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9,361,382 | 1 | 3 | 1. A method programmed in a non-transitory memory of a device comprising: a. automatically fact checking social networking information by comparing the social networking information with source information to generate a result, wherein comparing includes: i. searching for an exact match of the social networking information in the source information and returning the exact match search result of the exact match search if the exact match is found; ii. otherwise, if the exact match is not found, then utilizing pattern matching for fact checking and returning the result of the pattern matching fact check if a pattern matching result confidence score is above a pattern matching result confidence threshold; iii. otherwise, if the pattern matching result confidence score is not above the pattern matching result confidence threshold, then utilizing a natural language search for fact checking and returning the result of the natural language fact check if a natural language result confidence score is above a natural language result confidence threshold; and iv. otherwise, returning a negative result value as the result; and b. automatically presenting a status of the social networking information in real-time based on the result of the comparison of the social networking information with the source information, wherein searching for the exact match begins searching the source information located on a fastest access time hardware device, then using the source information located on a second fastest access time hardware device, and then using the source information located on slower access time hardware devices until a device list has been exhausted; wherein utilizing pattern matching begins utilizing the source information located on the fastest access time hardware device, then using the source information located on the second fastest access time hardware device, and then using the source information located on the slower access time hardware devices until the device list has been exhausted; and wherein the natural language search begins searching the source information located on the fastest access time hardware device, then using the source information located on the second fastest access time hardware device, and then using the source information located on the slower access time hardware devices until the device list has been exhausted. | 1. A method programmed in a non-transitory memory of a device comprising: a. automatically fact checking social networking information by comparing the social networking information with source information to generate a result, wherein comparing includes: i. searching for an exact match of the social networking information in the source information and returning the exact match search result of the exact match search if the exact match is found; ii. otherwise, if the exact match is not found, then utilizing pattern matching for fact checking and returning the result of the pattern matching fact check if a pattern matching result confidence score is above a pattern matching result confidence threshold; iii. otherwise, if the pattern matching result confidence score is not above the pattern matching result confidence threshold, then utilizing a natural language search for fact checking and returning the result of the natural language fact check if a natural language result confidence score is above a natural language result confidence threshold; and iv. otherwise, returning a negative result value as the result; and b. automatically presenting a status of the social networking information in real-time based on the result of the comparison of the social networking information with the source information, wherein searching for the exact match begins searching the source information located on a fastest access time hardware device, then using the source information located on a second fastest access time hardware device, and then using the source information located on slower access time hardware devices until a device list has been exhausted; wherein utilizing pattern matching begins utilizing the source information located on the fastest access time hardware device, then using the source information located on the second fastest access time hardware device, and then using the source information located on the slower access time hardware devices until the device list has been exhausted; and wherein the natural language search begins searching the source information located on the fastest access time hardware device, then using the source information located on the second fastest access time hardware device, and then using the source information located on the slower access time hardware devices until the device list has been exhausted. 3. The method of claim 1 wherein searching for the exact match begins searching the source information located in a designated fact checking database, then goes to a broader set of source information, and repeatedly goes to broader sets of source information until a broadest source information set has been exhausted; wherein utilizing pattern matching begins utilizing the source information located in the designated fact checking database, then goes to the broader set of source information, and repeatedly goes to broader sets of source information until the broadest source information set has been exhausted; and wherein the natural language search begins searching the source information located in the designated fact checking database, then goes to the broader set of source information, and repeatedly goes to broader sets of source information until the broadest source information set has been exhausted. | 0.628143 |
8,095,582 | 3 | 5 | 3. The method of claim 1 further comprising: selecting subordinate keywords from at least one of links clicked on by the user, other links associated with a document including links pointing to the document, descriptive text associated with each document in the search results, meta-tags connected to viewed documents, prominent words and phrases in viewed documents and a thesaurus; and improving the ranking of search results objects containing said subordinate keywords. | 3. The method of claim 1 further comprising: selecting subordinate keywords from at least one of links clicked on by the user, other links associated with a document including links pointing to the document, descriptive text associated with each document in the search results, meta-tags connected to viewed documents, prominent words and phrases in viewed documents and a thesaurus; and improving the ranking of search results objects containing said subordinate keywords. 5. The method of claim 3 further comprising: assigning weights to said subordinate keywords, such that search result objects having higher weighted subordinate keywords are given increased preference in the ranking. | 0.552083 |
9,164,988 | 11 | 14 | 11. A system for dynamically translating an original-language website, the system comprising: a server having an interface for receiving a request from a user system for a translated website, wherein the user request comprises a base URL identifying the original-language website and an extension identifying a target language, wherein the request is routed to an MT server configured to retrieve original content associated with the original-language website, wherein an MT engine is configured to translate at least one segment of the original content into the target language, wherein being configured to translate comprises: being configured to determine to bypass translation of a first segment of the original content upon a determination that a translation time associated with the first segment of the original content will likely exceed a predetermined threshold identified in a service level agreement, being configured to bypass translation of the first segment of the original content into the target language upon the determination that the translation time will likely exceed the predetermined threshold, and translating a second segment of the original content; and wherein the MT server is configured to return the translated second segment of the original content to the user system. | 11. A system for dynamically translating an original-language website, the system comprising: a server having an interface for receiving a request from a user system for a translated website, wherein the user request comprises a base URL identifying the original-language website and an extension identifying a target language, wherein the request is routed to an MT server configured to retrieve original content associated with the original-language website, wherein an MT engine is configured to translate at least one segment of the original content into the target language, wherein being configured to translate comprises: being configured to determine to bypass translation of a first segment of the original content upon a determination that a translation time associated with the first segment of the original content will likely exceed a predetermined threshold identified in a service level agreement, being configured to bypass translation of the first segment of the original content into the target language upon the determination that the translation time will likely exceed the predetermined threshold, and translating a second segment of the original content; and wherein the MT server is configured to return the translated second segment of the original content to the user system. 14. The system of claim 11 , wherein the server is configured to establish a secure connection with a host system associated with the original-language website, and wherein the MT server is configured to retrieve the original content and to return the translated content using the secure connection. | 0.597035 |
8,923,608 | 1 | 23 | 1. A computer-implemented method for evaluating training data comprising: receiving training data comprising a labeled training set of digital objects, at least some of the digital objects in the labeled training set including a label indicating that the digital object is positive for a respective class selected from a predetermined set of classes with which a classifier is to be trained; grouping the positively labeled digital objects in the labeled training set into positive label groups, one positive label group for each class in the set of classes, each label group comprising digital objects having a label indicating the digital object is positive for the respective class; with a trained categorizer, assigning a score vector to each digital object in the labeled training set of digital objects, the score vector comprising a score for each category of a predetermined set of categories; applying at least one heuristic to the training data to evaluate the training data for training the classifier based on the assigned score vectors and training data labels; and based on the at least one heuristic, providing an evaluation of the training data prior to training the classifier. | 1. A computer-implemented method for evaluating training data comprising: receiving training data comprising a labeled training set of digital objects, at least some of the digital objects in the labeled training set including a label indicating that the digital object is positive for a respective class selected from a predetermined set of classes with which a classifier is to be trained; grouping the positively labeled digital objects in the labeled training set into positive label groups, one positive label group for each class in the set of classes, each label group comprising digital objects having a label indicating the digital object is positive for the respective class; with a trained categorizer, assigning a score vector to each digital object in the labeled training set of digital objects, the score vector comprising a score for each category of a predetermined set of categories; applying at least one heuristic to the training data to evaluate the training data for training the classifier based on the assigned score vectors and training data labels; and based on the at least one heuristic, providing an evaluation of the training data prior to training the classifier. 23. The method of claim 1 , wherein the received training data comprises a set of unlabeled digital objects, the method further comprising: with the categorizer, assigning a score vector to each digital object in the set of unlabeled digital objects, the score vector comprising a score for each category of the set of categories; and wherein the applying of the at least one heuristic comprises applying a heuristic configured for identifying at least one class which is not represented in the set of unlabeled digital objects. | 0.698974 |
7,593,575 | 34 | 36 | 34. A method, comprising: providing a document to a computer system, wherein the document comprises a payee field; assessing, using the computer system, whether writing in the payee field approximately matches a writing profile representation, wherein the matching writing profile representation is associated with a corresponding text representation of a payee name in a computer processable format in memory on the computer system; associating the payee field with the text representation corresponding to the matching writing profile representation; assessing, using the computer system, whether the payee in the payee field of the document matches one or more entries in a list of suspicious payees; and performing one or more fraud tests of the document based at least in part on information captured from the payee field of the document. | 34. A method, comprising: providing a document to a computer system, wherein the document comprises a payee field; assessing, using the computer system, whether writing in the payee field approximately matches a writing profile representation, wherein the matching writing profile representation is associated with a corresponding text representation of a payee name in a computer processable format in memory on the computer system; associating the payee field with the text representation corresponding to the matching writing profile representation; assessing, using the computer system, whether the payee in the payee field of the document matches one or more entries in a list of suspicious payees; and performing one or more fraud tests of the document based at least in part on information captured from the payee field of the document. 36. The method of claim 34 , wherein the list of suspicious payees comprises one or more payee names frequently involved in transactions with fraud risk. | 0.5 |
8,775,130 | 1 | 2 | 1. A computer program product, comprising a computer usable medium having a computer readable program code embodied therein, the computer readable program code adapted to be executed to implement a method for automatically generating a package design, the method comprising: receiving, from a user via an input device, a packaging intent comprising one or more constraints, wherein the one or more constraints comprise one or more of the following industry constraints: trade or industry association guidelines; brand identification guidelines; instructions for product use; coding for quality assurance; expiration dates; or dietary and nutritional information; automatically generating, with a processing module and a semantic knowledge base, one or more external graphical layout rules and one or more structural design rules based on the one or more constraints, wherein the external graphical layout rules are associated with a plurality of graphical assets and guide a relationship between a graphical asset and layout of each graphical asset on one or more exterior surfaces of the package; automatically generating a three dimensional representation of a package design based on the one or more external graphical layout rules and the one or more structural design rules, wherein automatically generating a three dimensional representation comprises, for at least one graphical asset of the plurality of graphical assets, determining an exterior surface location, on the three dimensional representation, associated with the at least one graphical asset and determining one or more boundaries associated with the at least one graphical asset based at least in part on the one or more industry constraints; and displaying the three dimensional representation of the package design, wherein displaying the three dimensional representation comprises displaying the at least one of the plurality of graphical assets at the determined exterior surface location and within the determined boundaries associated with the graphical asset. | 1. A computer program product, comprising a computer usable medium having a computer readable program code embodied therein, the computer readable program code adapted to be executed to implement a method for automatically generating a package design, the method comprising: receiving, from a user via an input device, a packaging intent comprising one or more constraints, wherein the one or more constraints comprise one or more of the following industry constraints: trade or industry association guidelines; brand identification guidelines; instructions for product use; coding for quality assurance; expiration dates; or dietary and nutritional information; automatically generating, with a processing module and a semantic knowledge base, one or more external graphical layout rules and one or more structural design rules based on the one or more constraints, wherein the external graphical layout rules are associated with a plurality of graphical assets and guide a relationship between a graphical asset and layout of each graphical asset on one or more exterior surfaces of the package; automatically generating a three dimensional representation of a package design based on the one or more external graphical layout rules and the one or more structural design rules, wherein automatically generating a three dimensional representation comprises, for at least one graphical asset of the plurality of graphical assets, determining an exterior surface location, on the three dimensional representation, associated with the at least one graphical asset and determining one or more boundaries associated with the at least one graphical asset based at least in part on the one or more industry constraints; and displaying the three dimensional representation of the package design, wherein displaying the three dimensional representation comprises displaying the at least one of the plurality of graphical assets at the determined exterior surface location and within the determined boundaries associated with the graphical asset. 2. The computer program product of claim 1 wherein the code is further adapted to implement a method comprising: receiving user feedback regarding the displayed three dimensional representation of the package design; and modifying the displayed three dimensional representation based on the user feedback. | 0.728648 |
8,291,317 | 1 | 8 | 1. A document retrieving apparatus comprising: a document retrieving unit constructed to retrieve, from a plurality of document data, one or more document data which include a page or an image element that matches an input retrieval condition; a retrieval result list display unit constructed to display, on a display unit, a list display of the one or more document data which include the page or the image element that matches the retrieval condition based on retrieval results of the document retrieving unit; and a thumbnail display unit constructed to display, in the list display by the retrieval result list display unit, both of first and second thumbnail images for each displayed document data, wherein the first thumbnail image is associated with the page or the image element in the document data which matches the retrieval condition, and the second thumbnail image is associated with a page or an image element which is automatically selected from other pages or other image elements in the document data based on a thumbnail configuration setting, wherein for each displayed document data, the thumbnail display unit does not display a thumbnail image associated with a page or an image element which is not automatically selected from other pages or other image elements in the document data based on the thumbnail configuration setting, wherein the thumbnail configuration setting is a setting for selecting a first page or image element or a last page or image element in each displayed document data, wherein for each displayed document data, the second thumbnail image to be displayed includes a thumbnail image associated with a first page or image element or a last page or image element in the displayed document data, and wherein at least one of the document retrieving unit, the retrieval result list display unit, and the thumbnail display unit comprises at least one of a processor and a computer-readable storage medium. | 1. A document retrieving apparatus comprising: a document retrieving unit constructed to retrieve, from a plurality of document data, one or more document data which include a page or an image element that matches an input retrieval condition; a retrieval result list display unit constructed to display, on a display unit, a list display of the one or more document data which include the page or the image element that matches the retrieval condition based on retrieval results of the document retrieving unit; and a thumbnail display unit constructed to display, in the list display by the retrieval result list display unit, both of first and second thumbnail images for each displayed document data, wherein the first thumbnail image is associated with the page or the image element in the document data which matches the retrieval condition, and the second thumbnail image is associated with a page or an image element which is automatically selected from other pages or other image elements in the document data based on a thumbnail configuration setting, wherein for each displayed document data, the thumbnail display unit does not display a thumbnail image associated with a page or an image element which is not automatically selected from other pages or other image elements in the document data based on the thumbnail configuration setting, wherein the thumbnail configuration setting is a setting for selecting a first page or image element or a last page or image element in each displayed document data, wherein for each displayed document data, the second thumbnail image to be displayed includes a thumbnail image associated with a first page or image element or a last page or image element in the displayed document data, and wherein at least one of the document retrieving unit, the retrieval result list display unit, and the thumbnail display unit comprises at least one of a processor and a computer-readable storage medium. 8. The apparatus according to claim 1 , further comprising: an animation display setting unit constructed to set an animation-display of thumbnail images that represent contents of the one or more document data retrieved by the document retrieving unit, wherein the thumbnail display unit animation-displays the first thumbnail image and the second thumbnail image in accordance with the setting of the animation display setting unit. | 0.668196 |
9,405,532 | 16 | 17 | 16. The system of claim 10 , wherein processing the received response to validate the contents of the response further comprises determining if the received response satisfies one or more conditions for acceptance by one or more of the system or the first user. | 16. The system of claim 10 , wherein processing the received response to validate the contents of the response further comprises determining if the received response satisfies one or more conditions for acceptance by one or more of the system or the first user. 17. The system of claim 16 , wherein the one or more conditions for acceptance by one or more of the system or the first user include determining one or more of the response provides the translated language segment in the correct language, if the response provides the translated language segment in the correct format, if the response provides all of the requested translations, or if the response provides the translated language segment in a format that is compatible with the data storage element. | 0.5 |
8,346,775 | 13 | 14 | 13. The computer program product of claim 10 , wherein the first collection is within a hierarchy of collections of textual information. | 13. The computer program product of claim 10 , wherein the first collection is within a hierarchy of collections of textual information. 14. The computer program product of claim 13 , wherein the degree of relatedness is a first degree of relatedness, and further comprising: program code, stored on the computer readable storage medium for determining, by the processing unit, whether a third collection of textual information subordinate to the first collection of textual information in the hierarchy having a fourth concept related to the text within a second degree of relatedness is present in the database, wherein the second degree of relatedness is greater than the first degree of relatedness responsive to a determination that the first collection of textual information in the database having the first concept that is related to the second concept for the text is present in the database. | 0.5 |
8,510,327 | 18 | 19 | 18. A non-transitory computer-readable storage medium containing a computer-readable code that when read by a computer causes the computer to perform a method for configuring a memory subsystem of a computing system, the method comprising: using a graphical user interface to create an aggregation of graphical representations of annotations associated with a plurality of data elements contained within the corpus of data and graphical representations of search terms contained within the plurality of data elements, wherein the aggregation comprises at least one annotation and at least one search term; manipulating relative positions of the graphical representations of the annotations and the search terms within the aggregation within the graphical user interface to express relationships among the annotations and search terms by moving graphical representations of annotations to express a relationship between two or more graphical representations of annotations, the annotations, search terms and expressed relationships defining the semantic query; and searching the corpus of data using the defined semantic query. | 18. A non-transitory computer-readable storage medium containing a computer-readable code that when read by a computer causes the computer to perform a method for configuring a memory subsystem of a computing system, the method comprising: using a graphical user interface to create an aggregation of graphical representations of annotations associated with a plurality of data elements contained within the corpus of data and graphical representations of search terms contained within the plurality of data elements, wherein the aggregation comprises at least one annotation and at least one search term; manipulating relative positions of the graphical representations of the annotations and the search terms within the aggregation within the graphical user interface to express relationships among the annotations and search terms by moving graphical representations of annotations to express a relationship between two or more graphical representations of annotations, the annotations, search terms and expressed relationships defining the semantic query; and searching the corpus of data using the defined semantic query. 19. The non-transitory computer readable storage medium of claim 18 , wherein the step of using the graphical user interface to create an aggregation further comprises creating the graphical representations of the annotations and search terms by: creating a separate display window within the graphical user interface for each annotation and for each search term; and entering an annotation or search term into each display window. | 0.5 |
7,818,326 | 18 | 22 | 18. A machine-readable medium having stored thereon data representing instructions that, when executed by a processor of a capture system, cause the processor to perform operations comprising: extracting text contained in a captured object, wherein a content type of the object is determined and the content type is positioned in a content field of a tag associated with the object; generating a plurality of tokens from the extracted text; hashing the plurality of tokens to a plurality of bit position values; and creating a word index to be associated with the captured object by setting bits of a bit vector corresponding to the plurality of bit position values, wherein generating the plurality of tokens comprises tokenizing the extracted text using a context-aware parser, and wherein the context-aware parser uses a list of patterns associated with a content type of the captured object to sub-tokenize at least one of the tokens generated from the extracted text. | 18. A machine-readable medium having stored thereon data representing instructions that, when executed by a processor of a capture system, cause the processor to perform operations comprising: extracting text contained in a captured object, wherein a content type of the object is determined and the content type is positioned in a content field of a tag associated with the object; generating a plurality of tokens from the extracted text; hashing the plurality of tokens to a plurality of bit position values; and creating a word index to be associated with the captured object by setting bits of a bit vector corresponding to the plurality of bit position values, wherein generating the plurality of tokens comprises tokenizing the extracted text using a context-aware parser, and wherein the context-aware parser uses a list of patterns associated with a content type of the captured object to sub-tokenize at least one of the tokens generated from the extracted text. 22. The machine-readable medium of claim 18 , wherein the instructions further cause the processor perform operations comprising: receiving a query including a search term; hashing the search term to a term bit position of the bit vector; and eliminating the captured object from the query by observing that a bit in the term bit position is not set in the word index contained in the tag associated with the captured object. | 0.5 |
7,480,858 | 10 | 11 | 10. The system of claim 9 , wherein the paginating the webpage based on said hierarchical structure further comprises generating an index for one or more pages of the paginated webpage. | 10. The system of claim 9 , wherein the paginating the webpage based on said hierarchical structure further comprises generating an index for one or more pages of the paginated webpage. 11. The system of claim 10 , further comprising: receiving a request for the webpage from the device having the capabilities; and transmitting the adapted paginated webpage and the index therefore to the device | 0.5 |
8,312,376 | 1 | 3 | 1. A method, comprising: maintaining a user profile of a user to track user requests for media content; receiving a bookmark save event from a media device when a bookmark is initiated by the user while a video stream of media content is rendered by the media device; interpreting the bookmark to determine one or more bookmark representations based on a context interpretation of the bookmark with respect to the media content and based on the user requests that are tracked in the user profile for different types of the media content, the one or more bookmark representations derived from metadata that accompanies the media content; maintaining the bookmark for selection; and providing one or more of the bookmark representations that correspond to the bookmark when a request for the bookmark is received. | 1. A method, comprising: maintaining a user profile of a user to track user requests for media content; receiving a bookmark save event from a media device when a bookmark is initiated by the user while a video stream of media content is rendered by the media device; interpreting the bookmark to determine one or more bookmark representations based on a context interpretation of the bookmark with respect to the media content and based on the user requests that are tracked in the user profile for different types of the media content, the one or more bookmark representations derived from metadata that accompanies the media content; maintaining the bookmark for selection; and providing one or more of the bookmark representations that correspond to the bookmark when a request for the bookmark is received. 3. A method as recited in claim 1 , further comprising initiating a recording of the media content from which the bookmark save event is initiated, and wherein a bookmark representation corresponds to an on-demand recording of the media content. | 0.5 |
9,349,132 | 1 | 4 | 1. A method in a system of a host organization, the system having at least a processor and a memory therein, wherein the method comprises: generating indices from a dataset of columns and rows, the indices representing probabilistic relationships between the rows and the columns of the dataset; storing the indices within a database system of the host organization; exposing the database system of the host organization via a request interface; receiving, at the request interface, a query for the database system specifying a GROUP command term and a specified column as a parameter for the GROUP command term; querying the database system using the GROUP command term and passing the specified column to generate a predictive record set; returning the predictive record set responsive to the query, the predictive record set having a plurality of groups specified therein, each returned group of the returned groups of the predictive record set including a group of one or more rows of the dataset; and wherein a confidence indicator returned with each respective row of the one or more rows specified within each group of the plurality of groups returned with the predictive record set ranges from a minimum of 0 indicating a lowest possible confidence in a result that the respective row belongs to the group specified to a maximum of 1 indicating a highest possible confidence in the result that the respective row belongs to the group specified. | 1. A method in a system of a host organization, the system having at least a processor and a memory therein, wherein the method comprises: generating indices from a dataset of columns and rows, the indices representing probabilistic relationships between the rows and the columns of the dataset; storing the indices within a database system of the host organization; exposing the database system of the host organization via a request interface; receiving, at the request interface, a query for the database system specifying a GROUP command term and a specified column as a parameter for the GROUP command term; querying the database system using the GROUP command term and passing the specified column to generate a predictive record set; returning the predictive record set responsive to the query, the predictive record set having a plurality of groups specified therein, each returned group of the returned groups of the predictive record set including a group of one or more rows of the dataset; and wherein a confidence indicator returned with each respective row of the one or more rows specified within each group of the plurality of groups returned with the predictive record set ranges from a minimum of 0 indicating a lowest possible confidence in a result that the respective row belongs to the group specified to a maximum of 1 indicating a highest possible confidence in the result that the respective row belongs to the group specified. 4. The method of claim 1 , wherein the column passed with the GROUP command term provides the context of a latent structure in which the one or more rows of each specified group are assessed for similarity to any other rows within the same group, wherein the column passed with the GROUP command term provides the context of a latent structure in which the one or more rows of each specified group are assessed for similarity to any other rows within the same group. | 0.670904 |
9,607,048 | 18 | 20 | 18. A computer system comprising: a processor, a computer readable memory, and a computer readable storage medium; first program instructions to derive a context object for a non-contextual data object, wherein the non-contextual data object ambiguously relates to multiple subject-matters, wherein the context object provides a context that identifies a specific subject-matter, from multiple subject-matters, of the non-contextual data object, wherein the context object is derived by contextually searching and analyzing a document to derive the context object, and wherein the context object is selected according to a profile for a particular user; second program instructions to establish a minimum validity threshold for the context object, wherein the minimum validity threshold defines a probability that a set of one or more context objects accurately describes the context of the non-contextual data object; and third program instructions to expand a range of a search area of the document until the minimum validity threshold is reached; fourth program instructions to associate the non-contextual data object with the context object to define a synthetic context-based object; fifth program instructions to associate the synthetic context-based object with at least one specific data store, wherein said at least one specific data store comprises data that is associated with data contained in the non-contextual data object and the context object; sixth program instructions to construct a dimensionally constrained hierarchical synthetic context-based object library for multiple synthetic context-based objects, wherein synthetic context-based objects within a same dimension of the dimensionally constrained hierarchical synthetic context-based object library share data from a same non-contextual data object, and wherein synthetic context-based objects within the same dimension of the dimensionally constrained hierarchical synthetic context-based object library contain disparate data from different context objects; seventh program instructions to receive, from the particular user, a request for at least one data store that is associated with synthetic context-based objects within the same dimension of the dimensionally constrained hierarchical synthetic context-based object library; eighth program instructions to return, to the particular user, said at least one specific data store that is associated with synthetic context-based objects within the same dimension of the dimensionally constrained hierarchical synthetic context-based object library; and wherein the first, second, third, fourth, fifth, sixth, seventh, and eighth program instructions are stored on the computer readable storage medium for execution by the processor via the computer readable memory. | 18. A computer system comprising: a processor, a computer readable memory, and a computer readable storage medium; first program instructions to derive a context object for a non-contextual data object, wherein the non-contextual data object ambiguously relates to multiple subject-matters, wherein the context object provides a context that identifies a specific subject-matter, from multiple subject-matters, of the non-contextual data object, wherein the context object is derived by contextually searching and analyzing a document to derive the context object, and wherein the context object is selected according to a profile for a particular user; second program instructions to establish a minimum validity threshold for the context object, wherein the minimum validity threshold defines a probability that a set of one or more context objects accurately describes the context of the non-contextual data object; and third program instructions to expand a range of a search area of the document until the minimum validity threshold is reached; fourth program instructions to associate the non-contextual data object with the context object to define a synthetic context-based object; fifth program instructions to associate the synthetic context-based object with at least one specific data store, wherein said at least one specific data store comprises data that is associated with data contained in the non-contextual data object and the context object; sixth program instructions to construct a dimensionally constrained hierarchical synthetic context-based object library for multiple synthetic context-based objects, wherein synthetic context-based objects within a same dimension of the dimensionally constrained hierarchical synthetic context-based object library share data from a same non-contextual data object, and wherein synthetic context-based objects within the same dimension of the dimensionally constrained hierarchical synthetic context-based object library contain disparate data from different context objects; seventh program instructions to receive, from the particular user, a request for at least one data store that is associated with synthetic context-based objects within the same dimension of the dimensionally constrained hierarchical synthetic context-based object library; eighth program instructions to return, to the particular user, said at least one specific data store that is associated with synthetic context-based objects within the same dimension of the dimensionally constrained hierarchical synthetic context-based object library; and wherein the first, second, third, fourth, fifth, sixth, seventh, and eighth program instructions are stored on the computer readable storage medium for execution by the processor via the computer readable memory. 20. The computer system of claim 18 , further comprising: ninth program instructions to execute a map/reduce search of the document to reach the minimum validity threshold, wherein the map-reduce search sequentially performs evaluations of subsequently lower-level partitions of the document to determine finer levels of granularity to derive the context object; and tenth program instructions to utilize a progressively higher number of processors to execute the evaluations of the subsequently lower-level partitions of the document; and wherein the ninth and tenth program instructions are stored on the computer readable storage medium for execution by the processor via the computer readable memory. | 0.5 |
9,949,103 | 10 | 12 | 10. A system comprising: a processor; and a memory in communication with the processor, the memory containing program instructions that, when executed by the processor, are configured to cause the processor to perform a method comprising: determining, by the processor and using natural language processing, a writing style of content of a composed message written by a composer; analyzing, by the processor and using natural language processing, a set of previous messages written by the composer; identifying, based on the analyzing, writing habits of the composer; identifying, by the processor, a difference between the writing style of the content and the writing habits of the composer; determining, by the processor and based on the difference, that the composer was in an impaired state when composing the message; and displaying, by the processor and through a graphical user interface, a notification of the difference to the composer after a pre-determined wait time, wherein the wait time is based on the magnitude of the difference identified between the writing style and the writing habits. | 10. A system comprising: a processor; and a memory in communication with the processor, the memory containing program instructions that, when executed by the processor, are configured to cause the processor to perform a method comprising: determining, by the processor and using natural language processing, a writing style of content of a composed message written by a composer; analyzing, by the processor and using natural language processing, a set of previous messages written by the composer; identifying, based on the analyzing, writing habits of the composer; identifying, by the processor, a difference between the writing style of the content and the writing habits of the composer; determining, by the processor and based on the difference, that the composer was in an impaired state when composing the message; and displaying, by the processor and through a graphical user interface, a notification of the difference to the composer after a pre-determined wait time, wherein the wait time is based on the magnitude of the difference identified between the writing style and the writing habits. 12. The system of claim 10 , wherein the wait time is based on the type of difference identified between the writing style and the writing habits. | 0.776074 |
8,588,520 | 1 | 2 | 1. A character recognition method executed by a computer, the character recognition method comprising: specifying a character recognition target item from image data of the form; calculating a position and size of an image character in the specified character recognition target item; calculating a score that quantifies a possibility of handwriting or printing by analyzing the image character on the basis of characteristics of handwritten and printed characters; discriminating on the basis of the score whether the image character is handwritten or printed; calculating an average value of scores of characters of the recognition target item, and checking whether or not the recognition target item includes both handwritten and printed characters; and performing character recognition on each character of the recognition target item with an appropriate character recognition engine for a result of discriminating whether said each character is handwritten or printed and a result of checking whether the recognition target item includes both handwritten and printed characters, wherein: the calculating of the score includes: calculating a first score that quantifies a possibility of handwriting or printing by analyzing a gradation distribution of the image character; calculating a second score that quantifies a possibility of handwriting or printing by analyzing a character color of the image character; calculating a third score that quantifies a possibility of handwriting or printing by analyzing a gradation ratio between a turning point where a character stroke extracted from the image character changes and the character stroke other than the turning point; calculating a fourth score that quantifies a possibility of handwriting or printing by analyzing contrast at an edge of the character stroke, the contrast indicating a degree of change in gray level at a boundary between the character stroke and background; calculating a fifth score that quantifies a possibility of handwriting or printing by analyzing vertical sizes and center positions of the characters on the basis of a position and size of the image character; and calculating a sixth score that quantifies a possibility of handwriting or printing by analyzing character sizes and pitch on the basis of the position and size of the image character; and in discriminating whether the image character is handwritten or printed, the first to sixth scores are aggregated by weighting the first to sixth scores according to respective importance. | 1. A character recognition method executed by a computer, the character recognition method comprising: specifying a character recognition target item from image data of the form; calculating a position and size of an image character in the specified character recognition target item; calculating a score that quantifies a possibility of handwriting or printing by analyzing the image character on the basis of characteristics of handwritten and printed characters; discriminating on the basis of the score whether the image character is handwritten or printed; calculating an average value of scores of characters of the recognition target item, and checking whether or not the recognition target item includes both handwritten and printed characters; and performing character recognition on each character of the recognition target item with an appropriate character recognition engine for a result of discriminating whether said each character is handwritten or printed and a result of checking whether the recognition target item includes both handwritten and printed characters, wherein: the calculating of the score includes: calculating a first score that quantifies a possibility of handwriting or printing by analyzing a gradation distribution of the image character; calculating a second score that quantifies a possibility of handwriting or printing by analyzing a character color of the image character; calculating a third score that quantifies a possibility of handwriting or printing by analyzing a gradation ratio between a turning point where a character stroke extracted from the image character changes and the character stroke other than the turning point; calculating a fourth score that quantifies a possibility of handwriting or printing by analyzing contrast at an edge of the character stroke, the contrast indicating a degree of change in gray level at a boundary between the character stroke and background; calculating a fifth score that quantifies a possibility of handwriting or printing by analyzing vertical sizes and center positions of the characters on the basis of a position and size of the image character; and calculating a sixth score that quantifies a possibility of handwriting or printing by analyzing character sizes and pitch on the basis of the position and size of the image character; and in discriminating whether the image character is handwritten or printed, the first to sixth scores are aggregated by weighting the first to sixth scores according to respective importance. 2. The character recognition method according to claim 1 , wherein, in a case where one of the first to sixth scores, which are respectively obtained in analyzing the gradation distribution, analyzing the character color, analyzing the character stroke, analyzing the contrast at the edge of the character stroke, analyzing the vertical sizes and center positions of the characters, and analyzing the character sizes and pitch, exceeds a predetermined threshold set for determining with certainty that a character is a printed character, remaining analyses of the image character are skipped, and analyses of a next image character are started. | 0.5 |
8,335,689 | 1 | 5 | 1. A method to improve the speed and efficiency of human and computerized speech transcription through an automated transcription management system comprising: monitoring automatically the queue of transcription jobs to be worked; allocating automatically the transcription jobs across a pool of at least one of human computerized transcribing resources; monitoring automatically the performance of the current pool of at least one of human and computerized transcribing resources; creating automatically forecasts of expected future transcribing resource needs and, re-adjusting, by a computing device, automatically the use of currently active transcribing resources, pools of reserve transcribing resources, and recruitment of potential future transcribing resources to meet the transcription job forecasts. | 1. A method to improve the speed and efficiency of human and computerized speech transcription through an automated transcription management system comprising: monitoring automatically the queue of transcription jobs to be worked; allocating automatically the transcription jobs across a pool of at least one of human computerized transcribing resources; monitoring automatically the performance of the current pool of at least one of human and computerized transcribing resources; creating automatically forecasts of expected future transcribing resource needs and, re-adjusting, by a computing device, automatically the use of currently active transcribing resources, pools of reserve transcribing resources, and recruitment of potential future transcribing resources to meet the transcription job forecasts. 5. The method of claim 1 wherein the individual transcription jobs are broken into snippets for the purpose of increased at least one of overall efficiency in use of transcription resources or total speed for finishing the transcription job. | 0.566547 |
8,731,902 | 1 | 3 | 1. A computer-implemented method comprising: storing information in a datastore, the information corresponding to a plurality of computer applications, wherein the plurality of computer applications have associated annotations, the annotations comprising a verb describing one or more activities performed by an associated application and a noun describing work objects on which the activities are performed, and wherein users access the applications in the datastore; receiving an input from a user; providing a first verb and a first noun corresponding to a user intent based on said input; and specifying one or more of said plurality of applications based on the verb and noun annotations for the plurality of applications and the first verb and first noun corresponding to the user intent. | 1. A computer-implemented method comprising: storing information in a datastore, the information corresponding to a plurality of computer applications, wherein the plurality of computer applications have associated annotations, the annotations comprising a verb describing one or more activities performed by an associated application and a noun describing work objects on which the activities are performed, and wherein users access the applications in the datastore; receiving an input from a user; providing a first verb and a first noun corresponding to a user intent based on said input; and specifying one or more of said plurality of applications based on the verb and noun annotations for the plurality of applications and the first verb and first noun corresponding to the user intent. 3. The method of claim 1 wherein said specifying is based on semantically matching the first verb and first noun with the verb and noun annotations for the one or more specified applications. | 0.809761 |
8,307,279 | 1 | 3 | 1. A system for smooth zooming in web applications, comprising: one or more computer processors; a structured document defining a plurality of display elements, the plurality of display elements including a resizable container element and a scalable element defined to be located at least partially within the resizable container element when rendered; a rendering component, executed at the one or more computer processors, the rendering component operable to receive the structured document as an input, execute a rendering function that calculates a display position for each of the plurality of display elements, and define rendered content based at least in part on the display position for each of the plurality of display elements; a display component, executed at the one or more computer processors, the display component operable to output a viewable area of the rendered content; and a scaling component, executed at the one or more computer processors, the scaling component operable to receive a scaling input, redefine the scalable element based at least in part on the scaling input, determine whether the resizable container element will be located within the viewable area if the size of the resizable container element is changed so that the resizable container element completely contains the scalable element, redefine the size of the resizable container element if it will be located within the viewable area, and maintain the size of the resizable container element if it will not be located within the viewable area. | 1. A system for smooth zooming in web applications, comprising: one or more computer processors; a structured document defining a plurality of display elements, the plurality of display elements including a resizable container element and a scalable element defined to be located at least partially within the resizable container element when rendered; a rendering component, executed at the one or more computer processors, the rendering component operable to receive the structured document as an input, execute a rendering function that calculates a display position for each of the plurality of display elements, and define rendered content based at least in part on the display position for each of the plurality of display elements; a display component, executed at the one or more computer processors, the display component operable to output a viewable area of the rendered content; and a scaling component, executed at the one or more computer processors, the scaling component operable to receive a scaling input, redefine the scalable element based at least in part on the scaling input, determine whether the resizable container element will be located within the viewable area if the size of the resizable container element is changed so that the resizable container element completely contains the scalable element, redefine the size of the resizable container element if it will be located within the viewable area, and maintain the size of the resizable container element if it will not be located within the viewable area. 3. The system of claim 1 , wherein the size of the scalable element with respect to the rendered content changes when the scaling component redefines the scalable element according to the scaling input. | 0.579167 |
8,046,229 | 11 | 12 | 11. The apparatus of claim 10 wherein the navigation system is a keystroke navigation system. | 11. The apparatus of claim 10 wherein the navigation system is a keystroke navigation system. 12. The apparatus of claim 11 wherein one or more of the audio files comprise the menu options, and wherein the navigation system is assigned to the audio files by assigning a key on the user's input device to each menu option. | 0.5 |
7,533,812 | 17 | 18 | 17. A method of executing an RFID process within an RFID architecture comprising: employing a reader application markup language (RAML) schema that provides a portable format for setup and deployment of the RFID process; receiving RFID data related to the RFID architecture, the RFID architecture comprises a collection of RFD readers that form a sub-system that includes an RFID reader and an RFID tag; and generating the RAML schema based at least upon the received RFID data and comprising a sub-set definition and a process definition in order to provide a portable format in which the RFID process can be utilized to be setup and deployed, the process definition comprising a logical source that includes logical reader collection, an event policy, an event handler, and a write handler associated with the RFID process, the sub-system definition defining at least one of a server state or entities on which processes are built. | 17. A method of executing an RFID process within an RFID architecture comprising: employing a reader application markup language (RAML) schema that provides a portable format for setup and deployment of the RFID process; receiving RFID data related to the RFID architecture, the RFID architecture comprises a collection of RFD readers that form a sub-system that includes an RFID reader and an RFID tag; and generating the RAML schema based at least upon the received RFID data and comprising a sub-set definition and a process definition in order to provide a portable format in which the RFID process can be utilized to be setup and deployed, the process definition comprising a logical source that includes logical reader collection, an event policy, an event handler, and a write handler associated with the RFID process, the sub-system definition defining at least one of a server state or entities on which processes are built. 18. The method of claim 17 , the generating further comprises generating the sub-system definition to comprise the definition for entities in the server, the entities are independent of a process, and defining server state and entities on which processes are built. | 0.5 |
9,105,007 | 1 | 8 | 1. A computer-implemented document collaboration system for managing the input of reviewers connected over a network of computers, the document collaboration system comprising: a processor; and a memory coupled to the processor, the memory including instructions that, when executed by the processor, cause the processor to: store a master data file including a document having content created by an owner; create a hierarchical distribution file for tracking access to the document, the hierarchical distribution file including: first data identifying the owner of the document, second data identifying a first level reviewer designated by the owner, third data identifying a second level reviewer designated by the first level reviewer, and fourth data identifying an access level to a designated portion of the document for the first level reviewer, wherein the designated portion of the document is less than the entirety of the document; create a first data file associated with the first level reviewer comprising: first edit data reflecting a first edit made to the content of the document by the first level reviewer within the designated portion of the document, and first index data reflecting a first index to a location of the first edit in the document; and create a second data file associated with the second level reviewer comprising: second edit data reflecting a second edit made to the content of the document by the second level reviewer, and second index data reflecting a second index to a location of the second edit in the document; modify the first data file to include the second edit data and the second index data within the first data file in response to input reflecting that the first level reviewer accepts the second edit data, without modifying the master data file; modify the master data file to include the first edit data and the first index data in response to input reflecting that the owner accepts the first edit data; and modify the master data file to include the second edit data and the second index data incorporated within the first data file in response to input reflecting that the owner accepts the second edit data incorporated within the first data file. | 1. A computer-implemented document collaboration system for managing the input of reviewers connected over a network of computers, the document collaboration system comprising: a processor; and a memory coupled to the processor, the memory including instructions that, when executed by the processor, cause the processor to: store a master data file including a document having content created by an owner; create a hierarchical distribution file for tracking access to the document, the hierarchical distribution file including: first data identifying the owner of the document, second data identifying a first level reviewer designated by the owner, third data identifying a second level reviewer designated by the first level reviewer, and fourth data identifying an access level to a designated portion of the document for the first level reviewer, wherein the designated portion of the document is less than the entirety of the document; create a first data file associated with the first level reviewer comprising: first edit data reflecting a first edit made to the content of the document by the first level reviewer within the designated portion of the document, and first index data reflecting a first index to a location of the first edit in the document; and create a second data file associated with the second level reviewer comprising: second edit data reflecting a second edit made to the content of the document by the second level reviewer, and second index data reflecting a second index to a location of the second edit in the document; modify the first data file to include the second edit data and the second index data within the first data file in response to input reflecting that the first level reviewer accepts the second edit data, without modifying the master data file; modify the master data file to include the first edit data and the first index data in response to input reflecting that the owner accepts the first edit data; and modify the master data file to include the second edit data and the second index data incorporated within the first data file in response to input reflecting that the owner accepts the second edit data incorporated within the first data file. 8. The document collaboration system of claim 1 , wherein the processor transfers the owner's access rights to the document to another reviewer. | 0.64878 |
9,756,439 | 9 | 10 | 9. An output device for an audio file, comprising: a processor; and a memory for storing instructions executable by the processor; wherein the processor is configured to: acquire an audio file; detect a current value of a pre-specified parameter, wherein the pre-specified parameter comprises at least one of a ring tone setting parameter and an environmental noise parameter; and compare the current value of the pre-specified parameter with a preset condition, and output an object file corresponding to the current value of the pre-specified parameter based on a comparison result, the object file including the audio file or a text file converted from the audio file; wherein the processor is further configured to: detecting a ring volume value of the ring tone setting parameter; if the ring volume value is greater than a second threshold value, detect a noise value of the environmental noise parameter; if the detected noise value is smaller than or equal to a first threshold, output the audio file; and if the detected noise value is greater than the first threshold value, output the text file; and if the ring volume value is smaller than or equal to the second threshold value, output the text file. | 9. An output device for an audio file, comprising: a processor; and a memory for storing instructions executable by the processor; wherein the processor is configured to: acquire an audio file; detect a current value of a pre-specified parameter, wherein the pre-specified parameter comprises at least one of a ring tone setting parameter and an environmental noise parameter; and compare the current value of the pre-specified parameter with a preset condition, and output an object file corresponding to the current value of the pre-specified parameter based on a comparison result, the object file including the audio file or a text file converted from the audio file; wherein the processor is further configured to: detecting a ring volume value of the ring tone setting parameter; if the ring volume value is greater than a second threshold value, detect a noise value of the environmental noise parameter; if the detected noise value is smaller than or equal to a first threshold, output the audio file; and if the detected noise value is greater than the first threshold value, output the text file; and if the ring volume value is smaller than or equal to the second threshold value, output the text file. 10. The device of claim 9 , wherein the pre-specified parameter further comprises at least one of a mute setting parameter, a media playback parameter, and a setting parameter of an application acquiring the audio file. | 0.5 |
7,774,294 | 1 | 2 | 1. A computer-implemented user-interface method of selecting and presenting a collection of content items in which the presentation is ordered at least in part based on learning periodicities of user selections of content items, the method comprising: providing access to a set of content items, each content item having at least one associated descriptive term to describe the content item; receiving incremental input entered by the user for incrementally identifying desired content items; in response to the incremental input entered by the user, presenting a subset of content items to the user; receiving actions from the user resulting in the selection of content items from the subset; analyzing the descriptive terms associated with the selected content items to identify sets of actions resulting in the selection of similar content items, wherein similarity is determined by comparing the descriptive terms associated with any one of the selected content items with any of the previously selected content items; analyzing the date, day, and time of at least two of the individual selection actions of the sets of actions to learn periodicities of user actions resulting in the selections of similar content items, wherein the periodicity corresponding to a particular set of actions for selecting similar content items indicates the amount of time between the user actions of the set; associating the learned periodicities of the sets of actions resulting in the selection of similar content items with the corresponding descriptive terms associated with the similar content items that were selected; and in response to receiving subsequent incremental input entered by the user, selecting and ordering a collection of content items wherein content items associated with descriptive terms similar to the subsequent incremental input and associated with descriptive terms further associated with periodicities similar to the date, day, and time of the subsequent incremental input are presented on a display device as more relevant content. | 1. A computer-implemented user-interface method of selecting and presenting a collection of content items in which the presentation is ordered at least in part based on learning periodicities of user selections of content items, the method comprising: providing access to a set of content items, each content item having at least one associated descriptive term to describe the content item; receiving incremental input entered by the user for incrementally identifying desired content items; in response to the incremental input entered by the user, presenting a subset of content items to the user; receiving actions from the user resulting in the selection of content items from the subset; analyzing the descriptive terms associated with the selected content items to identify sets of actions resulting in the selection of similar content items, wherein similarity is determined by comparing the descriptive terms associated with any one of the selected content items with any of the previously selected content items; analyzing the date, day, and time of at least two of the individual selection actions of the sets of actions to learn periodicities of user actions resulting in the selections of similar content items, wherein the periodicity corresponding to a particular set of actions for selecting similar content items indicates the amount of time between the user actions of the set; associating the learned periodicities of the sets of actions resulting in the selection of similar content items with the corresponding descriptive terms associated with the similar content items that were selected; and in response to receiving subsequent incremental input entered by the user, selecting and ordering a collection of content items wherein content items associated with descriptive terms similar to the subsequent incremental input and associated with descriptive terms further associated with periodicities similar to the date, day, and time of the subsequent incremental input are presented on a display device as more relevant content. 2. The method of claim 1 , wherein the learned periodicity is about one day. | 0.948925 |
9,697,184 | 11 | 12 | 11. The method of claim 1 , wherein extracting position coordinates of a touch point formed by the touch operation on the user interface includes determining a central-point position of a contact area formed by the touch operation. | 11. The method of claim 1 , wherein extracting position coordinates of a touch point formed by the touch operation on the user interface includes determining a central-point position of a contact area formed by the touch operation. 12. The method of claim 11 , wherein the determining a precision of the touch operation with respect to the target hyperlink includes determining a distance between the central-point position and a center position of the target hyperlink. | 0.5 |
9,082,310 | 17 | 18 | 17. The method of claim 1 , further comprising: (e) automatically generating a first answer to the first question instance based on the first region definition in the first question instance and the data set. | 17. The method of claim 1 , further comprising: (e) automatically generating a first answer to the first question instance based on the first region definition in the first question instance and the data set. 18. The method of claim 17 , further comprising: (f) providing output to the user representing the first answer. | 0.877729 |
7,730,059 | 6 | 7 | 6. The method of claim 5 , wherein: creating the cube structure further comprises populating the cube structure with a plurality of measures, each measure being categorized by one or more dimensions of the cube, wherein each measure of the cube structure is based on documents classified by facets that correspond to the one or more dimensions categorizing the measure. | 6. The method of claim 5 , wherein: creating the cube structure further comprises populating the cube structure with a plurality of measures, each measure being categorized by one or more dimensions of the cube, wherein each measure of the cube structure is based on documents classified by facets that correspond to the one or more dimensions categorizing the measure. 7. The method of claim 6 , wherein outputting the multi-dimensional search interface comprises constructing a multi-dimensional search query on the cube structure to select measures for display in the multidimensional search interface, the selected measures being based on the documents that satisfy the query. | 0.5 |
9,042,923 | 6 | 10 | 6. A communication system comprising: machine memory or circuits comprising logic to expand a text message into a web page and to provide a link to the web page to a recipient device, the web page comprising image content representing a subject or verb of the text message; machine memory or circuits comprising logic to form a query for the image content from key words in the text message combined with key words for an emote in the text message; and a micro-payment accumulator comprising machine memory or circuits comprising logic to track value to content owners for use of the image content in the web page. | 6. A communication system comprising: machine memory or circuits comprising logic to expand a text message into a web page and to provide a link to the web page to a recipient device, the web page comprising image content representing a subject or verb of the text message; machine memory or circuits comprising logic to form a query for the image content from key words in the text message combined with key words for an emote in the text message; and a micro-payment accumulator comprising machine memory or circuits comprising logic to track value to content owners for use of the image content in the web page. 10. The communication system of claim 6 , further comprising: a layout generator comprising machine memory or circuits comprising logic to form a layout of the web page from a shape of a symbol in the text message. | 0.520179 |
9,002,715 | 6 | 8 | 6. The information processor according to claim 1 , further comprising: a cost calculating unit for calculating, as a cost value indicating user's labor required before executing a function, a difference between a time period in which the interface screen change key unit is continuously operated in the present operation and an average of elapsed time periods until the function execution key unit is operated in the past, which are determined from plural pieces of the past continuous operation information, by using the past continuous operation information which is recorded in the interface screen operation history recording unit and indicates the operation contents according to which the interface screen change key unit is continuously operated until the function execution key unit is operated and by using the current continuous operation information indicating operation contents according to which the interface screen change key unit is operated continuously without any operation of the function execution key unit up to now, wherein the priority recognition word setting unit, when the cost value calculated by the cost calculating unit is not less than the prescribed value, sets release so as to prevent the voice recognition of the word information corresponding to the function whose likelihood value, which is set by the likelihood value providing unit, is less than a prescribed value. | 6. The information processor according to claim 1 , further comprising: a cost calculating unit for calculating, as a cost value indicating user's labor required before executing a function, a difference between a time period in which the interface screen change key unit is continuously operated in the present operation and an average of elapsed time periods until the function execution key unit is operated in the past, which are determined from plural pieces of the past continuous operation information, by using the past continuous operation information which is recorded in the interface screen operation history recording unit and indicates the operation contents according to which the interface screen change key unit is continuously operated until the function execution key unit is operated and by using the current continuous operation information indicating operation contents according to which the interface screen change key unit is operated continuously without any operation of the function execution key unit up to now, wherein the priority recognition word setting unit, when the cost value calculated by the cost calculating unit is not less than the prescribed value, sets release so as to prevent the voice recognition of the word information corresponding to the function whose likelihood value, which is set by the likelihood value providing unit, is less than a prescribed value. 8. The information processor according to claim 6 , wherein the cost calculating unit weights the elapsed time periods until the function execution key unit is operated, which are determined from the past continuous operation information, by the likelihood values which are set to the functions of the function execution key unit, and calculates, as the cost value indicating user's labor required before executing the function, a difference between the time period in which the interface screen change key unit is continuously operated in the present operation and an average of the elapsed time periods which are derived from the plurality of pieces of the past continuous operation information and pass through the weighting. | 0.5 |
8,516,606 | 2 | 3 | 2. The computer-implemented method according to claim 1 , wherein the at least two character subsets are sent to the client in an animation file. | 2. The computer-implemented method according to claim 1 , wherein the at least two character subsets are sent to the client in an animation file. 3. The computer-implemented method according to claim 2 , wherein the animation file comprises at least one of a graphics interchange format file, a flash file, or animated joint photographic experts group file. | 0.5 |
8,660,372 | 19 | 20 | 19. The method of claim 12 , further comprising the computer system: receiving a plurality of uploaded one or more image frames from a plurality of users via a web interface; and automatically determining quality for the plurality of uploaded one or more image frames. | 19. The method of claim 12 , further comprising the computer system: receiving a plurality of uploaded one or more image frames from a plurality of users via a web interface; and automatically determining quality for the plurality of uploaded one or more image frames. 20. The method of claim 19 , further comprising the computer system, in response to automatically determining quality for each of the plurality of uploaded one or more image frames, automatically performing one or more actions on those one or more image frames. | 0.5 |
10,096,044 | 15 | 16 | 15. A computer-readable storage device having instructions stored which, when executed by a computing device, result in the computing device performing operations comprising: identifying a key phrase in text based on an emotion of a user, the user being associated with the text; receiving data from a user profile, the data describing habits of the user; and transmitting, via a network and to a user device, an advertisement related to the key phrase and the data. | 15. A computer-readable storage device having instructions stored which, when executed by a computing device, result in the computing device performing operations comprising: identifying a key phrase in text based on an emotion of a user, the user being associated with the text; receiving data from a user profile, the data describing habits of the user; and transmitting, via a network and to a user device, an advertisement related to the key phrase and the data. 16. The computer-readable storage device of claim 15 , having additional instructions stored which, when executed by the computing device, result in an operation comprising: generating the text based on speech from the user, wherein the speech is received via passive monitoring of the speech of the user. | 0.523438 |
8,918,796 | 1 | 3 | 1. A computer implemented method comprising: selecting a first software program and a second software program by placing a first icon on a graphical display screen in a prespecified relationship with a second icon on said display screen; extracting first metadata from at least one database, wherein the first metadata describe a first set of constraints that apply to installation of the first software program on a data processing system; extracting second metadata from the at least one database, wherein the second metadata describe a second set of constraints that apply to installation of the second software program on the data processing system; generating a third set of constraints from the first metadata and the second metadata, wherein the third set of constraints comprise an intersection of the first set of constraints and the second set of constraints; determining whether installation of both the first program and the second program on the data processing system violates any constraint contained in the third set of constraints; and storing the third set of constraints in a tooling mechanism configured to perform extracting the first metadata, extracting the second metadata, generating the third set of constraints, and determining whether installation violates any constraint. | 1. A computer implemented method comprising: selecting a first software program and a second software program by placing a first icon on a graphical display screen in a prespecified relationship with a second icon on said display screen; extracting first metadata from at least one database, wherein the first metadata describe a first set of constraints that apply to installation of the first software program on a data processing system; extracting second metadata from the at least one database, wherein the second metadata describe a second set of constraints that apply to installation of the second software program on the data processing system; generating a third set of constraints from the first metadata and the second metadata, wherein the third set of constraints comprise an intersection of the first set of constraints and the second set of constraints; determining whether installation of both the first program and the second program on the data processing system violates any constraint contained in the third set of constraints; and storing the third set of constraints in a tooling mechanism configured to perform extracting the first metadata, extracting the second metadata, generating the third set of constraints, and determining whether installation violates any constraint. 3. The method of claim 1 further comprising: transforming the first metadata and the second metadata into a constraint language selected from a group of languages consisting of: unified modeling language (UML), object constraint language (OCL), and JAVA. | 0.5 |
8,719,176 | 6 | 13 | 6. A computer-implemented method, said computer-implemented method comprising the following: receiving at a first computer system, via a computer network, first information, said first computer system comprising at least a processor and a memory; registering a first account; receiving, via said computer network, second information, said second information indicating or comprising at least a first approval, said first approval pertaining to said first information; determining, by computer, a first measure of popularity, said first measure of popularity pertaining to said first information and being based at least in part on said second information; at least partly causing, by computer, display of first indicia, said first indicia indicating said first measure of popularity; and promoting, by computer, said first information from a first status to a second status, said second status being different from said first status, the promoting said first information from said first status to said second status being performed at least partly according to said first measure of popularity; wherein: said first account is associated with at least a first real-time newsfeed or ticker for conveying a plurality of real-time news items, said plurality of real-time news items comprising at least a first news item, said first news item being related to said first account. | 6. A computer-implemented method, said computer-implemented method comprising the following: receiving at a first computer system, via a computer network, first information, said first computer system comprising at least a processor and a memory; registering a first account; receiving, via said computer network, second information, said second information indicating or comprising at least a first approval, said first approval pertaining to said first information; determining, by computer, a first measure of popularity, said first measure of popularity pertaining to said first information and being based at least in part on said second information; at least partly causing, by computer, display of first indicia, said first indicia indicating said first measure of popularity; and promoting, by computer, said first information from a first status to a second status, said second status being different from said first status, the promoting said first information from said first status to said second status being performed at least partly according to said first measure of popularity; wherein: said first account is associated with at least a first real-time newsfeed or ticker for conveying a plurality of real-time news items, said plurality of real-time news items comprising at least a first news item, said first news item being related to said first account. 13. The method in claim 6 additionally comprising: receiving, from a first phone, a first query; organizing, by computer, a plurality of results in response to said first query; and providing, to said phone, at least some of said plurality of results. | 0.797907 |
7,904,080 | 24 | 26 | 24. A method according to claim 22 , wherein said GUI comprises a map having at least one clickable icon, said icon providing information on a result of said query from said statistic and, when clicked, the GUI providing information on data from which said statistic is computed. | 24. A method according to claim 22 , wherein said GUI comprises a map having at least one clickable icon, said icon providing information on a result of said query from said statistic and, when clicked, the GUI providing information on data from which said statistic is computed. 26. A method according to claim 24 , wherein said icon, when repeatedly clicked, enables drill down to individual traffic messages captured from said network. | 0.757669 |
9,703,872 | 1 | 2 | 1. A method of automatically modifying text displayed on a graphical user interface by detecting offensive words in a string of words transmitted over a computer network, comprising: receiving and storing in a computer database, using one or more processors, a plurality of offensive words, wherein each respective offensive word in the plurality of offensive words is associated with a severity score identifying the offensiveness of the respective word; receiving a string of words, using the one or more processors, wherein a candidate word is selected from the string of words; calculating, for each respective offensive word in the plurality of offensive words, using the one or more processors, a distance between the candidate word and the respective offensive word, the distance between the candidate word and the respective offensive word being a value on a scale having more than two possible values; calculating a plurality of offensiveness scores for the candidate word using the one or more processors, each offensiveness score in the plurality of offensiveness scores based upon (i) the calculated distance between the candidate word and an offensive word in the plurality of offensive words and (ii) the severity score of the offensive word, wherein a particular offensiveness score is based on a product of two terms, a first of the two terms being based on the calculated distance between the candidate word and a particular offensive word, and a second of the two terms being based on the severity score of the particular offensive word; determining, using the one or more processors, whether the candidate word is an offender word based on whether the highest offensiveness score in the plurality of offensiveness scores for the candidate word exceeds an offensiveness threshold value; and when the candidate word is determined to be an offender word, adjusting the candidate word, as stored in a computer-readable memory, prior to display of the adjusted candidate word on a graphical user interface. | 1. A method of automatically modifying text displayed on a graphical user interface by detecting offensive words in a string of words transmitted over a computer network, comprising: receiving and storing in a computer database, using one or more processors, a plurality of offensive words, wherein each respective offensive word in the plurality of offensive words is associated with a severity score identifying the offensiveness of the respective word; receiving a string of words, using the one or more processors, wherein a candidate word is selected from the string of words; calculating, for each respective offensive word in the plurality of offensive words, using the one or more processors, a distance between the candidate word and the respective offensive word, the distance between the candidate word and the respective offensive word being a value on a scale having more than two possible values; calculating a plurality of offensiveness scores for the candidate word using the one or more processors, each offensiveness score in the plurality of offensiveness scores based upon (i) the calculated distance between the candidate word and an offensive word in the plurality of offensive words and (ii) the severity score of the offensive word, wherein a particular offensiveness score is based on a product of two terms, a first of the two terms being based on the calculated distance between the candidate word and a particular offensive word, and a second of the two terms being based on the severity score of the particular offensive word; determining, using the one or more processors, whether the candidate word is an offender word based on whether the highest offensiveness score in the plurality of offensiveness scores for the candidate word exceeds an offensiveness threshold value; and when the candidate word is determined to be an offender word, adjusting the candidate word, as stored in a computer-readable memory, prior to display of the adjusted candidate word on a graphical user interface. 2. The method of claim 1 , wherein each word in the plurality of offensive words and each word in the string of words comprises an abbreviation, a single word, a phrase, or a sentence. | 0.780952 |
7,810,021 | 38 | 40 | 38. The apparatus of claim 21 wherein the set of utility programs and scripts operating within the computer for converting the set of text files to hypertext files further comprises: one or more link determination programs for constructing a set of terms and objects for which hypertext links are to be installed in a text file; a link installation program for inserting hypertext links into a text file to convert it to a hypertext file; a Web page creation program for converting a hypertext file to a Web page; one or more literary macramé compilation scripts for invoking the link installation program and the Web page creation program for all text files to construct a complete linked literary macramé; and one or more manual scene link establishment scripts for enabling a user to link two scenes together using hypertext links. | 38. The apparatus of claim 21 wherein the set of utility programs and scripts operating within the computer for converting the set of text files to hypertext files further comprises: one or more link determination programs for constructing a set of terms and objects for which hypertext links are to be installed in a text file; a link installation program for inserting hypertext links into a text file to convert it to a hypertext file; a Web page creation program for converting a hypertext file to a Web page; one or more literary macramé compilation scripts for invoking the link installation program and the Web page creation program for all text files to construct a complete linked literary macramé; and one or more manual scene link establishment scripts for enabling a user to link two scenes together using hypertext links. 40. The apparatus of claim 38 wherein the set of terms and objects for which hypertext links are to be installed in a text file comprises one or more records each further comprising: a glossary or reference term to be linked from a referring location in the text file; a file reference identifying the glossary or reference in which the glossary term appears; a glossary term anchor identifier specifying the location in the glossary at which the glossary term appears; a term corresponding to the glossary or reference term to be displayed in the referring location; a target window in which the glossary or reference term appears when linked; and a class of reference defining the appearance of the reference in the referring location. | 0.5 |
9,406,030 | 6 | 14 | 6. A computerized method for electronic document classification, the method comprising: providing training documents sorted into a plurality of classes; using a processor to perform linear programming including selecting input values which maximize an output value, given specific constraints on the input values, wherein the output value maximized is a difference between: a. a first estimated probability that a document instance will be correctly classified, by a given classifier corresponding to given input values, as belonging to its own class, and b. a second estimated probability that the document instance will be classified, by the given classifier, as belonging to a class other than its own class; and classifying electronic document instances into the plurality of classes, using at least one preferred classifier corresponding to the input values selected by said linear programming including storing an indication of said classifying in computer memory, wherein said input values comprise weights used to compute linear combinations of functions of features derived from individual electronic document instances. | 6. A computerized method for electronic document classification, the method comprising: providing training documents sorted into a plurality of classes; using a processor to perform linear programming including selecting input values which maximize an output value, given specific constraints on the input values, wherein the output value maximized is a difference between: a. a first estimated probability that a document instance will be correctly classified, by a given classifier corresponding to given input values, as belonging to its own class, and b. a second estimated probability that the document instance will be classified, by the given classifier, as belonging to a class other than its own class; and classifying electronic document instances into the plurality of classes, using at least one preferred classifier corresponding to the input values selected by said linear programming including storing an indication of said classifying in computer memory, wherein said input values comprise weights used to compute linear combinations of functions of features derived from individual electronic document instances. 14. A method according to claim 6 , wherein said functions include probabilities that an individual document instance belongs to a given class given that the individual document instance is characterized by a particular feature derived from individual electronic document instances. | 0.5 |
7,958,067 | 12 | 16 | 12. A method for cleaning up data, comprising: receiving a plurality of labeled data items; selecting subsets of the data items for each of a plurality of categories; setting an uncertainty for the data items in each subset to about zero; setting an uncertainty for the data items not in the subsets to a predefined value that is not about zero; training a transductive classifier through iterative calculation using the uncertainties, the data items in the subsets, and the data items not in the subsets as training examples; applying the trained classifier to each of the labeled data items to classify each of the data items; and outputting a classification of the input data items, or derivative thereof, to at least one of a user, another system, and another process. | 12. A method for cleaning up data, comprising: receiving a plurality of labeled data items; selecting subsets of the data items for each of a plurality of categories; setting an uncertainty for the data items in each subset to about zero; setting an uncertainty for the data items not in the subsets to a predefined value that is not about zero; training a transductive classifier through iterative calculation using the uncertainties, the data items in the subsets, and the data items not in the subsets as training examples; applying the trained classifier to each of the labeled data items to classify each of the data items; and outputting a classification of the input data items, or derivative thereof, to at least one of a user, another system, and another process. 16. The method of claim 12 , wherein identifiers of data items having a confidence level below a predefined threshold after classification thereof are output to a user. | 0.5 |
9,514,222 | 1 | 3 | 1. A method for configuring a computer system to provide a set of selectable topic names on an interface for providing access to stored electronic resources by topic name, at least some of which are assigned to named storage sets in a folder structure, the method comprising: (1) determining a topic framework for providing the set of topic names for providing access to the electronic resources by topic name on the interface, the topic framework storing topic names, associations between each of the stored electronic resources and one or more topic names, and associations between topic names by: (i) determining the topic names for the topic framework from the names assigned to storage sets and the attributes of individual electronic resources by: generating one or more topic names from the names assigned to storage sets; and generating one or more topic names from attributes of individual electronic resources; and (ii) forming the associations between each of the stored electronic resources and one or more topic names by: associating electronic resources assigned to a storage set with one or more topic names which were generated from the name of the storage set; and associating electronic resources having an attribute or attributes with one or more topic names which were generated from the respective attribute or attributes of the electronic resources; (iii) associating one or more topic names with one or more other topic names by: generating associations between topic names from the relationships within the folder structure between the respective storage sets from which the topic names were generated; (2) storing the topic framework to provide the set of topic names for providing access to the electronic resources by topic name on the interface, wherein the topic framework stores the set of topic names, associations between each of the stored electronic resources and one or more topic names, and associations between topic names; and (3) using the topic framework to configure the computer system to present the interface through which: (i) a list of topic names is presented through which one or more topic names of the topic framework are selectable; (ii) when a topic name associated by the topic framework with one or more other topic names is selected, at least a list of the one or more other topic names is presented through which the one or more other topic names are selectable; and (iii) a group of stored electronic resources associated with a selected one or more topic names is presented so that one or more of the group of electronic resources can be selected for access. | 1. A method for configuring a computer system to provide a set of selectable topic names on an interface for providing access to stored electronic resources by topic name, at least some of which are assigned to named storage sets in a folder structure, the method comprising: (1) determining a topic framework for providing the set of topic names for providing access to the electronic resources by topic name on the interface, the topic framework storing topic names, associations between each of the stored electronic resources and one or more topic names, and associations between topic names by: (i) determining the topic names for the topic framework from the names assigned to storage sets and the attributes of individual electronic resources by: generating one or more topic names from the names assigned to storage sets; and generating one or more topic names from attributes of individual electronic resources; and (ii) forming the associations between each of the stored electronic resources and one or more topic names by: associating electronic resources assigned to a storage set with one or more topic names which were generated from the name of the storage set; and associating electronic resources having an attribute or attributes with one or more topic names which were generated from the respective attribute or attributes of the electronic resources; (iii) associating one or more topic names with one or more other topic names by: generating associations between topic names from the relationships within the folder structure between the respective storage sets from which the topic names were generated; (2) storing the topic framework to provide the set of topic names for providing access to the electronic resources by topic name on the interface, wherein the topic framework stores the set of topic names, associations between each of the stored electronic resources and one or more topic names, and associations between topic names; and (3) using the topic framework to configure the computer system to present the interface through which: (i) a list of topic names is presented through which one or more topic names of the topic framework are selectable; (ii) when a topic name associated by the topic framework with one or more other topic names is selected, at least a list of the one or more other topic names is presented through which the one or more other topic names are selectable; and (iii) a group of stored electronic resources associated with a selected one or more topic names is presented so that one or more of the group of electronic resources can be selected for access. 3. A method according to claim 1 , wherein generating one or more topic names from the attributes of individual electronic resources comprises: selecting a word as a topic name on the basis that the word occurs as an attribute for an electronic resource more than once. | 0.856915 |
7,730,059 | 20 | 22 | 20. The computer readable storage medium of claim 19 , wherein the instructions for constructing a facet hierarchy include instructions for constructing a facet hierarchy based on the metadata describing the hierarchical relationship associated with the documents that satisfy the query. | 20. The computer readable storage medium of claim 19 , wherein the instructions for constructing a facet hierarchy include instructions for constructing a facet hierarchy based on the metadata describing the hierarchical relationship associated with the documents that satisfy the query. 22. The computer readable storage medium of claim 20 , wherein: the facet hierarchy includes a plurality of facets; and the instructions for creating the cube structure comprise instructions for creating dimensions for the cube structure based on the plurality of facets. | 0.5 |
8,195,467 | 1 | 10 | 1. A wireless electronic device comprising: a microphone for receiving a speech input; a speech recognizer coupled to the microphone to receive the speech input; a memory, the memory comprising a stored resource access number; and a Bluetooth wireless transceiver for sending information from the electronic device to one or more other electronic devices using a Bluetooth protocol, wherein said electronic device is a Bluetooth headset, wherein the speech recognizer is configured to recognize a first spoken command word, and wherein if the first command word is recognized in the speech input, then the speech recognizer generates a corresponding first command result, wherein if the first command result matches a predefined criteria, then the electronic device automatically accesses the resource access number from memory and sends the resource access number and an externally executed command through said transceiver to a second electronic device, said second electronic device comprising a cellular phone, and wherein the externally executed command is received by the second electronic device and executed on the second electronic device, and in accordance therewith, the second electronic device uses the resource access number to establish a communication channel between said second electronic device and at least one remote device, and wherein a user provides second speech input to said microphone, and wherein the second speech input is sent from the Bluetooth headset to the second electronic device and through the communication channel to the at least one remote device, and the at least one remote device performs speech recognition on the second speech input. | 1. A wireless electronic device comprising: a microphone for receiving a speech input; a speech recognizer coupled to the microphone to receive the speech input; a memory, the memory comprising a stored resource access number; and a Bluetooth wireless transceiver for sending information from the electronic device to one or more other electronic devices using a Bluetooth protocol, wherein said electronic device is a Bluetooth headset, wherein the speech recognizer is configured to recognize a first spoken command word, and wherein if the first command word is recognized in the speech input, then the speech recognizer generates a corresponding first command result, wherein if the first command result matches a predefined criteria, then the electronic device automatically accesses the resource access number from memory and sends the resource access number and an externally executed command through said transceiver to a second electronic device, said second electronic device comprising a cellular phone, and wherein the externally executed command is received by the second electronic device and executed on the second electronic device, and in accordance therewith, the second electronic device uses the resource access number to establish a communication channel between said second electronic device and at least one remote device, and wherein a user provides second speech input to said microphone, and wherein the second speech input is sent from the Bluetooth headset to the second electronic device and through the communication channel to the at least one remote device, and the at least one remote device performs speech recognition on the second speech input. 10. The device of claim 1 wherein the resource access number is a URL. | 0.9 |
9,704,130 | 18 | 19 | 18. The computer program product of claim 16 , wherein the computer readable program code further comprises: computer readable program code for creating the first graphical map from a first topic map; computer readable program code for creating the second graphical map from a second topic map; computer readable program code for creating a combined topic map view comprising a representation of a subset of the instance data of the enterprise industry model and a representation of a subset of the instance data of the legacy model, wherein the combined topic map view indicates a relationship between the first one of the first nodes and the first one of the second nodes. | 18. The computer program product of claim 16 , wherein the computer readable program code further comprises: computer readable program code for creating the first graphical map from a first topic map; computer readable program code for creating the second graphical map from a second topic map; computer readable program code for creating a combined topic map view comprising a representation of a subset of the instance data of the enterprise industry model and a representation of a subset of the instance data of the legacy model, wherein the combined topic map view indicates a relationship between the first one of the first nodes and the first one of the second nodes. 19. The computer program product of claim 18 , wherein the computer readable program code further comprising: computer readable program code for applying a set of inference rules against the representation of enterprise industry model and the representation of legacy model by: examining tags associated with the first one of the first nodes and tags associated with the first one of the second nodes; determining whether the tags associated with the first one of the first nodes match any of the tags associated with the first one of the second nodes; responsive to determining a match, creating the relationship between the first one of the first nodes and the first one of the second nodes; and assigning the probability score to the relationship. | 0.5 |
8,316,030 | 9 | 11 | 9. A method of operating a computerized document search system where information is matched against a database containing documents in response to user queries, comprising the steps of: (a) receiving a query identifying a source document that has information content related to the documents within the database; (b) automatically detecting at least one important word within the source document identified as a SearchWord wherein the SearchWord is selected in part by using a WordRatio of the SearchWord related to a topic area and a number of topic areas that contain the SearchWord; (c) processing the documents in the database in which an importance value of the at least one important word within the source document is related to the WordRatio and at least one value selected from a group of values consisting of: a value defined for the at least one important word related to a document section that occurs in a document being processed from the processed documents; a value defined for the at least one important word in at least one classification associated with the document being processed; a value defined for the at least one important word in a document type that applies to the document being processed; a value defined for the at least one important word across multiple document classifications; and a value based on statistical occurrence of the at least one important word across at least two different documents; (d) generating a score for the processed document based partly on the value of the SearchWord in the processed document; creating a document list having the processed document identified that is related to the source document and an indication of a quality of match between the source document and a related document, and using, by a Presentation Manager, the document list to show identity of the processed document from the document list to the user of the user queries. | 9. A method of operating a computerized document search system where information is matched against a database containing documents in response to user queries, comprising the steps of: (a) receiving a query identifying a source document that has information content related to the documents within the database; (b) automatically detecting at least one important word within the source document identified as a SearchWord wherein the SearchWord is selected in part by using a WordRatio of the SearchWord related to a topic area and a number of topic areas that contain the SearchWord; (c) processing the documents in the database in which an importance value of the at least one important word within the source document is related to the WordRatio and at least one value selected from a group of values consisting of: a value defined for the at least one important word related to a document section that occurs in a document being processed from the processed documents; a value defined for the at least one important word in at least one classification associated with the document being processed; a value defined for the at least one important word in a document type that applies to the document being processed; a value defined for the at least one important word across multiple document classifications; and a value based on statistical occurrence of the at least one important word across at least two different documents; (d) generating a score for the processed document based partly on the value of the SearchWord in the processed document; creating a document list having the processed document identified that is related to the source document and an indication of a quality of match between the source document and a related document, and using, by a Presentation Manager, the document list to show identity of the processed document from the document list to the user of the user queries. 11. The method of claim 9 , further comprising the step of identifying at least one undefined acronym to be a qualified acronym derived from other words present within the document. | 0.5 |
10,089,640 | 12 | 16 | 12. The system of claim 11 wherein said instructions for analyzing said transaction data with respect to said spatio-temporal behavioral patterns are based on a representation of any parking episode via a set of heterogeneous features by transforming said transaction data into angular variables and incorporating sine and cosine components thereof in feature vectors. | 12. The system of claim 11 wherein said instructions for analyzing said transaction data with respect to said spatio-temporal behavioral patterns are based on a representation of any parking episode via a set of heterogeneous features by transforming said transaction data into angular variables and incorporating sine and cosine components thereof in feature vectors. 16. The system of claim 12 wherein said instructions for analyzing said transaction data with respect to said spatio-temporal behavioral patterns are based on an interpretation of said spatio-temporal behavioral patterns wherein said spatio-temporal behavioral patterns include temporal variables comprising circular variables, wherein each circular variable among said circular variables are decomposed into two components, wherein said two components are used for clustering by said clustering module. | 0.5 |
8,056,013 | 6 | 8 | 6. A method for arranging a set of graphic assemblies within an area, comprising: establishing at least one candidate tree having at least one internal node, and at least one terminal node emanating from an internal node, wherein each terminal node is associated with a presentation of a graphic assembly; determining a set of path lengths through each candidate tree; comparing a fixed distance term for each path length to a size of the area; discarding candidate trees where one or more of the fixed distance terms is greater than the size of the area; computing a score for each remaining candidate tree; selecting the candidate tree having a best score; and arranging the set of graphic assemblies within the area in accordance with the selected candidate tree. | 6. A method for arranging a set of graphic assemblies within an area, comprising: establishing at least one candidate tree having at least one internal node, and at least one terminal node emanating from an internal node, wherein each terminal node is associated with a presentation of a graphic assembly; determining a set of path lengths through each candidate tree; comparing a fixed distance term for each path length to a size of the area; discarding candidate trees where one or more of the fixed distance terms is greater than the size of the area; computing a score for each remaining candidate tree; selecting the candidate tree having a best score; and arranging the set of graphic assemblies within the area in accordance with the selected candidate tree. 8. The method of claim 6 , wherein each of the graphic assemblies comprise one or more graphic elements, and wherein each graphic element is one of a fixed area graphic element and a variable-area graphic element. | 0.52027 |
8,214,354 | 29 | 31 | 29. Apparatus for enforcing a referential integrity constraint between a constraint set and a constrained object in a relational database management system, the constraint set and the constrained object having values that are terms of an ontology, the relational database management system being implemented in a workstation having a processor and a storage device to which the processor has access, and the apparatus comprising: the storage device having an association between the constrained object and an ontology query, wherein the ontology query returns a set of terms of the ontology, the returned terms being the constraint set to be used to define the referential integrity constraint, wherein different constraint sets having different sets of terms can be derived by querying the same ontology, the constrained object comprising a constrained column that is defined in the relational database management system; the set of terms associated with the constrained object is a term object with a column, values in the column being the set of terms; and a referential integrity constraint for the constrained column which references the column in the term object; and the processor for executing a constraint enforcer in the relational database management system which, when an operation in the relational database management system adds a value to the constrained object, permits the operation only if the added value is a value belonging to the constraint set, and when a modification is performed on the ontology in the relational database management system that results in a different set of terms being returned by the ontology query, altering one or more values in the constrained object that are not contained in the different set of terms. | 29. Apparatus for enforcing a referential integrity constraint between a constraint set and a constrained object in a relational database management system, the constraint set and the constrained object having values that are terms of an ontology, the relational database management system being implemented in a workstation having a processor and a storage device to which the processor has access, and the apparatus comprising: the storage device having an association between the constrained object and an ontology query, wherein the ontology query returns a set of terms of the ontology, the returned terms being the constraint set to be used to define the referential integrity constraint, wherein different constraint sets having different sets of terms can be derived by querying the same ontology, the constrained object comprising a constrained column that is defined in the relational database management system; the set of terms associated with the constrained object is a term object with a column, values in the column being the set of terms; and a referential integrity constraint for the constrained column which references the column in the term object; and the processor for executing a constraint enforcer in the relational database management system which, when an operation in the relational database management system adds a value to the constrained object, permits the operation only if the added value is a value belonging to the constraint set, and when a modification is performed on the ontology in the relational database management system that results in a different set of terms being returned by the ontology query, altering one or more values in the constrained object that are not contained in the different set of terms. 31. The apparatus set forth in claim 29 wherein the term object comprises a materialized view. | 0.857576 |
7,810,029 | 17 | 19 | 17. A system for identifying relationships between text documents and structured variables pertaining to said text documents, comprising: an input device for inputting text documents; a processor for: forming categories of said text documents; counting occurrences of said structured variables, categories and combinations of structured variables and categories; calculating probabilities of occurrence of said combinations of structured variables and categories; and identifying a relationship between a structured variable of said structured variables and text documents included in a category of said categories based on a probability of occurrence of a combination of said structured variable and said category; and a display, for displaying said probabilities. | 17. A system for identifying relationships between text documents and structured variables pertaining to said text documents, comprising: an input device for inputting text documents; a processor for: forming categories of said text documents; counting occurrences of said structured variables, categories and combinations of structured variables and categories; calculating probabilities of occurrence of said combinations of structured variables and categories; and identifying a relationship between a structured variable of said structured variables and text documents included in a category of said categories based on a probability of occurrence of a combination of said structured variable and said category; and a display, for displaying said probabilities. 19. The system according to claim 17 , wherein said structured variables comprise predetermined time intervals. | 0.801075 |
9,251,225 | 1 | 10 | 1. A method for processing data in one or more data storage systems, the method including: receiving mapping information that specifies one or more attributes of one or more destination entities in terms of one or more attributes of one or more source entities, at least some of the one or more source entities corresponding to respective sets of records in the one or more data storage systems; and processing the mapping information to generate a procedural specification for computing values corresponding to at least some of the one or more attributes of one or more destination entities, the processing including generating a plurality of collections of nodes, each collection including a first node representing a first relational expression associated with an attribute specified by the mapping information, and at least some collections forming a directed acyclic graph that includes links to one or more other nodes representing respective relational expressions associated with at least one attribute of at least one source entity referenced by a relational expression of a node in the directed acyclic graph, and merging at least two of the collections with each other to form a third collection based on comparing relational expressions of nodes being merged. | 1. A method for processing data in one or more data storage systems, the method including: receiving mapping information that specifies one or more attributes of one or more destination entities in terms of one or more attributes of one or more source entities, at least some of the one or more source entities corresponding to respective sets of records in the one or more data storage systems; and processing the mapping information to generate a procedural specification for computing values corresponding to at least some of the one or more attributes of one or more destination entities, the processing including generating a plurality of collections of nodes, each collection including a first node representing a first relational expression associated with an attribute specified by the mapping information, and at least some collections forming a directed acyclic graph that includes links to one or more other nodes representing respective relational expressions associated with at least one attribute of at least one source entity referenced by a relational expression of a node in the directed acyclic graph, and merging at least two of the collections with each other to form a third collection based on comparing relational expressions of nodes being merged. 10. The method of claim 1 , wherein generating the procedural specification includes generating a dataflow graph from the third collection, the dataflow graph including components configured to perform operations corresponding to relational expressions in respective nodes of the third collection, and links representing flows of the records between output and input ports of components. | 0.5 |
7,478,192 | 15 | 16 | 15. An associative memory system according to claim 4 wherein the query system comprises: an entity query system that is configured to query the network of entity associative memory networks and the network of feedback associative memory networks to imagine associations of entities and user-task positive and/or negative evaluations in response to user queries; a document query system that is configured to query the network of document associative memory networks and the network of feedback associative memory networks to imagine associations of documents and user-task positive and/or negative evaluations in response to user queries; and a community query system that is configured to query the network of community associative memory networks to imagine associations of other user-tasks in response to user queries. | 15. An associative memory system according to claim 4 wherein the query system comprises: an entity query system that is configured to query the network of entity associative memory networks and the network of feedback associative memory networks to imagine associations of entities and user-task positive and/or negative evaluations in response to user queries; a document query system that is configured to query the network of document associative memory networks and the network of feedback associative memory networks to imagine associations of documents and user-task positive and/or negative evaluations in response to user queries; and a community query system that is configured to query the network of community associative memory networks to imagine associations of other user-tasks in response to user queries. 16. An associative memory system according to claim 15 wherein the processing system further comprises: a task input system that is responsive to user queries and is configured to produce user-task IDs and query data therefrom; a parser that is responsive to the task input system and is configured to extract entities from the query data; and a context generator that is responsive to the parser and is configured to identify observer entities and observed entities from the entities that are extracted and to provide the observer entities and observed entities to the entity query system, the document query system and the community query system. | 0.5 |
9,601,113 | 14 | 23 | 14. A computing device, comprising: at least one verbal input interface; at least one non-verbal input interface being selected from the group of: a kinetic input interface, an inertial input interface, a perceptual input interface, a touch input interface, a graphical user interface, and a sensor input interface; at least one processor in communication with the at least one verbal input interface and the at least one non-verbal input interface, the at least one processor being configured to: receive verbal input using the verbal input interface; receive, concurrently with at least part of the verbal input, at least one secondary input using the at least one non-verbal input interface; identify one or more target objects from the at least one secondary input; recognize text from the received verbal input; generate an interaction object, the interaction object comprising a natural language expression having references to the one or more identified target objects identified from the at least one secondary input, the references being embedded within the recognized text, the generation of the interaction object comprising identification of at least one attribute associated with each of the one or more identified target objects or at least one operation associated with each of the one or more identified target objects; process the interaction object to identify at least one operation to be executed on at least one of the one or more identified target objects; and execute the operation on the at least one of the one or more identified target objects. | 14. A computing device, comprising: at least one verbal input interface; at least one non-verbal input interface being selected from the group of: a kinetic input interface, an inertial input interface, a perceptual input interface, a touch input interface, a graphical user interface, and a sensor input interface; at least one processor in communication with the at least one verbal input interface and the at least one non-verbal input interface, the at least one processor being configured to: receive verbal input using the verbal input interface; receive, concurrently with at least part of the verbal input, at least one secondary input using the at least one non-verbal input interface; identify one or more target objects from the at least one secondary input; recognize text from the received verbal input; generate an interaction object, the interaction object comprising a natural language expression having references to the one or more identified target objects identified from the at least one secondary input, the references being embedded within the recognized text, the generation of the interaction object comprising identification of at least one attribute associated with each of the one or more identified target objects or at least one operation associated with each of the one or more identified target objects; process the interaction object to identify at least one operation to be executed on at least one of the one or more identified target objects; and execute the operation on the at least one of the one or more identified target objects. 23. The computing device of claim 14 , wherein the interaction object comprises a plurality of operations to be executed on the at least one of the one or more identified target objects, and the at least one processor is further configured to: execute a first one of the plurality of operations on the at least one of the one or more identified target objects while buffering remaining ones of the plurality of operations; and sequentially execute the remaining ones of the plurality of operations after execution of the first one of the plurality of operations. | 0.505282 |
8,301,624 | 1 | 6 | 1. A method comprising: determining a set of item-item affinities between a first item and a first plurality of items from a set of user-item data; determining a first set of nearest neighbor items from the first plurality of items based in part on the set of item-item affinities; determining a set of user feature-item affinities between a second plurality of items and a set of user features; determining a second set of nearest neighbor items based at least in part on the set of user feature-item affinities; determining affinity weights for a set of candidate items, the set of candidate items to be determined at least in part on the first set of nearest neighbor items and the second set of nearest neighbor items; and presenting to a user as a recommendation a candidate item from the set of candidate items, the candidate item to be determined at least in part based on an affinity weight of the candidate item; wherein determining the set of item-item affinities between the first item and the first plurality of items comprises for each particular column of a user-item matrix, setting an item-item affinity between the first item and another item represented by the particular column equal to a cosine similarity between the particular column and a first column of the user-item matrix representing the first item; wherein said each particular column of the user-item matrix indicates multiple ratings that multiple users have given to an item represented by said each particular column; wherein determining the set of user feature-item affinities between the second plurality of items and the set of user features comprises performing least square regression relative to an equation involving both said user-item matrix and a user profile matrix that is separate from said user-item matrix; wherein each particular column of the user profile matrix corresponds to a different user feature of a plurality of user features; wherein all user features in said plurality of user features differ from all items represented by columns of said user-item matrix; wherein each particular row of said user profile matrix corresponds to a different user of a plurality of users; and wherein the method is performed by one or more computing devices programmed to be special purpose machines pursuant to program instructions. | 1. A method comprising: determining a set of item-item affinities between a first item and a first plurality of items from a set of user-item data; determining a first set of nearest neighbor items from the first plurality of items based in part on the set of item-item affinities; determining a set of user feature-item affinities between a second plurality of items and a set of user features; determining a second set of nearest neighbor items based at least in part on the set of user feature-item affinities; determining affinity weights for a set of candidate items, the set of candidate items to be determined at least in part on the first set of nearest neighbor items and the second set of nearest neighbor items; and presenting to a user as a recommendation a candidate item from the set of candidate items, the candidate item to be determined at least in part based on an affinity weight of the candidate item; wherein determining the set of item-item affinities between the first item and the first plurality of items comprises for each particular column of a user-item matrix, setting an item-item affinity between the first item and another item represented by the particular column equal to a cosine similarity between the particular column and a first column of the user-item matrix representing the first item; wherein said each particular column of the user-item matrix indicates multiple ratings that multiple users have given to an item represented by said each particular column; wherein determining the set of user feature-item affinities between the second plurality of items and the set of user features comprises performing least square regression relative to an equation involving both said user-item matrix and a user profile matrix that is separate from said user-item matrix; wherein each particular column of the user profile matrix corresponds to a different user feature of a plurality of user features; wherein all user features in said plurality of user features differ from all items represented by columns of said user-item matrix; wherein each particular row of said user profile matrix corresponds to a different user of a plurality of users; and wherein the method is performed by one or more computing devices programmed to be special purpose machines pursuant to program instructions. 6. The method of claim 1 , further comprising: recalculating a weighting of the first set of nearest neighbors items or the second set of nearest neighbor items. | 0.826882 |
8,874,428 | 16 | 20 | 16. A system for fast translation memory search, comprising: a candidate module configured to identify a plurality of hypothesis strings stored in a translation memory as candidates to match a query string in response to the input query string; a string length signature module configured to eliminate one or more candidates, using a processor, where string lengths between the candidates and the query string are at least a cutoff value representing a string edit distance; a lexical distribution signature module configured to eliminate one or more candidates where differences in word frequency distributions between the candidates and the query string are at least the cutoff value; a dynamic programming module configured to eliminate one or more candidates by employing a dynamic programming matrix where string edit distances between the candidates and the query string are at least the cutoff value; and an output including a number of remaining candidates as matches to the query string. | 16. A system for fast translation memory search, comprising: a candidate module configured to identify a plurality of hypothesis strings stored in a translation memory as candidates to match a query string in response to the input query string; a string length signature module configured to eliminate one or more candidates, using a processor, where string lengths between the candidates and the query string are at least a cutoff value representing a string edit distance; a lexical distribution signature module configured to eliminate one or more candidates where differences in word frequency distributions between the candidates and the query string are at least the cutoff value; a dynamic programming module configured to eliminate one or more candidates by employing a dynamic programming matrix where string edit distances between the candidates and the query string are at least the cutoff value; and an output including a number of remaining candidates as matches to the query string. 20. The system as recited in claim 16 , wherein the string length signature module is further configured to: for string lengths of at least a first length, eliminate one or more candidates where string lengths are at least a first cutoff value; and for string lengths less than the first length, eliminating one or more candidates where string lengths are at least a second cutoff value. | 0.507634 |
9,003,287 | 1 | 11 | 1. A computer-implemented method for interaction between a 3D animation and a corresponding script, the method comprising: displaying a user interface that includes at least a 3D animation area and a script area, the 3D animation area including (i) a 3D view area for creating and playing a 3D animation and (ii) a timeline area for visualizing actions by one or more 3D animation characters, the script area comprising one or more objects representing lines from a script having one or more script characters; receiving a first user input corresponding to a user selecting at least one of the objects from the script area for assignment to a location in the timeline area and placing the selected object in the 3D viewing area: identifying the location in the timeline area as corresponding to a current state of the 3D view area and placing the selected object at the location in the timeline area based on the identification; generating a timeline object at the location in response to the first user input, the timeline object corresponding to the selected object; and associating audio data with the generated timeline object, the audio data corresponding to a line represented by the selected object. | 1. A computer-implemented method for interaction between a 3D animation and a corresponding script, the method comprising: displaying a user interface that includes at least a 3D animation area and a script area, the 3D animation area including (i) a 3D view area for creating and playing a 3D animation and (ii) a timeline area for visualizing actions by one or more 3D animation characters, the script area comprising one or more objects representing lines from a script having one or more script characters; receiving a first user input corresponding to a user selecting at least one of the objects from the script area for assignment to a location in the timeline area and placing the selected object in the 3D viewing area: identifying the location in the timeline area as corresponding to a current state of the 3D view area and placing the selected object at the location in the timeline area based on the identification; generating a timeline object at the location in response to the first user input, the timeline object corresponding to the selected object; and associating audio data with the generated timeline object, the audio data corresponding to a line represented by the selected object. 11. The computer-implemented method of claim 1 , further comprising: receiving a second user input after generating the timeline object, the second user input selecting one of the timeline object and the object from the script area; and highlighting, based on the second user input, the other of the timeline object and the object. | 0.557487 |
10,158,663 | 1 | 5 | 1. A method of improving security incident responses for a computing environment comprising a plurality of computing assets, the method comprising: in a processing system, maintaining asset configuration data for the plurality of computing assets, the asset configuration data comprising characteristics for each of the one or more computing assets; in response to identifying a security incident in the computing environment, providing, for display, security incident information related to the security incident to an administrator associated with the computing environment; identifying a selection of a security action from the administrator; identifying one or more computing assets related to the security action; identifying configuration data for the one or more computing assets from the maintained asset configuration data; identifying one or more action procedures to support the selection based on the identified configuration data; and initiating implementation of the one or more action procedures in the one or more computing assets. | 1. A method of improving security incident responses for a computing environment comprising a plurality of computing assets, the method comprising: in a processing system, maintaining asset configuration data for the plurality of computing assets, the asset configuration data comprising characteristics for each of the one or more computing assets; in response to identifying a security incident in the computing environment, providing, for display, security incident information related to the security incident to an administrator associated with the computing environment; identifying a selection of a security action from the administrator; identifying one or more computing assets related to the security action; identifying configuration data for the one or more computing assets from the maintained asset configuration data; identifying one or more action procedures to support the selection based on the identified configuration data; and initiating implementation of the one or more action procedures in the one or more computing assets. 5. The method of claim 1 wherein identifying the selection of the security action comprises identifying the selection of the security action in a command language. | 0.746894 |
8,122,069 | 6 | 9 | 6. A tangible computer-readable storage medium having computer-readable program code embodied therein that causes a computer system to perform: building a context graph including text snippets and files with links between nodes indicating a strength of a contextual relationship; pairing the text snippets with the files where a link weight between a text snippet and a file is increased when the text snippet is in temporal proximity to an event on the file; and using the context graph to classify a file. | 6. A tangible computer-readable storage medium having computer-readable program code embodied therein that causes a computer system to perform: building a context graph including text snippets and files with links between nodes indicating a strength of a contextual relationship; pairing the text snippets with the files where a link weight between a text snippet and a file is increased when the text snippet is in temporal proximity to an event on the file; and using the context graph to classify a file. 9. The tangible computer-readable storage medium of claim 6 that causes the computer system to further perform: receiving a search request to locate a document; and using the context graph to locate the document, wherein the context graph is a bipartite graph. | 0.645777 |
7,873,228 | 2 | 5 | 2. The method of claim 1 , further comprising: forming a plurality of clusters, each cluster of the plurality of clusters including one or more similar scanned images; and creating the plurality of prototypes based on processing the one or more similar scanned images of the plurality of clusters. | 2. The method of claim 1 , further comprising: forming a plurality of clusters, each cluster of the plurality of clusters including one or more similar scanned images; and creating the plurality of prototypes based on processing the one or more similar scanned images of the plurality of clusters. 5. The method of claim 2 , further comprising labeling the plurality of prototypes as a type character or ligature using optical character recognition (OCR) data associated with the scanned document. | 0.786481 |
10,015,177 | 1 | 15 | 1. A method comprising: receiving, by a computer system, first event data indicative of computer network activity of a plurality of users and network devices in a computer network; generating, by the computer system, classification metadata for each of the network devices and users, based on the first event data, to indicate relevance in a network security context of each of the users and network devices; identifying, by the computer system, usage relationships between one or more of the users and one or more of the network devices, based on first event data; assigning, by the computer system, usage similarity scores to the network devices based on the identified usage relationships, the usage similarity scores being indicative of which of the network devices have been used by the same or similar group of users; receiving, by the computer system, second event data indicative of computer network activity of a particular user of the plurality of users; and detecting, by the computer system and in response to the second event data, an anomaly indicative that the particular user has interacted with a particular network device with which the particular user does not normally interact, based on the usage similarity scores and the classification metadata. | 1. A method comprising: receiving, by a computer system, first event data indicative of computer network activity of a plurality of users and network devices in a computer network; generating, by the computer system, classification metadata for each of the network devices and users, based on the first event data, to indicate relevance in a network security context of each of the users and network devices; identifying, by the computer system, usage relationships between one or more of the users and one or more of the network devices, based on first event data; assigning, by the computer system, usage similarity scores to the network devices based on the identified usage relationships, the usage similarity scores being indicative of which of the network devices have been used by the same or similar group of users; receiving, by the computer system, second event data indicative of computer network activity of a particular user of the plurality of users; and detecting, by the computer system and in response to the second event data, an anomaly indicative that the particular user has interacted with a particular network device with which the particular user does not normally interact, based on the usage similarity scores and the classification metadata. 15. The method of claim 1 , wherein said assigning usage similarity scores comprises: assigning usage similarity scores to the network devices based on relationships between the users and the network devices, such that particular network devices having multiple exclusive users interacting with only the particular network devices tend to have usage similarity scores that have differences less than a threshold value. | 0.791 |
8,255,790 | 8 | 9 | 8. A form customization system comprising: a processor; a database which stores a set of application user interface forms in binary format; and a form user interface modification engine implemented at least in part on the processor, the form user interface modification engine comprising: an export component that retrieves a first form of the set of application user interface forms from the database and generates a first extensible markup language (XML) format form to be used in form customization converting the first form from binary format to XML format, wherein the export component deserializes the first form when retrieving the first form from the database; an XML editor configured to edit XML code of the first XML format form to obtain a customized XML format form; and an import component that receives the customized XML format form created using the first XML format form, serializes the customized XML format form, and stores the customized XML format form in the database as an XML layer with a reference to the associated first binary format form stored in the database that was used to generate the first XML format form, wherein the XML layer XML code indicative of differences between the customized XML format form and the first XML format form. | 8. A form customization system comprising: a processor; a database which stores a set of application user interface forms in binary format; and a form user interface modification engine implemented at least in part on the processor, the form user interface modification engine comprising: an export component that retrieves a first form of the set of application user interface forms from the database and generates a first extensible markup language (XML) format form to be used in form customization converting the first form from binary format to XML format, wherein the export component deserializes the first form when retrieving the first form from the database; an XML editor configured to edit XML code of the first XML format form to obtain a customized XML format form; and an import component that receives the customized XML format form created using the first XML format form, serializes the customized XML format form, and stores the customized XML format form in the database as an XML layer with a reference to the associated first binary format form stored in the database that was used to generate the first XML format form, wherein the XML layer XML code indicative of differences between the customized XML format form and the first XML format form. 9. The form customization system of claim 8 , wherein the XML editor is configured to edit XML code of the first XML format form based on an input received from an end user. | 0.65121 |
8,825,644 | 1 | 5 | 1. A method performed by one or more processing devices, comprising: obtaining search results responsive to a search query submitted by a user; determining, based on usage of a social network by the user, a maturity score for the user, where the maturity score represents a measure of user development of the user within the social network; for a particular type of content associated with a search result, retrieving, from a set of utility score instructions, a utility score instruction for the particular type of content; wherein the utility score instruction defines, for the particular type of content in the social network, a relationship between a utility score and the maturity score; wherein the utility score represents a measure of utility of the particular type of content to the user as defined by the measure of user development in the social network; and wherein the utility score is determined independent of user input; wherein defined relationships across the set of utility score instructions promote a first pre-defined type of content among less mature users of the social network relative to other maturities of other users of the social network and promote a second pre-defined type of content among more mature users of the social network relative to the other maturities of the other users of the social network; determining, based on the set of utility score instructions and the maturity score, utility scores for the search results; and adjusting rankings of the search results based on the utility scores. | 1. A method performed by one or more processing devices, comprising: obtaining search results responsive to a search query submitted by a user; determining, based on usage of a social network by the user, a maturity score for the user, where the maturity score represents a measure of user development of the user within the social network; for a particular type of content associated with a search result, retrieving, from a set of utility score instructions, a utility score instruction for the particular type of content; wherein the utility score instruction defines, for the particular type of content in the social network, a relationship between a utility score and the maturity score; wherein the utility score represents a measure of utility of the particular type of content to the user as defined by the measure of user development in the social network; and wherein the utility score is determined independent of user input; wherein defined relationships across the set of utility score instructions promote a first pre-defined type of content among less mature users of the social network relative to other maturities of other users of the social network and promote a second pre-defined type of content among more mature users of the social network relative to the other maturities of the other users of the social network; determining, based on the set of utility score instructions and the maturity score, utility scores for the search results; and adjusting rankings of the search results based on the utility scores. 5. The method of claim 1 , wherein the user comprises a first user, the maturity score comprises a first maturity score, the utility scores comprise first utility scores, and wherein the method further comprises: determining a second maturity score for a second user requesting the search query; determining, based on the second maturity score, second utility scores for the search results; and adjusting the rankings of the search results based on the second utility scores; wherein the adjusted rankings of the search results based on the second utility scores vary from the adjusted rankings of the search results based on the first utility scores. | 0.5 |
9,916,539 | 11 | 13 | 11. A computer implemented method according to claim 10 , wherein a classification result is deemed to indicate that the associated data set includes the target feature if the result is above a classification threshold. | 11. A computer implemented method according to claim 10 , wherein a classification result is deemed to indicate that the associated data set includes the target feature if the result is above a classification threshold. 13. A computer implemented method according to claim 11 , wherein the classification threshold is 0.5. | 0.5 |
9,183,259 | 1 | 3 | 1. A method for displaying content comprising: receiving, by one or more processors, content items that are publishable to an activity stream in a social networking application for a user in a social network; evaluating, by the one or more processors, the received content items using social criteria, including determining a social quality score for each content item, based at least in part on a measure of a likelihood, upon publishing each content item, of a specific social interaction with the content item and value to the social network of the specific social interaction, including measuring and determining probabilities associated with engagements that users have had with previously-presented content items and that users may have with content items that may be presented in the future; filtering, by the one or more processors, the received content items to remove content items having social quality scores below a predetermined threshold; ranking, by the one or more processors, remaining content items according to their associated social quality scores; and publishing, by the one or more processors, the remaining content items in the activity stream for the user in an order based at least in part on the ranking. | 1. A method for displaying content comprising: receiving, by one or more processors, content items that are publishable to an activity stream in a social networking application for a user in a social network; evaluating, by the one or more processors, the received content items using social criteria, including determining a social quality score for each content item, based at least in part on a measure of a likelihood, upon publishing each content item, of a specific social interaction with the content item and value to the social network of the specific social interaction, including measuring and determining probabilities associated with engagements that users have had with previously-presented content items and that users may have with content items that may be presented in the future; filtering, by the one or more processors, the received content items to remove content items having social quality scores below a predetermined threshold; ranking, by the one or more processors, remaining content items according to their associated social quality scores; and publishing, by the one or more processors, the remaining content items in the activity stream for the user in an order based at least in part on the ranking. 3. The method of claim 1 wherein evaluating the plurality of content items includes determining a social quality score for each of the content items and ranking the content items using the social quality scores for respective content items. | 0.777365 |
9,405,934 | 16 | 17 | 16. The system as claimed in claim 15 , including: a key pair component for determining if the user has a defined public/private key available to the working system; the hiding component using a public key in the hiding method to encrypt the plain text. | 16. The system as claimed in claim 15 , including: a key pair component for determining if the user has a defined public/private key available to the working system; the hiding component using a public key in the hiding method to encrypt the plain text. 17. The system as claimed in claim 16 , including: a key pair component for determining if the user's private key is available to the working system; the unhiding component using the private key to decrypt the hidden text. | 0.5 |
8,719,268 | 10 | 11 | 10. A computer program product for enabling parallel processing of an XML document without pre-parsing, wherein the XML document has associated metadata, comprising: a tangible computer readable storage device having computer readable program code embodied therewith, the computer readable program code comprising computer readable program code configured to: generate an XML document from input data; generate metadata associated with the XML document at a predetermined size interval of the XML document during the generation of the XML document, wherein the metadata comprises information that identifies at least N partition point evenly distributed throughout the XML document that enables the XML document to be partitioned without parsing into N partitions of the XML document corresponding to the at least N partition points for parallel processing; and store the XML document and the metadata. | 10. A computer program product for enabling parallel processing of an XML document without pre-parsing, wherein the XML document has associated metadata, comprising: a tangible computer readable storage device having computer readable program code embodied therewith, the computer readable program code comprising computer readable program code configured to: generate an XML document from input data; generate metadata associated with the XML document at a predetermined size interval of the XML document during the generation of the XML document, wherein the metadata comprises information that identifies at least N partition point evenly distributed throughout the XML document that enables the XML document to be partitioned without parsing into N partitions of the XML document corresponding to the at least N partition points for parallel processing; and store the XML document and the metadata. 11. The computer program product of claim 10 , wherein the metadata is stored in the XML document. | 0.71345 |
8,074,166 | 7 | 11 | 7. A system for performing focus inference when compiling an Extensible Markup Language Transforms (XSLT) stylesheet into a compiled XSLT processor, comprising: a processor coupled to a memory, the memory having stored thereon instructions that when executed by the processor cause the processor to: generate an Abstract Syntax Tree (AST) from said XSLT stylesheet; annotate nodes in said AST that are associated with variables and parameters with focus inference flags, said annotating comprising for each of said nodes determining which of a plurality of focus inference flags that define a focus is required to be maintained; build a reverse call graph for a template associated with the XSLT stylesheet; propagate any focus inference flags from a callee template to a caller template; propagate any focus inference flags through the reverse call graph; and use the focus defined by the focus inference flags directly in one or more of a code generator in an XSLT compilation architecture, an interpreter, and/or a JITer, wherein said focus inference flags comprise a “current†focus inference flag, a “position†focus inference flag, and a “last†focus inference flag. | 7. A system for performing focus inference when compiling an Extensible Markup Language Transforms (XSLT) stylesheet into a compiled XSLT processor, comprising: a processor coupled to a memory, the memory having stored thereon instructions that when executed by the processor cause the processor to: generate an Abstract Syntax Tree (AST) from said XSLT stylesheet; annotate nodes in said AST that are associated with variables and parameters with focus inference flags, said annotating comprising for each of said nodes determining which of a plurality of focus inference flags that define a focus is required to be maintained; build a reverse call graph for a template associated with the XSLT stylesheet; propagate any focus inference flags from a callee template to a caller template; propagate any focus inference flags through the reverse call graph; and use the focus defined by the focus inference flags directly in one or more of a code generator in an XSLT compilation architecture, an interpreter, and/or a JITer, wherein said focus inference flags comprise a “current†focus inference flag, a “position†focus inference flag, and a “last†focus inference flag. 11. The system of claim 7 , wherein propagating any focus inference flags through the reverse call graph further comprises using a fixed-point algorithm on a data-flow graph. | 0.560606 |
7,792,846 | 23 | 24 | 23. An apparatus comprising: a pattern matching engine to search for a plurality of N-grams in a set of training documents and a set of validation documents, each of said plurality of N-grams representing at least a portion of a keyword in a natural language, and the set of training documents and the set of validation documents being written in the natural language, wherein each of said plurality of N-grams comprises a sequence of N bytes, where N is an integer; and a model generator coupled to the search engine to generate a statistical content classification model based on occurrences of each of the plurality of N-grams in the set of training documents and the set of validation documents, wherein the search engine is operable to compute a plurality of scores for each of the plurality of N-grams with respect to a plurality of categories; wherein the model generator is operable to determine a plurality of thresholds for the plurality of categories using the plurality of scores and the set of validation documents, each of the plurality of thresholds being associated with a distinct one of the plurality of categories; wherein the model generator is operable to compute each of the plurality of thresholds using a frequency of occurrences of each of the plurality of N-grams in the set of validation documents, the plurality of scores, and a predetermined false positive limit. | 23. An apparatus comprising: a pattern matching engine to search for a plurality of N-grams in a set of training documents and a set of validation documents, each of said plurality of N-grams representing at least a portion of a keyword in a natural language, and the set of training documents and the set of validation documents being written in the natural language, wherein each of said plurality of N-grams comprises a sequence of N bytes, where N is an integer; and a model generator coupled to the search engine to generate a statistical content classification model based on occurrences of each of the plurality of N-grams in the set of training documents and the set of validation documents, wherein the search engine is operable to compute a plurality of scores for each of the plurality of N-grams with respect to a plurality of categories; wherein the model generator is operable to determine a plurality of thresholds for the plurality of categories using the plurality of scores and the set of validation documents, each of the plurality of thresholds being associated with a distinct one of the plurality of categories; wherein the model generator is operable to compute each of the plurality of thresholds using a frequency of occurrences of each of the plurality of N-grams in the set of validation documents, the plurality of scores, and a predetermined false positive limit. 24. The apparatus of claim 23 , further comprising: a processing module to select the plurality of N-grams from a second plurality of N-grams based on utilities of the plurality of N-grams in content classification with respect to the set of training documents. | 0.584395 |
9,613,636 | 1 | 14 | 1. A method of selectively visually representing speaker content generated in an audio conference, the method comprising: obtaining a profile for each of a plurality of audience members who listen to an audio conference; monitoring, using a computer with a tangible processor and memory, speaker content from a plurality of audio conference participants who speak in the audio conference; analyzing the speaker content from each of the plurality of audio conference participants; determining a relation of the speaker content to a topic of discussion based on the analyzing; identifying, based on the analyzing and on the profiles of the plurality of audience members, visual representations of the speaker content to present to the audience members; generating visual representations of the speaker content based on the analyzing and determining; and at a specific point in time, different visual representations of the speaker content are presented to different audience members based on the analyzing and identifying, wherein the presented visual representations include selective visual representation of the speaker content related to the topic of discussion, such that speaker content that is not related to the topic of discussion is not visually represented, wherein the analyzing comprises classifying different sets of words and assigning different weights to the different sets of words, and wherein the identifying comprises selecting sets of words with highest assigned weights of the different sets of words. | 1. A method of selectively visually representing speaker content generated in an audio conference, the method comprising: obtaining a profile for each of a plurality of audience members who listen to an audio conference; monitoring, using a computer with a tangible processor and memory, speaker content from a plurality of audio conference participants who speak in the audio conference; analyzing the speaker content from each of the plurality of audio conference participants; determining a relation of the speaker content to a topic of discussion based on the analyzing; identifying, based on the analyzing and on the profiles of the plurality of audience members, visual representations of the speaker content to present to the audience members; generating visual representations of the speaker content based on the analyzing and determining; and at a specific point in time, different visual representations of the speaker content are presented to different audience members based on the analyzing and identifying, wherein the presented visual representations include selective visual representation of the speaker content related to the topic of discussion, such that speaker content that is not related to the topic of discussion is not visually represented, wherein the analyzing comprises classifying different sets of words and assigning different weights to the different sets of words, and wherein the identifying comprises selecting sets of words with highest assigned weights of the different sets of words. 14. The method of claim 1 , further comprising: obtaining profile information of communications devices used by audience members, wherein the generated visual representations of the speaker content are further generated based on the profile information of the communications devices. | 0.5 |
8,380,507 | 37 | 41 | 37. The Computer readable media for providing speech content, the computer readable media comprising computer readable instructions recorded thereon for: receiving a set of text strings for which speech content is requested; receiving a default language associated with the electronic device; identify a title text string from the received set of text strings, wherein the title text string is associated with a title text string language; identify an artist text string from the received set of text strings, wherein the artist text string is associated with an artist text string language; determine that at least two of the title text string language, album text string language, and default language are different; and select one of the title text string language, album text string language, and default language for generating speech content for the title text string and album text string. | 37. The Computer readable media for providing speech content, the computer readable media comprising computer readable instructions recorded thereon for: receiving a set of text strings for which speech content is requested; receiving a default language associated with the electronic device; identify a title text string from the received set of text strings, wherein the title text string is associated with a title text string language; identify an artist text string from the received set of text strings, wherein the artist text string is associated with an artist text string language; determine that at least two of the title text string language, album text string language, and default language are different; and select one of the title text string language, album text string language, and default language for generating speech content for the title text string and album text string. 41. The computer readable media of claim 37 , further comprising instructions for: determining that the artist text string language is speakable in the title text string language; and generating the speech content using the title text string language. | 0.678205 |
9,875,295 | 1 | 6 | 1. A computer-implemented method comprising: receiving a query having an original term; determining a plurality of substitution contexts for the original term, wherein each substitution context includes one or more context terms, and wherein, when the substitution context is associated with a substitute term, the substitution context specifies substituting the original term with the substitute term in the query if and only if the one or more context terms occur in the query at a position relative to the original term specified by the substitution context; computing respective scores for each first substitution context of the plurality of substitution contexts for the original term including: generating a first alternate set comprising terms that each occur at least once in a textual collection at a position specified by the first substitution context, the position being relative to one or more context terms of the first substitution context, computing respective first rates for each first term in the first alternate set, each first rate for a first term representing (i) how often the first term occurs in the textual collection at the position specified by the first substitution context compared to (ii) how often the original term occurs in the textual collection at the position specified by the first substitution context, generating a second alternate set comprising terms that each occur at least once in a textual collection at a position specified by a different second substitution context of the plurality of substitution contexts for the original term, the position being relative to one or more context terms of the second substitution context, computing respective second rates for each second term in the second alternate set, each second rate for a second term representing (i) how often the second term occurs in the textual collection at the position specified by the second substitution context compared to (ii) how often the original term occurs in the textual collection at the position specified by the first substitution context, computing an alternate set difference between the first alternate set and the second alternate set, the alternate set difference representing a measure of divergence between the computed first rates for the first alternate set and the computed second rates for the second alternate set, and computing the score for the first substitution context relative to the second substitution context based on the alternate set difference between the first alternate set and the second alternate set; classifying each of the plurality of substitution contexts into a first category or a second category based on the respective score computed for each substitution context; associating the original term with one or more substitution contexts in the first category; and providing only substitution contexts in the first category to a substitute term generation process that generates substitute terms for the original term in the query. | 1. A computer-implemented method comprising: receiving a query having an original term; determining a plurality of substitution contexts for the original term, wherein each substitution context includes one or more context terms, and wherein, when the substitution context is associated with a substitute term, the substitution context specifies substituting the original term with the substitute term in the query if and only if the one or more context terms occur in the query at a position relative to the original term specified by the substitution context; computing respective scores for each first substitution context of the plurality of substitution contexts for the original term including: generating a first alternate set comprising terms that each occur at least once in a textual collection at a position specified by the first substitution context, the position being relative to one or more context terms of the first substitution context, computing respective first rates for each first term in the first alternate set, each first rate for a first term representing (i) how often the first term occurs in the textual collection at the position specified by the first substitution context compared to (ii) how often the original term occurs in the textual collection at the position specified by the first substitution context, generating a second alternate set comprising terms that each occur at least once in a textual collection at a position specified by a different second substitution context of the plurality of substitution contexts for the original term, the position being relative to one or more context terms of the second substitution context, computing respective second rates for each second term in the second alternate set, each second rate for a second term representing (i) how often the second term occurs in the textual collection at the position specified by the second substitution context compared to (ii) how often the original term occurs in the textual collection at the position specified by the first substitution context, computing an alternate set difference between the first alternate set and the second alternate set, the alternate set difference representing a measure of divergence between the computed first rates for the first alternate set and the computed second rates for the second alternate set, and computing the score for the first substitution context relative to the second substitution context based on the alternate set difference between the first alternate set and the second alternate set; classifying each of the plurality of substitution contexts into a first category or a second category based on the respective score computed for each substitution context; associating the original term with one or more substitution contexts in the first category; and providing only substitution contexts in the first category to a substitute term generation process that generates substitute terms for the original term in the query. 6. The method of claim 1 , further comprising: determining that no substitution contexts are classified in the first category; and in response to determining that no substitution contexts are classified in the first category, classifying a general context into the first category. | 0.51049 |
9,049,549 | 1 | 3 | 1. A method of delivering location-based information, comprising: receiving a request via connections to a packet-based network, the request including a location indicator, the location indicator including first location components; deriving one or more second location components from one or more of the first location components; forming one or more location component groups each including a respective subset of one or more location components selected from the first location components and the one or more second location components, the respective subset of one or more location components being determined to be consistent with each other; generating a probabilistic representation of a mobile user's location based on the location indicator and historical data collected from mobile devices, the probabilistic representation including one or more probable geographical areas each having an associated weight, each of the one or more probable geographical areas corresponding to a respective one of the one or more location component groups; retrieving information from a data store based on the probabilistic representation; and transmitting the information to the packet-based network for receipt by the mobile user. | 1. A method of delivering location-based information, comprising: receiving a request via connections to a packet-based network, the request including a location indicator, the location indicator including first location components; deriving one or more second location components from one or more of the first location components; forming one or more location component groups each including a respective subset of one or more location components selected from the first location components and the one or more second location components, the respective subset of one or more location components being determined to be consistent with each other; generating a probabilistic representation of a mobile user's location based on the location indicator and historical data collected from mobile devices, the probabilistic representation including one or more probable geographical areas each having an associated weight, each of the one or more probable geographical areas corresponding to a respective one of the one or more location component groups; retrieving information from a data store based on the probabilistic representation; and transmitting the information to the packet-based network for receipt by the mobile user. 3. The method of claim 1 , wherein the first location components include geographical coordinates, the method further comprising: comparing the geographical coordinates with a set of pre-recorded coordinates to determine whether the geographical coordinates are valid location components; and removing the geographical coordinates from the first geographical components in response to the geographical coordinates being determined as invalid. | 0.734375 |
8,978,033 | 1 | 21 | 1. A method for formulating a context representation, the method comprising: selecting at least one keyword from a plurality of text items; determining a task associated with the plurality of text items; selecting at least one query transformation rule from a plurality of different query transformation rules based on the plurality of text items and the task; generating the context representation by applying the at least one query transformation rule to the at least one keyword, the query transformation rule causing the at least one keyword to be replaced by another keyword; generating a search query based on the context representation; and storing search results associated with the search query in a memory. | 1. A method for formulating a context representation, the method comprising: selecting at least one keyword from a plurality of text items; determining a task associated with the plurality of text items; selecting at least one query transformation rule from a plurality of different query transformation rules based on the plurality of text items and the task; generating the context representation by applying the at least one query transformation rule to the at least one keyword, the query transformation rule causing the at least one keyword to be replaced by another keyword; generating a search query based on the context representation; and storing search results associated with the search query in a memory. 21. The method of claim 1 , wherein selecting the at least one query transformation rule is based on a computer application associated with the task. | 0.540123 |
9,165,028 | 1 | 9 | 1. A computer implemented method, comprising: receiving a current query including a plurality of current query terms; determining, based on one or more of the current query terms, that the current query is indicative of an intent of a user to refine a query; determining a previous query associated with the current query, the previous query including a plurality of previous query terms and issued prior to the current query by at least one of a computing device and the user that issued the current query; determining a modification n-gram based on one or more of the current query terms; generating modifications of the previous query that each include the modification n-gram substituted for one or more of the previous query terms; identifying, for each modification of multiple of the modifications: a popularity measure, wherein the popularity measure is indicative of the popularity of the modification; and a related concept measure, wherein the related concept measure is indicative of a likelihood of co-occurrence, in one or more documents, of the modification n-gram and the one or more previous query terms replaced by the modification n-gram in the modification; determining a ranking for each of the multiple of the modifications, wherein the ranking of the modification is based on the popularity measure for the modification and the related concept measure of the modification; and selecting one modification of the modifications when the ranking of the one modification is more prominent than at least the rankings of the other modifications, wherein the one modification includes the modification n-gram and includes at least one of the previous query terms; and submitting the selected one modification to a query system as a submission query for the current query of the user. | 1. A computer implemented method, comprising: receiving a current query including a plurality of current query terms; determining, based on one or more of the current query terms, that the current query is indicative of an intent of a user to refine a query; determining a previous query associated with the current query, the previous query including a plurality of previous query terms and issued prior to the current query by at least one of a computing device and the user that issued the current query; determining a modification n-gram based on one or more of the current query terms; generating modifications of the previous query that each include the modification n-gram substituted for one or more of the previous query terms; identifying, for each modification of multiple of the modifications: a popularity measure, wherein the popularity measure is indicative of the popularity of the modification; and a related concept measure, wherein the related concept measure is indicative of a likelihood of co-occurrence, in one or more documents, of the modification n-gram and the one or more previous query terms replaced by the modification n-gram in the modification; determining a ranking for each of the multiple of the modifications, wherein the ranking of the modification is based on the popularity measure for the modification and the related concept measure of the modification; and selecting one modification of the modifications when the ranking of the one modification is more prominent than at least the rankings of the other modifications, wherein the one modification includes the modification n-gram and includes at least one of the previous query terms; and submitting the selected one modification to a query system as a submission query for the current query of the user. 9. The method of claim 1 , wherein the previous query and the current query are provided via spoken input of the user. | 0.866213 |
9,240,016 | 7 | 11 | 7. The method of claim 1 , further comprising: receiving the dataset from the authenticated subscriber prior to receiving the prediction request from the authenticated subscriber; and processing the dataset on behalf of the authenticated subscriber to generate the indices, each of the indices representing probabilistic relationships between the rows and the columns of the dataset. | 7. The method of claim 1 , further comprising: receiving the dataset from the authenticated subscriber prior to receiving the prediction request from the authenticated subscriber; and processing the dataset on behalf of the authenticated subscriber to generate the indices, each of the indices representing probabilistic relationships between the rows and the columns of the dataset. 11. The method of claim 7 : wherein the host organization comprises a plurality of application servers; wherein the processing further comprises distributing the generation of the indices and storing of the indices amongst multiple of the application servers; and wherein executing the query against indices of the predictive database comprises simultaneously querying the generated indices in parallel against the multiple of the application servers to which the indices were distributed and stored. | 0.742268 |
7,870,486 | 1 | 5 | 1. A system for simultaneously commencing output of disparately encoded electronic documents comprising: a document processing device including a processor and associated data storage; means adapted for receiving, into the document processing device, selection data representative of a plurality of different user-selected electronic documents, each of the plurality of documents being encoded in a unique one of a plurality of disparate formats; association means adapted for associating each of the plurality of disparate formats with at least one software module; means adapted for retrieving the plurality of user-selected electronic documents in accordance with received selection data; means adapted for communicating each of the plurality of user-selected electronic documents to one of a plurality of corresponding software modules in accordance with an output of the association means; means adapted for acquiring common document output characteristics associated with each of the plurality of user-selected electronic documents; means adapted for communicating configuration data corresponding to acquired document output characteristics to each of a plurality of unique software modules in a format compatible thereto; and document processor means adapted for commencing a selected document processing operation on each of a series of the user-selected electronic documents by calling a sequence of the software modules, with each module corresponding to one of the series of user-selected electronic documents such that each module is operative in accordance with the common document output characteristics. | 1. A system for simultaneously commencing output of disparately encoded electronic documents comprising: a document processing device including a processor and associated data storage; means adapted for receiving, into the document processing device, selection data representative of a plurality of different user-selected electronic documents, each of the plurality of documents being encoded in a unique one of a plurality of disparate formats; association means adapted for associating each of the plurality of disparate formats with at least one software module; means adapted for retrieving the plurality of user-selected electronic documents in accordance with received selection data; means adapted for communicating each of the plurality of user-selected electronic documents to one of a plurality of corresponding software modules in accordance with an output of the association means; means adapted for acquiring common document output characteristics associated with each of the plurality of user-selected electronic documents; means adapted for communicating configuration data corresponding to acquired document output characteristics to each of a plurality of unique software modules in a format compatible thereto; and document processor means adapted for commencing a selected document processing operation on each of a series of the user-selected electronic documents by calling a sequence of the software modules, with each module corresponding to one of the series of user-selected electronic documents such that each module is operative in accordance with the common document output characteristics. 5. The system for simultaneously commencing output of disparately encoded electronic documents of claim 1 further comprising means adapted for communicating an output of each software module to a common document output device. | 0.630719 |
9,374,087 | 17 | 19 | 17. A virtual world processing method comprising: encoding information relating to sensor capability into first metadata based on predetermined representation syntax, wherein the predetermined representation syntax defines attributes and flags corresponding to the attributes, and wherein the first metadata includes the flags corresponding to the attributes, and at least one attribute corresponding to at least one flag having a predefined logic value; encoding information relating to a virtual world into second metadata, wherein the information relating to the virtual world comprises a virtual world object characteristic; generating information that is applied to the virtual world, based on the first metadata and the second metadata; and encoding the generated information into third metadata. | 17. A virtual world processing method comprising: encoding information relating to sensor capability into first metadata based on predetermined representation syntax, wherein the predetermined representation syntax defines attributes and flags corresponding to the attributes, and wherein the first metadata includes the flags corresponding to the attributes, and at least one attribute corresponding to at least one flag having a predefined logic value; encoding information relating to a virtual world into second metadata, wherein the information relating to the virtual world comprises a virtual world object characteristic; generating information that is applied to the virtual world, based on the first metadata and the second metadata; and encoding the generated information into third metadata. 19. The virtual world processing method of claim 17 , wherein the encoding of the information on sensor capability into the first metadata comprises generating the first metadata by encoding the information relating to sensor capability into a binary format. | 0.595611 |
8,411,086 | 23 | 27 | 23. The method of claim 22 , wherein joint constraints include at least one of joint type, joint axis, joint stops, joint location and joint anchor. | 23. The method of claim 22 , wherein joint constraints include at least one of joint type, joint axis, joint stops, joint location and joint anchor. 27. The method of claim 23 , wherein the joint stops include a physical extent of motion, wherein the physical extent of motion comprises a maximum angle of travel for a rotational motion or a maximum linear distance of travel for a sliding motion. | 0.5 |
9,753,897 | 1 | 4 | 1. A method for building a custom publication comprising: receiving a selection of units of content for inclusion in a custom publication, each unit of content selected from source publications; accessing a library of electronic source publications, the library having defined units of content within the same publications and storing source publication metadata for the defined units of content, wherein the custom publication includes references to defined units of content associated with the selected units of content; creating a set of custom publication units for an unpublished custom publication, wherein creating the set of custom publication units comprises copying the selected units of content and associating the copied, selected units of content with the unpublished custom publication; including additional content in at least one of the set of custom publication units of content; publishing the unpublished custom publication, wherein publishing the unpublished custom publication comprises: for common structural elements in the custom publication units, including the at least one custom publication unit including the additional content, determining corresponding structural element type, and applying consistent styling to each of the common structural elements in the set of custom publication units of content, including the at least one custom publication unit including the additional content, based upon the determined structural element type, to create a published custom publication with consistent styling; and providing the published custom publication in an electronic format. | 1. A method for building a custom publication comprising: receiving a selection of units of content for inclusion in a custom publication, each unit of content selected from source publications; accessing a library of electronic source publications, the library having defined units of content within the same publications and storing source publication metadata for the defined units of content, wherein the custom publication includes references to defined units of content associated with the selected units of content; creating a set of custom publication units for an unpublished custom publication, wherein creating the set of custom publication units comprises copying the selected units of content and associating the copied, selected units of content with the unpublished custom publication; including additional content in at least one of the set of custom publication units of content; publishing the unpublished custom publication, wherein publishing the unpublished custom publication comprises: for common structural elements in the custom publication units, including the at least one custom publication unit including the additional content, determining corresponding structural element type, and applying consistent styling to each of the common structural elements in the set of custom publication units of content, including the at least one custom publication unit including the additional content, based upon the determined structural element type, to create a published custom publication with consistent styling; and providing the published custom publication in an electronic format. 4. The method of claim 1 , wherein the electronic format is a format that can be consumed by an e-reader, a format that can be consumed by a web browser, or a print format. | 0.61435 |
9,424,522 | 3 | 4 | 3. The system of claim 1 wherein the reasoning system comprises a plurality of different regions which individually include a plurality of the reasoning modules, wherein the reasoning modules of the different regions are configured to process a plurality of the abstractions according to different rules defined by a plurality of different domain ontologies which correspond to respective ones of the regions. | 3. The system of claim 1 wherein the reasoning system comprises a plurality of different regions which individually include a plurality of the reasoning modules, wherein the reasoning modules of the different regions are configured to process a plurality of the abstractions according to different rules defined by a plurality of different domain ontologies which correspond to respective ones of the regions. 4. The system of claim 3 wherein the reasoning modules of one of the regions are configured to process a plurality of the abstractions which were previously processed by the reasoning modules of another of the regions. | 0.5 |
8,423,370 | 14 | 22 | 14. A system for providing an automated translation, the system comprising: a receiving unit configured to receive a verbal communication from a user; a processing unit in communication with the receiving unit, the processing unit configured to: identify a presence of a cultural sensitivity in the received verbal communication; determine guidance for dealing with the identified cultural sensitivity; and translate the verbal communication into a target language. | 14. A system for providing an automated translation, the system comprising: a receiving unit configured to receive a verbal communication from a user; a processing unit in communication with the receiving unit, the processing unit configured to: identify a presence of a cultural sensitivity in the received verbal communication; determine guidance for dealing with the identified cultural sensitivity; and translate the verbal communication into a target language. 22. The system of claim 14 , wherein the processing unit is further configured to classify the received verbal communication as having a durable importance beyond a temporal scope of a medical encounter. | 0.678797 |
8,712,828 | 1 | 5 | 1. A system for managing churn among customers of a business having a statistically large customer base, the system comprising: a memory device configured to store a data mart; a processor in communication with the memory device; a population architecture executable by the processor to receive customer data from one or more data sources stored in the data mart, the customer data defining a plurality of customer attributes for each customer in the customer base; a data manipulation module executable by the processor to: calculate derived variable values based on the customer data, wherein each of the derived variable values is indicative of at least one customer characteristic; select a subset of the derived variable values in response to a preselected data mining function; and generate at least one analytical record containing the subset of the derived variable values, wherein the at least one analytical record is associated with a plurality of customers; a data mining tool executable by the processor to perform the preselected data mining function, the preselected data mining function configured to: analyze the at least one analytical record; return results identifying clusters of customers sharing common customer attributes in response to the analysis of the at least one analytical record; and calculate, based on the at least one analytical record, individual customers' propensities to churn during a predefined period in the future, the data manipulation module storing the results in the data mart; and an end user access module executable by the processor to: access the results returned from the data mining tool; and present the results to a user. | 1. A system for managing churn among customers of a business having a statistically large customer base, the system comprising: a memory device configured to store a data mart; a processor in communication with the memory device; a population architecture executable by the processor to receive customer data from one or more data sources stored in the data mart, the customer data defining a plurality of customer attributes for each customer in the customer base; a data manipulation module executable by the processor to: calculate derived variable values based on the customer data, wherein each of the derived variable values is indicative of at least one customer characteristic; select a subset of the derived variable values in response to a preselected data mining function; and generate at least one analytical record containing the subset of the derived variable values, wherein the at least one analytical record is associated with a plurality of customers; a data mining tool executable by the processor to perform the preselected data mining function, the preselected data mining function configured to: analyze the at least one analytical record; return results identifying clusters of customers sharing common customer attributes in response to the analysis of the at least one analytical record; and calculate, based on the at least one analytical record, individual customers' propensities to churn during a predefined period in the future, the data manipulation module storing the results in the data mart; and an end user access module executable by the processor to: access the results returned from the data mining tool; and present the results to a user. 5. The system for managing churn of claim 1 wherein the subset of derived variable values included in the analytical record are selected to provide customer value data to the data mining tool, and wherein the data mining tool is further executable by the processor to identify significant clusters of customers based on common value characteristics. | 0.519284 |
8,139,900 | 21 | 27 | 21. A system comprising: one or more processors; and a memory coupled to the one or more processors, wherein the memory stores instructions that, when executed by the one or more processors, cause the one or more processors to: supplement an image with metadata that identifies an object in the image; providing the metadata with the image when the image is rendered so that at least a portion of the image depicting the object is interactive, in order to enable a user to enter a selection input that corresponds to the object; and perform an action in response to detecting the selection input that corresponds to the object depicted in the image. | 21. A system comprising: one or more processors; and a memory coupled to the one or more processors, wherein the memory stores instructions that, when executed by the one or more processors, cause the one or more processors to: supplement an image with metadata that identifies an object in the image; providing the metadata with the image when the image is rendered so that at least a portion of the image depicting the object is interactive, in order to enable a user to enter a selection input that corresponds to the object; and perform an action in response to detecting the selection input that corresponds to the object depicted in the image. 27. The system of claim 21 , wherein the one or more processors store the metadata in a header of a file of the image. | 0.695876 |
7,483,833 | 1 | 4 | 1. A method for speech to text transformation comprising the steps of: performing a speech recognition step to provide a text, applying at least one rule to the text for performing at least one automatic text modification, outputting the text on a user interface, outputting at least one suggestion for the automatic text modification on the user interface, and wherein the text modification comprises a number of editing operations, a suggestion for the text modification being outputted when the number of editing operations exceeds a predefined threshold value. | 1. A method for speech to text transformation comprising the steps of: performing a speech recognition step to provide a text, applying at least one rule to the text for performing at least one automatic text modification, outputting the text on a user interface, outputting at least one suggestion for the automatic text modification on the user interface, and wherein the text modification comprises a number of editing operations, a suggestion for the text modification being outputted when the number of editing operations exceeds a predefined threshold value. 4. The method according to claim 1 , the at least one rule providing a confidence value for the at least one modification, wherein the suggestion is only outputted for a user's review when the confidence value is below a threshold. | 0.654192 |
8,572,021 | 16 | 17 | 16. The method of claim 15 , further comprising: receiving the search query; and determining search results for the search query using the indices associated with the first and second medical documents, wherein the search results include a subset of medical documents from the first and second medical documents that are determined to match the search query. | 16. The method of claim 15 , further comprising: receiving the search query; and determining search results for the search query using the indices associated with the first and second medical documents, wherein the search results include a subset of medical documents from the first and second medical documents that are determined to match the search query. 17. The method of claim 16 , further comprising displaying the search results in an interface, wherein the subset of medical documents is displayed in the image-based format. | 0.5 |
8,892,596 | 9 | 12 | 9. A system comprising: one or more devices to: identify, in a first document, a reference to a second document, the second document being different than the first document; identify that the reference to the second document is associated with a relation indicator, the relation indicator being associated with a link that references the second document; determine, based on identifying that the reference to the second document is associated with the relation indicator, that content of the second document is related to content of the first document; where the one or more devices, when determining that the content of the second document is related to the content of the first document, are further to: translate the first document to obtain a translated first document, the translated first document being in a language that matches a language of the second document; compare the translated first document to the second document to obtain a measure of similarity between the translated first document and the second document; and determine, based on the comparing, that the content of the second document is related to the content of the first document when the measure of similarity satisfies a particular similarity threshold; and process the second document based on determining that the content of the second document is related to the content of the first document. | 9. A system comprising: one or more devices to: identify, in a first document, a reference to a second document, the second document being different than the first document; identify that the reference to the second document is associated with a relation indicator, the relation indicator being associated with a link that references the second document; determine, based on identifying that the reference to the second document is associated with the relation indicator, that content of the second document is related to content of the first document; where the one or more devices, when determining that the content of the second document is related to the content of the first document, are further to: translate the first document to obtain a translated first document, the translated first document being in a language that matches a language of the second document; compare the translated first document to the second document to obtain a measure of similarity between the translated first document and the second document; and determine, based on the comparing, that the content of the second document is related to the content of the first document when the measure of similarity satisfies a particular similarity threshold; and process the second document based on determining that the content of the second document is related to the content of the first document. 12. The system of claim 9 , where the one or more devices are further to: identify, in the second document, a reference to the first document, where the one or more devices, when determining the content of the second document is related to the content of the first document, are further to: determine that the content of the second document is related to the content of the first document based on identifying that the second document includes the reference to the first document. | 0.681698 |
9,159,584 | 10 | 12 | 10. The method of claim 1 , wherein based on the respective similarity measures a set of candidate documents is chosen for further inspection, the set of candidate documents being further evaluated with respect to their similarity to the query documents being further evaluated with respect to their similarity measures reflecting the similarity between query and candidate under one or more aspects. | 10. The method of claim 1 , wherein based on the respective similarity measures a set of candidate documents is chosen for further inspection, the set of candidate documents being further evaluated with respect to their similarity to the query documents being further evaluated with respect to their similarity measures reflecting the similarity between query and candidate under one or more aspects. 12. The method of claim 10 , wherein the further inspection comprises comparing query elements with elements of the candidate documents to obtain one or more of the following further similarity measures: a measure for a similarity between the textual query elements and textual document elements; obtaining for each query element a corresponding textual document element based on a similarity measure; obtaining a measure for the degree of coincidence between a sequential order of the textual query elements and a sequential order of the corresponding textual document elements; obtaining a measure for a similarity between a distance between elements in the query and a corresponding distance between elements in the document. | 0.5 |
9,576,042 | 18 | 22 | 18. The computer-implemented method of claim 1 , further comprising: receiving a request for registering an identifier to a user; identifying one or more terms associated with the identifier from the request; comparing the one or more terms to each of the categorized one or more search terms; and determining whether to grant the request based on the comparison. | 18. The computer-implemented method of claim 1 , further comprising: receiving a request for registering an identifier to a user; identifying one or more terms associated with the identifier from the request; comparing the one or more terms to each of the categorized one or more search terms; and determining whether to grant the request based on the comparison. 22. The computer-implemented method of claim 18 , wherein the identifier forms at least part of different uniform resource locators. | 0.721519 |
9,779,063 | 14 | 18 | 14. A document creation apparatus comprising: a processor adapted to: receive a request to create a document, the request comprising a document type, create a primary data object (“PDO”), associate the PDO with a document schema corresponding to the document type, the document schema comprising information relating to allowable node data object types and allowable node data object relationships; receive a first metadata data object comprising document-type dependent information; associate the first metadata data object with the PDO; receive a node data object comprising a node type, content, and relationship information; determine that the received node data object is allowed, based on the document schema and the type and relationship information of the received node data object; associate the received node data object with the PDO; select a document template, based on the document type; and create a storable document, based on the document template, the PDO, the first metadata data object, and the node data object; and a memory adapted to store: the PDO the metadata data object, the node data object, and the document schema. | 14. A document creation apparatus comprising: a processor adapted to: receive a request to create a document, the request comprising a document type, create a primary data object (“PDO”), associate the PDO with a document schema corresponding to the document type, the document schema comprising information relating to allowable node data object types and allowable node data object relationships; receive a first metadata data object comprising document-type dependent information; associate the first metadata data object with the PDO; receive a node data object comprising a node type, content, and relationship information; determine that the received node data object is allowed, based on the document schema and the type and relationship information of the received node data object; associate the received node data object with the PDO; select a document template, based on the document type; and create a storable document, based on the document template, the PDO, the first metadata data object, and the node data object; and a memory adapted to store: the PDO the metadata data object, the node data object, and the document schema. 18. A document creation apparatus according to claim 14 , wherein the stored document is an intermediate document, and the processor is further adapted to interpret the intermediate document to create a rendered document. | 0.539583 |
9,304,984 | 18 | 21 | 18. A method comprising: presenting, by a system including a processor, an interactive interface that includes representations of a plurality of patterns including respective different syntaxes of intention phrases; receiving, by the system, user selection in the interactive interface of a selected pattern of the plurality of patterns; and extracting, by the system, intention statement information from textual data, the intention statement information including an intention statement according to the selected pattern and comprising a group of words or phrases expressing an intention of an author of the intention statement to perform an action, wherein a first syntax of intention phrases of a first pattern of the plurality of patterns includes an intention verb and an action verb, and a second syntax of intention phrases of a second pattern of the plurality of patterns includes an intention verb, a preposition, and an action verb, and wherein the selected pattern is one of the first and second patterns. | 18. A method comprising: presenting, by a system including a processor, an interactive interface that includes representations of a plurality of patterns including respective different syntaxes of intention phrases; receiving, by the system, user selection in the interactive interface of a selected pattern of the plurality of patterns; and extracting, by the system, intention statement information from textual data, the intention statement information including an intention statement according to the selected pattern and comprising a group of words or phrases expressing an intention of an author of the intention statement to perform an action, wherein a first syntax of intention phrases of a first pattern of the plurality of patterns includes an intention verb and an action verb, and a second syntax of intention phrases of a second pattern of the plurality of patterns includes an intention verb, a preposition, and an action verb, and wherein the selected pattern is one of the first and second patterns. 21. The method of claim 18 , further comprising: identifying, by the system, the intention statement in the textual data by: identifying an intention verb within text in the textual data; and identifying an action verb associated with the intention verb, the action verb specifying the action, the intention verb and the action verb having the syntax of intention phrases of the selected pattern. | 0.5 |
8,060,367 | 1 | 12 | 1. A non-transitory computer readable medium having stored thereon one or more sequences of instructions for causing one or more processors to perform the steps for speech recognition using tiles, each tile defines an area on the surface of the earth and the defined area is a more or less symmetrical shape defined by a coordinate system and can have a spatially proximate relationship to other tiles, a grammar is associated with each tile and is derived from feature names of first level identifiers in the area defined by the tile and, each first level identifier corresponds to a point on the surface of the earth, the steps comprising: identifying a candidate area location; choosing an initial tile based on the candidate area location; comparing an utterance of a first level identifier against a first grammar associated with the initial tile to determine if the utterance corresponds to a feature from which the first grammar was derived, wherein the grammar comprises an audio file associated with each of the feature names of the first level identifiers associated with the tile, and wherein the utterance corresponds to a feature from which the first grammar was derived if the utterance matches an audio file associated with the first grammar; if the utterance does not correspond to a feature in the first grammar, determining a plurality of second tiles; and comparing the utterance of the first level identifier against the plurality of grammars associated with the plurality of second tiles to determine if the utterance corresponds to a feature from which the plurality of grammars was derived; and determining a point coordinate associated with the feature which matches the utterance. | 1. A non-transitory computer readable medium having stored thereon one or more sequences of instructions for causing one or more processors to perform the steps for speech recognition using tiles, each tile defines an area on the surface of the earth and the defined area is a more or less symmetrical shape defined by a coordinate system and can have a spatially proximate relationship to other tiles, a grammar is associated with each tile and is derived from feature names of first level identifiers in the area defined by the tile and, each first level identifier corresponds to a point on the surface of the earth, the steps comprising: identifying a candidate area location; choosing an initial tile based on the candidate area location; comparing an utterance of a first level identifier against a first grammar associated with the initial tile to determine if the utterance corresponds to a feature from which the first grammar was derived, wherein the grammar comprises an audio file associated with each of the feature names of the first level identifiers associated with the tile, and wherein the utterance corresponds to a feature from which the first grammar was derived if the utterance matches an audio file associated with the first grammar; if the utterance does not correspond to a feature in the first grammar, determining a plurality of second tiles; and comparing the utterance of the first level identifier against the plurality of grammars associated with the plurality of second tiles to determine if the utterance corresponds to a feature from which the plurality of grammars was derived; and determining a point coordinate associated with the feature which matches the utterance. 12. The computer readable medium of claim 1 wherein the step of determining a plurality of second tiles further comprises removing a duplicate feature from the plurality of second grammars. | 0.865 |
8,831,948 | 1 | 4 | 1. A method comprising: receiving a metadata request from a user, wherein the metadata request is associated with a primary media content and comprises a gesture; selecting a piece of metadata for output to yield selected metadata, the selected metadata being responsive to the metadata request regarding the primary media content and received during presentation of the primary media content; and outputting, with the primary media content, the selected metadata as synthetically generated speech, the synthetically generated speech having an accent, wherein the accent is selected from a plurality of accents based on the selected metadata. | 1. A method comprising: receiving a metadata request from a user, wherein the metadata request is associated with a primary media content and comprises a gesture; selecting a piece of metadata for output to yield selected metadata, the selected metadata being responsive to the metadata request regarding the primary media content and received during presentation of the primary media content; and outputting, with the primary media content, the selected metadata as synthetically generated speech, the synthetically generated speech having an accent, wherein the accent is selected from a plurality of accents based on the selected metadata. 4. The method of claim 1 , wherein the synthetically generated speech is output during gaps in the primary media content. | 0.759921 |
8,170,875 | 8 | 14 | 8. A method of determining at least one of a beginning or end of an audio speech segment, the method comprising: receiving a portion of an audio stream that includes a speech segment; identifying a triggering characteristic in the speech segment; applying at least one decision rule to the speech segment of the audio stream to count a number of isolated energy events in the audio stream that precede the triggering characteristic; and determining that a frame of the audio stream is outside of an endpoint of the speech segment when a number of allowed isolated energy events is exceeded. | 8. A method of determining at least one of a beginning or end of an audio speech segment, the method comprising: receiving a portion of an audio stream that includes a speech segment; identifying a triggering characteristic in the speech segment; applying at least one decision rule to the speech segment of the audio stream to count a number of isolated energy events in the audio stream that precede the triggering characteristic; and determining that a frame of the audio stream is outside of an endpoint of the speech segment when a number of allowed isolated energy events is exceeded. 14. The method of claim 8 , further comprising detecting the beginning and end of the audio speech segment. | 0.725641 |
9,940,317 | 19 | 20 | 19. The system of claim 18 wherein said format element includes a color merge element wherein an area on the display screen defined by two overlapping expandable container images displays a color different from the colors unique to the two overlapping expandable container images. | 19. The system of claim 18 wherein said format element includes a color merge element wherein an area on the display screen defined by two overlapping expandable container images displays a color different from the colors unique to the two overlapping expandable container images. 20. The system of claim 19 wherein the color in the area on the display screen defined by two overlapping expandable container images has a spectral relationship to each of the colors in the two overlapping expandable container images. | 0.5 |
8,306,752 | 1 | 4 | 1. A computer-implemented method for identifying a regulatory interaction between a transcription factor and a gene target of said transcription factor, the method comprising: a) providing a compendium of biochemical expression measurements reflecting gene expression for a set of biochemical species in an organism wherein at least a subset of said species are transcription factors and a second subset of said species are gene targets of transcription factors; b) in a specifically programmed computer, computing mutual information between members of said set of biochemical species; c) in a specifically programmed computer, applying a background correction to each said mutual information value so as to identify a set of those mutual information values that are significantly higher than background mutual information values, wherein the step of applying a background correction comprises the step of estimating a likelihood of the mutual information score, MI, for each possible pair of genes, by comparing the mutual information score for that pair to a background distribution of mutual information values, and wherein said set of mutual information values identified in step (c) identifies a regulatory interaction between a transcription factor and a gene target of said transcription factor; and d) outputting the identified regulatory interaction to a user interface. | 1. A computer-implemented method for identifying a regulatory interaction between a transcription factor and a gene target of said transcription factor, the method comprising: a) providing a compendium of biochemical expression measurements reflecting gene expression for a set of biochemical species in an organism wherein at least a subset of said species are transcription factors and a second subset of said species are gene targets of transcription factors; b) in a specifically programmed computer, computing mutual information between members of said set of biochemical species; c) in a specifically programmed computer, applying a background correction to each said mutual information value so as to identify a set of those mutual information values that are significantly higher than background mutual information values, wherein the step of applying a background correction comprises the step of estimating a likelihood of the mutual information score, MI, for each possible pair of genes, by comparing the mutual information score for that pair to a background distribution of mutual information values, and wherein said set of mutual information values identified in step (c) identifies a regulatory interaction between a transcription factor and a gene target of said transcription factor; and d) outputting the identified regulatory interaction to a user interface. 4. The method of claim 1 wherein said mutual information is higher order mutual information. | 0.89823 |
8,510,103 | 6 | 7 | 6. The method of claim 3 , wherein the stored audio patterns and digital tokens are stored in a table and one of the plurality of stored audio patterns in the table is selected by: comparing a digital audio input signal with each stored audio pattern associated with the identified user; and selecting one of the plurality of stored audio patterns with the highest correspondence to the digital audio input. | 6. The method of claim 3 , wherein the stored audio patterns and digital tokens are stored in a table and one of the plurality of stored audio patterns in the table is selected by: comparing a digital audio input signal with each stored audio pattern associated with the identified user; and selecting one of the plurality of stored audio patterns with the highest correspondence to the digital audio input. 7. The method of claim 6 , wherein comparing the digital audio input signal with each stored audio pattern associated with the identified user is performed by calculating a correlation between the digital audio input signal and the stored audio pattern. | 0.798567 |
9,141,686 | 12 | 16 | 12. A method, comprising: receiving unstructured data from a plurality of data sources, the plurality of data sources comprising a competitor database, a vendor database, and a marketing database, wherein the unstructured data relates to a financial risk of an organization and comprises a plurality of text documents, each text document comprising a plurality of groups of words; deconstructing, by a processor, each group of words from the unstructured data into individual words; converting, by the processor, the individual words from each group of words into a plurality of structured forms, each structured form corresponding to a single group of words; determining, by the processor, a numerical value associated with each individual word according to: a number of times the individual word appears in the group of words and an association of the group of words with a risk experienced by an organization, wherein each structured form is a vector that includes each individual word and a quantification of the individual word; comparing, by the processor, each structured form to another structured form using a Bayesian inference; categorizing, by the processor, the individual words in each structured form into at least one category according to the comparison and the at least one category is selected from a set of categories consisting of organization name, geographical region, organization size, number of employees, number of countries represented, public organization, private organization, regulatory body, industry, and fine amount, the categories indicating the financial risk of the organization; and quantifying, by the processor, the individual words in each structured form according to at least the categorization of the individual words by weighting each individual word. | 12. A method, comprising: receiving unstructured data from a plurality of data sources, the plurality of data sources comprising a competitor database, a vendor database, and a marketing database, wherein the unstructured data relates to a financial risk of an organization and comprises a plurality of text documents, each text document comprising a plurality of groups of words; deconstructing, by a processor, each group of words from the unstructured data into individual words; converting, by the processor, the individual words from each group of words into a plurality of structured forms, each structured form corresponding to a single group of words; determining, by the processor, a numerical value associated with each individual word according to: a number of times the individual word appears in the group of words and an association of the group of words with a risk experienced by an organization, wherein each structured form is a vector that includes each individual word and a quantification of the individual word; comparing, by the processor, each structured form to another structured form using a Bayesian inference; categorizing, by the processor, the individual words in each structured form into at least one category according to the comparison and the at least one category is selected from a set of categories consisting of organization name, geographical region, organization size, number of employees, number of countries represented, public organization, private organization, regulatory body, industry, and fine amount, the categories indicating the financial risk of the organization; and quantifying, by the processor, the individual words in each structured form according to at least the categorization of the individual words by weighting each individual word. 16. The method of claim 12 , wherein quantifying the individual words comprises weighting the individual words based on quantifiable data. | 0.758741 |
9,218,810 | 8 | 12 | 8. A system comprising: a processor; and a computer-readable storage medium having instructions stored which, when executed by the processor, cause the processor to perform operations comprising: generating a semantic and syntactic graph associated with a first call type; converting the semantic and syntactic graph into a first finite state transducer; composing the first finite state transducer with a second finite state transducer to form a third finite state transducer, wherein the second finite state transducer comprises all possible n-grams, and wherein the third finite state transducer comprises a subset of the all-possible n-grams; extracting the subset of the all-possible n-grams as features from the third finite state transducer, to yield extracted n-grams; associating an utterance with a second call type based on the extracted n-grams, to yield a classified utterance, wherein the second call type is determined based on semantic and syntactic features in the extracted n-grams; and responding to a user in a natural language dialog based on the classified utterance. | 8. A system comprising: a processor; and a computer-readable storage medium having instructions stored which, when executed by the processor, cause the processor to perform operations comprising: generating a semantic and syntactic graph associated with a first call type; converting the semantic and syntactic graph into a first finite state transducer; composing the first finite state transducer with a second finite state transducer to form a third finite state transducer, wherein the second finite state transducer comprises all possible n-grams, and wherein the third finite state transducer comprises a subset of the all-possible n-grams; extracting the subset of the all-possible n-grams as features from the third finite state transducer, to yield extracted n-grams; associating an utterance with a second call type based on the extracted n-grams, to yield a classified utterance, wherein the second call type is determined based on semantic and syntactic features in the extracted n-grams; and responding to a user in a natural language dialog based on the classified utterance. 12. The system of claim 8 , wherein generating the semantic and syntactic graph extends a feature set of a classifier that performs classifying the utterance. | 0.703008 |
8,082,246 | 6 | 7 | 6. The method of claim 1 , wherein ranking search results using the click distance values of the high authority nodes and the other nodes as a query-independent relevance measure further comprises using a component corresponding to the click distance in a scoring function for determining a relevance score for each of the documents. | 6. The method of claim 1 , wherein ranking search results using the click distance values of the high authority nodes and the other nodes as a query-independent relevance measure further comprises using a component corresponding to the click distance in a scoring function for determining a relevance score for each of the documents. 7. The method of claim 6 , wherein the relevance score is offset by a Uniform Resource Locator depth property that smoothes the effect of the click distance on the relevance score. | 0.5 |
8,650,211 | 1 | 3 | 1. A non-transitory data storage medium containing instructions which, when executed, cause one or more computers to perform operations comprising: a. accessing a plurality of databases, at least two of which are incompatible, wherein each of the plurality of databases contains live source data and associated metadata; b. retrieving at least a portion of the associated metadata from each of the plurality of databases; c. storing the portion of the associated metadata in a dimensional format within a metadata repository; d. receiving user login credentials corresponding to a user; e. identifying one or more access codes corresponding to the user login credentials, each identified access code providing access to one or more of the plurality of databases; f. receiving a data retrieval request through a graphical user interface in response to user input, and in response to receiving the data retrieval request: i. using the portion of the associated metadata to search the live source data in the plurality of databases, wherein the use of the associated metadata to search the live source data occurs only if the one or more identified access codes provides access to one or more of the plurality of databases; ii. retrieving source data responsive to the data retrieval request, wherein the retrieved source data includes live source data; and iii. dynamically assembling a slice of an OLAP cube using at least a portion of the retrieved source data, wherein at least a portion of the dynamically assembling is performed without accessing a repository of warehoused; g. displaying a representation of the slice of the OLAP cube on the graphical user interface, wherein the operations further comprise: h. receiving, from the graphical user interface in response to user input, a request to modify a portion of the displayed representation of the slice of the OLAP cube; and i. in response to receiving the request to modify: i. directly updating one or more of the plurality of databases consistent with the request to modify; and ii. directly updating the slice of the OLAP cube consistent with the request to modify. | 1. A non-transitory data storage medium containing instructions which, when executed, cause one or more computers to perform operations comprising: a. accessing a plurality of databases, at least two of which are incompatible, wherein each of the plurality of databases contains live source data and associated metadata; b. retrieving at least a portion of the associated metadata from each of the plurality of databases; c. storing the portion of the associated metadata in a dimensional format within a metadata repository; d. receiving user login credentials corresponding to a user; e. identifying one or more access codes corresponding to the user login credentials, each identified access code providing access to one or more of the plurality of databases; f. receiving a data retrieval request through a graphical user interface in response to user input, and in response to receiving the data retrieval request: i. using the portion of the associated metadata to search the live source data in the plurality of databases, wherein the use of the associated metadata to search the live source data occurs only if the one or more identified access codes provides access to one or more of the plurality of databases; ii. retrieving source data responsive to the data retrieval request, wherein the retrieved source data includes live source data; and iii. dynamically assembling a slice of an OLAP cube using at least a portion of the retrieved source data, wherein at least a portion of the dynamically assembling is performed without accessing a repository of warehoused; g. displaying a representation of the slice of the OLAP cube on the graphical user interface, wherein the operations further comprise: h. receiving, from the graphical user interface in response to user input, a request to modify a portion of the displayed representation of the slice of the OLAP cube; and i. in response to receiving the request to modify: i. directly updating one or more of the plurality of databases consistent with the request to modify; and ii. directly updating the slice of the OLAP cube consistent with the request to modify. 3. The data storage medium of claim 1 wherein the metadata repository further comprises metadata-based correlation parameters. | 0.798722 |
9,378,423 | 14 | 18 | 14. A method, comprising: identifying a plurality of shots in video content; creating a lattice of nodes that comprises at least one of a scene boundary node or a non-scene boundary node for each shot in the plurality of shots, wherein the lattice of nodes defines a plurality of paths beginning at a first shot of the plurality of shots and ending at a last shot of the plurality of shots; ranking the plurality of paths; selecting, based on the ranking, which one of the plurality of paths is to define where boundaries of a scene are located in the video content; for the scene, identifying first confidence values that are representative of features of the scene and that are a result of a video recognition process; for the scene, identifying second confidence values that are representative of features of the scene and that are a result of an audio recognition process; and based on the first confidence values and the second confidence values, determining, by a computing device, at least one identifier that defines whether an entity is present in the scene. | 14. A method, comprising: identifying a plurality of shots in video content; creating a lattice of nodes that comprises at least one of a scene boundary node or a non-scene boundary node for each shot in the plurality of shots, wherein the lattice of nodes defines a plurality of paths beginning at a first shot of the plurality of shots and ending at a last shot of the plurality of shots; ranking the plurality of paths; selecting, based on the ranking, which one of the plurality of paths is to define where boundaries of a scene are located in the video content; for the scene, identifying first confidence values that are representative of features of the scene and that are a result of a video recognition process; for the scene, identifying second confidence values that are representative of features of the scene and that are a result of an audio recognition process; and based on the first confidence values and the second confidence values, determining, by a computing device, at least one identifier that defines whether an entity is present in the scene. 18. The method of claim 14 , further comprising: determining a measurement that numerically indicates an importance of the entity to the scene; determining that the measurement satisfies a salience threshold; and inserting an identifier of the entity into a listing of entities that are present and salient to the scene. | 0.665272 |
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