fields for entering search terms in a free textual format, including an account holder field, an asset field, an address, and a date field; automatically generate technical database queries based on the search terms entered via the query fields; search all of the information in the database based on the automatically generated technical database queries; update the user interface responsive to the user searches, wherein the user interface is configured to display the transaction data including one or more representations of the organized information within the user interface, the one or more representations of the organized information corresponding to parameters of the transaction data determinable via the one or more search queries, the representations displayed in the user interface comprising a graphical representation comprising at least a single parent node as an initial object and a plurality of child nodes, and wherein the representations further comprise displaying in the user interface a plurality of second objects comprising second identifying information not identified in the initial search terms but associated with the parent node or one or more of the child nodes, the second objects comprising attributes associated with resources in which data regarding the second objects is stored and graphical indicia of the attributes, wherein the graphical indicia of the attributes is arranged and structured in the user interface such that user, via interaction with the graphical indicia in the user interface, selects the resources to search or filters the search to selected resources; and in response to selection of one or more of the second objects in the user interface: perform a secondary search based on the selection of one or more of the second objects; process the organized information into at least one subset that meets the secondary search; and update the user interface to display the at least one subset that meets the secondary search, the subset comprising attributes or properties of the parent node or one of the child nodes displayed as roots of the graph, wherein the subset contains only refined search results provided via the secondary search as a function of the graphical indicia selected by the user. | 1. A system configured to provide an interactive user interface and process one or more data sets in response to inputs received via the interactive user interface in order to search and analyze transaction data within at least two databases, the system comprising: one or more hardware computer processors configured to execute software code stored in at least one tangible storage device in order to cause the system to: process data involving a user interface that is configured to process information between a user and the databases, the databases containing organized information including object oriented and relationally-structured information associated with the transaction data, wherein at least a portion of the information is only semi-structured and not organized in a hierarchical structure or directory of folders and subfolders, and wherein at least one of the databases is configured to be accessed via technical queries using a technical search language, and wherein the information is organized in accordance with a data model with initial objects as nodes which may be linked to other second objects having a relationship with the initial objects, the second objects defining properties or attributes of the initial objects; provide interactive user interface tools in the user interface including at least one of graphical input fields or indicia to perform at least one of predefined or customizable searches of the transaction data as a function of one or more search queries, the graphical input fields or indicia comprising query fields for entering search terms in a free textual format, including an account holder field, an asset field, an address, and a date field; automatically generate technical database queries based on the search terms entered via the query fields; search all of the information in the database based on the automatically generated technical database queries; update the user interface responsive to the user searches, wherein the user interface is configured to display the transaction data including one or more representations of the organized information within the user interface, the one or more representations of the organized information corresponding to parameters of the transaction data determinable via the one or more search queries, the representations displayed in the user interface comprising a graphical representation comprising at least a single parent node as an initial object and a plurality of child nodes, and wherein the representations further comprise displaying in the user interface a plurality of second objects comprising second identifying information not identified in the initial search terms but associated with the parent node or one or more of the child nodes, the second objects comprising attributes associated with resources in which data regarding the second objects is stored and graphical indicia of the attributes, wherein the graphical indicia of the attributes is arranged and structured in the user interface such that user, via interaction with the graphical indicia in the user interface, selects the resources to search or filters the search to selected resources; and in response to selection of one or more of the second objects in the user interface: perform a secondary search based on the selection of one or more of the second objects; process the organized information into at least one subset that meets the secondary search; and update the user interface to display the at least one subset that meets the secondary search, the subset comprising attributes or properties of the parent node or one of the child nodes displayed as roots of the graph, wherein the subset contains only refined search results provided via the secondary search as a function of the graphical indicia selected by the user. 8. The system of claim 1 , wherein the code is further configured to: provide, via the user interfaces, a first custom view including summary data regarding the search results and a second custom view including graphical depiction of object model data associated with the summary data displayed in the first custom view; and provide the user at least one tool to navigate between the first custom view and the second custom view. | 0.748829 |
7,865,699 | 14 | 17 | 14. A method as in claim 13 , further comprising setting a state of at least one page table entry bit for indicating, on a code page by code page basis, whether the code page is partitioned into said first and second sections for storing instruction words and at least one instruction word extension, or whether the code page is comprised instead of a single section storing only instruction words. | 14. A method as in claim 13 , further comprising setting a state of at least one page table entry bit for indicating, on a code page by code page basis, whether the code page is partitioned into said first and second sections for storing instruction words and at least one instruction word extension, or whether the code page is comprised instead of a single section storing only instruction words. 17. A method as in claim 14 , further comprising addressing an instruction word in said first section using a current instruction address, while simultaneously addressing an extension to said instruction word at a fixed offset from said current instruction address. | 0.5 |
7,613,731 | 1 | 2 | 1. A computer system for presenting an electronic document to a viewer to facilitate comprehension and control display and speed of delivery, comprising: a plurality of knowledge databases in the computer system for use in assigning an emphasis value to each word in the electronic document; an annotation module in the computer system including a cognitive cluster parser configured to group selected word pairings as cognitive clusters to be treated as one word and an analysis engine configured to assign an emphasis value to each word and cognitive cluster, the cognitive cluster parser and analysis engine interacting to generate a first tagged file of assigned emphasis values for each word and cognitive cluster; a first analysis module in the computer system including a compiler engine configured to derive emphasis values for recognizability and comprehensibility and an author interface configured to facilitate tag editing, the first analysis module for processing the first tagged file to generate a second tagged file of derived emphasis values; a second analysis module in the computer system including a property editor configured to facilitate editing of properties of selected words and cognitive clusters in the electronic document, the second analysis module for processing the second tagged file to generate a deliverable file that dynamically controls the presentation of the electronic document to the viewer; a printer or an electronic display device; and a delivery display module operative with the property deliverable file and the printer or electronic display device to at least one of print or display the electronic document. | 1. A computer system for presenting an electronic document to a viewer to facilitate comprehension and control display and speed of delivery, comprising: a plurality of knowledge databases in the computer system for use in assigning an emphasis value to each word in the electronic document; an annotation module in the computer system including a cognitive cluster parser configured to group selected word pairings as cognitive clusters to be treated as one word and an analysis engine configured to assign an emphasis value to each word and cognitive cluster, the cognitive cluster parser and analysis engine interacting to generate a first tagged file of assigned emphasis values for each word and cognitive cluster; a first analysis module in the computer system including a compiler engine configured to derive emphasis values for recognizability and comprehensibility and an author interface configured to facilitate tag editing, the first analysis module for processing the first tagged file to generate a second tagged file of derived emphasis values; a second analysis module in the computer system including a property editor configured to facilitate editing of properties of selected words and cognitive clusters in the electronic document, the second analysis module for processing the second tagged file to generate a deliverable file that dynamically controls the presentation of the electronic document to the viewer; a printer or an electronic display device; and a delivery display module operative with the property deliverable file and the printer or electronic display device to at least one of print or display the electronic document. 2. The system for presenting an electronic document of claim 1 wherein the plurality of knowledge databases comprises at least one of a cognitive cluster database, a rarity database, a graphical similarity database, a parts of speech database, and a context database. | 0.620739 |
8,265,932 | 11 | 18 | 11. A method for identifying audio command prompts for use in a voice response environment, comprising: generating a signature for one or more received audio samples each having preceding audio, reference phrase audio, and trailing audio segments, comprising: removing the trailing audio segment and dividing each of the preceding audio and reference phrase audio segments into buffers; transforming the buffers into discrete fourier transform buffers; and selecting one of the discrete fourier transform buffers from the reference phrase audio segment that is least like any of the discrete fourier transform buffers from the preceding audio segment as the signature that identifies an audio phrase under the reference phrase audio segment for that audio sample, comprising: determining a preceding audio correlation coefficient between each of the discrete fourier transform buffers from the reference phrase audio segment and each of the discrete fourier transform buffers from the preceding audio segment; selecting for each of the discrete fourier transform buffers from the reference phrase audio segment, a maximum value of the preceding audio correlation coefficients; determining a reference audio correlation coefficient between each of the discrete fourier transform buffers in the reference phrase audio segment and the remaining discrete fourier transform buffers in the reference phrase audio segment; selecting for each of the discrete fourier transform buffers from the reference phrase audio segment, a maximum value of the reference audio correlation coefficients; determining a distance for each of the discrete fourier transform buffers in the reference phrase audio segment based on the maximum values of the preceding audio correlation coefficient and the maximum value of the reference audio correlation coefficient; and selecting the one discrete fourier transform buffer from the reference phrase audio segment with the greatest distance as the signature; receiving audio command prompts and processing each of the audio command prompts to generate a discrete fourier transform; comparing each discrete fourier transform for the audio command prompts with each of the signatures and determining a correlation value of each comparison; and determining that one such audio command prompt matches one such signature when the correlation value for that audio command prompt and signature satisfies a threshold. | 11. A method for identifying audio command prompts for use in a voice response environment, comprising: generating a signature for one or more received audio samples each having preceding audio, reference phrase audio, and trailing audio segments, comprising: removing the trailing audio segment and dividing each of the preceding audio and reference phrase audio segments into buffers; transforming the buffers into discrete fourier transform buffers; and selecting one of the discrete fourier transform buffers from the reference phrase audio segment that is least like any of the discrete fourier transform buffers from the preceding audio segment as the signature that identifies an audio phrase under the reference phrase audio segment for that audio sample, comprising: determining a preceding audio correlation coefficient between each of the discrete fourier transform buffers from the reference phrase audio segment and each of the discrete fourier transform buffers from the preceding audio segment; selecting for each of the discrete fourier transform buffers from the reference phrase audio segment, a maximum value of the preceding audio correlation coefficients; determining a reference audio correlation coefficient between each of the discrete fourier transform buffers in the reference phrase audio segment and the remaining discrete fourier transform buffers in the reference phrase audio segment; selecting for each of the discrete fourier transform buffers from the reference phrase audio segment, a maximum value of the reference audio correlation coefficients; determining a distance for each of the discrete fourier transform buffers in the reference phrase audio segment based on the maximum values of the preceding audio correlation coefficient and the maximum value of the reference audio correlation coefficient; and selecting the one discrete fourier transform buffer from the reference phrase audio segment with the greatest distance as the signature; receiving audio command prompts and processing each of the audio command prompts to generate a discrete fourier transform; comparing each discrete fourier transform for the audio command prompts with each of the signatures and determining a correlation value of each comparison; and determining that one such audio command prompt matches one such signature when the correlation value for that audio command prompt and signature satisfies a threshold. 18. A method according to claim 11 , further comprising: receiving the reference phrase audio segment from a user. | 0.785714 |
8,775,437 | 2 | 3 | 2. The method of claim 1 , further comprising computing at least one contribution dimension for the sources associated with the promoted results. | 2. The method of claim 1 , further comprising computing at least one contribution dimension for the sources associated with the promoted results. 3. The method of claim 2 , wherein the contribution dimension filter is configured to manipulate the promoted results and the search result based upon the contribution dimension. | 0.5 |
8,612,202 | 8 | 13 | 8. An information analysis method using a plurality of linguistic expressions as an analysis target, the information analysis method comprising: (a) a step of extracting time information included in each of a plurality of electronic documents including at least any one of the plurality of linguistic expressions and a relationship between the electronic documents in the plurality of electronic documents from the plurality of electronic documents; (b) a step of detecting a link between one linguistic expression and another linguistic expression in the plurality of linguistic expressions and an appearance time of the link based on the time information and the relationship between the electronic documents that are extracted in step (a), and generating link information specifying the detected link and the appearance time of the link; and (c) a step of specifying the number of appearances of links between the one linguistic expression and the other linguistic expression and an appearance time of each link based on the link information generated in step (b), and calculating a correlation value between the one linguistic expression and the other linguistic expression by using the number of appearances of the link and the appearance time of each link, the calculation of the correlation value being made by using a function that increases depending on a difference between first appearance time of one link and second appearance time of another link, wherein each step is implemented by a CPU. | 8. An information analysis method using a plurality of linguistic expressions as an analysis target, the information analysis method comprising: (a) a step of extracting time information included in each of a plurality of electronic documents including at least any one of the plurality of linguistic expressions and a relationship between the electronic documents in the plurality of electronic documents from the plurality of electronic documents; (b) a step of detecting a link between one linguistic expression and another linguistic expression in the plurality of linguistic expressions and an appearance time of the link based on the time information and the relationship between the electronic documents that are extracted in step (a), and generating link information specifying the detected link and the appearance time of the link; and (c) a step of specifying the number of appearances of links between the one linguistic expression and the other linguistic expression and an appearance time of each link based on the link information generated in step (b), and calculating a correlation value between the one linguistic expression and the other linguistic expression by using the number of appearances of the link and the appearance time of each link, the calculation of the correlation value being made by using a function that increases depending on a difference between first appearance time of one link and second appearance time of another link, wherein each step is implemented by a CPU. 13. The information analysis method according to claim 8 , wherein step (b) comprises calculating an intermediate time between a time included in the time information of the electronic document including the one linguistic expression and a time included in the time information of the electronic document including the other linguistic expression, and using the calculated intermediate time as the appearance time of the link. | 0.592734 |
9,653,071 | 1 | 7 | 1. A computer implemented method for speech recognition error detection, the method comprising: analyzing an utterance received from an audio input device; generating a text sentence of one or more words based on the utterance; generating a N-best list of predicted error sequences of the text sentence, wherein each of the one or more words of the text sentence is assigned a label in the N-best list of predicted error sequences, wherein the label represents a likelihood of error that is associated with each word of the one of more words of the text sentence, wherein the label is assigned a probability score indicative of a probability that the label is accurate, wherein the probability score for the label is determined by a weighted sum of at least two word features; rescoring each label of the N-best list of the predicted error sequences, wherein rescoring each label of the N-best list of predicted error sequences comprises using optimal metacost parameters to rescore each label, wherein the optimal metacost parameters are parameters of a metacost matrix; selecting a best rescored error sequence from the N-best list of the predicted error sequences based on rescored labels; and executing a dialog action based on the best rescored error sequence and a dialog action policy, wherein the dialog action policy indicates the dialog action based on the rescored labels of the best rescored error sequence, wherein executing the dialog action includes controlling an electronic computing device to execute at least one of: playing back of at least a portion of the text sentence and requesting a confirmation of accuracy of the text sentence when the best rescored error sequence comprises a major error, and discarding the text sentence and requesting to repeat the utterance when the best rescored error sequence comprises at least two of the major errors, wherein the best rescored error sequence comprises the major error when the one or more words of the text sentence include a noun, a proper-noun, or a verb, wherein executing the dialog action includes controlling the electronic computing device to compare the dialog action of the best rescored error sequence to a previously determined dialog action of a previously selected best rescored error sequence to determine if the dialog action of the best rescored error sequence is less or more severe than the previously determined dialog action policy of the previously selected best rescored error sequence, wherein the electronic computing device is controlled to update optimal metacost parameters of a metacost matrix when it is determined that the dialog action of the best rescored error sequence is more severe than the previously determined dialog action policy of the previously selected best rescored error sequence. | 1. A computer implemented method for speech recognition error detection, the method comprising: analyzing an utterance received from an audio input device; generating a text sentence of one or more words based on the utterance; generating a N-best list of predicted error sequences of the text sentence, wherein each of the one or more words of the text sentence is assigned a label in the N-best list of predicted error sequences, wherein the label represents a likelihood of error that is associated with each word of the one of more words of the text sentence, wherein the label is assigned a probability score indicative of a probability that the label is accurate, wherein the probability score for the label is determined by a weighted sum of at least two word features; rescoring each label of the N-best list of the predicted error sequences, wherein rescoring each label of the N-best list of predicted error sequences comprises using optimal metacost parameters to rescore each label, wherein the optimal metacost parameters are parameters of a metacost matrix; selecting a best rescored error sequence from the N-best list of the predicted error sequences based on rescored labels; and executing a dialog action based on the best rescored error sequence and a dialog action policy, wherein the dialog action policy indicates the dialog action based on the rescored labels of the best rescored error sequence, wherein executing the dialog action includes controlling an electronic computing device to execute at least one of: playing back of at least a portion of the text sentence and requesting a confirmation of accuracy of the text sentence when the best rescored error sequence comprises a major error, and discarding the text sentence and requesting to repeat the utterance when the best rescored error sequence comprises at least two of the major errors, wherein the best rescored error sequence comprises the major error when the one or more words of the text sentence include a noun, a proper-noun, or a verb, wherein executing the dialog action includes controlling the electronic computing device to compare the dialog action of the best rescored error sequence to a previously determined dialog action of a previously selected best rescored error sequence to determine if the dialog action of the best rescored error sequence is less or more severe than the previously determined dialog action policy of the previously selected best rescored error sequence, wherein the electronic computing device is controlled to update optimal metacost parameters of a metacost matrix when it is determined that the dialog action of the best rescored error sequence is more severe than the previously determined dialog action policy of the previously selected best rescored error sequence. 7. The computer implemented method of claim 1 , wherein the word features include lexical features, automated speech recognition features, syntactic features, and subword features; the lexical features include at least one of the word in the text sentence and a position of the word in the text sentence; the automated speech recognition features include at least one of a posterior confidence of an accuracy of the word in the text sentence, a duration of time for the word in the utterance, a presence of an ngram of the word in a language model, and a ratio of alternative nodes to a current node in a word confusion network; the syntactic features include at least one of a part of speech tag for the word in the text sentence, a part of speech confidence for the word in the text sentence, and a chunk label for the word in the text sentence; and the subword features include a presence of a subword in a timeframe of an output of a hybrid decoder module. | 0.5 |
10,152,525 | 1 | 5 | 1. A method for transforming training data to improve data classification, the method comprising: extracting, by a data transforming system, concepts from a training data set, wherein the training data set comprises data records corresponding to one or more categories; computing, by the data transforming system, frequency of occurrence of each concept in each category of the one or more categories; removing, by the data transforming system, one or more concepts from the data records when the frequency of occurrence of a concept in a category is less than a threshold frequency value; computing, by the data transforming system, a percentage contribution of each concept of remaining concepts in each category upon removing the one or more concepts; eliminating, by the data transforming system, concepts, from the remaining concepts, contributing equally to each category based on the percentage contribution of each concept to provide a reformed training data set, wherein eliminating concepts contributing equally to each category comprises eliminating concepts corresponding to a row in an asymmetry matrix from the training data set when a maximum distance of distances in the row of the asymmetry matrix is less than a pre-defined contribution value; and appending, by the data transforming system, a category name to a corresponding data record in the reformed training data set based on a normalized frequency of occurrence of the concept in a category to improve data classification. | 1. A method for transforming training data to improve data classification, the method comprising: extracting, by a data transforming system, concepts from a training data set, wherein the training data set comprises data records corresponding to one or more categories; computing, by the data transforming system, frequency of occurrence of each concept in each category of the one or more categories; removing, by the data transforming system, one or more concepts from the data records when the frequency of occurrence of a concept in a category is less than a threshold frequency value; computing, by the data transforming system, a percentage contribution of each concept of remaining concepts in each category upon removing the one or more concepts; eliminating, by the data transforming system, concepts, from the remaining concepts, contributing equally to each category based on the percentage contribution of each concept to provide a reformed training data set, wherein eliminating concepts contributing equally to each category comprises eliminating concepts corresponding to a row in an asymmetry matrix from the training data set when a maximum distance of distances in the row of the asymmetry matrix is less than a pre-defined contribution value; and appending, by the data transforming system, a category name to a corresponding data record in the reformed training data set based on a normalized frequency of occurrence of the concept in a category to improve data classification. 5. The method of claim 1 , wherein appending the category name to the corresponding data record comprises: creating, by the data transformation system, a domain concept frequency matrix comprising concepts in the reformed training data set and the frequency of occurrence of each concept in each category; computing, by the data transformation system, the normalized frequency of occurrence based on a minimum frequency of occurrence and a maximum frequency of occurrence; and appending, by the data transformation system, the category name corresponding to a maximum normalized frequency of occurrence to the corresponding data record the maximum normalized frequency of occurrence times to improve data classification. | 0.5 |
9,830,950 | 1 | 12 | 1. A mobile discovery method for recognizing and/or identifying media and physical objects, the method employing a mobile device equipped with plural sensors, including an optical sensor, the mobile device being operated in an ambient environment illuminated by a solid state lamp fixture that is separate from the mobile device, the method including the acts: in a first circumstance, a processor of said device selecting a first recognition agent, from among plural available recognition agents, and launching said first recognition agent, the first recognition agent performing a recognition process selected from the list: image watermark recognition, pattern matching, object recognition, facial recognition, barcode recognition, sign language recognition, optical character recognition, audio watermark recognition, speech recognition, and music recognition; and in a second circumstance, the processor selecting a second recognition agent different than the first recognition agent, and launching said second recognition agent, the second recognition agent performing a second, different, recognition process selected from said list; wherein the method includes the optical sensor of the mobile device sensing an encoded optical signal emitted by said solid state lamp fixture, and the mobile device decoding said optical signal sensed by the optical sensor to extract plural-bit payload data, wherein said selecting of the first recognition agent from among the plural available recognition agents depends at least in part on said plural-bit payload data decoded by the mobile device from the encoded optical signal emitted from the lamp fixture. | 1. A mobile discovery method for recognizing and/or identifying media and physical objects, the method employing a mobile device equipped with plural sensors, including an optical sensor, the mobile device being operated in an ambient environment illuminated by a solid state lamp fixture that is separate from the mobile device, the method including the acts: in a first circumstance, a processor of said device selecting a first recognition agent, from among plural available recognition agents, and launching said first recognition agent, the first recognition agent performing a recognition process selected from the list: image watermark recognition, pattern matching, object recognition, facial recognition, barcode recognition, sign language recognition, optical character recognition, audio watermark recognition, speech recognition, and music recognition; and in a second circumstance, the processor selecting a second recognition agent different than the first recognition agent, and launching said second recognition agent, the second recognition agent performing a second, different, recognition process selected from said list; wherein the method includes the optical sensor of the mobile device sensing an encoded optical signal emitted by said solid state lamp fixture, and the mobile device decoding said optical signal sensed by the optical sensor to extract plural-bit payload data, wherein said selecting of the first recognition agent from among the plural available recognition agents depends at least in part on said plural-bit payload data decoded by the mobile device from the encoded optical signal emitted from the lamp fixture. 12. The method of claim 1 that includes, in the first circumstance, and in dependence on the plural-bit data decoded from the optical signal, selecting a first recognition agent that performs optical character recognition, and launching said first recognition agent. | 0.581761 |
7,991,790 | 60 | 61 | 60. The system of claim 59 , the method further comprising: applying a hash function to the document, therein generating a hash value, and including the hash value within the unique identifier. | 60. The system of claim 59 , the method further comprising: applying a hash function to the document, therein generating a hash value, and including the hash value within the unique identifier. 61. The system of claim 60 , the applying of the hash function and the including of the hash value in the unique identifier are performed in association with the storing of the document in the document management storage. | 0.5 |
7,519,223 | 44 | 45 | 44. The interactive display system of claim 40 , wherein the machine instructions further cause the processor to analyze temporal patterns of a plurality of sets of touch connected components as the touch connected components change over time, to identify appendages of each of a plurality of different users, where the appendages are hovering adjacent to the display surface, and to determine that groupings of multiple fingers in contact with the display surface belong to specific ones of the appendages, and thus, belong to specific users, based on an orientation of each appendage, and on the temporal patterns. | 44. The interactive display system of claim 40 , wherein the machine instructions further cause the processor to analyze temporal patterns of a plurality of sets of touch connected components as the touch connected components change over time, to identify appendages of each of a plurality of different users, where the appendages are hovering adjacent to the display surface, and to determine that groupings of multiple fingers in contact with the display surface belong to specific ones of the appendages, and thus, belong to specific users, based on an orientation of each appendage, and on the temporal patterns. 45. The interactive display system of claim 44 , wherein the machine instructions further cause the processor to determine that an appendage and a grouping of multiple fingers belongs to a specific user based upon knowledge of where the specific user is located around the display surface. | 0.5 |
8,423,978 | 13 | 17 | 13. A data processing system for processing a JavaServer page, comprising: a processor, wherein the process is configured to perform: translating the JavaServer page into a document object model object; configuring a set of visitor classes for invocation in a selected sequence; and processing the document object model using the set of visitor classes in the selected sequence to perform a desired set of custom functions on the document object model. | 13. A data processing system for processing a JavaServer page, comprising: a processor, wherein the process is configured to perform: translating the JavaServer page into a document object model object; configuring a set of visitor classes for invocation in a selected sequence; and processing the document object model using the set of visitor classes in the selected sequence to perform a desired set of custom functions on the document object model. 17. The data processing system of claim 13 , wherein the set of visitor classes for invocation in the selected sequence is defined in a configuration file. | 0.753185 |
7,555,287 | 36 | 37 | 36. A system, comprising: a user interface coupled to an access point, configured to prepare a customized message and a trigger word for storage in the access point, to enable the access point to detect events specified by the trigger word, the trigger word including a specification of an address of a wireless terminal to be detected, a specification of a type of the wireless terminal, and a specification of a time of day to detect the wireless terminal wherein the events include receiving a signal from a wireless terminal within a coverage area of the access point, the signal indicating a type of the wireless terminal and an address of the wireless terminal; a radio in the access point configured to receive a packet including said type indication and address from a mobile wireless terminal; a processor in the access point configured to match said type indication and said address in the received packet with said trigger word; said processor determining that the time of day specified in the trigger word is the same as the time of day that the wireless terminal is detected; and said processor determining a match and in response, using said trigger word to invoke sending the customized message to a server. | 36. A system, comprising: a user interface coupled to an access point, configured to prepare a customized message and a trigger word for storage in the access point, to enable the access point to detect events specified by the trigger word, the trigger word including a specification of an address of a wireless terminal to be detected, a specification of a type of the wireless terminal, and a specification of a time of day to detect the wireless terminal wherein the events include receiving a signal from a wireless terminal within a coverage area of the access point, the signal indicating a type of the wireless terminal and an address of the wireless terminal; a radio in the access point configured to receive a packet including said type indication and address from a mobile wireless terminal; a processor in the access point configured to match said type indication and said address in the received packet with said trigger word; said processor determining that the time of day specified in the trigger word is the same as the time of day that the wireless terminal is detected; and said processor determining a match and in response, using said trigger word to invoke sending the customized message to a server. 37. The system of claim 36 , wherein said type indication is a class of device indication of the wireless terminal. | 0.5 |
9,194,001 | 8 | 12 | 8. The method of sequencing of claim 1 , wherein the cDNAs are made by the following process: (i) pooling a plurality of samples to make a pooled sample; and (ii) selecting tagged cDNAs from the pooled sample, wherein the tagged cDNAs correspond to one or more genes, thereby producing the plurality of cDNAs that are sequenced. | 8. The method of sequencing of claim 1 , wherein the cDNAs are made by the following process: (i) pooling a plurality of samples to make a pooled sample; and (ii) selecting tagged cDNAs from the pooled sample, wherein the tagged cDNAs correspond to one or more genes, thereby producing the plurality of cDNAs that are sequenced. 12. The method of sequencing of claim 8 , wherein the selecting is done by template-driven ligation. | 0.66443 |
8,630,859 | 12 | 13 | 12. The method of claim 1 , wherein a state in the selected recursive transition network flow controller has a subdialog attribute that is a name of a flow controller invoked as the subdialog. | 12. The method of claim 1 , wherein a state in the selected recursive transition network flow controller has a subdialog attribute that is a name of a flow controller invoked as the subdialog. 13. The method of claim 12 , wherein the state in the selected recursive transition network flow controller having the subdialog attribute that invokes a subdialog further comprises a set of instructions that retrieve values from a parent dialog and set values in the subdialog. | 0.5 |
9,288,058 | 1 | 2 | 1. A method, comprising: identifying, by a hardware processor, a first compliance script; determining a value of a cryptographic hash function of at least part of the first compliance script; determining, using the value of the cryptographic hash function, an installation path of a second compliance script; identifying a security context associated with the second compliance script at installation time; and executing, by the hardware processor, the second compliance script within the security context to determine whether a parameter of a computer system is within an allowed range. | 1. A method, comprising: identifying, by a hardware processor, a first compliance script; determining a value of a cryptographic hash function of at least part of the first compliance script; determining, using the value of the cryptographic hash function, an installation path of a second compliance script; identifying a security context associated with the second compliance script at installation time; and executing, by the hardware processor, the second compliance script within the security context to determine whether a parameter of a computer system is within an allowed range. 2. The method of claim 1 , wherein the second compliance script comprises at least one of: a compliance verification rule or a compliance remediation rule. | 0.777299 |
8,533,222 | 1 | 7 | 1. A computer-implemented system comprising: one or more computers; one or more data storage devices in data communication with the one or more computers, storing: a training data repository that includes client training data comprising a first plurality of training data sets belonging to a client entity and received over a network; a plurality of training functions; and instructions that, when executed by the one or more computers, cause the one or more computers to perform operations comprising: generating a plurality of trained predictive models using the plurality of training functions and a first sample of the client training data; determining a respective accuracy of each of the plurality of trained predictive models using a different, second sample of the client training data; receiving, over the network one or more new training data sets belonging to the client entity, wherein each of the one or more new training data sets is new relative to the first plurality of training data sets; updating the client training data to include the one or more new training data sets; generating a plurality of new trained predictive models using the plurality of training functions and a different, third sample of the client training data; determining, a respective accuracy of each of the plurality of new trained predictive models using a different, fourth sample of the client training data; generating a respective effectiveness score for each of the plurality of trained predictive models and each of the plurality of new trained predictive models using the determined accuracy of its respective trained predictive model; receiving, over the network from a client computing system, a first prediction request and first input data; selecting a first trained predictive model to service the first prediction request from among the plurality of trained predictive models and the plurality of new trained predictive models based on the respective effectiveness scores; running the first trained predictive model on the first input data to generate a predictive output; and providing, to the client computing system, the predictive output in response to the first prediction request. | 1. A computer-implemented system comprising: one or more computers; one or more data storage devices in data communication with the one or more computers, storing: a training data repository that includes client training data comprising a first plurality of training data sets belonging to a client entity and received over a network; a plurality of training functions; and instructions that, when executed by the one or more computers, cause the one or more computers to perform operations comprising: generating a plurality of trained predictive models using the plurality of training functions and a first sample of the client training data; determining a respective accuracy of each of the plurality of trained predictive models using a different, second sample of the client training data; receiving, over the network one or more new training data sets belonging to the client entity, wherein each of the one or more new training data sets is new relative to the first plurality of training data sets; updating the client training data to include the one or more new training data sets; generating a plurality of new trained predictive models using the plurality of training functions and a different, third sample of the client training data; determining, a respective accuracy of each of the plurality of new trained predictive models using a different, fourth sample of the client training data; generating a respective effectiveness score for each of the plurality of trained predictive models and each of the plurality of new trained predictive models using the determined accuracy of its respective trained predictive model; receiving, over the network from a client computing system, a first prediction request and first input data; selecting a first trained predictive model to service the first prediction request from among the plurality of trained predictive models and the plurality of new trained predictive models based on the respective effectiveness scores; running the first trained predictive model on the first input data to generate a predictive output; and providing, to the client computing system, the predictive output in response to the first prediction request. 7. The computer-implemented system of claim 1 , wherein the operations further comprise: maintaining the training data repository according to a data retention policy that defines rules determining which training data to retain and which training data to delete from the repository based on one or more of the following: respective dates of receipts of the training data and respective properties of the training data. | 0.821976 |
8,515,951 | 13 | 14 | 13. The method of claim 1 , wherein the data associated with the first population comprises a number of members of the first population. | 13. The method of claim 1 , wherein the data associated with the first population comprises a number of members of the first population. 14. The method of claim 13 , wherein the number of members of the first population comprises a number of members of the first population that selected a result returned for the search query. | 0.5 |
10,152,549 | 12 | 13 | 12. A system comprising: one or more processors; and a machine-readable medium comprising instructions stored therein, which when executed by the processors, cause the processors to perform operations comprising: receiving an indication of a request to provide a user with one or more suggestion items; identifying social activity and interaction data relating to the user and one or more contacts of the user at a social networking service, wherein the social activity and interaction data includes content corresponding to activity performed by at least one of the one or more contacts of the user within the social networking service; analyzing the social activity and interaction data; selecting a plurality of n-grams in response to the analyzing, each n-gram comprising a string of characters related to a plurality of terms; assigning a score to each of the plurality of n-grams based on one or more significance criteria; generating one or more candidate suggestions from the plurality of n-grams based on the score of each of the plurality of n-grams, the one or more candidate suggestions including recommended actions to perform within the social networking service; identifying one or more contacts or groups of contacts associated with at least one particular n-gram of the plurality of n-grams based on contacts and groups of contacts associated with the social activity and interaction data that the at least one particular n-gram appears in; and providing the one or more contacts or groups of contacts for display, by the social network service, along with a particular candidate suggestion relating to the at least one particular n-gram of the plurality of n-grams to facilitate additional user activity within the social networking service. | 12. A system comprising: one or more processors; and a machine-readable medium comprising instructions stored therein, which when executed by the processors, cause the processors to perform operations comprising: receiving an indication of a request to provide a user with one or more suggestion items; identifying social activity and interaction data relating to the user and one or more contacts of the user at a social networking service, wherein the social activity and interaction data includes content corresponding to activity performed by at least one of the one or more contacts of the user within the social networking service; analyzing the social activity and interaction data; selecting a plurality of n-grams in response to the analyzing, each n-gram comprising a string of characters related to a plurality of terms; assigning a score to each of the plurality of n-grams based on one or more significance criteria; generating one or more candidate suggestions from the plurality of n-grams based on the score of each of the plurality of n-grams, the one or more candidate suggestions including recommended actions to perform within the social networking service; identifying one or more contacts or groups of contacts associated with at least one particular n-gram of the plurality of n-grams based on contacts and groups of contacts associated with the social activity and interaction data that the at least one particular n-gram appears in; and providing the one or more contacts or groups of contacts for display, by the social network service, along with a particular candidate suggestion relating to the at least one particular n-gram of the plurality of n-grams to facilitate additional user activity within the social networking service. 13. The system of claim 12 , wherein the one or more significance criteria includes one or more of popularity of the n-grams, volume of social activity performed with respect to one or more social content items, a social affinity of the user and the one or more contacts, a level of interest of the user in content items relating to the n-grams, or relevance of the n-grams to user activity. | 0.564588 |
8,176,048 | 1 | 6 | 1. A method for transforming unstructured text into structured data using a domain-specific ontology, the method comprising: recording the unstructured text using an information extraction module (IEM); discovering text phrases contained in the recorded unstructured text via the IEM; retrieving lexical data from a knowledge source using the IEM and the discovered text phrases; processing each of the discovered text phrases and the lexical data using the IEM to thereby generate a plurality of nodes in the domain-specific ontology, wherein each of the plurality of nodes represents a corresponding single concept as a cluster of synonyms; using the plurality of generated nodes to classify the discovered text phrases by corresponding objects of interest, thereby transforming the unstructured text into structured data; generating a list of sub-phrases of the discovered text phrases; mapping each sub-phrase in the generated list of sub-phrases into the domain-specific ontology via the IEM; using an informativeness function to quantify each of the sub-phrases of the discovered text phrases by a normalized relative importance informativeness score of between 0 and 1; and eliminating all sub-phrases from the domain-specific ontology that have an informativeness score that is less than a calibrated threshold. | 1. A method for transforming unstructured text into structured data using a domain-specific ontology, the method comprising: recording the unstructured text using an information extraction module (IEM); discovering text phrases contained in the recorded unstructured text via the IEM; retrieving lexical data from a knowledge source using the IEM and the discovered text phrases; processing each of the discovered text phrases and the lexical data using the IEM to thereby generate a plurality of nodes in the domain-specific ontology, wherein each of the plurality of nodes represents a corresponding single concept as a cluster of synonyms; using the plurality of generated nodes to classify the discovered text phrases by corresponding objects of interest, thereby transforming the unstructured text into structured data; generating a list of sub-phrases of the discovered text phrases; mapping each sub-phrase in the generated list of sub-phrases into the domain-specific ontology via the IEM; using an informativeness function to quantify each of the sub-phrases of the discovered text phrases by a normalized relative importance informativeness score of between 0 and 1; and eliminating all sub-phrases from the domain-specific ontology that have an informativeness score that is less than a calibrated threshold. 6. The method of claim 1 , further comprising: automatically cleaning the unstructured text by at least one of: splitting joined words in the unstructured text, joining split words in the unstructured text, expanding an abbreviation in the unstructured text, executing a spell check process on the unstructured text, removing from the unstructured text any words lacking a domain-specific meaning, and stemming words or phrases in the unstructured text using a stemmer program. | 0.5 |
9,411,803 | 5 | 15 | 5. A non-transitory computer-readable medium storing instructions that upon execution cause at least one processor to: determine keywords likely to appear in natural language queries, the determining based on source code text of application programming interface (API) modules executable in response to the natural language queries to obtain data; associate each of the determined keywords with a respective API module of the API modules; alter an association between a determined keyword of the determined keywords and a respective API module of the API modules, in response to determining that the altered association is more likely to trigger an accurate response to a natural language query of the natural language queries; determine whether at least one determined keyword of the determined keywords appears in a received natural language query; respond to the received natural language query with data produced by each API module, of the API modules, that is associated with the at least one determined keyword that appears in the received natural language query; and rank the data returned by each API module associated with the at least one determined keyword based on a probability that the data is a correct response to the received natural language query. | 5. A non-transitory computer-readable medium storing instructions that upon execution cause at least one processor to: determine keywords likely to appear in natural language queries, the determining based on source code text of application programming interface (API) modules executable in response to the natural language queries to obtain data; associate each of the determined keywords with a respective API module of the API modules; alter an association between a determined keyword of the determined keywords and a respective API module of the API modules, in response to determining that the altered association is more likely to trigger an accurate response to a natural language query of the natural language queries; determine whether at least one determined keyword of the determined keywords appears in a received natural language query; respond to the received natural language query with data produced by each API module, of the API modules, that is associated with the at least one determined keyword that appears in the received natural language query; and rank the data returned by each API module associated with the at least one determined keyword based on a probability that the data is a correct response to the received natural language query. 15. The non-transitory computer-readable medium of claim 5 , wherein the instructions when executed cause the at least one processor to execute each API module associated with the at least one determined keyword to obtain data from a data structure that stores data in a format not obtainable by a structured query language (SQL). | 0.525862 |
9,691,483 | 6 | 8 | 6. A content addressable memory (CAM) comprising: a plurality of dictionary words, the dictionary words divided into a plurality of banks; at least two input words, the input words divided into segments, the segments aligned with the plurality of banks; and a scheduler to schedule parallel comparison of different segments of the input words with the banks aligned to the respective different segments. | 6. A content addressable memory (CAM) comprising: a plurality of dictionary words, the dictionary words divided into a plurality of banks; at least two input words, the input words divided into segments, the segments aligned with the plurality of banks; and a scheduler to schedule parallel comparison of different segments of the input words with the banks aligned to the respective different segments. 8. The CAM of claim 6 , wherein a dictionary word mismatch for a bank indicates the entire dictionary word does not match the input word currently being compared to the bank. | 0.5 |
8,972,851 | 1 | 9 | 1. A method of coding or decoding a structured document, the method comprising: (i) configuring an encoder or decoder including obtaining data describing a plurality of items of a document structure model and storing the data as a plurality of recordings to be used by the encoder or decoder for coding or decoding a plurality of corresponding items of a structured document, wherein each of the recordings is associated with a different one of the items of the document structure model and includes, for each said different item of the document structure model: minimum and maximum numbers of occurrences of said different item, and a number of possible types of item liable to occur after one of the occurrences of said different item, said number being calculated according to the document structure model, and wherein the recordings are stored in an order of appearance of associated items within the data describing the document structure model; and (ii) determining a possible item able to succeed a given item that is furthest away from the given item in the order of appearance within the data describing the document structure model, and for an item following the given item, the number of possible types of item is calculated based on a number of items separating the item following the given item and the possible item that is furthest away from the given item. | 1. A method of coding or decoding a structured document, the method comprising: (i) configuring an encoder or decoder including obtaining data describing a plurality of items of a document structure model and storing the data as a plurality of recordings to be used by the encoder or decoder for coding or decoding a plurality of corresponding items of a structured document, wherein each of the recordings is associated with a different one of the items of the document structure model and includes, for each said different item of the document structure model: minimum and maximum numbers of occurrences of said different item, and a number of possible types of item liable to occur after one of the occurrences of said different item, said number being calculated according to the document structure model, and wherein the recordings are stored in an order of appearance of associated items within the data describing the document structure model; and (ii) determining a possible item able to succeed a given item that is furthest away from the given item in the order of appearance within the data describing the document structure model, and for an item following the given item, the number of possible types of item is calculated based on a number of items separating the item following the given item and the possible item that is furthest away from the given item. 9. The method according to claim 1 , wherein the data describing the document structure model describe at least one group of items within which at least one other group of items is nested, a group of items describing a structure of the items constituting an element, and at least one of the recordings is associated with each group of items and gives information on the minimum and maximum numbers of occurrences of the group as defined by the document structure model. | 0.5 |
8,447,863 | 1 | 3 | 1. A method comprising: receiving, from a robot having at least one sensor, a query comprising: identification data obtained by the at least one sensor and associated with an unidentified object, contextual data obtained by the at least one sensor and associated with a location of the unidentified object, and situational data comprising a command obtained by the at least one sensor at a time proximate to the contextual data being obtained; identifying a plurality of candidate objects based on the identification data; making a determination of whether the unidentified object is an identified object in the plurality of candidate objects based at least in part on the contextual data and the situational data; and sending data associated with the identified object to the robot based on the determination. | 1. A method comprising: receiving, from a robot having at least one sensor, a query comprising: identification data obtained by the at least one sensor and associated with an unidentified object, contextual data obtained by the at least one sensor and associated with a location of the unidentified object, and situational data comprising a command obtained by the at least one sensor at a time proximate to the contextual data being obtained; identifying a plurality of candidate objects based on the identification data; making a determination of whether the unidentified object is an identified object in the plurality of candidate objects based at least in part on the contextual data and the situational data; and sending data associated with the identified object to the robot based on the determination. 3. The method of claim 1 , wherein the contextual data is further associated with at least one of (i) location data associated with the robot, and (ii) information associated with other objects within a predetermined distance of the unidentified object. | 0.657182 |
9,990,421 | 1 | 2 | 1. A computer-implemented method comprising: obtaining, from a phrase-based index for an Internet search engine, a list of documents from a collection of documents available via the Internet that contain a first phrase, the first phrase being relevant to a query; for each document in the list: determining, using related phrase information stored in the index for each document in the list of documents, whether the document includes one or more related phrases of the first phrase, where each related phrase has an actual co-occurrence rate of the related phrase and the first phrase in the document collection that exceeds an expected co-occurrence rate of the related phrase and the first phrase in the document collection; ranking the documents in the list based on a quantity of related phrases determined for each document, so that documents with more related phrases are ranked higher than documents with fewer related phrases; and selecting at least some of the highest-ranked documents to include in a result to the query. | 1. A computer-implemented method comprising: obtaining, from a phrase-based index for an Internet search engine, a list of documents from a collection of documents available via the Internet that contain a first phrase, the first phrase being relevant to a query; for each document in the list: determining, using related phrase information stored in the index for each document in the list of documents, whether the document includes one or more related phrases of the first phrase, where each related phrase has an actual co-occurrence rate of the related phrase and the first phrase in the document collection that exceeds an expected co-occurrence rate of the related phrase and the first phrase in the document collection; ranking the documents in the list based on a quantity of related phrases determined for each document, so that documents with more related phrases are ranked higher than documents with fewer related phrases; and selecting at least some of the highest-ranked documents to include in a result to the query. 2. The method of claim 1 , wherein determining whether the document includes one or more related phrases of the first phrase includes: accessing a posting list for the first phrase, the posting list including, for each document identified in the posting list, an indication of the quantity of related phrases present in the document. | 0.646497 |
8,122,026 | 1 | 10 | 1. A method for identifying documents referring to an entity, the entity being associated with a first set of features, the method comprising: identifying a first set of documents based on a first model and the first set of features, wherein the first model includes a first set of rules specifying at least one combination of features from the first set of features that are sufficient for identifying a document referring to the entity, each document of the first set of documents comprising a sufficient number of features in common with the first set of features to identify a document referring to the entity according to the first model; determining a second model based on the features of the first set of documents, wherein the second model includes a second set of rules specifying at least one combination of features from the first set of documents that are sufficient for identifying a document referring to the entity; identifying a second set of documents based on the second model and the first set of features, each document of the second set of documents comprising a sufficient number of features in common with the first set of features to identify a document referring to the entity according to the second model; identifying a second set of features based on the second set of documents; determining if the second set of features are associated with the entity; and responsive to determining that the second set of features are associated with the entity, identifying a third set of documents based on a third model and the second set of features, the third set of documents each comprising a sufficient number of features in common with the second set of features to identify a document referring to the entity according to the third model. | 1. A method for identifying documents referring to an entity, the entity being associated with a first set of features, the method comprising: identifying a first set of documents based on a first model and the first set of features, wherein the first model includes a first set of rules specifying at least one combination of features from the first set of features that are sufficient for identifying a document referring to the entity, each document of the first set of documents comprising a sufficient number of features in common with the first set of features to identify a document referring to the entity according to the first model; determining a second model based on the features of the first set of documents, wherein the second model includes a second set of rules specifying at least one combination of features from the first set of documents that are sufficient for identifying a document referring to the entity; identifying a second set of documents based on the second model and the first set of features, each document of the second set of documents comprising a sufficient number of features in common with the first set of features to identify a document referring to the entity according to the second model; identifying a second set of features based on the second set of documents; determining if the second set of features are associated with the entity; and responsive to determining that the second set of features are associated with the entity, identifying a third set of documents based on a third model and the second set of features, the third set of documents each comprising a sufficient number of features in common with the second set of features to identify a document referring to the entity according to the third model. 10. The method of claim 1 , further comprising: estimating importance of the entity based on an estimated importance of at least one of the documents in the second set of documents. | 0.650579 |
9,378,654 | 16 | 22 | 16. A system for rendering music notation comprising: one or more processors configured to: receive a request for electronic content, the request being communicated to the server by a client; obtain one or more files associated with the electronic content from a storage unit; parse one or more files associated with the electronic content to determine a music notation element; translate the music notation from a first format to a second format that is supported by a browser application; create a music notation object based at least in part on the translation; and send the music notation object to the client, wherein the client renders the music notation object via the browser application; and one or more memories coupled to the one or more processors, configured to provide the one or more processors with instructions. | 16. A system for rendering music notation comprising: one or more processors configured to: receive a request for electronic content, the request being communicated to the server by a client; obtain one or more files associated with the electronic content from a storage unit; parse one or more files associated with the electronic content to determine a music notation element; translate the music notation from a first format to a second format that is supported by a browser application; create a music notation object based at least in part on the translation; and send the music notation object to the client, wherein the client renders the music notation object via the browser application; and one or more memories coupled to the one or more processors, configured to provide the one or more processors with instructions. 22. The system of claim 16 , wherein the one or more processors are further configured to determine an audio rendering of the music object. | 0.57622 |
8,468,494 | 17 | 21 | 17. A computer-readable memory storing a set of instructions which, when executed by a processor, cause the processor to edit textual displays of a web-based software application having multiple web pages and multiple text items by: executing the web-based software application, the software application including a set of executable instructions for displaying web pages on a graphical user interface and allowing interaction therewith by a user, the software application including at least one secondary file providing resource bundles having a single key and text strings corresponding to text items, the executable instructions having an identifier for locating the single key and for calling the text strings for display on the web page; reading code for each text item which may be edited; receiving a selection of a text item to be edited through a web page on which the text item is displayed; creating an edited text item based on edits to the text item on the web page; saving the edited text item to the secondary file, wherein the single key of the secondary file identifies text items that are displayed a plurality of times on the web page; and dynamically displaying the edited text item in place of the text item on the web page using the single key for a plurality of users across a distributed network without reloading or refreshing the web page by the users. | 17. A computer-readable memory storing a set of instructions which, when executed by a processor, cause the processor to edit textual displays of a web-based software application having multiple web pages and multiple text items by: executing the web-based software application, the software application including a set of executable instructions for displaying web pages on a graphical user interface and allowing interaction therewith by a user, the software application including at least one secondary file providing resource bundles having a single key and text strings corresponding to text items, the executable instructions having an identifier for locating the single key and for calling the text strings for display on the web page; reading code for each text item which may be edited; receiving a selection of a text item to be edited through a web page on which the text item is displayed; creating an edited text item based on edits to the text item on the web page; saving the edited text item to the secondary file, wherein the single key of the secondary file identifies text items that are displayed a plurality of times on the web page; and dynamically displaying the edited text item in place of the text item on the web page using the single key for a plurality of users across a distributed network without reloading or refreshing the web page by the users. 21. The computer-readable memory of claim 17 further comprising: hosting the software application on a host machine; allowing simultaneous access to a plurality of users on a plurality of user terminals; and dynamically changing the displayed text item to the edited text item on each of the user terminals displaying the page having the text item thereon. | 0.5 |
9,846,743 | 1 | 4 | 1. A method comprising: receiving one or more indications of an occurrence of one or more browser events; determining, whether one or more webpage portions associated with the one or more browser events are to be analyzed for topic association, based on one or more temporal factors and textual characteristics associated with the one or more webpage portions, said temporal factors comprising a determination as to whether the one or more web page portions have been processed within a given time frame; analyzing the one or more webpage portions associated with the browser event where it is determined that the one or more webpage portions are to be analyzed, said analyzing comprising downloading a webpage portion from at least one website, extracting a text portion from the webpage portion and associating, in response to extracting the text portion, at least one topic from the text portion; storing the one or more analyzed webpage portions and the one or more indications of an occurrence of the one or more browser events in a database; aggregating, in response to receiving a query, a first set of analyzed webpage portions associated with a first website and a second set of analyzed webpage portions associated with at least one second, unaffiliated website, wherein the aggregated first set of analyzed webpage portions is associated with a set of publisher-specific metadata and the aggregated second set of analyzed webpage portions is associated with a set of anonymous metadata; comparing the aggregated first set of analyzed webpage portions and the aggregated second set of analyzed webpage portions; generating a comparison result, comprising the aggregated first set of analyzed webpage portions and the aggregated second set of analyzed webpage portions in response to the comparison; generating a set of recommended content associated with the comparison result; and transmitting the comparison result and the set of recommended content in response to the query. | 1. A method comprising: receiving one or more indications of an occurrence of one or more browser events; determining, whether one or more webpage portions associated with the one or more browser events are to be analyzed for topic association, based on one or more temporal factors and textual characteristics associated with the one or more webpage portions, said temporal factors comprising a determination as to whether the one or more web page portions have been processed within a given time frame; analyzing the one or more webpage portions associated with the browser event where it is determined that the one or more webpage portions are to be analyzed, said analyzing comprising downloading a webpage portion from at least one website, extracting a text portion from the webpage portion and associating, in response to extracting the text portion, at least one topic from the text portion; storing the one or more analyzed webpage portions and the one or more indications of an occurrence of the one or more browser events in a database; aggregating, in response to receiving a query, a first set of analyzed webpage portions associated with a first website and a second set of analyzed webpage portions associated with at least one second, unaffiliated website, wherein the aggregated first set of analyzed webpage portions is associated with a set of publisher-specific metadata and the aggregated second set of analyzed webpage portions is associated with a set of anonymous metadata; comparing the aggregated first set of analyzed webpage portions and the aggregated second set of analyzed webpage portions; generating a comparison result, comprising the aggregated first set of analyzed webpage portions and the aggregated second set of analyzed webpage portions in response to the comparison; generating a set of recommended content associated with the comparison result; and transmitting the comparison result and the set of recommended content in response to the query. 4. The method of claim 1 wherein the first set of analyzed webpage portions and the second set of analyzed webpage portions are associated with a topic. | 0.735192 |
8,533,680 | 8 | 9 | 8. One or more nonvolatile computer-readable storage media containing instructions which, when executed by a computer, cause the computer to perform a method, the method comprising: passing a symbolic parameter to a function of a program in a symbolic state representation of a program, the symbolic parameter comprising a symbolic sub-parameter that comprises a variable term; examining a set of value constraints for a pre-defined approximation of possible values associated with the symbolic parameter; as a result of not finding the pre-defined approximation of possible values in the set of value constraints, generating a domain of possible solutions for the symbolic parameter, the generating comprising: determining properties of the symbolic parameter, the properties of the symbolic parameter comprising a term type; determining possible values for the variable term, the determining the possible values for the variable term comprises walking over field maps of a representation of a given state and extracting one or more object terms appearing in the given state which match a type of the variable term; and selecting and applying one or more of a plurality of domain computation techniques according to the properties of the symbolic parameter comprising the term type; and performing the symbolic execution of the function using one or more solutions of the domain of possible solutions to generate a set of one or more actual solutions. | 8. One or more nonvolatile computer-readable storage media containing instructions which, when executed by a computer, cause the computer to perform a method, the method comprising: passing a symbolic parameter to a function of a program in a symbolic state representation of a program, the symbolic parameter comprising a symbolic sub-parameter that comprises a variable term; examining a set of value constraints for a pre-defined approximation of possible values associated with the symbolic parameter; as a result of not finding the pre-defined approximation of possible values in the set of value constraints, generating a domain of possible solutions for the symbolic parameter, the generating comprising: determining properties of the symbolic parameter, the properties of the symbolic parameter comprising a term type; determining possible values for the variable term, the determining the possible values for the variable term comprises walking over field maps of a representation of a given state and extracting one or more object terms appearing in the given state which match a type of the variable term; and selecting and applying one or more of a plurality of domain computation techniques according to the properties of the symbolic parameter comprising the term type; and performing the symbolic execution of the function using one or more solutions of the domain of possible solutions to generate a set of one or more actual solutions. 9. The one or more nonvolatile computer-readable storage media of claim 8 , wherein the symbolic parameter further comprises an operator. | 0.639474 |
7,583,845 | 1 | 3 | 1. An associative vector storage system, comprising: an encoding engine that takes input vectors, and generates transformed coefficients for a tunable number of iterations, wherein each iteration performs a complete transformation to obtain coefficients, thereby performing a process of iterative transformations, wherein said encoding engine selects a subset of coefficients from the coefficients generated by the process of iterative transformations to form an approximation vector with reduced dimension; a data store that stores the approximation vectors with a corresponding set of meta data containing information about how the approximation vectors are generated, wherein the meta data includes at least one of the number of iterations, a projection map, quantization, or statistical information associated with each approximation vector; and a search engine that uses a comparator module to perform similarity search between the approximation vectors and a query vector in a transformed domain, wherein said search engine uses the meta data in a distance calculation of the similarity search. | 1. An associative vector storage system, comprising: an encoding engine that takes input vectors, and generates transformed coefficients for a tunable number of iterations, wherein each iteration performs a complete transformation to obtain coefficients, thereby performing a process of iterative transformations, wherein said encoding engine selects a subset of coefficients from the coefficients generated by the process of iterative transformations to form an approximation vector with reduced dimension; a data store that stores the approximation vectors with a corresponding set of meta data containing information about how the approximation vectors are generated, wherein the meta data includes at least one of the number of iterations, a projection map, quantization, or statistical information associated with each approximation vector; and a search engine that uses a comparator module to perform similarity search between the approximation vectors and a query vector in a transformed domain, wherein said search engine uses the meta data in a distance calculation of the similarity search. 3. The system of claim 1 , wherein said search engine monitors standard deviations for each iteration in order to decide whether additional iteration can provide convergence of the standard deviation of the approximation vector to a threshold value. | 0.625 |
7,774,349 | 1 | 16 | 1. A system that facilitates generation of a system profile, comprising: a storage component that receives data relating to respective existing profiles of a community of disparate users, the existing profiles are generated by a plurality of client computers and represent application configuration settings used by the respective users of the client computers; an analyzer that processes the existing profile data for the community of users in view of demographic data of a first user and selects a subset of the existing profiles to present to the first user based on similarities between the first user and the respective users in the community; a filter component that applies collaborative filtering in accordance with the analyzer to process previous system settings preferences of existing users in the community to predict likely or possible settings or profiles for new users of a system, the filter component identifies software settings or preferences about context-sensitive computing that are applicable to an application employed by the first user; and a user interface that displays the subset of existing profiles selected by the analyzer, the user interface having at least one input to select from the displayed subset of profiles, the selected profile is used to configure the application settings for the first user; wherein the profiles include user definitions of a cost of interruption associated with each of a set of activities defined in a communications application, and the filter component selects at least one of the profiles for presentation to the first user based on a calculated similarity between the cost of interruption definitions in the existing profiles and the first user's cost of interruption definitions, wherein selection of the at least one profile by the first user applies the configuration settings defined in the selected profile to the communications application employed by the first user. | 1. A system that facilitates generation of a system profile, comprising: a storage component that receives data relating to respective existing profiles of a community of disparate users, the existing profiles are generated by a plurality of client computers and represent application configuration settings used by the respective users of the client computers; an analyzer that processes the existing profile data for the community of users in view of demographic data of a first user and selects a subset of the existing profiles to present to the first user based on similarities between the first user and the respective users in the community; a filter component that applies collaborative filtering in accordance with the analyzer to process previous system settings preferences of existing users in the community to predict likely or possible settings or profiles for new users of a system, the filter component identifies software settings or preferences about context-sensitive computing that are applicable to an application employed by the first user; and a user interface that displays the subset of existing profiles selected by the analyzer, the user interface having at least one input to select from the displayed subset of profiles, the selected profile is used to configure the application settings for the first user; wherein the profiles include user definitions of a cost of interruption associated with each of a set of activities defined in a communications application, and the filter component selects at least one of the profiles for presentation to the first user based on a calculated similarity between the cost of interruption definitions in the existing profiles and the first user's cost of interruption definitions, wherein selection of the at least one profile by the first user applies the configuration settings defined in the selected profile to the communications application employed by the first user. 16. A computer readable medium having computer readable instructions stored thereon for implementing the components of claim 1 . | 0.817664 |
8,612,233 | 1 | 10 | 1. A method for conducting an expert conversation, the method comprising: constructing a knowledge database comprising a dialogue repository comprising a plurality of dialogues, each dialogue representing a framework for creating at least one expert conversation and comprising a plurality of nodes and a plurality of edges extending between pairs of nodes; and using the dialogue repository in combination with a runtime dialogue system executing on a computing system and in communication with the knowledge database to conduct the expert conversation between the runtime dialogue system and a user based on a given dialogue selected from the plurality of dialogues by presenting comments and questions derived from nodes in the given dialogue to the user, inputting data from the user in response to the presented comments and questions and identifying appropriate edges at each node based on the inputted data, wherein the expert conversation comprises a directed acyclic graph constructed from the nodes and edges of the selected dialogue. | 1. A method for conducting an expert conversation, the method comprising: constructing a knowledge database comprising a dialogue repository comprising a plurality of dialogues, each dialogue representing a framework for creating at least one expert conversation and comprising a plurality of nodes and a plurality of edges extending between pairs of nodes; and using the dialogue repository in combination with a runtime dialogue system executing on a computing system and in communication with the knowledge database to conduct the expert conversation between the runtime dialogue system and a user based on a given dialogue selected from the plurality of dialogues by presenting comments and questions derived from nodes in the given dialogue to the user, inputting data from the user in response to the presented comments and questions and identifying appropriate edges at each node based on the inputted data, wherein the expert conversation comprises a directed acyclic graph constructed from the nodes and edges of the selected dialogue. 10. The method of claim 1 , wherein the step of constructing the knowledge database further comprises using a plurality of authors to collaboratively author the plurality of dialogues. | 0.823755 |
9,692,865 | 12 | 16 | 12. A method of controlling a mobile terminal having a display and a controller, the method comprising: activating, via the controller, a mode for voice recognition in response to a touch input to a soft button displayed on the display or to a hard button on the mobile terminal; receiving, via the controller, a first voice input associated with an executable menu relating operation of the mobile terminal; displaying, via the controller, an indicator on the display indicating the first voice input is being recognized by the mobile terminal; determining, via the controller, a meaning of a voice command in the first voice input based on information stored in the at least one database (DB); displaying, via the controller, information corresponding to the determined meaning; receiving, via the controller, a second voice input associated with a user's confirmation about the displayed information; if the received second voice input matches an affirmative received response, executing, via the controller a menu relating operation corresponding to the displayed information; if the received second voice input matches a negative received response, performing, via the controller, a learning process based on a third voice input for learning the meaning of the voice command in the first voice input and executing a menu relating operation corresponding to the learned meaning; and updating, via the controller, the at least one database (DB) to store the learned meaning according to the third voice input. | 12. A method of controlling a mobile terminal having a display and a controller, the method comprising: activating, via the controller, a mode for voice recognition in response to a touch input to a soft button displayed on the display or to a hard button on the mobile terminal; receiving, via the controller, a first voice input associated with an executable menu relating operation of the mobile terminal; displaying, via the controller, an indicator on the display indicating the first voice input is being recognized by the mobile terminal; determining, via the controller, a meaning of a voice command in the first voice input based on information stored in the at least one database (DB); displaying, via the controller, information corresponding to the determined meaning; receiving, via the controller, a second voice input associated with a user's confirmation about the displayed information; if the received second voice input matches an affirmative received response, executing, via the controller a menu relating operation corresponding to the displayed information; if the received second voice input matches a negative received response, performing, via the controller, a learning process based on a third voice input for learning the meaning of the voice command in the first voice input and executing a menu relating operation corresponding to the learned meaning; and updating, via the controller, the at least one database (DB) to store the learned meaning according to the third voice input. 16. The method of claim 12 , further comprising: updating a recognition rate for the first voice input based on the second voice input. | 0.865805 |
9,916,365 | 1 | 2 | 1. A computer-implemented method for linking documents that refer to other documents through implicit linkages, the method comprising: identifying a first document, the first document comprising an authoritative comment regarding a second document; establishing an explicit linkage between the first document and the second document based upon the authoritative comment; identifying one or more third documents based upon the existence of a citation relationship between the second document and each of the one or more third documents detecting an implicit relationship between the first document and the one or more third documents by using common information between the second document and the one or more third documents; generating an impact value for each of the one or more third documents by comparing the implicit relationship with the first document to the explicit relationship with the second document, the impact value being an indicator of the implicit relationship between the first document and each of the one or more third documents; linking the first document to the one or more third documents based upon the impact value; and presenting the one or more third documents in response to a query for the first document. | 1. A computer-implemented method for linking documents that refer to other documents through implicit linkages, the method comprising: identifying a first document, the first document comprising an authoritative comment regarding a second document; establishing an explicit linkage between the first document and the second document based upon the authoritative comment; identifying one or more third documents based upon the existence of a citation relationship between the second document and each of the one or more third documents detecting an implicit relationship between the first document and the one or more third documents by using common information between the second document and the one or more third documents; generating an impact value for each of the one or more third documents by comparing the implicit relationship with the first document to the explicit relationship with the second document, the impact value being an indicator of the implicit relationship between the first document and each of the one or more third documents; linking the first document to the one or more third documents based upon the impact value; and presenting the one or more third documents in response to a query for the first document. 2. The computer-implemented method of claim 1 , wherein the generation of the impact value is based on metadata and semantic text analysis. | 0.682648 |
8,892,420 | 1 | 2 | 1. A method of text processing, comprising: training, using a processor, a classifier for classifying text, wherein: the training is based on a plurality of training sample entries; a training sample entry in the plurality of training sample entries includes: a character count; an independent use rate; a phrase structure rule value indicating whether the training sample entry complies with phrase structure rules; a semantic attribute value indicating an inclusion state of the training sample entry in a predetermined set of enumerated entries; an overlap attribute value indicating overlap of the training sample entry with another entry in the predetermined set of enumerated entries; and a classification result indicating whether the training sample entry is a compound semantic unit or a smallest semantic unit; building, using the processor, a lexicon of smallest semantic units, comprising: receiving an entry to be classified; using the trained classifier to determine whether the entry to be classified is a smallest semantic unit or a compound semantic unit; and in the event that the entry is determined to be a smallest semantic unit, adding the entry to the lexicon of smallest semantic units; segmenting, using the processor, received text based on the lexicon of smallest semantic units to obtain medium-grained segmentation results; merging, using the processor, the medium-grained segmentation results to obtain coarse-grained segmentation results, the coarse-grained segmentation results having coarser granularity than the medium-grained segmentation results; looking up, using the processor, in the lexicon of smallest semantic units respective search elements that correspond to segments in the medium-grained segmentation results; and forming, using the processor, fine-grained segmentation results based on the respective search elements, the fine-grained segmentation results having finer granularity than the medium-grained segmentation results. | 1. A method of text processing, comprising: training, using a processor, a classifier for classifying text, wherein: the training is based on a plurality of training sample entries; a training sample entry in the plurality of training sample entries includes: a character count; an independent use rate; a phrase structure rule value indicating whether the training sample entry complies with phrase structure rules; a semantic attribute value indicating an inclusion state of the training sample entry in a predetermined set of enumerated entries; an overlap attribute value indicating overlap of the training sample entry with another entry in the predetermined set of enumerated entries; and a classification result indicating whether the training sample entry is a compound semantic unit or a smallest semantic unit; building, using the processor, a lexicon of smallest semantic units, comprising: receiving an entry to be classified; using the trained classifier to determine whether the entry to be classified is a smallest semantic unit or a compound semantic unit; and in the event that the entry is determined to be a smallest semantic unit, adding the entry to the lexicon of smallest semantic units; segmenting, using the processor, received text based on the lexicon of smallest semantic units to obtain medium-grained segmentation results; merging, using the processor, the medium-grained segmentation results to obtain coarse-grained segmentation results, the coarse-grained segmentation results having coarser granularity than the medium-grained segmentation results; looking up, using the processor, in the lexicon of smallest semantic units respective search elements that correspond to segments in the medium-grained segmentation results; and forming, using the processor, fine-grained segmentation results based on the respective search elements, the fine-grained segmentation results having finer granularity than the medium-grained segmentation results. 2. The method of claim 1 , wherein the received text is in a non-divider marked language. | 0.914423 |
8,423,349 | 5 | 8 | 5. One or more computer-readable media storing computer-executable instructions that, when executed on one or more processors, perform acts comprising: generating a first corpus of phrases each comprising at least two grammatically-correct words; filtering the first corpus of phrases to define a second corpus of phrases, wherein the filtering the first corpus of phrases comprises: determining a commonality of words of the multiple phrases of the first corpus of phrases; and filtering out phrases of the first corpus of phrases to define a second corpus of phrases based at least in part on the determined commonality of the words of the multiple phrases; outputting phrases of the second corpus of phrases to each of multiple users; receiving selections of phrases from each of the multiple users; and responsive to the receiving of the selection, associating a selected phrase with each respective user of the multiple users. | 5. One or more computer-readable media storing computer-executable instructions that, when executed on one or more processors, perform acts comprising: generating a first corpus of phrases each comprising at least two grammatically-correct words; filtering the first corpus of phrases to define a second corpus of phrases, wherein the filtering the first corpus of phrases comprises: determining a commonality of words of the multiple phrases of the first corpus of phrases; and filtering out phrases of the first corpus of phrases to define a second corpus of phrases based at least in part on the determined commonality of the words of the multiple phrases; outputting phrases of the second corpus of phrases to each of multiple users; receiving selections of phrases from each of the multiple users; and responsive to the receiving of the selection, associating a selected phrase with each respective user of the multiple users. 8. One or more computer-readable media as recited in claim 5 , wherein the filtering of the first corpus of phrases further comprises: comparing words of phrases of the first corpus of phrases to a list of words; and removing phrases of the first corpus of phrases that have words that do not appear on the list of words. | 0.713393 |
7,549,052 | 1 | 2 | 1. A method to match a hash value representing an unidentified information signal with a plurality of hash values stored in a database and to identify a respective one of a plurality of information signals, the method comprising: receiving said hash value in the form of a plurality of reliable hash bits and unreliable hash bits; searching in the database the stored hash values for which holds that the reliable bits of the applied hash value match the corresponding bits of the stored hash value while ignoring unreliable bits of the applied hash value and corresponding bits of the stored hash value; for each stored hash value found in response to the searching, calculating the bit error rate between the reliable bits of the hash value representing the unidentified information signal and the corresponding bits of the stored hash value; determining for which stored hash values the bit error rate is minimal; and returning an identification of the respective one of the plurality of information signals that corresponds to the minimal bit error rate. | 1. A method to match a hash value representing an unidentified information signal with a plurality of hash values stored in a database and to identify a respective one of a plurality of information signals, the method comprising: receiving said hash value in the form of a plurality of reliable hash bits and unreliable hash bits; searching in the database the stored hash values for which holds that the reliable bits of the applied hash value match the corresponding bits of the stored hash value while ignoring unreliable bits of the applied hash value and corresponding bits of the stored hash value; for each stored hash value found in response to the searching, calculating the bit error rate between the reliable bits of the hash value representing the unidentified information signal and the corresponding bits of the stored hash value; determining for which stored hash values the bit error rate is minimal; and returning an identification of the respective one of the plurality of information signals that corresponds to the minimal bit error rate. 2. The method of claim 1 , further comprising generating the hash value, the generating of the hash value comprising: dividing the unidentified information signal into frames; computing a hash word for each frame; and concatenating successive hash words to constitute the hash value. | 0.5 |
7,895,275 | 2 | 3 | 2. The computer-implemented method of claim 1 wherein effecting review of the digital content comprises: a) selecting a group of reviewers from the others of the plurality of authors for a review at a first quality level that is less than the target quality level based on the reviewer credentials; b) effecting transfer of the digital content to user devices associated with the group of reviewers; c) receiving feedback from the group of reviewers; d) determining whether the digital content is to be reviewed at a next quality level based on the feedback and the target quality level; and e) if the digital content is to be reviewed at the next quality level, repeating steps a)-e) for the next quality level. | 2. The computer-implemented method of claim 1 wherein effecting review of the digital content comprises: a) selecting a group of reviewers from the others of the plurality of authors for a review at a first quality level that is less than the target quality level based on the reviewer credentials; b) effecting transfer of the digital content to user devices associated with the group of reviewers; c) receiving feedback from the group of reviewers; d) determining whether the digital content is to be reviewed at a next quality level based on the feedback and the target quality level; and e) if the digital content is to be reviewed at the next quality level, repeating steps a)-e) for the next quality level. 3. The computer-implemented method of claim 2 wherein determining whether the digital content is to be reviewed at the next quality level comprises determining whether the digital content is rated at or above a current quality level based on the feedback from the group of reviewers and whether the current quality level is less than the target quality level. | 0.676577 |
8,140,326 | 7 | 8 | 7. The method of claim 1 , further comprising identifying syllables within the vocalic region before computing the vocal tract transfer function. | 7. The method of claim 1 , further comprising identifying syllables within the vocalic region before computing the vocal tract transfer function. 8. The method of claim 7 , further comprising identifying the syllables within each vocalic region by identifying voiced segments and identifying syllable boundaries. | 0.5 |
9,318,027 | 1 | 6 | 1. A method, in a data processing system comprising a processor and a memory, for answering an input question, the method comprising: receiving, in the data processing system, an input question to be answered from a source; processing, by the data processing system, the input question to extract one or more features of the input question; comparing, by the data processing system, the extracted one or more features to cached features stored in one or more entries of a question and answer (QA) cache of the data processing system; determining, by the data processing system, whether there is a matching entry in the one or more entries of the QA cache based on results of the comparing, wherein determining whether there is a matching entry in the one or more entries of the QA cache comprises: generating, for each entry in the QA cache, a match value indicative of a degree of matching between the one or more extracted features of the input question to cached features of the entry in the QA cache; and comparing the match value to one or more threshold values indicating one or more requisite degrees of similarity between the input question and an entry in the QA cache, wherein: in response to the match value equaling or exceeding a first threshold value, a corresponding entry is determined to match the input question, and in response to the match value being less than the first threshold value but the match value being equal to or greater than a second threshold value, determining that the corresponding entry is sufficiently similar for updating the corresponding entry with the one or more extracted features of the input question; retrieving, by the data processing system, in response to a matching entry being present in the one or more entries of the QA cache, candidate answer information from the matching entry; and returning, by the data processing system, the retrieved candidate answer information to the source of the input question as candidate answer information for answering the input question. | 1. A method, in a data processing system comprising a processor and a memory, for answering an input question, the method comprising: receiving, in the data processing system, an input question to be answered from a source; processing, by the data processing system, the input question to extract one or more features of the input question; comparing, by the data processing system, the extracted one or more features to cached features stored in one or more entries of a question and answer (QA) cache of the data processing system; determining, by the data processing system, whether there is a matching entry in the one or more entries of the QA cache based on results of the comparing, wherein determining whether there is a matching entry in the one or more entries of the QA cache comprises: generating, for each entry in the QA cache, a match value indicative of a degree of matching between the one or more extracted features of the input question to cached features of the entry in the QA cache; and comparing the match value to one or more threshold values indicating one or more requisite degrees of similarity between the input question and an entry in the QA cache, wherein: in response to the match value equaling or exceeding a first threshold value, a corresponding entry is determined to match the input question, and in response to the match value being less than the first threshold value but the match value being equal to or greater than a second threshold value, determining that the corresponding entry is sufficiently similar for updating the corresponding entry with the one or more extracted features of the input question; retrieving, by the data processing system, in response to a matching entry being present in the one or more entries of the QA cache, candidate answer information from the matching entry; and returning, by the data processing system, the retrieved candidate answer information to the source of the input question as candidate answer information for answering the input question. 6. The method of claim 1 , wherein, in response to determining that there is not a matching entry in the one or more entries of the QA cache: determining if there is a subset of entries in the one or more entries that is similar to the input question; and outputting a listing of the subset of entries to a user for user selection of an entry in the subset of entries to be retrieved and used to generate candidate answers for the input question. | 0.5 |
8,631,385 | 5 | 7 | 5. A computer program product comprising a computer readable storage medium having a computer readable program code embodied therein, said storage medium not comprising a signal, said computer readable program code containing instructions configured to be executed by a processor of a computer system to implement a method for a code generation system, said method comprising: said processor parsing the input code into data items of program code and data items of at least one code generating instruction, said input code comprising the program code and a set of comments in the programming language of the program code such that the set of comments includes the at least one code generating instruction; said processor generating a model comprising the parsed data items of the program code such that the generated model represents all parameters in the program code; said processor generating a template as a result of applying said at least one code generation instruction to the parsed data items of the program code such that the template comprises a respective variable that holds a respective instance of the generated model for each parameter in the program code; said processor obtaining a code generator as a result of running a template engine of the code generation system using the generated template, wherein said code generator comprises at least one definition of a respective string and at least one procedure; said processor creating an output code of the code generation system as a result of running the obtained code generator using the at least one procedure, the at least one definition of the respective string, and a respective instance of the generated model, wherein the output code comprises parameters in the generated model; and said processor forwarding the created output code to at least one output device. | 5. A computer program product comprising a computer readable storage medium having a computer readable program code embodied therein, said storage medium not comprising a signal, said computer readable program code containing instructions configured to be executed by a processor of a computer system to implement a method for a code generation system, said method comprising: said processor parsing the input code into data items of program code and data items of at least one code generating instruction, said input code comprising the program code and a set of comments in the programming language of the program code such that the set of comments includes the at least one code generating instruction; said processor generating a model comprising the parsed data items of the program code such that the generated model represents all parameters in the program code; said processor generating a template as a result of applying said at least one code generation instruction to the parsed data items of the program code such that the template comprises a respective variable that holds a respective instance of the generated model for each parameter in the program code; said processor obtaining a code generator as a result of running a template engine of the code generation system using the generated template, wherein said code generator comprises at least one definition of a respective string and at least one procedure; said processor creating an output code of the code generation system as a result of running the obtained code generator using the at least one procedure, the at least one definition of the respective string, and a respective instance of the generated model, wherein the output code comprises parameters in the generated model; and said processor forwarding the created output code to at least one output device. 7. The computer program product of claim 5 , wherein the programming language of the program code accommodates comments in the syntax of the programming language such that said at least code generating instruction is embedded in said comments of the programming language. | 0.647135 |
9,979,777 | 1 | 6 | 1. A method comprising: determining, using one or more processors, an inferred interest for a first user; generating, using the one or more processors, a model based on the inferred interest of the first user and storing the model in a non-transitory storage medium; generating, using the one or more processors, a set of candidate content items using an item from a second user with a similarity to the first user; determining, using the one or more processors, a first attribute and a second attribute associated with a candidate content item in the set of candidate content items; determining, using the one or more processors, a first score associated with the first attribute for the candidate content item based on the model of the first user and a first number of candidate content items having the first attribute in the set of candidate content items; determining, using the one or more processors, a second score associated with the second attribute for the candidate content item based on the model of the first user and a second number of candidate content items having the second attribute in the set of candidate content items; computing, using the one or more processors, a third score for the candidate content item in the set of candidate content items by summing the first score associated with the first attribute and the second score associated with the second attribute; selecting, using the one or more processors, content items for a stream of content associated with the first user from the set of candidate content items based on the third score of the content items; generating, using the one or more processors, an explanation for a first content item in the selected content items, the explanation indicating a reason for presenting the first content item to the first user; and transmitting, using the one or more processors, an instruction to a device that causes the device to present for display the stream of content to the first user with the explanation alongside the first content item, the explanation including a selectable graphic element for the first user to access an expanded explanation. | 1. A method comprising: determining, using one or more processors, an inferred interest for a first user; generating, using the one or more processors, a model based on the inferred interest of the first user and storing the model in a non-transitory storage medium; generating, using the one or more processors, a set of candidate content items using an item from a second user with a similarity to the first user; determining, using the one or more processors, a first attribute and a second attribute associated with a candidate content item in the set of candidate content items; determining, using the one or more processors, a first score associated with the first attribute for the candidate content item based on the model of the first user and a first number of candidate content items having the first attribute in the set of candidate content items; determining, using the one or more processors, a second score associated with the second attribute for the candidate content item based on the model of the first user and a second number of candidate content items having the second attribute in the set of candidate content items; computing, using the one or more processors, a third score for the candidate content item in the set of candidate content items by summing the first score associated with the first attribute and the second score associated with the second attribute; selecting, using the one or more processors, content items for a stream of content associated with the first user from the set of candidate content items based on the third score of the content items; generating, using the one or more processors, an explanation for a first content item in the selected content items, the explanation indicating a reason for presenting the first content item to the first user; and transmitting, using the one or more processors, an instruction to a device that causes the device to present for display the stream of content to the first user with the explanation alongside the first content item, the explanation including a selectable graphic element for the first user to access an expanded explanation. 6. The method of claim 1 , wherein the model is generated based on a prior action from a group of heterogeneous data sources, the heterogeneous data sources including at least one of a log of activities on a social network, a search history, a blog post, a news article, a news feed, a video, a map, a message, an email message, an instant message, a microblog, a text-based post, a phone call and an activity on site. | 0.5 |
9,286,061 | 15 | 16 | 15. The computing device according to claim 14 , further comprising a monitoring agent, maintained on the at least one memory and executed on the at least one processor, to cause the computing device to: monitor outbound messages sent by the launched external component to the external computing device; and capture at least one outbound message sent from the launched external component to the external computing device for insertion into the document following triggering of the at least one outbound message by a user interacting with the launched external component. | 15. The computing device according to claim 14 , further comprising a monitoring agent, maintained on the at least one memory and executed on the at least one processor, to cause the computing device to: monitor outbound messages sent by the launched external component to the external computing device; and capture at least one outbound message sent from the launched external component to the external computing device for insertion into the document following triggering of the at least one outbound message by a user interacting with the launched external component. 16. The computing device according to claim 15 , wherein: the at least one outbound message is parsed for relevant information and a corresponding structured data message is placed into a message queue; and the structured data message is rendered in the document by a rendering engine executed on the at least one processor. | 0.5 |
9,623,119 | 1 | 2 | 1. A computer-implemented method, comprising: receiving documents responsive to a query, each document having a respective associated score indicative of the document's relevance to the query, wherein: each respective associated score is based on a respective value for each of a plurality of different score factors; each score factor for a given associated score corresponds to a different criterion than each other score factor for the given associated score; and each score factor has a respective trustworthiness score that indicates a respective reliability of values determined based on the score factor; determining, based on the trustworthiness scores for the score factors of a plurality of the associated scores of a plurality of different documents, a value-based distribution of the trustworthiness scores for each of the different score factors of the plurality of associated scores along a dimension based on relative values of the trustworthiness scores, the distribution including trustworthiness scores for multiple score factors for each of the different documents; adjusting the value of at least one score factor of a given associated score by an amount that is determined based on: a relative position of the at least one score factor's respective trustworthiness score in the distribution with respect to other trustworthiness scores in the distribution; and a measure of how widely the trustworthiness scores for each of the different score factors of the plurality of associated scores are distributed in the distribution; adjusting the given associated score based on the adjusted value of the at least one score factor; and ranking the documents to account for the adjusted associated score. | 1. A computer-implemented method, comprising: receiving documents responsive to a query, each document having a respective associated score indicative of the document's relevance to the query, wherein: each respective associated score is based on a respective value for each of a plurality of different score factors; each score factor for a given associated score corresponds to a different criterion than each other score factor for the given associated score; and each score factor has a respective trustworthiness score that indicates a respective reliability of values determined based on the score factor; determining, based on the trustworthiness scores for the score factors of a plurality of the associated scores of a plurality of different documents, a value-based distribution of the trustworthiness scores for each of the different score factors of the plurality of associated scores along a dimension based on relative values of the trustworthiness scores, the distribution including trustworthiness scores for multiple score factors for each of the different documents; adjusting the value of at least one score factor of a given associated score by an amount that is determined based on: a relative position of the at least one score factor's respective trustworthiness score in the distribution with respect to other trustworthiness scores in the distribution; and a measure of how widely the trustworthiness scores for each of the different score factors of the plurality of associated scores are distributed in the distribution; adjusting the given associated score based on the adjusted value of the at least one score factor; and ranking the documents to account for the adjusted associated score. 2. The method of claim 1 , wherein the distribution is a frequency distribution and wherein the amount is determined based on a distance between a lowest and a highest trustworthiness score in the distribution and the at least one score factor's trustworthiness score. | 0.751852 |
6,064,820 | 13 | 14 | 13. An article of manufacture comprising a program storage medium having computer readable program code embodied therein for optimizing a source program for execution on a computer, the computer readable program code including computer readable program code for representing a source program having at least one loop, and at least one instruction having at least one variable, by a graph including a plurality of nodes, each node including at least one of the instructions, the article of manufacture comprising: computer readable program code for including definition instructions, that establishes at least one original name variable, at least one cloned name variable, or at least one incarnation name variable; computer readable program code for including use instructions that include use of the original name, use of the cloned name, or use of the incarnation name; computer readable program code for maintaining correspondence between the cloned name and the original name; computer readable program code for including a set of at least one first instruction that identifies nodes having the definition instructions and the identified nodes are inside of the loop; computer readable program code for including a set of at least one second instruction that identifies nodes having the use instructions and the identified nodes are outside of the loop; computer readable program code for including a set of at least one tail node; computer readable program code for including a set of at least one third instruction having the original names that are in both the first instruction set and the second instruction set; wherein, for each tail node in the set of tail nodes: wherein, when the original name is in the tail node and the third instruction set, computer readable program code for inserting in the tail node a cloned definition instruction that establishes the cloned name by the correspondence to the original name; and wherein, for all the use instructions in the second instruction set, when the original name is used, and when the cloned name is established in the cloned definition instruction, computer readable program code for replacing the original name with the corresponding cloned name; and computer readable program code for generating an executable module from the graph for execution on the computer thereby optimizing the source program with the cloned name. | 13. An article of manufacture comprising a program storage medium having computer readable program code embodied therein for optimizing a source program for execution on a computer, the computer readable program code including computer readable program code for representing a source program having at least one loop, and at least one instruction having at least one variable, by a graph including a plurality of nodes, each node including at least one of the instructions, the article of manufacture comprising: computer readable program code for including definition instructions, that establishes at least one original name variable, at least one cloned name variable, or at least one incarnation name variable; computer readable program code for including use instructions that include use of the original name, use of the cloned name, or use of the incarnation name; computer readable program code for maintaining correspondence between the cloned name and the original name; computer readable program code for including a set of at least one first instruction that identifies nodes having the definition instructions and the identified nodes are inside of the loop; computer readable program code for including a set of at least one second instruction that identifies nodes having the use instructions and the identified nodes are outside of the loop; computer readable program code for including a set of at least one tail node; computer readable program code for including a set of at least one third instruction having the original names that are in both the first instruction set and the second instruction set; wherein, for each tail node in the set of tail nodes: wherein, when the original name is in the tail node and the third instruction set, computer readable program code for inserting in the tail node a cloned definition instruction that establishes the cloned name by the correspondence to the original name; and wherein, for all the use instructions in the second instruction set, when the original name is used, and when the cloned name is established in the cloned definition instruction, computer readable program code for replacing the original name with the corresponding cloned name; and computer readable program code for generating an executable module from the graph for execution on the computer thereby optimizing the source program with the cloned name. 14. The article of manufacture as set forth in claim 13, further comprising: computer readable program code for each tail node in the set of tail nodes and that when the loop is unrolled, further including: computer readable program code for including a first variable that represents the number of times the loop is unrolled; computer readable program code for maintaining correspondence between the incarnation name and the cloned name; wherein, for each time the loop is unrolled: computer readable program code for setting the first variable to the number of times the loop has been unrolled; and computer readable program code for including at least one second variable by inserting the first variable and the incarnation name into the second variable to maintain correspondence between the incarnation name and the first variable; and computer readable program code for merging the second variables into the corresponding cloned name thereby optimizing the source program with the cloned name when the loop is unrolled. | 0.761295 |
9,529,604 | 2 | 3 | 2. The method according to claim 1 , wherein the storing a microblog message includes storing the microblog message in a way of a microblog message content list and the method further comprises identifying the microblog message content list with a user ID; the scanning the stored microblog message and obtaining the one or more keyword(s) of the microblog message according to the preset extracting policy comprises: scanning the microblog message content list at regular time, and extracting the one or more keyword(s) comprised in the microblog message content list according to the preset extracting policy. | 2. The method according to claim 1 , wherein the storing a microblog message includes storing the microblog message in a way of a microblog message content list and the method further comprises identifying the microblog message content list with a user ID; the scanning the stored microblog message and obtaining the one or more keyword(s) of the microblog message according to the preset extracting policy comprises: scanning the microblog message content list at regular time, and extracting the one or more keyword(s) comprised in the microblog message content list according to the preset extracting policy. 3. The method according to claim 2 , wherein the extracting the one or more keyword(s) comprised in the microblog message content list according to the preset extracting policy comprises: matching the microblog message content list with preset keyword lists corresponding to various application scenes, and obtaining the one or more keyword(s), which matches the preset keyword lists corresponding to various application scenes, from the microblog message content list. | 0.5 |
9,431,003 | 10 | 18 | 10. A computer program product for imbuing an artificial intelligence system with idiomatic traits, the computer program product comprising a tangible computer readable storage medium having program code embodied therewith, wherein the program code is readable and executable by a processor to perform a method comprising: collecting electronic units of speech from an electronic stream of speech, wherein the electronic stream of speech is generated by a first entity; identifying tokens from the electronic stream of speech, wherein each token identifies a particular electronic unit of speech from the electronic stream of speech, and wherein identification of the tokens is semantic-free such that the tokens are identified independently of a semantic meaning of a respective electronic unit of speech; populating nodes in a first speech graph with the tokens; identifying a first shape of the first speech graph; matching the first shape to a second shape, wherein the second shape is of a second speech graph from a second entity in a known category; assigning the first entity to the known category in response to the first shape matching the second shape; and modifying synthetic speech generated by an artificial intelligence system based on the first entity being assigned to the known category, wherein said modifying imbues the artificial intelligence system with idiomatic traits of persons in the known category. | 10. A computer program product for imbuing an artificial intelligence system with idiomatic traits, the computer program product comprising a tangible computer readable storage medium having program code embodied therewith, wherein the program code is readable and executable by a processor to perform a method comprising: collecting electronic units of speech from an electronic stream of speech, wherein the electronic stream of speech is generated by a first entity; identifying tokens from the electronic stream of speech, wherein each token identifies a particular electronic unit of speech from the electronic stream of speech, and wherein identification of the tokens is semantic-free such that the tokens are identified independently of a semantic meaning of a respective electronic unit of speech; populating nodes in a first speech graph with the tokens; identifying a first shape of the first speech graph; matching the first shape to a second shape, wherein the second shape is of a second speech graph from a second entity in a known category; assigning the first entity to the known category in response to the first shape matching the second shape; and modifying synthetic speech generated by an artificial intelligence system based on the first entity being assigned to the known category, wherein said modifying imbues the artificial intelligence system with idiomatic traits of persons in the known category. 18. The computer program product of claim 10 , wherein the known category is for a group having a common level of education. | 0.9634 |
10,146,939 | 16 | 17 | 16. The non-transitory computer-readable medium of claim 15 , wherein the anomaly detection score is determined by applying a content anomaly detection model to the received input dataset. | 16. The non-transitory computer-readable medium of claim 15 , wherein the anomaly detection score is determined by applying a content anomaly detection model to the received input dataset. 17. The non-transitory computer-readable medium of claim 16 , wherein the content anomaly detection model is a frequency distribution-based detection model that determines a plurality of appearance frequencies, and wherein each of the plurality of appearance frequencies corresponds to one of the training n-grams. | 0.5 |
8,812,320 | 17 | 18 | 17. A non-transitory computer-readable medium storing software comprising instructions executable by one or more computers which, upon such execution, cause the one or more computers to perform operations comprising: receiving a request for a verification phrase for verifying an identity of a user; in response to receiving the request for the verification phrase for verifying the identity of the user, identifying subwords to be included in the verification phrase; in response to identifying the subwords to be included in the verification phrase, obtaining a candidate phrase that includes at least some of the identified subwords as the verification phrase; and providing the verification phrase as a response to the request for the verification phrase for verifying the identity of the user. | 17. A non-transitory computer-readable medium storing software comprising instructions executable by one or more computers which, upon such execution, cause the one or more computers to perform operations comprising: receiving a request for a verification phrase for verifying an identity of a user; in response to receiving the request for the verification phrase for verifying the identity of the user, identifying subwords to be included in the verification phrase; in response to identifying the subwords to be included in the verification phrase, obtaining a candidate phrase that includes at least some of the identified subwords as the verification phrase; and providing the verification phrase as a response to the request for the verification phrase for verifying the identity of the user. 18. The medium of claim 17 , wherein identifying subwords to be included in the verification phrase comprises: identifying candidate subwords, for which stored acoustic data is associated with the user, as one or more of the subwords to be included in the verification phrase. | 0.783019 |
8,234,263 | 32 | 40 | 32. The computer program product of claim 29 , wherein characteristics of the taxonomic nouns include at least one of a term type, a flag, a document count, and an occurrence count. | 32. The computer program product of claim 29 , wherein characteristics of the taxonomic nouns include at least one of a term type, a flag, a document count, and an occurrence count. 40. The computer program product of claim 32 , wherein the term type includes a topic name, the topic name including a single term that represents a cluster of related terms. | 0.649194 |
9,015,803 | 33 | 37 | 33. An apparatus comprising: one or more non-transitory computer-readable storage devices comprising processor- executable instructions, the processor-executable instructions capable of causing one or more processors of a server computer system to perform the following method steps: establishing an account for each of a plurality of users, wherein each account is associated with storage space to store one or more documents; storing a first document in the server computer system in a first account, the first document capable of being modified by a plurality of authorized users; enabling access to the first document via a browser-controlled window executing on a client computer by one or more authorized users; associating a set of restrictions with the first document, the restrictions including an ability to modify the first document in one or more permitted ways by one of a first group of users, the first group of users being users whose identities are known to the server computer system; receiving a request to access the first document from a first user, wherein the first user is a member of the first group of users, wherein the request to access accompanies the first user's identification information and authorization information; verifying the identity of the first user; if the first user is authorized to access the first document, then permitting the first user to access the first document via a first browser-controlled window executing on a client computer; and if the first user is authorized to modify the first document, then: (a) applying one or more modifications to the first document, the one or more modifications having been received from the first user; (b) electronically notifying one or more of a second group of users that the first user modified the first document, the second group of users being users whose identities are known to the server computer system; and (c) enabling a second user to further modify the first document, wherein the second user is a member of the second group of users who are notified of the one or more modifications made by the first user to the first document, and wherein the second user is not the same as the first user. | 33. An apparatus comprising: one or more non-transitory computer-readable storage devices comprising processor- executable instructions, the processor-executable instructions capable of causing one or more processors of a server computer system to perform the following method steps: establishing an account for each of a plurality of users, wherein each account is associated with storage space to store one or more documents; storing a first document in the server computer system in a first account, the first document capable of being modified by a plurality of authorized users; enabling access to the first document via a browser-controlled window executing on a client computer by one or more authorized users; associating a set of restrictions with the first document, the restrictions including an ability to modify the first document in one or more permitted ways by one of a first group of users, the first group of users being users whose identities are known to the server computer system; receiving a request to access the first document from a first user, wherein the first user is a member of the first group of users, wherein the request to access accompanies the first user's identification information and authorization information; verifying the identity of the first user; if the first user is authorized to access the first document, then permitting the first user to access the first document via a first browser-controlled window executing on a client computer; and if the first user is authorized to modify the first document, then: (a) applying one or more modifications to the first document, the one or more modifications having been received from the first user; (b) electronically notifying one or more of a second group of users that the first user modified the first document, the second group of users being users whose identities are known to the server computer system; and (c) enabling a second user to further modify the first document, wherein the second user is a member of the second group of users who are notified of the one or more modifications made by the first user to the first document, and wherein the second user is not the same as the first user. 37. The apparatus of claim 33 , wherein the processor executable instructions include instructions to cause the server computer system to alter storage space to accommodate modifications made to the first document. | 0.880713 |
8,447,760 | 14 | 55 | 14. A system for identifying one or more second documents related to one or more documents of a set of first documents, the system comprising: one or more computers configured to perform operations comprising: determining a respective strength of relationship score between each candidate document in a group of candidate documents and each of the first documents by aggregating user selection data for multiple users, the first documents and the candidate documents being in a corpus of web documents, the user selection data indicating, for each of the multiple users, whether the user viewed the candidate document during a window of time after the first document is presented to the user on a search results web page in response to a query, wherein the strength of relationship score is a probability that the candidate document will be viewed given that the first document has been presented to a user on a search results web page in response to a query; calculating an aggregate strength of relationship score for each candidate document from the respective strength of relationship scores for the candidate document; and selecting the one or more second documents from the candidate documents according to the aggregate strength of relationship scores for the candidate documents. | 14. A system for identifying one or more second documents related to one or more documents of a set of first documents, the system comprising: one or more computers configured to perform operations comprising: determining a respective strength of relationship score between each candidate document in a group of candidate documents and each of the first documents by aggregating user selection data for multiple users, the first documents and the candidate documents being in a corpus of web documents, the user selection data indicating, for each of the multiple users, whether the user viewed the candidate document during a window of time after the first document is presented to the user on a search results web page in response to a query, wherein the strength of relationship score is a probability that the candidate document will be viewed given that the first document has been presented to a user on a search results web page in response to a query; calculating an aggregate strength of relationship score for each candidate document from the respective strength of relationship scores for the candidate document; and selecting the one or more second documents from the candidate documents according to the aggregate strength of relationship scores for the candidate documents. 55. The system of claim 14 wherein the respective strength of relationship score is a count of the users who viewed the candidate document during the window of time after the first document was presented divided by a count of the users who viewed the first document. | 0.755963 |
9,672,524 | 1 | 19 | 1. A system for organizing, managing, and reporting data relating to a corporate entity, comprising: at least one database configured to store a document record relating to a corporate action, the document record further comprising a core record reflecting human-readable information for incorporation into the generated document and stored with the document record, the document record further comprising a set of tags stored with the document record; a business logic module, coupled to the at least one database; and at least one document template stored in the at least one database and comprising instructions for generating, at the business logic module, a document based on the core record with an initial set of tags, wherein a first tag of the set of tags is in a text format and associates a human-readable document type with the document record, and wherein the at least one database is configured to store the document record with a hierarchically delimited child tag by storing the document record in association with both the hierarchically delimited child tag and additional tags that are hierarchically related as parent tags of the hierarchically delimited child tag, without requiring a user to request storage of both the child tag and the additional parent tags, thereby providing namespaced tagging and retrieval of document records. | 1. A system for organizing, managing, and reporting data relating to a corporate entity, comprising: at least one database configured to store a document record relating to a corporate action, the document record further comprising a core record reflecting human-readable information for incorporation into the generated document and stored with the document record, the document record further comprising a set of tags stored with the document record; a business logic module, coupled to the at least one database; and at least one document template stored in the at least one database and comprising instructions for generating, at the business logic module, a document based on the core record with an initial set of tags, wherein a first tag of the set of tags is in a text format and associates a human-readable document type with the document record, and wherein the at least one database is configured to store the document record with a hierarchically delimited child tag by storing the document record in association with both the hierarchically delimited child tag and additional tags that are hierarchically related as parent tags of the hierarchically delimited child tag, without requiring a user to request storage of both the child tag and the additional parent tags, thereby providing namespaced tagging and retrieval of document records. 19. The system of claim 1 , wherein the business logic module is configured to retrieve, for a given entity record, a prior-generated document storing a core record referenced by the given entity record and with an active status stored in a tag of the prior-generated document. | 0.666265 |
10,146,672 | 12 | 14 | 12. One or more non-transitory machine readable information storage mediums comprising one or more instructions which when executed by one or more hardware processors causes: selecting the (UI) model using a selection module ( 210 ); creating a test case model for the selected UI model and populating the created test case model into a test case editor ( 222 ) using a test case model creation module ( 212 ), wherein the test case model is created as a sequence of UI Actions based on a structure pattern of the selected UI model; validating the test case model for the selected UI model using a validation module ( 214 ); generating a test case script from the test case model for the selected UI model using a script generation module ( 216 ). | 12. One or more non-transitory machine readable information storage mediums comprising one or more instructions which when executed by one or more hardware processors causes: selecting the (UI) model using a selection module ( 210 ); creating a test case model for the selected UI model and populating the created test case model into a test case editor ( 222 ) using a test case model creation module ( 212 ), wherein the test case model is created as a sequence of UI Actions based on a structure pattern of the selected UI model; validating the test case model for the selected UI model using a validation module ( 214 ); generating a test case script from the test case model for the selected UI model using a script generation module ( 216 ). 14. The one or more non-transitory machine readable information storage mediums of claim 12 , wherein validation comprises assessing the test case model based on a rule engine ( 220 ) such that the rule engine ( 220 ) comprises a set of predefined rules. | 0.692494 |
6,112,177 | 1 | 4 | 1. A method for generating a photo-realistic talking head for a text-to-speech synthesis application, comprising the steps of: sampling images of a subject; extracting a plurality of parameters from each image sample; storing the image sample parameters into an animation library; sampling multiphone images of the subject; sampling sounds associated with the multiphone images; extracting a plurality of parameters from each multiphone image sample; storing the multiphone image parameters and associated sound samples into a coarticulation library; reading, based on an input stimulus comprising one or more phoneme sequences, parameters from the coarticulation library corresponding to each phoneme sequence; generating, using parameters from the animation library corresponding to the read parameters, a sequence of animated frames, the sequence tracking the input stimulus. | 1. A method for generating a photo-realistic talking head for a text-to-speech synthesis application, comprising the steps of: sampling images of a subject; extracting a plurality of parameters from each image sample; storing the image sample parameters into an animation library; sampling multiphone images of the subject; sampling sounds associated with the multiphone images; extracting a plurality of parameters from each multiphone image sample; storing the multiphone image parameters and associated sound samples into a coarticulation library; reading, based on an input stimulus comprising one or more phoneme sequences, parameters from the coarticulation library corresponding to each phoneme sequence; generating, using parameters from the animation library corresponding to the read parameters, a sequence of animated frames, the sequence tracking the input stimulus. 4. The method of claim 1, further comprising the step of: timestamping the multiphone image samples and sound samples. | 0.638037 |
8,396,864 | 1 | 2 | 1. A method comprising: selecting a topic from a hierarchy of topics; receiving, from a user, a seed set including one or more seed pages for the topic; receiving a document that is not associated with the topic; using the seed to determine, with a processor, a topic destination score and a topic source score for the document relative to the document, the topic destination score indicating an amount of content in the document relating to the topic and the topic source score indicating reachability of content relating to the topic through the document; receiving a query; and returning the document as a result for the query based at least in part on the topic source score and the topic destination score for the document; wherein returning the document as a result for the query based at least in part on the topic source score and the topic destination score for the document further comprises calculating a topic score according to a weighted average of the topic source score and topic destination score; and returning the document as a result for the query based at least in part on the topic score. | 1. A method comprising: selecting a topic from a hierarchy of topics; receiving, from a user, a seed set including one or more seed pages for the topic; receiving a document that is not associated with the topic; using the seed to determine, with a processor, a topic destination score and a topic source score for the document relative to the document, the topic destination score indicating an amount of content in the document relating to the topic and the topic source score indicating reachability of content relating to the topic through the document; receiving a query; and returning the document as a result for the query based at least in part on the topic source score and the topic destination score for the document; wherein returning the document as a result for the query based at least in part on the topic source score and the topic destination score for the document further comprises calculating a topic score according to a weighted average of the topic source score and topic destination score; and returning the document as a result for the query based at least in part on the topic score. 2. The method of claim 1 wherein the document is received as a result of a search. | 0.824786 |
9,805,089 | 11 | 12 | 11. A computer implemented method for identifying retail locations likely to sell a particular product, comprising: receiving a query from a remote computing device with a computing system, the query identifying a particular product; connecting with a database associated with the computing system, the database including retail location information representing a plurality of retail locations, retail category information for at least some of the plurality of the retail locations, and product information representing a plurality of products, the product information including natural language representations of at least some of the products, each of the natural language representations comprising one or more natural language words representing the corresponding product, the database further including a plurality of mappings between the products and retail categories represented in the retail category information, the database further including product ontology information representing hierarchies of product categories, and retail category ontology information representing hierarchies of retail categories; using the computing system to identify in the database a subset of the retail locations in a particular geographic area likely to provide the particular product in response to a query identifying the particular product by making one or more inferences that each of the subset of the retail locations is characterized by a corresponding one of a plurality of different probabilities of being a supplier of the particular product, the probability corresponding to each of the subset of the retail locations being represented in the database by a corresponding relationship between one of the retail categories to which the retail location belongs and one of the product categories in which the particular product is included, a first retail location of the subset of the retail locations being inferred to be a probable supplier of the particular product, and a second retail location of the subset of the retail locations being inferred to be a possible supplier of the particular product, the one or more inferences being made with reference to the particular product and the mappings between the products and the retail categories, and by extending the mappings using the product ontology information and the retail category ontology information to identify one or more relationships not explicitly represented in the database; and transmitting a response to the query to the remote computing device communicating the identified subset of the retail locations, including communicating the first retail location as a probable supplier of the particular product and communicating the second retail location as a possible supplier of the particular product. | 11. A computer implemented method for identifying retail locations likely to sell a particular product, comprising: receiving a query from a remote computing device with a computing system, the query identifying a particular product; connecting with a database associated with the computing system, the database including retail location information representing a plurality of retail locations, retail category information for at least some of the plurality of the retail locations, and product information representing a plurality of products, the product information including natural language representations of at least some of the products, each of the natural language representations comprising one or more natural language words representing the corresponding product, the database further including a plurality of mappings between the products and retail categories represented in the retail category information, the database further including product ontology information representing hierarchies of product categories, and retail category ontology information representing hierarchies of retail categories; using the computing system to identify in the database a subset of the retail locations in a particular geographic area likely to provide the particular product in response to a query identifying the particular product by making one or more inferences that each of the subset of the retail locations is characterized by a corresponding one of a plurality of different probabilities of being a supplier of the particular product, the probability corresponding to each of the subset of the retail locations being represented in the database by a corresponding relationship between one of the retail categories to which the retail location belongs and one of the product categories in which the particular product is included, a first retail location of the subset of the retail locations being inferred to be a probable supplier of the particular product, and a second retail location of the subset of the retail locations being inferred to be a possible supplier of the particular product, the one or more inferences being made with reference to the particular product and the mappings between the products and the retail categories, and by extending the mappings using the product ontology information and the retail category ontology information to identify one or more relationships not explicitly represented in the database; and transmitting a response to the query to the remote computing device communicating the identified subset of the retail locations, including communicating the first retail location as a probable supplier of the particular product and communicating the second retail location as a possible supplier of the particular product. 12. The computer implemented method of claim 11 further comprising identifying the geographic area with reference to geographic information received in association with the query. | 0.84622 |
9,910,829 | 1 | 8 | 1. A method for automatically separating documents represented within a plurality of images by delineating document boundaries and identifying document types in accordance with classification rules, the method comprising: automatically generating classification rules that predict a document type or subdocument type for each of the plurality of images based on textual information and/or graphical information represented in each respective one of the plurality of images, wherein the classification rules are generated based on analyzing textual information and/or graphical information of a plurality of training images using one or more of: a probabilistic network; relational algebra; and machine learning techniques automatically generating one or more identifiers for identifying which of a plurality of document images belongs to which of a plurality of categories; automatically categorizing a plurality of document images into a plurality of predetermined categories based on analyzing textual information and/or image characteristics of each of the plurality of document images using the classification rules, wherein the step of automatically categorizing comprises: producing an output score for each document image based on the analysis thereof using the classification rules, wherein each output score represents an estimated document type probability or a subdocument type probability; and using a graph search algorithm to determine an optimum categorization sequence from a plurality of possible categorization sequences for the plurality of document images based on the output scores; and separating documents within the plurality of document images from one another by either: electronically associating at least one computer-generated label with at least some of the plurality of document images, each label corresponding to a different one of the plurality of categories and comprising one of the one or more identifiers generated for identifying which of the plurality of document images belongs to which of the plurality of categories; or inserting one or more computer-generated separation pages between at least some of the plurality of document images to delineate images belonging to different ones of the plurality of categories, each separation page comprising one of the one or more identifiers generated for identifying which of the plurality of document images belongs to which of the plurality of categories; or both electronically associating the at least one computer-generated label with at least some of the plurality of document images and inserting the one or more computer-generated separation pages between at least some of the plurality of document images. | 1. A method for automatically separating documents represented within a plurality of images by delineating document boundaries and identifying document types in accordance with classification rules, the method comprising: automatically generating classification rules that predict a document type or subdocument type for each of the plurality of images based on textual information and/or graphical information represented in each respective one of the plurality of images, wherein the classification rules are generated based on analyzing textual information and/or graphical information of a plurality of training images using one or more of: a probabilistic network; relational algebra; and machine learning techniques automatically generating one or more identifiers for identifying which of a plurality of document images belongs to which of a plurality of categories; automatically categorizing a plurality of document images into a plurality of predetermined categories based on analyzing textual information and/or image characteristics of each of the plurality of document images using the classification rules, wherein the step of automatically categorizing comprises: producing an output score for each document image based on the analysis thereof using the classification rules, wherein each output score represents an estimated document type probability or a subdocument type probability; and using a graph search algorithm to determine an optimum categorization sequence from a plurality of possible categorization sequences for the plurality of document images based on the output scores; and separating documents within the plurality of document images from one another by either: electronically associating at least one computer-generated label with at least some of the plurality of document images, each label corresponding to a different one of the plurality of categories and comprising one of the one or more identifiers generated for identifying which of the plurality of document images belongs to which of the plurality of categories; or inserting one or more computer-generated separation pages between at least some of the plurality of document images to delineate images belonging to different ones of the plurality of categories, each separation page comprising one of the one or more identifiers generated for identifying which of the plurality of document images belongs to which of the plurality of categories; or both electronically associating the at least one computer-generated label with at least some of the plurality of document images and inserting the one or more computer-generated separation pages between at least some of the plurality of document images. 8. The method of claim 1 , wherein the output scores represents a probability that each document image belongs to at least one respective category from the plurality of categories. | 0.744318 |
9,154,306 | 38 | 39 | 38. The system of claim 36 , wherein the request is for pseudonymous access at the RP, and the pseudonymous access is linkable to a pseudonym previously registered at the RP. | 38. The system of claim 36 , wherein the request is for pseudonymous access at the RP, and the pseudonymous access is linkable to a pseudonym previously registered at the RP. 39. The system of claim 38 , wherein the operations further comprise: receiving proof of possession of the pseudonym previously registered at the RP, wherein the proof is made by a zero-knowledge proof, by signing, or by decrypting a challenge. | 0.5 |
8,576,049 | 8 | 11 | 8. A computer-implemented method for document authentication and identification, comprising: receiving a digitized document; comparing the digitized document to a set of markers to determine whether the digitized document is an encoded document with one or more text characters replaced, wherein the one or more text characters replaced includes at least one letter, number, symbol or space changed to another letter, number, or symbol; in response to determining that the digitized document is an encoded document with one or more characters replaced, extracting information from the set of markers using a decoder according to an encoding strategy; and comparing the extracted information and the set of markers with data stored in an encoding history to authenticate and identify the received digitized document. | 8. A computer-implemented method for document authentication and identification, comprising: receiving a digitized document; comparing the digitized document to a set of markers to determine whether the digitized document is an encoded document with one or more text characters replaced, wherein the one or more text characters replaced includes at least one letter, number, symbol or space changed to another letter, number, or symbol; in response to determining that the digitized document is an encoded document with one or more characters replaced, extracting information from the set of markers using a decoder according to an encoding strategy; and comparing the extracted information and the set of markers with data stored in an encoding history to authenticate and identify the received digitized document. 11. The method of claim 8 further comprising: selecting the set of markers based on attributes associated with the digitized document, the attributes comprising one or more of: author, originator, content, sender, recipient, location of the recipient, and a time stamp. | 0.521352 |
9,082,207 | 1 | 9 | 1. A method of printing content on a three dimensional structure, comprising: creating a graphical design style sheet for a three dimensional structure, wherein: the style sheet comprises a plurality of rules for graphical content to be printed on the structure, and wherein each rule comprises a selector that identifies a facet of the structure and a declaration, and creating the graphical design style sheet comprises: selecting a facet to be specified in the selector; selecting, for the selector, one or more attributes of the graphical content that will be affected by the rule's declaration; and including, in the declaration, a property and a value that sets forth an effect that the rule will have on the selected facet, applying, using a graphical design layout renderer, one or more of the rules for a first facet of the structure to first semantic structural design data to generate a first portion of a graphical design template for the structure; applying, using the graphical design layout renderer, one or more of the rules for at least one additional facet of the structure to additional semantic structural design data until the graphic design template is prepared; receiving graphical content to be applied to the structure; and by a processor, using one or more of the rules of the style sheet to automatically link the graphical content to the template to generate graphical design data for printing the graphical content on the structure in accordance with the rules. | 1. A method of printing content on a three dimensional structure, comprising: creating a graphical design style sheet for a three dimensional structure, wherein: the style sheet comprises a plurality of rules for graphical content to be printed on the structure, and wherein each rule comprises a selector that identifies a facet of the structure and a declaration, and creating the graphical design style sheet comprises: selecting a facet to be specified in the selector; selecting, for the selector, one or more attributes of the graphical content that will be affected by the rule's declaration; and including, in the declaration, a property and a value that sets forth an effect that the rule will have on the selected facet, applying, using a graphical design layout renderer, one or more of the rules for a first facet of the structure to first semantic structural design data to generate a first portion of a graphical design template for the structure; applying, using the graphical design layout renderer, one or more of the rules for at least one additional facet of the structure to additional semantic structural design data until the graphic design template is prepared; receiving graphical content to be applied to the structure; and by a processor, using one or more of the rules of the style sheet to automatically link the graphical content to the template to generate graphical design data for printing the graphical content on the structure in accordance with the rules. 9. The method of claim 1 , wherein the linking further comprises: determining that the graphical content comprises a background image, and expanding the graphical content so that the background image spans a plurality of the facets. | 0.692308 |
8,412,511 | 1 | 3 | 1. A system for providing a translation of a set of one or more terms or phrases from a source language to more than one target language, the system comprising: (a) a memory adapted to store one or more translations of said set of one or more terms or phrases in said more than one target language; and (b) a processor in communication with said memory and adapted to execute a translation module, wherein said translation module is adapted for execution by said processor to: (1) obtain said one or more translations in said more than one target language for individual terms or phrases of said set of one or more terms or phrases provided by one or more users, wherein said one or more users enter said one or more translations into one or more computer systems, that are in communication with said processor; (2) store said one or more translations for said individual terms or phrases in said memory; (3) store a first particular target language and a second particular target language identified by a user; and (4) in response to receiving a user's request for a preferred translation of each term or phrase in said set of one or more terms or phrases: (i) retrieve said user's first particular target language and said user's second particular target language; (ii) identify said preferred translation for each individual term or phrase of said set of one or more terms or phrases, wherein said preferred translation for each said individual term or phrase is a translation of said one or more translations most frequently provided by said one or more users for each said individual term or phrase in said first particular target language; (iii) in response to a translation not being provided for an individual term or phrase of said set of one or more terms or phrases for said user's first target language, identify said preferred translation for said individual term or phrase wherein said preferred translation for each said individual term or phrase is a translation of said one or more translations most frequently provided by said one or more users for each said individual term or phrase in said second target language; and (iv) cause display said identified preferred translation to said user. | 1. A system for providing a translation of a set of one or more terms or phrases from a source language to more than one target language, the system comprising: (a) a memory adapted to store one or more translations of said set of one or more terms or phrases in said more than one target language; and (b) a processor in communication with said memory and adapted to execute a translation module, wherein said translation module is adapted for execution by said processor to: (1) obtain said one or more translations in said more than one target language for individual terms or phrases of said set of one or more terms or phrases provided by one or more users, wherein said one or more users enter said one or more translations into one or more computer systems, that are in communication with said processor; (2) store said one or more translations for said individual terms or phrases in said memory; (3) store a first particular target language and a second particular target language identified by a user; and (4) in response to receiving a user's request for a preferred translation of each term or phrase in said set of one or more terms or phrases: (i) retrieve said user's first particular target language and said user's second particular target language; (ii) identify said preferred translation for each individual term or phrase of said set of one or more terms or phrases, wherein said preferred translation for each said individual term or phrase is a translation of said one or more translations most frequently provided by said one or more users for each said individual term or phrase in said first particular target language; (iii) in response to a translation not being provided for an individual term or phrase of said set of one or more terms or phrases for said user's first target language, identify said preferred translation for said individual term or phrase wherein said preferred translation for each said individual term or phrase is a translation of said one or more translations most frequently provided by said one or more users for each said individual term or phrase in said second target language; and (iv) cause display said identified preferred translation to said user. 3. The system of claim 1 , wherein in response to receiving said user's request, said translation module is adapted for execution by said processor to identify said particular target language. | 0.666667 |
9,690,758 | 11 | 12 | 11. The mobile device of claim 9 , wherein the display is further configured to output at least one of: a list output screen, when the e-book has e-book auxiliary content, for showing pages and words, serving as items, included in the e-book auxiliary content, according to a user's inputs; or a text output screen where the words to which the e-book auxiliary content are applied are displayed differently from other words on a same page of the e-book. | 11. The mobile device of claim 9 , wherein the display is further configured to output at least one of: a list output screen, when the e-book has e-book auxiliary content, for showing pages and words, serving as items, included in the e-book auxiliary content, according to a user's inputs; or a text output screen where the words to which the e-book auxiliary content are applied are displayed differently from other words on a same page of the e-book. 12. The mobile device of claim 11 , wherein, when a particular item comprising at least one word and page is selected on the list output screen, the display is further configured to output at least one of: sub-items included in the selected item; or information regarding a map that displays information regarding a route connecting a place location corresponding to a word, selected on a previous page, to a place location corresponding to the currently selected word on the currently selected page. | 0.5 |
8,635,293 | 10 | 11 | 10. A method according to claim 7 , further comprising performing analysis on one or more frames and/or audio clips of the video clips. | 10. A method according to claim 7 , further comprising performing analysis on one or more frames and/or audio clips of the video clips. 11. A method according to claim 10 , wherein the analysis comprises image processing of the frames to identify key icons to represent the video messages or to identify content in the video clips, and the method further comprises either displaying the key icons to represent the video messages or indexing keywords that correspond to the identified content. | 0.5 |
8,150,869 | 11 | 13 | 11. One or more computer-readable storage media devices comprising instructions that are executable and, responsive to executing the instructions, a computing device: navigates to a Web page being browsed or navigated to; identifies context information for a user of the computing device, the context information including information for at least one of the Web page browsed to or navigated to, previous Web pages accessed by the user, links selected by the user for Web page navigation, or a browsing pattern of the user; uses the context information to identify a set of keywords based at least in part on a current Web page being displayed and one or more of the previous Web pages H displayed for the user in a current Web browsing session, the context information being used to identify the set of keywords in response to a determination that the one or more previous Web pages are related to the current Web page being displayed; uses the set of keywords and at least one of previous searches by the user or current popular searches by other users to identify a set of query terms; displays one or more query terms of the identified set of query terms as part of a user interface of the computing device; and displays the current Web page concurrently with search results of a query based on the one or more query terms in the user interface of the computing device. | 11. One or more computer-readable storage media devices comprising instructions that are executable and, responsive to executing the instructions, a computing device: navigates to a Web page being browsed or navigated to; identifies context information for a user of the computing device, the context information including information for at least one of the Web page browsed to or navigated to, previous Web pages accessed by the user, links selected by the user for Web page navigation, or a browsing pattern of the user; uses the context information to identify a set of keywords based at least in part on a current Web page being displayed and one or more of the previous Web pages H displayed for the user in a current Web browsing session, the context information being used to identify the set of keywords in response to a determination that the one or more previous Web pages are related to the current Web page being displayed; uses the set of keywords and at least one of previous searches by the user or current popular searches by other users to identify a set of query terms; displays one or more query terms of the identified set of query terms as part of a user interface of the computing device; and displays the current Web page concurrently with search results of a query based on the one or more query terms in the user interface of the computing device. 13. One or more computer-readable storage media devices as recited in claim 11 , further comprising additional instructions that are executable and, responsive to executing the additional instructions, the computing device uses a category method to identify one or more general categories that the set of keywords are part of, and includes the one or more general categories in the set of query terms. | 0.507371 |
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