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8,447,603 | 10 | 13 | 10. A server usable for evaluating naturalness of speech utterances by using crowd wisdom models, the server comprising: a features extraction module; a modeler; a scoring module; and a client-server communication module, wherein the server is in communication with a plurality of client devices that have user interface modules that are each controlled by the client-server communication module, wherein the client-server communication module is configured to: present, via the client devices, a plurality of human-testers with some of the obtained speech utterances, and receive, via the client devices, for each presented speech utterance, a plurality of corresponding human testers generated speech utterances being repetitions of the presented speech utterance, wherein the features extraction module is configured to extract speech features from speech utterances, wherein the modeler is configured to: generate, for each presented speech utterance, an utterance-specific scoring model for each one of a plurality of obtained speech utterances, that is based on respective the corresponding human-tester generated speech utterances, each scoring model being configured to estimate a level of speech naturalness for the presented speech utterances using at least crowd wisdom models, and update the utterance-specific scoring model based on the speech features extracted from the received speech utterances, and wherein the scoring module is configured to derive a speech naturalness score for each presented speech utterance, by applying the updated utterance-specific scoring model to each presented speech utterance, wherein at least one of: the features extraction module, the modeler, the scoring module and the client-server communication module is at least partially embodied in hardware. | 10. A server usable for evaluating naturalness of speech utterances by using crowd wisdom models, the server comprising: a features extraction module; a modeler; a scoring module; and a client-server communication module, wherein the server is in communication with a plurality of client devices that have user interface modules that are each controlled by the client-server communication module, wherein the client-server communication module is configured to: present, via the client devices, a plurality of human-testers with some of the obtained speech utterances, and receive, via the client devices, for each presented speech utterance, a plurality of corresponding human testers generated speech utterances being repetitions of the presented speech utterance, wherein the features extraction module is configured to extract speech features from speech utterances, wherein the modeler is configured to: generate, for each presented speech utterance, an utterance-specific scoring model for each one of a plurality of obtained speech utterances, that is based on respective the corresponding human-tester generated speech utterances, each scoring model being configured to estimate a level of speech naturalness for the presented speech utterances using at least crowd wisdom models, and update the utterance-specific scoring model based on the speech features extracted from the received speech utterances, and wherein the scoring module is configured to derive a speech naturalness score for each presented speech utterance, by applying the updated utterance-specific scoring model to each presented speech utterance, wherein at least one of: the features extraction module, the modeler, the scoring module and the client-server communication module is at least partially embodied in hardware. 13. The server according to claim 10 , wherein the modeler is further configured to filter out at least some of the human testers-generated utterances which exhibit speech naturalness score below a specified threshold such that the filtered out testers-generated utterances are not used in the updating of the scoring model. | 0.647826 |
9,195,714 | 9 | 12 | 9. A non-transitory computer-readable storage medium having program instructions stored thereon that, in response to execution by a computer system, cause the computer system to perform operations comprising: initiating, based on receiving a source document, a routine for identifying one or more candidate duplicate documents of the source document from a document corpus, said identifying comprising: receiving the source document, wherein a document type of the source document is the same as a document type of at least some of a plurality of reference documents in the document corpus; determining two or more different queries, from content of the source document; in response to receiving the source document, executing the two or more different queries on the document corpus, wherein the two or more different queries differ from one another by at least one search term, wherein individual ones of the two or more different queries return a respective list of reference documents that identifies at least some of the plurality of reference documents of the document corpus, and wherein the respective reference documents identified in the respective lists are associated with a respective score representing, at least in part, a relevance of that reference document with respect to the source document; based, at least in part, on the scores for the reference documents from at least two of the respective lists, selecting one or more of the reference documents having a respective score that meets a score threshold as potential duplicates of the same received source document that initiated the routine; and storing an identification of the one or more potential duplicate documents. | 9. A non-transitory computer-readable storage medium having program instructions stored thereon that, in response to execution by a computer system, cause the computer system to perform operations comprising: initiating, based on receiving a source document, a routine for identifying one or more candidate duplicate documents of the source document from a document corpus, said identifying comprising: receiving the source document, wherein a document type of the source document is the same as a document type of at least some of a plurality of reference documents in the document corpus; determining two or more different queries, from content of the source document; in response to receiving the source document, executing the two or more different queries on the document corpus, wherein the two or more different queries differ from one another by at least one search term, wherein individual ones of the two or more different queries return a respective list of reference documents that identifies at least some of the plurality of reference documents of the document corpus, and wherein the respective reference documents identified in the respective lists are associated with a respective score representing, at least in part, a relevance of that reference document with respect to the source document; based, at least in part, on the scores for the reference documents from at least two of the respective lists, selecting one or more of the reference documents having a respective score that meets a score threshold as potential duplicates of the same received source document that initiated the routine; and storing an identification of the one or more potential duplicate documents. 12. The non-transitory computer-readable storage medium of claim 9 , wherein at least one of the different queries is configured to score a reference document based on the reference document's relevance with respect to the source document and on a number of reference documents identified by the at least one query's respective list of documents. | 0.752504 |
8,533,666 | 13 | 14 | 13. The method of claim 12 , further comprising: upon receiving input setting a breakpoint at an operation, associating a breakpoint with the operation; upon executing the operation associated with the breakpoint: breaking the executing of the resource script, and upon receiving input requesting resuming the executing of the resource script, resuming the executing of the resource script. | 13. The method of claim 12 , further comprising: upon receiving input setting a breakpoint at an operation, associating a breakpoint with the operation; upon executing the operation associated with the breakpoint: breaking the executing of the resource script, and upon receiving input requesting resuming the executing of the resource script, resuming the executing of the resource script. 14. The method of claim 13 , further comprising: upon receiving input selecting a property of an executing resource script, displaying the property of the executing resource script within the design environment. | 0.910517 |
7,894,986 | 5 | 12 | 5. A method of facilitating specification of locations by end users for obtaining navigation-related or map-related features, the method comprising the steps of: with an on-line keyword program accessible to a first end user in a geographic region, accepting keyword registration requests from the first end user to register keywords, wherein each keyword is an alphanumeric word, string, or phrase, and further wherein the on-line keyword registration program is also operable to allow the first end user registering a keyword to associate a physical location in the geographic region and a user-provided instruction to facilitate routing to the physical location with the keyword; maintaining a keyword database that associates the keywords with data indicating the respective physical locations and instructions associated therewith by the first end user; and making the keyword database accessible on-line so that a second end user in the geographic region can use keywords registered by the first end user to specify locations in the geographic region and to receive the associated instruction. | 5. A method of facilitating specification of locations by end users for obtaining navigation-related or map-related features, the method comprising the steps of: with an on-line keyword program accessible to a first end user in a geographic region, accepting keyword registration requests from the first end user to register keywords, wherein each keyword is an alphanumeric word, string, or phrase, and further wherein the on-line keyword registration program is also operable to allow the first end user registering a keyword to associate a physical location in the geographic region and a user-provided instruction to facilitate routing to the physical location with the keyword; maintaining a keyword database that associates the keywords with data indicating the respective physical locations and instructions associated therewith by the first end user; and making the keyword database accessible on-line so that a second end user in the geographic region can use keywords registered by the first end user to specify locations in the geographic region and to receive the associated instruction. 12. The method of claim 5 wherein the user-provided instruction includes delivery instructions for the physical location. | 0.816109 |
9,219,746 | 1 | 6 | 1. A method, comprising: receiving, by a risk identification system including at least one computing device having at least one processor and at least one memory coupled to the processor, a string of terms; determining, by the at least one computing device of the risk identification system, whether the string of terms includes at least one word matching a keyword of a keyword listing; responsive to determining that the string of terms includes at least one word matching the keyword, identifying, by the risk identification system, at least a noun and a verb in the string of terms; identifying, by the at least one computing device of the risk identification system, a category of risk associated with the identified noun and a category of risk associated with the identified verb; determining, by the at least one computing device of the risk identification system, whether the identified category of risk associated with the identified noun and the identified category of risk associated with the identified verb are a same category of risk; responsive to determining that the identified category of risk associated with the identified noun and the identified category of risk associated with the identified verb are the same category, determining, by the risk identification system, a first risk rating of the received string of terms including the identified noun and the identified verb, the first risk rating being based on the identified noun, the identified verb and the same category; and responsive to determining that the identified category of risk associated with the identified noun and the identified category of risk associated with the identified verb are different categories, determining, by the risk identification system, a second risk rating of the received string of terms including the identified noun and the identified verb, the second risk rating being based on the identified noun, the identified verb, the identified category of risk associated with the noun and the identified category of risk associated with the verb, the second risk rating being different from the first risk rating. | 1. A method, comprising: receiving, by a risk identification system including at least one computing device having at least one processor and at least one memory coupled to the processor, a string of terms; determining, by the at least one computing device of the risk identification system, whether the string of terms includes at least one word matching a keyword of a keyword listing; responsive to determining that the string of terms includes at least one word matching the keyword, identifying, by the risk identification system, at least a noun and a verb in the string of terms; identifying, by the at least one computing device of the risk identification system, a category of risk associated with the identified noun and a category of risk associated with the identified verb; determining, by the at least one computing device of the risk identification system, whether the identified category of risk associated with the identified noun and the identified category of risk associated with the identified verb are a same category of risk; responsive to determining that the identified category of risk associated with the identified noun and the identified category of risk associated with the identified verb are the same category, determining, by the risk identification system, a first risk rating of the received string of terms including the identified noun and the identified verb, the first risk rating being based on the identified noun, the identified verb and the same category; and responsive to determining that the identified category of risk associated with the identified noun and the identified category of risk associated with the identified verb are different categories, determining, by the risk identification system, a second risk rating of the received string of terms including the identified noun and the identified verb, the second risk rating being based on the identified noun, the identified verb, the identified category of risk associated with the noun and the identified category of risk associated with the verb, the second risk rating being different from the first risk rating. 6. The method of claim 1 , wherein the string of terms is input into a user computing device by a user, wherein the user computing device is different from the at least one computing device of the risk identification system. | 0.80177 |
8,655,961 | 1 | 2 | 1. A system, comprising: a source client executable on a first computing device, the source client configured to generate an electronic envelope including a first electronic document to be distributed over a network for electronic signature and an electronic signing template defining a set of at least one task that must be performed by an executor of the first electronic document to complete the electronic signature, the first electronic document being subject to a document-execution workflow comprising a plurality of events including the at least one task, the first electronic document including an embedded activatable control; and an electronic device coupled to the first computing device over the network, the electronic device configured to: receive from the first computing device an electronic selection of an identifier of at least one event of the plurality of events, wherein the electronic selection of the identifier is provided via a graphical user interface that is configured to: display identifiers of the plurality of events including envelope sent, envelope delivered, and envelope signed, receive selections of identifiers of each of the plurality of events, and receive from a user a selection of an identifier of the at least one event of the plurality of events, monitor, over the network, progress of the first electronic document through the workflow, determine that the at least one event has occurred with respect to the first electronic document, by receiving an indication that the control has been activated, and in response to determining that the at least one event has occurred with respect to the first electronic document, notify the first computing device that the at least one event has occurred with respect to the first electronic document. | 1. A system, comprising: a source client executable on a first computing device, the source client configured to generate an electronic envelope including a first electronic document to be distributed over a network for electronic signature and an electronic signing template defining a set of at least one task that must be performed by an executor of the first electronic document to complete the electronic signature, the first electronic document being subject to a document-execution workflow comprising a plurality of events including the at least one task, the first electronic document including an embedded activatable control; and an electronic device coupled to the first computing device over the network, the electronic device configured to: receive from the first computing device an electronic selection of an identifier of at least one event of the plurality of events, wherein the electronic selection of the identifier is provided via a graphical user interface that is configured to: display identifiers of the plurality of events including envelope sent, envelope delivered, and envelope signed, receive selections of identifiers of each of the plurality of events, and receive from a user a selection of an identifier of the at least one event of the plurality of events, monitor, over the network, progress of the first electronic document through the workflow, determine that the at least one event has occurred with respect to the first electronic document, by receiving an indication that the control has been activated, and in response to determining that the at least one event has occurred with respect to the first electronic document, notify the first computing device that the at least one event has occurred with respect to the first electronic document. 2. The system of claim 1 , wherein: the source client is further configured to embed into the first document the activatable control; and the electronic device is further configured to determine that the event has occurred in response to receiving an indication that activated user has clicked a button in the first electronic document. | 0.72549 |
9,390,174 | 11 | 19 | 11. A system for providing search results, the system comprising: a database comprising a knowledge graph; and one or more processors configured to perform operations comprising: parsing a search query to identify one or more words; determining an entity reference from the search query based on the one or more identified words; analyzing the entity reference to determine a type of entity reference; identifying a list of properties associated with the determined type of the entity reference from the knowledge graph; ranking the list of properties associated with the determined type of the entity reference; identifying a property for generating a presentation of search results from the ranked list of properties, based at least in part on the search query and on the type of the entity reference; determining a presentation technique associated with the property for generating a presentation; and causing to be presented search results based on the corresponding presentation technique of the property on the knowledge graph for generating a presentation. | 11. A system for providing search results, the system comprising: a database comprising a knowledge graph; and one or more processors configured to perform operations comprising: parsing a search query to identify one or more words; determining an entity reference from the search query based on the one or more identified words; analyzing the entity reference to determine a type of entity reference; identifying a list of properties associated with the determined type of the entity reference from the knowledge graph; ranking the list of properties associated with the determined type of the entity reference; identifying a property for generating a presentation of search results from the ranked list of properties, based at least in part on the search query and on the type of the entity reference; determining a presentation technique associated with the property for generating a presentation; and causing to be presented search results based on the corresponding presentation technique of the property on the knowledge graph for generating a presentation. 19. The system of claim 11 , wherein identifying a property for generating a presentation of search results comprises selecting a property from the ranked list of property based at least in part on the search query. | 0.716359 |
8,442,826 | 1 | 4 | 1. A computer-implemented recognition system, comprising: a constraints component for parsing input data, the constraints component interfaces to a probability space; an integration component for integrating application-dependent information into the constraints component for the recognition processing, the application-dependent information comprises embedded slot grammars specific to a user from an n-gram language model; and a microprocessor that executes instructions stored in a memory. | 1. A computer-implemented recognition system, comprising: a constraints component for parsing input data, the constraints component interfaces to a probability space; an integration component for integrating application-dependent information into the constraints component for the recognition processing, the application-dependent information comprises embedded slot grammars specific to a user from an n-gram language model; and a microprocessor that executes instructions stored in a memory. 4. The system of claim 1 , wherein the application-dependent information is integrated into a reserved section of the probability space when available. | 0.808376 |
8,874,929 | 12 | 13 | 12. A system for cross domain discovery, comprising: a microprocessor configured to execute instructions of the user service component of the system; a plurality of user service components of the system, an object being uploaded into the system, each of user service components configured to generate a composite object structure of the uploaded object, the composite object structure including an object identification that is a random number, to detect an object identification collision, and to generate a new object identification of the composite object structure; an object service component configured to store an object having a first entity with a first restriction level and a second entity with a second restriction level, one of the first and second entities is an existing entity that has at least information of a person to contact for the object; a search service component configured to store first keywords in association with the first entity, and second keywords in association with the second entity, determine a search request having the first restriction level matching the first keywords, and respond to the search request with the first entity stored in the object service component; a policy service component configured to authorize the search request; and a key service component configured to generate a first symmetric key and a second symmetric key in association with the object, wherein the object service component is further configured to encrypt the first entity using the first symmetric key; encrypt the second entity using the second symmetric key; split the first symmetric key into a first key split and a second key split; and split the second symmetric key into a third key split and a forth key split; encrypt the first key split and the third key split using a public key of a first symmetric key pair belonging to the object service component, and encrypt the second key split and the forth key split using a public key of a second asymmetric key pair belonging to the policy service. | 12. A system for cross domain discovery, comprising: a microprocessor configured to execute instructions of the user service component of the system; a plurality of user service components of the system, an object being uploaded into the system, each of user service components configured to generate a composite object structure of the uploaded object, the composite object structure including an object identification that is a random number, to detect an object identification collision, and to generate a new object identification of the composite object structure; an object service component configured to store an object having a first entity with a first restriction level and a second entity with a second restriction level, one of the first and second entities is an existing entity that has at least information of a person to contact for the object; a search service component configured to store first keywords in association with the first entity, and second keywords in association with the second entity, determine a search request having the first restriction level matching the first keywords, and respond to the search request with the first entity stored in the object service component; a policy service component configured to authorize the search request; and a key service component configured to generate a first symmetric key and a second symmetric key in association with the object, wherein the object service component is further configured to encrypt the first entity using the first symmetric key; encrypt the second entity using the second symmetric key; split the first symmetric key into a first key split and a second key split; and split the second symmetric key into a third key split and a forth key split; encrypt the first key split and the third key split using a public key of a first symmetric key pair belonging to the object service component, and encrypt the second key split and the forth key split using a public key of a second asymmetric key pair belonging to the policy service. 13. The system of claim 12 , wherein the search service component further comprises: a hash table configured to store at least one of the first keywords and the second keywords. | 0.936101 |
9,483,224 | 1 | 13 | 1. A method for creating a document in a web application, and sending the document to a printer over a network, the web application executed by a web browser, the method comprising steps of: providing an intelligent module adapted to connect to the printer, the intelligent module configured to be set a network address, to receive the document, and to send the document to the printer; embedding an application program interface (API) in the web application, the API providing: (i) a first object for creating the document, the object including a command buffer, (ii) a first method element for processing the first object, the first method element being configured to add commands for controlling the printer into the command buffer, and creating the document according to the commands in the command buffer, (iii) a second object for sending the document, (iv) an address property element configured to designate the network address of the intelligent module, and (v) a second method element for processing the second object, the second method element configured to send the created document to the intelligent module over the network; setting the network address of the intelligent module into the address property element; creating the document by use of the first method element embedded in the web application; sending the document, by use of the second method element embedded in the web application, to the intelligent module having the network address designated by the address property element; and sending the document from the intelligent module to the printer. | 1. A method for creating a document in a web application, and sending the document to a printer over a network, the web application executed by a web browser, the method comprising steps of: providing an intelligent module adapted to connect to the printer, the intelligent module configured to be set a network address, to receive the document, and to send the document to the printer; embedding an application program interface (API) in the web application, the API providing: (i) a first object for creating the document, the object including a command buffer, (ii) a first method element for processing the first object, the first method element being configured to add commands for controlling the printer into the command buffer, and creating the document according to the commands in the command buffer, (iii) a second object for sending the document, (iv) an address property element configured to designate the network address of the intelligent module, and (v) a second method element for processing the second object, the second method element configured to send the created document to the intelligent module over the network; setting the network address of the intelligent module into the address property element; creating the document by use of the first method element embedded in the web application; sending the document, by use of the second method element embedded in the web application, to the intelligent module having the network address designated by the address property element; and sending the document from the intelligent module to the printer. 13. The method according to claim 1 , wherein: one of the commands is a text command for adding a text for printing to the command buffer; one of the commands is a text setting command for adding a parameter for setting a property of the text, to the command buffer; and the text setting command includes a first text setting parameter specifying at least one of a start position, an alignment, a language, a font, a style, a scale, or a size of the text. | 0.618928 |
7,574,053 | 6 | 7 | 6. The system of claim 1 , wherein the computer program generates a semantic cognition network, and wherein the semantic cognition network comprises the data object network, the processing object network, and a class object network. | 6. The system of claim 1 , wherein the computer program generates a semantic cognition network, and wherein the semantic cognition network comprises the data object network, the processing object network, and a class object network. 7. The system of claim 6 , wherein the class object network comprises a class domain, and wherein the parent process is unambiguously defined by the one of the plurality of neighborhood descriptions, the one algorithm of the set of algorithms, and the class domain. | 0.868421 |
7,764,771 | 10 | 11 | 10. A method of filling out an invention disclosure form, the method comprising: receiving a request from an inventor to connect to a network; supplying oral queries to the inventor over the network; receiving dictation from the inventor over the network in response to the oral queries, the dictation being related to a concept at least in part attributable to the inventor; converting the dictation to text with a computer having a processor; using the computer to place the text into the invention disclosure form; searching for prior art relating to the concept; attaching any prior art located during the search to the invention disclosure form; and transmitting the invention disclosure form with the located prior art to a recipient. | 10. A method of filling out an invention disclosure form, the method comprising: receiving a request from an inventor to connect to a network; supplying oral queries to the inventor over the network; receiving dictation from the inventor over the network in response to the oral queries, the dictation being related to a concept at least in part attributable to the inventor; converting the dictation to text with a computer having a processor; using the computer to place the text into the invention disclosure form; searching for prior art relating to the concept; attaching any prior art located during the search to the invention disclosure form; and transmitting the invention disclosure form with the located prior art to a recipient. 11. The method of claim 10 wherein transmitting the invention disclosure form to a recipient includes transmitting the invention disclosure form via e-mail. | 0.6 |
10,019,824 | 19 | 20 | 19. The computing system of claim 18 wherein the computer-executable instructions further control the computing system to display on the original image an annotation indicator and, when a user selects the object, provide the annotation to the user. | 19. The computing system of claim 18 wherein the computer-executable instructions further control the computing system to display on the original image an annotation indicator and, when a user selects the object, provide the annotation to the user. 20. The computing system of claim 19 wherein objects of the 3D model are color-coded so that when a user selects a pixel in the original image, a corresponding pixel in the model image is used to identify the object based on the color coding. | 0.9347 |
9,652,478 | 1 | 2 | 1. A method for generating a schema for data asset information, the method comprising: accessing complex type information corresponding to a logical relational data model that defines an organization of the data asset information, the logical relational data model including a parent entity and child entities corresponding to the parent entity; treating the complex type information to produce scrubbed complex type information, said treating of the complex type information including removing at least one foreign key from at least one of the child entities; translating the scrubbed complex type information to produce a hierarchical data model corresponding to the logical relational data model, the hierarchical data model including a plurality of containers respectively corresponding to the child entities of the logical relational data model, the treating and translating being carried out such that the at least one foreign key removed from the at least one child entity is omitted from a first level container in the hierarchical data model and is present in a second level container in the hierarchical data model, the first level container paralleling the child entity from which the foreign key is removed, the second level container being at a higher level in the hierarchical data model than that of the first level container; and generating a schema for the data asset information based upon the hierarchical data model. | 1. A method for generating a schema for data asset information, the method comprising: accessing complex type information corresponding to a logical relational data model that defines an organization of the data asset information, the logical relational data model including a parent entity and child entities corresponding to the parent entity; treating the complex type information to produce scrubbed complex type information, said treating of the complex type information including removing at least one foreign key from at least one of the child entities; translating the scrubbed complex type information to produce a hierarchical data model corresponding to the logical relational data model, the hierarchical data model including a plurality of containers respectively corresponding to the child entities of the logical relational data model, the treating and translating being carried out such that the at least one foreign key removed from the at least one child entity is omitted from a first level container in the hierarchical data model and is present in a second level container in the hierarchical data model, the first level container paralleling the child entity from which the foreign key is removed, the second level container being at a higher level in the hierarchical data model than that of the first level container; and generating a schema for the data asset information based upon the hierarchical data model. 2. The method of claim 1 , wherein said treating of the complex type information comprises replacing data types in the complex type information corresponding to the logical relational data model. | 0.704545 |
8,849,619 | 1 | 5 | 1. A system for generating three dimensional functional space reservation systems of a vehicle using delta storage, comprising: a processor; and memory coupled to the processor, Wherein the memory comprises a file reader tool including: a functional geometrical information (FGI) reader module for collecting functional, connectivity and geometrical information associated with two conceptual space reservation versions of the vehicle from one or more design databases upon receiving a request from a client device for three dimensional functional space reservation systems, wherein the two conceptual space reservation versions include a current conceptual space reservation version and a previous conceptual space reservation version, wherein the functional, connectivity and geometrical information associated with the two conceptual space reservation versions are transformed into a binary form, and wherein each conceptual space reservation version includes multiple design entities; a mathematical modeler module for receiving the binary form of the functional, connectivity and geometrical information associated with the two conceptual space reservation versions and creating associated mathematical cal models in an organized binary form for creating design entities associated with the two conceptual space reservation versions; a comparator and segregator module for receiving the mathematical models and outputting delta information detected from the two conceptual space reservation versions of the vehicle; a standardization module for applying a set of rules and checks governing a design of the vehicle to the design entities in the mathematical model of the current conceptual space reservation version and outputting standardized entities information; a functional mapper module for receiving the delta information from the comparator and segregator module and applying a set of functional attributes to the standardized entities associated with the delta information to create standardized functional entities associated with the delta information; and a writer module for generating the three dimensional functional space reservation systems including new part numbers for the design entities associated with the delta information for a computer-aided design (CAD) standard platform and storing the design entities in the generated three dimensional functional space reservation systems of the vehicle. | 1. A system for generating three dimensional functional space reservation systems of a vehicle using delta storage, comprising: a processor; and memory coupled to the processor, Wherein the memory comprises a file reader tool including: a functional geometrical information (FGI) reader module for collecting functional, connectivity and geometrical information associated with two conceptual space reservation versions of the vehicle from one or more design databases upon receiving a request from a client device for three dimensional functional space reservation systems, wherein the two conceptual space reservation versions include a current conceptual space reservation version and a previous conceptual space reservation version, wherein the functional, connectivity and geometrical information associated with the two conceptual space reservation versions are transformed into a binary form, and wherein each conceptual space reservation version includes multiple design entities; a mathematical modeler module for receiving the binary form of the functional, connectivity and geometrical information associated with the two conceptual space reservation versions and creating associated mathematical cal models in an organized binary form for creating design entities associated with the two conceptual space reservation versions; a comparator and segregator module for receiving the mathematical models and outputting delta information detected from the two conceptual space reservation versions of the vehicle; a standardization module for applying a set of rules and checks governing a design of the vehicle to the design entities in the mathematical model of the current conceptual space reservation version and outputting standardized entities information; a functional mapper module for receiving the delta information from the comparator and segregator module and applying a set of functional attributes to the standardized entities associated with the delta information to create standardized functional entities associated with the delta information; and a writer module for generating the three dimensional functional space reservation systems including new part numbers for the design entities associated with the delta information for a computer-aided design (CAD) standard platform and storing the design entities in the generated three dimensional functional space reservation systems of the vehicle. 5. The system of claim 1 , wherein the functional mapper module comprises a filter module to separate the design entities based on the delta information and to send the separated design entities information to the writer module. | 0.896833 |
9,325,508 | 33 | 41 | 33. The method of claim 32 , wherein the presentation authority operates under at least one of a plurality of operational policies and procedures of the presentation authority. | 33. The method of claim 32 , wherein the presentation authority operates under at least one of a plurality of operational policies and procedures of the presentation authority. 41. The method of claim 33 , wherein the relying party includes evaluating the operational policies and procedures of the presentation authority in determining whether to trust the digital signing signature. | 0.961567 |
8,935,303 | 1 | 7 | 1. A method of optimizing an output ranked list of recommended items given an input user, an input item list, and an input context, comprising: providing a multidimensional data set that comprises information of interactions from a plurality of users with a plurality of items and in a plurality of contexts; factorizing the multidimensional data set into a number of two-dimensional matrices, the number of two-dimensional matrices being equivalent to the number of dimensions that the multidimensional data set has; computing a mathematical recommendation model by optimizing an objective function over the two-dimensional matrices into which the multidimensional data set has been factorized, the recommendation model comprising a score value for each combination of user, item and context; and computing the output ranked list by applying the computed recommendation model to the input user, input item list and input context, wherein the recommendation model further comprises a ranked list of recommended items for each user and context, being each ranked list determined by sorting the scores of the plurality of items for each user and context; and wherein the objective function is a continuous function with infinite continuous derivatives that quantifies a relevance of the recommended items of each ranked list of the recommendation model, calculated over at least some of the plurality of users and over at least some of the plurality of contexts. | 1. A method of optimizing an output ranked list of recommended items given an input user, an input item list, and an input context, comprising: providing a multidimensional data set that comprises information of interactions from a plurality of users with a plurality of items and in a plurality of contexts; factorizing the multidimensional data set into a number of two-dimensional matrices, the number of two-dimensional matrices being equivalent to the number of dimensions that the multidimensional data set has; computing a mathematical recommendation model by optimizing an objective function over the two-dimensional matrices into which the multidimensional data set has been factorized, the recommendation model comprising a score value for each combination of user, item and context; and computing the output ranked list by applying the computed recommendation model to the input user, input item list and input context, wherein the recommendation model further comprises a ranked list of recommended items for each user and context, being each ranked list determined by sorting the scores of the plurality of items for each user and context; and wherein the objective function is a continuous function with infinite continuous derivatives that quantifies a relevance of the recommended items of each ranked list of the recommendation model, calculated over at least some of the plurality of users and over at least some of the plurality of contexts. 7. The method of claim 1 wherein the recommendation model is optimized with a gradient ascend algorithm. | 0.905282 |
8,320,681 | 1 | 2 | 1. A method for recognizing a character in a character recognizing apparatus, the method comprising the steps of: activating a camera in accordance with a character recognition request, and setting a preview mode for displaying one or more images photographed through the camera in real time; controlling an auto focus of the camera and obtaining an image having a predetermined level of clarity for character recognition from the one or more images obtained in the preview mode; character-recognition-processing the image for character recognition so as to extract recognition result data; and drawing a final recognition character row that excludes non-character data from the recognition result data, wherein obtaining the image for character recognition comprises: determining whether a character exists in the one or more images obtained in the preview mode; and controlling the auto focus of the camera and obtaining the image having a predetermined level of clarity from the one or more images obtained in the preview mode for character recognition, when a character exists, and wherein the step of controlling the auto focus of the camera comprises: identifying whether the outlines of the existed character is as clear as the predetermined level of clarity or not, determining that a blur is present in image including the existed character from the one or more images and executing the auto focus of the camera, when the outlines of the existed character is not as clear as the predetermined level of clarity. | 1. A method for recognizing a character in a character recognizing apparatus, the method comprising the steps of: activating a camera in accordance with a character recognition request, and setting a preview mode for displaying one or more images photographed through the camera in real time; controlling an auto focus of the camera and obtaining an image having a predetermined level of clarity for character recognition from the one or more images obtained in the preview mode; character-recognition-processing the image for character recognition so as to extract recognition result data; and drawing a final recognition character row that excludes non-character data from the recognition result data, wherein obtaining the image for character recognition comprises: determining whether a character exists in the one or more images obtained in the preview mode; and controlling the auto focus of the camera and obtaining the image having a predetermined level of clarity from the one or more images obtained in the preview mode for character recognition, when a character exists, and wherein the step of controlling the auto focus of the camera comprises: identifying whether the outlines of the existed character is as clear as the predetermined level of clarity or not, determining that a blur is present in image including the existed character from the one or more images and executing the auto focus of the camera, when the outlines of the existed character is not as clear as the predetermined level of clarity. 2. The method as claimed in claim 1 , wherein determining whether the character exists comprises: obtaining the one or more images obtained in the preview mode; obtaining a character detection area in the one or more images; performing edge filtering so as to extract a number of edges; determining that a character exists when the extracted number of edges is greater than or equal to a boundary value; and re-performing the steps of determining whether the character exists when the extracted number of edges is less than the boundary value. | 0.500919 |
9,236,049 | 14 | 15 | 14. The mash-up service generation method of claim 12 , wherein the providing of the runtime code comprises driving the runtime code to generate a mash-up service. | 14. The mash-up service generation method of claim 12 , wherein the providing of the runtime code comprises driving the runtime code to generate a mash-up service. 15. The mash-up service generation method of claim 14 , further comprising displaying the mash-up service on a web browser. | 0.957557 |
7,725,481 | 1 | 13 | 1. A computer-implemented method for providing a computer user with information related to a word in electronic content, the method comprising: receiving a first request for information corresponding to a word appearing in electronic content being rendered to a party submitting the first request when the first request is submitted, deriving context information for the word based on the electronic content being rendered to the party when the first request is submitted; storing the context information in association with the word; receiving a second request, at a time subsequent to the first request, for information corresponding to the word; in response to receiving the second request, accessing, from electronic storage, the context information stored in association with the word and derived based on the electronic content rendered during the first request; and enabling presentation, to a party submitting the second request, of the accessed context information derived based on the electronic content rendered during the first request along with information corresponding to the word. | 1. A computer-implemented method for providing a computer user with information related to a word in electronic content, the method comprising: receiving a first request for information corresponding to a word appearing in electronic content being rendered to a party submitting the first request when the first request is submitted, deriving context information for the word based on the electronic content being rendered to the party when the first request is submitted; storing the context information in association with the word; receiving a second request, at a time subsequent to the first request, for information corresponding to the word; in response to receiving the second request, accessing, from electronic storage, the context information stored in association with the word and derived based on the electronic content rendered during the first request; and enabling presentation, to a party submitting the second request, of the accessed context information derived based on the electronic content rendered during the first request along with information corresponding to the word. 13. The computer-implemented method of claim 1 wherein: receiving the first request and receiving the second request includes receiving a first request for a definition of a word and receiving a second request for the definition of the word; and enabling presentation, to the party submitting the second request, of the accessed context information derived based on the electronic content rendered during the first request along with information corresponding to the word includes enabling presentation, to the party submitting the second request, of the accessed context information derived based on the electronic content rendered during the first request along with the definition of the word. | 0.500717 |
9,137,345 | 9 | 10 | 9. The communication system of claim 8 wherein a form document is populated by the second communication terminal based upon the saved first text data and second text data. | 9. The communication system of claim 8 wherein a form document is populated by the second communication terminal based upon the saved first text data and second text data. 10. The communication system of claim 9 further comprising a second communication device, and wherein the second communication terminal sends the form document to at least one of the second communication device and the first communication device. | 0.966366 |
8,261,196 | 1 | 11 | 1. A method of displaying search results and usage metrics for a search of one or more documents that a user has opened and had in focus, the method comprising: monitoring documents that the user has opened and had in focus, wherein a document being opened by the user and in focus of the user includes a document relative to which an operation has been performed by the user within a predetermined time interval; storing, on a workstation of a user, an index that includes entries for only monitored documents that the user has opened and had in focus, wherein an index entry is created or modified for each of the monitored documents only in response to the user having opened and had in focus that monitored document, wherein only the user has performed an operation relative to that monitored document within the predetermined time interval; receiving, from the user, a request to search said index; presenting a user interface, said user interface displaying search results including a listing of documents from the monitored documents and one or more graphical visualizations characterizing the search results in the listing of documents, wherein documents in the listing includes documents relative to each of which an operation has been performed by the user within the predetermined time interval; receiving, from the user, an input instruction to display usage metrics for a selected one of said documents in the listing of documents; and updating said user interface to display said usage metrics, wherein said usage metrics include a total amount of time the user had a selected document opened and in focus, wherein the total amount of time the user has spent on the selected document when the selected document is open and in focus includes one or more instances when the user has performed an operation relative to the selected document within the predetermined time interval. | 1. A method of displaying search results and usage metrics for a search of one or more documents that a user has opened and had in focus, the method comprising: monitoring documents that the user has opened and had in focus, wherein a document being opened by the user and in focus of the user includes a document relative to which an operation has been performed by the user within a predetermined time interval; storing, on a workstation of a user, an index that includes entries for only monitored documents that the user has opened and had in focus, wherein an index entry is created or modified for each of the monitored documents only in response to the user having opened and had in focus that monitored document, wherein only the user has performed an operation relative to that monitored document within the predetermined time interval; receiving, from the user, a request to search said index; presenting a user interface, said user interface displaying search results including a listing of documents from the monitored documents and one or more graphical visualizations characterizing the search results in the listing of documents, wherein documents in the listing includes documents relative to each of which an operation has been performed by the user within the predetermined time interval; receiving, from the user, an input instruction to display usage metrics for a selected one of said documents in the listing of documents; and updating said user interface to display said usage metrics, wherein said usage metrics include a total amount of time the user had a selected document opened and in focus, wherein the total amount of time the user has spent on the selected document when the selected document is open and in focus includes one or more instances when the user has performed an operation relative to the selected document within the predetermined time interval. 11. The method of claim 1 , further comprising: specifying one or more documents that should not be monitored, or specifying one or more documents for which an index entry should not be created. | 0.758105 |
8,433,708 | 16 | 17 | 16. The computer readable medium of claim 1 further comprising a step of: generating a corpus report using the correlation data structure, the corpus report comprising rows comprising: a) prior context, b) a word or phrase, c) subsequent context, and d) an internal citation. | 16. The computer readable medium of claim 1 further comprising a step of: generating a corpus report using the correlation data structure, the corpus report comprising rows comprising: a) prior context, b) a word or phrase, c) subsequent context, and d) an internal citation. 17. The computer readable medium of claim 16 wherein the corpus report is based on a single word root. | 0.964485 |
8,019,767 | 2 | 3 | 2. The computer-implementable method according to claim 1 , further comprising: receiving at least one filtering preference for displaying said tree structure. | 2. The computer-implementable method according to claim 1 , further comprising: receiving at least one filtering preference for displaying said tree structure. 3. The computer-implementable method according to claim 2 , wherein said outputting further comprises: outputting said tree structure wherein quality of service (QoS) elements specified by said at least one filtering preference are expanded during display of said tree structure. | 0.858087 |
10,140,591 | 8 | 9 | 8. The method of claim 2 , wherein the subset of the content related to the post object comprises profile information corresponding to one or more users of the plurality of users, wherein the one or more users are associated with the post object. | 8. The method of claim 2 , wherein the subset of the content related to the post object comprises profile information corresponding to one or more users of the plurality of users, wherein the one or more users are associated with the post object. 9. The method of claim 8 , wherein performing a transformation on the subset of the content related to the post object comprises aggregating the subset of the content related to the post object to produce one or more pieces of aggregated content. | 0.971508 |
8,146,051 | 10 | 11 | 10. A computer software product for representing software, including a non-transitory computer-readable storage medium in which computer program instructions are stored, which instructions, when executed by a computer, cause the computer to perform the steps of: defining actual semantic concerns relating to the software; constructing a plurality of models representing respective ones of the actual semantic concerns and actual semantic inter-relationships therebetween, wherein the models have model elements comprising semantic elements and conform to a meta-model, and wherein the actual semantic concerns comprise dynamic actual semantic concerns that are subject to updating, and an n-ary relationship exists between at least one group of the model elements that comprises a set of the actual semantic concerns; executing a graphic interface to display a graphic representation of the models; constructing semantic queries to validate the models; detecting a re-evaluation event; responsively to the re-evaluation event making a revision of the graphic representation to conform the dynamic actual semantic concerns to the re-evaluation event; conforming the models with the revision of the graphic representation, updating the semantic queries in compliance with the conformed models; and executing the updated semantic queries to determine whether the software violates a predetermined validation rule. | 10. A computer software product for representing software, including a non-transitory computer-readable storage medium in which computer program instructions are stored, which instructions, when executed by a computer, cause the computer to perform the steps of: defining actual semantic concerns relating to the software; constructing a plurality of models representing respective ones of the actual semantic concerns and actual semantic inter-relationships therebetween, wherein the models have model elements comprising semantic elements and conform to a meta-model, and wherein the actual semantic concerns comprise dynamic actual semantic concerns that are subject to updating, and an n-ary relationship exists between at least one group of the model elements that comprises a set of the actual semantic concerns; executing a graphic interface to display a graphic representation of the models; constructing semantic queries to validate the models; detecting a re-evaluation event; responsively to the re-evaluation event making a revision of the graphic representation to conform the dynamic actual semantic concerns to the re-evaluation event; conforming the models with the revision of the graphic representation, updating the semantic queries in compliance with the conformed models; and executing the updated semantic queries to determine whether the software violates a predetermined validation rule. 11. The computer software product according to claim 10 , wherein the re-evaluation event comprises an alteration in one of the models. | 0.723361 |
7,900,134 | 10 | 14 | 10. A method of providing a user interface comprising: considering multiple parameters one of which includes an XSL-T file; and based upon the considered parameters, rendering a user interface sufficient to enable a user to interact with a DHTML view that has been rendered from an XML document using a crystal, the crystal containing one or more behaviors and at least one XSL-T file; and receiving, via the user interface, a user interaction with the DHTML view; and mapping, via the one or more behaviors, the user interaction to the XML document. | 10. A method of providing a user interface comprising: considering multiple parameters one of which includes an XSL-T file; and based upon the considered parameters, rendering a user interface sufficient to enable a user to interact with a DHTML view that has been rendered from an XML document using a crystal, the crystal containing one or more behaviors and at least one XSL-T file; and receiving, via the user interface, a user interaction with the DHTML view; and mapping, via the one or more behaviors, the user interaction to the XML document. 14. The method of claim 10 , wherein the parameters comprise: a user location within a particular document; a portion of an XML schema that corresponds to a user's selection; and one or more UI types that would be desirable to generate. | 0.514403 |
10,002,187 | 13 | 23 | 13. A computer readable medium having stored thereon a sequence of instructions which, when executed by a processor causes the processor to execute a method comprising: generating a user interface that displays analysis results identified from within one or more social media data sources, the user interface comprising: (a) a first interface portion of the user interface comprising a list of one or more analysis results identified from within one or more social media data sources, an individual analysis result from among the one or more analysis results being selectable to display a set of terms associated with a selected individual analysis result in a second interface portion, (b) the second interface portion of the user interface comprising the set of terms, a first interface control, and a second interface control, the set of terms associated with the selected individual analysis result, the first interface control constraining a search to include themes that correspond to the selected individual analysis result, the second interface control constraining the search to exclude the themes that correspond to the selected individual analysis result, and (c) a third interface portion of the user interface comprising a set of one or more semantic filters selected according to the second interface portion; receiving a search criteria to perform a search of content from the one or more social media data sources; performing the search of the content from the one or more social media data sources to generate the list of the one or more analysis results, a volatility index corresponding to a level of commonality between two or more themes being generated for the one or more analysis results, the volatility index usable to automatically control creation of a new topic based at least in part upon a threshold value established for the volatility index, the level of commonality between the two or more themes is calculated by computing centroids for the two or more themes and determining distances between the centroids; displaying the list of one or more analysis results identified from within one or more social media data sources pertaining to the search criteria in the first interface portion of the user interface; receiving a selection of the first or second interface control in the second interface portion of the user interface corresponding to an application of a semantic filter, the semantic filter constraining the search of the content from the one or more social media data sources by: (a) adding the semantic filter to definition parameters for a new topic if the first interface control is selected; (b) adding the semantic filter to the set of one or more semantic filters in the third interface portion of the user interface if the second interface control is selected; and (c) performing a modified search of the content with application of the semantic filter, the modified search updating the list of one or more analysis results identified from within one or more social media data sources in the first interface portion of the user interface to either remove or add results in the first interface portion that pertain to the semantic filter; and creating the new topic based at least in part on the definition parameters, wherein the new topic corresponds to the search criteria and the semantic filter. | 13. A computer readable medium having stored thereon a sequence of instructions which, when executed by a processor causes the processor to execute a method comprising: generating a user interface that displays analysis results identified from within one or more social media data sources, the user interface comprising: (a) a first interface portion of the user interface comprising a list of one or more analysis results identified from within one or more social media data sources, an individual analysis result from among the one or more analysis results being selectable to display a set of terms associated with a selected individual analysis result in a second interface portion, (b) the second interface portion of the user interface comprising the set of terms, a first interface control, and a second interface control, the set of terms associated with the selected individual analysis result, the first interface control constraining a search to include themes that correspond to the selected individual analysis result, the second interface control constraining the search to exclude the themes that correspond to the selected individual analysis result, and (c) a third interface portion of the user interface comprising a set of one or more semantic filters selected according to the second interface portion; receiving a search criteria to perform a search of content from the one or more social media data sources; performing the search of the content from the one or more social media data sources to generate the list of the one or more analysis results, a volatility index corresponding to a level of commonality between two or more themes being generated for the one or more analysis results, the volatility index usable to automatically control creation of a new topic based at least in part upon a threshold value established for the volatility index, the level of commonality between the two or more themes is calculated by computing centroids for the two or more themes and determining distances between the centroids; displaying the list of one or more analysis results identified from within one or more social media data sources pertaining to the search criteria in the first interface portion of the user interface; receiving a selection of the first or second interface control in the second interface portion of the user interface corresponding to an application of a semantic filter, the semantic filter constraining the search of the content from the one or more social media data sources by: (a) adding the semantic filter to definition parameters for a new topic if the first interface control is selected; (b) adding the semantic filter to the set of one or more semantic filters in the third interface portion of the user interface if the second interface control is selected; and (c) performing a modified search of the content with application of the semantic filter, the modified search updating the list of one or more analysis results identified from within one or more social media data sources in the first interface portion of the user interface to either remove or add results in the first interface portion that pertain to the semantic filter; and creating the new topic based at least in part on the definition parameters, wherein the new topic corresponds to the search criteria and the semantic filter. 23. The computer readable medium of claim 13 , in which the volatility index is displayable in an interface. | 0.852459 |
7,725,499 | 19 | 20 | 19. The method of claim 14 further comprising the step of creating a database axis wherein at least one anchor point acts as a pool anchor to permit storage of a plurality of information units. | 19. The method of claim 14 further comprising the step of creating a database axis wherein at least one anchor point acts as a pool anchor to permit storage of a plurality of information units. 20. The method of claim 19 further comprising linking to part of an information unit, a complete Information unit, or an address range. | 0.982385 |
9,972,320 | 10 | 13 | 10. A computer-implemented method comprising: receiving, by a server and from a first computing device, data indicating that the first computing device is configured to respond to a particular, predefined hotword; receiving, by the server and from a second computing device that is in a vicinity of the first computing device, data indicating that the second computing device is configured to respond to the particular, predefined hotword; determining a group identifier that identifies the first computing device and the second computing device; receiving, by a server and from the first device, (i) data indicating that the first computing device likely received the particular, predefined hotword, (ii) data identifying the first computing device, and (iii) the group identifier that identifies the first computing device and the second computing device; accessing context data that indicates a context of the first computing device; based on the context data of the first computing device, determining that the first computing device commence speech recognition processing on audio data associated with the particular, predefined hotword; and transmitting, to the first computing device, an instruction to commence speech recognition processing on the audio data associated with the particular, predefined hotword. | 10. A computer-implemented method comprising: receiving, by a server and from a first computing device, data indicating that the first computing device is configured to respond to a particular, predefined hotword; receiving, by the server and from a second computing device that is in a vicinity of the first computing device, data indicating that the second computing device is configured to respond to the particular, predefined hotword; determining a group identifier that identifies the first computing device and the second computing device; receiving, by a server and from the first device, (i) data indicating that the first computing device likely received the particular, predefined hotword, (ii) data identifying the first computing device, and (iii) the group identifier that identifies the first computing device and the second computing device; accessing context data that indicates a context of the first computing device; based on the context data of the first computing device, determining that the first computing device commence speech recognition processing on audio data associated with the particular, predefined hotword; and transmitting, to the first computing device, an instruction to commence speech recognition processing on the audio data associated with the particular, predefined hotword. 13. The method of claim 10 , wherein the context data that indicates a context of the first computing device comprises data indicating one of more capabilities of the first computing device, wherein determining that the first computing device commence speech recognition processing on audio data associated with the particular, predefined hotword is based on the one of more capabilities of the first computing device. | 0.822731 |
8,502,783 | 18 | 19 | 18. A handheld electronic device comprising: an input apparatus; an output apparatus; and a processor apparatus; the input apparatus including a number of input members, the number of input members including a plurality of linguistic input members, each linguistic input member of at least a portion of the plurality of linguistic input members having a plurality of linguistic elements assigned thereto; the processor apparatus including a processor and a memory, the memory storing a plurality of word objects each corresponding to one of a plurality of stored words; the output apparatus including a display; the processor being adapted to receive an ambiguous input comprising a number of actuations of a number of the plurality of linguistic input members, at least one of the number of actuations being an actuation of one of the linguistic input members having a plurality of linguistic elements assigned thereto, wherein the actuation of the one of the linguistic input members corresponds to each of the plurality of linguistic elements assigned thereto, and, responsive to the ambiguous input, to display at a first location on the display a plurality of outputs, each corresponding to the ambiguous input, and at least one of the plurality of outputs being an orphan prefix corresponding to the ambiguous input, wherein the orphan prefix consists of k linguistic elements, k being the quantity of the number of actuations, and wherein the orphan prefix is different from the first k characters in each of the plurality of stored words. | 18. A handheld electronic device comprising: an input apparatus; an output apparatus; and a processor apparatus; the input apparatus including a number of input members, the number of input members including a plurality of linguistic input members, each linguistic input member of at least a portion of the plurality of linguistic input members having a plurality of linguistic elements assigned thereto; the processor apparatus including a processor and a memory, the memory storing a plurality of word objects each corresponding to one of a plurality of stored words; the output apparatus including a display; the processor being adapted to receive an ambiguous input comprising a number of actuations of a number of the plurality of linguistic input members, at least one of the number of actuations being an actuation of one of the linguistic input members having a plurality of linguistic elements assigned thereto, wherein the actuation of the one of the linguistic input members corresponds to each of the plurality of linguistic elements assigned thereto, and, responsive to the ambiguous input, to display at a first location on the display a plurality of outputs, each corresponding to the ambiguous input, and at least one of the plurality of outputs being an orphan prefix corresponding to the ambiguous input, wherein the orphan prefix consists of k linguistic elements, k being the quantity of the number of actuations, and wherein the orphan prefix is different from the first k characters in each of the plurality of stored words. 19. The handheld electronic device of claim 18 , the processor further being adapted to display at a second location on the display a disambiguation of the ambiguous input, wherein the disambiguation is one of the plurality of outputs displayed at the first location. | 0.924234 |
9,589,074 | 11 | 16 | 11. A system for identifying duplicate crash dumps, the system comprising: a crash dump data store, wherein: the crash dump data store includes a plurality of crash dumps; and the plurality of crash dumps comprises function signatures; a computer system running an application, wherein when the application crashes, a first crash dump is triggered; and a function matching module operating on a server that is in communication with the computer system, wherein: the function matching module receives the first crash dump from the computer system; the function matching module extracts, from the first crash dump, a first function signature of a function that caused the first crash dump; the function matching module searches the plurality of crash dumps from the crash dump data store for function signatures that substantially match the first function signature by: performing an approximate string-match between each of the function signatures and the first function signature; comparing the approximate string-matches to a first threshold; performing an exact string match between each of the function signatures and the first function signature; comparing the exact string-matches to a second threshold; combining weighted results of the approximate string-match with weighted results of the exact string match to generate match scores for each of the function signatures; comparing the match scores to a third threshold; and identifying the function signatures that substantially match the first function signature based on: the comparing of the approximate string-matches to the first threshold; the comparing of the exact string-matches to the second threshold; and the comparing of the match scores to the third threshold. | 11. A system for identifying duplicate crash dumps, the system comprising: a crash dump data store, wherein: the crash dump data store includes a plurality of crash dumps; and the plurality of crash dumps comprises function signatures; a computer system running an application, wherein when the application crashes, a first crash dump is triggered; and a function matching module operating on a server that is in communication with the computer system, wherein: the function matching module receives the first crash dump from the computer system; the function matching module extracts, from the first crash dump, a first function signature of a function that caused the first crash dump; the function matching module searches the plurality of crash dumps from the crash dump data store for function signatures that substantially match the first function signature by: performing an approximate string-match between each of the function signatures and the first function signature; comparing the approximate string-matches to a first threshold; performing an exact string match between each of the function signatures and the first function signature; comparing the exact string-matches to a second threshold; combining weighted results of the approximate string-match with weighted results of the exact string match to generate match scores for each of the function signatures; comparing the match scores to a third threshold; and identifying the function signatures that substantially match the first function signature based on: the comparing of the approximate string-matches to the first threshold; the comparing of the exact string-matches to the second threshold; and the comparing of the match scores to the third threshold. 16. The system of claim 11 , wherein extracting the first function signature from the crash dump comprises identifying unique function signatures that are called when an application crashes. | 0.536585 |
9,118,704 | 1 | 2 | 1. A homoglyph monitoring system comprising: a memory to store machine readable instructions; and at least one processor to execute the machine readable instructions in the memory to: receive a target domain name, create potential attack vector strings based on the target domain name, including: identify a homoglyph in an index of homoglyphs that is similar to a character in the target domain name, determine whether a similarity between the homoglyph and the character of the target domain name is greater than a minimum similarity threshold, and in response to a determination that the similarity is greater than the minimum similarity threshold, replace the character in the target domain name with the homoglyph to create one of the potential attack vector strings; and facilitate searching domain name system (DNS) servers in a target geographic region based on the potential attack vector strings and determine from results of the searching whether a DNS record in the results includes one of the potential attack vector strings. | 1. A homoglyph monitoring system comprising: a memory to store machine readable instructions; and at least one processor to execute the machine readable instructions in the memory to: receive a target domain name, create potential attack vector strings based on the target domain name, including: identify a homoglyph in an index of homoglyphs that is similar to a character in the target domain name, determine whether a similarity between the homoglyph and the character of the target domain name is greater than a minimum similarity threshold, and in response to a determination that the similarity is greater than the minimum similarity threshold, replace the character in the target domain name with the homoglyph to create one of the potential attack vector strings; and facilitate searching domain name system (DNS) servers in a target geographic region based on the potential attack vector strings and determine from results of the searching whether a DNS record in the results includes one of the potential attack vector strings. 2. The homoglyph monitoring system of claim 1 , wherein the at least one processor is further to execute the machine readable instructions to: store the index of homoglyphs for each character of a plurality of characters in a glyph collision database in the memory. | 0.50188 |
10,057,199 | 7 | 17 | 7. The method of claim 1 , wherein the qualitative analysis comprises a collective qualitative analysis of a subset of the impressions related to the comment. | 7. The method of claim 1 , wherein the qualitative analysis comprises a collective qualitative analysis of a subset of the impressions related to the comment. 17. The method of claim 7 , wherein the collective qualitative analysis is based on a plurality of different categories of interactions for the impressions in the subset. | 0.949435 |
8,965,835 | 1 | 2 | 1. A system for analyzing sentiment trends based on term taxonomies of user generated content, comprising: a network interface enabling access to one or more data sources through a network; a mining unit for collecting textual content from the one or more data sources and generating phrases, the phrases including sentiment phrases and non-sentiment phrases, each of the sentiment phrases including one or more words describing a sentiment, the sentiment being any one of a positive sentiment, a neutral sentiment, and a negative sentiment, each of the sentiment phrases being associated with a score indicating whether the sentiment phrase describes the sentiment; a non-transitory data warehouse storage medium connected to the network; and an analysis unit for generating term taxonomies that include at least associations between a non-sentiment phrase and at least one sentiment phrase based on the generated phrases, wherein generated term taxonomies are saved in the data warehouse, the analysis unit is further configured to periodically statistically analyze the stored term taxonomies to determine at least a statistical trend by performing a correlation analysis on at least two term taxonomies including performing a first correlation and a second correlation, wherein the first correlation is performed on a first stored term taxonomy comprising a non-sentiment phrase and a first sentiment phrase provided by a first group of users and wherein the second correlation is performed on a second stored term taxonomy including said non-sentiment phrase and a second sentiment phrase provided by a second group of users, wherein the first sentiment phrase is different from the second sentiment phrase and the first group of users is different from the second group of users, the analysis unit is further configured to store results of the at least statistical trend in the data warehouse storage, wherein the stored results are available upon receiving a request to generate a trend report regarding the at least statistical trend, wherein the analysis unit is further configured to perform a dynamic weighting of trends from different data sources of the one or more data sources based on at least a frequency that taxonomies results from each data source change. | 1. A system for analyzing sentiment trends based on term taxonomies of user generated content, comprising: a network interface enabling access to one or more data sources through a network; a mining unit for collecting textual content from the one or more data sources and generating phrases, the phrases including sentiment phrases and non-sentiment phrases, each of the sentiment phrases including one or more words describing a sentiment, the sentiment being any one of a positive sentiment, a neutral sentiment, and a negative sentiment, each of the sentiment phrases being associated with a score indicating whether the sentiment phrase describes the sentiment; a non-transitory data warehouse storage medium connected to the network; and an analysis unit for generating term taxonomies that include at least associations between a non-sentiment phrase and at least one sentiment phrase based on the generated phrases, wherein generated term taxonomies are saved in the data warehouse, the analysis unit is further configured to periodically statistically analyze the stored term taxonomies to determine at least a statistical trend by performing a correlation analysis on at least two term taxonomies including performing a first correlation and a second correlation, wherein the first correlation is performed on a first stored term taxonomy comprising a non-sentiment phrase and a first sentiment phrase provided by a first group of users and wherein the second correlation is performed on a second stored term taxonomy including said non-sentiment phrase and a second sentiment phrase provided by a second group of users, wherein the first sentiment phrase is different from the second sentiment phrase and the first group of users is different from the second group of users, the analysis unit is further configured to store results of the at least statistical trend in the data warehouse storage, wherein the stored results are available upon receiving a request to generate a trend report regarding the at least statistical trend, wherein the analysis unit is further configured to perform a dynamic weighting of trends from different data sources of the one or more data sources based on at least a frequency that taxonomies results from each data source change. 2. The system of claim 1 , wherein the analysis unit is further configured to provide the trend report respective of at least one sentiment phrase with respect of at least one non-sentiment phrase. | 0.692188 |
7,503,006 | 18 | 19 | 18. The system of claim 17 , wherein prior to displaying the visual indicator, the machine instructions further cause the processor to carry out the function of determining whether the listener has elected to hear voice communications from the voice speaker. | 18. The system of claim 17 , wherein prior to displaying the visual indicator, the machine instructions further cause the processor to carry out the function of determining whether the listener has elected to hear voice communications from the voice speaker. 19. The system of claim 18 , wherein the machine instructions further cause the processor to carry out at least one of the functions of: (a) determining whether the listener has muted voice communications from the voice speaker; and (b) determining whether the voice speaker provided evidence that the voice speaker is trusted by the listener, so that voice communications from the voice speaker are allowed to be heard by the listener. | 0.893294 |
9,880,693 | 1 | 4 | 1. A method, implemented at a computer system that includes one or more processors, for automatically editing storyboards based on a learned user-specific editing style, the method comprising: determining a first set of characteristics for a first plurality of media content items in a first storyboard, including: receiving first user input associating each of the first plurality of media content items with one or more of a first plurality of cells of a first storyboard; and analyzing each of the first plurality of media content items, including their associations with the first plurality of cells, to identify the first set of characteristics of the first plurality of media content items; determining a set of user-specific editing characteristics applied to the first plurality of media content items in the first story board, including: receiving second user input comprising a set of editing decisions, to create an edited first storyboard, the set of editing decisions including a plurality of editing decisions applied to the first plurality of cells to edit the first plurality of media content items in the first storyboard; and based on receiving the second user input, automatically defining a user-specific editing style, including comparing the first storyboard to the edited first storyboard to determine one or more user-specific editing style rules corresponding to the set of editing decisions that resulted in the differences between the first storyboard and the edited first storyboard, and defining metadata representing at least one of the plurality of editing decisions applied to the first plurality of cells; and automatically applying the user-specific editing style to a second plurality of media content items, including: receiving third user input associating each of the second plurality of media content items with one or more of a second plurality of cells of a second storyboard; analyzing each of the second plurality of media content items, including, their associations with the second plurality of cells, to identify a second set of characteristics of the second plurality of media content items; comparing the first set of characteristics of the first plurality of media content items with the second set of characteristics of the second plurality of media content items, to identify at least one of the second plurality of media content items that has at least one characteristic that matches at least one characteristic of at least one of the first plurality of media content items; automatically creating an edited second storyboard, by at least applying the user-specific editing style to the identified at least one of the second plurality of media content items that has at least one characteristic that matches at least one characteristic of at least one of the first plurality of media content items; and displaying the edited second storyboard. | 1. A method, implemented at a computer system that includes one or more processors, for automatically editing storyboards based on a learned user-specific editing style, the method comprising: determining a first set of characteristics for a first plurality of media content items in a first storyboard, including: receiving first user input associating each of the first plurality of media content items with one or more of a first plurality of cells of a first storyboard; and analyzing each of the first plurality of media content items, including their associations with the first plurality of cells, to identify the first set of characteristics of the first plurality of media content items; determining a set of user-specific editing characteristics applied to the first plurality of media content items in the first story board, including: receiving second user input comprising a set of editing decisions, to create an edited first storyboard, the set of editing decisions including a plurality of editing decisions applied to the first plurality of cells to edit the first plurality of media content items in the first storyboard; and based on receiving the second user input, automatically defining a user-specific editing style, including comparing the first storyboard to the edited first storyboard to determine one or more user-specific editing style rules corresponding to the set of editing decisions that resulted in the differences between the first storyboard and the edited first storyboard, and defining metadata representing at least one of the plurality of editing decisions applied to the first plurality of cells; and automatically applying the user-specific editing style to a second plurality of media content items, including: receiving third user input associating each of the second plurality of media content items with one or more of a second plurality of cells of a second storyboard; analyzing each of the second plurality of media content items, including, their associations with the second plurality of cells, to identify a second set of characteristics of the second plurality of media content items; comparing the first set of characteristics of the first plurality of media content items with the second set of characteristics of the second plurality of media content items, to identify at least one of the second plurality of media content items that has at least one characteristic that matches at least one characteristic of at least one of the first plurality of media content items; automatically creating an edited second storyboard, by at least applying the user-specific editing style to the identified at least one of the second plurality of media content items that has at least one characteristic that matches at least one characteristic of at least one of the first plurality of media content items; and displaying the edited second storyboard. 4. The method of claim 1 , wherein receiving the first media content items comprises receiving, via a drag and drop model in a user interface, the first media content items into the first plurality of cells in the first storyboard. | 0.920455 |
9,104,659 | 6 | 8 | 6. The method of claim 1 further comprising, in response to the detection of the one member of the defined set of confidential expression patterns occurring in the document content, using the electronic processing platform to redact the occurrence of the detected one member expression. | 6. The method of claim 1 further comprising, in response to the detection of the one member of the defined set of confidential expression patterns occurring in the document content, using the electronic processing platform to redact the occurrence of the detected one member expression. 8. The method of claim 6 further comprising using the electronic processing platform to redact the set of confidential expression patterns occurring in the document content according to a system-defined template. | 0.952805 |
9,471,695 | 1 | 3 | 1. A method for generating semantic image navigation experiences, the method comprising: selecting, by one or more computing devices, a first geographic entity of a plurality of distinct geographic entities; identifying, by the one or more computing devices, a plurality of distinct geographic sub-entities, each distinct geographic sub-entity having a geographic containment relationship with the first geographic entity, the plurality of distinct geographic sub-entities including: a first distinct geographic sub-entity that is both (i) visually represented by at least one landmark corresponding to the first distinct geographic sub-entity and (ii) associated with a pre-stored navigation experience of a plurality of pre-stored navigation experiences that is unique to the first distinct geographic sub-entity, and a second distinct geographic sub-entity that is not at least one of (i) visually represented by at least one landmark corresponding to the second distinct geographic sub-entity and (ii) associated with a pre-stored navigation experience of the plurality of pre-stored navigation experiences that is unique to the second distinct geographic sub-entity, wherein each pre-stored navigation experience in the plurality of pre-stored navigation experiences corresponds to a given geographic entity and comprises a sequence of images and transitions between the images that produces a tour of at least one landmark associated with the given geographic entity; filtering, by the one or more computing devices, the plurality of distinct geographic sub-entities to remove at least one distinct geographic sub-entity that is not at least one of (i) visually represented by at least one landmark and (ii) associated with a pre-stored navigation experience of the plurality of pre-stored navigation experiences that is unique to the at least one distinct geographic sub-entity, the at least one distinct geographic sub-entity including the second geographic sub-entity; determining, by the one or more computing devices, a ranking order of the filtered plurality of distinct geographic sub-entities based at least in part on one or more characteristics of each distinct geographic sub-entity in the filtered plurality of distinct geographic sub-entities; selecting, by one or more computing devices, a subset of at least two distinct geographic sub-entities based on the ranking order; and generating, by the one or more computing devices, a semantic image navigation experience for the first geographic entity based on at least the pre-stored navigation experiences associated with the subset of at least two distinct geographic sub-entities by: automatically selecting a plurality of images from each pre-stored navigation experience of the subset of at least two distinct geographic sub-entities, and including the plurality of selected images in the semantic image navigation experience as a sequence of images based on the ranking order. | 1. A method for generating semantic image navigation experiences, the method comprising: selecting, by one or more computing devices, a first geographic entity of a plurality of distinct geographic entities; identifying, by the one or more computing devices, a plurality of distinct geographic sub-entities, each distinct geographic sub-entity having a geographic containment relationship with the first geographic entity, the plurality of distinct geographic sub-entities including: a first distinct geographic sub-entity that is both (i) visually represented by at least one landmark corresponding to the first distinct geographic sub-entity and (ii) associated with a pre-stored navigation experience of a plurality of pre-stored navigation experiences that is unique to the first distinct geographic sub-entity, and a second distinct geographic sub-entity that is not at least one of (i) visually represented by at least one landmark corresponding to the second distinct geographic sub-entity and (ii) associated with a pre-stored navigation experience of the plurality of pre-stored navigation experiences that is unique to the second distinct geographic sub-entity, wherein each pre-stored navigation experience in the plurality of pre-stored navigation experiences corresponds to a given geographic entity and comprises a sequence of images and transitions between the images that produces a tour of at least one landmark associated with the given geographic entity; filtering, by the one or more computing devices, the plurality of distinct geographic sub-entities to remove at least one distinct geographic sub-entity that is not at least one of (i) visually represented by at least one landmark and (ii) associated with a pre-stored navigation experience of the plurality of pre-stored navigation experiences that is unique to the at least one distinct geographic sub-entity, the at least one distinct geographic sub-entity including the second geographic sub-entity; determining, by the one or more computing devices, a ranking order of the filtered plurality of distinct geographic sub-entities based at least in part on one or more characteristics of each distinct geographic sub-entity in the filtered plurality of distinct geographic sub-entities; selecting, by one or more computing devices, a subset of at least two distinct geographic sub-entities based on the ranking order; and generating, by the one or more computing devices, a semantic image navigation experience for the first geographic entity based on at least the pre-stored navigation experiences associated with the subset of at least two distinct geographic sub-entities by: automatically selecting a plurality of images from each pre-stored navigation experience of the subset of at least two distinct geographic sub-entities, and including the plurality of selected images in the semantic image navigation experience as a sequence of images based on the ranking order. 3. The method of claim 1 , wherein generating the semantic image navigation experience further comprises: selecting, by the one or more computing devices, a set of images from a pre-stored navigation experience for the first geographic entity; and inserting, by the one or more computing devices, the set of images from the pre-stored navigation experience for the first geographic entity at a beginning of the semantic image navigation experience for the first geographic entity. | 0.50104 |
6,061,648 | 2 | 3 | 2. An apparatus as claimed in claim 1, wherein said separating device calculates an autocorrelation parameter based on the input mixed speech signal, detects peaks of the calculated autocorrelation parameter, and generates each of the single speed signals associated with a corresponding one of the plurality of speakers which has a period based on the detected peaks. | 2. An apparatus as claimed in claim 1, wherein said separating device calculates an autocorrelation parameter based on the input mixed speech signal, detects peaks of the calculated autocorrelation parameter, and generates each of the single speed signals associated with a corresponding one of the plurality of speakers which has a period based on the detected peaks. 3. An apparatus as claimed in claim 2, wherein said separating device includes a plurality of sets of an autocorrelation operating block that calculates said autocorrelation parameter based on the input mixed speech signal, and a synthesizer that detects peaks of the calculates autocorrection parameter and generates one of the single speed signals associated with a corresponding one of the plurality of speakers which has a period based on the detected peaks, and wherein a difference between a single speech signal generated by a first set of said autocorrelation operating block and said synthesizer and the input mixed speech signal is sent as the the input mixed speech signal to a second set to generate a second single speech signal, followed by sequentially executing similar operations of generating single speech signals by respective subsequent sets. | 0.773728 |
9,176,951 | 13 | 14 | 13. A method executed by one or more processors for determining the conceptual model of an activity, wherein, specialized entities called conceptual entities are employed to depict conceptual structures, and effects of processing on real entities, and wherein, states of particular aspects of a subset of said conceptual entities called macro entities, could yield new states, owing to the conceptual execution of said activity, such that a sequence of activities called KBM workflow, is determined from an initial set of macro entities and the states of their aspects, called initial planning state, and a final set of macro entities and the states of their aspects called goal planning state, by a framework called KBM workflow planning, which comprises: a) Assigning a type to said conceptual entity, whereby said conceptual entity is classified as entity, process, or wrapper, and wherein the entity type is further sub classified as component, port, fluent, signal, channel, connector, event or concept; b) Storing Conceptual entities in memory by means of a predefined data structure called Conceptual object data structure, which assists in accessing and manipulating the contents of the conceptual entity; such that, said components could store other components, ports, fluents, characteristics, and functions; said ports store channels or connectors as components; said channel or connector stores source and target components as components, and source and target ports as ports; said conceptual entities of all types store their colors, characteristics, in a predefined object called KBMAdapter; c) Associating complete or partial paths of execution of said KBM rule graphs or any generic process structure with novel functions called conceptual Mu-Functions, which operate on said conceptual entities; such that, Said Mu-Functions, operate on conceptual entities and perform operations such as, create, morph, delete, bind, unbind, move, insert, remove, send, receive, increase, decrease, set, reset, compute, perform, start, stop, pause, publish, subscribe; d) Compiling a list of applicable Mu-functions, for a particular path of KBM activity based on contained KBM gears, and the contained KBM graphs within the said contained KBM gears, based on specifications in a table called process structure table; e) Executing the said Mu-functions compiled for an activity from the contained KBM Gears and KBM Rule graphs, with a pre-specified initial configuration of conceptual entities, which when executed yields a transformed configuration of the initial configuration, in terms of conceptual entities; f) Evaluating said configuration further by a set of predefined kbm rules, called aspect rules, of said macro entities, to yield new states of particular aspects of macro entities; g) Storing the state switching behavior of said activities with respect to said aspects of the said macro entities, in the form of a table, called Activity Switching table, wherein the said initial configuration is depicted by “Start Macro Entity Aspect vector” or start state, and the transformed configuration is depicted by “Target Macro Entity Aspect vector” or target state. | 13. A method executed by one or more processors for determining the conceptual model of an activity, wherein, specialized entities called conceptual entities are employed to depict conceptual structures, and effects of processing on real entities, and wherein, states of particular aspects of a subset of said conceptual entities called macro entities, could yield new states, owing to the conceptual execution of said activity, such that a sequence of activities called KBM workflow, is determined from an initial set of macro entities and the states of their aspects, called initial planning state, and a final set of macro entities and the states of their aspects called goal planning state, by a framework called KBM workflow planning, which comprises: a) Assigning a type to said conceptual entity, whereby said conceptual entity is classified as entity, process, or wrapper, and wherein the entity type is further sub classified as component, port, fluent, signal, channel, connector, event or concept; b) Storing Conceptual entities in memory by means of a predefined data structure called Conceptual object data structure, which assists in accessing and manipulating the contents of the conceptual entity; such that, said components could store other components, ports, fluents, characteristics, and functions; said ports store channels or connectors as components; said channel or connector stores source and target components as components, and source and target ports as ports; said conceptual entities of all types store their colors, characteristics, in a predefined object called KBMAdapter; c) Associating complete or partial paths of execution of said KBM rule graphs or any generic process structure with novel functions called conceptual Mu-Functions, which operate on said conceptual entities; such that, Said Mu-Functions, operate on conceptual entities and perform operations such as, create, morph, delete, bind, unbind, move, insert, remove, send, receive, increase, decrease, set, reset, compute, perform, start, stop, pause, publish, subscribe; d) Compiling a list of applicable Mu-functions, for a particular path of KBM activity based on contained KBM gears, and the contained KBM graphs within the said contained KBM gears, based on specifications in a table called process structure table; e) Executing the said Mu-functions compiled for an activity from the contained KBM Gears and KBM Rule graphs, with a pre-specified initial configuration of conceptual entities, which when executed yields a transformed configuration of the initial configuration, in terms of conceptual entities; f) Evaluating said configuration further by a set of predefined kbm rules, called aspect rules, of said macro entities, to yield new states of particular aspects of macro entities; g) Storing the state switching behavior of said activities with respect to said aspects of the said macro entities, in the form of a table, called Activity Switching table, wherein the said initial configuration is depicted by “Start Macro Entity Aspect vector” or start state, and the transformed configuration is depicted by “Target Macro Entity Aspect vector” or target state. 14. The method of claim 13 , further comprises of— a) Creating a node called “root” planning node and storing the said initial planning state in the root-planning node; Said root node is set as current planning node or state, to assist recursive processing; b) Searching the entries of said Activity Switching table, for the planning state, in the current planning node, such that all the states of aspects of macro entities of a starting planning state of an entry of the said Activity Switching table, are covered by the said current planning state; The activities of said entries, which matched, are stored in current planning node, along with the disposition and mode of processing colors; c) Creating planning nodes, for each of the target states depicted by the said entries of the Activity Switching table, which matched the current planning state, and adding these nodes as child nodes of the current planning node; d) Recursively processing the newly created planning nodes, as stated above, and expanding the planning node set as a graph called “Abstract Planning Graph”, until the goal planning state is reached; e) Storing the “Abstract Planning Graph” in a persistable storage; f) Pruning the branches or arcs of the said “Abstract Planning Graph”, if they do not lead towards to the goal state, by using bit values assigned to branches; Said pruning is accomplished by traversing the graph from the goal node, and assigning bit values to branches, which are in the path towards the root node; g) Creating a graph called “Concrete Planning Graph”, by traversing the said “Abstract Planning Graph” from the root, and by taking into consideration the pruned branches via the said bit values, and persisting the said Concrete planning graph to persistable storage; h) Compiling input requirements by taking into consideration, the input requirements of the activities of the said “Concrete Planning graph”, and any interdependencies that could exist owing to data base schemas; Said activities depict their input requirements, and a special gear called planning gear in their configuration documents; i) Capturing the inputs from the user, using said input requirements complied from the said “Concrete Planning graph” and asserting that the inputs satisfy the initial planning state; j) Traversing the said “Concrete Planning graph”, from the root, by executing the planning gears associated with said activities of planning nodes, with implicit backtracking; k) Preserving the bit values of only those branches, which correspond to the activity and the disposition color determined by the planning gear, and setting the rest of the bit values of the planning node to zero; l) Selecting activities in the path from root to final goal, of the said “Concrete Planning graph”, as possible workflows, wherein only those branches, which correspond to the activity and the disposition color determined by the planning gear, are regarded as viable. | 0.835102 |
8,612,229 | 1 | 4 | 1. A method for facilitating development of a natural language understanding (NLU) model associated with an NLU application executing on a computer system comprising a combination of hardware and software, the method comprising acts of: receiving, from a developer of the NLU application, at least one expected user entry and a corresponding desired routing destination; determining whether the NLU model associates the at least one expected user entry with the desired routing destination, the determining comprising: interpreting the at least one expected user entry via the NLU model to determine an actual routing destination for the at least one expected user entry, and comparing the actual routing destination to the desired routing destination; if it is determined that the actual routing destination of the at least one expected user entry matches the desired routing destination, selecting the at least one expected user entry for presentation to a user during a help prompt of the NLU application as an example of a legitimate utterance the user could speak to be routed to the desired routing destination; and if it is determined that the actual routing destination does not match the desired routing destination: (i) adding the at least one expected user entry to an NLU entry data set associated with the NLU model, and (ii) training the NLU model to associate the at least one expected user entry with the desired routing destination. | 1. A method for facilitating development of a natural language understanding (NLU) model associated with an NLU application executing on a computer system comprising a combination of hardware and software, the method comprising acts of: receiving, from a developer of the NLU application, at least one expected user entry and a corresponding desired routing destination; determining whether the NLU model associates the at least one expected user entry with the desired routing destination, the determining comprising: interpreting the at least one expected user entry via the NLU model to determine an actual routing destination for the at least one expected user entry, and comparing the actual routing destination to the desired routing destination; if it is determined that the actual routing destination of the at least one expected user entry matches the desired routing destination, selecting the at least one expected user entry for presentation to a user during a help prompt of the NLU application as an example of a legitimate utterance the user could speak to be routed to the desired routing destination; and if it is determined that the actual routing destination does not match the desired routing destination: (i) adding the at least one expected user entry to an NLU entry data set associated with the NLU model, and (ii) training the NLU model to associate the at least one expected user entry with the desired routing destination. 4. The method of claim 1 , further comprising: if it is determined that the actual routing destination does not match the desired routing destination, presenting a failure dialog to the developer of the NLU application indicating that the actual routing destination does not match to the desired routing destination. | 0.777465 |
8,718,239 | 5 | 6 | 5. A tangible computer-readable memory containing instructions that, when executed by a processor, cause the processor to execute a method for performing actions for users based on collections of information specified via spoken information, comprising: receiving a spoken voice message from a user during a telephone call; automatically analyzing the received voice message to identify a spoken indication of one of multiple predefined collections of information for the user that are each specific to a distinct associated topic, and to identify a spoken indication of each of one or more information items to be added to the indicated one predefined information collection; automatically adding generated textual representations of the identified one or more information items to a stored copy of the identified predefined information collection for the user, the stored copy further including one or more other generated textual representations of one or more other identified information items added based on one or more prior spoken voice messages from the user during one or more prior telephone calls; and after obtaining an indication from the user of one or more actions to take for the identified predefined information collection, wherein at least one of the actions includes providing determined information to the user that is based at least in part on the textual representations added to the identified predefined information collection, automatically performing the one or more actions so as to provide the determined information to the user; and obtaining information from one or more partner services related to the user acquiring from the one or more partner services at least one of the one or more products to which the identified one or more information items correspond, wherein the obtained information includes price bids by multiple partner services, and wherein the determined information that is provided to the user includes the obtained information. | 5. A tangible computer-readable memory containing instructions that, when executed by a processor, cause the processor to execute a method for performing actions for users based on collections of information specified via spoken information, comprising: receiving a spoken voice message from a user during a telephone call; automatically analyzing the received voice message to identify a spoken indication of one of multiple predefined collections of information for the user that are each specific to a distinct associated topic, and to identify a spoken indication of each of one or more information items to be added to the indicated one predefined information collection; automatically adding generated textual representations of the identified one or more information items to a stored copy of the identified predefined information collection for the user, the stored copy further including one or more other generated textual representations of one or more other identified information items added based on one or more prior spoken voice messages from the user during one or more prior telephone calls; and after obtaining an indication from the user of one or more actions to take for the identified predefined information collection, wherein at least one of the actions includes providing determined information to the user that is based at least in part on the textual representations added to the identified predefined information collection, automatically performing the one or more actions so as to provide the determined information to the user; and obtaining information from one or more partner services related to the user acquiring from the one or more partner services at least one of the one or more products to which the identified one or more information items correspond, wherein the obtained information includes price bids by multiple partner services, and wherein the determined information that is provided to the user includes the obtained information. 6. The computer-readable memory of claim 5 wherein the providing of the determined information to the user includes sending one or more electronic messages to the user that include at least one generated textual representation of an information item added to the identified predefined information collection. | 0.772189 |
7,945,389 | 4 | 6 | 4. A computer-readable medium encoded with a program for processing information on a nucleotide sequence which allows a computer to execute processes including: (a) receiving, via a communication network, request information of an object or service, wherein the object or service is provided for an individual based on one or more genetic differences between individuals, and wherein the request information does not include genetic information; (b) searching a first memory area for positional information, and wherein the positional information corresponds to information on classification of the object or service, and wherein the positional information represents a position in a nucleotide sequence, and retrieving the positional information, wherein the first memory area is permitted to be accessed by a first processor; (c) transmitting, via a communication network, the positional information retrieved in process (b) to a second processor which is permitted to access a second memory area storing polymorphism information regarding the individual; (d) receiving, via a communication network, polymorphism information based on the positional information transmitted in process (c); and (e) outputting, via a communication network, the polymorphism information received in process (d) to a user, and wherein the user includes a third processor which is permitted to access a third memory area storing semantic information, and which searches the third memory area to retrieve, in response to said transmission of the polymorphism information, semantic information based on the transmitted polymorphism information, and outputs the semantic information to a device that utilizes the semantic information or information corresponding to the semantic information, which is used for a provision of the object or service substantially included in the request information, wherein processes (a)-(e) are conducted under the control of the first processor. | 4. A computer-readable medium encoded with a program for processing information on a nucleotide sequence which allows a computer to execute processes including: (a) receiving, via a communication network, request information of an object or service, wherein the object or service is provided for an individual based on one or more genetic differences between individuals, and wherein the request information does not include genetic information; (b) searching a first memory area for positional information, and wherein the positional information corresponds to information on classification of the object or service, and wherein the positional information represents a position in a nucleotide sequence, and retrieving the positional information, wherein the first memory area is permitted to be accessed by a first processor; (c) transmitting, via a communication network, the positional information retrieved in process (b) to a second processor which is permitted to access a second memory area storing polymorphism information regarding the individual; (d) receiving, via a communication network, polymorphism information based on the positional information transmitted in process (c); and (e) outputting, via a communication network, the polymorphism information received in process (d) to a user, and wherein the user includes a third processor which is permitted to access a third memory area storing semantic information, and which searches the third memory area to retrieve, in response to said transmission of the polymorphism information, semantic information based on the transmitted polymorphism information, and outputs the semantic information to a device that utilizes the semantic information or information corresponding to the semantic information, which is used for a provision of the object or service substantially included in the request information, wherein processes (a)-(e) are conducted under the control of the first processor. 6. The computer-readable medium according to claim 4 , wherein in process (c), secondary positional information corresponding to the positional information retrieved in process (b) is set and the positional information retrieved in process (b) is transmitted along with the secondary positional information, and in process (d), the polymorphism information is received along with the secondary positional information. | 0.596712 |
9,336,299 | 14 | 15 | 14. A computing device comprising: at least one processing unit; and at least one memory storing instructions which, when executed by the at least one processing unit, cause the at least one processing unit to: identify seed probabilities that a seed phrase belongs to different semantic classes, the seed probabilities including at least: a first seed probability that the seed phrase belongs to a first semantic class, and a second seed probability that the seed phrase belongs to a second semantic class that is different than the first semantic class; identify, from a plurality of web documents, phrase lists that include the seed phrase as well as other phrases; and based at least on the seed probabilities, determine other probabilities that the other phrases included in the phrase lists belong to the different semantic classes, including at least first other probabilities that the other phrases belong to the first semantic class and second other probabilities that the other phrases belong to the second semantic class. | 14. A computing device comprising: at least one processing unit; and at least one memory storing instructions which, when executed by the at least one processing unit, cause the at least one processing unit to: identify seed probabilities that a seed phrase belongs to different semantic classes, the seed probabilities including at least: a first seed probability that the seed phrase belongs to a first semantic class, and a second seed probability that the seed phrase belongs to a second semantic class that is different than the first semantic class; identify, from a plurality of web documents, phrase lists that include the seed phrase as well as other phrases; and based at least on the seed probabilities, determine other probabilities that the other phrases included in the phrase lists belong to the different semantic classes, including at least first other probabilities that the other phrases belong to the first semantic class and second other probabilities that the other phrases belong to the second semantic class. 15. The computing device of claim 14 , wherein the instructions, when executed by the at least one processing unit, cause the at least one processing unit to: obtain training data having labeled instances of the seed phrase, including first instances where the seed phrase is labeled as belonging to the first semantic class and second instances where the seed phrase is labeled as belonging to the second semantic class; determine a first number of times the seed phrase is labeled in the training data as belonging to the first semantic class; determine a second number of times the seed phrase is labeled in the training data as belonging to the second semantic class; calculate the first seed probability based at least on the first number of times the seed phrase is labeled in the training data as belonging to the first semantic class; and calculate the second seed probability based at least on the second number of times the seed phrase is labeled in the training data as belonging to the second semantic class. | 0.50049 |
9,858,928 | 8 | 13 | 8. A system comprising: one or more computer processors; and one or more non-transitory computer readable devices that include instructions that, when executed by the one or more computer processors, causes the processors to perform operations, the operations comprising: transmitting, to a remote server, a verbal input; receiving, from the remote server, a digital message that comprises a symbolic representation of the verbal input; determining, based on the symbolic representation of the verbal input, an application identifier for an application that is indicated by the symbolic representation of the verbal input; launching, using the application identifier, the application that is indicated by the symbolic representation of the verbal input; transmitting, using the application and to an information provider, a query that was generated based on the symbolic representation of the verbal input; obtaining, from the information provider as a response to the query, an information result; and presenting, through an application interface, the information result. | 8. A system comprising: one or more computer processors; and one or more non-transitory computer readable devices that include instructions that, when executed by the one or more computer processors, causes the processors to perform operations, the operations comprising: transmitting, to a remote server, a verbal input; receiving, from the remote server, a digital message that comprises a symbolic representation of the verbal input; determining, based on the symbolic representation of the verbal input, an application identifier for an application that is indicated by the symbolic representation of the verbal input; launching, using the application identifier, the application that is indicated by the symbolic representation of the verbal input; transmitting, using the application and to an information provider, a query that was generated based on the symbolic representation of the verbal input; obtaining, from the information provider as a response to the query, an information result; and presenting, through an application interface, the information result. 13. The system of claim 8 , the operations further comprising: receiving a confirmation request; and transmitting a confirmation response to the remote server. | 0.67418 |
8,555,180 | 12 | 13 | 12. The portable media player of claim 11 , wherein the steps of the instructions for the UI presentation program further comprises: receiving an input originating from the portable media device; and in response to the input, updating the UI in a manner described by the UI document. | 12. The portable media player of claim 11 , wherein the steps of the instructions for the UI presentation program further comprises: receiving an input originating from the portable media device; and in response to the input, updating the UI in a manner described by the UI document. 13. The portable media player of claim 12 , wherein the steps of the instructions for the UI presentation program further comprises: in response to the input, modifying an operation of the peripheral device in a manner described by the UI document. | 0.858931 |
9,666,184 | 12 | 13 | 12. The apparatus of claim 8 , wherein the processor is configured to use the trained language model to convert a speech received from a microphone into output data. | 12. The apparatus of claim 8 , wherein the processor is configured to use the trained language model to convert a speech received from a microphone into output data. 13. The apparatus of claim 12 , wherein the apparatus is configured to use the output data as a user command in controlling applications on the apparatus. | 0.917735 |
8,924,216 | 8 | 9 | 8. At least one non-transitory computer-readable medium storing computer-executable instructions that, when executed, perform a method for synchronizing an audio medical dictation and a manual transcription of the audio medical dictation, the method comprising: establishing a repetition frequency at which to query playback of the audio medical dictation; while the audio medical dictation is being played back and manually transcribed, repeatedly obtaining, at the established repetition frequency, a current time position of a corresponding currently played sound datum in the audio medical dictation, and a currently transcribed text datum in the manual transcription at the current time position; generating a corrected time position for the currently transcribed text datum by applying to the current time position a time correction value in accordance with a transcription delay; and generating at least one association datum indicative of a synchronization association between the corrected time position and the currently transcribed text datum. | 8. At least one non-transitory computer-readable medium storing computer-executable instructions that, when executed, perform a method for synchronizing an audio medical dictation and a manual transcription of the audio medical dictation, the method comprising: establishing a repetition frequency at which to query playback of the audio medical dictation; while the audio medical dictation is being played back and manually transcribed, repeatedly obtaining, at the established repetition frequency, a current time position of a corresponding currently played sound datum in the audio medical dictation, and a currently transcribed text datum in the manual transcription at the current time position; generating a corrected time position for the currently transcribed text datum by applying to the current time position a time correction value in accordance with a transcription delay; and generating at least one association datum indicative of a synchronization association between the corrected time position and the currently transcribed text datum. 9. The at least one non-transitory computer-readable medium of claim 8 , wherein the method further comprises: in response to identifying a pause in the audio medical dictation that corresponds to punctuation in the manual transcription, generating an additional association datum. | 0.597421 |
9,256,795 | 15 | 17 | 15. A non-transitory computer-readable storage medium storing instructions that, when executed by at least one processor, cause a computing device to: receive an output from an optical character recognition (OCR) engine; analyze the output to isolate a character string indicative of a text entity; assign each character of the isolated character string to a character class to produce a character class string; and based at least in part on a pattern of the character class string, identify the isolated character string as being the text entity, wherein the isolated character string is identified as the text entity in response to determining a matching score above a threshold for the isolated character string, the matching score being based at least in part on a number of edits made to the character class string, and wherein determining the matching store comprises assigning costs to edits made to the character class string, wherein a cost associated with mistaking characters that are similar in appearance is small and the cost associated with mistaking characters that are relatively different in appearance is greater than a threshold value. | 15. A non-transitory computer-readable storage medium storing instructions that, when executed by at least one processor, cause a computing device to: receive an output from an optical character recognition (OCR) engine; analyze the output to isolate a character string indicative of a text entity; assign each character of the isolated character string to a character class to produce a character class string; and based at least in part on a pattern of the character class string, identify the isolated character string as being the text entity, wherein the isolated character string is identified as the text entity in response to determining a matching score above a threshold for the isolated character string, the matching score being based at least in part on a number of edits made to the character class string, and wherein determining the matching store comprises assigning costs to edits made to the character class string, wherein a cost associated with mistaking characters that are similar in appearance is small and the cost associated with mistaking characters that are relatively different in appearance is greater than a threshold value. 17. The non-transitory computer-readable storage medium of claim 15 , wherein the instructions that, when executed by the at least one processor, further cause the computing device to: autocorrecting a character in the character string to a character of a character class associated with the text entity in response to identifying the character belonging to a character class not associated with the text entity type. | 0.797573 |
10,127,287 | 17 | 19 | 17. A system comprising: a processor, and; a memory storing instructions that, when executed, cause the system to: retrieve a plurality of related content items that are related to a user in an online service; identify a plurality of topics of interest to the user using at least one of the plurality of related content items; rank the topics by relevance to one of a plurality of content items in a stream of content and based on a relationship between an author of the topics and the user; associate an identified topic to a content item in the stream of content where the identified topic is ranked as being relevant to the content item; generate a marker for the identified topic; generate a user interface including one or more tiles and the generated marker rendered with a tile of the one or more tiles, the one or more tiles being an element on the user interface, and each of the one or more tiles corresponding to the content item of the plurality of content items in the stream of content; detect a cursor movement towards the marker; in response to the cursor movement towards the marker, update the user interface by expanding the marker in size to reveal an overlay of the identified topic on the tile; receive a selection of the identified topic by the user; in response to the selection of the identified topic, replace the tile with at least one of the plurality of related content items on the identified topic such that the user views related information when viewing the stream of content without having to transition to a different element of the user interface; and provide the user interface for display. | 17. A system comprising: a processor, and; a memory storing instructions that, when executed, cause the system to: retrieve a plurality of related content items that are related to a user in an online service; identify a plurality of topics of interest to the user using at least one of the plurality of related content items; rank the topics by relevance to one of a plurality of content items in a stream of content and based on a relationship between an author of the topics and the user; associate an identified topic to a content item in the stream of content where the identified topic is ranked as being relevant to the content item; generate a marker for the identified topic; generate a user interface including one or more tiles and the generated marker rendered with a tile of the one or more tiles, the one or more tiles being an element on the user interface, and each of the one or more tiles corresponding to the content item of the plurality of content items in the stream of content; detect a cursor movement towards the marker; in response to the cursor movement towards the marker, update the user interface by expanding the marker in size to reveal an overlay of the identified topic on the tile; receive a selection of the identified topic by the user; in response to the selection of the identified topic, replace the tile with at least one of the plurality of related content items on the identified topic such that the user views related information when viewing the stream of content without having to transition to a different element of the user interface; and provide the user interface for display. 19. The system of claim 17 wherein the plurality of related content items are also related to a social graph of the user. | 0.868478 |
9,520,123 | 13 | 14 | 13. The system of claim 11 , further comprising: receiving a text input corresponding to an utterance during a massive synthesis phase associated with the concatenative speech synthesis. | 13. The system of claim 11 , further comprising: receiving a text input corresponding to an utterance during a massive synthesis phase associated with the concatenative speech synthesis. 14. The system of claim 13 , further comprising: determining a unit set based upon, at least in part, the utterance; and providing the unit set as feedback prior to the pruning. | 0.906151 |
7,603,647 | 14 | 17 | 14. The computer-readable storage medium of claim 13 , wherein determining whether an identified process is a clock process includes searching for an IF statement and a corresponding ELSE or ELSEIF statement. | 14. The computer-readable storage medium of claim 13 , wherein determining whether an identified process is a clock process includes searching for an IF statement and a corresponding ELSE or ELSEIF statement. 17. The computer-readable storage medium of claim 14 , further including: if ELSE or ELSEIF statements are not found, searching for a THEN statement associated with the IF statement; and searching for a clock statement between the IF statement and the THEN statement. | 0.838182 |
8,392,360 | 6 | 10 | 6. A computer-implemented method for providing an answer to a question left unanswered in a discussion forum, the computer-implemented method comprising: as implemented by one or more computing devices configured with specific executable instructions, identifying a question in a first discussion forum stored in a data store; determining that the first discussion forum does not include an answer to the question; determining a second discussion forum in which to present the question, wherein the second discussion forum is more likely than the first discussion forum to result in an answer to the question; presenting the question in the second discussion forum based at least in part on the determination that the first discussion forum does not include an answer to the question; receiving one or more responses to the question in the second discussion forum; determining whether one of the one or more responses comprises a good answer to the question; and when the determination is that the one of the one or more responses in the second discussion forum comprises a good answer, notifying a user that the question has received a good answer, wherein the user submitted the question in the first discussion forum. | 6. A computer-implemented method for providing an answer to a question left unanswered in a discussion forum, the computer-implemented method comprising: as implemented by one or more computing devices configured with specific executable instructions, identifying a question in a first discussion forum stored in a data store; determining that the first discussion forum does not include an answer to the question; determining a second discussion forum in which to present the question, wherein the second discussion forum is more likely than the first discussion forum to result in an answer to the question; presenting the question in the second discussion forum based at least in part on the determination that the first discussion forum does not include an answer to the question; receiving one or more responses to the question in the second discussion forum; determining whether one of the one or more responses comprises a good answer to the question; and when the determination is that the one of the one or more responses in the second discussion forum comprises a good answer, notifying a user that the question has received a good answer, wherein the user submitted the question in the first discussion forum. 10. The computer-implemented method of claim 6 , wherein the first discussion forum and the second discussion forum are each associated with at least one of an item, a category, a sub-category, a community, and a tag. | 0.836596 |
9,740,684 | 19 | 20 | 19. The program product of claim 16 , wherein the code that performs determining the plurality of logograms having the pronunciation that matches the pronunciation of the logogram further performs selecting the plurality of logograms from a data set in which logograms are grouped together in subsets based on pronunciation. | 19. The program product of claim 16 , wherein the code that performs determining the plurality of logograms having the pronunciation that matches the pronunciation of the logogram further performs selecting the plurality of logograms from a data set in which logograms are grouped together in subsets based on pronunciation. 20. The program product of claim 19 , wherein the code that performs selecting the plurality of logograms from the dataset further performs matching the logogram with a substantially equal logogram within one of the subsets and selecting all logograms within the one of the subsets as the plurality of logograms. | 0.797139 |
8,676,722 | 26 | 36 | 26. A computer implemented method for synthesizing media utilizing a semantic network, the method comprising: (a) generating, or facilitating the generation of, by one or more computer processors, a thought network including: an active concept translated from a text query received from a human user, selected data entities from an information domain, and relationships derived between the active concept and the selected data entities, the generating comprising: including the active concept as a node in the thought network, and populating the thought network at least in part with the selected data entities from the information domain and the derived relationships between the active concept and the selected data entities; and (b) transforming the thought network to generate and provide one or more forms of synthesized media to the human user. | 26. A computer implemented method for synthesizing media utilizing a semantic network, the method comprising: (a) generating, or facilitating the generation of, by one or more computer processors, a thought network including: an active concept translated from a text query received from a human user, selected data entities from an information domain, and relationships derived between the active concept and the selected data entities, the generating comprising: including the active concept as a node in the thought network, and populating the thought network at least in part with the selected data entities from the information domain and the derived relationships between the active concept and the selected data entities; and (b) transforming the thought network to generate and provide one or more forms of synthesized media to the human user. 36. The computer implemented method of claim 26 , further comprising providing a user interface for the consumer to input or select content elements. | 0.847336 |
10,162,729 | 12 | 13 | 12. A computing device for automatically reviewing structured query language (SQL) statements, the device comprising: a communication element configured to receive and transmit communications to and from a communication network; a memory element electronically coupled to the communication element, the memory element configured to store executable instructions; and a processing element electronically coupled to the communication element and the memory element, the processing element configured to— receive SQL code from a user seeking to access a database; parse the SQL code to retrieve SQL keywords, mathematical operators, and logical operators; identify the version of SQL that was used to create the SQL code; detect pre-SQL-92 code based on a lack of newer SQL statement syntax; set a temporary score if pre-SQL-92 code is detected; apply a complexity score calculation algorithm to the parsed SOL code to determine a presence of keywords and operators in the parsed SQL code; calculate a complexity score that varies according to a number of occurrences of keywords or operators and a variable complexity factor; execute the SQL code on a computing system which stores the database if the complexity score is less than or equal to a first threshold; flag the SQL code to be reviewed by a computer administrator if the complexity score is greater than the first threshold; compare the complexity score to a second threshold, greater than the first threshold; and return the SQL code to an original coder to rewrite at least a portion of the SQL code in a different programming language if the complexity score is greater than the second threshold. | 12. A computing device for automatically reviewing structured query language (SQL) statements, the device comprising: a communication element configured to receive and transmit communications to and from a communication network; a memory element electronically coupled to the communication element, the memory element configured to store executable instructions; and a processing element electronically coupled to the communication element and the memory element, the processing element configured to— receive SQL code from a user seeking to access a database; parse the SQL code to retrieve SQL keywords, mathematical operators, and logical operators; identify the version of SQL that was used to create the SQL code; detect pre-SQL-92 code based on a lack of newer SQL statement syntax; set a temporary score if pre-SQL-92 code is detected; apply a complexity score calculation algorithm to the parsed SOL code to determine a presence of keywords and operators in the parsed SQL code; calculate a complexity score that varies according to a number of occurrences of keywords or operators and a variable complexity factor; execute the SQL code on a computing system which stores the database if the complexity score is less than or equal to a first threshold; flag the SQL code to be reviewed by a computer administrator if the complexity score is greater than the first threshold; compare the complexity score to a second threshold, greater than the first threshold; and return the SQL code to an original coder to rewrite at least a portion of the SQL code in a different programming language if the complexity score is greater than the second threshold. 13. The computing device of claim 12 , wherein the complexity score calculation algorithm calculates a temporary score for the retrieved keywords, mathematical operators, and logical operators. | 0.502577 |
9,691,291 | 1 | 9 | 1. A system for generating student group assignments based on student attributes and student-variable-related criteria and conducting group learning over a network based on the student group assignments, the system comprising: one or more physical processors programmed with computer program instructions which, when executed, program the one or more physical processors to obtain student information about students registered to take a course, wherein, for each student, the student information comprises attributes of the student that correspond to variables of the student; obtain group criteria information associated with the course, wherein the group criteria information comprises first criteria indicating that the students are to be grouped in a manner that they achieve a target level of diversity with respect to a first variable and second criteria indicating that the students are to be grouped in a manner that they achieve a level of similarity with respect to a second variable; assign, based on the attributes, the first criteria, and the second criteria, a first set of the students to a first student group, wherein the first set of the students in the first student group, as a whole, are grouped together to be diverse with respect to the first variable based on the target level of diversity and are grouped together to be similar with respect to the second variable based on the target level of similarity; assign, based on the attributes, the first criteria, and the second criteria, a second set of the students to a second student group, wherein the second set of the students in the second student group, as a whole, are grouped together to be diverse with respect to the first variable based on the target level of diversity and are grouped together to be similar with respect to the second variable based on the target level of similarity; generate an instructor user interface display; provide, through the instructor user interface display, a first display option associated with the first student group, the first display option, when selected, specifies that a first message interface should be displayed on the instructor user interface display, wherein the first message interface display includes one or more first messages exchanged via a first communication channel accessible by the first student group; provide, through the instructor user interface display, a second display option associated with the second student group, the second display option, when selected, specifies that a second message interface should be displayed on the instructor user interface display instead of the first message interface, wherein the second message interface display includes one or more second messages exchanged via a second communication channel accessible by the second student group; receive a selection of the first display option, and cause the first message interface to be displayed on the instructor user interface display in response to the selection of the first display option; and receive a selection of the second display option, and cause the second message interface to be displayed on the instructor user interface display instead of the first message interface display in response to the selection of the second display option. | 1. A system for generating student group assignments based on student attributes and student-variable-related criteria and conducting group learning over a network based on the student group assignments, the system comprising: one or more physical processors programmed with computer program instructions which, when executed, program the one or more physical processors to obtain student information about students registered to take a course, wherein, for each student, the student information comprises attributes of the student that correspond to variables of the student; obtain group criteria information associated with the course, wherein the group criteria information comprises first criteria indicating that the students are to be grouped in a manner that they achieve a target level of diversity with respect to a first variable and second criteria indicating that the students are to be grouped in a manner that they achieve a level of similarity with respect to a second variable; assign, based on the attributes, the first criteria, and the second criteria, a first set of the students to a first student group, wherein the first set of the students in the first student group, as a whole, are grouped together to be diverse with respect to the first variable based on the target level of diversity and are grouped together to be similar with respect to the second variable based on the target level of similarity; assign, based on the attributes, the first criteria, and the second criteria, a second set of the students to a second student group, wherein the second set of the students in the second student group, as a whole, are grouped together to be diverse with respect to the first variable based on the target level of diversity and are grouped together to be similar with respect to the second variable based on the target level of similarity; generate an instructor user interface display; provide, through the instructor user interface display, a first display option associated with the first student group, the first display option, when selected, specifies that a first message interface should be displayed on the instructor user interface display, wherein the first message interface display includes one or more first messages exchanged via a first communication channel accessible by the first student group; provide, through the instructor user interface display, a second display option associated with the second student group, the second display option, when selected, specifies that a second message interface should be displayed on the instructor user interface display instead of the first message interface, wherein the second message interface display includes one or more second messages exchanged via a second communication channel accessible by the second student group; receive a selection of the first display option, and cause the first message interface to be displayed on the instructor user interface display in response to the selection of the first display option; and receive a selection of the second display option, and cause the second message interface to be displayed on the instructor user interface display instead of the first message interface display in response to the selection of the second display option. 9. The system of claim 1 , wherein to cause the first message interface to be displayed, the computer system is further programmed to: cause at least the second display option to continue to be displayed along with the first message interface on the instructor user interface display. | 0.865019 |
7,828,552 | 8 | 9 | 8. A non-transitory computer readable storage medium containing one or more program instructions for administering an assessment to a student, the programming instructions, when executed, causing a computer processor to execute steps comprising: for one or more tasks, calculating an expected weight of evidence for the task based on a student model pertaining to a particular student, wherein the student model comprises one or more variables, wherein each of the one ore more variables corresponds to a proficiency of the student and is based on student specific information collected prior to the assessment, wherein each of the one or more variables includes a probability of a plurality of probabilities, wherein each of the plurality of probabilities corresponds to a likelihood that the student has a particular proficiency level, wherein the expected weight of evidence is calculated based on the one or more variables corresponding to the proficiency for the particular student and the student specific information collected prior to the assessment; selecting one of the one or more tasks based on the calculated expected weights of evidence; administering the selected task to the student; collecting evidence regarding the selected task; updating the student model pertaining to the student based on the evidence; determining whether additional information is required to assess the student; if so, repeating the above steps; and if not, assigning a proficiency status to the student based on the student model. | 8. A non-transitory computer readable storage medium containing one or more program instructions for administering an assessment to a student, the programming instructions, when executed, causing a computer processor to execute steps comprising: for one or more tasks, calculating an expected weight of evidence for the task based on a student model pertaining to a particular student, wherein the student model comprises one or more variables, wherein each of the one ore more variables corresponds to a proficiency of the student and is based on student specific information collected prior to the assessment, wherein each of the one or more variables includes a probability of a plurality of probabilities, wherein each of the plurality of probabilities corresponds to a likelihood that the student has a particular proficiency level, wherein the expected weight of evidence is calculated based on the one or more variables corresponding to the proficiency for the particular student and the student specific information collected prior to the assessment; selecting one of the one or more tasks based on the calculated expected weights of evidence; administering the selected task to the student; collecting evidence regarding the selected task; updating the student model pertaining to the student based on the evidence; determining whether additional information is required to assess the student; if so, repeating the above steps; and if not, assigning a proficiency status to the student based on the student model. 9. The computer readable storage medium of claim 8 wherein the evidence comprises a scored response to the selected task. | 0.89 |
8,676,937 | 34 | 35 | 34. The machine-implemented process of claim 25 and further comprising: (d) transparently and automatically repeatedly monitoring current activities of a second user and attributes of the second user's current surroundings; (e) automatically generating current focus indicator signals (CFi's) that represent respective and temporally adjacent ones of said monitorings of the current activities of the second user and of the attributes of the second user's current surroundings; (f) automatically relaying the generated CFi's to the machine-implemented Social-Topical Adaptive Networking (STAN) system, wherein the Communal Cognitions-representing Spaces each include data representing points, nodes or subregions to which corresponding ones of the likely individual cognitions of the monitored second user can be correlated; wherein the points, nodes or subregions of the Context Space include ones representing different user-adoptable roles or user performable activities that are respectively adoptable and performable by the second user; (g) using the respective CFi's of the first and second users, automatically and respectively pointing to respective parts within at least one of the one or more Cognitive Attention Receiving Spaces that respectively correspond to the respective CFi's of the first and second users; and (h) based on sameness or closeness of the respective recently pointed-to parts within at least one of the one or more Cognitive Attention Receiving Spaces that are respectively pointed to on behalf of the first and second users, generating a desirability of joinder score indicating how desirable it is to automatically suggest to both of the first and second users that they join into a common online forum participation session and/or into a common real life (ReL) or virtual life event. | 34. The machine-implemented process of claim 25 and further comprising: (d) transparently and automatically repeatedly monitoring current activities of a second user and attributes of the second user's current surroundings; (e) automatically generating current focus indicator signals (CFi's) that represent respective and temporally adjacent ones of said monitorings of the current activities of the second user and of the attributes of the second user's current surroundings; (f) automatically relaying the generated CFi's to the machine-implemented Social-Topical Adaptive Networking (STAN) system, wherein the Communal Cognitions-representing Spaces each include data representing points, nodes or subregions to which corresponding ones of the likely individual cognitions of the monitored second user can be correlated; wherein the points, nodes or subregions of the Context Space include ones representing different user-adoptable roles or user performable activities that are respectively adoptable and performable by the second user; (g) using the respective CFi's of the first and second users, automatically and respectively pointing to respective parts within at least one of the one or more Cognitive Attention Receiving Spaces that respectively correspond to the respective CFi's of the first and second users; and (h) based on sameness or closeness of the respective recently pointed-to parts within at least one of the one or more Cognitive Attention Receiving Spaces that are respectively pointed to on behalf of the first and second users, generating a desirability of joinder score indicating how desirable it is to automatically suggest to both of the first and second users that they join into a common online forum participation session and/or into a common real life (ReL) or virtual life event. 35. The machine-implemented process of claim 34 wherein the common real life (ReL) event, if suggested, is at least one of: a group discount transactional event; a promotional offering event; a customized promotional offering event; an eating experience; a drinking experience; a business meeting; a sports event; a conference; a shared multi-media experience; and a resources using event in which physical resources of a shared physical location are to be used. | 0.962933 |
7,707,275 | 1 | 3 | 1. A method for validating a Command Line Interface(CLI)/configlet on an image, the method comprising: creating a parse graph using a plurality of self-describing data constructs, wherein each of the self-describing data constructs is a parser specific data structure; identifying a plurality of parse chain data constructs in the parse graph; deriving at least one CLI/configlet from the image file based on the plurality of self-describing data constructs; and comparing the at least one CLI/configlet derived from the image file with a plurality of CLIs/configlets, wherein the steps above are implemented by a processor. | 1. A method for validating a Command Line Interface(CLI)/configlet on an image, the method comprising: creating a parse graph using a plurality of self-describing data constructs, wherein each of the self-describing data constructs is a parser specific data structure; identifying a plurality of parse chain data constructs in the parse graph; deriving at least one CLI/configlet from the image file based on the plurality of self-describing data constructs; and comparing the at least one CLI/configlet derived from the image file with a plurality of CLIs/configlets, wherein the steps above are implemented by a processor. 3. The method according to claim 1 , wherein the plurality of self-describing data constructs created for the image file comprises a plurality of link points. | 0.769006 |
9,998,472 | 18 | 20 | 18. The computer-readable medium of claim 16 , further comprising: ranking the search result data based on a relevance of the entities and entity facts in relation to the query and member information of the member; and providing the search results, based on the search result data, in an order of the rankings to the member of the enterprise including data describing the entities and entity facts determined to be relevant to the query. | 18. The computer-readable medium of claim 16 , further comprising: ranking the search result data based on a relevance of the entities and entity facts in relation to the query and member information of the member; and providing the search results, based on the search result data, in an order of the rankings to the member of the enterprise including data describing the entities and entity facts determined to be relevant to the query. 20. The computer-readable medium of claim 18 , further comprises: receiving a selection from the search results provided to the member; and adjusting a quality score of the entities and entity facts based on the selection from the search results provided to the member. | 0.947089 |
7,779,388 | 1 | 3 | 1. A computing device configured with a processor for performing a method for implementing (Simple Object Access Protocol) SOAP-based Web services via a programming language in a computing system comprising: in connection with code that implements at least one SOAP-based Web service, identifying at least one (Simple Object Access Protocol) SOAP message attribute supported by an attribute provider, wherein the (Simple Object Access Protocol) SOAP message attribute is a (Simple Object Access Protocol) SOAP handling mechanism; declaring the syntax of the (Simple Object Access Protocol) SOAP handling mechanism corresponding to the at least one SOAP-based Web service via a construct of said programming language, when compiling said code, communicating with the attribute provider wherein the attribute provider queries a compiler for information about the (Simple Object Access Protocol) SOAP handling mechanism, wherein the information about the (Simple Object Access Protocol) SOAP handling mechanism includes a parameter name, a type, and an interface definition language (IDL) attribute; generating at least one of additional code and data from the information for use at run-time when at least one of sending and receiving a (Simple Object Access Protocol) SOAP message for said at least one SOAP-based Web service occurs. | 1. A computing device configured with a processor for performing a method for implementing (Simple Object Access Protocol) SOAP-based Web services via a programming language in a computing system comprising: in connection with code that implements at least one SOAP-based Web service, identifying at least one (Simple Object Access Protocol) SOAP message attribute supported by an attribute provider, wherein the (Simple Object Access Protocol) SOAP message attribute is a (Simple Object Access Protocol) SOAP handling mechanism; declaring the syntax of the (Simple Object Access Protocol) SOAP handling mechanism corresponding to the at least one SOAP-based Web service via a construct of said programming language, when compiling said code, communicating with the attribute provider wherein the attribute provider queries a compiler for information about the (Simple Object Access Protocol) SOAP handling mechanism, wherein the information about the (Simple Object Access Protocol) SOAP handling mechanism includes a parameter name, a type, and an interface definition language (IDL) attribute; generating at least one of additional code and data from the information for use at run-time when at least one of sending and receiving a (Simple Object Access Protocol) SOAP message for said at least one SOAP-based Web service occurs. 3. The computing device according to claim 1 , wherein said programming language is C++. | 0.947681 |
9,552,213 | 1 | 3 | 1. A method for facilitating software interface localization comprising: receiving a software module to be localized, the software module having a first graphical user interface comprising at least one control label displaying a plurality of first graphemes in a first language, wherein the plurality of first graphemes correspond to text comprising one or more words in the first language; providing at least one look up table having at least some of the first graphemes and a plurality of second graphemes in a second language associated therewith, said association being based on a phonetic similarly between the first and second graphemes when the first graphemes are vocalized in the first language and the second graphemes are vocalized in the second language; and generating a second graphical user interface of the software module based on the first graphical user interface, including searching the at least one look up table for at least one second grapheme corresponding to at least one of a plurality of portions of the first graphemes, determining a plurality at least a first matching grapheme and a second matching grapheme among the plurality of second graphemes, wherein the first matching grapheme corresponds to a first portion of the plurality of portions of first graphemes, wherein the second matching grapheme corresponds to a second portion of the plurality of portions of first graphemes, wherein the first portion has more text characters than the second portion, and replacing at least one of the first graphemes in the at least one control label of the first graphical user interface with the associated second graphemes such that the second graphical user interface displays the second graphemes in the second language, the second graphemes being understandable in the first language when the second graphemes are vocalized, wherein the replacing of the at least one of the first graphemes comprises determining the first portion has more text characters than the second portion, and replacing the first portion with the first matching grapheme before replacing the second portion with the second matching grapheme based at least in part on a number of text characters comprised in each of the first portion and the second portion. | 1. A method for facilitating software interface localization comprising: receiving a software module to be localized, the software module having a first graphical user interface comprising at least one control label displaying a plurality of first graphemes in a first language, wherein the plurality of first graphemes correspond to text comprising one or more words in the first language; providing at least one look up table having at least some of the first graphemes and a plurality of second graphemes in a second language associated therewith, said association being based on a phonetic similarly between the first and second graphemes when the first graphemes are vocalized in the first language and the second graphemes are vocalized in the second language; and generating a second graphical user interface of the software module based on the first graphical user interface, including searching the at least one look up table for at least one second grapheme corresponding to at least one of a plurality of portions of the first graphemes, determining a plurality at least a first matching grapheme and a second matching grapheme among the plurality of second graphemes, wherein the first matching grapheme corresponds to a first portion of the plurality of portions of first graphemes, wherein the second matching grapheme corresponds to a second portion of the plurality of portions of first graphemes, wherein the first portion has more text characters than the second portion, and replacing at least one of the first graphemes in the at least one control label of the first graphical user interface with the associated second graphemes such that the second graphical user interface displays the second graphemes in the second language, the second graphemes being understandable in the first language when the second graphemes are vocalized, wherein the replacing of the at least one of the first graphemes comprises determining the first portion has more text characters than the second portion, and replacing the first portion with the first matching grapheme before replacing the second portion with the second matching grapheme based at least in part on a number of text characters comprised in each of the first portion and the second portion. 3. The method of claim 1 , wherein the step of replacing the first graphemes is automated. | 0.914611 |
7,996,763 | 12 | 13 | 12. A computer readable storage medium having a computer program for assessing complexity levels of data representations, the program having instructions for performing: obtaining a first document having information associated with a first data representation being used to model a concept and a second document having information associated with a second data representation being used to model the same concept; prompting a user to provide individual element values for individual element objects contained in the data representation, individual attribute values for individual attribute objects contained in the data representation, and nesting values for nesting levels contained in the data representation; inputting the element values, the attribute values, and the nesting values received from the user in a table of values; analyzing structural components of the first document and the second document to assess a complexity score for the first data representation associated with the first document and a complexity score for the second data representation associated with the second document, wherein nesting levels of structural components in a respective document being analyzed and individual values assigned to different types of structural components in the respective document being analyzed are factored into computing the complexity score for the respective document, a customizable nesting value assigned to a nesting level being multiplied against all of the individual values of the structural components residing at the nesting level, the complexity score of the respective document being impacted by an attribute structural component of the respective document; and determining which of the first data representation of the first document and the second data representation of the second document has a smaller complexity score, wherein the structural components comprise element objects and attribute objects, the element objects comprising a first element object having a first individual element value and a second element object having a second individual element value that is different than the first individual element value, wherein, to determine the complexity score for the respective document, the customizable nesting value of a nesting level for each element object within a respective data representation is multiplied against an element value for the element object and the customizable nesting value of the nesting level for each attribute object within the respective data representation is multiplied against an attribute value for the attribute object to determine complexity levels of the structural components of the data representation, the complexity levels of the structural components being aggregated. | 12. A computer readable storage medium having a computer program for assessing complexity levels of data representations, the program having instructions for performing: obtaining a first document having information associated with a first data representation being used to model a concept and a second document having information associated with a second data representation being used to model the same concept; prompting a user to provide individual element values for individual element objects contained in the data representation, individual attribute values for individual attribute objects contained in the data representation, and nesting values for nesting levels contained in the data representation; inputting the element values, the attribute values, and the nesting values received from the user in a table of values; analyzing structural components of the first document and the second document to assess a complexity score for the first data representation associated with the first document and a complexity score for the second data representation associated with the second document, wherein nesting levels of structural components in a respective document being analyzed and individual values assigned to different types of structural components in the respective document being analyzed are factored into computing the complexity score for the respective document, a customizable nesting value assigned to a nesting level being multiplied against all of the individual values of the structural components residing at the nesting level, the complexity score of the respective document being impacted by an attribute structural component of the respective document; and determining which of the first data representation of the first document and the second data representation of the second document has a smaller complexity score, wherein the structural components comprise element objects and attribute objects, the element objects comprising a first element object having a first individual element value and a second element object having a second individual element value that is different than the first individual element value, wherein, to determine the complexity score for the respective document, the customizable nesting value of a nesting level for each element object within a respective data representation is multiplied against an element value for the element object and the customizable nesting value of the nesting level for each attribute object within the respective data representation is multiplied against an attribute value for the attribute object to determine complexity levels of the structural components of the data representation, the complexity levels of the structural components being aggregated. 13. The computer readable storage medium of claim 12 , wherein the information associated with the data representations of the first document and the second document comprises an extensible markup language data representation. | 0.583026 |
9,361,325 | 1 | 2 | 1. A method comprising: receiving, by a computing system comprising a computer processor, first data defining a scope and context of an information governance project, said computing system storing a meta-model profile associated with a meta-model, wherein said meta-model comprises an implementation mechanism, and wherein said implementation mechanism comprises a software tool that includes: a user interface configured to capture information requirements from stakeholders for customizing the meta-model profile by adding or removing concepts and relationships; a UML interpreter configured to instantiate or run a specification of said meta-model; a method interpreter configured to instantiate phases, activities, and tasks defined in a method to ensure that requirements are captured in a correct order following a format defined by said meta-model; a connector system configured to connect to and operate common technical systems used to manage databases; and a controller configured to mediate interactions between components; displaying, by said computer processor, high level subject areas comprising a scope/context for extending said the high level subject areas by adding or removing said concepts and relationships; importing, by said computer processor, existing logical information/data model formats used in existing enterprise systems; linking, by said computer processor, said existing logical information/data model formats to at least one concept of said concepts; integrating, by said computer processor, business and technical stakeholders across diverse models; mapping, by said computer processor, information management requirements with respect to an organization onto publicly available information models and technical systems; receiving, by said computer processor, information requirements data associated with said first data, said information requirements data conforming to semantics and syntax specified in said meta-model profile; classifying, by said computer processor, said information requirements data into concepts in accordance with said meta-model profile; generating, by said computer processor in accordance with a sequence for generating models, conceptual models from said concepts and in accordance with said meta-model profile, wherein said conceptual models define a structure and meaning of said first data, and wherein each concept model of said conceptual models comprises a subject area and a concept instance; generating, by said computer processor in accordance with said sequence, realization models from said concepts and in accordance with said meta-model profile, wherein said realization models are configured to deliver requirements using existing or planned technical software and hardware systems and associated interfaces, messages, and data storage structures, and wherein each realization model of said realization models comprises a role, a realization user interface, a realizing system interface, a canonical message model comprising message attributes, and a deployment system; associating, by said computer processor executing said realization user interface, realizing systems and associated interfaces with message standards and canonical message models of said data realization models; defining, by said computer processor, a stewardship model configured to govern said conceptual models and said realization models; assigning, by said computer processor, governance roles associated with said meta-model profile to informational assets within said conceptual models; generating, by said computer processor in accordance with said sequence, policy models in accordance with said governance roles, said informational assets, and said meta-model profile, wherein said policy models are configured to determine how specific instances of said conceptual models, said realization models, and said stewardship models are configured for specific customer needs; modifying, by said computer processor in response to user commands, elements of said policy models resulting in said modified policy models; and deploying, by said computer processor, a final architecture option associated with said modified policy models and said information assets. | 1. A method comprising: receiving, by a computing system comprising a computer processor, first data defining a scope and context of an information governance project, said computing system storing a meta-model profile associated with a meta-model, wherein said meta-model comprises an implementation mechanism, and wherein said implementation mechanism comprises a software tool that includes: a user interface configured to capture information requirements from stakeholders for customizing the meta-model profile by adding or removing concepts and relationships; a UML interpreter configured to instantiate or run a specification of said meta-model; a method interpreter configured to instantiate phases, activities, and tasks defined in a method to ensure that requirements are captured in a correct order following a format defined by said meta-model; a connector system configured to connect to and operate common technical systems used to manage databases; and a controller configured to mediate interactions between components; displaying, by said computer processor, high level subject areas comprising a scope/context for extending said the high level subject areas by adding or removing said concepts and relationships; importing, by said computer processor, existing logical information/data model formats used in existing enterprise systems; linking, by said computer processor, said existing logical information/data model formats to at least one concept of said concepts; integrating, by said computer processor, business and technical stakeholders across diverse models; mapping, by said computer processor, information management requirements with respect to an organization onto publicly available information models and technical systems; receiving, by said computer processor, information requirements data associated with said first data, said information requirements data conforming to semantics and syntax specified in said meta-model profile; classifying, by said computer processor, said information requirements data into concepts in accordance with said meta-model profile; generating, by said computer processor in accordance with a sequence for generating models, conceptual models from said concepts and in accordance with said meta-model profile, wherein said conceptual models define a structure and meaning of said first data, and wherein each concept model of said conceptual models comprises a subject area and a concept instance; generating, by said computer processor in accordance with said sequence, realization models from said concepts and in accordance with said meta-model profile, wherein said realization models are configured to deliver requirements using existing or planned technical software and hardware systems and associated interfaces, messages, and data storage structures, and wherein each realization model of said realization models comprises a role, a realization user interface, a realizing system interface, a canonical message model comprising message attributes, and a deployment system; associating, by said computer processor executing said realization user interface, realizing systems and associated interfaces with message standards and canonical message models of said data realization models; defining, by said computer processor, a stewardship model configured to govern said conceptual models and said realization models; assigning, by said computer processor, governance roles associated with said meta-model profile to informational assets within said conceptual models; generating, by said computer processor in accordance with said sequence, policy models in accordance with said governance roles, said informational assets, and said meta-model profile, wherein said policy models are configured to determine how specific instances of said conceptual models, said realization models, and said stewardship models are configured for specific customer needs; modifying, by said computer processor in response to user commands, elements of said policy models resulting in said modified policy models; and deploying, by said computer processor, a final architecture option associated with said modified policy models and said information assets. 2. The method of claim 1 , further comprising: synchronizing, by said computer processor, associated and related concepts of said concepts, wherein said conceptual models are generated from said associated concepts. | 0.862356 |
8,713,003 | 17 | 32 | 17. A method comprising: capturing a query for one or more documents, applications, sound or visual media; determining, with a processor, that a user has navigated at least one of the one or more documents, applications, sound or visual media for at least a defined period of time, the defined period of time being defined based on at least one of (a) a length of the at least one of the one or more documents, applications, sound or visual media, (b) a word count of the at least one of the one or more documents, or (c) a fragmentation of the at least one of the one or more documents, applications, sound or visual media; monitoring, in relation to the at least one of the one or more documents, applications, sound or visual media, and based on a determination that the user has navigated the at least one of the one or more documents, applications, sound or visual media for at least the defined period of time, one or more interaction events, the one or more interaction events comprising one or more user behaviors that demonstrate interest in the at least one of the one or more documents, applications, sound or visual media, each of the one or more interaction events having a respective weight that reflects a relative significance of the interaction event in relation to a relevance of the one or more documents, applications, sound or visual media to the query; and providing a relevance measure for the at least one of the one or more documents, applications, sound or visual media based on a respective weight associated with the one or more interaction events. | 17. A method comprising: capturing a query for one or more documents, applications, sound or visual media; determining, with a processor, that a user has navigated at least one of the one or more documents, applications, sound or visual media for at least a defined period of time, the defined period of time being defined based on at least one of (a) a length of the at least one of the one or more documents, applications, sound or visual media, (b) a word count of the at least one of the one or more documents, or (c) a fragmentation of the at least one of the one or more documents, applications, sound or visual media; monitoring, in relation to the at least one of the one or more documents, applications, sound or visual media, and based on a determination that the user has navigated the at least one of the one or more documents, applications, sound or visual media for at least the defined period of time, one or more interaction events, the one or more interaction events comprising one or more user behaviors that demonstrate interest in the at least one of the one or more documents, applications, sound or visual media, each of the one or more interaction events having a respective weight that reflects a relative significance of the interaction event in relation to a relevance of the one or more documents, applications, sound or visual media to the query; and providing a relevance measure for the at least one of the one or more documents, applications, sound or visual media based on a respective weight associated with the one or more interaction events. 32. The method of claim 17 , further comprising providing one or more search results based on the relevance measure of the at least one of the one or more documents, applications, sound or visual media. | 0.866225 |
9,075,779 | 1 | 2 | 1. A method, comprising: receiving, by one or more computing devices, an image of a portion of a document that was captured by a first user using a camera, wherein the image includes text; identifying, by the one or more computing devices, an electronic document that includes the text; determining, by the one or more computing devices, that there are a plurality of versions related to the identified electronic document, wherein the plurality of versions of the electronic document include a first version that corresponds to the document and a second version that differs from the first version; and providing, by the one or more computing devices and in response to the determination, data that present document information informing the first user of the plurality of versions of the electronic document together with information identifying, to the first user, a second user that is currently reading a most recent version of the document. | 1. A method, comprising: receiving, by one or more computing devices, an image of a portion of a document that was captured by a first user using a camera, wherein the image includes text; identifying, by the one or more computing devices, an electronic document that includes the text; determining, by the one or more computing devices, that there are a plurality of versions related to the identified electronic document, wherein the plurality of versions of the electronic document include a first version that corresponds to the document and a second version that differs from the first version; and providing, by the one or more computing devices and in response to the determination, data that present document information informing the first user of the plurality of versions of the electronic document together with information identifying, to the first user, a second user that is currently reading a most recent version of the document. 2. The method of claim 1 , wherein the second version of the electronic document is derived from the first version of the electronic document. | 0.862934 |
5,537,628 | 1 | 7 | 1. A method for handling text that uses a code page different than a native code page, comprising the steps of: (a) producing a piece table that includes an array of character positions, and an array of data records, said array of character positions being divided into a plurality of pieces, each data record corresponding to a piece of the array of character positions, each piece referencing adjacent characters of the text that have common format properties; (b) based upon data in the array of data records, identifying files in which the text referenced by the plurality of pieces is stored; (c) writing data blocks to each file, said data blocks recording a default code page for the text stored in each file; (d) if any text stored in a file uses a code page different than the default code page recorded for said file, writing exception data to the data block that identify an exception code page for said text; and (e) if the code page for any text to be displayed differs from the native code page, displaying said text by translating between the code page used by the text and the native code page, the code page for the text to be displayed remaining unchanged in the file in which said text is stored, so that any characters in the text that do not use the native code page are retained in said file. | 1. A method for handling text that uses a code page different than a native code page, comprising the steps of: (a) producing a piece table that includes an array of character positions, and an array of data records, said array of character positions being divided into a plurality of pieces, each data record corresponding to a piece of the array of character positions, each piece referencing adjacent characters of the text that have common format properties; (b) based upon data in the array of data records, identifying files in which the text referenced by the plurality of pieces is stored; (c) writing data blocks to each file, said data blocks recording a default code page for the text stored in each file; (d) if any text stored in a file uses a code page different than the default code page recorded for said file, writing exception data to the data block that identify an exception code page for said text; and (e) if the code page for any text to be displayed differs from the native code page, displaying said text by translating between the code page used by the text and the native code page, the code page for the text to be displayed remaining unchanged in the file in which said text is stored, so that any characters in the text that do not use the native code page are retained in said file. 7. The method of claim 1, wherein the step of translating includes the step of mapping characters in the text using a code page that is different than the native code page to a display buffer, said step of mapping comprising the step of applying a best possible match of characters using the native code page, to the characters using the code page that is different. | 0.918084 |
7,562,342 | 1 | 31 | 1. A method in a data processing system for incrementally processing program annotations, the method comprising: obtaining at least one changed source file: detecting at least one annotation in the at least one changed source file, wherein the at least one annotation is changed in the at least one changed source file; loading into a memory of the data processing system a previously serialized state from a state location: recording changes of the at least one annotation in a source model of the previously serialized state, wherein an annotation recorder reconciles the recorded changes to remove a change value having a same value as an original value, thereby leaving only added, deleted and actual changed objects to form recorded changes; and processing by the data processing system, only the recorded changes into a doclet model to form a set of incremental changes in the doclet model, wherein the set of incremental changes contains one or more changes. | 1. A method in a data processing system for incrementally processing program annotations, the method comprising: obtaining at least one changed source file: detecting at least one annotation in the at least one changed source file, wherein the at least one annotation is changed in the at least one changed source file; loading into a memory of the data processing system a previously serialized state from a state location: recording changes of the at least one annotation in a source model of the previously serialized state, wherein an annotation recorder reconciles the recorded changes to remove a change value having a same value as an original value, thereby leaving only added, deleted and actual changed objects to form recorded changes; and processing by the data processing system, only the recorded changes into a doclet model to form a set of incremental changes in the doclet model, wherein the set of incremental changes contains one or more changes. 31. The method of claim 1 , wherein the source model and the doclet model are implemented in a same meta-data model. | 0.945946 |
8,825,589 | 1 | 3 | 1. A method for visualizing rule input attributes with a rule according to disparate rule attribute distributions, the method comprising: identifying in response to a selection of a rule for viewing in a rule viewer executing in memory of a computer, an input for the selected rule; determining an attribute for the input; computing a global distribution of the attribute irrespective of the identified input and a specific distribution for the identified input; and, flagging the attribute as being correlated with the selected rule responsive to determining a sufficient disparity between the global distribution and the specific distribution. | 1. A method for visualizing rule input attributes with a rule according to disparate rule attribute distributions, the method comprising: identifying in response to a selection of a rule for viewing in a rule viewer executing in memory of a computer, an input for the selected rule; determining an attribute for the input; computing a global distribution of the attribute irrespective of the identified input and a specific distribution for the identified input; and, flagging the attribute as being correlated with the selected rule responsive to determining a sufficient disparity between the global distribution and the specific distribution. 3. The method of claim 1 , wherein a sufficient disparity exists when a probability of the specific distribution being derived from a random sampling of the global distribution is small below a threshold value. | 0.50237 |
7,890,505 | 1 | 8 | 1. A method for use in personalizing advertising for a user, the method comprising: accessing, using one or more processing devices, information indicating which documents in a set of documents were selected by a user for viewing and which documents in the set of documents were not selected by the user for viewing, wherein each of the documents in the set of documents is associated with a category; generating, using the one or more processing devices, at least one positive word vector using words contained in at least a segment of at least one of the documents that was selected by the user for viewing; generating, using the one or more processing devices, at least one negative word vector using words contained in at least a segment of at least one of the documents that was not selected by the user for viewing; generating, using the one or more processing devices, document word vectors for at least some of the documents that were selected by the user for viewing; performing, using the one or more processing devices, a vector space relationship analysis of the positive word vector, the negative word vector, and the document word vectors; establishing, using the one or more processing devices, a document rank order of the documents selected by the user for viewing based on the performed vector space relationship analysis; ranking, using the one or more processing devices, the categories associated with the documents in the set of documents based on the document rank order; and creating, using the one or more processing devices, an advertising profile for the user, the advertising profile comprising the ranked categories. | 1. A method for use in personalizing advertising for a user, the method comprising: accessing, using one or more processing devices, information indicating which documents in a set of documents were selected by a user for viewing and which documents in the set of documents were not selected by the user for viewing, wherein each of the documents in the set of documents is associated with a category; generating, using the one or more processing devices, at least one positive word vector using words contained in at least a segment of at least one of the documents that was selected by the user for viewing; generating, using the one or more processing devices, at least one negative word vector using words contained in at least a segment of at least one of the documents that was not selected by the user for viewing; generating, using the one or more processing devices, document word vectors for at least some of the documents that were selected by the user for viewing; performing, using the one or more processing devices, a vector space relationship analysis of the positive word vector, the negative word vector, and the document word vectors; establishing, using the one or more processing devices, a document rank order of the documents selected by the user for viewing based on the performed vector space relationship analysis; ranking, using the one or more processing devices, the categories associated with the documents in the set of documents based on the document rank order; and creating, using the one or more processing devices, an advertising profile for the user, the advertising profile comprising the ranked categories. 8. The method of claim 1 wherein the documents in the set of documents are available at a website. | 0.913274 |
9,477,755 | 5 | 6 | 5. A computer program product comprising: a non-transitory computer readable storage medium; and computer usable code stored on the non-transitory computer readable storage medium, where, if executed by a processor, the computer usable code causes a computer to: determine a user-question affinity value between a user and a question that is to indicate an extent of affinity between the user and the question; determine a user-community affinity value between the user and each of a plurality of candidate social communities that is to indicate an extent of affinity between the user and each of the plurality of candidate social communities, wherein at least one of the plurality of candidate social communities includes a pre-existing online social community having a candidate member that is to proactively establish a relationship with another candidate member and is to form a group of candidate members that are to interact with each other; and determine a question-community affinity value between the question and each of the plurality of candidate social communities based on the user-question affinity value and the user-community affinity value to identify one or more relevant social communities for the question, wherein the question-community affinity value is to indicate an extent of affinity between the question and each of the plurality of candidate social communities, and wherein the question is to be available to each member of the group of candidate members to respond to the question when it is determined that the pre-existing online social community is to be one of the one or more relevant social communities. | 5. A computer program product comprising: a non-transitory computer readable storage medium; and computer usable code stored on the non-transitory computer readable storage medium, where, if executed by a processor, the computer usable code causes a computer to: determine a user-question affinity value between a user and a question that is to indicate an extent of affinity between the user and the question; determine a user-community affinity value between the user and each of a plurality of candidate social communities that is to indicate an extent of affinity between the user and each of the plurality of candidate social communities, wherein at least one of the plurality of candidate social communities includes a pre-existing online social community having a candidate member that is to proactively establish a relationship with another candidate member and is to form a group of candidate members that are to interact with each other; and determine a question-community affinity value between the question and each of the plurality of candidate social communities based on the user-question affinity value and the user-community affinity value to identify one or more relevant social communities for the question, wherein the question-community affinity value is to indicate an extent of affinity between the question and each of the plurality of candidate social communities, and wherein the question is to be available to each member of the group of candidate members to respond to the question when it is determined that the pre-existing online social community is to be one of the one or more relevant social communities. 6. The computer program product of claim 5 , wherein the computer usable code, if executed, further causes a computer to one or more of: sort each of the plurality of candidate social communities based on the question-community affinity value to identify the one or more relevant social communities from the plurality of candidate social communities; and select one or more of the plurality of candidate social communities based on the question-community affinity value to identify the one or more relevant social communities from the plurality of candidate social communities. | 0.584892 |
8,095,487 | 8 | 13 | 8. A non-transitory computer readable medium comprising: a stopwords engine configured to conduct a stopwords analysis of stopwords in a document and to generate a stopwords score based on the stopwords analysis, the stopwords score including a binary value, wherein the stopwords engine is configured to conduct stopwords analysis of introductory level stopwords suggesting introductory content and advanced level stopwords suggesting advanced content; a reading level engine configured to conduct a reading level analysis of the document; a document features engine configured to conduct a feature analysis of the document; and a familiarity level classifier module configured to generate a document familiarity level based on the stopwords score, the reading level analysis, and the feature analysis, the familiarity level classifier module is further configured to implement a familiarity level classification function that incorporates weighting coefficients for each of the stopwords analysis, reading level analysis and the feature analysis. | 8. A non-transitory computer readable medium comprising: a stopwords engine configured to conduct a stopwords analysis of stopwords in a document and to generate a stopwords score based on the stopwords analysis, the stopwords score including a binary value, wherein the stopwords engine is configured to conduct stopwords analysis of introductory level stopwords suggesting introductory content and advanced level stopwords suggesting advanced content; a reading level engine configured to conduct a reading level analysis of the document; a document features engine configured to conduct a feature analysis of the document; and a familiarity level classifier module configured to generate a document familiarity level based on the stopwords score, the reading level analysis, and the feature analysis, the familiarity level classifier module is further configured to implement a familiarity level classification function that incorporates weighting coefficients for each of the stopwords analysis, reading level analysis and the feature analysis. 13. The classifier of claim 8 , wherein the stopwords engine is configured to generate a stopwords score based on the stopwords analysis, the stopwords score including a sliding scale value. | 0.652015 |
9,032,290 | 8 | 9 | 8. The method of claim 7 , wherein receiving a selection of object type configurations from the entity external to the social networking system utilizing the user interface for defining a new object type further comprises: receiving a selection of a different object type as a property of the new object type; and storing the different object type as an object type configuration for the new object type. | 8. The method of claim 7 , wherein receiving a selection of object type configurations from the entity external to the social networking system utilizing the user interface for defining a new object type further comprises: receiving a selection of a different object type as a property of the new object type; and storing the different object type as an object type configuration for the new object type. 9. The method of claim 8 , further comprising: associating the different object type with the new action type. | 0.964562 |
9,111,092 | 6 | 10 | 6. A processor-implemented method to execute on one or more processors that perform the method, comprising: receiving an indication that a context associated with a source of an event is malicious, wherein the context includes information about an environment surrounding an interaction between a corresponding event and one or more functions provided by an application at a point-in-time, and wherein the event is an action capable of being monitored and recorded within a computer; generating a context taint to identify the context as a tainted context that is malicious when the context has not been previously known to be malicious; transforming the event from an unmarked event to a tainted event by marking the unmarked event with the context taint; marking a prior unmarked context associated with the tainted event with the taint to create a prior tainted context, so as to propagate the taint from the tainted context to the prior tainted context, propagation of the taint being time-limited; marking any subsequent context linked to the prior tainted context by the tainted event or other events, as subsequent tainted contexts, so as to propagate the taint from the tainted context, to the prior tainted context, and then to the subsequent tainted contexts, propagation of the taint being time-limited; marking any other unmarked event emanating from the tainted context, the prior tainted context, or the subsequent tainted contexts as other tainted events with the taint; and publishing an event horizon to a display, the event horizon including the tainted event and all of the other tainted events. | 6. A processor-implemented method to execute on one or more processors that perform the method, comprising: receiving an indication that a context associated with a source of an event is malicious, wherein the context includes information about an environment surrounding an interaction between a corresponding event and one or more functions provided by an application at a point-in-time, and wherein the event is an action capable of being monitored and recorded within a computer; generating a context taint to identify the context as a tainted context that is malicious when the context has not been previously known to be malicious; transforming the event from an unmarked event to a tainted event by marking the unmarked event with the context taint; marking a prior unmarked context associated with the tainted event with the taint to create a prior tainted context, so as to propagate the taint from the tainted context to the prior tainted context, propagation of the taint being time-limited; marking any subsequent context linked to the prior tainted context by the tainted event or other events, as subsequent tainted contexts, so as to propagate the taint from the tainted context, to the prior tainted context, and then to the subsequent tainted contexts, propagation of the taint being time-limited; marking any other unmarked event emanating from the tainted context, the prior tainted context, or the subsequent tainted contexts as other tainted events with the taint; and publishing an event horizon to a display, the event horizon including the tainted event and all of the other tainted events. 10. The method of claim 6 , further comprising: creating the taint to include a universally unique identifier (UUID) value. | 0.791525 |
8,892,589 | 8 | 10 | 8. A non-transitory computer storage medium encoded with a computer program, the program comprising instructions that when executed by one or more data processing apparatus cause the one or more data processing apparatus to perform operations comprising: determining that at least two or more previous search queries, previously received from a particular user device, are search queries for a same topic; determining that the particular user device requested presentation of fewer than a specified number of web pages referenced by search results provided to the particular user device in response to the previous search queries; identifying, in response to determining that both the two or more previous search queries are related to the same topic and that fewer than the specified number of web pages referenced by the search results were requested, a related query for the same topic as the two or more previous search queries, the related query being different than each of the previous search queries; receiving a current search query from the particular user device, the current search query being received subsequent to the two or more previous search queries; and providing, for presentation on a search results page for the current query, the identified related query to the particular user device. | 8. A non-transitory computer storage medium encoded with a computer program, the program comprising instructions that when executed by one or more data processing apparatus cause the one or more data processing apparatus to perform operations comprising: determining that at least two or more previous search queries, previously received from a particular user device, are search queries for a same topic; determining that the particular user device requested presentation of fewer than a specified number of web pages referenced by search results provided to the particular user device in response to the previous search queries; identifying, in response to determining that both the two or more previous search queries are related to the same topic and that fewer than the specified number of web pages referenced by the search results were requested, a related query for the same topic as the two or more previous search queries, the related query being different than each of the previous search queries; receiving a current search query from the particular user device, the current search query being received subsequent to the two or more previous search queries; and providing, for presentation on a search results page for the current query, the identified related query to the particular user device. 10. The computer storage medium of claim 8 , wherein the instructions further cause the one or more data processing apparatus to perform operations comprising: identifying, from a data store, a plurality of previous search queries that were received from the particular user device; identifying, from among the previous search queries, a first search query that is related to a first topic; determining that a second search query, from among the previous search queries, was received after the first search query and is related to a second topic that differs from the first topic; and defining, as a beginning of a search session for the second search query, a time after receipt of the first search query and up to a time at which the second search query was received. | 0.55906 |
6,064,982 | 5 | 7 | 5. A smart configurator for needs assessment and product configuration, comprising: a configuration tool in the form of a series of cascading style sheets, said configuration tool comprising: a module that assists a user in determining hardware needs; a customer needs identification page for assessing a customer's product requirements, in which a customer may select among various statements; a system needs determination page in which hardware requirements are identified; and a recommended system configuration page that provides a recommended system configuration that includes any of product identification, pricing information, various options that have been selected, and sales terms and conditions that may be desired; a browser for progressing through said style sheets during an interactive, off-line customer needs assessment and product configuration session; and means for automatically recommending a system configuration that most nearly meets a customer's needs, based upon the results of said interactive customer product selection session. | 5. A smart configurator for needs assessment and product configuration, comprising: a configuration tool in the form of a series of cascading style sheets, said configuration tool comprising: a module that assists a user in determining hardware needs; a customer needs identification page for assessing a customer's product requirements, in which a customer may select among various statements; a system needs determination page in which hardware requirements are identified; and a recommended system configuration page that provides a recommended system configuration that includes any of product identification, pricing information, various options that have been selected, and sales terms and conditions that may be desired; a browser for progressing through said style sheets during an interactive, off-line customer needs assessment and product configuration session; and means for automatically recommending a system configuration that most nearly meets a customer's needs, based upon the results of said interactive customer product selection session. 7. The smart configurator of claim 5, wherein said configuration tool is connected to a network. | 0.859238 |
8,832,057 | 11 | 12 | 11. A computer-implemented method comprising: selecting, from a search corpus, a set of documents that are relevant to a specified topic; wherein the set of documents includes at least a first document and a second document; for each particular document within at least a subset of the set of documents, extracting one or more lists contained within that particular document and adding the one or more lists into a set of lists; wherein extracting one or more lists includes, extracting a first list from the first document and extracting a second list from the second document; for each particular list in the set of lists, and for each particular item within that particular list, generating an item score for that particular item based at least in part on a number of occurrences of that particular item within other lists in the set of lists; selecting a subset of list items from among all list items in lists in the set of lists based at least in part on the item scores generated for those list items; wherein selecting the subset of list items includes selecting a first subset of items from the first list and selecting a second subset of items from the second list; ranking the selected list items in the subset of list items based at least in part on the item scores generated for the selected list items, thereby generating a ranked master list for the specified topic; and storing the ranked master list in association with the specified topic; wherein the method is performed by one or more computing devices. | 11. A computer-implemented method comprising: selecting, from a search corpus, a set of documents that are relevant to a specified topic; wherein the set of documents includes at least a first document and a second document; for each particular document within at least a subset of the set of documents, extracting one or more lists contained within that particular document and adding the one or more lists into a set of lists; wherein extracting one or more lists includes, extracting a first list from the first document and extracting a second list from the second document; for each particular list in the set of lists, and for each particular item within that particular list, generating an item score for that particular item based at least in part on a number of occurrences of that particular item within other lists in the set of lists; selecting a subset of list items from among all list items in lists in the set of lists based at least in part on the item scores generated for those list items; wherein selecting the subset of list items includes selecting a first subset of items from the first list and selecting a second subset of items from the second list; ranking the selected list items in the subset of list items based at least in part on the item scores generated for the selected list items, thereby generating a ranked master list for the specified topic; and storing the ranked master list in association with the specified topic; wherein the method is performed by one or more computing devices. 12. The method of claim 11 , wherein the step of selecting the set of documents that are relevant to the specified topic comprises: locating, within the search corpus, documents that contain words that are associated with the specified topic. | 0.864045 |
7,957,974 | 5 | 6 | 5. The method of claim 1 , further comprising: (f) monitoring the states of the home electronic devices, wherein a state of a home electronic device changes according to the control of the home electronic device connected to the home network. | 5. The method of claim 1 , further comprising: (f) monitoring the states of the home electronic devices, wherein a state of a home electronic device changes according to the control of the home electronic device connected to the home network. 6. The method of claim 5 , wherein the step (f) comprises: receiving changed home electronic device state information from the home electronic devices connected to the home network; and updating a device state library which stores the state information of the home electronic devices connected to the home network based on the received home electronic device state information. | 0.886377 |
8,269,773 | 1 | 14 | 1. A computer-implemented method for creating a graph, comprising: providing, using one or more data processors, a variable selection region including a variable for display; providing, using the one or more data processors, a graph creation region that includes a plurality of graph components for display, wherein at least one graph component is an axis; defining, using the one or more data processors, one or more hotspots on the graph creation region, wherein a hotspot covers a portion of the graph creation region; associating, using the one or more data processors, a hotspot with a graph component, wherein the hotspot is used to generate an association between the graph component and a variable; generating, using the one or more data processors, an association between a variable and the graph component when a particular variable from the variable selection region is dragged onto the hotspot associated with the graph component; updating, using the one or more data processors, the graph creation region using the association, wherein the updated graph creation region displays a preview of the association between the particular variable and the graph component; confirming, using the one or more data processors, the association between the particular variable and the graph component displayed in the preview, wherein the association is confirmed when the particular variable is dropped onto the hotspot associated with the graph component; and using, using the one or more data processors, the confirmed association to redefine the one or more hotspots to include additional available hotspots on the graph creation region. | 1. A computer-implemented method for creating a graph, comprising: providing, using one or more data processors, a variable selection region including a variable for display; providing, using the one or more data processors, a graph creation region that includes a plurality of graph components for display, wherein at least one graph component is an axis; defining, using the one or more data processors, one or more hotspots on the graph creation region, wherein a hotspot covers a portion of the graph creation region; associating, using the one or more data processors, a hotspot with a graph component, wherein the hotspot is used to generate an association between the graph component and a variable; generating, using the one or more data processors, an association between a variable and the graph component when a particular variable from the variable selection region is dragged onto the hotspot associated with the graph component; updating, using the one or more data processors, the graph creation region using the association, wherein the updated graph creation region displays a preview of the association between the particular variable and the graph component; confirming, using the one or more data processors, the association between the particular variable and the graph component displayed in the preview, wherein the association is confirmed when the particular variable is dropped onto the hotspot associated with the graph component; and using, using the one or more data processors, the confirmed association to redefine the one or more hotspots to include additional available hotspots on the graph creation region. 14. The method of claim 1 , wherein generating the association uses an association data structure. | 0.810811 |
8,452,763 | 10 | 12 | 10. A computer-implemented method, comprising: receiving extraction patterns from a repository of extraction patterns; applying the extraction patterns to document text of one or more documents to derive a plurality of candidate class-instance pairs in the document text, wherein each candidate class-instance pair comprises a candidate class name and a candidate instance name derived by matching at least one of the extraction patterns to document text including the candidate class name and the candidate instance name; determining a frequency score and a diversity score for each candidate class-instance pair, wherein the frequency score relates to a frequency with which the class-instance pair was derived and the diversity score relates to a number of distinct extraction patterns that matched document text including the candidate class name and the candidate instance name of the candidate class-instance pair; and determining a pair score for each candidate class-instance pair in the plurality of candidate class-instance pairs from the frequency score and the diversity score, wherein determining the pair score comprises multiplying the frequency score by the diversity score. | 10. A computer-implemented method, comprising: receiving extraction patterns from a repository of extraction patterns; applying the extraction patterns to document text of one or more documents to derive a plurality of candidate class-instance pairs in the document text, wherein each candidate class-instance pair comprises a candidate class name and a candidate instance name derived by matching at least one of the extraction patterns to document text including the candidate class name and the candidate instance name; determining a frequency score and a diversity score for each candidate class-instance pair, wherein the frequency score relates to a frequency with which the class-instance pair was derived and the diversity score relates to a number of distinct extraction patterns that matched document text including the candidate class name and the candidate instance name of the candidate class-instance pair; and determining a pair score for each candidate class-instance pair in the plurality of candidate class-instance pairs from the frequency score and the diversity score, wherein determining the pair score comprises multiplying the frequency score by the diversity score. 12. The method of claim 10 , further comprising: determining, for each candidate class-instance pair, a number of distinct phrases from which the candidate class-instance pair was derived; wherein the frequency score for a candidate class-instance pair is derived from the number of distinct phrases from which the candidate class-instance pair was derived. | 0.755814 |
9,588,964 | 1 | 2 | 1. A method implemented at least partially in hardware of a computing device, the method comprising: mining, by the computing device, one or more search results returned from a search engine for a particular one of a plurality of domains to determine a frequency at which words occur in the one or more search results relating to the particular domain, respectively; selecting, by the computing device, a set of the words from the search results of the particular domain based on the determined frequency; assigning, by the computing device, a sense to each of the selected set of the words that identifies a part-of-speech for a respective said word, the sense based in part on the particular domain; and generating, by the computing device, a vocabulary for the particular domain that includes the selected set of the words and a respective said sense, the vocabulary describing a term sense bias as applied to a term semantic distance, the vocabulary configured for use in natural language processing to disambiguate natural language input according to the term sense bias applied to the term semantic distance of the particular domain. | 1. A method implemented at least partially in hardware of a computing device, the method comprising: mining, by the computing device, one or more search results returned from a search engine for a particular one of a plurality of domains to determine a frequency at which words occur in the one or more search results relating to the particular domain, respectively; selecting, by the computing device, a set of the words from the search results of the particular domain based on the determined frequency; assigning, by the computing device, a sense to each of the selected set of the words that identifies a part-of-speech for a respective said word, the sense based in part on the particular domain; and generating, by the computing device, a vocabulary for the particular domain that includes the selected set of the words and a respective said sense, the vocabulary describing a term sense bias as applied to a term semantic distance, the vocabulary configured for use in natural language processing to disambiguate natural language input according to the term sense bias applied to the term semantic distance of the particular domain. 2. A method as described in claim 1 , wherein the one or more search results are generated such that the particular domain is used as part of a search query that is used to generate the one or more search results. | 0.714477 |
8,930,820 | 1 | 6 | 1. A method for maintaining a calendar of a user, comprising: accessing an online profile of the user at a first social networking website; identifying, on the online profile, a first post referencing a physical location, wherein the first post is created on the first social networking website by a client application of the user on a first calendar date, and wherein the first post comprises a timestamp of the first calendar date; identifying, on the online profile, a second post referencing the physical location, wherein the second post is created on the first social networking website by the client application of the user on a second calendar date, and wherein the second post comprises a timestamp of the second calendar date; calculating, by a computer processor and based on the timestamp of first calendar date and the timestamp of second calendar date, a first time period between user visits to the physical location; estimating, based on the first time period between user visits, a future calendar date when the user is expected to visit the physical location; creating, in the calendar, an event scheduled to occur at the physical location and on the future calendar date; determining, after the future calendar date and based on the first social networking website and a second social networking website, that the user did not visit the physical location on the future calendar date; identifying, on the first social networking website, a third post referencing the physical location, wherein the third post is entered by the user on a third calendar date, wherein the third post comprises a timestamp of the third calendar date, and wherein the third calendar date is after the future calendar date; calculating a modified first time period between user visits based on the third calendar date; estimating, based on the modified first time period between user visits, a new future calendar date when the user is expected to visit the physical location; and creating, in the calendar, a new event corresponding to the new future calendar date. | 1. A method for maintaining a calendar of a user, comprising: accessing an online profile of the user at a first social networking website; identifying, on the online profile, a first post referencing a physical location, wherein the first post is created on the first social networking website by a client application of the user on a first calendar date, and wherein the first post comprises a timestamp of the first calendar date; identifying, on the online profile, a second post referencing the physical location, wherein the second post is created on the first social networking website by the client application of the user on a second calendar date, and wherein the second post comprises a timestamp of the second calendar date; calculating, by a computer processor and based on the timestamp of first calendar date and the timestamp of second calendar date, a first time period between user visits to the physical location; estimating, based on the first time period between user visits, a future calendar date when the user is expected to visit the physical location; creating, in the calendar, an event scheduled to occur at the physical location and on the future calendar date; determining, after the future calendar date and based on the first social networking website and a second social networking website, that the user did not visit the physical location on the future calendar date; identifying, on the first social networking website, a third post referencing the physical location, wherein the third post is entered by the user on a third calendar date, wherein the third post comprises a timestamp of the third calendar date, and wherein the third calendar date is after the future calendar date; calculating a modified first time period between user visits based on the third calendar date; estimating, based on the modified first time period between user visits, a new future calendar date when the user is expected to visit the physical location; and creating, in the calendar, a new event corresponding to the new future calendar date. 6. The method of claim 1 , further comprising: identifying, within a financial management application of the user, a plurality of financial transactions between the user and a merchant; calculating, based on the plurality of financial transactions, a frequency of transactions between the user and the merchant; estimating, based on the frequency, an execution date of a future financial transaction between the user and the merchant; and creating, in the calendar, a notification of the future financial transaction corresponding to the execution date. | 0.637139 |
8,914,359 | 15 | 16 | 15. One of an optical disk, a solid state storage device or a magnetic storage device having computer-executable instructions stored thereon which, and executed by a computer, cause the computer to: crawl documents to obtain document ranking features; crawl a profile database to collect social tags associated with a document, the profile database comprising a plurality of user profiles associated with a plurality of users, each user profile comprising the social tags associated with the document by at least one of the plurality of users, the social tags comprising a text string containing one or more terms at least one of describing, categorizing and providing information regarding the document, and being indexed and stored in user profile tables separately from the document they are associated with; determine, based on the social tags, a number ranking feature containing a number of times the document was tagged with the social tags by the plurality of users; determine, based on the social tags, a textual property ranking textual stream containing a union of all the social tags associated with the document by the plurality of users; transform the number ranking feature into a static input value by applying a normalization constant to the number ranking feature, the static input value being query independent; transform the textual property ranking textual stream into a dynamic query dependent input value that is query dependent and includes a number of times a given term in a query appears in the textual property ranking textual stream; and determine a document rank for the document by inputting the static input value and the dynamic query dependent input value into a ranking function, and further inputting the document ranking features into the ranking function. | 15. One of an optical disk, a solid state storage device or a magnetic storage device having computer-executable instructions stored thereon which, and executed by a computer, cause the computer to: crawl documents to obtain document ranking features; crawl a profile database to collect social tags associated with a document, the profile database comprising a plurality of user profiles associated with a plurality of users, each user profile comprising the social tags associated with the document by at least one of the plurality of users, the social tags comprising a text string containing one or more terms at least one of describing, categorizing and providing information regarding the document, and being indexed and stored in user profile tables separately from the document they are associated with; determine, based on the social tags, a number ranking feature containing a number of times the document was tagged with the social tags by the plurality of users; determine, based on the social tags, a textual property ranking textual stream containing a union of all the social tags associated with the document by the plurality of users; transform the number ranking feature into a static input value by applying a normalization constant to the number ranking feature, the static input value being query independent; transform the textual property ranking textual stream into a dynamic query dependent input value that is query dependent and includes a number of times a given term in a query appears in the textual property ranking textual stream; and determine a document rank for the document by inputting the static input value and the dynamic query dependent input value into a ranking function, and further inputting the document ranking features into the ranking function. 16. The optical disk, the solid state storage device or the magnetic storage device of claim 15 , wherein the document is privately accessible only by a subset of the plurality of users. | 0.835979 |
9,208,134 | 11 | 12 | 11. A computer program product comprising a non-transitory tangible computer usable storage medium having readable program code embodied in the non-transitory tangible computer usable storage medium, the computer program product includes at least one component operable to: determine an attribute of a current character in input text, the attribute of the current character indicating one or more classes of characters the current character is assigned thereto; determine one or more attributes of one or more next characters in the input text, the one or more attributes of the one or more next characters indicating the one or more classes the one or more next characters are assigned thereto; and construct a token of the input text that comprises the current character and the one or more next characters, the attribute of the current character and the one or more attributes of the one or more next characters intersecting with each other, and the attribute of the current character and the one or more attributes of the one or more next characters comprising an attribute data structure which comprises a one-byte array, wherein the one-byte array comprises a plurality of binary bits and each bit of the binary bits indicates a different class from remaining bits of the binary bits. | 11. A computer program product comprising a non-transitory tangible computer usable storage medium having readable program code embodied in the non-transitory tangible computer usable storage medium, the computer program product includes at least one component operable to: determine an attribute of a current character in input text, the attribute of the current character indicating one or more classes of characters the current character is assigned thereto; determine one or more attributes of one or more next characters in the input text, the one or more attributes of the one or more next characters indicating the one or more classes the one or more next characters are assigned thereto; and construct a token of the input text that comprises the current character and the one or more next characters, the attribute of the current character and the one or more attributes of the one or more next characters intersecting with each other, and the attribute of the current character and the one or more attributes of the one or more next characters comprising an attribute data structure which comprises a one-byte array, wherein the one-byte array comprises a plurality of binary bits and each bit of the binary bits indicates a different class from remaining bits of the binary bits. 12. The computer program product of claim 11 , wherein the at least one component is further operable to set the attribute data structure of the current character and the one or more next characters, to assign the current character and the one or more next characters to the one or more classes. | 0.812102 |
7,590,533 | 6 | 7 | 6. The computer-readable storage medium of claim 5 , wherein placing the phonetic units in a search structure comprises aligning the speech-based phonetic sequence and the at least one text-based phonetic sequence to identify phonetic units that are alternatives of each other. | 6. The computer-readable storage medium of claim 5 , wherein placing the phonetic units in a search structure comprises aligning the speech-based phonetic sequence and the at least one text-based phonetic sequence to identify phonetic units that are alternatives of each other. 7. The computer-readable storage medium of claim 6 , wherein the search structure contains a single path for a phonetic unit that is found in both the text-based phonetic sequence and the speech-based phonetic sequence. | 0.918829 |
9,472,209 | 22 | 25 | 22. A method for navigating to a location in recorded content, the method comprising the steps of: a computer receiving a descriptive term or phrase associated with a searchable tag, wherein the searchable tag corresponds to a point-in-time at which a non-speech sound occurred during the recording of recorded content of a communication between a plurality of participants, wherein the recorded content comprises speech from one or more of the plurality of participants, wherein the descriptive term includes an automatically generated phonetic translation of the non-speech sound, and wherein the non-speech sound was transmitted to the plurality of participants during the recording; and the computer navigating to a location in the recorded content corresponding to the point-in-time at which the non-speech sound occurred. | 22. A method for navigating to a location in recorded content, the method comprising the steps of: a computer receiving a descriptive term or phrase associated with a searchable tag, wherein the searchable tag corresponds to a point-in-time at which a non-speech sound occurred during the recording of recorded content of a communication between a plurality of participants, wherein the recorded content comprises speech from one or more of the plurality of participants, wherein the descriptive term includes an automatically generated phonetic translation of the non-speech sound, and wherein the non-speech sound was transmitted to the plurality of participants during the recording; and the computer navigating to a location in the recorded content corresponding to the point-in-time at which the non-speech sound occurred. 25. The method of claim 22 , wherein the step of receiving a descriptive term or phrase associated with the searchable tag comprises: the computer receiving a search query including the descriptive term or phrase; and the computer searching the recorded content for a match between the descriptive term or phrase and a term or phrase included in the searchable tag. | 0.707063 |
7,764,701 | 1 | 2 | 1. A method comprising: providing an ontology that represents a hierarchical organization of a plurality of nodes, wherein each node of the plurality of nodes corresponds to one class of a plurality of classes; associating each peer system of a plurality of peer systems with at least one of the plurality of nodes in the ontology based on information maintained on each peer system and a class of the plurality of classes to which the information corresponds; receiving a request including a select class of the plurality of classes from a first peer system of the plurality of peer systems; identifying a select node of the plurality of nodes based on the select class; identifying at least one peer system of the plurality of peer systems that is associated with the select node; and sending to the first peer system identification information identifying the at least one peer system and identifying a date and a time of when the at least one peer system was associated with the ontology. | 1. A method comprising: providing an ontology that represents a hierarchical organization of a plurality of nodes, wherein each node of the plurality of nodes corresponds to one class of a plurality of classes; associating each peer system of a plurality of peer systems with at least one of the plurality of nodes in the ontology based on information maintained on each peer system and a class of the plurality of classes to which the information corresponds; receiving a request including a select class of the plurality of classes from a first peer system of the plurality of peer systems; identifying a select node of the plurality of nodes based on the select class; identifying at least one peer system of the plurality of peer systems that is associated with the select node; and sending to the first peer system identification information identifying the at least one peer system and identifying a date and a time of when the at least one peer system was associated with the ontology. 2. A method according to claim 1 , wherein the step of sending to the first peer system the identification information identifying the at least one peer system comprises sending an identification of content available from the at least one peer system. | 0.526415 |
8,887,291 | 1 | 5 | 1. A computer-implemented method for data loss prevention for text fields, at least a portion of the method being performed by a computing device comprising at least one processor, the method comprising: identifying, by the computing device, a form submission sent from a client system, the form submission comprising a textual field; storing, by the computing device, at least one characteristic of a value of the textual field within the form submission in connection with an identifier of a form used to generate the form submission; determining, by the computing device and based at least in part on the characteristic of the value of the textual field, that the textual field comprises user-generated content; storing, by the computing device an additional characteristic of an additional value of an additional textual field within the form submission in connection with the identifier of the form; determining, by the computing device and based at least in part on the additional characteristic, that the additional textual field does not comprise user-generated content; intercepting, by the computing device and a subsequent form submission derived from the form; subjecting, by the computing device, the textual field within the subsequent form submission to a data-loss-prevention analysis based at least in part on determining that the textual field comprises user-generated content; omitting, by the computing device, the additional textual field from the data-loss-prevention analysis based at least in part on determining that the additional textual field does not comprise user-generated content; performing, by the computing device, a data-loss-prevention action based on the data-loss-prevention analysis. | 1. A computer-implemented method for data loss prevention for text fields, at least a portion of the method being performed by a computing device comprising at least one processor, the method comprising: identifying, by the computing device, a form submission sent from a client system, the form submission comprising a textual field; storing, by the computing device, at least one characteristic of a value of the textual field within the form submission in connection with an identifier of a form used to generate the form submission; determining, by the computing device and based at least in part on the characteristic of the value of the textual field, that the textual field comprises user-generated content; storing, by the computing device an additional characteristic of an additional value of an additional textual field within the form submission in connection with the identifier of the form; determining, by the computing device and based at least in part on the additional characteristic, that the additional textual field does not comprise user-generated content; intercepting, by the computing device and a subsequent form submission derived from the form; subjecting, by the computing device, the textual field within the subsequent form submission to a data-loss-prevention analysis based at least in part on determining that the textual field comprises user-generated content; omitting, by the computing device, the additional textual field from the data-loss-prevention analysis based at least in part on determining that the additional textual field does not comprise user-generated content; performing, by the computing device, a data-loss-prevention action based on the data-loss-prevention analysis. 5. The computer-implemented method of claim 1 , wherein the characteristic comprises at least one of: a character distribution within the value of the textual field; a textual length of the value of the textual field; a number of spaces within the value of the textual field. | 0.603746 |
8,370,144 | 8 | 14 | 8. A method according to claim 6 , wherein the windows are overlapping and the step of segmenting comprises segmenting the audio stream into the overlapping windows. | 8. A method according to claim 6 , wherein the windows are overlapping and the step of segmenting comprises segmenting the audio stream into the overlapping windows. 14. A method according to claim 8 , wherein the second limit is 15 windows. | 0.983836 |
8,719,296 | 19 | 20 | 19. At least one non-transitory computer-readable medium storing computer-readable instructions that, when executed by one or more computing devices, cause at least one of the one or more computing devices to: apply an extractor pattern to a computer-readable data source, wherein the extractor pattern is generated based at least in part on a prior identification of data of interest and wherein the extractor pattern includes one or more regular expressions which are configured to identify additional data of interest in the computer-readable data source; retrieve the additional data of interest from the computer-readable data source using the one or more regular expressions; and store the additional data of interest in a data storage device. | 19. At least one non-transitory computer-readable medium storing computer-readable instructions that, when executed by one or more computing devices, cause at least one of the one or more computing devices to: apply an extractor pattern to a computer-readable data source, wherein the extractor pattern is generated based at least in part on a prior identification of data of interest and wherein the extractor pattern includes one or more regular expressions which are configured to identify additional data of interest in the computer-readable data source; retrieve the additional data of interest from the computer-readable data source using the one or more regular expressions; and store the additional data of interest in a data storage device. 20. The at least one non-transitory computer-readable medium of claim 19 , wherein the instructions that, when executed by at least one of the one or more computing devices, cause at least one of the one or more computing devices to apply the extractor pattern to the computer-readable data source further cause at least one of the one or more computing devices to apply one or more extraction instructions in conjunction with the extractor pattern, the one or more extraction instructions being selected from a plurality of extraction instructions. | 0.566351 |
8,185,396 | 13 | 14 | 13. The machine-readable medium of claim 11 wherein said determining said pronunciation for said top level domain is further based upon whether said top level domain has at least a threshold number of characters. | 13. The machine-readable medium of claim 11 wherein said determining said pronunciation for said top level domain is further based upon whether said top level domain has at least a threshold number of characters. 14. The machine-readable medium of claim 13 wherein said threshold number of characters is three. | 0.966343 |
8,250,046 | 7 | 8 | 7. A computer program product stored in one or more non-transitory computer readable storage media comprising executable instructions which, when executed by a processing system, cause the processing system to perform cross-language search, comprising: receiving an original search query in a first language; determining that the original search query includes an entity, the entity being one or more words that are a noun indicative of a place of origin where a second language is primarily spoken, the second language being different from the first language; and in response to the determination: obtaining a translated search query for the original search query, the translated search query being in the second language; determining that the translated search query is a candidate for a cross-language search, wherein the determining comprises: identifying a number of previous queries that have included the entity from a list of foreign entities; comparing the number of previous queries including the entity to a threshold numberof queries; determining that the number of previous queries that have included the entity exceeds the threshold number of queries; and determining that the translated search query including the entity is a candidate in response to determining that the number of previous queries that have included the entity exceeds the threshold number of queries; and generating search results relevant to the translated search query in response to determining that the translated search query is a candidate for a cross-language search. | 7. A computer program product stored in one or more non-transitory computer readable storage media comprising executable instructions which, when executed by a processing system, cause the processing system to perform cross-language search, comprising: receiving an original search query in a first language; determining that the original search query includes an entity, the entity being one or more words that are a noun indicative of a place of origin where a second language is primarily spoken, the second language being different from the first language; and in response to the determination: obtaining a translated search query for the original search query, the translated search query being in the second language; determining that the translated search query is a candidate for a cross-language search, wherein the determining comprises: identifying a number of previous queries that have included the entity from a list of foreign entities; comparing the number of previous queries including the entity to a threshold numberof queries; determining that the number of previous queries that have included the entity exceeds the threshold number of queries; and determining that the translated search query including the entity is a candidate in response to determining that the number of previous queries that have included the entity exceeds the threshold number of queries; and generating search results relevant to the translated search query in response to determining that the translated search query is a candidate for a cross-language search. 8. The computer program product of claim 7 , wherein determining that the translated search query is a candidate for a cross-language search further comprises determining that a translation confidence score for the translated search query exceeds a translation confidence score threshold for search queries that are candidates for cross-language search. | 0.756887 |
8,930,817 | 1 | 3 | 1. A method for displaying photographs in a photographic slideshow, comprising: receiving with an electronic device contextual information; after the receiving: identifying with the electronic device at least one photograph that is associated with the received contextual information; and selecting with the electronic device at least one theme element that is associated with the received contextual information, after the identifying and after the selecting, generating with the electronic device the photographic slideshow, wherein the generated photographic slideshow comprises a first slideshow portion, and wherein the first slideshow portion comprises at least a portion of a first photograph, at least a portion of the identified at least one photograph, and the selected at least one theme element; and after the generating, displaying with the electronic device the first slideshow portion of the generated photographic slideshow by displaying each of the at least a portion of the first photograph, the at least a portion of the identified at least one photograph, and the selected at least one theme element, wherein during the displaying the first slideshow portion: the displayed at least a portion of the identified at least one photograph is within a boundary of the displayed at least one theme element; each of the displayed at least a portion of the identified at least one photograph and the displayed at least one theme element is at least partially overlaid on the displayed at least a portion of the first photograph; and each of the displayed at least a portion of the identified at least one photograph and the displayed at least one theme element moves relative to the displayed at least a portion of the first photograph. | 1. A method for displaying photographs in a photographic slideshow, comprising: receiving with an electronic device contextual information; after the receiving: identifying with the electronic device at least one photograph that is associated with the received contextual information; and selecting with the electronic device at least one theme element that is associated with the received contextual information, after the identifying and after the selecting, generating with the electronic device the photographic slideshow, wherein the generated photographic slideshow comprises a first slideshow portion, and wherein the first slideshow portion comprises at least a portion of a first photograph, at least a portion of the identified at least one photograph, and the selected at least one theme element; and after the generating, displaying with the electronic device the first slideshow portion of the generated photographic slideshow by displaying each of the at least a portion of the first photograph, the at least a portion of the identified at least one photograph, and the selected at least one theme element, wherein during the displaying the first slideshow portion: the displayed at least a portion of the identified at least one photograph is within a boundary of the displayed at least one theme element; each of the displayed at least a portion of the identified at least one photograph and the displayed at least one theme element is at least partially overlaid on the displayed at least a portion of the first photograph; and each of the displayed at least a portion of the identified at least one photograph and the displayed at least one theme element moves relative to the displayed at least a portion of the first photograph. 3. The method of claim 1 , wherein the receiving comprises automatically selecting with the electronic device the contextual information. | 0.7249 |
8,145,494 | 1 | 6 | 1. A voice interactive system for responding to a voice inquiry from a user during a session between the user and the system, comprising: a combination of hardware and software configured to embody: a voice interactive unit for recognizing speech in the voice inquiry from the user and providing responses to the inquiry; a dialog history log for storing a record of a dialog between the voice interactive unit and the user; a dialog state diagram definition file for defining each expected dialog state for the session and information regarding at least display of a dialog state diagram; a dialog state determination model comprising information for estimating a current dialog state according to the dialog history log from a service start time to a current time; a dialog information analyzing unit, responsive to a determination by the voice interactive unit that it cannot provide a valid response to the voice inquiry from the user, for estimating the current dialog state between the user and the voice interactive unit based on the dialog history log and the dialog state determination model; and a dialog state display unit remote from the user for displaying the dialog state diagram, including a representation of each expected dialog state for the session, and further including a representation of at least one dialog state, other than a transition between dialog states, not yet entered during the session, according to the dialog state diagram definition file, and for visually presenting the current dialog state estimated by the dialog information analyzing unit on said dialog state diagram to an operator other than the user. | 1. A voice interactive system for responding to a voice inquiry from a user during a session between the user and the system, comprising: a combination of hardware and software configured to embody: a voice interactive unit for recognizing speech in the voice inquiry from the user and providing responses to the inquiry; a dialog history log for storing a record of a dialog between the voice interactive unit and the user; a dialog state diagram definition file for defining each expected dialog state for the session and information regarding at least display of a dialog state diagram; a dialog state determination model comprising information for estimating a current dialog state according to the dialog history log from a service start time to a current time; a dialog information analyzing unit, responsive to a determination by the voice interactive unit that it cannot provide a valid response to the voice inquiry from the user, for estimating the current dialog state between the user and the voice interactive unit based on the dialog history log and the dialog state determination model; and a dialog state display unit remote from the user for displaying the dialog state diagram, including a representation of each expected dialog state for the session, and further including a representation of at least one dialog state, other than a transition between dialog states, not yet entered during the session, according to the dialog state diagram definition file, and for visually presenting the current dialog state estimated by the dialog information analyzing unit on said dialog state diagram to an operator other than the user. 6. The voice interactive system according to claim 1 , wherein the dialog state display unit visually highlights the current dialog state estimated by the dialog information analyzing unit on the dialog state diagram. | 0.72807 |
9,031,937 | 19 | 22 | 19. 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 search system from a user device, a search query submitted by a user through a search interface of a website of a content provider; identifying, by the search system, a context file provided by the content provider, the context file identifying one or more preferences of the content provider for obtaining search results for users requesting searches through the search interface of the content provider, wherein the context file includes, for each of one or more resources, a respective score assigned by the content provider for the resource, the score representing a figure of merit of the resource relative to other resources identified in the context file by the content provider; obtaining, by the search system, one or more search results that satisfy the search query; ranking the one or more search results according to the respective scores assigned by the content provider in the context file; and providing the one or more search results to the user device for presentation to the user. | 19. 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 search system from a user device, a search query submitted by a user through a search interface of a website of a content provider; identifying, by the search system, a context file provided by the content provider, the context file identifying one or more preferences of the content provider for obtaining search results for users requesting searches through the search interface of the content provider, wherein the context file includes, for each of one or more resources, a respective score assigned by the content provider for the resource, the score representing a figure of merit of the resource relative to other resources identified in the context file by the content provider; obtaining, by the search system, one or more search results that satisfy the search query; ranking the one or more search results according to the respective scores assigned by the content provider in the context file; and providing the one or more search results to the user device for presentation to the user. 22. The system of claim 19 , wherein the respective score for each of the one or more resources represents an indication of relative accuracy of the resource among the one or more resources specified in the context file by the content provider. | 0.633634 |
7,962,477 | 8 | 9 | 8. A system comprising: a machine-readable storage device including instructions; and one or more computers operable to execute the instructions and perform operations comprising: receiving a search query, a plurality of generic search results, and a plurality of mobile search results from the user interface device, wherein the generic search results each satisfy the search query, identify a respective generic resource, and have a respective search result quality score, and wherein the mobile search results each satisfy the search query, identify a respective mobile resource, and have a respective search result quality score; determining that the search query came from a mobile user; evaluating, for each mobile search result in a set of one or more of the plurality of mobile search results, one or more properties of the respective mobile resource identified by the particular mobile search result, and modifying the particular mobile search result's respective quality score based at least partially on the one or more properties; and wherein a first mobile search result in the set of mobile search results links to a mobile resource that links to downloadable content for a mobile device, and in which modifying the first mobile search result's respective quality score comprises increasing the respective quality score of the first mobile search result. | 8. A system comprising: a machine-readable storage device including instructions; and one or more computers operable to execute the instructions and perform operations comprising: receiving a search query, a plurality of generic search results, and a plurality of mobile search results from the user interface device, wherein the generic search results each satisfy the search query, identify a respective generic resource, and have a respective search result quality score, and wherein the mobile search results each satisfy the search query, identify a respective mobile resource, and have a respective search result quality score; determining that the search query came from a mobile user; evaluating, for each mobile search result in a set of one or more of the plurality of mobile search results, one or more properties of the respective mobile resource identified by the particular mobile search result, and modifying the particular mobile search result's respective quality score based at least partially on the one or more properties; and wherein a first mobile search result in the set of mobile search results links to a mobile resource that links to downloadable content for a mobile device, and in which modifying the first mobile search result's respective quality score comprises increasing the respective quality score of the first mobile search result. 9. The system of claim 8 , wherein modifying the particular mobile search result's respective quality score further comprises: identifying a first language of the search query; identifying that the respective mobile resource identified by the particular mobile search result is written in a second language; and decreasing the particular mobile search result's quality score if the first language is different from the second language. | 0.680147 |
9,196,252 | 15 | 16 | 15. The non-transitory machine readable storage medium of claim 13 , wherein said pre-determined characterization specifies a pre-determined preference for processing said speech grammar either locally at the client device or remotely at the at least one speech server. | 15. The non-transitory machine readable storage medium of claim 13 , wherein said pre-determined characterization specifies a pre-determined preference for processing said speech grammar either locally at the client device or remotely at the at least one speech server. 16. The non-transitory machine readable storage medium of claim 15 , wherein said pre-determined characterization further specifies a location of the at least one speech server for remotely processing said speech grammar. | 0.885965 |
8,914,276 | 1 | 4 | 1. A computer-implemented method to provide automated translation of video captions and playback to one or more clients, the method comprising: receiving an indication of a video that includes associated caption text; identifying a source language associated with the caption text without playing the video; selecting a target language to which to translate the associated caption text from the identified source language; automatically translating the caption text from the identified source language to the selected target language without playing the video; storing the translated captions in a caption file after automatically translating the caption text; repackaging the received video and translated captions so that the video can be played with the new captions; and playing the received video and displaying each translated caption at appropriate points during the video, wherein the preceding steps are performed by at least one processor. | 1. A computer-implemented method to provide automated translation of video captions and playback to one or more clients, the method comprising: receiving an indication of a video that includes associated caption text; identifying a source language associated with the caption text without playing the video; selecting a target language to which to translate the associated caption text from the identified source language; automatically translating the caption text from the identified source language to the selected target language without playing the video; storing the translated captions in a caption file after automatically translating the caption text; repackaging the received video and translated captions so that the video can be played with the new captions; and playing the received video and displaying each translated caption at appropriate points during the video, wherein the preceding steps are performed by at least one processor. 4. The method of claim 1 wherein identifying the source language comprises accessing a language identifier stored with the caption text. | 0.885135 |
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