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10,088,562 | 7 | 13 | 7. A semantic sensing system comprising: a first sensing entity and a second sensing entity; a semantic engine coupled with the first sensing entity and the second sensing entity; a memory associated with the semantic engine, the memory storing a plurality of semantics; the memory further storing a plurality of rules comprising: a first semantic inference rule associating data from the first sensing entity with a first semantic; a second semantic inference rule associating data from the second sensing entity with a second semantic; a third semantic inference rule for a composite semantic indicating that the composite semantic is a combination of the first and the second semantic; a plurality of access control rules, each of the plurality of access control rules associating at least one time interval and at least one semantic from among the plurality of semantics stored in the memory with an access control action; the semantic engine being configured to interpret the plurality of rules; the semantic engine further being configured to perform the access control action by: inferring the first semantic based on an input from the first sensing entity at a first time and the first semantic inference rule; inferring the second semantic based on an input from the second sensing entity at a second time and the second semantic inference rule, wherein the second semantic is further inferred based on an external input; inferring the composite semantic based on the first and the second semantics and the third semantic inference rule; identifying a first access control rule from among the plurality of access control rules applicable to the composite semantic and performing the access control action associated with the first access control rule. | 7. A semantic sensing system comprising: a first sensing entity and a second sensing entity; a semantic engine coupled with the first sensing entity and the second sensing entity; a memory associated with the semantic engine, the memory storing a plurality of semantics; the memory further storing a plurality of rules comprising: a first semantic inference rule associating data from the first sensing entity with a first semantic; a second semantic inference rule associating data from the second sensing entity with a second semantic; a third semantic inference rule for a composite semantic indicating that the composite semantic is a combination of the first and the second semantic; a plurality of access control rules, each of the plurality of access control rules associating at least one time interval and at least one semantic from among the plurality of semantics stored in the memory with an access control action; the semantic engine being configured to interpret the plurality of rules; the semantic engine further being configured to perform the access control action by: inferring the first semantic based on an input from the first sensing entity at a first time and the first semantic inference rule; inferring the second semantic based on an input from the second sensing entity at a second time and the second semantic inference rule, wherein the second semantic is further inferred based on an external input; inferring the composite semantic based on the first and the second semantics and the third semantic inference rule; identifying a first access control rule from among the plurality of access control rules applicable to the composite semantic and performing the access control action associated with the first access control rule. 13. The system of claim 7 , wherein at least one of the plurality of access control rules is based on a semantic interval. | 0.781362 |
9,430,451 | 12 | 19 | 12. A computer system for parsing author names in a document, the system comprising: a scanner with a digital processor, the scanner configured to: electronically scan a document that contains an author name text string, the author name text string comprising a set of initials, one or more surnames, and punctuation, and the author name text string comprising at least one author name in non-standardized format; identify a character sequence in the document as potentially being the author name text string, wherein the identifying is based on: (i) a sequence of title-case words, capital letters, and punctuation in the character sequence, and (ii) the character sequence ending with a recognized indicator; and a parser with a digital processor, the parser configured to: parse the identified character sequence and determining whether the identified character sequence is the author name text string, wherein the parsing and determining comprises: updating the identified character sequence by converting any punctuation or whitespace between terms in the character sequence to single space character, and determining whether one or more author names are contained in the updated character sequence by identifying a pattern of surname and set of initials in the updated character sequence, such that an author name in non-standardized format in the document is identified and output in standardized format. | 12. A computer system for parsing author names in a document, the system comprising: a scanner with a digital processor, the scanner configured to: electronically scan a document that contains an author name text string, the author name text string comprising a set of initials, one or more surnames, and punctuation, and the author name text string comprising at least one author name in non-standardized format; identify a character sequence in the document as potentially being the author name text string, wherein the identifying is based on: (i) a sequence of title-case words, capital letters, and punctuation in the character sequence, and (ii) the character sequence ending with a recognized indicator; and a parser with a digital processor, the parser configured to: parse the identified character sequence and determining whether the identified character sequence is the author name text string, wherein the parsing and determining comprises: updating the identified character sequence by converting any punctuation or whitespace between terms in the character sequence to single space character, and determining whether one or more author names are contained in the updated character sequence by identifying a pattern of surname and set of initials in the updated character sequence, such that an author name in non-standardized format in the document is identified and output in standardized format. 19. The computer system of claim 12 , wherein the recognized indicator includes at least one of: (i) “et al”, (ii) a digit indication of a year, or (iii) a title-case word followed by at least three lowercase terms. | 0.839312 |
8,601,008 | 18 | 20 | 18. In a computer readable storage medium having stored therein data representing instructions executable by a programmed processor for determining geographic range of a search query, the storage medium comprising instructions operative for: identifying a root term from the search query; accessing a query history of the root term from a root term database, wherein the query history includes geographic ranges associated with each root term stored in the root term database; analyzing the query history of the root term including each of the geographic ranges stored in the query history that are associated with the root term from the search query; and determining, based on the analysis, the geographic range for the search query based on the geographic ranges stored in the root term database for the root term from the search query. | 18. In a computer readable storage medium having stored therein data representing instructions executable by a programmed processor for determining geographic range of a search query, the storage medium comprising instructions operative for: identifying a root term from the search query; accessing a query history of the root term from a root term database, wherein the query history includes geographic ranges associated with each root term stored in the root term database; analyzing the query history of the root term including each of the geographic ranges stored in the query history that are associated with the root term from the search query; and determining, based on the analysis, the geographic range for the search query based on the geographic ranges stored in the root term database for the root term from the search query. 20. The storage medium of claim 18 wherein the geographic range is determined based on a plurality of frequencies by which the root term is associated with a plurality of location bands in the query history of the root term, further wherein one of the plurality of frequencies of the root term is associated with one of the plurality of location bands. | 0.650099 |
9,552,281 | 13 | 14 | 13. The system of claim 12 , wherein the set of test operations comprises a set of automated tests of a domain name server. | 13. The system of claim 12 , wherein the set of test operations comprises a set of automated tests of a domain name server. 14. The system of claim 13 , wherein the set of automated tests of the domain name server comprises at least one of— testing an availability of a domain name, retrieving a set of metadata associated with the domain name, or performing an access of a Web site associated with the domain name. | 0.916571 |
7,822,786 | 8 | 13 | 8. A method for defining a metadata schema to facilitate passing data between an eXtensible Markup Language (XML) document and a hierarchical database, the method comprising: accessing a database schema indicative of database field names and a hierarchical structure for a hierarchical database; accessing a document schema that defines the hierarchical structure, content data syntax, and semantics of valid, well-formed, XML documents that can be passed into and out of the hierarchical database, the document schema including an XML element name that maps to a database field name in the database schema; relating the database schema and the document schema to provide a metadata schema that enables data to be passed between an XML document and the hierarchical database; and wherein the document schema comprises at least one directive metadata element configured to not interfere with third-party applications using the document schema and to facilitate passing data between the XML document and the hierarchical database. | 8. A method for defining a metadata schema to facilitate passing data between an eXtensible Markup Language (XML) document and a hierarchical database, the method comprising: accessing a database schema indicative of database field names and a hierarchical structure for a hierarchical database; accessing a document schema that defines the hierarchical structure, content data syntax, and semantics of valid, well-formed, XML documents that can be passed into and out of the hierarchical database, the document schema including an XML element name that maps to a database field name in the database schema; relating the database schema and the document schema to provide a metadata schema that enables data to be passed between an XML document and the hierarchical database; and wherein the document schema comprises at least one directive metadata element configured to not interfere with third-party applications using the document schema and to facilitate passing data between the XML document and the hierarchical database. 13. The method of claim 8 , wherein the at least one directive metadata element is selected from the group of directives consisting of a storage and retrieval directive, an index directive, and a hierarchical database indicator directive. | 0.772467 |
8,654,138 | 8 | 12 | 8. A system comprising: one or more devices to: receive data in a first format, the data including first information associated with a first information type and second information associated with a second information type, and the first information type and the second information type being different, provide the data for display via a graphical interface, determine one or more translation rules, of a plurality of translation rules, associated with converting the data to a second format that is different from the first format, determine respective effects associated with applying the one or more translation rules to the first information type and to the second information type, the one or more translation rules affecting the first information type differently than the second information type, provide information associated with the respective effects for display via the graphical interface, the information identifying differences between applying the one or more translation rules to the first information type and to the second information type; determine that the first information is compatible with the second format and that the second information is incompatible with the second format; apply a first visual style to the first information to modify a display of the first information, the first visual style indicating that the first information is compatible with the second format, and the first visual style providing the first information in the second format for display via the graphical interface in conjunction with the first information in the first format; apply a second visual style to the second information to modify a display of the second information, the second visual style indicating that the second information is incompatible with the second format; and provide information identifying one or more rules for converting the second information into the second format. | 8. A system comprising: one or more devices to: receive data in a first format, the data including first information associated with a first information type and second information associated with a second information type, and the first information type and the second information type being different, provide the data for display via a graphical interface, determine one or more translation rules, of a plurality of translation rules, associated with converting the data to a second format that is different from the first format, determine respective effects associated with applying the one or more translation rules to the first information type and to the second information type, the one or more translation rules affecting the first information type differently than the second information type, provide information associated with the respective effects for display via the graphical interface, the information identifying differences between applying the one or more translation rules to the first information type and to the second information type; determine that the first information is compatible with the second format and that the second information is incompatible with the second format; apply a first visual style to the first information to modify a display of the first information, the first visual style indicating that the first information is compatible with the second format, and the first visual style providing the first information in the second format for display via the graphical interface in conjunction with the first information in the first format; apply a second visual style to the second information to modify a display of the second information, the second visual style indicating that the second information is incompatible with the second format; and provide information identifying one or more rules for converting the second information into the second format. 12. The system of claim 8 , where, when providing the information associated with the respective effects, the one or more devices are to: provide portions of the data for display at respective regions of the graphical interface, and provide information associated with converting a particular portion, of the portions of the data, to the second format for display, the information associated with converting the particular portion being provided at a corresponding region of the graphical interface associated with the particular portion, and the information associated with converting the particular portion indicating whether the portion is compatible with the second format. | 0.725244 |
9,058,174 | 12 | 13 | 12. The computer-implemented method of claim 11 , wherein wiring the plurality of web widgets comprises: creating a plurality of wirings, wherein each wiring connects: (i) a respective first web widget producing a resource and (ii) a respective second web widget consuming a compatible resource, as determined based on the ontology of semantic tags. | 12. The computer-implemented method of claim 11 , wherein wiring the plurality of web widgets comprises: creating a plurality of wirings, wherein each wiring connects: (i) a respective first web widget producing a resource and (ii) a respective second web widget consuming a compatible resource, as determined based on the ontology of semantic tags. 13. The system of claim 12 , wherein the widget manager module is configured to independently resolve the determined cycle by each individual operation selected from: (i) in one instance, removing a wiring of the plurality of wirings without requiring any user input specifying to remove the wiring, thereby removing the determined cycle; (ii) in another instance, removing the wiring upon receiving user input specifying to remove the determined cycle, thereby removing the determined cycle; and (iii) in still another instance, upon receiving user input specifying not to remove the determined cycle, designating the determined cycle as a desired cycle, wherein the desired cycle is not removed. | 0.824698 |
8,346,534 | 63 | 88 | 63. An apparatus for automatically generating one or more keywords from an electronic document, the apparatus comprising; an interface to a document storage repository; a memory; and a processor communicably connected to the interface and the memory, wherein the processor (a) identifies candidate entries for the keywords by extracting all n-grams up to a specified length that do not cross sentence boundaries, reducing a size of a data set consisting of the extracted n-grams by applying one or more filters and balancing a distribution of positive and negative examples whenever the data set is derived from a training data set, (b) constructs a feature vector for each candidate entry, wherein the feature vector comprises at least one feature selected from the group consisting of one or more discourse comprehension features, one or more part-of-speech pattern features, and one or more encyclopedic annotation features, (c) assigns a numeric score to each candidate entry based on the feature vector for that candidate entry, and (d) selects a specified number of entries to be retained as the keywords. | 63. An apparatus for automatically generating one or more keywords from an electronic document, the apparatus comprising; an interface to a document storage repository; a memory; and a processor communicably connected to the interface and the memory, wherein the processor (a) identifies candidate entries for the keywords by extracting all n-grams up to a specified length that do not cross sentence boundaries, reducing a size of a data set consisting of the extracted n-grams by applying one or more filters and balancing a distribution of positive and negative examples whenever the data set is derived from a training data set, (b) constructs a feature vector for each candidate entry, wherein the feature vector comprises at least one feature selected from the group consisting of one or more discourse comprehension features, one or more part-of-speech pattern features, and one or more encyclopedic annotation features, (c) assigns a numeric score to each candidate entry based on the feature vector for that candidate entry, and (d) selects a specified number of entries to be retained as the keywords. 88. The apparatus as recited in claim 63 , wherein the processor further: extracts sense definitions from a sense inventory; and applies at least one disambiguation algorithm to each candidate entry, whereby the most likely sense is determined for each candidate entry. | 0.919268 |
9,104,655 | 1 | 5 | 1. A computer-implemented method for performing contextual classification of objects, comprising: receiving supervised training data transmitted over a network from at least one content reviewer, the supervised training data comprising at least one comment and at least one tag specifying whether the at least one comment is abusive; storing the supervised training data in a database; preprocessing, with at least one processor, the supervised training data to form at least one vectorized object; training a plurality of models by applying a plurality of machine learning algorithms to each vectorized object in parallel; identifying, with at least one processor, an optimal model from the plurality of models; and filtering at least one abusive comment using the identified optimal model. | 1. A computer-implemented method for performing contextual classification of objects, comprising: receiving supervised training data transmitted over a network from at least one content reviewer, the supervised training data comprising at least one comment and at least one tag specifying whether the at least one comment is abusive; storing the supervised training data in a database; preprocessing, with at least one processor, the supervised training data to form at least one vectorized object; training a plurality of models by applying a plurality of machine learning algorithms to each vectorized object in parallel; identifying, with at least one processor, an optimal model from the plurality of models; and filtering at least one abusive comment using the identified optimal model. 5. The computer-implemented method of claim 1 , wherein: preprocessing the supervised training data to form at least one vectorized object comprises preprocessing the supervised training data using a plurality of machines operating in parallel. | 0.539623 |
9,025,213 | 18 | 19 | 18. A method for processing documents, the method comprising: creating a reservation for a paper document; specifying in the reservation for the paper document metadata corresponding to the paper document, where the metadata includes a unique identifier of a label that is applied to the paper document and further includes a first disposition policy for the paper document and a second disposition policy for a corresponding electronic document; applying the label to the paper document; scanning the paper document to generate the electronic document; reading the unique identifier of the label in the electronic document; linking the electronic document with the reservation for the paper document based on the unique identifier of the label; performing quality assurance processing related to the electronic document after the paper document has been scanned to produce the electronic document, wherein the quality assurance processing comprises: comparing the electronic document to the paper document to assure the electronic document accurately represents the paper document; verifying completeness and accuracy of the metadata corresponding to the paper document; verifying the electronic document is written to a document management system; verifying any needed workflows associated with the paper document and the electronic document are triggered; building an audit trail for the paper document; and taking corrective action if any of the quality assurance processing indicates corrective action is needed; storing the electronic document in a database; and scheduling disposition of the paper document according to the disposition policy for the paper document that was specified by the user during the reservation session for the paper document. | 18. A method for processing documents, the method comprising: creating a reservation for a paper document; specifying in the reservation for the paper document metadata corresponding to the paper document, where the metadata includes a unique identifier of a label that is applied to the paper document and further includes a first disposition policy for the paper document and a second disposition policy for a corresponding electronic document; applying the label to the paper document; scanning the paper document to generate the electronic document; reading the unique identifier of the label in the electronic document; linking the electronic document with the reservation for the paper document based on the unique identifier of the label; performing quality assurance processing related to the electronic document after the paper document has been scanned to produce the electronic document, wherein the quality assurance processing comprises: comparing the electronic document to the paper document to assure the electronic document accurately represents the paper document; verifying completeness and accuracy of the metadata corresponding to the paper document; verifying the electronic document is written to a document management system; verifying any needed workflows associated with the paper document and the electronic document are triggered; building an audit trail for the paper document; and taking corrective action if any of the quality assurance processing indicates corrective action is needed; storing the electronic document in a database; and scheduling disposition of the paper document according to the disposition policy for the paper document that was specified by the user during the reservation session for the paper document. 19. The method of claim 18 wherein the first disposition policy comprises a default disposition policy. | 0.695266 |
7,996,793 | 1 | 13 | 1. A method for providing recognition of gestures made by a user using a filter representing a gesture, the filter comprising base information about the gesture, comprising: receiving data captured by a camera, the data corresponding to a first application; applying the filter to the data and determining an output from the base information about the gesture; sending the first application the output; receiving second data captured by the camera, the data corresponding to a second application; applying the filter to the second data and determining a second output from the base information about the gesture; and sending the second application the second output. | 1. A method for providing recognition of gestures made by a user using a filter representing a gesture, the filter comprising base information about the gesture, comprising: receiving data captured by a camera, the data corresponding to a first application; applying the filter to the data and determining an output from the base information about the gesture; sending the first application the output; receiving second data captured by the camera, the data corresponding to a second application; applying the filter to the second data and determining a second output from the base information about the gesture; and sending the second application the second output. 13. The method of claim 1 , wherein a filter comprises a number of inputs, a collective type of inputs, a number of outputs, and a collective type of outputs, comprising: replacing the filter with a second filter, the second filter comprising base information about the gesture, the number of inputs of the second filter equaling the number of inputs of the filter, the collective type of inputs of the second filter equaling the collective type of inputs of the filter, the number of outputs of the second filter equaling the number of outputs of the filter, the collective type of outputs of the second filter equaling the collective type of outputs of the filter, receiving third data captured by a camera; applying the third filter to the data and determining a third output from the base information of the second filter; and sending the first application the third output. | 0.500569 |
8,805,686 | 19 | 21 | 19. The method of claim 1 , further including applying dynamic programming to hidden Markov models of the utterance and of the word representation during the searching and/or scoring. | 19. The method of claim 1 , further including applying dynamic programming to hidden Markov models of the utterance and of the word representation during the searching and/or scoring. 21. The method of claim 19 , wherein the hidden Markov models for the word representations model words without intermediate phoneme representations. | 0.961196 |
8,120,789 | 6 | 7 | 6. The method of claim 1 , further comprising determining which nodes and contexts of the input document are streamable. | 6. The method of claim 1 , further comprising determining which nodes and contexts of the input document are streamable. 7. The method of claim 6 , further comprising determining that the node is streamable if the node can produce an output to which the node contributes as the node's input data is parsed. | 0.938579 |
9,626,703 | 25 | 26 | 25. A system for providing voice commerce, the system comprising: one or more physical processors programmed with computer program instructions which, when executed, cause the one or more physical processors to: receive a user input comprising a natural language utterance; provide, without further user input after the receipt of the user input, the natural language utterance as an input to a speech recognition engine; obtain, without further user input after the receipt of the user input, one or more words or phrases recognized from the natural language utterance as an output of the speech recognition engine; determine, without further user input after the receipt of the user input, a context based at least on the one or more words or phrases; identify, without further user input after the receipt of the user input, the product or service to be purchased on behalf of the user based at least on the determined context; obtain payment information with which to pay for the product or service; obtain, without further user input after the receipt of the user input, shipping information with which to deliver the product or service, wherein the shipping information specifies a name or address of a recipient to which the product or service is to be delivered after the product or service is purchased; and provide, without further user input after the receipt of the user input, a request for user confirmation to use the payment information and the shipping information for a purchase transaction for the product or service. | 25. A system for providing voice commerce, the system comprising: one or more physical processors programmed with computer program instructions which, when executed, cause the one or more physical processors to: receive a user input comprising a natural language utterance; provide, without further user input after the receipt of the user input, the natural language utterance as an input to a speech recognition engine; obtain, without further user input after the receipt of the user input, one or more words or phrases recognized from the natural language utterance as an output of the speech recognition engine; determine, without further user input after the receipt of the user input, a context based at least on the one or more words or phrases; identify, without further user input after the receipt of the user input, the product or service to be purchased on behalf of the user based at least on the determined context; obtain payment information with which to pay for the product or service; obtain, without further user input after the receipt of the user input, shipping information with which to deliver the product or service, wherein the shipping information specifies a name or address of a recipient to which the product or service is to be delivered after the product or service is purchased; and provide, without further user input after the receipt of the user input, a request for user confirmation to use the payment information and the shipping information for a purchase transaction for the product or service. 26. The system of claim 25 , wherein the one or more physical processors are further caused to: determine whether the user has confirmed use of the payment information and the shipping information for the purchase transaction; and complete, without further user input after the receipt of the user input other than a user confirmation with respect to the confirmation request, the purchase transaction based on the payment information, the shipping information, and a determination that the user has confirmed use of the payment information and the shipping information. | 0.699684 |
9,218,427 | 24 | 25 | 24. A network computer for managing data over a network, comprising: a transceiver that communicates over the network; a memory that stores at least instructions; and a processor device that executes instructions that perform actions, including: providing source data to the network computer from one or more separate data sources; providing a plurality of particular types of indices that are separate and optimized for one or more different content-types, wherein the particular types of indices include one or more of n-gram indices, temporal indices, or geo-spatial indices; generating a raw data graph from the source data, wherein the structure of the raw data graph is based on the structure of the source data; mapping one or more elements of the raw data graph to a concept graph; generating one or more concept instances based on at least the concept graph, the raw data graph, and the source data; generating one or more model-identifiers (MIDs) that correspond to the one or more concept instances, wherein the one or more MIDs include at least a path in the concept graph and one or more value keys that correspond to one or more portions of the source data; indexing values from the source data that correspond to the one or more MIDs in one or more indices that are selected from the plurality of indices based on a content-type of the source data that is associated with the one or more MIDs; and responsive to a query, generating a result set that includes one or more result MIDs based on one or more indices of the plurality of indices, wherein a content-type of at least one portion of the query is employed to select the one or more indices used to generate the result set. | 24. A network computer for managing data over a network, comprising: a transceiver that communicates over the network; a memory that stores at least instructions; and a processor device that executes instructions that perform actions, including: providing source data to the network computer from one or more separate data sources; providing a plurality of particular types of indices that are separate and optimized for one or more different content-types, wherein the particular types of indices include one or more of n-gram indices, temporal indices, or geo-spatial indices; generating a raw data graph from the source data, wherein the structure of the raw data graph is based on the structure of the source data; mapping one or more elements of the raw data graph to a concept graph; generating one or more concept instances based on at least the concept graph, the raw data graph, and the source data; generating one or more model-identifiers (MIDs) that correspond to the one or more concept instances, wherein the one or more MIDs include at least a path in the concept graph and one or more value keys that correspond to one or more portions of the source data; indexing values from the source data that correspond to the one or more MIDs in one or more indices that are selected from the plurality of indices based on a content-type of the source data that is associated with the one or more MIDs; and responsive to a query, generating a result set that includes one or more result MIDs based on one or more indices of the plurality of indices, wherein a content-type of at least one portion of the query is employed to select the one or more indices used to generate the result set. 25. The network computer of claim 24 , wherein indexing the values from the source data that correspond to the one or more MIDs further comprises, generating one or more index records that include semantic equivalents of at least the value of the one or more MIDs. | 0.813822 |
9,785,891 | 22 | 24 | 22. The system of claim 15 , wherein the plurality of data sequences are prelabeled using a plurality of predetermined labels corresponding to at least one of the plurality of formulated tasks. | 22. The system of claim 15 , wherein the plurality of data sequences are prelabeled using a plurality of predetermined labels corresponding to at least one of the plurality of formulated tasks. 24. The system of claim 22 , wherein the plurality of predetermined labels includes at least one of “COMPLAINT”, “REQUEST”, “APOLOGY”, “ANSWER”, “RECEIPT”, “COMPLIMENT”, “RESPONSE TO POSITIVITY”, “GREETING”, “THANK”, “ANNOUNCEMENT”, “SOLVED”, and “OTHER” corresponding to a task for determining a nature of the conversation among the plurality of formulated tasks. | 0.921619 |
8,156,100 | 12 | 14 | 12. A computer-implemented method comprising: identifying at a server a plurality of sites, each of the sites hosting a respective plurality of documents; wherein the plurality of sites include at least one site visited by multiple distinct counted visitors during a time period; accessing, at the server, usage information associated with each of the plurality of sites hosting the documents, the usage information including, for each site: (i) a frequency of visit value based on a total number of times the site was visited by all counted visitors visiting the documents hosting by the site during a time period; and (ii) a unique visit value based on a number of unique visitors among all counted visitors visiting the respective documents hosted by the site; determining at the server, for each site, a usage score from the frequency of visit value and the unique visit value for the site; and determining, at the server, an organization for the documents based on the usage scores for the respective sites hosting the documents. | 12. A computer-implemented method comprising: identifying at a server a plurality of sites, each of the sites hosting a respective plurality of documents; wherein the plurality of sites include at least one site visited by multiple distinct counted visitors during a time period; accessing, at the server, usage information associated with each of the plurality of sites hosting the documents, the usage information including, for each site: (i) a frequency of visit value based on a total number of times the site was visited by all counted visitors visiting the documents hosting by the site during a time period; and (ii) a unique visit value based on a number of unique visitors among all counted visitors visiting the respective documents hosted by the site; determining at the server, for each site, a usage score from the frequency of visit value and the unique visit value for the site; and determining, at the server, an organization for the documents based on the usage scores for the respective sites hosting the documents. 14. The computer-implemented method of claim 12 , wherein, for each site: the frequency of visit value is equal to the number of times the documents hosted by the site were visited during the time period; and the unique visit value is equal to the number of unique visitors to the documents hosted by the site during the time period. | 0.716354 |
9,893,941 | 23 | 24 | 23. A server for wireless communications, comprising: a transceiver; a memory configured to store instructions; and one or more processors communicatively coupled with the transceiver and the memory, wherein the one or more processors are configured to execute instructions to: receive information from a user equipment (UE), the information comprising a device identifier, a modem function executed by the UE, a selected hypothesis for the corresponding modem function, metrics for each feature associated with the corresponding modem function and state information, if the state information is available, in response to a trigger point associated with the modem function being met when executing the modem function; store the received information; run one or more learning algorithms based on the stored information to cluster the information and to select a unit sourced hypothesis and associated weights for the corresponding modem function when the UE provided the state information; run one or more learning algorithms based on crowd sourced information from other UEs to cluster the information and to select a unit sourced hypothesis and associated weights for the corresponding modem function when the state information was not provided by the UE; select the unit sourced hypothesis and associated weights based on the one or more learning algorithms; run one or more learning algorithms based on crowd sourced information from other UEs to cluster the information and to select a crowd sourced hypothesis and associated weights for the corresponding modem function when the UE provided the state information; select the crowd sourced hypothesis and associated weights based on the one or more learning algorithms; and send, to the UE, at least one of the selected unit sourced hypothesis and associated weights or the selected crowd sourced hypothesis and associated weights for the corresponding modem function. | 23. A server for wireless communications, comprising: a transceiver; a memory configured to store instructions; and one or more processors communicatively coupled with the transceiver and the memory, wherein the one or more processors are configured to execute instructions to: receive information from a user equipment (UE), the information comprising a device identifier, a modem function executed by the UE, a selected hypothesis for the corresponding modem function, metrics for each feature associated with the corresponding modem function and state information, if the state information is available, in response to a trigger point associated with the modem function being met when executing the modem function; store the received information; run one or more learning algorithms based on the stored information to cluster the information and to select a unit sourced hypothesis and associated weights for the corresponding modem function when the UE provided the state information; run one or more learning algorithms based on crowd sourced information from other UEs to cluster the information and to select a unit sourced hypothesis and associated weights for the corresponding modem function when the state information was not provided by the UE; select the unit sourced hypothesis and associated weights based on the one or more learning algorithms; run one or more learning algorithms based on crowd sourced information from other UEs to cluster the information and to select a crowd sourced hypothesis and associated weights for the corresponding modem function when the UE provided the state information; select the crowd sourced hypothesis and associated weights based on the one or more learning algorithms; and send, to the UE, at least one of the selected unit sourced hypothesis and associated weights or the selected crowd sourced hypothesis and associated weights for the corresponding modem function. 24. The server of claim 23 , wherein the received information further comprises weights associated with the selected hypothesis for the corresponding modem function. | 0.752994 |
8,280,831 | 8 | 9 | 8. The computer-implementable method of claim 1 , wherein if not in run-time, the method further comprises the steps of: creating new computer-generated knowledge statements; and storing the newly-created computer-generated knowledge statements in the memory storage device at the head of the generalization/analog case base. | 8. The computer-implementable method of claim 1 , wherein if not in run-time, the method further comprises the steps of: creating new computer-generated knowledge statements; and storing the newly-created computer-generated knowledge statements in the memory storage device at the head of the generalization/analog case base. 9. The computer-implementable method of claim 8 , wherein the step of creating new computer-generated knowledge statements comprises the steps of: selecting, by chance in proportion to the size of the base, either the case base or the generalization/analog base; using a 3-2-1 skew algorithm, selecting a knowledge statement having at least two antecedent features; deleting one of the antecedent features of the selected knowledge statement, wherein the resulting generalized knowledge statement does not contradict an existing knowledge statement in the selected base. | 0.893696 |
8,214,347 | 1 | 12 | 1. A method of operating a computer system environment for the processing of search results which match a search query to provide for sub-topic identification of the search results, the method comprising: receiving a search result; extracting snippets from said search result that contain said query; truncating snippets on an instance of a boundary token; identifying phrases within said snippets that include the query; comparing all said phrases to determine optimal phrases; and presenting said optimal phrases; wherein said comparing all said phrases comprises comparisons between a first phrase and a second phrase, wherein said comparisons between combinations of two phrases comprises: skipping comparisons where said first phrase starts with the query term and said second phrase ends with the query term; eliminating a first phrase that is a superstring of said second phrase if said first phrase has a lower frequency of occurrence than said second phrase; and eliminating said first phrase that is a substring of said second phrase if said first phrase has the same frequency of occurrence as said second phrase. | 1. A method of operating a computer system environment for the processing of search results which match a search query to provide for sub-topic identification of the search results, the method comprising: receiving a search result; extracting snippets from said search result that contain said query; truncating snippets on an instance of a boundary token; identifying phrases within said snippets that include the query; comparing all said phrases to determine optimal phrases; and presenting said optimal phrases; wherein said comparing all said phrases comprises comparisons between a first phrase and a second phrase, wherein said comparisons between combinations of two phrases comprises: skipping comparisons where said first phrase starts with the query term and said second phrase ends with the query term; eliminating a first phrase that is a superstring of said second phrase if said first phrase has a lower frequency of occurrence than said second phrase; and eliminating said first phrase that is a substring of said second phrase if said first phrase has the same frequency of occurrence as said second phrase. 12. A method according to claim 1 , wherein said method comprises: eliminating extracted phrases that contain one or more terms or expressions that are included in a predefined list of eliminator words and expressions. | 0.685879 |
9,383,977 | 17 | 20 | 17. A non-transitory computer-readable storage medium having executable computer program instructions for performing a method comprising: extracting, by a compiler description generator, information from an architecture description describing an architecture for an application specific instruction set processor (ASIP); receiving, by the compiler description generator via a source different than the architecture description, definitions for a plurality of abstract elements of a compiler that have no direct representative in the architecture description, the abstract elements comprising a non-terminal representing a data path in common with a plurality of compiler instructions; extracting, by the compiler description generator, a mapping of compiler rules to instructions included in the architecture description; and automatically generating, by the compiler description generator, a compiler description of the compiler for the architecture of the ASIP based on the extracted information, the received definitions for the plurality of abstract elements, and the extracted mapping, wherein a compiler generator generates the compiler based on the compiler description. | 17. A non-transitory computer-readable storage medium having executable computer program instructions for performing a method comprising: extracting, by a compiler description generator, information from an architecture description describing an architecture for an application specific instruction set processor (ASIP); receiving, by the compiler description generator via a source different than the architecture description, definitions for a plurality of abstract elements of a compiler that have no direct representative in the architecture description, the abstract elements comprising a non-terminal representing a data path in common with a plurality of compiler instructions; extracting, by the compiler description generator, a mapping of compiler rules to instructions included in the architecture description; and automatically generating, by the compiler description generator, a compiler description of the compiler for the architecture of the ASIP based on the extracted information, the received definitions for the plurality of abstract elements, and the extracted mapping, wherein a compiler generator generates the compiler based on the compiler description. 20. The computer-readable storage medium of claim 17 , wherein the extracted information describes a register of the architecture and through a graphical user interface, a user provides instructions to not use the register in generating the compiler description. | 0.686603 |
7,613,997 | 5 | 6 | 5. A computing system in accordance with claim 1 , wherein the act of determining that at least one group identifier is associated with the hierarchically-structured document comprises the following: an act of reading a pre-processor directive that indicates that the at least one group identifier is associated with the hierarchically-structured document. | 5. A computing system in accordance with claim 1 , wherein the act of determining that at least one group identifier is associated with the hierarchically-structured document comprises the following: an act of reading a pre-processor directive that indicates that the at least one group identifier is associated with the hierarchically-structured document. 6. A computing system in accordance with claim 5 , wherein the act of accessing a hierarchically-structured document comprises the following: an act of receiving an electronic message that includes the hierarchically-structured document; and an act of reading the hierarchically-structured document from the electronic message. | 0.881779 |
9,201,855 | 1 | 8 | 1. A method for arranging content in an electronic page, the method comprising: identifying a plurality of objects on the electronic page; forming a membrane for each identified object by setting a geometric shape around each identified object, wherein forming the membrane comprises generating guidelines for each identified object, wherein generating the guidelines further comprises associating a gravity distance with each of the generated guidelines; receiving an entry of an insertion point in the electronic page; and aligning the insertion point based on at least one of the guidelines, wherein aligning the insertion point based on at least one of the guidelines comprises: determining a plurality of guidelines from the generated guidelines having the gravity distance extending to the point of insertion, and selecting a dominant guideline from the plurality of guidelines, wherein selecting the dominant guideline comprises: determining a guideline hierarchy associated with each of the plurality of guidelines based on the gravity distance associated with each of the plurality of guidelines and a position of the insertion point relative to each of the plurality of guidelines, and selecting the dominant guideline from the plurality of guidelines based on the determined guideline hierarchy; and aligning the insertion point relative to the selected dominant guideline. | 1. A method for arranging content in an electronic page, the method comprising: identifying a plurality of objects on the electronic page; forming a membrane for each identified object by setting a geometric shape around each identified object, wherein forming the membrane comprises generating guidelines for each identified object, wherein generating the guidelines further comprises associating a gravity distance with each of the generated guidelines; receiving an entry of an insertion point in the electronic page; and aligning the insertion point based on at least one of the guidelines, wherein aligning the insertion point based on at least one of the guidelines comprises: determining a plurality of guidelines from the generated guidelines having the gravity distance extending to the point of insertion, and selecting a dominant guideline from the plurality of guidelines, wherein selecting the dominant guideline comprises: determining a guideline hierarchy associated with each of the plurality of guidelines based on the gravity distance associated with each of the plurality of guidelines and a position of the insertion point relative to each of the plurality of guidelines, and selecting the dominant guideline from the plurality of guidelines based on the determined guideline hierarchy; and aligning the insertion point relative to the selected dominant guideline. 8. The method of claim 1 , further comprising: forming a ghost membrane around the insertion point in the electronic page. | 0.767176 |
7,620,911 | 19 | 20 | 19. A system for collapsing a dialog window of an application in a computer system comprising: (a) a computer; (b) a display device connected to the computer; and (c) a currently active application executing on the computer, the application configured to: (i) display a complete dialog window of the currently active application on the display device; (ii) determine a location of a cursor with respect to the dialog window; (iii) display a collapsed version of the dialog window in response to the cursor moving from within the complete dialog window to outside of the complete dialog window without depressing a button of the dialog window, wherein the collapsed version of the dialog window consumes a smaller area of the display device than the complete dialog window and wherein the collapsed version of the dialog window comprises a title bar of the dialog window; and (iv) display the complete dialog window only in response to the cursor moving from outside of the collapsed version of the dialog window to within the title bar of the collapsed version of the dialog window without depressing a button of the dialog window. | 19. A system for collapsing a dialog window of an application in a computer system comprising: (a) a computer; (b) a display device connected to the computer; and (c) a currently active application executing on the computer, the application configured to: (i) display a complete dialog window of the currently active application on the display device; (ii) determine a location of a cursor with respect to the dialog window; (iii) display a collapsed version of the dialog window in response to the cursor moving from within the complete dialog window to outside of the complete dialog window without depressing a button of the dialog window, wherein the collapsed version of the dialog window consumes a smaller area of the display device than the complete dialog window and wherein the collapsed version of the dialog window comprises a title bar of the dialog window; and (iv) display the complete dialog window only in response to the cursor moving from outside of the collapsed version of the dialog window to within the title bar of the collapsed version of the dialog window without depressing a button of the dialog window. 20. The system of claim 19 wherein the collapsed version of the dialog window comprises a size that exactly encompasses a title of the dialog window and system buttons. | 0.874814 |
9,928,308 | 1 | 6 | 1. A method for dynamically modifying a content item on a per-request basis, the method being performed by data processing apparatus and comprising: receiving, from a user device, a content item request that includes context data specifying (i) a set of one or more attributes of a resource on which the content item will be presented and (ii) a set of one or more attributes of a user to which the content item will be presented; in response to receiving the content item request: identifying a given content item to provide in response to the content item request; identifying a set of templates that are eligible for use in generating variations of the given content item; filtering the set of templates based on the one or more attributes of the resource on which the content item will be presented, the filtering including removing, from the set of templates, one or more templates that are not eligible for use in generating content items for presentation with resources having the one or more attributes of the resource on which the content item will be presented; determining, for each particular template from the set of templates, a contextual performance measure that indicates a performance of content items that have been provided using the particular template and in response to content item requests having context data that matches the one or more attributes of the user; selecting, from the set of templates and based on the contextual performance measure of each template in the set of templates, a template for the given content item; creating a different formatted content item by populating the selected template with content for the given content item; and providing, to the user device and for presentation with the resource, the different formatted content item in response to the content item request. | 1. A method for dynamically modifying a content item on a per-request basis, the method being performed by data processing apparatus and comprising: receiving, from a user device, a content item request that includes context data specifying (i) a set of one or more attributes of a resource on which the content item will be presented and (ii) a set of one or more attributes of a user to which the content item will be presented; in response to receiving the content item request: identifying a given content item to provide in response to the content item request; identifying a set of templates that are eligible for use in generating variations of the given content item; filtering the set of templates based on the one or more attributes of the resource on which the content item will be presented, the filtering including removing, from the set of templates, one or more templates that are not eligible for use in generating content items for presentation with resources having the one or more attributes of the resource on which the content item will be presented; determining, for each particular template from the set of templates, a contextual performance measure that indicates a performance of content items that have been provided using the particular template and in response to content item requests having context data that matches the one or more attributes of the user; selecting, from the set of templates and based on the contextual performance measure of each template in the set of templates, a template for the given content item; creating a different formatted content item by populating the selected template with content for the given content item; and providing, to the user device and for presentation with the resource, the different formatted content item in response to the content item request. 6. The method of claim 1 , wherein the contextual performance measure for the particular template is based on a combination of (i) a first performance of content items that have been provided using the particular template in response to content item requests having context data that specifies the one or more attributes of the resource on which the content item will be presented and (ii) a second performance of content items that have been provided using the particular template in response to content item requests having context data that specifies the one or more attributes of user to which the content item will be presented. | 0.620048 |
6,144,939 | 1 | 4 | 1. A concatenative speech synthesizer, comprising: a database containing (a) demi-syllable waveform data associated with a plurality of demi-syllables and (b) filter parameter data associated with said plurality of demi-syllables; a unit selection system for extracting selected demi-syllable waveform data and filter parameters from said database that correspond to an input string to be synthesized; a waveform cross fade mechanism for joining pairs of extracted demi-syllable waveform data into syllable waveform signals; a filter parameter cross fade mechanism for defining a set of syllable-level filter data by interpolating said extracted filter parameters; and a filter module receptive of said set of syllable-level filter data and operative to process said syllable waveform signals to generate synthesized speech. | 1. A concatenative speech synthesizer, comprising: a database containing (a) demi-syllable waveform data associated with a plurality of demi-syllables and (b) filter parameter data associated with said plurality of demi-syllables; a unit selection system for extracting selected demi-syllable waveform data and filter parameters from said database that correspond to an input string to be synthesized; a waveform cross fade mechanism for joining pairs of extracted demi-syllable waveform data into syllable waveform signals; a filter parameter cross fade mechanism for defining a set of syllable-level filter data by interpolating said extracted filter parameters; and a filter module receptive of said set of syllable-level filter data and operative to process said syllable waveform signals to generate synthesized speech. 4. The synthesizer of claim 1 wherein said waveform cross fade mechanism performs a linear cross fade upon two demi-syllables over a predefined duration corresponding to a syllable. | 0.518617 |
7,809,536 | 1 | 2 | 1. A computer-based method of defining a model of an information processing system, comprising: defining a set of discovery instructions configured to discover first snapshot data via a computer communications network about hardware and/or software resources within said information processing system, including a client and a server computer system, wherein said model: defines a set of components of said information processing system, the set being a subset of said resources needed to deploy an instance of an application, defines properties of said components, and provides said discovery instructions to said application to discover first said snapshot data about a state of said properties; and executing on a computer system a software program configured to provide visualization and analysis of said information processing system based on said first snapshot data wherein said analysis includes at least one of: loading and comparing a second snapshot data to said first snapshot data, loading an analysis overlay and using said analysis overlay to evaluate said first snapshot data. | 1. A computer-based method of defining a model of an information processing system, comprising: defining a set of discovery instructions configured to discover first snapshot data via a computer communications network about hardware and/or software resources within said information processing system, including a client and a server computer system, wherein said model: defines a set of components of said information processing system, the set being a subset of said resources needed to deploy an instance of an application, defines properties of said components, and provides said discovery instructions to said application to discover first said snapshot data about a state of said properties; and executing on a computer system a software program configured to provide visualization and analysis of said information processing system based on said first snapshot data wherein said analysis includes at least one of: loading and comparing a second snapshot data to said first snapshot data, loading an analysis overlay and using said analysis overlay to evaluate said first snapshot data. 2. The method of claim 1 further comprising: defining a relationship between a model of the client computer system and a model of the server computer system, and providing an instruction configured to discover data about said relationship. | 0.777467 |
8,717,367 | 1 | 5 | 1. In a system comprising one or more computing devices, a method for automatically generating an audiovisual work, the method comprising: inferentially selecting one or more design animation modules from among a plurality of design animation modules to use to generate an audiovisual work based at least upon all of: (a) one or more first metadata values reflecting one or more detected visual characteristics of at least one of one or more digital visual media items, (b) one or more second metadata values reflecting one or more detected audio characteristics of at least one of one or more digital audio media items and comprising beat timing information pertaining to the at least one digital audio media item, and (c) one or more third metadata values associated with at least one of the plurality of design animation modules and comprising beat timing information pertaining to the at least one design animation module; wherein each design animation module of the plurality of design animation modules is an independent interchangeable unit that can be combined with other design animation modules of the plurality of design animation modules to form different audiovisual works; wherein the one or more selected design animation modules comprises the at least one design animation module; wherein inferentially selecting the at least one design animation module comprises comparing the beat timing information of the one or more second metadata values pertaining to the at least one digital audio media item to the beat timing information of the one or more third metadata values pertaining to the at least one design animation module; wherein the at least one design animation modules comprises a specification of an animation scene; assigning the at least one digital visual media item to the at least one design animation module including incorporating the at least one digital visual media item into the specification of the animation scene; and generating the audiovisual work using the one or more selected design animation modules, the one or more digital visual media items, and the one or more digital audio media items; wherein the method is performed by the one or more computing devices. | 1. In a system comprising one or more computing devices, a method for automatically generating an audiovisual work, the method comprising: inferentially selecting one or more design animation modules from among a plurality of design animation modules to use to generate an audiovisual work based at least upon all of: (a) one or more first metadata values reflecting one or more detected visual characteristics of at least one of one or more digital visual media items, (b) one or more second metadata values reflecting one or more detected audio characteristics of at least one of one or more digital audio media items and comprising beat timing information pertaining to the at least one digital audio media item, and (c) one or more third metadata values associated with at least one of the plurality of design animation modules and comprising beat timing information pertaining to the at least one design animation module; wherein each design animation module of the plurality of design animation modules is an independent interchangeable unit that can be combined with other design animation modules of the plurality of design animation modules to form different audiovisual works; wherein the one or more selected design animation modules comprises the at least one design animation module; wherein inferentially selecting the at least one design animation module comprises comparing the beat timing information of the one or more second metadata values pertaining to the at least one digital audio media item to the beat timing information of the one or more third metadata values pertaining to the at least one design animation module; wherein the at least one design animation modules comprises a specification of an animation scene; assigning the at least one digital visual media item to the at least one design animation module including incorporating the at least one digital visual media item into the specification of the animation scene; and generating the audiovisual work using the one or more selected design animation modules, the one or more digital visual media items, and the one or more digital audio media items; wherein the method is performed by the one or more computing devices. 5. The method of claim 1 , further comprising: responsive to successfully generating the audiovisual work, sending an e-mail notification to a user that the audiovisual work has been successfully generated. | 0.880925 |
7,912,718 | 1 | 3 | 1. A method for enhancing a speech database for speech synthesis, comprising: labeling audio files in a primary speech database and a secondary speech database, wherein the primary speech database and the secondary speech database are for the same language; enhancing the primary speech database by placing the labeled audio files from the secondary speech database into the primary speech database; and storing the enhanced primary speech database for use in unit selection concatenative speech synthesis. | 1. A method for enhancing a speech database for speech synthesis, comprising: labeling audio files in a primary speech database and a secondary speech database, wherein the primary speech database and the secondary speech database are for the same language; enhancing the primary speech database by placing the labeled audio files from the secondary speech database into the primary speech database; and storing the enhanced primary speech database for use in unit selection concatenative speech synthesis. 3. The method of claim 1 , wherein the enhanced primary speech database includes speech segments that are one of syllables, phones, half-phones, diphones, triphones, phonemes, half-phonemes, demi-syllables, and polyphones. | 0.830015 |
10,032,465 | 11 | 13 | 11. A system, comprising: at least one processor; and a memory storing executable instructions that, when executed by the at least one processor, causes the at least one processor to perform the following operations: extracting an audio track from an electronic media content; detecting, based on a speech model, a speaker segment within the extracted audio track; determining, by the processor, a first probability of the detected speaker segment being associated with an individual speaker by using both a speaker speech model and a non-speaker speech model, wherein the speaker speech model represents an individual speaker and the non-speaker speech model represents common characteristics from one or more speakers; determining a first ranking value of the electronic media content relative to other electronic media content based on the first probability of the detected speaker segment and probabilities for detected speaker segments within the other electronic media content; receiving a search query from a user; determining a second ranking value of the electronic media content based on relevancy between the query and the individual speaker; and determining a final ranking value of the electronic media content based on the first ranking value and the second ranking value. | 11. A system, comprising: at least one processor; and a memory storing executable instructions that, when executed by the at least one processor, causes the at least one processor to perform the following operations: extracting an audio track from an electronic media content; detecting, based on a speech model, a speaker segment within the extracted audio track; determining, by the processor, a first probability of the detected speaker segment being associated with an individual speaker by using both a speaker speech model and a non-speaker speech model, wherein the speaker speech model represents an individual speaker and the non-speaker speech model represents common characteristics from one or more speakers; determining a first ranking value of the electronic media content relative to other electronic media content based on the first probability of the detected speaker segment and probabilities for detected speaker segments within the other electronic media content; receiving a search query from a user; determining a second ranking value of the electronic media content based on relevancy between the query and the individual speaker; and determining a final ranking value of the electronic media content based on the first ranking value and the second ranking value. 13. The system of claim 11 , wherein detecting a speaker segment within the extracted audio track is based on a speech model and a non-speech model. | 0.791549 |
8,990,082 | 11 | 12 | 11. The method of claim 1 , further comprising determining whether the speech sample includes plagiarized material. | 11. The method of claim 1 , further comprising determining whether the speech sample includes plagiarized material. 12. The method of claim 11 , wherein determining whether the speech sample includes plagiarized material includes applying a plagiarism detection filter, wherein an output of the plagiarism detection filter is based upon an automatic-speech-recognizer confidence metric or a similarity of the speech sample to a particular text. | 0.873749 |
9,645,656 | 1 | 6 | 1. A method for text input of ambiguous input sequences entered by a device user, the method comprising: a primary process of receiving a user input on an input device having a plurality of selectable input items, each input item being associated with at least one character, an input sequence being generated in dependence of selection of input items, wherein the generated input sequence corresponds to the sequence of input items that have been selected, and wherein the generated input sequence has a textual interpretation of the characters associated with the input sequence, wherein the textual interpretation is ambiguous, and displaying on a display the textual interpretation; and a secondary process, initiated upon receiving an input associated with a delete-character command and comprising deleting a character of the textual interpretation, at a position thereof, wherein the deleted character corresponds to a first input item, and returning to the primary process where textual interpretations associated with the deleted character for said position are excluded, and displaying an updated textual interpretation, wherein the updated textual interpretation, at a position corresponding to the deleted character of the textual interpretation, has another character being associated with a second input item of the input device, wherein the second input item is in vicinity of the first input item; wherein the primary and secondary processes are performed until a user input associated with a confirm-text command is received. | 1. A method for text input of ambiguous input sequences entered by a device user, the method comprising: a primary process of receiving a user input on an input device having a plurality of selectable input items, each input item being associated with at least one character, an input sequence being generated in dependence of selection of input items, wherein the generated input sequence corresponds to the sequence of input items that have been selected, and wherein the generated input sequence has a textual interpretation of the characters associated with the input sequence, wherein the textual interpretation is ambiguous, and displaying on a display the textual interpretation; and a secondary process, initiated upon receiving an input associated with a delete-character command and comprising deleting a character of the textual interpretation, at a position thereof, wherein the deleted character corresponds to a first input item, and returning to the primary process where textual interpretations associated with the deleted character for said position are excluded, and displaying an updated textual interpretation, wherein the updated textual interpretation, at a position corresponding to the deleted character of the textual interpretation, has another character being associated with a second input item of the input device, wherein the second input item is in vicinity of the first input item; wherein the primary and secondary processes are performed until a user input associated with a confirm-text command is received. 6. The method of claim 1 , wherein the secondary process includes storing the deleted character and position of the deleted character in a temporary data structure, and the primary process includes accessing the temporary data structure upon performing the textual interpretation, wherein the temporary data structure is discarded when the confirm-text command is received. | 0.803062 |
7,949,574 | 1 | 5 | 1. A system for an enterprise having multiple business units to communicate with a user over multiple channels, the system comprising: channel interfaces respectively coupled to the multiple channels; a knowledge management system coupled to the channel interfaces, the knowledge management system comprising: an offer database, the offer database storing potential offers to the user, the potential offers being supplied from the multiple business units within the enterprise; a user profile database, the user profile database storing a user profile with respect to the user; and a decision engine coupled to the offer database and the user profile database, the decision engine implementing computer processing components for making a decision as to which of the potential offers to present to the user and which of the multiple channels over which to make the presentation. | 1. A system for an enterprise having multiple business units to communicate with a user over multiple channels, the system comprising: channel interfaces respectively coupled to the multiple channels; a knowledge management system coupled to the channel interfaces, the knowledge management system comprising: an offer database, the offer database storing potential offers to the user, the potential offers being supplied from the multiple business units within the enterprise; a user profile database, the user profile database storing a user profile with respect to the user; and a decision engine coupled to the offer database and the user profile database, the decision engine implementing computer processing components for making a decision as to which of the potential offers to present to the user and which of the multiple channels over which to make the presentation. 5. The system of claim 1 , wherein the knowledge management system further comprises a plurality of selected ones of the following: a contact data base, workflow database, security database, audit database, customer preference database, customer entitlement database, content database, application database, data warehouse, data mart, customer profile database, segmentation database, business rules database, campaign rules database and product/service/information database. | 0.525 |
9,852,219 | 7 | 8 | 7. The method of claim 3 , wherein the at least one group is indicated in a sample group description box. | 7. The method of claim 3 , wherein the at least one group is indicated in a sample group description box. 8. The method of claim 7 , wherein the at least one group of one or more samples of the streamed data is indicated in a sample group description box for the timed metadata track through associating the at least one group of one or more samples of the streamed data with respective timed metadata samples in the timed metadata track. | 0.885832 |
8,392,446 | 12 | 17 | 12. A system for providing a plurality of vector terms in response to a search query comprising: one or more client devices connected to a network; a search provider connected to said network; a search server operative to receive search queries from said client devices and to retrieve links to one or more content items from a content data store; a vector term generator operative to generate one or more first term vectors corresponding to said content items, to generate a plurality of vector terms from said first terms vectors, and to select one or more vector terms not exceeding a threshold number of vector terms from said plurality of vector terms, wherein the threshold is determined as a percentage of the total vector terms; and said search server further operative to combine said links to one or more content items with said vector terms to form a search results page, wherein the links to said content items provided in a first section of the search results page and said vector terms provided in a second section of the search results page, the search results page comprising a plurality of search results and an assistance panel, the assistance panel comprising at least a suggested search term component comprising suggested search terms and a vector term component comprising the selected vector terms, said search server further operative to receive one or more selected given vector terms and to execute, based on the selected one or more given vector terms, a second search query asynchronously selecting a given vector term, the server operative to execute a second search query asynchronously; to generate one or more of second term vectors corresponding to said second query and select one or more vector terms from said one or more second term vectors; and to update the search results page without programmatically reloading the search results page, where reloading includes receiving an entirely new search results page, and wherein to update the search results page comprises updating the first section of the search results page to include links to content items associated with the second search query and updating the second section to include the one or more vector terms selected from said second term vectors. | 12. A system for providing a plurality of vector terms in response to a search query comprising: one or more client devices connected to a network; a search provider connected to said network; a search server operative to receive search queries from said client devices and to retrieve links to one or more content items from a content data store; a vector term generator operative to generate one or more first term vectors corresponding to said content items, to generate a plurality of vector terms from said first terms vectors, and to select one or more vector terms not exceeding a threshold number of vector terms from said plurality of vector terms, wherein the threshold is determined as a percentage of the total vector terms; and said search server further operative to combine said links to one or more content items with said vector terms to form a search results page, wherein the links to said content items provided in a first section of the search results page and said vector terms provided in a second section of the search results page, the search results page comprising a plurality of search results and an assistance panel, the assistance panel comprising at least a suggested search term component comprising suggested search terms and a vector term component comprising the selected vector terms, said search server further operative to receive one or more selected given vector terms and to execute, based on the selected one or more given vector terms, a second search query asynchronously selecting a given vector term, the server operative to execute a second search query asynchronously; to generate one or more of second term vectors corresponding to said second query and select one or more vector terms from said one or more second term vectors; and to update the search results page without programmatically reloading the search results page, where reloading includes receiving an entirely new search results page, and wherein to update the search results page comprises updating the first section of the search results page to include links to content items associated with the second search query and updating the second section to include the one or more vector terms selected from said second term vectors. 17. The system of claim 12 , wherein the execution of a second search query results in one or more links to second content items and a second set of vector terms forming a second result page. | 0.820826 |
9,633,652 | 1 | 8 | 1. A method of speaker dependent speech recognition, comprising: building a universal background model (UBM) for a user responsive to unknown speech from only the user; adapting the universal background model (UBM) to build a single Gaussian Mixture Model (GMM) responsive to a registration code phrase spoken by the user and using the single GMM to generate a code-phrase model (CPM) for the user; generating a longest common sequence (LCS) template for the user from the code-phrase model (CPM), wherein the LCS template is represented by a sequence of an index of a best performing component of the single GMM; utilizing the universal background model (UBM), code-phrase model (CPM) and longest common sequence (LCS) template to determine whether the user is an authorized user and has spoken the registration code phrase, the utilizing including, capturing a test code phrase; accepting the test code phrase as being spoken by the authorized user when the log likelihood ratio between the code-phrase model (CPM) and the universal background model (UBM) is positive; and comparing the Longest Common Sequence (LCS) template with a test code-phrase template for the captured test code phrase. | 1. A method of speaker dependent speech recognition, comprising: building a universal background model (UBM) for a user responsive to unknown speech from only the user; adapting the universal background model (UBM) to build a single Gaussian Mixture Model (GMM) responsive to a registration code phrase spoken by the user and using the single GMM to generate a code-phrase model (CPM) for the user; generating a longest common sequence (LCS) template for the user from the code-phrase model (CPM), wherein the LCS template is represented by a sequence of an index of a best performing component of the single GMM; utilizing the universal background model (UBM), code-phrase model (CPM) and longest common sequence (LCS) template to determine whether the user is an authorized user and has spoken the registration code phrase, the utilizing including, capturing a test code phrase; accepting the test code phrase as being spoken by the authorized user when the log likelihood ratio between the code-phrase model (CPM) and the universal background model (UBM) is positive; and comparing the Longest Common Sequence (LCS) template with a test code-phrase template for the captured test code phrase. 8. The method of claim 1 wherein the code-phrase model (CPM) is continuously updated using captured speech frames that have a high confidence value of belonging to the registered code phrase. | 0.836752 |
8,099,287 | 10 | 15 | 10. A method comprising: operating at least one processor programmed to perform ascertaining that an utterance to be associated with a user-defined speech command is acoustically similar to an existing speech command; automatically determining at least one substitute for the utterance; and presenting the substitute as an alternative to the utterance. | 10. A method comprising: operating at least one processor programmed to perform ascertaining that an utterance to be associated with a user-defined speech command is acoustically similar to an existing speech command; automatically determining at least one substitute for the utterance; and presenting the substitute as an alternative to the utterance. 15. The method of claim 10 , wherein the at least one substitute comprises a first substitute and a second substitute, said determining step further comprises: automatically determining the first substitute; ascertaining that the first substitute is acoustically similar to an existing speech command; automatically determining the second substitute; and ascertaining that the second substitute is not acoustically similar to an existing speech command, wherein the second substitute is the substitute presented in the presenting step. | 0.605457 |
9,507,891 | 2 | 5 | 2. The computing system of claim 1 , wherein the automatically generating the model and the automatically generating the interface are for a simulation flow supported by the environment, and wherein in response to a request to create synthesized versions of the one or more user-defined modules the environment performs a synthesis flow wherein: automatically generating an interface further comprises synthesizing the interface at least by converting the set of access methods to the pipeline to a set of ports in a hardware description language; and performing simulations further comprises performing simulations on the one or more user-defined modules with workloads using the automatically generated model of the pipeline and the automatically generated model of the interface to determine one or more design evaluation metrics of the one or more user-defined modules. | 2. The computing system of claim 1 , wherein the automatically generating the model and the automatically generating the interface are for a simulation flow supported by the environment, and wherein in response to a request to create synthesized versions of the one or more user-defined modules the environment performs a synthesis flow wherein: automatically generating an interface further comprises synthesizing the interface at least by converting the set of access methods to the pipeline to a set of ports in a hardware description language; and performing simulations further comprises performing simulations on the one or more user-defined modules with workloads using the automatically generated model of the pipeline and the automatically generated model of the interface to determine one or more design evaluation metrics of the one or more user-defined modules. 5. The computing system of claim 2 , wherein interface methods and parameter information is preserved in names and types of hardware ports converted from interface methods accessed in modules. | 0.932107 |
7,640,531 | 11 | 14 | 11. A system for managing a project to be developed, comprising: an interface control document stored on a computer-readable storage medium modeling a first set of interactions between a plurality of applications through one or more sequence diagrams, the plurality of applications including a plurality of software components, classes, or objects, and the first set of interactions identifying functionality of the project; an application model document stored on a computer-readable storage medium modeling a second set of interactions within at least one of the plurality of applications through one or more sequence diagrams, the second set of interactions identifying additional functionality of the project, wherein the first set of interactions and the second set of interactions include a plurality of types of interactions, the plurality of types of interactions includes two or more of group consisting of internal logical files types of interactions, external interfaces files types of interactions, external inputs types of interactions, external outputs types of interactions, and external queries types of interactions; a baseline document stored on a computer-readable storage medium identifying existing interactions between the plurality of applications and existing interactions within the plurality of applications; an estimator component stored on a computer-readable storage medium that accesses the interface control document, the application model document, and baseline document and counts a number of business operation points based on the interactions identified in the first and second sets of interactions not identified in the baseline document of existing interactions, wherein a first count of the number of business operation points based on the interactions identified in the interface control document is weighted differently relative to a second count of the number of business operation points based on the interactions in the application model document, and wherein the business operation points include interactions between applications and interactions within an application between components of the application, but do not include the components of the applications themselves or interactions with external non-application entities. | 11. A system for managing a project to be developed, comprising: an interface control document stored on a computer-readable storage medium modeling a first set of interactions between a plurality of applications through one or more sequence diagrams, the plurality of applications including a plurality of software components, classes, or objects, and the first set of interactions identifying functionality of the project; an application model document stored on a computer-readable storage medium modeling a second set of interactions within at least one of the plurality of applications through one or more sequence diagrams, the second set of interactions identifying additional functionality of the project, wherein the first set of interactions and the second set of interactions include a plurality of types of interactions, the plurality of types of interactions includes two or more of group consisting of internal logical files types of interactions, external interfaces files types of interactions, external inputs types of interactions, external outputs types of interactions, and external queries types of interactions; a baseline document stored on a computer-readable storage medium identifying existing interactions between the plurality of applications and existing interactions within the plurality of applications; an estimator component stored on a computer-readable storage medium that accesses the interface control document, the application model document, and baseline document and counts a number of business operation points based on the interactions identified in the first and second sets of interactions not identified in the baseline document of existing interactions, wherein a first count of the number of business operation points based on the interactions identified in the interface control document is weighted differently relative to a second count of the number of business operation points based on the interactions in the application model document, and wherein the business operation points include interactions between applications and interactions within an application between components of the application, but do not include the components of the applications themselves or interactions with external non-application entities. 14. The system of claim 11 further including a database containing a historical information including a level of effort expended to deliver a plurality of business operation points providing functionality to a plurality of completed projects and wherein the estimator component accesses the database and estimates a level of effort of the project based on the count and on the historical information. | 0.501247 |
9,135,330 | 6 | 8 | 6. A computer-implemented method comprising: receiving a query expansion source, a query expansion candidate, and feature data for the query expansion source and the query expansion candidate, the feature data comprising information for a plurality of features, the plurality of features comprising a measure of price divergence for the query expansion source and the query expansion candidate, the measure of price divergence being a measure of similarity between a distribution of prices of item listings returned as results for a search on the query expansion source and a distribution of prices of item listings returned as results for a search on the query expansion candidate, and the measure of price divergence comprising a Student's t-statistic; determining whether the query expansion candidate qualifies as an expansion of the query expansion source based on an analysis of the information for the plurality of features; and assigning the query expansion candidate as an expanded query of the query expansion source in a query expansion dictionary in response to a determination that the query expansion candidate qualifies as an expansion of the query expansion source. | 6. A computer-implemented method comprising: receiving a query expansion source, a query expansion candidate, and feature data for the query expansion source and the query expansion candidate, the feature data comprising information for a plurality of features, the plurality of features comprising a measure of price divergence for the query expansion source and the query expansion candidate, the measure of price divergence being a measure of similarity between a distribution of prices of item listings returned as results for a search on the query expansion source and a distribution of prices of item listings returned as results for a search on the query expansion candidate, and the measure of price divergence comprising a Student's t-statistic; determining whether the query expansion candidate qualifies as an expansion of the query expansion source based on an analysis of the information for the plurality of features; and assigning the query expansion candidate as an expanded query of the query expansion source in a query expansion dictionary in response to a determination that the query expansion candidate qualifies as an expansion of the query expansion source. 8. The method of claim 6 , wherein the plurality of features comprises a measure of co-occurrence for the query expansion source and the query expansion candidate in item listings of an e-commerce website. | 0.838328 |
8,966,360 | 1 | 5 | 1. In a computer-based system, a method of editing a time-based media program that includes recorded speech, the method comprising: receiving an augmented transcript of the recorded speech in a mark-up language format, wherein the augmented transcript includes text of a transcript of the recorded speech and timing information that, for each of a plurality of words of the text within the transcript, associates that text word with a temporal location of recorded speech within the time-based media program that corresponds to that text word; in a user interface displaying a transcript text view of the augmented transcript, editing the transcript text of the augmented transcript, wherein the editing comprises selecting one or more spans of text words, copying a span of the text words, and pasting a span of the text words into the transcript text, wherein the association of the timing information with each of the plurality of words within the transcript is preserved during the editing; and outputting the edited augmented transcript, wherein the edited augmented transcript, when received and processed by a time-based media editing system, is capable of causing the time-based media editing system to generate an edited version of the time-based media program that includes time-based media in a temporal sequence that corresponds to the transcript text of the edited augmented transcript. | 1. In a computer-based system, a method of editing a time-based media program that includes recorded speech, the method comprising: receiving an augmented transcript of the recorded speech in a mark-up language format, wherein the augmented transcript includes text of a transcript of the recorded speech and timing information that, for each of a plurality of words of the text within the transcript, associates that text word with a temporal location of recorded speech within the time-based media program that corresponds to that text word; in a user interface displaying a transcript text view of the augmented transcript, editing the transcript text of the augmented transcript, wherein the editing comprises selecting one or more spans of text words, copying a span of the text words, and pasting a span of the text words into the transcript text, wherein the association of the timing information with each of the plurality of words within the transcript is preserved during the editing; and outputting the edited augmented transcript, wherein the edited augmented transcript, when received and processed by a time-based media editing system, is capable of causing the time-based media editing system to generate an edited version of the time-based media program that includes time-based media in a temporal sequence that corresponds to the transcript text of the edited augmented transcript. 5. The method of claim 1 , wherein the editing step is performed using text editing software. | 0.935237 |
9,275,331 | 1 | 3 | 1. A system for classifying documents, the system comprising: a processor; and a non-transitory computer readable storage medium having a computer readable program, the computer readable program executable by the processor to: before a new rule is added to a plurality of rules: applying the new rule to a plurality of previously classified documents; determining an application of the new rule results in misclassification of a given number of the plurality of previously classified documents; assigning to the new rule a damping factor based on the given number of misclassifications; adding the new rule to the plurality of rules with the assigned damping factor; classifying a document from among a plurality of documents in a first class, in response to applying statistical analysis to data associated with the document; classifying the document in a second class, in response to applying the new rule to the document according to the damping factor assigned to the new rule; and recalculating damping factors assigned to the plurality of rules, comprising: classifying the plurality of documents by applying the plurality of rules to the plurality of documents according to the damping factors assigned to the plurality of rules; inserting into a status matrix statuses of the classification of the plurality of documents; tallying the statuses in a column of the status matrix corresponding to a given rule; and recalculating the damping factor for the given rule based on the tallied statuses for the given rule, wherein each cell (Cij) of the status matrix comprises a status of the classification of a given document (i) of the plurality of documents with respect to a given rule (j) of the plurality of rules, wherein the statuses comprise: X=the classification of the given document (i) improved by the given rule (j); Y=the classification of the given document (i) spoiled by given rule (j); and Z=the classification of the given document (i) unaffected by the given rule (j). | 1. A system for classifying documents, the system comprising: a processor; and a non-transitory computer readable storage medium having a computer readable program, the computer readable program executable by the processor to: before a new rule is added to a plurality of rules: applying the new rule to a plurality of previously classified documents; determining an application of the new rule results in misclassification of a given number of the plurality of previously classified documents; assigning to the new rule a damping factor based on the given number of misclassifications; adding the new rule to the plurality of rules with the assigned damping factor; classifying a document from among a plurality of documents in a first class, in response to applying statistical analysis to data associated with the document; classifying the document in a second class, in response to applying the new rule to the document according to the damping factor assigned to the new rule; and recalculating damping factors assigned to the plurality of rules, comprising: classifying the plurality of documents by applying the plurality of rules to the plurality of documents according to the damping factors assigned to the plurality of rules; inserting into a status matrix statuses of the classification of the plurality of documents; tallying the statuses in a column of the status matrix corresponding to a given rule; and recalculating the damping factor for the given rule based on the tallied statuses for the given rule, wherein each cell (Cij) of the status matrix comprises a status of the classification of a given document (i) of the plurality of documents with respect to a given rule (j) of the plurality of rules, wherein the statuses comprise: X=the classification of the given document (i) improved by the given rule (j); Y=the classification of the given document (i) spoiled by given rule (j); and Z=the classification of the given document (i) unaffected by the given rule (j). 3. The system of claim 1 , wherein the recalculated damping factor for the given rule (j)=(number of X's in column j of the status matrix)/(sum of the number of X's and Y's in column j). | 0.701923 |
8,112,713 | 1 | 5 | 1. A method for interactively collaborating within a secure, server-based community, comprising: a plurality of members; at least one network of members that excludes at least one member of the secure, server-based community, whereby members of said network share access to a set of documents in a secured remote environment, such that members not belonging to said network do not have access to said set of documents; a document management tool for managing documents comprised of a document filing tool and at least one software application chosen from a group consisting of a message application, an email application, word processor application, a spreadsheet application, a presentations application and an images application, whereby the document management tool enables said members of said network to remotely manage documents of said set of documents, wherein: the document filing tool is comprised of at least one shared folder shared by said members of said network, and at least one alias folder accessible to a first member of said network and not accessible to at least one other member of said network, wherein the alias folder is a subfolder of the at least one shared folder, and wherein a first member moving a document from the at least one shared folder to the alias folder causes the document to appear in the alias folder as viewed by the first member but to remain in the at least one shared folder as viewed by the at least one other member. | 1. A method for interactively collaborating within a secure, server-based community, comprising: a plurality of members; at least one network of members that excludes at least one member of the secure, server-based community, whereby members of said network share access to a set of documents in a secured remote environment, such that members not belonging to said network do not have access to said set of documents; a document management tool for managing documents comprised of a document filing tool and at least one software application chosen from a group consisting of a message application, an email application, word processor application, a spreadsheet application, a presentations application and an images application, whereby the document management tool enables said members of said network to remotely manage documents of said set of documents, wherein: the document filing tool is comprised of at least one shared folder shared by said members of said network, and at least one alias folder accessible to a first member of said network and not accessible to at least one other member of said network, wherein the alias folder is a subfolder of the at least one shared folder, and wherein a first member moving a document from the at least one shared folder to the alias folder causes the document to appear in the alias folder as viewed by the first member but to remain in the at least one shared folder as viewed by the at least one other member. 5. The method of claim 1 , wherein at least one other member of said network may create at least one alias folder, wherein the at least one alias folder of said at least one other member is distinct from the at least one alias folder of the first member and wherein the first member does not see the at least one alias folder of the at least one other member, and wherein the at least one other member does not see the at least one alias folder of the first member. | 0.65859 |
7,982,802 | 13 | 14 | 13. A method of recording a text subtitle stream in a data storage, the method comprising: recording the text subtitle stream downloaded from an external source, the text subtitle stream including a first segment and a second segment, the first segment including region style information including at least one region style to be applied to a subtitle region including text data, the second segment including the text data to be displayed in the subtitle region and inline style information including at least one font related style to be applied to the text data, wherein the region style information and the inline style information are used for a rendering operation that converts the text data into bitmap data, the recording records a first clip information file including attribute information corresponding to a text subtitle stream file including the text subtitle stream and a second clip information file including attribute information corresponding to an AV stream file including an AV stream, the text subtitle stream file and the AV stream file have one-to-one correspondence with the first and the second clip information files, respectively, wherein reproduction of the AV stream is managed by a playitem, and reproduction of the text subtitle stream is managed by a subplayitem, wherein the playitem indicates beginning and ending times for reproduction of the AV stream, and the subplayitem indicates beginning and ending times for reproduction of the text subtitle stream, wherein the AV stream file and the text subtitle stream file are separate files. | 13. A method of recording a text subtitle stream in a data storage, the method comprising: recording the text subtitle stream downloaded from an external source, the text subtitle stream including a first segment and a second segment, the first segment including region style information including at least one region style to be applied to a subtitle region including text data, the second segment including the text data to be displayed in the subtitle region and inline style information including at least one font related style to be applied to the text data, wherein the region style information and the inline style information are used for a rendering operation that converts the text data into bitmap data, the recording records a first clip information file including attribute information corresponding to a text subtitle stream file including the text subtitle stream and a second clip information file including attribute information corresponding to an AV stream file including an AV stream, the text subtitle stream file and the AV stream file have one-to-one correspondence with the first and the second clip information files, respectively, wherein reproduction of the AV stream is managed by a playitem, and reproduction of the text subtitle stream is managed by a subplayitem, wherein the playitem indicates beginning and ending times for reproduction of the AV stream, and the subplayitem indicates beginning and ending times for reproduction of the text subtitle stream, wherein the AV stream file and the text subtitle stream file are separate files. 14. The method of claim 13 , wherein the at least one region style is specified by at least one of a region position, a region size, a region background color, a text position, a text flow, a text alignment, a line space, a font identification, a font style, a font size, and a font color defined in the region style information. | 0.82666 |
8,484,245 | 14 | 20 | 14. An apparatus comprising: a digital processing device configured to: generate a hierarchical classifier for a taxonomy of hierarchically organized categories wherein each category is represented by one or more category descriptors, the digital processing device generating the hierarchical classifier by a method including: constructing queries for categories of the taxonomy of hierarchically organized categories, the query constructed for a category c of the taxonomy including a query component constructed from one or more textual descriptors of the category c and at least one of a query component constructed from one or more textual descriptors of an ancestor category of the category c and a query component constructed from textual descriptors of one or more descendant categories of the category c; querying a documents database using the constructed queries to retrieve pseudo-relevant documents; and extracting category profiles for the categories of the taxonomy from at least the pseudo-relevant documents by inferring a hierarchical topic model representing the taxonomy; and classify an input document different from the pseudo-relevant documents using the generated hierarchical classifier. | 14. An apparatus comprising: a digital processing device configured to: generate a hierarchical classifier for a taxonomy of hierarchically organized categories wherein each category is represented by one or more category descriptors, the digital processing device generating the hierarchical classifier by a method including: constructing queries for categories of the taxonomy of hierarchically organized categories, the query constructed for a category c of the taxonomy including a query component constructed from one or more textual descriptors of the category c and at least one of a query component constructed from one or more textual descriptors of an ancestor category of the category c and a query component constructed from textual descriptors of one or more descendant categories of the category c; querying a documents database using the constructed queries to retrieve pseudo-relevant documents; and extracting category profiles for the categories of the taxonomy from at least the pseudo-relevant documents by inferring a hierarchical topic model representing the taxonomy; and classify an input document different from the pseudo-relevant documents using the generated hierarchical classifier. 20. The apparatus as set forth in claim 14 , wherein the hierarchical topic model comprises a mixture model in which a document is represented as a mixture of the category profiles of a plurality of categories and their ancestor categories. | 0.802632 |
8,983,900 | 3 | 4 | 3. The system of claim 1 , wherein the method further comprises: determining a business object among the tables that identifies a main table among the tables which provides information for linking the related tables. | 3. The system of claim 1 , wherein the method further comprises: determining a business object among the tables that identifies a main table among the tables which provides information for linking the related tables. 4. The system of claim 3 , wherein the business object is a representation of an intelligible business or non-business entity, such as an account, an order, employee, an invoice or a financial report. | 0.87013 |
9,519,872 | 10 | 13 | 10. A method for determining a business ontology, the method comprising acts of: performing an analysis by a computer system of a plurality of business documents, wherein the analysis comprises acts of: establishing an analysis scope that includes the plurality of business documents; determining a plurality of sentences within the plurality of business documents within the analysis scope, including separating the sentences for analysis; identifying terms and associations between terms within each separated sentence of the plurality of sentences, including determining a proximity between at least two of the terms within at least one sentence of the separated sentences, the proximity including a sentence proximity association for terms of the identified terms occurring in the same sentence but not in a same term group, a term proximity association for identifying actions acted upon terms of the identified terms by other terms, and a document proximity association for all verbs in the same business document of the plurality of business documents; analyzing the terms and associations including the sentence proximity association, the term proximity association, and the document proximity association; after analyzing the terms and associations, identifying frequently-used terms and associations within the plurality of sentences used most within the scope; and determining a business ontology based on the identified frequently-used terms and associations within the plurality of sentences among the plurality of business documents. | 10. A method for determining a business ontology, the method comprising acts of: performing an analysis by a computer system of a plurality of business documents, wherein the analysis comprises acts of: establishing an analysis scope that includes the plurality of business documents; determining a plurality of sentences within the plurality of business documents within the analysis scope, including separating the sentences for analysis; identifying terms and associations between terms within each separated sentence of the plurality of sentences, including determining a proximity between at least two of the terms within at least one sentence of the separated sentences, the proximity including a sentence proximity association for terms of the identified terms occurring in the same sentence but not in a same term group, a term proximity association for identifying actions acted upon terms of the identified terms by other terms, and a document proximity association for all verbs in the same business document of the plurality of business documents; analyzing the terms and associations including the sentence proximity association, the term proximity association, and the document proximity association; after analyzing the terms and associations, identifying frequently-used terms and associations within the plurality of sentences used most within the scope; and determining a business ontology based on the identified frequently-used terms and associations within the plurality of sentences among the plurality of business documents. 13. The method according to claim 10 , further comprising an act of determining an association by a proximity between at least two of the terms within at least one document. | 0.571782 |
8,869,015 | 1 | 6 | 1. A method of rendering a document on a computerized device with language-related content in accordance with a selected language, comprising: identifying a first language content identifier in the document; generating a secure request using one or more of a public encryption key of a public/private key pair and secure authorization credentials; providing the secure request for language-related content to a language server, the language-related content being associated with a second language content identifier; receiving, from the language server in a secure response that is responsive to the secure request, the language-related content for which the second language content identifier corresponds to the first language content identifier; obtaining the language-related content from the secure response by one or more of decrypting the secure response and authenticating a digital signature associated with the secure response; and inserting at least a portion of the language-related content into the document at a location associated with the first language content identifier. | 1. A method of rendering a document on a computerized device with language-related content in accordance with a selected language, comprising: identifying a first language content identifier in the document; generating a secure request using one or more of a public encryption key of a public/private key pair and secure authorization credentials; providing the secure request for language-related content to a language server, the language-related content being associated with a second language content identifier; receiving, from the language server in a secure response that is responsive to the secure request, the language-related content for which the second language content identifier corresponds to the first language content identifier; obtaining the language-related content from the secure response by one or more of decrypting the secure response and authenticating a digital signature associated with the secure response; and inserting at least a portion of the language-related content into the document at a location associated with the first language content identifier. 6. The method according to claim 1 , further comprising: providing the secure request to the language server from a server where the at least a portion of the language-related content is to be inserted into the document. | 0.805654 |
8,371,857 | 1 | 2 | 1. A system for teaching a user pronunciation, comprising: a voice portal arrangement; a communication arrangement adapted to be coupled with the voice portal arrangement; an application server adapted to be coupled with the voice portal arrangement; and a geo-server for determining a location; wherein: the geo-server determines a location of the user and a dominant language and a regional dialect prevailing at the determined location of the user; the voice portal arrangement provides the user a prompt in the determined regional dialect of the dominant language, and compares at least one word spoken by the user in response to the prompt to determine a confidence lever; the at least one word spoken by the user is associated in memory with a plurality of valid pronunciations; and one of the plurality of valid pronunciations used by the user for the at least one word spoken by the user is determined to be incorrect based on the regional dialect. | 1. A system for teaching a user pronunciation, comprising: a voice portal arrangement; a communication arrangement adapted to be coupled with the voice portal arrangement; an application server adapted to be coupled with the voice portal arrangement; and a geo-server for determining a location; wherein: the geo-server determines a location of the user and a dominant language and a regional dialect prevailing at the determined location of the user; the voice portal arrangement provides the user a prompt in the determined regional dialect of the dominant language, and compares at least one word spoken by the user in response to the prompt to determine a confidence lever; the at least one word spoken by the user is associated in memory with a plurality of valid pronunciations; and one of the plurality of valid pronunciations used by the user for the at least one word spoken by the user is determined to be incorrect based on the regional dialect. 2. The system of claim 1 , wherein the communication arrangement is adapted to be wirelessly coupled with the voice portal server. | 0.898754 |
9,886,726 | 10 | 12 | 10. A computer system for detecting social networking spam, the system comprising: a computer-readable storage medium storing executable software modules, comprising: a selection module for: selecting a central member who is a user of a social networking environment; measuring degrees of association between the central member and other users of the social networking environment; and defining a social networking group containing the central member and other members, where the other members are a subset of the other users of the social networking environment selected responsive to the other users' degrees of association with the central member; an identification module for identifying that a new entry has been posted on a blog of the central member; an analysis module for: analyzing the new entry in comparison to a group usage profile for the social networking group, the group usage profile indicating a pattern of publishing activity of the members of the social networking group in posting information on blogs of other members of the social networking group over a period of time; responsive to the analysis in comparison to the group usage profile indicating that the new entry deviates from the pattern of publishing activity, analyzing the new entry using a global usage profile comprising a spam usage profile to determine whether the new entry matches a spam signature representing known spam; and a spam detection module for detecting that the new entry is spam, responsive to analyzing the new entry using the global usage profile; and a pattern module for determining a pattern of global publishing activity of users in posting information on blogs of other users in the social networking environment; wherein the global usage profile is based on the determined pattern of global publishing activity; and a processor configured to execute the software modules stored by the computer readable storage medium. | 10. A computer system for detecting social networking spam, the system comprising: a computer-readable storage medium storing executable software modules, comprising: a selection module for: selecting a central member who is a user of a social networking environment; measuring degrees of association between the central member and other users of the social networking environment; and defining a social networking group containing the central member and other members, where the other members are a subset of the other users of the social networking environment selected responsive to the other users' degrees of association with the central member; an identification module for identifying that a new entry has been posted on a blog of the central member; an analysis module for: analyzing the new entry in comparison to a group usage profile for the social networking group, the group usage profile indicating a pattern of publishing activity of the members of the social networking group in posting information on blogs of other members of the social networking group over a period of time; responsive to the analysis in comparison to the group usage profile indicating that the new entry deviates from the pattern of publishing activity, analyzing the new entry using a global usage profile comprising a spam usage profile to determine whether the new entry matches a spam signature representing known spam; and a spam detection module for detecting that the new entry is spam, responsive to analyzing the new entry using the global usage profile; and a pattern module for determining a pattern of global publishing activity of users in posting information on blogs of other users in the social networking environment; wherein the global usage profile is based on the determined pattern of global publishing activity; and a processor configured to execute the software modules stored by the computer readable storage medium. 12. The system of claim 10 , further comprising a rendering module for rendering on a client the blog without the new entry that was detected to be spam or with the new entry consolidated with other similar entries detected to be spam. | 0.684987 |
7,752,557 | 1 | 8 | 1. A data processing system for visually coding search results, the data processing system comprising: a display device to display data; at least one processor; and a memory coupled to the at least one processor storing computer readable instructions executable by the at least one processor, the computer readable instructions when executed by the at least one processor configuring the data processing system to provide: i. a visualization interface module processing a result list of a plurality of modified document surrogates, each of the modified document surrogates comprising a document surrogate returned from a search engine in response to a search query, and an indication of a frequency of occurrence of at least one query term of the search query in the document surrogate, the visualization interface module processing the result list to provide display information to display the result list on the display device, the display information providing: (1) a main portion for displaying a subset of the result list in a first format, the first format displays for each modified document surrogate in the subset of the result list: (a) a title of the modified document surrogate, the title displayed as a readable hyperlink; and (b) a visual indication of the frequency of occurrence of the at least one query term, the visual indication based on the indication of the frequency of occurrence of the at least one query term in the modified document surrogate; and (2) a compressed portion for displaying a compressed view of the result list, including the subset of the result list displayed in the main portion, in a second format, the second format displays for each modified document surrogate in the result list: (c) a representation of the title of the modified document surrogate corresponding to the length and display of the readable hyperlink of the title of the modified document surrogate displayed in the first format; and (d) a compressed visual indication of the frequency of occurrence of the at least one query term, the compressed visual indication comprising a color shade corresponding to the visual indication of the frequency of occurrence of the at least one query term displayed in the main portion; wherein the compressed portion further for displaying an indicator frame around the compressed view of the subset of the result list displayed in the main portion and wherein the visualization interface module further updates the subset of the result set displayed in the main portion when the indicator frame is repositioned. | 1. A data processing system for visually coding search results, the data processing system comprising: a display device to display data; at least one processor; and a memory coupled to the at least one processor storing computer readable instructions executable by the at least one processor, the computer readable instructions when executed by the at least one processor configuring the data processing system to provide: i. a visualization interface module processing a result list of a plurality of modified document surrogates, each of the modified document surrogates comprising a document surrogate returned from a search engine in response to a search query, and an indication of a frequency of occurrence of at least one query term of the search query in the document surrogate, the visualization interface module processing the result list to provide display information to display the result list on the display device, the display information providing: (1) a main portion for displaying a subset of the result list in a first format, the first format displays for each modified document surrogate in the subset of the result list: (a) a title of the modified document surrogate, the title displayed as a readable hyperlink; and (b) a visual indication of the frequency of occurrence of the at least one query term, the visual indication based on the indication of the frequency of occurrence of the at least one query term in the modified document surrogate; and (2) a compressed portion for displaying a compressed view of the result list, including the subset of the result list displayed in the main portion, in a second format, the second format displays for each modified document surrogate in the result list: (c) a representation of the title of the modified document surrogate corresponding to the length and display of the readable hyperlink of the title of the modified document surrogate displayed in the first format; and (d) a compressed visual indication of the frequency of occurrence of the at least one query term, the compressed visual indication comprising a color shade corresponding to the visual indication of the frequency of occurrence of the at least one query term displayed in the main portion; wherein the compressed portion further for displaying an indicator frame around the compressed view of the subset of the result list displayed in the main portion and wherein the visualization interface module further updates the subset of the result set displayed in the main portion when the indicator frame is repositioned. 8. The data processing system as claimed in claim 1 , wherein the visualization interface module further processes the result list to reorder the result list based on the frequency of occurrence of one of the query terms of the search query and updates the display information of the compressed and main portions based on the reordered result list. | 0.501433 |
7,856,375 | 37 | 54 | 37. A method for automatically preparing customized communications for a plurality of consumer entities, the method comprising the steps of: using data from a first electronic data file containing financial product and/or financial service data for the customized communications, which financial product and/or financial service data includes a plurality of separate descriptions, characteristics and/or identifications for at least a first financial product and/or financial service; using data from a second electronic data file containing customer information for at least certain of the plurality of consumer entities, said customer information including customer related data in addition to, but not excluding, any one or more of customer name, customer address and customer account information obtained for said certain of the plurality of consumer entities; performing an automated composition process using one or more computing systems configured to access said first electronic data file and second electronic data file to compose an electronic document file representing a customized communication for at least one of said certain of the plurality of the consumer entities; wherein said customized communication includes an identifying section adapted to present identifying content to identify a consumer entity, and a separate customized section adapted to present at least some customized content relating to an offering for said consumer entity of said first financial product and/or financial service; wherein at least some of said customized content included in said customized communication for said separate customized section is variable information that is determined for said consumer entity from said first electronic data file and said second electronic data file during creation of said electronic document file; delivering said customized communications to said at least one of said certain of the plurality of consumer entities based on said electronic document file. | 37. A method for automatically preparing customized communications for a plurality of consumer entities, the method comprising the steps of: using data from a first electronic data file containing financial product and/or financial service data for the customized communications, which financial product and/or financial service data includes a plurality of separate descriptions, characteristics and/or identifications for at least a first financial product and/or financial service; using data from a second electronic data file containing customer information for at least certain of the plurality of consumer entities, said customer information including customer related data in addition to, but not excluding, any one or more of customer name, customer address and customer account information obtained for said certain of the plurality of consumer entities; performing an automated composition process using one or more computing systems configured to access said first electronic data file and second electronic data file to compose an electronic document file representing a customized communication for at least one of said certain of the plurality of the consumer entities; wherein said customized communication includes an identifying section adapted to present identifying content to identify a consumer entity, and a separate customized section adapted to present at least some customized content relating to an offering for said consumer entity of said first financial product and/or financial service; wherein at least some of said customized content included in said customized communication for said separate customized section is variable information that is determined for said consumer entity from said first electronic data file and said second electronic data file during creation of said electronic document file; delivering said customized communications to said at least one of said certain of the plurality of consumer entities based on said electronic document file. 54. The method of claim 37 , wherein said customized communications are prepared in groups corresponding to groupings by different consumer types and/or groupings by different financial product types or different plan types. | 0.759657 |
8,965,926 | 10 | 13 | 10. A method for creating and managing persistent document collections comprising the steps of: displaying a plurality of documents that are managed by a browser-based content management application that receives user input from a client-side web browser; receiving an add selection from the client-side web browser which specifies at least one document of the plurality of documents to add to a persistent document collection, the persistent document collection comprising a grouping of a sub-set of the plurality of documents, the persistent document collection enabling access to the sub-set of documents as a group and having an attribute that specifies any external applications with which the persistent document collection can share its documents; and storing the persistent document collection comprising the at least one document of the plurality of documents in a data store, in storage space allocated to the persistent document collection, wherein the content management application is further processed to assign one or more attributes to the persistent document collection, wherein the one or more attributes include an amount of disk space measured in a multiple of bits or a multiple of bytes to allocate to the persistent document collection. | 10. A method for creating and managing persistent document collections comprising the steps of: displaying a plurality of documents that are managed by a browser-based content management application that receives user input from a client-side web browser; receiving an add selection from the client-side web browser which specifies at least one document of the plurality of documents to add to a persistent document collection, the persistent document collection comprising a grouping of a sub-set of the plurality of documents, the persistent document collection enabling access to the sub-set of documents as a group and having an attribute that specifies any external applications with which the persistent document collection can share its documents; and storing the persistent document collection comprising the at least one document of the plurality of documents in a data store, in storage space allocated to the persistent document collection, wherein the content management application is further processed to assign one or more attributes to the persistent document collection, wherein the one or more attributes include an amount of disk space measured in a multiple of bits or a multiple of bytes to allocate to the persistent document collection. 13. The method of claim 10 , further comprising: at a later point in time, receiving a remove selection which specifies the at least one or more of the plurality of documents to remove from the persistent document collection. | 0.777228 |
10,083,155 | 16 | 17 | 16. The system of claim 15 wherein the computer readable program code configured to identify the original language is further configured to: calculate a confidence score based on the given pair vector and the threshold vector distance; and identifying the original language based on the confidence score. | 16. The system of claim 15 wherein the computer readable program code configured to identify the original language is further configured to: calculate a confidence score based on the given pair vector and the threshold vector distance; and identifying the original language based on the confidence score. 17. The system of claim 16 wherein the computer readable program code configured to calculate a confidence score is further configured to: evaluate metadata of the retrieved document to identify data relevant to the original language; determine the original language of the relevant data; and incorporate the original language of the relevant data into the confidence score. | 0.841794 |
8,869,113 | 14 | 20 | 14. One or more computer-readable non-transitory storage media embodying software operable when executed by one or more computer systems to: compile a C++ program having one or more input variables to obtain bytecode of the C++ program; modify a standard C++ library associated with the C++ program to create an optimized C++ library, the optimized C++ library used for symbolic execution and the standard C++ library used for concrete execution, wherein modifying the standard C++ library comprises rewriting one or more classes defined in the standard C++ library to result in fewer execution paths; compile the optimized C++ library to obtain bytecode of the optimized C++ library; symbolically execute the bytecode of the C++ program and the bytecode of the optimized C++ library, comprising: assign a symbolic input to each input variable of the C++ program; determine one or more execution paths in the C++ program; and for each execution path, construct a symbolic expression that if satisfied, causes the C++ program to proceed down the execution path; generate one or more test cases for the C++ program by solving each of the symbolic expressions, the one or more test cases indicating values that satisfy a feasible execution path of the C++ program with respect to the symbolic input; and test the C++ program by compiling the C++ program to obtain machine code and applying the test cases as input to the machine code. | 14. One or more computer-readable non-transitory storage media embodying software operable when executed by one or more computer systems to: compile a C++ program having one or more input variables to obtain bytecode of the C++ program; modify a standard C++ library associated with the C++ program to create an optimized C++ library, the optimized C++ library used for symbolic execution and the standard C++ library used for concrete execution, wherein modifying the standard C++ library comprises rewriting one or more classes defined in the standard C++ library to result in fewer execution paths; compile the optimized C++ library to obtain bytecode of the optimized C++ library; symbolically execute the bytecode of the C++ program and the bytecode of the optimized C++ library, comprising: assign a symbolic input to each input variable of the C++ program; determine one or more execution paths in the C++ program; and for each execution path, construct a symbolic expression that if satisfied, causes the C++ program to proceed down the execution path; generate one or more test cases for the C++ program by solving each of the symbolic expressions, the one or more test cases indicating values that satisfy a feasible execution path of the C++ program with respect to the symbolic input; and test the C++ program by compiling the C++ program to obtain machine code and applying the test cases as input to the machine code. 20. The media of claim 14 , wherein when modifying the standard C++ library the software is further operable when executed to rewrite one or more classes defined in the standard C++ library to result in fewer execution paths. | 0.794333 |
9,411,859 | 6 | 8 | 6. The method of claim 1 , further comprising: determining, from the merged table, and based at least in part from the aggregate weights, a first leading scorer of the matched fields and a second leading scorer of the matched fields, the first leading scorer associated with a record having a highest aggregate weight and the second leading scorer associated with a record having a second highest aggregate weight; determining a first condition comprising whether a first weight associated with the first leading scorer meets or exceeds a first predetermined value; determining a second condition comprising whether a difference between the first weight and a second weight associated with the second leading scorer meets or exceeds a second predetermined value; and wherein the matching entity corresponds to the first leading scorer and is based at least in part on the determining of the first condition and on the determining of the second condition. | 6. The method of claim 1 , further comprising: determining, from the merged table, and based at least in part from the aggregate weights, a first leading scorer of the matched fields and a second leading scorer of the matched fields, the first leading scorer associated with a record having a highest aggregate weight and the second leading scorer associated with a record having a second highest aggregate weight; determining a first condition comprising whether a first weight associated with the first leading scorer meets or exceeds a first predetermined value; determining a second condition comprising whether a difference between the first weight and a second weight associated with the second leading scorer meets or exceeds a second predetermined value; and wherein the matching entity corresponds to the first leading scorer and is based at least in part on the determining of the first condition and on the determining of the second condition. 8. The method of claim 6 , further comprising; merging aggregate weights of one or more entities associated with intermediate hierarchy levels in the grouping in response to determining that the first condition or the second condition is not met; re-determining the first condition and the second condition; and outputting a record identifier corresponding to an entity associated with a lowest hierarchy level of the grouping in response to re-determining the first condition and the second condition. | 0.873104 |
9,047,337 | 8 | 9 | 8. A computer program product comprising a non-transitory computer readable storage medium having a computer readable program, wherein the computer readable program when executed on a computer causes the computer to perform an operation comprising: displaying a portion of source code in an editing pane of the IDE tool, wherein the portion of the source code includes at least a text string representing a database statement; determining a database to be accessed using the database statement; establishing a database connection between the IDE tool and the database; retrieving a data model associated with the database; upon determining the database statement includes one or more host variables passing data to the database, prompting for a value for each host variable; evaluating, based on the data model, the database statement to identify any errors in the database statement, wherein evaluating the database statement includes executing the database statement and providing an option to commit or rollback one or more database changes made as a result of executing the database statement; and providing programming assistance based on the database statement and the data model, including providing an indication of any errors identified by the evaluation; and storing, by the IDE tool, the value provided for each host variable to allow the database statement to be re-executed from within the IDE tool without again prompting for values for the host variables. | 8. A computer program product comprising a non-transitory computer readable storage medium having a computer readable program, wherein the computer readable program when executed on a computer causes the computer to perform an operation comprising: displaying a portion of source code in an editing pane of the IDE tool, wherein the portion of the source code includes at least a text string representing a database statement; determining a database to be accessed using the database statement; establishing a database connection between the IDE tool and the database; retrieving a data model associated with the database; upon determining the database statement includes one or more host variables passing data to the database, prompting for a value for each host variable; evaluating, based on the data model, the database statement to identify any errors in the database statement, wherein evaluating the database statement includes executing the database statement and providing an option to commit or rollback one or more database changes made as a result of executing the database statement; and providing programming assistance based on the database statement and the data model, including providing an indication of any errors identified by the evaluation; and storing, by the IDE tool, the value provided for each host variable to allow the database statement to be re-executed from within the IDE tool without again prompting for values for the host variables. 9. The computer readable storage medium of claim 8 , wherein the data model comprises a relational schema specifying an organization of tables, columns, and keys defined for the database associated with the data model. | 0.703804 |
9,892,102 | 2 | 3 | 2. The method of claim 1 , wherein the receiving the requests comprises receiving the requests to display and edit the documents in a format that is not compatible with an Internet-based document editor. | 2. The method of claim 1 , wherein the receiving the requests comprises receiving the requests to display and edit the documents in a format that is not compatible with an Internet-based document editor. 3. The method of claim 2 , wherein the modified version of the document is in a format that is compatible with the Internet-based document editor. | 0.963772 |
9,876,860 | 1 | 2 | 1. A method comprising: creating, by a microprocessor, a first communication session with a first application and a communication device of a user, wherein the first application is written in a first programming language; detecting, by the microprocessor, a change in a first plurality of variables in the first application; in response to detecting the change in the first plurality of variables, storing, by the microprocessor, the first plurality of variables in a common data store comprising a persistent set of variables associated with applications servicing communication sessions; transferring, by the microprocessor, the first communication session to a second application written in a second programming language; detecting, by the microprocessor, a change in a second variable in the second application; in response to detecting the change in the second variable, storing, by the microprocessor, the second variable from the second application in the common data store; matching, by the microprocessor, a common pair of variables between the first plurality of variables stored in the common data store and the second variable stored in the common data store, wherein matching the common pair of variables comprises matching a variable of the first plurality of variables and the second variable and wherein the variable of the first plurality of variables and the second variable have different values due to at least one of a network delay, a processing delay, and a difference in a clock; and in response to matching the common pair of variables, retrieving, by the microprocessor, the first plurality of variables stored in the common data store and using the first plurality of variables stored in the common data store in the second application. | 1. A method comprising: creating, by a microprocessor, a first communication session with a first application and a communication device of a user, wherein the first application is written in a first programming language; detecting, by the microprocessor, a change in a first plurality of variables in the first application; in response to detecting the change in the first plurality of variables, storing, by the microprocessor, the first plurality of variables in a common data store comprising a persistent set of variables associated with applications servicing communication sessions; transferring, by the microprocessor, the first communication session to a second application written in a second programming language; detecting, by the microprocessor, a change in a second variable in the second application; in response to detecting the change in the second variable, storing, by the microprocessor, the second variable from the second application in the common data store; matching, by the microprocessor, a common pair of variables between the first plurality of variables stored in the common data store and the second variable stored in the common data store, wherein matching the common pair of variables comprises matching a variable of the first plurality of variables and the second variable and wherein the variable of the first plurality of variables and the second variable have different values due to at least one of a network delay, a processing delay, and a difference in a clock; and in response to matching the common pair of variables, retrieving, by the microprocessor, the first plurality of variables stored in the common data store and using the first plurality of variables stored in the common data store in the second application. 2. The method of claim 1 , wherein the first plurality of variables comprise one or more program variables created during execution of the first application and further comprising: identifying, by the microprocessor during execution of the first application, the one or more program variables. | 0.853938 |
9,697,178 | 8 | 9 | 8. The computer program product as recited in claim 1 , wherein the instructions are further configured, when executed by the computing device, to cause the computing device to: generate an outline for the narrative based on the instantiated content block data structure and the selected data set; and automatically render the narrative from the outline. | 8. The computer program product as recited in claim 1 , wherein the instructions are further configured, when executed by the computing device, to cause the computing device to: generate an outline for the narrative based on the instantiated content block data structure and the selected data set; and automatically render the narrative from the outline. 9. The computer program product as recited in claim 8 , wherein the outline comprises a language independent data structure specifying a plurality of data features and a plurality of angles to be conveyed in the narrative and the order in which to convey the data features and the angles. | 0.954646 |
8,027,990 | 11 | 14 | 11. A computer-readable medium with computer-executable instructions stored thereon an executable by a processing system and operable to cause the processing system upon such execution to perform operations comprising: storing a query graph generated from query data, the query data comprising a plurality of queries and the query graph comprising a plurality of nodes, each node representing a portion of a query, wherein each node representing a query prefix directs to one or more child nodes, each node has an associated frequency measure that is based on a number of times that the query that is represented by the node was received from users that belong to an associated user category; receiving a portion of a query from a user device; locating a first node representing the portion of a query in the query graph; locating descendant nodes of the first node, each descendent node being a node that represents a query in the query graph; ranking the queries represented by the located descendant nodes based on the frequency measures associated with the located descendant nodes; and sending the portions of queries to the user device. | 11. A computer-readable medium with computer-executable instructions stored thereon an executable by a processing system and operable to cause the processing system upon such execution to perform operations comprising: storing a query graph generated from query data, the query data comprising a plurality of queries and the query graph comprising a plurality of nodes, each node representing a portion of a query, wherein each node representing a query prefix directs to one or more child nodes, each node has an associated frequency measure that is based on a number of times that the query that is represented by the node was received from users that belong to an associated user category; receiving a portion of a query from a user device; locating a first node representing the portion of a query in the query graph; locating descendant nodes of the first node, each descendent node being a node that represents a query in the query graph; ranking the queries represented by the located descendant nodes based on the frequency measures associated with the located descendant nodes; and sending the portions of queries to the user device. 14. The computer-readable medium of claim 11 , further comprising: receiving an identifier of a user category from the user device; and ranking the portions of queries represented by the located descendant nodes based on the identified user category specific frequency measures associated with the nodes. | 0.501639 |
9,600,585 | 1 | 4 | 1. A computer-implemented method, comprising: receiving a request; inferring a request reading level representation for the request, inferring the request reading level representation for the request being based at least in part on previous behavior prior to the request, the previous behavior comprising a set of behavior, the set of behavior being computer-based search behavior or computer-based browsing behavior, the inferring the request reading level representation comprising: defining a search session that includes the request; identifying one or more search actions prior to the request in the search session; and inferring a reading level from the one or more search actions prior to the request in the search session; in response to the request, comparing the request reading level representation with one or more reading difficulty level representations for one or more response items; and in response to the request, returning one or more indications of results of comparing the request reading level representation with one or more reading difficulty level representations for the one or more response items. | 1. A computer-implemented method, comprising: receiving a request; inferring a request reading level representation for the request, inferring the request reading level representation for the request being based at least in part on previous behavior prior to the request, the previous behavior comprising a set of behavior, the set of behavior being computer-based search behavior or computer-based browsing behavior, the inferring the request reading level representation comprising: defining a search session that includes the request; identifying one or more search actions prior to the request in the search session; and inferring a reading level from the one or more search actions prior to the request in the search session; in response to the request, comparing the request reading level representation with one or more reading difficulty level representations for one or more response items; and in response to the request, returning one or more indications of results of comparing the request reading level representation with one or more reading difficulty level representations for the one or more response items. 4. The method of claim 1 , wherein inferring the request reading level representation comprises performing a reading level analysis of one or more search queries. | 0.877273 |
9,766,784 | 7 | 8 | 7. The system of claim 5 , wherein the receiving the second indication comprises receiving newer message content newer than the first message content, and wherein the selectable ratio results in a minimum number of rows of text that are displayed in conjunction with the message element at the fourth token value. | 7. The system of claim 5 , wherein the receiving the second indication comprises receiving newer message content newer than the first message content, and wherein the selectable ratio results in a minimum number of rows of text that are displayed in conjunction with the message element at the fourth token value. 8. The system of claim 7 , further comprising, in response to the receiving the newer message content, transitioning the second message content from the first device display area to the second device display area to facilitate displaying the newer message content in the first device display area and transitioning the first message content from the second device display area to the third device display area to facilitate displaying the second message content in the second device display area. | 0.922524 |
9,437,207 | 19 | 22 | 19. A computer-implemented method for processing speech data in accordance with a privacy regulation, the method comprising: receiving, from a user device executing an entertainment application, a raw audio waveform that includes speech data of a user, wherein the raw audio waveform is recorded by the user device in response to the user interacting with the entertainment application; providing metadata and the raw audio waveform to a speech processing environment controlled by a third party for processing, where the metadata identifies a frequency component of a frequency representation of the raw audio waveform that is to be modified; directing the third party to perform an anonymization operation on the raw audio waveform before performing a speech processing operation, wherein the anonymization operation includes generating the frequency representation of the raw audio waveform, modifying the frequency component of the frequency representation that could be used to identify the user in order to produce a modified frequency representation, and generating an anonymized representation of the raw audio waveform from the modified frequency representation; allowing the third-party speech processing system to copy an element of the anonymized representation to improve future instances of speech processing; receiving, from the speech processing environment, a textual depiction of speech in the anonymized representation of the raw audio waveform; determining a responsive action for a synthetic character based at least in part on the textual depiction; and transmitting, to the user device, an instruction indicative of the responsive action for execution by the user device, wherein execution of the instruction causes the synthetic character to perform the responsive action within the entertainment application. | 19. A computer-implemented method for processing speech data in accordance with a privacy regulation, the method comprising: receiving, from a user device executing an entertainment application, a raw audio waveform that includes speech data of a user, wherein the raw audio waveform is recorded by the user device in response to the user interacting with the entertainment application; providing metadata and the raw audio waveform to a speech processing environment controlled by a third party for processing, where the metadata identifies a frequency component of a frequency representation of the raw audio waveform that is to be modified; directing the third party to perform an anonymization operation on the raw audio waveform before performing a speech processing operation, wherein the anonymization operation includes generating the frequency representation of the raw audio waveform, modifying the frequency component of the frequency representation that could be used to identify the user in order to produce a modified frequency representation, and generating an anonymized representation of the raw audio waveform from the modified frequency representation; allowing the third-party speech processing system to copy an element of the anonymized representation to improve future instances of speech processing; receiving, from the speech processing environment, a textual depiction of speech in the anonymized representation of the raw audio waveform; determining a responsive action for a synthetic character based at least in part on the textual depiction; and transmitting, to the user device, an instruction indicative of the responsive action for execution by the user device, wherein execution of the instruction causes the synthetic character to perform the responsive action within the entertainment application. 22. The method of claim 19 , wherein the speech processing environment comprises a server, and wherein providing the raw audio waveform to the speech processing environment requires the raw audio waveform be transmitted to the server over a network. | 0.630564 |
10,061,843 | 12 | 18 | 12. A system for providing natural language query translation, the system comprising: a memory storage; and a processing unit coupled to the memory storage, wherein the processing unit is operable to: train a statistical machine translation model according to a plurality of mined query pairs, wherein train the statistical machine translation model comprises; identifying a set of previously received keyword type queries that are semantically similar to a set of previously received natural language type queries utilizing a query click graph, pairing at least one keyword type query with at least one natural language type query that is most semantically similar to form the mined query pair; receive a query from a user, determine whether the query is a natural language type query or is a keyword type query, and in response to determining that the query comprises the natural language type query: map the natural language type query into a keyword-based type query according to the trained statistical machine translation model; perform a search query according to the natural language type query and the keyword-based type query; and provide a plurality of results associated with the search query to the user. | 12. A system for providing natural language query translation, the system comprising: a memory storage; and a processing unit coupled to the memory storage, wherein the processing unit is operable to: train a statistical machine translation model according to a plurality of mined query pairs, wherein train the statistical machine translation model comprises; identifying a set of previously received keyword type queries that are semantically similar to a set of previously received natural language type queries utilizing a query click graph, pairing at least one keyword type query with at least one natural language type query that is most semantically similar to form the mined query pair; receive a query from a user, determine whether the query is a natural language type query or is a keyword type query, and in response to determining that the query comprises the natural language type query: map the natural language type query into a keyword-based type query according to the trained statistical machine translation model; perform a search query according to the natural language type query and the keyword-based type query; and provide a plurality of results associated with the search query to the user. 18. The system of claim 12 , wherein a previously received natural language type query and a previously received keyword-based type query are associated according to a weighted Uniform Resource Locator (URL) click graph. | 0.640523 |
8,600,984 | 7 | 8 | 7. The computer-executed method of claim 6 , wherein determining the affinity score comprises calculating a weighted sum over the social media users in the intersecting population. | 7. The computer-executed method of claim 6 , wherein determining the affinity score comprises calculating a weighted sum over the social media users in the intersecting population. 8. The computer-executed method of claim 7 , wherein a weight is assigned to each social media user in the intersecting population, and wherein each weight is determined based on at least one from the group consisting of: a number of times the social media user has commented on either the first or second time based media event, and a probability that the social media user comments on either the first or second time based media event. | 0.754494 |
9,271,130 | 25 | 26 | 25. The method of claim 14 , further comprising responding to a request from the first user to retrieve one or more archived messages. | 25. The method of claim 14 , further comprising responding to a request from the first user to retrieve one or more archived messages. 26. The method of claim 25 , wherein responding to the request includes transmitting the one or more archived messages to the first user in an email or in a text message. | 0.94194 |
8,479,094 | 4 | 5 | 4. The method of claim 1 , further comprising associating each of one or more of said reference sources with at least one style of writing. | 4. The method of claim 1 , further comprising associating each of one or more of said reference sources with at least one style of writing. 5. The method of claim 4 , wherein which of said search results are provided in said subset is based on said style of writing of said search results as compared to said user writing style specific to said document. | 0.941562 |
8,090,612 | 28 | 34 | 28. The method of claim 27 , wherein the providing comprises presenting one or more potential replacement contents to the user. | 28. The method of claim 27 , wherein the providing comprises presenting one or more potential replacement contents to the user. 34. The method of claim 28 , wherein the providing comprises automatically composing a composite image-based content from a set of constituent images selected by the user. | 0.92875 |
7,567,975 | 1 | 2 | 1. A computer-implemented method for managing evaluation of a rule based on a composite event that is defined to consist of multiple primitive events, the method comprising the steps of: determining that a first part of a condition, of the rule, is satisfied by an instance of a first primitive event of the multiple primitive events, wherein the first part of the condition must be satisfied to trigger an action corresponding to the rule; storing, persistently in a first table of a database and based on a first SQL operation on the first table, first state information associated with the first part of the condition and associated with the rule, wherein the first state information represents that the first part of the condition is satisfied by the instance of the first primitive event of the multiple primitive events; wherein the first state information includes a reference to a record, in a second table, of the instance of the first primitive event of the multiple primitive events; determining that a second part of the condition, of the rule, is satisfied by an instance of a second primitive event of the multiple primitive events, wherein the instance of the second primitive event of the multiple primitive events is different than the instance of the first primitive event of the multiple primitive events and wherein the second part of the condition must be satisfied to trigger the action corresponding to the rule; in response to determining that the second part of the condition is satisfied, reading the first state information stored persistently in the first table of the database; and determining, based at least in part on the read first state information stored persistently in the first table of the database, that the first part of the condition and the second part of the condition are satisfied, wherein determining that the first part of the condition and the second part of the condition is satisfied includes identifying, based on a second SQL operation on a third table, the condition in the third table, and wherein reading the first state information includes identifying, based on a third SQL operation on the first table, the first state information in the first table; and wherein the steps are performed on one or more computing devices. | 1. A computer-implemented method for managing evaluation of a rule based on a composite event that is defined to consist of multiple primitive events, the method comprising the steps of: determining that a first part of a condition, of the rule, is satisfied by an instance of a first primitive event of the multiple primitive events, wherein the first part of the condition must be satisfied to trigger an action corresponding to the rule; storing, persistently in a first table of a database and based on a first SQL operation on the first table, first state information associated with the first part of the condition and associated with the rule, wherein the first state information represents that the first part of the condition is satisfied by the instance of the first primitive event of the multiple primitive events; wherein the first state information includes a reference to a record, in a second table, of the instance of the first primitive event of the multiple primitive events; determining that a second part of the condition, of the rule, is satisfied by an instance of a second primitive event of the multiple primitive events, wherein the instance of the second primitive event of the multiple primitive events is different than the instance of the first primitive event of the multiple primitive events and wherein the second part of the condition must be satisfied to trigger the action corresponding to the rule; in response to determining that the second part of the condition is satisfied, reading the first state information stored persistently in the first table of the database; and determining, based at least in part on the read first state information stored persistently in the first table of the database, that the first part of the condition and the second part of the condition are satisfied, wherein determining that the first part of the condition and the second part of the condition is satisfied includes identifying, based on a second SQL operation on a third table, the condition in the third table, and wherein reading the first state information includes identifying, based on a third SQL operation on the first table, the first state information in the first table; and wherein the steps are performed on one or more computing devices. 2. The method of claim 1 , farther comprising: determining whether a join condition associated with the first part of the condition and the second part of the condition is satisfied by the instance of the first primitive event of the multiple primitive events and the instance of the second primitive event of the multiple primitive events. | 0.51567 |
9,805,023 | 1 | 9 | 1. A device comprising: at least one processor; a display accessible to the at least one processor; and storage accessible to the at least one processor and bearing instructions executable by the at least one processor to: store a first phrase from a sent message for presentation of the first phrase again during a subsequent composition of a second message, wherein the first phrase from the sent message that is stored comprises a variable when stored that will be replaced in the second message with at least one character for a particular recipient during composition of the second message; and identify the first phrase for presentation during composition of the second message; and present, on the display and during composition of the second message, the first phrase. | 1. A device comprising: at least one processor; a display accessible to the at least one processor; and storage accessible to the at least one processor and bearing instructions executable by the at least one processor to: store a first phrase from a sent message for presentation of the first phrase again during a subsequent composition of a second message, wherein the first phrase from the sent message that is stored comprises a variable when stored that will be replaced in the second message with at least one character for a particular recipient during composition of the second message; and identify the first phrase for presentation during composition of the second message; and present, on the display and during composition of the second message, the first phrase. 9. The device of claim 1 , wherein the first phrase is identified from a data structure that stores phrases based on at least one parameter. | 0.789157 |
8,064,688 | 37 | 38 | 37. A computer system, which, upon being programmed, is configured to perform the following: compute, using one or more data processors, a transform of a digitized version of a 2D (two-dimensional) image containing a 2D representation of an object, wherein said transform generates a plurality of transform coefficients; apply, using the one or more data processors, a plurality of view-based classifiers to the plurality of transform coefficients, wherein each view-based classifier is configured to detect a specific orientation of said object in said 2D image based on visual information received from corresponding transform coefficients, wherein at least one of said plurality of view-based classifiers includes a plurality of cascaded sub-classifiers, and wherein at least one of said plurality of sub-classifiers is based on a ratio of a plurality of graphical probability models; wherein a classifier is determined by: applying a view-based classifier to said 2D image, wherein said classifier includes a plurality of sub-classifiers; computing a sum of log-likelihood ratios for each of said plurality of sub-classifiers, wherein said log-likelihood ratio is a ratio of two graphical probability models; wherein a graphical probability model comprises a probability distribution over a set of variables where statistical independence and conditional statistical independence exist among various combinations of the variables, wherein the graphical probability model is a probability distribution representation derived from statistical dependencies among image input variables; and detect orientation and location of each instance of said object in said 2D image from a combination of results of the application of said plurality of view-based classifiers. | 37. A computer system, which, upon being programmed, is configured to perform the following: compute, using one or more data processors, a transform of a digitized version of a 2D (two-dimensional) image containing a 2D representation of an object, wherein said transform generates a plurality of transform coefficients; apply, using the one or more data processors, a plurality of view-based classifiers to the plurality of transform coefficients, wherein each view-based classifier is configured to detect a specific orientation of said object in said 2D image based on visual information received from corresponding transform coefficients, wherein at least one of said plurality of view-based classifiers includes a plurality of cascaded sub-classifiers, and wherein at least one of said plurality of sub-classifiers is based on a ratio of a plurality of graphical probability models; wherein a classifier is determined by: applying a view-based classifier to said 2D image, wherein said classifier includes a plurality of sub-classifiers; computing a sum of log-likelihood ratios for each of said plurality of sub-classifiers, wherein said log-likelihood ratio is a ratio of two graphical probability models; wherein a graphical probability model comprises a probability distribution over a set of variables where statistical independence and conditional statistical independence exist among various combinations of the variables, wherein the graphical probability model is a probability distribution representation derived from statistical dependencies among image input variables; and detect orientation and location of each instance of said object in said 2D image from a combination of results of the application of said plurality of view-based classifiers. 38. The computer system of claim 37 , which, upon being programmed, is further configured to perform the following: establish a communication link with a client computer over a communication network; receive said digitized version of said 2D image from the client computer over said communication network; perform said detection of said orientation and location of each instance of said object in said 2D image received from the client computer; and send a notification of the orientation and location of each said instance of said object to the client computer over the communication network. | 0.500842 |
8,244,539 | 6 | 7 | 6. The method of claim 1 , wherein the one or more of the plurality of advertising files belongs to a corresponding one of a plurality of product categories. | 6. The method of claim 1 , wherein the one or more of the plurality of advertising files belongs to a corresponding one of a plurality of product categories. 7. The method of claim 6 , wherein each of the plurality of categories is associated with a distinct set of phonemes, and wherein the corresponding one of the plurality of product categories is associated with the second set of phonemes. | 0.859763 |
10,013,679 | 1 | 11 | 1. A method comprising: identifying, by a processor, first vehicle service data represents terms of a natural human language that match one or more taxonomy terms within a defined taxonomy searchable by the processor, wherein a first identifier uniquely identifies the first vehicle service data; associating, by the processor, a meaning with the first vehicle service data based on the terms of the natural human language represented by the first vehicle service data that match the one or more taxonomy terms; generating, by the processor, first metadata that represents the meaning associated with the first vehicle service data; generating vehicle service content based at least in part on the first metadata; generating, by the processor, second metadata that represents a meaning with at least a portion of second vehicle service data; aggregating, by the processor, at least the first metadata and the second metadata to produce aggregated metadata; associating, by the processor, the first identifier with the first metadata; receiving a request for the vehicle service content, wherein the request includes the first identifier and/or the first metadata, and in response to the request for the vehicle service content, sending the vehicle service content to be displayed by a service tool. | 1. A method comprising: identifying, by a processor, first vehicle service data represents terms of a natural human language that match one or more taxonomy terms within a defined taxonomy searchable by the processor, wherein a first identifier uniquely identifies the first vehicle service data; associating, by the processor, a meaning with the first vehicle service data based on the terms of the natural human language represented by the first vehicle service data that match the one or more taxonomy terms; generating, by the processor, first metadata that represents the meaning associated with the first vehicle service data; generating vehicle service content based at least in part on the first metadata; generating, by the processor, second metadata that represents a meaning with at least a portion of second vehicle service data; aggregating, by the processor, at least the first metadata and the second metadata to produce aggregated metadata; associating, by the processor, the first identifier with the first metadata; receiving a request for the vehicle service content, wherein the request includes the first identifier and/or the first metadata, and in response to the request for the vehicle service content, sending the vehicle service content to be displayed by a service tool. 11. The method of claim 1 , wherein the meaning associated with the at least a portion of the first vehicle service data is a likely-meaning of the at least a portion of the first vehicle service data or an actual-meaning of the at least a portion of the first vehicle service data. | 0.737918 |
9,471,204 | 1 | 8 | 1. A method for web application navigation control, comprising: updating navigation data models used in navigation constraints with received data from an end-user or system, the data models being stored on a computer storage medium; without needing a centralized application-specific controller, automatically selecting from a collection of extensible navigation rules associated with each page of a plurality of pages the extensible navigation rules; evaluating the navigation constraints associated only with the pages potentially changing their ready state to execute from among the plurality of pages in an entire application to determine which pages are ready to run, wherein determining which pages are ready to run is based on updated data from the navigation data models; and selecting a preferred page to be actually navigated to next from among a set of all available and ready pages. | 1. A method for web application navigation control, comprising: updating navigation data models used in navigation constraints with received data from an end-user or system, the data models being stored on a computer storage medium; without needing a centralized application-specific controller, automatically selecting from a collection of extensible navigation rules associated with each page of a plurality of pages the extensible navigation rules; evaluating the navigation constraints associated only with the pages potentially changing their ready state to execute from among the plurality of pages in an entire application to determine which pages are ready to run, wherein determining which pages are ready to run is based on updated data from the navigation data models; and selecting a preferred page to be actually navigated to next from among a set of all available and ready pages. 8. The method as recited in claim 1 , wherein with received data from an end-user or system includes a presence of data provided by one of a user and memory storage independent of the user. | 0.609504 |
8,086,959 | 8 | 9 | 8. A computer system for inferring a schema from an electronic document containing hierarchical data comprising: an application program that determines that the electronic document containing hierarchical data does not reference a schema; a memory for storing the hierarchical data, wherein the hierarchical data includes one or more nodes; a parser for receiving the hierarchical data from the memory and parsing the hierarchical data in the electronic document to discover the one or more nodes; a logical memory module for: (a) receiving one of the discovered nodes from the parser; (b) determining content associated with the discovered node; and (c) saving the content associated with the discovered node in the memory; (d) repeating tasks (a)-(c) until the content for each discovered node has been saved in the memory; and a schema generator module for generating the schema based on the content saved for each discovered node that includes specifying repeating nodes that are out of sequence as unbounded by checking at least a repeating indicator, wherein the schema provides the electronic document a set of grammatical and data type rules that govern types and a structure of data that may be included in the electronic document. | 8. A computer system for inferring a schema from an electronic document containing hierarchical data comprising: an application program that determines that the electronic document containing hierarchical data does not reference a schema; a memory for storing the hierarchical data, wherein the hierarchical data includes one or more nodes; a parser for receiving the hierarchical data from the memory and parsing the hierarchical data in the electronic document to discover the one or more nodes; a logical memory module for: (a) receiving one of the discovered nodes from the parser; (b) determining content associated with the discovered node; and (c) saving the content associated with the discovered node in the memory; (d) repeating tasks (a)-(c) until the content for each discovered node has been saved in the memory; and a schema generator module for generating the schema based on the content saved for each discovered node that includes specifying repeating nodes that are out of sequence as unbounded by checking at least a repeating indicator, wherein the schema provides the electronic document a set of grammatical and data type rules that govern types and a structure of data that may be included in the electronic document. 9. The system of claim 8 , wherein in saving the content associated with the discovered node in the memory, the logical memory module: determines whether the discovered node has previously been discovered; if the discovered node has been previously discovered, then stores a first indicator indicating that the discovered node is a repeating node in the memory; and saves the content associated with the repeating node in the memory; and if the discovered node has not been previously discovered, then saves the content associated with the discovered node in the memory. | 0.500876 |
9,292,855 | 11 | 12 | 11. The method of claim 10 , wherein the non-promoted content synthesized for possible display is prioritized, wherein a higher priority results in a higher probability of display and/or a higher number in an order sequence for display. | 11. The method of claim 10 , wherein the non-promoted content synthesized for possible display is prioritized, wherein a higher priority results in a higher probability of display and/or a higher number in an order sequence for display. 12. The method of claim 11 , wherein the priority is based on a parameter selected from the group consisting of: relevancy, higher fees, location of an IP address, GPS coordinates, or a combination thereof. | 0.936341 |
10,140,017 | 1 | 10 | 1. A method comprising: outputting, by a first application executing at a computing device, a graphical user interface including a text edit region that includes uncommitted text input, and an output region that includes committed text input: invoking, by the first application, a keyboard application executing at the computing device to provide a graphical keyboard within the graphical user interface; outputting, by the keyboard application, for display adjacent to the text edit and output regions of the graphical user interface, the graphical keyboard, wherein the graphical keyboard includes a plurality of character keys, a word suggestion region and a search element, wherein the word suggestion region and the search element are each positioned above the plurality of character keys and below the text edit and output regions, wherein the word suggestion region includes a plurality of word suggestions based on the uncommitted text input displayed by the text edit region; receiving, by the keyboard application, an indication of a selection of the search element; responsive to receiving the indication of the selection of the search element, outputting, by the keyboard application, for display within the graphical keyboard, adjacent to the text edit and output regions of the graphical user interface, and in place of the word suggestion region, a query suggestion region including one or more suggested search queries; while outputting the query suggestion region for display, receiving, by the keyboard application, an indication of a selection of one or more character keys from the plurality of character keys; outputting, by the keyboard application, for display within the graphical keyboard, adjacent to the text edit and output regions of the graphical user interface, and in place of the query suggestion region, an updated query suggestion region including one or more characters selected in response to the selection of the one or more character keys; determining, by the keyboard application, based on the one or more characters, one or more updated suggested search queries; outputting, by the keyboard application, for display, the one or more updated suggested search queries in the updated query suggestion region; receiving, by the keyboard application, an indication of a selection of one of one or more updated suggested search queries, the one of the one or more updated suggested search queries being a selected search query; invoking, by the keyboard application and based on the selected search query, a search; responsive to invoking the search, receiving, by the keyboard application, search results; and outputting, by the keyboard application, for display within the graphical keyboard, adjacent to the text edit and output regions of the graphical user interface, and in place of a portion, but not all, of the plurality of character keys, a graphical indication of at least a portion of the search results. | 1. A method comprising: outputting, by a first application executing at a computing device, a graphical user interface including a text edit region that includes uncommitted text input, and an output region that includes committed text input: invoking, by the first application, a keyboard application executing at the computing device to provide a graphical keyboard within the graphical user interface; outputting, by the keyboard application, for display adjacent to the text edit and output regions of the graphical user interface, the graphical keyboard, wherein the graphical keyboard includes a plurality of character keys, a word suggestion region and a search element, wherein the word suggestion region and the search element are each positioned above the plurality of character keys and below the text edit and output regions, wherein the word suggestion region includes a plurality of word suggestions based on the uncommitted text input displayed by the text edit region; receiving, by the keyboard application, an indication of a selection of the search element; responsive to receiving the indication of the selection of the search element, outputting, by the keyboard application, for display within the graphical keyboard, adjacent to the text edit and output regions of the graphical user interface, and in place of the word suggestion region, a query suggestion region including one or more suggested search queries; while outputting the query suggestion region for display, receiving, by the keyboard application, an indication of a selection of one or more character keys from the plurality of character keys; outputting, by the keyboard application, for display within the graphical keyboard, adjacent to the text edit and output regions of the graphical user interface, and in place of the query suggestion region, an updated query suggestion region including one or more characters selected in response to the selection of the one or more character keys; determining, by the keyboard application, based on the one or more characters, one or more updated suggested search queries; outputting, by the keyboard application, for display, the one or more updated suggested search queries in the updated query suggestion region; receiving, by the keyboard application, an indication of a selection of one of one or more updated suggested search queries, the one of the one or more updated suggested search queries being a selected search query; invoking, by the keyboard application and based on the selected search query, a search; responsive to invoking the search, receiving, by the keyboard application, search results; and outputting, by the keyboard application, for display within the graphical keyboard, adjacent to the text edit and output regions of the graphical user interface, and in place of a portion, but not all, of the plurality of character keys, a graphical indication of at least a portion of the search results. 10. The method of claim 1 , further comprising: while maintaining the text edit and output regions of the graphical user interface adjacent to the graphical keyboard: receiving, by the keyboard application, an indication of a swipe gesture initiated within the portion of the search results displayed within the graphical keyboard; and outputting, by the graphical keyboard, for display within the graphical keyboard and in place of the portion of search results previously displayed, a graphical indication of a different portion of the search results. | 0.500903 |
7,921,137 | 1 | 8 | 1. A computer-implemented method for managing documents implemented in a business processing chain, comprising: receiving a request to generate a document for electronic publication with a computer processor; determining a first object to be included in the document, the first object having characteristics; classifying the characteristics of the first object into a plurality of classes; describing a characteristic of the first object with a first semantic primitive, the first semantic primitive; identifying at least one class among a plurality of classes; wherein, each class among the plurality of classes is stored as metadata defining a document definition associated with the document; determining whether at least one characteristic of the first object belongs to the class identified by the first semantic primitive and whether or not there is a constraint on the use of the first object in the document; wherein when a constraint on the use of the first object in the document or a document template exists, a message is generated indicating a conflict and, wherein when a constraint on the use of the first object in the document or the document template does not exist, metadata associated with the first object and the first semantic primitive is used in generating a document model; generating a first document model, based on a result of the determination of the constraints and the document definition; publishing the document to a computer display using the computer processor, wherein updates to the first document model and document definition are reflected in the document when the document is published; receiving a request to modify the first object based on information associated with the business processing chain; modifying the first semantic primitive describing a characteristic of the first object and the document definition based on the request; modifying subsequent publications of the document based on the modified document definition; receiving a request to publish a second document associated with a second document model referencing the first object; and publishing the second document based on a second document model, the second document being published based on the modifications to the first object. | 1. A computer-implemented method for managing documents implemented in a business processing chain, comprising: receiving a request to generate a document for electronic publication with a computer processor; determining a first object to be included in the document, the first object having characteristics; classifying the characteristics of the first object into a plurality of classes; describing a characteristic of the first object with a first semantic primitive, the first semantic primitive; identifying at least one class among a plurality of classes; wherein, each class among the plurality of classes is stored as metadata defining a document definition associated with the document; determining whether at least one characteristic of the first object belongs to the class identified by the first semantic primitive and whether or not there is a constraint on the use of the first object in the document; wherein when a constraint on the use of the first object in the document or a document template exists, a message is generated indicating a conflict and, wherein when a constraint on the use of the first object in the document or the document template does not exist, metadata associated with the first object and the first semantic primitive is used in generating a document model; generating a first document model, based on a result of the determination of the constraints and the document definition; publishing the document to a computer display using the computer processor, wherein updates to the first document model and document definition are reflected in the document when the document is published; receiving a request to modify the first object based on information associated with the business processing chain; modifying the first semantic primitive describing a characteristic of the first object and the document definition based on the request; modifying subsequent publications of the document based on the modified document definition; receiving a request to publish a second document associated with a second document model referencing the first object; and publishing the second document based on a second document model, the second document being published based on the modifications to the first object. 8. The computer-implemented method of claim 1 , wherein the first semantic primitive reflects a class describing the first object as including content that is rendered in a content frame of an extended hypertext markup language object, an object that may be referenced by a public entity, and an object that is used for linking to other data. | 0.644491 |
8,832,088 | 41 | 44 | 41. The system of claim 35 , wherein the operations further comprise: determining a query value Q for the query, wherein the query value is based on the QtoA ratio; determining a resource value D for the resource, the resource value being based on a function of an age of the resource, F(age); and wherein the boosting function is a boosting function of the query value Q and the resource value D. | 41. The system of claim 35 , wherein the operations further comprise: determining a query value Q for the query, wherein the query value is based on the QtoA ratio; determining a resource value D for the resource, the resource value being based on a function of an age of the resource, F(age); and wherein the boosting function is a boosting function of the query value Q and the resource value D. 44. The system of claim 41 , wherein determining Q comprises determining Q from a maximum Max(QFval) of one or more of the following query freshness values: a percentile value of a number of occurrences of the query being received within a first recent time period; percentile value of a number of occurrences of the query on blog web pages within a second recent time period; a percentile value of a number of occurrences of the query on news web pages within a third recent time period; a percentile value of a number of occurrences of the query on social network web pages within a fourth recent time period; a percentile value of a number of occurrences of the query requesting news search results within a fifth recent time period; a percentile value of a ratio of a number of occurrences of the query requesting news search results within a sixth recent time period to a number of occurrences of the query requesting web search results within the sixth recent time period; a percentile value of a number of user selections of news search results provided in response to the query within a seventh recent time period; and a percentile value of a ratio of a number of user selections of news search results provided in response to the query within an eighth recent time period to a number of user selections of web search results provided in response to the query within the eighth recent time period. | 0.563935 |
8,477,109 | 28 | 29 | 28. One or more non-transitory computer-readable media as recited in claim 26 , wherein the multiple different reference work entries each reside within a same category of reference work. | 28. One or more non-transitory computer-readable media as recited in claim 26 , wherein the multiple different reference work entries each reside within a same category of reference work. 29. One or more non-transitory computer-readable media as recited in claim 28 , wherein the multiple different reference work entries within the same category of reference work comprise one or more of a science reference work entry, a science-fiction reference work entry, a medical reference work entry, a business reference work entry, a legal reference work entry, a native-language reference work entry, or a non-native-language reference work entry. | 0.82525 |
7,996,246 | 7 | 36 | 7. A method for generating information for determining resource allocation in a resident care facility, the method comprising: providing a set of assessment questions to an assessor, the set of assessment questions being: based on a base assessment model having questions relating to a plurality of resident care areas; and related to at least a portion of the plurality of resident care areas; receiving responses to at least a portion of the set of assessment questions from a number of respondents; processing the responses to generate an assessment dataset; generating, with a computer, a quality score for at least one of the resident care areas based on the assessment dataset; generating, with a computer, a likelihood of citation in the resident care area associated with the quality score, as a function of the quality score, the number of respondents, a model threshold, and a model sample size, the model threshold and the model sample size being derived from the base assessment model; and displaying the likelihood of citation for the resident care area associated with the quality score. | 7. A method for generating information for determining resource allocation in a resident care facility, the method comprising: providing a set of assessment questions to an assessor, the set of assessment questions being: based on a base assessment model having questions relating to a plurality of resident care areas; and related to at least a portion of the plurality of resident care areas; receiving responses to at least a portion of the set of assessment questions from a number of respondents; processing the responses to generate an assessment dataset; generating, with a computer, a quality score for at least one of the resident care areas based on the assessment dataset; generating, with a computer, a likelihood of citation in the resident care area associated with the quality score, as a function of the quality score, the number of respondents, a model threshold, and a model sample size, the model threshold and the model sample size being derived from the base assessment model; and displaying the likelihood of citation for the resident care area associated with the quality score. 36. The method of claim 7 , further comprising: displaying the quality score graphically in relation to the data derived from the base assessment model. | 0.895604 |
9,972,310 | 1 | 3 | 1. A method for training acoustic models in speech recognition systems, wherein the speech recognition system comprises a neural network, the method comprising the steps of: a. extracting acoustic features from a speech signal using the neural network; and b. processing the acoustic features into an acoustic model by the speech recognition system, wherein the neural network comprises at least one of: activation functions with parameters, prealigned feature data, and training, wherein the training is performed using a stochastic gradient descent method on a cost function, and wherein the cost function is a linear discriminant analysis cost function. | 1. A method for training acoustic models in speech recognition systems, wherein the speech recognition system comprises a neural network, the method comprising the steps of: a. extracting acoustic features from a speech signal using the neural network; and b. processing the acoustic features into an acoustic model by the speech recognition system, wherein the neural network comprises at least one of: activation functions with parameters, prealigned feature data, and training, wherein the training is performed using a stochastic gradient descent method on a cost function, and wherein the cost function is a linear discriminant analysis cost function. 3. The method of claim 1 , wherein the features are extracted from a speech signal spectrum. | 0.784038 |
8,666,750 | 1 | 2 | 1. A system, comprising: a speech recognition unit configured to: receive a first control signal comprising a radio signal from a wireless first mobile device associated with a first user, wherein the first control signal is unrelated to speech of the first user; receive a first speech signal from the first user associated with the first mobile device; receive an audio signal from the first mobile device and determine a distance of the first user by measuring a difference in transmission time between the radio signal and the audio signal; and identify the first user from the first control signal and configure speech settings for speech recognition of speech by the first user based on the identity of the first user and the determined distance. | 1. A system, comprising: a speech recognition unit configured to: receive a first control signal comprising a radio signal from a wireless first mobile device associated with a first user, wherein the first control signal is unrelated to speech of the first user; receive a first speech signal from the first user associated with the first mobile device; receive an audio signal from the first mobile device and determine a distance of the first user by measuring a difference in transmission time between the radio signal and the audio signal; and identify the first user from the first control signal and configure speech settings for speech recognition of speech by the first user based on the identity of the first user and the determined distance. 2. The system according to claim 1 , wherein the first control signal comprises radio signals from a binaural hearing aid. | 0.789655 |
7,814,127 | 16 | 18 | 16. A method of providing natural language support for users running queries against a database, comprising: retrieving an abstract query comprising a plurality of logical fields, each corresponding to a logical field specification of a data abstraction model abstractly describing physical data residing in the database; determining, from the data abstraction model, an associated language resource component; determining, from the associated language resource component, at least two natural language expressions for the plurality of logical fields of the abstract query; and displaying the abstract query in one of the at least two determined natural language expressions to a user, wherein the natural language expression displayed is determined by a security setting of the user. | 16. A method of providing natural language support for users running queries against a database, comprising: retrieving an abstract query comprising a plurality of logical fields, each corresponding to a logical field specification of a data abstraction model abstractly describing physical data residing in the database; determining, from the data abstraction model, an associated language resource component; determining, from the associated language resource component, at least two natural language expressions for the plurality of logical fields of the abstract query; and displaying the abstract query in one of the at least two determined natural language expressions to a user, wherein the natural language expression displayed is determined by a security setting of the user. 18. The method of claim 16 wherein the associated language resource component is a language resource file, the data abstraction model including a reference to the language resource file. | 0.836268 |
8,782,518 | 1 | 12 | 1. A computer-implemented medical diagnosis system, comprising: a. a memory and a display; b. a plurality of multilingual forms stored in the memory c. the multilingual forms containing a plurality of diagnostic information in a plurality of predetermined diagnostic-information locations; d. two or more language selection buttons, e. a plurality of audio activation buttons, each audio activation button located adjacent to a diagnostic-information location, f. activation of one of said audio activation buttons causes the system to play an audio clip, wherein i. the audio clip explains the diagnostic information adjacent to the activated audio-activation-button, and ii. the audio clip explains the diagnostic information in the most recently selected output language. | 1. A computer-implemented medical diagnosis system, comprising: a. a memory and a display; b. a plurality of multilingual forms stored in the memory c. the multilingual forms containing a plurality of diagnostic information in a plurality of predetermined diagnostic-information locations; d. two or more language selection buttons, e. a plurality of audio activation buttons, each audio activation button located adjacent to a diagnostic-information location, f. activation of one of said audio activation buttons causes the system to play an audio clip, wherein i. the audio clip explains the diagnostic information adjacent to the activated audio-activation-button, and ii. the audio clip explains the diagnostic information in the most recently selected output language. 12. The medical diagnosis system of claim 1 , wherein the memory stores the multilingual forms in a remote server. | 0.885772 |
9,678,580 | 18 | 19 | 18. An interface system according to claim 15 , wherein the one or more data dictionaries comprises two or more data dictionaries, wherein the data processor is configured to maintain lookup chains between the two or more data dictionaries such that a given data string in a first data dictionary is mapped to at least one data string in one or more other data dictionaries of the two or more data dictionaries for selection by the user. | 18. An interface system according to claim 15 , wherein the one or more data dictionaries comprises two or more data dictionaries, wherein the data processor is configured to maintain lookup chains between the two or more data dictionaries such that a given data string in a first data dictionary is mapped to at least one data string in one or more other data dictionaries of the two or more data dictionaries for selection by the user. 19. An interface system according to claim 18 , wherein where a given data string in the first data dictionary is mapped to a plurality of data strings in the one or more other data dictionaries, said data strings are prioritized via the configuration means for ease of selection by the user. | 0.896011 |
8,364,669 | 8 | 9 | 8. The method of claim 1 wherein the content item is a musical album, wherein a musical album includes an electronic organization of songs. | 8. The method of claim 1 wherein the content item is a musical album, wherein a musical album includes an electronic organization of songs. 9. The method of claim 8 wherein generating a perceived popularity for the musical album comprises: identifying songs related to the musical album; determining a perceived popularity for each of the songs; determining a preliminary perceived popularity for the musical album as a whole; and determining the perceived popularity for the musical album based on the perceived popularity for each of the songs and the preliminary perceived popularity for the musical album as a whole. | 0.885496 |
9,489,657 | 16 | 17 | 16. The computing device of claim 14 in which one of the chat rooms is designated by a user as an active chat room, the distinct region for the active chat room including a scrolling full-text display of an ongoing dialog by participants in the chat room. | 16. The computing device of claim 14 in which one of the chat rooms is designated by a user as an active chat room, the distinct region for the active chat room including a scrolling full-text display of an ongoing dialog by participants in the chat room. 17. The computing device of claim 16 in which the distinct region for each non-active chat room extends along a horizontal row of the chat room summary window and the scrolling full-text display of the active chat room summary extends in a vertical column alongside the non-active chat room summaries. | 0.85274 |
8,918,308 | 1 | 13 | 1. A method implemented in a computer infrastructure, comprising: receiving a search query containing a transliterated word; determining a source language corresponding to the transliterated word, wherein the determining the source language comprises: determining a weighted score for each one of a plurality of candidate languages, and designating the candidate language with the highest weighted score as the source language; converting the transliterated word to a word in the source language; translating the word in the source language to a word in a target language; and performing a search using the word in the target language wherein the weighted score of each one of the plurality of candidate languages is based on: correlating user-entered words against language-specific dictionaries; environmental variables; location-based services; and user profile and/or history. | 1. A method implemented in a computer infrastructure, comprising: receiving a search query containing a transliterated word; determining a source language corresponding to the transliterated word, wherein the determining the source language comprises: determining a weighted score for each one of a plurality of candidate languages, and designating the candidate language with the highest weighted score as the source language; converting the transliterated word to a word in the source language; translating the word in the source language to a word in a target language; and performing a search using the word in the target language wherein the weighted score of each one of the plurality of candidate languages is based on: correlating user-entered words against language-specific dictionaries; environmental variables; location-based services; and user profile and/or history. 13. The method of claim 1 , wherein the transliterated word comprises a first transliterated word and the search query contains a second transliterated word, and further comprising: determining a second source language corresponding to the second transliterated word; converting the second transliterated word to a word in the second source language; translating the word in the second source language to a second word in the target language; and performing the search using the word in the target language and the second word in the target language. | 0.500907 |
9,002,900 | 1 | 8 | 1. A method comprising: storing, in a first area of a memory of a first computer system, a hierarchical data structure including a plurality of activity data items each representing an activity and each having a description and a status, wherein: each activity data item other than a root activity data item is a child of a parent activity data item and represents a subtask of the task represented by the parent activity data item; and the status for each node is recorded in a data field associated with that node; storing, in a second area of the memory of the first computer system, an unstructured set of activity data items each having a description; receiving a user input instructing a processor of the first computer system to associate an activity data item from the unstructured set of activity data items with the hierarchical data structure as a child or parent of one of the activity data items of the hierarchical data structure; receiving from a second computer system an additional activity data item; and storing the received additional activity data item in the second area. | 1. A method comprising: storing, in a first area of a memory of a first computer system, a hierarchical data structure including a plurality of activity data items each representing an activity and each having a description and a status, wherein: each activity data item other than a root activity data item is a child of a parent activity data item and represents a subtask of the task represented by the parent activity data item; and the status for each node is recorded in a data field associated with that node; storing, in a second area of the memory of the first computer system, an unstructured set of activity data items each having a description; receiving a user input instructing a processor of the first computer system to associate an activity data item from the unstructured set of activity data items with the hierarchical data structure as a child or parent of one of the activity data items of the hierarchical data structure; receiving from a second computer system an additional activity data item; and storing the received additional activity data item in the second area. 8. The method of claim 1 , wherein receiving the input instructing the processor of the first computer system to associate the additional activity data item from the unstructured set of activity data items with the hierarchical data structure as a child or parent of one of the activity data items of the hierarchical data structure comprises: receiving the user input in a graphical user interface dragging and dropping a graphical representation of the activity data item from a graphical representation of the unstructured set of activity data items onto a graphical representation of the hierarchical data structure. | 0.610553 |
9,418,128 | 1 | 7 | 1. One or more computer storage media having embodied thereon computer-usable instructions that, when executed, perform a method of entity linking, comprising: identifying mentions of entities within a document; identifying candidate entities associated with each mention; defining mention-entity pairs for each mention and the associated candidate entities; identifying a confidence score for each mention-entity pair; identifying relationships between the candidate entities; for each mention-entity pair, updating the confidence score based on the relationships between the associated candidate entity and the candidate entities associated with other mention-entity pairs; selecting candidate entities from the mention-entity pairs based on the updated confidence scores; and ranking the selected entities, wherein the ranking indicates a relevance of the selected entities to a topic of the document. | 1. One or more computer storage media having embodied thereon computer-usable instructions that, when executed, perform a method of entity linking, comprising: identifying mentions of entities within a document; identifying candidate entities associated with each mention; defining mention-entity pairs for each mention and the associated candidate entities; identifying a confidence score for each mention-entity pair; identifying relationships between the candidate entities; for each mention-entity pair, updating the confidence score based on the relationships between the associated candidate entity and the candidate entities associated with other mention-entity pairs; selecting candidate entities from the mention-entity pairs based on the updated confidence scores; and ranking the selected entities, wherein the ranking indicates a relevance of the selected entities to a topic of the document. 7. The media of claim 1 , the method further comprising as each candidate entity is selected, eliminating any mention-entity pairs that are mutually exclusive with the mention entity-pair that corresponds to the selected candidate entity. | 0.920081 |
9,601,116 | 15 | 19 | 15. A system comprising: one or more computers; and one or more storage devices storing instructions that are operable, when executed by the one or more computers, to cause the one or more computers to perform operations comprising: receiving, by a mobile device, an audio signal; determining, by the mobile device and using a model that is trained to detect a presence of a synthesized voice and a model that is trained to detect a presence of a user's voice, that the audio signal likely includes both the synthesized voice and the user's voice; in response to determining, by the mobile device and using a model that is trained to detect a presence of a synthesized voice and a model that is trained to detect a presence of a user's voice, that the audio signal likely includes both the synthesized voice and the user's voice, suppressing, by the mobile device, operation of a speech synthesis module implemented by the mobile device; after suppressing operation of the speech synthesis module, obtaining, by the mobile device, a transcription corresponding to the audio signal from an automated speech recognizer; and providing, by the mobile device, the transcription for output. | 15. A system comprising: one or more computers; and one or more storage devices storing instructions that are operable, when executed by the one or more computers, to cause the one or more computers to perform operations comprising: receiving, by a mobile device, an audio signal; determining, by the mobile device and using a model that is trained to detect a presence of a synthesized voice and a model that is trained to detect a presence of a user's voice, that the audio signal likely includes both the synthesized voice and the user's voice; in response to determining, by the mobile device and using a model that is trained to detect a presence of a synthesized voice and a model that is trained to detect a presence of a user's voice, that the audio signal likely includes both the synthesized voice and the user's voice, suppressing, by the mobile device, operation of a speech synthesis module implemented by the mobile device; after suppressing operation of the speech synthesis module, obtaining, by the mobile device, a transcription corresponding to the audio signal from an automated speech recognizer; and providing, by the mobile device, the transcription for output. 19. The system of claim 15 , further comprising: obtaining a first vector corresponding to at least a portion of the audio signal; and determining that the audio signal comprises additional audio other than the synthesized voice based on the first vector satisfying a threshold. | 0.671395 |
8,104,017 | 56 | 57 | 56. The computer readable medium of claim 53 , where the instructions are further for: searching the graphical model for the portion; and relating the segment with the portion graphically. | 56. The computer readable medium of claim 53 , where the instructions are further for: searching the graphical model for the portion; and relating the segment with the portion graphically. 57. The computer readable medium of claim 56 , where the instructions are further for: replacing the portion with another portion; and updating the segment to reflect the replacing. | 0.952218 |
4,612,532 | 8 | 9 | 8. A system according to claim 1, wherein each possible character in the stream of characters is classified into one of a plurality of Types and the followset means includes means for storing, accessing and updating a followset table, for each of a plurality of ordered character groups, each group including a last character therein and the Type of the character immediately preceding the last character, i.e., the Type of the next-to-last character, such table listing candidates for the character which may follow, in the stream, the character group with which the table is associated. | 8. A system according to claim 1, wherein each possible character in the stream of characters is classified into one of a plurality of Types and the followset means includes means for storing, accessing and updating a followset table, for each of a plurality of ordered character groups, each group including a last character therein and the Type of the character immediately preceding the last character, i.e., the Type of the next-to-last character, such table listing candidates for the character which may follow, in the stream, the character group with which the table is associated. 9. A system according to claim 8, wherein the character group consists of the last character therein, the Type of the next-to-last character, and the Type of the character immediately preceding the next-to-last character. | 0.946593 |
7,694,311 | 11 | 12 | 11. An article of manufacture having computer readable storage medium comprising computer readable program code executable by a computer to implement a method of detecting tasks, said medium comprising: computer readable program code labeling each URL in a set of URLs with a token; computer readable program code defining a task grammar based on identifying a plurality of tasks, each task based on a feasible sequence of tokens representing a sequence of URLs accessed to accomplish that task; computer readable program code receiving a web access log; computer readable program code extracting and tokenizing a sequence of accessed URLs from said web access log, said sequence of URLs part of said set of URLs for which said task grammar is defined; computer readable program code applying said task grammar to said tokenized sequence of accessed URLs; and computer readable program code, based on said applying said task grammar, detecting and reporting any of, or a combination of, the following: unfinished task, broken tasks, unsuccessful task, failed tasks, paused tasks, stopped tasks, or canceled tasks. | 11. An article of manufacture having computer readable storage medium comprising computer readable program code executable by a computer to implement a method of detecting tasks, said medium comprising: computer readable program code labeling each URL in a set of URLs with a token; computer readable program code defining a task grammar based on identifying a plurality of tasks, each task based on a feasible sequence of tokens representing a sequence of URLs accessed to accomplish that task; computer readable program code receiving a web access log; computer readable program code extracting and tokenizing a sequence of accessed URLs from said web access log, said sequence of URLs part of said set of URLs for which said task grammar is defined; computer readable program code applying said task grammar to said tokenized sequence of accessed URLs; and computer readable program code, based on said applying said task grammar, detecting and reporting any of, or a combination of, the following: unfinished task, broken tasks, unsuccessful task, failed tasks, paused tasks, stopped tasks, or canceled tasks. 12. The article of manufacture of claim 11 , wherein said grammar is compact and is described in Backus Naur form (BNF). | 0.817629 |
7,849,439 | 10 | 18 | 10. A method for automatically generating updated sequence diagrams for communications protocol transactions in response to user changes to sequence diagram source data, the method comprising: in a computer: loading a textual source file into an intermediate variable and displaying content of the intermediate variable in a graphical user interface as editable text, wherein said textual source file is in non-proprietary language and describes a flow for a communications protocol generated by a software application; building, by a source parser executed by the computer and based upon said intermediate variable, a data model for a diagram of said flow described by said textual source file; generating, by a diagram parser executed by the computer and based on said data model, corresponding drawing commands; responsive to said drawing commands, rendering by a rendering engine executed by the computer a sequence diagram representing said flow described by said intermediate variable as editable text, wherein the sequence diagram includes a graphical representation of a series of transactions between two or more actors, wherein the actors comprise entities that exchange message packets in communications protocol transactions and wherein: each of the two or more actors is represented by a vertical line; time is represented by a vertical progression down the vertical lines; transactions are represented by message packets exchanged between the two or more actors; and message packets are represented by directional horizontal lines between the vertical lines of actors and a label corresponding to each directional horizontal line denotes the message packet being transmitted; allowing a user to edit said content of said intermediate variable via said graphical user interface; and generating, by said diagram parser and based upon said edited content of said intermediate variable, an updated sequence diagram reflecting a change made by said user. | 10. A method for automatically generating updated sequence diagrams for communications protocol transactions in response to user changes to sequence diagram source data, the method comprising: in a computer: loading a textual source file into an intermediate variable and displaying content of the intermediate variable in a graphical user interface as editable text, wherein said textual source file is in non-proprietary language and describes a flow for a communications protocol generated by a software application; building, by a source parser executed by the computer and based upon said intermediate variable, a data model for a diagram of said flow described by said textual source file; generating, by a diagram parser executed by the computer and based on said data model, corresponding drawing commands; responsive to said drawing commands, rendering by a rendering engine executed by the computer a sequence diagram representing said flow described by said intermediate variable as editable text, wherein the sequence diagram includes a graphical representation of a series of transactions between two or more actors, wherein the actors comprise entities that exchange message packets in communications protocol transactions and wherein: each of the two or more actors is represented by a vertical line; time is represented by a vertical progression down the vertical lines; transactions are represented by message packets exchanged between the two or more actors; and message packets are represented by directional horizontal lines between the vertical lines of actors and a label corresponding to each directional horizontal line denotes the message packet being transmitted; allowing a user to edit said content of said intermediate variable via said graphical user interface; and generating, by said diagram parser and based upon said edited content of said intermediate variable, an updated sequence diagram reflecting a change made by said user. 18. A computer program which is executed in the computer and which, while being executed, performs the method of claim 10 . | 0.730263 |
8,645,369 | 1 | 3 | 1. A computer-implemented method, comprising: for each one of a plurality of documents, identifying a plurality of queries which resulted in user selection of the one of the plurality of documents from among search results provided in response to the queries; identifying itemsets within the queries, at least some of the itemsets representing recurring patterns in the queries; for each one of the plurality of documents, generating a representation of the corresponding one of the plurality of documents, wherein the representation of the one of the plurality of documents is generated based, at least in part, upon the itemsets identified within the corresponding queries which resulted in user selection of the document from among the search results provided in response to the corresponding queries; and for each one of the plurality of documents, classifying the one of the plurality of documents using the corresponding representation; wherein, for each one of the plurality of documents, the representation of the one of the plurality of documents comprises a vector including a plurality of scalar values, each scalar value representing a frequency with which a represented one of the itemsets appears within the corresponding queries. | 1. A computer-implemented method, comprising: for each one of a plurality of documents, identifying a plurality of queries which resulted in user selection of the one of the plurality of documents from among search results provided in response to the queries; identifying itemsets within the queries, at least some of the itemsets representing recurring patterns in the queries; for each one of the plurality of documents, generating a representation of the corresponding one of the plurality of documents, wherein the representation of the one of the plurality of documents is generated based, at least in part, upon the itemsets identified within the corresponding queries which resulted in user selection of the document from among the search results provided in response to the corresponding queries; and for each one of the plurality of documents, classifying the one of the plurality of documents using the corresponding representation; wherein, for each one of the plurality of documents, the representation of the one of the plurality of documents comprises a vector including a plurality of scalar values, each scalar value representing a frequency with which a represented one of the itemsets appears within the corresponding queries. 3. The method of claim 1 wherein the patterns in the associated queries comprise combinations of keywords. | 0.922965 |
8,788,270 | 49 | 54 | 49. A method for determining an emotion state of a speaker, comprising: providing an acoustic space having one or more dimensions, wherein each dimension of the one or more dimensions of the acoustic space corresponds to at least one baseline acoustic characteristic; receiving a training utterance of speech by the speaker; analyzing the training utterance of speech; modifying the acoustic space based on the analysis of the training reference of speech to produce a modified acoustic space having one or more modified dimensions, wherein each modified dimension of the one or more modified dimensions of the modified acoustic space corresponds to at least one modified baseline acoustic characteristic; receiving a subject utterance of speech by a speaker; measuring one or more acoustic characteristic of the subject utterance of speech; comparing each acoustic characteristic of the one or more acoustic characteristics of the subject utterance of speech to a corresponding one or more baseline acoustic characteristic; and determining an emotion state of the speaker based on the comparison. | 49. A method for determining an emotion state of a speaker, comprising: providing an acoustic space having one or more dimensions, wherein each dimension of the one or more dimensions of the acoustic space corresponds to at least one baseline acoustic characteristic; receiving a training utterance of speech by the speaker; analyzing the training utterance of speech; modifying the acoustic space based on the analysis of the training reference of speech to produce a modified acoustic space having one or more modified dimensions, wherein each modified dimension of the one or more modified dimensions of the modified acoustic space corresponds to at least one modified baseline acoustic characteristic; receiving a subject utterance of speech by a speaker; measuring one or more acoustic characteristic of the subject utterance of speech; comparing each acoustic characteristic of the one or more acoustic characteristics of the subject utterance of speech to a corresponding one or more baseline acoustic characteristic; and determining an emotion state of the speaker based on the comparison. 54. The method according to claim 49 , wherein each of the one or more acoustic characteristic of the subject utterance of speech comprises a suprasegmental property of the subject utterance of speech, and each of the at least one modified at least one baseline acoustic characteristic comprises a corresponding suprasegmental property. | 0.76 |
8,296,130 | 1 | 2 | 1. A method, comprising: receiving, using one or more data processors, a plurality of offensive words, wherein each respective offensive word in the plurality of offensive words is associated with a severity score identifying the offensiveness of the respective word; receiving, using the one or more data processors, a string of words, wherein a candidate word is selected from the string of words; calculating, using the one or more data processors, for each respective offensive word in the plurality of offensive words, a distance between the candidate word and the respective offensive word; calculating, using the one or more data processors, a plurality of offensiveness scores for the candidate word, each offensiveness score in the plurality of offensiveness scores based upon (i) the calculated distance between the candidate word and an offensive word in the plurality of offensive words and (ii) the severity score of the offensive word, wherein the plurality of offensiveness scores are calculated according to one or more of:
offensiveness score= A *(( B−C )/ B );
offensiveness score= A *(( B−( 1/ C ))/ B );
offensiveness score=Max((( A−C )/ A ),0); and
offensiveness score=((( B−C )/ B )> T ); wherein, A is the severity score for an offensive word in the plurality of offensive words; B is a function of a length of the offensive word; C is the calculated distance between the candidate word and the offensive word; and T is a threshold value; and determining, using the one or more data processors, whether the candidate word is an offender word based on whether the highest offensiveness score in the plurality of offensiveness scores for the candidate word exceeds an offensiveness threshold value. | 1. A method, comprising: receiving, using one or more data processors, a plurality of offensive words, wherein each respective offensive word in the plurality of offensive words is associated with a severity score identifying the offensiveness of the respective word; receiving, using the one or more data processors, a string of words, wherein a candidate word is selected from the string of words; calculating, using the one or more data processors, for each respective offensive word in the plurality of offensive words, a distance between the candidate word and the respective offensive word; calculating, using the one or more data processors, a plurality of offensiveness scores for the candidate word, each offensiveness score in the plurality of offensiveness scores based upon (i) the calculated distance between the candidate word and an offensive word in the plurality of offensive words and (ii) the severity score of the offensive word, wherein the plurality of offensiveness scores are calculated according to one or more of:
offensiveness score= A *(( B−C )/ B );
offensiveness score= A *(( B−( 1/ C ))/ B );
offensiveness score=Max((( A−C )/ A ),0); and
offensiveness score=((( B−C )/ B )> T ); wherein, A is the severity score for an offensive word in the plurality of offensive words; B is a function of a length of the offensive word; C is the calculated distance between the candidate word and the offensive word; and T is a threshold value; and determining, using the one or more data processors, whether the candidate word is an offender word based on whether the highest offensiveness score in the plurality of offensiveness scores for the candidate word exceeds an offensiveness threshold value. 2. The method of claim 1 , wherein each word in the plurality of offensive words and each word in the string of words comprises an abbreviation, a single word, a phrase, or a sentence. | 0.781473 |
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