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8,959,489 | 15 | 16 | 15. A method performed on a computing device, the method for forming an editing interface for editing an object, the method comprising: enumerating object properties of the object, the enumerating based on object metadata that defines the object, and where a serialization of the object is based on a markup language; iterating through at least a portion of the enumerated object properties of the object, the iterating including processing each property of the at least a portion of the enumerated object properties of the object, the processing including: determining if a pre-existing editor is available that is configured for editing the each property and, if so, selecting the pre-existing editor, otherwise constructing, based on the serialization and in response to the pre-existing editor not being available, a collection editor configured for editing the each property, where the constructing comprises determining if one of the at least a portion of the enumerated object properties is a collection, and adding the selected pre-existing editor or the constructed collection editor to the editing interface, the editing interface including a plurality of editors; and serializing, according to the markup language, the object including the at least a portion of the enumerated object properties, the serializing in response to editing the one of the iterated properties of the object via the constructed collection editor. | 15. A method performed on a computing device, the method for forming an editing interface for editing an object, the method comprising: enumerating object properties of the object, the enumerating based on object metadata that defines the object, and where a serialization of the object is based on a markup language; iterating through at least a portion of the enumerated object properties of the object, the iterating including processing each property of the at least a portion of the enumerated object properties of the object, the processing including: determining if a pre-existing editor is available that is configured for editing the each property and, if so, selecting the pre-existing editor, otherwise constructing, based on the serialization and in response to the pre-existing editor not being available, a collection editor configured for editing the each property, where the constructing comprises determining if one of the at least a portion of the enumerated object properties is a collection, and adding the selected pre-existing editor or the constructed collection editor to the editing interface, the editing interface including a plurality of editors; and serializing, according to the markup language, the object including the at least a portion of the enumerated object properties, the serializing in response to editing the one of the iterated properties of the object via the constructed collection editor. 16. The method of claim 15 embodied as computer-executable instructions stored on a computer-readable medium. | 0.5 |
8,417,514 | 6 | 10 | 6. A system for selecting answers to natural language questions from a collection of textual documents, comprising: a memory; and at least one processor, coupled to the memory, operative to: extract scoring features from a candidate list of passages of possible answers, wherein said scoring feature is a number of words in a candidate answer that are different than words in said natural language question; score the possible answers using the extracted scoring features and a features scoring function; and present the best scoring possible answer to the user with context from the passage containing the answer. | 6. A system for selecting answers to natural language questions from a collection of textual documents, comprising: a memory; and at least one processor, coupled to the memory, operative to: extract scoring features from a candidate list of passages of possible answers, wherein said scoring feature is a number of words in a candidate answer that are different than words in said natural language question; score the possible answers using the extracted scoring features and a features scoring function; and present the best scoring possible answer to the user with context from the passage containing the answer. 10. A system as in claim 6 , wherein the candidate list of passages of possible answers is obtained from the collection of documents using an information retrieval engine. | 0.5 |
7,882,146 | 1 | 2 | 1. A database system for storing data including Extensible Markup Language (XML) instances, said database system comprising: a computer processor; and a computer readable storage medium having a tangible physical structure, the tangible medium having program code that causes said processor to perform a plurality of operations, said operations comprising: generating an XML schema collections container in a relational database for collecting a plurality of XML schema namespace universal resource identifiers (URIs), each namespace URI respectively identifying a single collection of element types and attribute names in an XML instance that corresponds to a location typed XML schema document wherein, the XML schema document defines the namespace URIs in the container and a set of attributes, relationships, organizations, and functions for confirming with the XML instance; and each namespace URI in the container allows a reference to any XML schema document in the system; placing in the created container at least two XML schema namespace universal resource identifiers (URIs) which represent at least two different location typed SQL server namespace schemas in the relational database; validating a single complex namespace schema for a redefined XML instance by calling an import function specified in the redefined XML instance with at least one of the two location typed schemas that were placed in the container by the respective URIs; associating a column of a table in another database with the XML schema collections container prior to the validating operation, by setting the location type of the column in the table of the other database in context of the single complex namespace schema for the redefined XML instance, with any other XML schemas being placed in the container when referencing respective URLs; and storing the validated single complex name space schema for the redefined XML instance within the column of the container when invoking an alter XML schema collection function specified by the redefined XML instance that adds the validated single complex name space schema for the redefined XML instance into the column of the container in a form of the location typed URI. | 1. A database system for storing data including Extensible Markup Language (XML) instances, said database system comprising: a computer processor; and a computer readable storage medium having a tangible physical structure, the tangible medium having program code that causes said processor to perform a plurality of operations, said operations comprising: generating an XML schema collections container in a relational database for collecting a plurality of XML schema namespace universal resource identifiers (URIs), each namespace URI respectively identifying a single collection of element types and attribute names in an XML instance that corresponds to a location typed XML schema document wherein, the XML schema document defines the namespace URIs in the container and a set of attributes, relationships, organizations, and functions for confirming with the XML instance; and each namespace URI in the container allows a reference to any XML schema document in the system; placing in the created container at least two XML schema namespace universal resource identifiers (URIs) which represent at least two different location typed SQL server namespace schemas in the relational database; validating a single complex namespace schema for a redefined XML instance by calling an import function specified in the redefined XML instance with at least one of the two location typed schemas that were placed in the container by the respective URIs; associating a column of a table in another database with the XML schema collections container prior to the validating operation, by setting the location type of the column in the table of the other database in context of the single complex namespace schema for the redefined XML instance, with any other XML schemas being placed in the container when referencing respective URLs; and storing the validated single complex name space schema for the redefined XML instance within the column of the container when invoking an alter XML schema collection function specified by the redefined XML instance that adds the validated single complex name space schema for the redefined XML instance into the column of the container in a form of the location typed URI. 2. The database system of claim 1 , said computer readable storage medium further comprising program code executable by said computer processor that comprises an include function which assembles URIs identified in a plurality of schema location attributes. | 0.5 |
9,720,907 | 19 | 20 | 19. The computer-readable storage device of claim 17 , wherein predicting the label for the target word is further based on a connectionist model. | 19. The computer-readable storage device of claim 17 , wherein predicting the label for the target word is further based on a connectionist model. 20. The computer-readable storage device of claim 19 , wherein the connectionist model comprises a learnable linear mapping which maps each word in the first natural language corpus to a low dimensional latent space. | 0.5 |
8,027,977 | 6 | 11 | 6. A document recommendation system comprising: a set of positive documents determined to be of interest to a user; a set of negative documents determined to not be of interest to the user; a plurality of candidate documents; and a module configured to calculate similarity scores of each document in the set of positive documents relative to the plurality of candidate documents and to calculate similarity scores of each document in the set of negative documents relative to the plurality of candidate documents, and wherein the module receives a new document apart from the plurality of candidate documents, calculates a similarity score, using a processor, of the new document relative to each of the plurality of candidate documents using a measure of discriminatively trained similarity associated with each of the plurality of candidate documents, and outputs a reference to at least one of the plurality of candidate documents based on the calculated similarity scores. | 6. A document recommendation system comprising: a set of positive documents determined to be of interest to a user; a set of negative documents determined to not be of interest to the user; a plurality of candidate documents; and a module configured to calculate similarity scores of each document in the set of positive documents relative to the plurality of candidate documents and to calculate similarity scores of each document in the set of negative documents relative to the plurality of candidate documents, and wherein the module receives a new document apart from the plurality of candidate documents, calculates a similarity score, using a processor, of the new document relative to each of the plurality of candidate documents using a measure of discriminatively trained similarity associated with each of the plurality of candidate documents, and outputs a reference to at least one of the plurality of candidate documents based on the calculated similarity scores. 11. The document recommendation system of claim 6 wherein the measure of similarity is based on Latent Semantic Analysis (LSA) or Probabilistic Latent Semantic Analysis (PLSA). | 0.812766 |
9,697,057 | 2 | 3 | 2. The method of claim 1 , further comprising: establishing a goal for the user, where the goal is achievable by performing a set of action(s); and determining, based, at least in part, on the first user data, whether the user has achieved the goal by performing the set of action(s). | 2. The method of claim 1 , further comprising: establishing a goal for the user, where the goal is achievable by performing a set of action(s); and determining, based, at least in part, on the first user data, whether the user has achieved the goal by performing the set of action(s). 3. The method of claim 2 , further comprising: on condition that the goal has been determined to have not been achieved by the user, allowing, by one or more processors, the user to perform one or more remaining action(s) of the set of action(s) on the second application via the second interaction mode. | 0.5 |
8,903,828 | 1 | 9 | 1. A method for configuring a multi-path index, the method comprising: receiving, by an indexing engine in a database management system configured to store a structured document in its native format, a multi-path index definition associated with a data model corresponding to the structured document; and storing, by the indexing engine, the multi-path index definition in a data structure associated with a multi-path index configured to store indexed data from a structured document conforming to the data model, the multi-path index definition including a first sub-path definition that covers a first plurality of descendant elements of a root element of the data model and a second sub-path definition that covers a second plurality of descendant elements of the root element of the data model, the multi-path index definition further including at least two index properties, wherein each of a plurality of descendant elements covered by the sub-path definitions is automatically indexed according to the at least two index properties that specify types of searches to be performed for the content of each of the descendant elements covered by the sub-path definitions, and wherein the at least two index properties are selected from a set of index properties including at least a full-text search, a value comparison, an element type definition, an enumerate repeating elements, and a start end marker. | 1. A method for configuring a multi-path index, the method comprising: receiving, by an indexing engine in a database management system configured to store a structured document in its native format, a multi-path index definition associated with a data model corresponding to the structured document; and storing, by the indexing engine, the multi-path index definition in a data structure associated with a multi-path index configured to store indexed data from a structured document conforming to the data model, the multi-path index definition including a first sub-path definition that covers a first plurality of descendant elements of a root element of the data model and a second sub-path definition that covers a second plurality of descendant elements of the root element of the data model, the multi-path index definition further including at least two index properties, wherein each of a plurality of descendant elements covered by the sub-path definitions is automatically indexed according to the at least two index properties that specify types of searches to be performed for the content of each of the descendant elements covered by the sub-path definitions, and wherein the at least two index properties are selected from a set of index properties including at least a full-text search, a value comparison, an element type definition, an enumerate repeating elements, and a start end marker. 9. The method of claim 1 wherein the database management system is an extensible markup language (XML) database management system and the structured document is an XML document. | 0.785194 |
9,891,900 | 10 | 15 | 10. A method, comprising: passing, by a platform-independent, object-oriented, runtime environment implemented on one or more computing devices comprising one or more hardware processors and memory, a generic method and specialization metadata to a specialized method generator of the platform-independent, object-oriented, runtime environment, wherein the specialization metadata comprises information identifying one or more program elements of the generic method to be adjusted when specializing the generic method for a particular type parameterization; generating, by the specialized method generator in response to said passing, a specialized method based, at least in part, on the generic method and the specialization metadata, wherein the specialized method is a version of the generic method specialized for the particular type parameterization; and storing, as a result of the specialized method being generated, a handle to the specialized method, such that the handle is usable to invoke the specialized method. | 10. A method, comprising: passing, by a platform-independent, object-oriented, runtime environment implemented on one or more computing devices comprising one or more hardware processors and memory, a generic method and specialization metadata to a specialized method generator of the platform-independent, object-oriented, runtime environment, wherein the specialization metadata comprises information identifying one or more program elements of the generic method to be adjusted when specializing the generic method for a particular type parameterization; generating, by the specialized method generator in response to said passing, a specialized method based, at least in part, on the generic method and the specialization metadata, wherein the specialized method is a version of the generic method specialized for the particular type parameterization; and storing, as a result of the specialized method being generated, a handle to the specialized method, such that the handle is usable to invoke the specialized method. 15. The method of claim 10 , further comprising: generating a container class, wherein said generating comprises generating the specialized method as a member of the container class; storing the specialized method; and treating the specialized method as if it were a member of a class to which the generic method is a member. | 0.721747 |
8,612,879 | 9 | 13 | 9. One or more computer storage media storing computer-useable instructions that, when used by one or more computing devices, cause the one or more computing devices to perform a method, the method comprising: displaying a selection area of a mobile device including a plurality of symbols, wherein each of the plurality of symbols is a phonetic representation of one or more characters; receiving a user selection of a symbol of the plurality of symbols; and upon receiving the user selection of the symbol, replacing a first set of keys of the selection area with a plurality of tone keys, wherein each of the plurality of tone keys is associated with a tone marker. | 9. One or more computer storage media storing computer-useable instructions that, when used by one or more computing devices, cause the one or more computing devices to perform a method, the method comprising: displaying a selection area of a mobile device including a plurality of symbols, wherein each of the plurality of symbols is a phonetic representation of one or more characters; receiving a user selection of a symbol of the plurality of symbols; and upon receiving the user selection of the symbol, replacing a first set of keys of the selection area with a plurality of tone keys, wherein each of the plurality of tone keys is associated with a tone marker. 13. The one or more computer storage media of claim 9 , wherein the mobile device is a mobile phone. | 0.787234 |
8,484,578 | 11 | 13 | 11. The method of claim 10 , further comprising: displaying the status of the document in a document status display pane that is displayed in the out-space user interface; and visually highlighting the document status display pane to indicate that the status of the document displayed in the document status display pane is associated with the message bar displayed in the in-space user interface for alerting a user of the document about the availability of the status of the document. | 11. The method of claim 10 , further comprising: displaying the status of the document in a document status display pane that is displayed in the out-space user interface; and visually highlighting the document status display pane to indicate that the status of the document displayed in the document status display pane is associated with the message bar displayed in the in-space user interface for alerting a user of the document about the availability of the status of the document. 13. The method of claim 11 , further comprising: determining a non-authoring feature that may be utilized for changing the status of the document; and displaying information about the feature that may be utilized for changing the status of the document in the out-space user interface with the displayed status of the document. | 0.530172 |
7,606,782 | 1 | 29 | 1. A computer-based enterprise knowledge management system that represents and stores business knowledge in a natural language and generates program source code or rules to implement said business knowledge for use in business practices, comprising: at least one user interface for receiving said business knowledge in one or more sentences in a natural language; at least one user interface interactively presenting one or more statements from a knowledge manager and one or more production rules from a generator to the user via the user interface; at least one computer-readable memory, containing: (a) said knowledge manager programmed to represent said business knowledge as said at least one statement comprising at least one relationship, said relationship instantiating at least one relation having at least one role and at least one concept filling said role, wherein the relationships are defined using semantic modeling, wherein said representation of said business knowledge is accomplished using the Rete algorithm; and (b) said knowledge manager programmed to process said relationships semantically and syntactically; (c) said generator in communication with said knowledge manager to generate computer program code or production rules that combine syntactic and semantic constraints for implementing said business knowledge; and at least one tangible computer-readable storage medium selected from the group consisting of a temporary memory system and a permanent memory system for storing said statement and said computer program code or production rules to be integrated with external object models and databases. | 1. A computer-based enterprise knowledge management system that represents and stores business knowledge in a natural language and generates program source code or rules to implement said business knowledge for use in business practices, comprising: at least one user interface for receiving said business knowledge in one or more sentences in a natural language; at least one user interface interactively presenting one or more statements from a knowledge manager and one or more production rules from a generator to the user via the user interface; at least one computer-readable memory, containing: (a) said knowledge manager programmed to represent said business knowledge as said at least one statement comprising at least one relationship, said relationship instantiating at least one relation having at least one role and at least one concept filling said role, wherein the relationships are defined using semantic modeling, wherein said representation of said business knowledge is accomplished using the Rete algorithm; and (b) said knowledge manager programmed to process said relationships semantically and syntactically; (c) said generator in communication with said knowledge manager to generate computer program code or production rules that combine syntactic and semantic constraints for implementing said business knowledge; and at least one tangible computer-readable storage medium selected from the group consisting of a temporary memory system and a permanent memory system for storing said statement and said computer program code or production rules to be integrated with external object models and databases. 29. The system of claim 1 , wherein said interface is programmed to receive said business knowledge using one or more selected from the group consisting of voice recognition, keyboard input, and computer pointing device selection. | 0.673295 |
6,029,131 | 4 | 5 | 4. A method for generating synthetic speech, comprising; detecting natural timing boundaries in words to be spoken by a synthetic speech system, to produce natural timing intervals; identifying phonemes in said natural timing intervals; assigning first time durations for each of said phonemes; changing a selected first time duration of a selected phoneme to achieve a desired time duration for a selected natural timing interval containing said selected phoneme; and setting a plurality of said natural timing intervals to substantially the same second time duration, a particular phoneme having a computed time duration in response to number of phonemes within said selected natural timing interval and said second time durations; wherein at least said selected first time duration is based upon a predetermined parameter indicative of degree to which said selected first time duration may be adjusted without undesirably degrading speech produced by said system. | 4. A method for generating synthetic speech, comprising; detecting natural timing boundaries in words to be spoken by a synthetic speech system, to produce natural timing intervals; identifying phonemes in said natural timing intervals; assigning first time durations for each of said phonemes; changing a selected first time duration of a selected phoneme to achieve a desired time duration for a selected natural timing interval containing said selected phoneme; and setting a plurality of said natural timing intervals to substantially the same second time duration, a particular phoneme having a computed time duration in response to number of phonemes within said selected natural timing interval and said second time durations; wherein at least said selected first time duration is based upon a predetermined parameter indicative of degree to which said selected first time duration may be adjusted without undesirably degrading speech produced by said system. 5. The method of claim 4 further comprising: selecting each natural timing interval to be a respective syllable. | 0.633987 |
6,131,091 | 11 | 12 | 11. A method for evaluation of data relevance, comprising: (a) evaluating a document for relevance with regard to a list of specified topics; (b) using the relevance determination to create a topic-evaluation vector the topic-evaluation vector including a plurality of relevance determinations for a collection of data, each relevance determination in the plurality of relevance determinations pertaining to a topic; and (c) transmitting the topic-evaluation vector. | 11. A method for evaluation of data relevance, comprising: (a) evaluating a document for relevance with regard to a list of specified topics; (b) using the relevance determination to create a topic-evaluation vector the topic-evaluation vector including a plurality of relevance determinations for a collection of data, each relevance determination in the plurality of relevance determinations pertaining to a topic; and (c) transmitting the topic-evaluation vector. 12. The method of claim 11, further comprising: (e) transmitting the evaluated document along with the topic-evaluation vector. | 0.746 |
8,365,066 | 1 | 5 | 1. A processor-implemented method for storing formatting information for at least one cell in a spreadsheet document described in a markup language, wherein the spreadsheet document includes a plurality of style objects, the method comprising: parsing the spreadsheet document to generate at least one display list of a cell format object for the at least one cell by: obtaining cell formatting information for the at least one cell from a master style object that stores master formatting information for the at least one cell; obtaining named style information for the at least one cell from a style name object that stores named styles for the at least one cell and references the cell master style object; obtaining cell specific formatting information for the at least one cell from a cell-specific style object that includes cell specific formatting information for the at least one cell and references the master style object, wherein the cell specific formatting information overrides master formatting information; generating combined cell formatting information for the at least one cell in the cell format object, wherein the combined cell formatting information in the cell format object comprises named styles for the at least one cell, cell-specific formatting information that has overridden formatting information in the master style object, and master formatting information that has not been overridden by the cell-specific formatting information, wherein the formatting information originally described in the master style object but overridden by the cell-specific information is not included in the combined cell formatting information for the cell format object; and storing the combined cell formatting information as the at least one display list of the cell format object; and rasterizing the at least one cell in a frame buffer using the stored at least one display list of the cell format object. | 1. A processor-implemented method for storing formatting information for at least one cell in a spreadsheet document described in a markup language, wherein the spreadsheet document includes a plurality of style objects, the method comprising: parsing the spreadsheet document to generate at least one display list of a cell format object for the at least one cell by: obtaining cell formatting information for the at least one cell from a master style object that stores master formatting information for the at least one cell; obtaining named style information for the at least one cell from a style name object that stores named styles for the at least one cell and references the cell master style object; obtaining cell specific formatting information for the at least one cell from a cell-specific style object that includes cell specific formatting information for the at least one cell and references the master style object, wherein the cell specific formatting information overrides master formatting information; generating combined cell formatting information for the at least one cell in the cell format object, wherein the combined cell formatting information in the cell format object comprises named styles for the at least one cell, cell-specific formatting information that has overridden formatting information in the master style object, and master formatting information that has not been overridden by the cell-specific formatting information, wherein the formatting information originally described in the master style object but overridden by the cell-specific information is not included in the combined cell formatting information for the cell format object; and storing the combined cell formatting information as the at least one display list of the cell format object; and rasterizing the at least one cell in a frame buffer using the stored at least one display list of the cell format object. 5. The processor-implemented method of claim 1 , wherein the cell format object is used to render the cell. | 0.82107 |
8,510,656 | 1 | 6 | 1. A computer-based interactive storybook system, comprising: a processor executing a storybook program; a memory storing story data and image data associated with at least one story, each story including at least one user-modifiable scene; said story data including, for each user-modifiable scene, a static text portion and a plurality of alternative, user selectable text elements; said system having a first, word-based mode of operation wherein each user selectable text element is selectable by an end user to modify the story and alter the storyline while the story is in progress; said image data including, for each user-modifiable scene, a static image portion and a plurality of provisional image elements, wherein each of said provisional image elements is associated with a corresponding one of said user selectable text elements; said storybook program having a second, picture-based mode of operation wherein each of the plurality of image elements is selectable by the end user to modify the story and alter the storyline while the story is in progress; an input device for selecting from among said plurality of user selectable text elements; a display for displaying said story data and said image data; the storybook program configured to respond to the user selectable text elements selected via the first mode of operation and to cause the display of the static text portion in combination with the user selected provisional text elements and to cause the display to display the static image portion in combination with the provisional image element associated with the selected one of the user selectable provisional text elements; and the storybook program configured, responsive to one of the plurality of image elements being selected in the second mode of operation, to cause the display to display the static image portion in combination with the selected one of the provisional image elements and to cause the display to display the static text portion in combination with the user selectable text element that is associated with the selected one of the plurality of provisional image elements. | 1. A computer-based interactive storybook system, comprising: a processor executing a storybook program; a memory storing story data and image data associated with at least one story, each story including at least one user-modifiable scene; said story data including, for each user-modifiable scene, a static text portion and a plurality of alternative, user selectable text elements; said system having a first, word-based mode of operation wherein each user selectable text element is selectable by an end user to modify the story and alter the storyline while the story is in progress; said image data including, for each user-modifiable scene, a static image portion and a plurality of provisional image elements, wherein each of said provisional image elements is associated with a corresponding one of said user selectable text elements; said storybook program having a second, picture-based mode of operation wherein each of the plurality of image elements is selectable by the end user to modify the story and alter the storyline while the story is in progress; an input device for selecting from among said plurality of user selectable text elements; a display for displaying said story data and said image data; the storybook program configured to respond to the user selectable text elements selected via the first mode of operation and to cause the display of the static text portion in combination with the user selected provisional text elements and to cause the display to display the static image portion in combination with the provisional image element associated with the selected one of the user selectable provisional text elements; and the storybook program configured, responsive to one of the plurality of image elements being selected in the second mode of operation, to cause the display to display the static image portion in combination with the selected one of the provisional image elements and to cause the display to display the static text portion in combination with the user selectable text element that is associated with the selected one of the plurality of provisional image elements. 6. The system of claim 1 , further comprising: an authoring tool for one or both of creating a new story and editing said at least one story. | 0.654412 |
8,001,126 | 1 | 2 | 1. A system providing conversation persistence in real-time collaboration system comprising: a computing platform having hardware to perform a logical process; a transcript store portion of the computing platform configured to persistently store a transcript of real-time collaboration system messages for a first conversation thread in a first real-time collaboration system user interface, the first conversation thread having a beginning point and an ending point and a series of messages therebetween; a user interface portion of the computing platform configured to allow a user to specify conditions for a messaging client to automatically insert a continuation point between two messages within the first conversation thread; a portion of a user display of the computing platform configured to display an indicator proximate to an entry for the first conversation thread in the first real-time collaboration system user interface, the entry being shown in a hierarchical list of organized subjects of conversations, the indicator indicating storage of the transcript from the first conversation thread; a transcript retriever and copier portion of the computing platform configured to, responsive to operation of the indicator, automatically retrieve the stored transcript, and copy a portion of the first conversation thread into a second real-time collaboration system user interface, the copied portion being defined by at least two points selected from a group consisting of the beginning point, the continuation point, and the ending point; and a transcript resumer portion of the computing platform configured to append newly authored and received messages in the second real-time collaboration system user interface to the copied portion of the first conversation thread, wherein a second conversation thread of is provided in the second real-time collaboration system user interface having the copied portion of the first conversation thread, wherein the copied portion allows a user to be refreshed of a context of the first conversation thread. | 1. A system providing conversation persistence in real-time collaboration system comprising: a computing platform having hardware to perform a logical process; a transcript store portion of the computing platform configured to persistently store a transcript of real-time collaboration system messages for a first conversation thread in a first real-time collaboration system user interface, the first conversation thread having a beginning point and an ending point and a series of messages therebetween; a user interface portion of the computing platform configured to allow a user to specify conditions for a messaging client to automatically insert a continuation point between two messages within the first conversation thread; a portion of a user display of the computing platform configured to display an indicator proximate to an entry for the first conversation thread in the first real-time collaboration system user interface, the entry being shown in a hierarchical list of organized subjects of conversations, the indicator indicating storage of the transcript from the first conversation thread; a transcript retriever and copier portion of the computing platform configured to, responsive to operation of the indicator, automatically retrieve the stored transcript, and copy a portion of the first conversation thread into a second real-time collaboration system user interface, the copied portion being defined by at least two points selected from a group consisting of the beginning point, the continuation point, and the ending point; and a transcript resumer portion of the computing platform configured to append newly authored and received messages in the second real-time collaboration system user interface to the copied portion of the first conversation thread, wherein a second conversation thread of is provided in the second real-time collaboration system user interface having the copied portion of the first conversation thread, wherein the copied portion allows a user to be refreshed of a context of the first conversation thread. 2. The system as set forth in claim 1 further comprising a portion of a messaging server configured to associate the persistently stored transcript of real-time collaboration system messages with one or more items in a list of conversational items. | 0.589404 |
8,880,403 | 12 | 15 | 12. A system for transcribing a communication, comprising: a device, including: a memory containing a program for transcribing speech; and a processor which, when executing the program, performs an operation comprising: receiving a spoken first communication from a first sender to a first recipient; obtaining information relating to a second communication from a second sender to a second recipient, wherein the second communication was made before the spoken first communication and is different from the first spoken communication; using the obtained information to create a final language model by: obtaining a general language model; using the obtained information to create a specific language model; and creating the final language model using the general language model and the specific language model; and using the language model to transcribe the spoken first communication. | 12. A system for transcribing a communication, comprising: a device, including: a memory containing a program for transcribing speech; and a processor which, when executing the program, performs an operation comprising: receiving a spoken first communication from a first sender to a first recipient; obtaining information relating to a second communication from a second sender to a second recipient, wherein the second communication was made before the spoken first communication and is different from the first spoken communication; using the obtained information to create a final language model by: obtaining a general language model; using the obtained information to create a specific language model; and creating the final language model using the general language model and the specific language model; and using the language model to transcribe the spoken first communication. 15. The system of claim 12 , wherein the obtained information includes information about a news event. | 0.75122 |
9,607,303 | 13 | 20 | 13. One or more non-transitory computer readable media having instructions stored thereon that, when executed by an apparatus, cause the apparatus to: receive a first transmission comprising data from a first content provider and a second transmission comprising data from a second content provider; determine a first context for a first message to be transmitted from the apparatus to a consumer computing device, wherein the first context defines a meaning of first payload data included in the first message; generate a first message, wherein the first message is structured according to: a transport layer defining one or more interaction paradigms for categorizing interactions and defining a plurality of message types, wherein each message type of the plurality of message types includes a set of attributes that comprises at least a message attribute and a transport attribute; a data layer defining one or more data formats, wherein the plurality of message types include first payload data formatted according to at least one of the one or more data formats; and a first domain message layer that defines a first set of the plurality of message types used to generate messages between the consumer computing device and the apparatus for the first context; send the first message to the consumer computing device; determine a second context different from the first context for a second message to be transmitted from the apparatus to the consumer computing device, wherein the second context defines a meaning of second payload data included in the second message; generate a second message, wherein the second message is structured according to the transport layer, the data layer, and a second domain message layer that defines, for the second context, a second set of the plurality of message types different from the first set of the plurality of message types; and send the second message to the consumer computing device, wherein the first domain message layer includes the item type model and a content definition model, wherein the content definition model defines at least one of a field meaning or a field relationship for a field used by the item type model. | 13. One or more non-transitory computer readable media having instructions stored thereon that, when executed by an apparatus, cause the apparatus to: receive a first transmission comprising data from a first content provider and a second transmission comprising data from a second content provider; determine a first context for a first message to be transmitted from the apparatus to a consumer computing device, wherein the first context defines a meaning of first payload data included in the first message; generate a first message, wherein the first message is structured according to: a transport layer defining one or more interaction paradigms for categorizing interactions and defining a plurality of message types, wherein each message type of the plurality of message types includes a set of attributes that comprises at least a message attribute and a transport attribute; a data layer defining one or more data formats, wherein the plurality of message types include first payload data formatted according to at least one of the one or more data formats; and a first domain message layer that defines a first set of the plurality of message types used to generate messages between the consumer computing device and the apparatus for the first context; send the first message to the consumer computing device; determine a second context different from the first context for a second message to be transmitted from the apparatus to the consumer computing device, wherein the second context defines a meaning of second payload data included in the second message; generate a second message, wherein the second message is structured according to the transport layer, the data layer, and a second domain message layer that defines, for the second context, a second set of the plurality of message types different from the first set of the plurality of message types; and send the second message to the consumer computing device, wherein the first domain message layer includes the item type model and a content definition model, wherein the content definition model defines at least one of a field meaning or a field relationship for a field used by the item type model. 20. The non-transitory computer readable media of claim 13 , wherein the apparatus has compressed the payload data by removing an element common to each record of a plurality of records in the payload data. | 0.810662 |
9,298,811 | 1 | 2 | 1. A method for providing a voice application, comprising: executing control flow logic modeling a dialog flow with a user via a voice browser, the control flow logic producing a disambiguation/confirmation requirement; initiating a disambiguation/confirmation module in response to the disambiguation/confirmation requirement; sending a set of at least two candidates and partitioning criteria from the control flow logic to the disambiguation/confirmation module; analyzing attributes of the set of candidates to determine a partitioning score for each attribute indicative of that attribute's ability to distinguish between the at least two candidates based on the partitioning criteria; sorting the attributes based on their corresponding partitioning scores; querying the user based on a top-sorted attribute and using results of the query to at least reduce the set of candidates; repeating the steps of analyzing, sorting, and querying until the set of candidates is reduced to a single candidate; and returning the single candidate from the disambiguation/confirmation module to the control flow logic for continued execution. | 1. A method for providing a voice application, comprising: executing control flow logic modeling a dialog flow with a user via a voice browser, the control flow logic producing a disambiguation/confirmation requirement; initiating a disambiguation/confirmation module in response to the disambiguation/confirmation requirement; sending a set of at least two candidates and partitioning criteria from the control flow logic to the disambiguation/confirmation module; analyzing attributes of the set of candidates to determine a partitioning score for each attribute indicative of that attribute's ability to distinguish between the at least two candidates based on the partitioning criteria; sorting the attributes based on their corresponding partitioning scores; querying the user based on a top-sorted attribute and using results of the query to at least reduce the set of candidates; repeating the steps of analyzing, sorting, and querying until the set of candidates is reduced to a single candidate; and returning the single candidate from the disambiguation/confirmation module to the control flow logic for continued execution. 2. The method of claim 1 , wherein the control flow logic incorporates business process modeling (BPM). | 0.880787 |
9,373,030 | 20 | 21 | 20. A system comprising: a processor; and a memory communicatively coupled to the processor, the memory storing instructions executable to perform a method, the method including: receiving an image of an identity document, the image being produced using a video stream; improving the image, wherein the improving includes removing blurring, adjusting brightness, and adjusting colors; recognizing a plurality of text elements in the image using optical character recognition; finding a document template of a plurality of templates having a high degree of coincidence with the image using a substantially rectangular shape of the image overall, at least one of the text elements, and a respective location in the image for the at least one text element; associating each of the text elements with a respective field of the document template using the text elements and a respective location in the image for each of the text elements; placing at least one of the associated text elements in a respective field of a form, the respective field of the form corresponding to the respective associated field of the document template; and making the completed form accessible on the system. | 20. A system comprising: a processor; and a memory communicatively coupled to the processor, the memory storing instructions executable to perform a method, the method including: receiving an image of an identity document, the image being produced using a video stream; improving the image, wherein the improving includes removing blurring, adjusting brightness, and adjusting colors; recognizing a plurality of text elements in the image using optical character recognition; finding a document template of a plurality of templates having a high degree of coincidence with the image using a substantially rectangular shape of the image overall, at least one of the text elements, and a respective location in the image for the at least one text element; associating each of the text elements with a respective field of the document template using the text elements and a respective location in the image for each of the text elements; placing at least one of the associated text elements in a respective field of a form, the respective field of the form corresponding to the respective associated field of the document template; and making the completed form accessible on the system. 21. The system of claim 20 wherein the method further includes: ascertaining an authenticity characteristic in the image; and providing the authenticity characteristic for biometric verification. | 0.708084 |
9,971,960 | 1 | 2 | 1. A method for providing gesture recognition services to a user application, comprising: storing sets of training data in a database at a server, the training data received from a sensor associated with the user application, the training data being indicative of characteristics of a gesture, the user application running on a client device; training a gesture recognition algorithm with the sets of training data to generate a trained gesture recognition algorithm, wherein the output of the trained gesture recognition algorithm is an indication of the gesture and the gesture recognition algorithm is a neural network; storing the trained gesture recognition algorithm in a client library at the server; receiving raw data from the sensor via the user application and storing the raw data in the client library; applying the trained gesture recognition algorithm to the raw data; and, when the trained gesture recognition algorithm recognizes the gesture, sending the indication of the gesture from the client library to the user application. | 1. A method for providing gesture recognition services to a user application, comprising: storing sets of training data in a database at a server, the training data received from a sensor associated with the user application, the training data being indicative of characteristics of a gesture, the user application running on a client device; training a gesture recognition algorithm with the sets of training data to generate a trained gesture recognition algorithm, wherein the output of the trained gesture recognition algorithm is an indication of the gesture and the gesture recognition algorithm is a neural network; storing the trained gesture recognition algorithm in a client library at the server; receiving raw data from the sensor via the user application and storing the raw data in the client library; applying the trained gesture recognition algorithm to the raw data; and, when the trained gesture recognition algorithm recognizes the gesture, sending the indication of the gesture from the client library to the user application. 2. The method of claim 1 , wherein communications between the server and the user application are by way of an application programming interface (“API”), the client library being associated with the API. | 0.662791 |
9,792,563 | 3 | 10 | 3. A system for defining a human resources system, comprising: a processor; a storage module for storing data associated with the human resources system; and a memory coupled with the processor, wherein the memory is configured to provide the processor with instructions which when executed cause the processor to: receive at least one new metadata model that defines at least one new object class in the human resource system, wherein the new metadata model includes one or more attributes, one or more relationships, and one or more methods associated with the new object class; receive process definitions; store the new metadata model including data associated with the new metadata model, and the process definitions in a minimalistic metamodel for persistence, wherein the minimalistic metamodel for persistence comprises three tables comprising an instance table, an attribute table, and a reference table for all of the objects in the human resources system, wherein the new metadata model including data associated with the new metadata model is stored by storing one or more instances of the new object class in the instance table, the one or more attributes in the attribute table, and the one or more relationships in the reference table, wherein: the instance table stores all instances of object classes in the human resource system as defined by a plurality of metadata models; the attribute table stores attribute data associated with all the instances of the object classes as defined by the plurality of metadata models; the reference table stores relationship data associated with all the instances of the object classes as defined by the plurality of metadata models; the instance table, the attribute table, and the reference table store data that has been specified; metadata model definitions and the process definitions are able to be interpreted using an interpretive engine; and the interpretive engine is configured to process the metadata model definitions and process definitions without compilation of any code; at a time of execution by the interpretive engine, all the objects specified in the instance table, the attribute table, and the reference table and processes are loaded into the memory for easy modification of instances of objects defined by the plurality of metadata models and the new metadata model; and for a process of one or more processes defined by the process definitions: defining an element to which the process responds; defining one or more process steps in response to the element; and defining an output response, wherein the process when interpreted by the interpretive engine are sufficient to define a fully functional human resource system; receive an update, wherein the update includes a change to an existing instance of an object class in the human resource system; update the human resource system by adding, removing, or changing a plurality of entries associated with the existing instance of the object class in at least one of the instance table, the attribute table, and the reference table, comprising: validate a transaction request relating to the existing instance of the object class, comprising: ensure a requestor has privileges to perform a requested transaction; check whether the transaction request corresponds to a metadata definition of an element of the transaction request; and ensure that data in the requested transaction is of a correct type and in a correct range of values; determine whether a controlling object to be updated exists, wherein the instances of the object class are organized in a tree structure, the controlling object relating to a trunk of the tree structure; in the event that the controlling object to be updated does not exist create the controlling object; and in the event that the controlling object to be updated exists, locate the controlling object associated with an instance of the object class; transfer the plurality of entries associated with the existing instance of the object class in the at least one of the instance table, the attribute table, and the reference table to the storage module after the updating of the human resource system is performed, wherein the transferring of the plurality of entries to the storage module is performed after each of the adding, removing, or changing to the plurality of entries have been completed to avoid inconsistencies in the human resource system the storage module including permanent storage; and execute the updated human resources system by interpreting the stored metadata model definitions and process definitions using the interpretive engine. | 3. A system for defining a human resources system, comprising: a processor; a storage module for storing data associated with the human resources system; and a memory coupled with the processor, wherein the memory is configured to provide the processor with instructions which when executed cause the processor to: receive at least one new metadata model that defines at least one new object class in the human resource system, wherein the new metadata model includes one or more attributes, one or more relationships, and one or more methods associated with the new object class; receive process definitions; store the new metadata model including data associated with the new metadata model, and the process definitions in a minimalistic metamodel for persistence, wherein the minimalistic metamodel for persistence comprises three tables comprising an instance table, an attribute table, and a reference table for all of the objects in the human resources system, wherein the new metadata model including data associated with the new metadata model is stored by storing one or more instances of the new object class in the instance table, the one or more attributes in the attribute table, and the one or more relationships in the reference table, wherein: the instance table stores all instances of object classes in the human resource system as defined by a plurality of metadata models; the attribute table stores attribute data associated with all the instances of the object classes as defined by the plurality of metadata models; the reference table stores relationship data associated with all the instances of the object classes as defined by the plurality of metadata models; the instance table, the attribute table, and the reference table store data that has been specified; metadata model definitions and the process definitions are able to be interpreted using an interpretive engine; and the interpretive engine is configured to process the metadata model definitions and process definitions without compilation of any code; at a time of execution by the interpretive engine, all the objects specified in the instance table, the attribute table, and the reference table and processes are loaded into the memory for easy modification of instances of objects defined by the plurality of metadata models and the new metadata model; and for a process of one or more processes defined by the process definitions: defining an element to which the process responds; defining one or more process steps in response to the element; and defining an output response, wherein the process when interpreted by the interpretive engine are sufficient to define a fully functional human resource system; receive an update, wherein the update includes a change to an existing instance of an object class in the human resource system; update the human resource system by adding, removing, or changing a plurality of entries associated with the existing instance of the object class in at least one of the instance table, the attribute table, and the reference table, comprising: validate a transaction request relating to the existing instance of the object class, comprising: ensure a requestor has privileges to perform a requested transaction; check whether the transaction request corresponds to a metadata definition of an element of the transaction request; and ensure that data in the requested transaction is of a correct type and in a correct range of values; determine whether a controlling object to be updated exists, wherein the instances of the object class are organized in a tree structure, the controlling object relating to a trunk of the tree structure; in the event that the controlling object to be updated does not exist create the controlling object; and in the event that the controlling object to be updated exists, locate the controlling object associated with an instance of the object class; transfer the plurality of entries associated with the existing instance of the object class in the at least one of the instance table, the attribute table, and the reference table to the storage module after the updating of the human resource system is performed, wherein the transferring of the plurality of entries to the storage module is performed after each of the adding, removing, or changing to the plurality of entries have been completed to avoid inconsistencies in the human resource system the storage module including permanent storage; and execute the updated human resources system by interpreting the stored metadata model definitions and process definitions using the interpretive engine. 10. A system as in claim 3 , wherein processes include one or more elements to respond to. | 0.951974 |
8,615,707 | 15 | 16 | 15. The apparatus of claim 14 , wherein formulating the collection of attribute suggestions comprises comparing characteristics of a preexisting structured presentation with content of electronic documents in the electronic document collection. | 15. The apparatus of claim 14 , wherein formulating the collection of attribute suggestions comprises comparing characteristics of a preexisting structured presentation with content of electronic documents in the electronic document collection. 16. The apparatus of claim 15 , wherein formulating the collection of attribute suggestions comprises identifying documents in the electronic document collection that include structured components that characterize instances identified in the preexisting structured presentation. | 0.654703 |
7,891,003 | 1 | 6 | 1. A method for generating a threat model for a software application, comprising: receiving application modeling data in a user interface, the application modeling data defines a software application that includes components and one or more calls, a call identifies a caller, first data affected by the call, an action taken by the caller with respect to the first data, and at least one of the components affected by the action of the caller; providing, in the user interface, a list of pre-defined attributes that are relevant to threats; receiving a selection of at least one of the pre-defined attributes, the selection associating the selected pre-defined attribute with a first component of the components; determining allowable actions based on the definitions of the calls in the application modeling data; automatically generating threat information based on the application modeling data, the allowed actions, the selected at least one pre-defined attribute, and an attack library, the attack library includes attacks that are associated with the pre-defined attributes, the automatically generating threat information includes identifying attacks in the attack library that are associated with the selected pre-defined attribute; and providing, in the user interface, countermeasures associated with the threat information. | 1. A method for generating a threat model for a software application, comprising: receiving application modeling data in a user interface, the application modeling data defines a software application that includes components and one or more calls, a call identifies a caller, first data affected by the call, an action taken by the caller with respect to the first data, and at least one of the components affected by the action of the caller; providing, in the user interface, a list of pre-defined attributes that are relevant to threats; receiving a selection of at least one of the pre-defined attributes, the selection associating the selected pre-defined attribute with a first component of the components; determining allowable actions based on the definitions of the calls in the application modeling data; automatically generating threat information based on the application modeling data, the allowed actions, the selected at least one pre-defined attribute, and an attack library, the attack library includes attacks that are associated with the pre-defined attributes, the automatically generating threat information includes identifying attacks in the attack library that are associated with the selected pre-defined attribute; and providing, in the user interface, countermeasures associated with the threat information. 6. The method of claim 1 , further comprising determining un-allowable actions based on the allowable actions, wherein the determining un-allowable actions includes: determining an unauthorized disclosure that is a variation of one of the allowed actions. | 0.5 |
8,601,079 | 3 | 4 | 3. The network device of claim 1 , wherein the processor enables further actions, the actions comprising: receiving, from the user, a request to attach a file to the message; displaying at least a first level of tags within the PHST to the user; enabling the user to expand or collapse at least the first level of tags to display at least a second level of tags within the PHST to the user; receiving, from the user, a tag selection of a tag from within the PHST; and attaching, to the message, at least one file associated with the selected tag. | 3. The network device of claim 1 , wherein the processor enables further actions, the actions comprising: receiving, from the user, a request to attach a file to the message; displaying at least a first level of tags within the PHST to the user; enabling the user to expand or collapse at least the first level of tags to display at least a second level of tags within the PHST to the user; receiving, from the user, a tag selection of a tag from within the PHST; and attaching, to the message, at least one file associated with the selected tag. 4. The network device of claim 3 , wherein attaching the at least one file further comprises attaching a plurality of files associated with the selected tag from a plurality of received messages. | 0.528986 |
6,070,007 | 57 | 58 | 57. The computer-readable medium of claim 55, further comprising: when the current selection is the selection of the computational construct representing the terminal operand in the right selection mode and the user inputs a second indicator, setting the current selection to the selection of a parent computational construct of the computational construct representing the terminal operand in the tree selection mode. | 57. The computer-readable medium of claim 55, further comprising: when the current selection is the selection of the computational construct representing the terminal operand in the right selection mode and the user inputs a second indicator, setting the current selection to the selection of a parent computational construct of the computational construct representing the terminal operand in the tree selection mode. 58. The computer-readable medium of claim 57 wherein the first indicator is a tab and the second indicator is a shift-tab. | 0.5 |
7,925,507 | 12 | 13 | 12. The method of claim 11 , further comprising a partial name derivation unit configured to derive partial names from one or more of the names from the first set of full names and the second set of full names. | 12. The method of claim 11 , further comprising a partial name derivation unit configured to derive partial names from one or more of the names from the first set of full names and the second set of full names. 13. The method of claim 12 , wherein the first set of full names and the second set of full names and the partial names are combined to generate a name model. | 0.5 |
8,387,024 | 5 | 6 | 5. A computer implemented method of testing an operation of a software product, comprising: receiving an indication of whether a native language of a human tester matches a target language of a software product to be tested; receiving a testing parameter, wherein the testing parameter comprises an attribute that defines a type of test case to be used in testing the software product; if the native language and the target language are different: generating a test case in the target language based upon the received testing parameter, wherein the test case comprises an input, an action corresponding to the testing parameter, and an expected output having a format corresponding to a language-specific format rule for the action in the target language, and wherein the expected output is determined based upon the testing parameter, the input, and the action, applying the test case to the software product by entering the input into a computing device that is running the software product, and receiving a generated output after the software product implements the action, analyzing the generated output to determine whether the generated output matches the expected output as defined by the testing parameter, and displaying an indication of whether the generated output matches the expected output as defined by the testing parameter; and if the native language and the target language are the same: analyzing a generated output to determine whether the generated output matches an expected output as defined by the testing parameter, and displaying an indication of whether the generated output matches the expected output as defined by the testing parameter. | 5. A computer implemented method of testing an operation of a software product, comprising: receiving an indication of whether a native language of a human tester matches a target language of a software product to be tested; receiving a testing parameter, wherein the testing parameter comprises an attribute that defines a type of test case to be used in testing the software product; if the native language and the target language are different: generating a test case in the target language based upon the received testing parameter, wherein the test case comprises an input, an action corresponding to the testing parameter, and an expected output having a format corresponding to a language-specific format rule for the action in the target language, and wherein the expected output is determined based upon the testing parameter, the input, and the action, applying the test case to the software product by entering the input into a computing device that is running the software product, and receiving a generated output after the software product implements the action, analyzing the generated output to determine whether the generated output matches the expected output as defined by the testing parameter, and displaying an indication of whether the generated output matches the expected output as defined by the testing parameter; and if the native language and the target language are the same: analyzing a generated output to determine whether the generated output matches an expected output as defined by the testing parameter, and displaying an indication of whether the generated output matches the expected output as defined by the testing parameter. 6. The computer implemented method of claim 5 , wherein the action comprises one or more of the following: sorting, generating a date, generating a time, converting a number to a representation of currency, inserting punctuation, adding a keystroke, and correcting pronunciation. | 0.5 |
7,877,343 | 28 | 29 | 28. A system for automatically extracting relational information from a corpus of text without specifying criteria or patterns for controlling extraction of the relational information, comprising: (a) a memory in which a plurality of machine instructions are stored; (b) a storage in which a corpus of text is stored; (c) an interface for coupling to the storage; and (d) a processor that is coupled to the memory and also coupled to the storage through the interface, the processor executing the machine instructions stored in the memory to carry out a plurality of functions, including: (i) employing a first module that determines a set of linguistic features that are domain independent and which can be used to extract relationships between objects from text; and (ii) employing a second module that uses an extractor and the linguistic features to automatically extract a plurality of tuples from the corpus of text, each tuple including a plurality of objects connected by at least one relationship, wherein the extractor provides the plurality of tuples by tagging at least a portion of words within the corpus of text with each tagged word's most probable part of speech, without parsing the corpus of text and without generating a parse tree. | 28. A system for automatically extracting relational information from a corpus of text without specifying criteria or patterns for controlling extraction of the relational information, comprising: (a) a memory in which a plurality of machine instructions are stored; (b) a storage in which a corpus of text is stored; (c) an interface for coupling to the storage; and (d) a processor that is coupled to the memory and also coupled to the storage through the interface, the processor executing the machine instructions stored in the memory to carry out a plurality of functions, including: (i) employing a first module that determines a set of linguistic features that are domain independent and which can be used to extract relationships between objects from text; and (ii) employing a second module that uses an extractor and the linguistic features to automatically extract a plurality of tuples from the corpus of text, each tuple including a plurality of objects connected by at least one relationship, wherein the extractor provides the plurality of tuples by tagging at least a portion of words within the corpus of text with each tagged word's most probable part of speech, without parsing the corpus of text and without generating a parse tree. 29. The system of claim 28 , wherein the machine instructions further cause the processor to determine the linguistic features automatically without using manually input tagged examples, and without manual intervention. | 0.758811 |
9,418,331 | 12 | 16 | 12. An apparatus, comprising: at least one processor configured to identify a first network comprising one or more indexed classes of artificial neurons and determine one or more tags for the one or more indexed classes of artificial neurons regardless of their indexing, wherein the at least one processor is configured to determine the one or more tags for the one or more indexed classes of artificial neurons by: augmenting the first network with a second network comprising one or more artificial neurons, wherein each neuron in the second network corresponds to a tag; connecting each of the one or more indexed classes of artificial neurons to all the neurons in the second network with one or more plastic connections; and providing supervisory bias signals to the one or more indexed classes of artificial neurons via the plastic connections, such that the supervisory signal imposes a desired mapping between classes and output layer neurons; and a memory coupled with the at least one processor. | 12. An apparatus, comprising: at least one processor configured to identify a first network comprising one or more indexed classes of artificial neurons and determine one or more tags for the one or more indexed classes of artificial neurons regardless of their indexing, wherein the at least one processor is configured to determine the one or more tags for the one or more indexed classes of artificial neurons by: augmenting the first network with a second network comprising one or more artificial neurons, wherein each neuron in the second network corresponds to a tag; connecting each of the one or more indexed classes of artificial neurons to all the neurons in the second network with one or more plastic connections; and providing supervisory bias signals to the one or more indexed classes of artificial neurons via the plastic connections, such that the supervisory signal imposes a desired mapping between classes and output layer neurons; and a memory coupled with the at least one processor. 16. The apparatus of claim 12 , wherein each of the indexed classes of artificial neurons correspond to one or more tags. | 0.783929 |
8,874,516 | 14 | 16 | 14. A computer program product for replicating IP address assignment changes in a distributed database having a plurality of nodes, the computer program product being embodied in a non-transitory computer readable medium and comprising computer instructions for: receiving a semantic command at a first node having a first local version of the database, wherein the semantic command comprises a semantically expressed request to modify one or more IP address assignments in the database that allows for provisional modification of the first local version of the database before sending the semantic command to a master node having a master version of the database; and provisionally applying the semantic command to the first local version of the database before sending the semantic command to the master node, wherein the provisional applying the semantic command to the first local version of the database comprises modifying the first local version of the database before reconciling the modification with the master node, and wherein if the semantic command includes any IP address assignment changes that would result in an IP address assignment conflict with IP address assignment data stored in the master version of the database on the master node, then the semantic command is not applied to the master node. | 14. A computer program product for replicating IP address assignment changes in a distributed database having a plurality of nodes, the computer program product being embodied in a non-transitory computer readable medium and comprising computer instructions for: receiving a semantic command at a first node having a first local version of the database, wherein the semantic command comprises a semantically expressed request to modify one or more IP address assignments in the database that allows for provisional modification of the first local version of the database before sending the semantic command to a master node having a master version of the database; and provisionally applying the semantic command to the first local version of the database before sending the semantic command to the master node, wherein the provisional applying the semantic command to the first local version of the database comprises modifying the first local version of the database before reconciling the modification with the master node, and wherein if the semantic command includes any IP address assignment changes that would result in an IP address assignment conflict with IP address assignment data stored in the master version of the database on the master node, then the semantic command is not applied to the master node. 16. A computer program product as recited in claim 14 , the computer program product further comprising further including interpreting the semantic command, including determining an operation associated with the semantic command, wherein the semantic command is defined by one or more instructions or operations. | 0.657143 |
9,984,116 | 14 | 17 | 14. A computer system comprising: one or more hardware processors, one or more computer-readable memories, and one or more computer-readable, tangible storage devices; program instructions, stored on at least one of the one or more storage devices for execution by at least one of the one or more processors via at least one of the one or more memories, to perform natural language processing and semantic processing on a natural language query to identify data sets relevant to the natural language query; program instructions, stored on at least one of the one or more storage devices for execution by at least one of the one or more processors via at least one of the one or more memories, group the data sets into one or more query domains based at least in part on one or more relationships among the data sets, wherein each query domain includes a data set comprising a fact table that has one-to-many cardinality with a plurality of other data sets and no many-to-one cardinality with any data set, and one or more data sets each having a direct many-to-one cardinality relationship with the fact table; program instructions, stored on at least one of the one or more storage devices for execution by at least one of the one or more processors via at least one of the one or more memories, to prioritize the one or more query domains; and program instructions, stored on at least one of the one or more storage devices for execution by at least one of the one or more processors via at least one of the one or more memories, to load the one or more query domains in an order based on the prioritizing of the query domains. | 14. A computer system comprising: one or more hardware processors, one or more computer-readable memories, and one or more computer-readable, tangible storage devices; program instructions, stored on at least one of the one or more storage devices for execution by at least one of the one or more processors via at least one of the one or more memories, to perform natural language processing and semantic processing on a natural language query to identify data sets relevant to the natural language query; program instructions, stored on at least one of the one or more storage devices for execution by at least one of the one or more processors via at least one of the one or more memories, group the data sets into one or more query domains based at least in part on one or more relationships among the data sets, wherein each query domain includes a data set comprising a fact table that has one-to-many cardinality with a plurality of other data sets and no many-to-one cardinality with any data set, and one or more data sets each having a direct many-to-one cardinality relationship with the fact table; program instructions, stored on at least one of the one or more storage devices for execution by at least one of the one or more processors via at least one of the one or more memories, to prioritize the one or more query domains; and program instructions, stored on at least one of the one or more storage devices for execution by at least one of the one or more processors via at least one of the one or more memories, to load the one or more query domains in an order based on the prioritizing of the query domains. 17. The computer system of claim 14 , further comprising program instructions to present, in a user interface, one or more user menus for user-enabled filtering of the one or more query domains. | 0.642066 |
7,542,973 | 1 | 7 | 1. A computer program product for adaptive matching of records in a data repository comprising: a computer usable memory medium having computer readable program code embodied therein wherein said computer readable program code comprises a matching executable unit configured to: present at least one field common to a first record and a second record wherein said at least one field is used to perform a match between said first record and said second record and wherein said at least one field is presented to a user; obtain a first selected field from said first record and a second selected field from said second record wherein said first selected field and said second selected field is obtained from said user; obtain a first data entry in said first selected field for said first record, said first data entry comprising a first string; tokenize said first string to retrieve a first tokenized data entry string; obtain a second data entry in said second selected field for said second record, said second data entry comprising a second string; tokenize said second string to retrieve a second tokenized data entry string; exclude at least one character from said first tokenized data entry string for utilization in said match that involves said first selected field and said second selected field; exclude at least one different character with respect to said at least one character from said second tokenized data entry string for utilization in said match that involves said first selected field and said second selected field; remove frequently used strings from said first tokenized data entry string and from said second tokenized data entry string; normalize data from said first selected field and from said second selected field to cleanse strings; accept a first list of tokens desired for said match to occur utilizing said first selected field; accept a second list of tokens desired for said match to occur utilizing said second selected field; assign weights to each token in said first list of tokens and each token in said second list of tokens; calculate a score for said match through summation of said weights for each token occurring in said first tokenized data entry string and said first record and for each token that occurs in said second tokenized data entry string and said second record; generate a group of similar records when said score is above a threshold; display said group of similar records to said user; learn at least one token that is relevant; learn at least one weight that results in a match; and learn at least one match criteria appropriate for said match for use in future matching based on user input regarding said score. | 1. A computer program product for adaptive matching of records in a data repository comprising: a computer usable memory medium having computer readable program code embodied therein wherein said computer readable program code comprises a matching executable unit configured to: present at least one field common to a first record and a second record wherein said at least one field is used to perform a match between said first record and said second record and wherein said at least one field is presented to a user; obtain a first selected field from said first record and a second selected field from said second record wherein said first selected field and said second selected field is obtained from said user; obtain a first data entry in said first selected field for said first record, said first data entry comprising a first string; tokenize said first string to retrieve a first tokenized data entry string; obtain a second data entry in said second selected field for said second record, said second data entry comprising a second string; tokenize said second string to retrieve a second tokenized data entry string; exclude at least one character from said first tokenized data entry string for utilization in said match that involves said first selected field and said second selected field; exclude at least one different character with respect to said at least one character from said second tokenized data entry string for utilization in said match that involves said first selected field and said second selected field; remove frequently used strings from said first tokenized data entry string and from said second tokenized data entry string; normalize data from said first selected field and from said second selected field to cleanse strings; accept a first list of tokens desired for said match to occur utilizing said first selected field; accept a second list of tokens desired for said match to occur utilizing said second selected field; assign weights to each token in said first list of tokens and each token in said second list of tokens; calculate a score for said match through summation of said weights for each token occurring in said first tokenized data entry string and said first record and for each token that occurs in said second tokenized data entry string and said second record; generate a group of similar records when said score is above a threshold; display said group of similar records to said user; learn at least one token that is relevant; learn at least one weight that results in a match; and learn at least one match criteria appropriate for said match for use in future matching based on user input regarding said score. 7. The computer program product of claim 1 wherein said computer readable program code is further configured to: accept input that signifies if said first list of tokens is required to match in non-sequential order. | 0.65981 |
8,219,438 | 1 | 15 | 1. A method for determining a person's response to a retail element, based on the person's facial expression and shopping behavior, comprising the following steps of: a) detecting and tracking a face from first input images captured by at least a first means for capturing images, estimating two-dimensional and three-dimensional poses of the face, and localizing facial features, using at least a control and processing system, b) estimating gaze direction of the person using the two-dimensional and three-dimensional poses and positions of the facial features and changes in affective state of the person by extracting emotion-sensitive features, and recognizing a demographic category of the person, c) detecting and tracking the person from second input images captured by at least a second means for capturing images, producing a trajectory of the person, and estimating body orientation, using the control and processing system, d) identifying the shopping behaviors of the person toward the retail element, utilizing position and the body orientation of the person relative to the retail element, and e) determining intermediate responses and end response of the person to the retail element by analyzing the changes in affective states and interest, in the context of the shopping behavior and the demographics category of the person, wherein the first means for capturing images and the second means for capturing images are connected to the control and processing system via at least a means for video interface, and wherein the shopping behaviors include showing interest, engagement, interaction, or purchasing. | 1. A method for determining a person's response to a retail element, based on the person's facial expression and shopping behavior, comprising the following steps of: a) detecting and tracking a face from first input images captured by at least a first means for capturing images, estimating two-dimensional and three-dimensional poses of the face, and localizing facial features, using at least a control and processing system, b) estimating gaze direction of the person using the two-dimensional and three-dimensional poses and positions of the facial features and changes in affective state of the person by extracting emotion-sensitive features, and recognizing a demographic category of the person, c) detecting and tracking the person from second input images captured by at least a second means for capturing images, producing a trajectory of the person, and estimating body orientation, using the control and processing system, d) identifying the shopping behaviors of the person toward the retail element, utilizing position and the body orientation of the person relative to the retail element, and e) determining intermediate responses and end response of the person to the retail element by analyzing the changes in affective states and interest, in the context of the shopping behavior and the demographics category of the person, wherein the first means for capturing images and the second means for capturing images are connected to the control and processing system via at least a means for video interface, and wherein the shopping behaviors include showing interest, engagement, interaction, or purchasing. 15. The method according to claim 1 , wherein the method further comprises a step of detecting the person's engagement with the retail element based on a trajectory from tracking the person and the body orientation of the person. | 0.682825 |
9,529,795 | 10 | 11 | 10. A system comprising: a. a processor; b. a memory coupled to the processor; c. a program stored in the memory for execution by the processor, the program configured to: i. identify, by a ranking module, a first statistically generated template matching a set of domain tags, the first statistically generated template being stored in a memory; ii. identify, by the ranking module, a second statistically generated template matching the set of domain tags, the second statistically generated template being stored in the memory; iii. select, by the ranking module, the first statistically generated template instead of the second statistically generated template; iv. generate, by the ranking module, a set of natural language text by inserting a set of information associated with a record into the first statistically generated template, the set of natural language text being stored in memory; and v. provide, by a delivery module, the set of natural language text; wherein the first statistically generated template and the second statistically generated template were generated by: 1. receiving a corpus comprising a set of pre-segmented texts; 2. creating a plurality of modified pre-segmented texts for the set of pre-segmented texts by: a. extracting a set of semantic terms for each pre-segmented text within the set of pre-segmented texts; and b. applying at least one domain tag for each pre-segmented text within the set of pre-segmented texts; and 3. applying a k-means clustering technique to cluster the plurality of modified pre-segmented texts into one or more conceptual units, the k-means clustering technique including: a. placing k points into the space represented by a set of modified pre-segmented texts that are being clustered, the k points representing initial group centroids; b. assigning each of the set of modified pre-segmented texts to the group having the closest centroid; c. when all of the set of modified pre-segmented texts have been assigned, recalculating the positions of the k centroids; and d. repeating steps b and c until the centroids become stable; wherein each of the one or more conceptual units is represented as k clusters and is associated with one or more templates, wherein each of the one or more templates corresponds to one of the set of pre-segmented texts, and wherein a conceptual unit identifier is assigned to each modified pre-segmented text and pre-segmented text in the plurality of modified pre-segmented texts and set of pre-segmented texts respectively. | 10. A system comprising: a. a processor; b. a memory coupled to the processor; c. a program stored in the memory for execution by the processor, the program configured to: i. identify, by a ranking module, a first statistically generated template matching a set of domain tags, the first statistically generated template being stored in a memory; ii. identify, by the ranking module, a second statistically generated template matching the set of domain tags, the second statistically generated template being stored in the memory; iii. select, by the ranking module, the first statistically generated template instead of the second statistically generated template; iv. generate, by the ranking module, a set of natural language text by inserting a set of information associated with a record into the first statistically generated template, the set of natural language text being stored in memory; and v. provide, by a delivery module, the set of natural language text; wherein the first statistically generated template and the second statistically generated template were generated by: 1. receiving a corpus comprising a set of pre-segmented texts; 2. creating a plurality of modified pre-segmented texts for the set of pre-segmented texts by: a. extracting a set of semantic terms for each pre-segmented text within the set of pre-segmented texts; and b. applying at least one domain tag for each pre-segmented text within the set of pre-segmented texts; and 3. applying a k-means clustering technique to cluster the plurality of modified pre-segmented texts into one or more conceptual units, the k-means clustering technique including: a. placing k points into the space represented by a set of modified pre-segmented texts that are being clustered, the k points representing initial group centroids; b. assigning each of the set of modified pre-segmented texts to the group having the closest centroid; c. when all of the set of modified pre-segmented texts have been assigned, recalculating the positions of the k centroids; and d. repeating steps b and c until the centroids become stable; wherein each of the one or more conceptual units is represented as k clusters and is associated with one or more templates, wherein each of the one or more templates corresponds to one of the set of pre-segmented texts, and wherein a conceptual unit identifier is assigned to each modified pre-segmented text and pre-segmented text in the plurality of modified pre-segmented texts and set of pre-segmented texts respectively. 11. The system of claim 10 wherein the program further configured to select the first statistically generated template instead of the second statistically generated template based on a set of model weights. | 0.5 |
7,483,908 | 36 | 37 | 36. The system of claim 35 , further comprising a message dispatcher that sends a message to a monitor based on an output from the auditor. | 36. The system of claim 35 , further comprising a message dispatcher that sends a message to a monitor based on an output from the auditor. 37. The system of claim 36 , wherein the monitor comprises at least one of: an electronic mail server, a telephony server, a paging server, a portable communicator, an alarm device and a human operator. | 0.5 |
7,605,938 | 1 | 2 | 1. A method of printing data, the method comprising: generating a first mark-up document that describes a file to be printed, the first mark-up document comprising text data and link data that indicates a location at which the file is stored in a storage unit; generating a second mark-up document that describes the file, the second mark-up document comprising identification information that identifies the file at the location indicated by the link data; generating a document to be transmitted to a printing device using the first mark-up document and the second mark-up document; transmitting the generated document to the printing device; analyzing the document at the printing device to obtain the link data and the identification information; transmitting a request for the file based on the extracted link data and identification information; extracting the file from the storage unit in response to the request for the file based on the extracted link data and identification information; receiving the file in response to the request for the file at the printing device; and outputting the file at the printing device. | 1. A method of printing data, the method comprising: generating a first mark-up document that describes a file to be printed, the first mark-up document comprising text data and link data that indicates a location at which the file is stored in a storage unit; generating a second mark-up document that describes the file, the second mark-up document comprising identification information that identifies the file at the location indicated by the link data; generating a document to be transmitted to a printing device using the first mark-up document and the second mark-up document; transmitting the generated document to the printing device; analyzing the document at the printing device to obtain the link data and the identification information; transmitting a request for the file based on the extracted link data and identification information; extracting the file from the storage unit in response to the request for the file based on the extracted link data and identification information; receiving the file in response to the request for the file at the printing device; and outputting the file at the printing device. 2. The method according to claim 1 , wherein the document to be transmitted to the printing device is prepared in accordance with a Multipurpose Internet Mail Extension (MIME) standard. | 0.5 |
8,027,834 | 1 | 7 | 1. A method for testing a phonetic decision tree, the method comprising: testing a first phonetic decision tree, created using a first set of data, with a second set of data, the second set of data including at least one second term not in the first set of data, by phonetizing terms of the second set of data using the first phonetic decision tree; categorizing results of the testing into a set of correctly phonetized terms and a set of incorrectly phonetized terms; and operating at least one processor to create an exception dictionary including at least one term from the set of incorrectly phonetized terms and phonetization information related to the at least one term. | 1. A method for testing a phonetic decision tree, the method comprising: testing a first phonetic decision tree, created using a first set of data, with a second set of data, the second set of data including at least one second term not in the first set of data, by phonetizing terms of the second set of data using the first phonetic decision tree; categorizing results of the testing into a set of correctly phonetized terms and a set of incorrectly phonetized terms; and operating at least one processor to create an exception dictionary including at least one term from the set of incorrectly phonetized terms and phonetization information related to the at least one term. 7. The method of claim 1 , wherein the testing, categorizing, and creating are performed by at least one machine in accordance with at least one computer program stored in a computer readable storage media, said computer programming having a plurality of code sections that are executable by the at least one machine. | 0.669102 |
9,369,433 | 13 | 15 | 13. A cloud network configured for enforcing website policy, comprising: a plurality of cloud nodes communicatively coupled to an external network and a plurality of users, wherein the plurality of cloud nodes are in a distributed, cloud-based security system, wherein the cloud-based security system is external from the plurality of users and external from an enterprise network and each of the plurality of nodes is configured as a proxy for the plurality of users between the external network in a location and platform independent manner for the user, wherein the user utilizes a mobile device and the platform independent manner comprises the cloud node operating similarly for any device, platform, and operating system, each of the plurality of cloud nodes is configured to: establish a connection with a user of the plurality of users via a tunnel, a transparent proxy, a forward proxy, or redirection to one of the plurality of nodes, wherein the mobile device of the user is configured with one of a mobile profile and an application, wherein the mobile profile and the application enables the mobile device to communicate through the cloud system; provide the user secure and monitored communication access to the external network, wherein the secure and monitored communication access comprises inspecting and filtering inbound traffic to the user, and blocking malicious data and notifying the user of the blocking, the malicious data comprises viruses, spyware, malware, Trojans, botnets, spam email, or phishing content, wherein the inspecting and filtering inbound traffic is through the cloud node which maintains transaction summaries for compliance; and while providing the communication access to the external network, enforce policy on the user's activity associated with at least one Web 2.0 website, the at least one Web 2.0 website comprising a social networking site; and a quarantine server communicatively coupled to the plurality of cloud nodes and configured to: quarantine any user generated data for Web 2.0 sites in the external network, wherein the user generated data is allowed for posting to the Web 2.0 sites subsequent to an approval process, used to prevent data leakage prevention for an enterprise, the data leakage prevention is performed by the quarantine server, and sending the quarantined user generated data to the Web 2.0 sites. | 13. A cloud network configured for enforcing website policy, comprising: a plurality of cloud nodes communicatively coupled to an external network and a plurality of users, wherein the plurality of cloud nodes are in a distributed, cloud-based security system, wherein the cloud-based security system is external from the plurality of users and external from an enterprise network and each of the plurality of nodes is configured as a proxy for the plurality of users between the external network in a location and platform independent manner for the user, wherein the user utilizes a mobile device and the platform independent manner comprises the cloud node operating similarly for any device, platform, and operating system, each of the plurality of cloud nodes is configured to: establish a connection with a user of the plurality of users via a tunnel, a transparent proxy, a forward proxy, or redirection to one of the plurality of nodes, wherein the mobile device of the user is configured with one of a mobile profile and an application, wherein the mobile profile and the application enables the mobile device to communicate through the cloud system; provide the user secure and monitored communication access to the external network, wherein the secure and monitored communication access comprises inspecting and filtering inbound traffic to the user, and blocking malicious data and notifying the user of the blocking, the malicious data comprises viruses, spyware, malware, Trojans, botnets, spam email, or phishing content, wherein the inspecting and filtering inbound traffic is through the cloud node which maintains transaction summaries for compliance; and while providing the communication access to the external network, enforce policy on the user's activity associated with at least one Web 2.0 website, the at least one Web 2.0 website comprising a social networking site; and a quarantine server communicatively coupled to the plurality of cloud nodes and configured to: quarantine any user generated data for Web 2.0 sites in the external network, wherein the user generated data is allowed for posting to the Web 2.0 sites subsequent to an approval process, used to prevent data leakage prevention for an enterprise, the data leakage prevention is performed by the quarantine server, and sending the quarantined user generated data to the Web 2.0 sites. 15. The cloud network of claim 13 , further comprising: a transaction log communicatively coupled to the plurality of cloud nodes and configured to log all transactions between the plurality of users and a plurality of Web 2.0 sites in the external network. | 0.711236 |
9,817,804 | 1 | 17 | 1. A device implementable in a web site design program, said device comprising: a component based version comparer to compare at least two versions of a website, said at least two versions having components in a set of hierarchies, wherein said components are at least one of a visual component, a container and a non-visual site element, and to generate a difference tree representing the differences in said components between said at least two versions of the same website, wherein said version comparer preprocesses said components in each single version of said at least two versions of said website to determine at least one of internal geometric, semantic, content and attribute relationships before comparing said components and said relationships between said at least two versions of said website using at least one of semantic, geometrical, content and attribute analysis; and wherein said hierarchies and said difference tree are trees and wherein said trees comprise nodes representing said components, said components having attributes; and wherein said component based version comparer comprises: a structural version comparer to compare nodes of said at least two versions of said website through comparison of their geometrical, content and semantic relationships; an order based version comparer to compare said nodes of said at least two versions of said website based on the order of said nodes and to pre-match said nodes according to an internal said website design system identifier; a semantic matching comparer to perform semantic classification on said nodes of said at least two versions of said website and match them according to their semantic classes and geometrical parameters; a comparison selector and coordinator to provide selection and coordination between said structural version comparer, said order based version comparer and said semantic matching comparer based on at least one of the structure and attributes of said components; a difference tree generator to generate said difference tree based on a combination of the results of said structural version comparer, said order based version comparer and said semantic matching comparer; a version merger to create an integrated version of said two versions of said website based on said difference tree; and a processor and a memory unit, said processor to activate said component based version comparer and said version merger. | 1. A device implementable in a web site design program, said device comprising: a component based version comparer to compare at least two versions of a website, said at least two versions having components in a set of hierarchies, wherein said components are at least one of a visual component, a container and a non-visual site element, and to generate a difference tree representing the differences in said components between said at least two versions of the same website, wherein said version comparer preprocesses said components in each single version of said at least two versions of said website to determine at least one of internal geometric, semantic, content and attribute relationships before comparing said components and said relationships between said at least two versions of said website using at least one of semantic, geometrical, content and attribute analysis; and wherein said hierarchies and said difference tree are trees and wherein said trees comprise nodes representing said components, said components having attributes; and wherein said component based version comparer comprises: a structural version comparer to compare nodes of said at least two versions of said website through comparison of their geometrical, content and semantic relationships; an order based version comparer to compare said nodes of said at least two versions of said website based on the order of said nodes and to pre-match said nodes according to an internal said website design system identifier; a semantic matching comparer to perform semantic classification on said nodes of said at least two versions of said website and match them according to their semantic classes and geometrical parameters; a comparison selector and coordinator to provide selection and coordination between said structural version comparer, said order based version comparer and said semantic matching comparer based on at least one of the structure and attributes of said components; a difference tree generator to generate said difference tree based on a combination of the results of said structural version comparer, said order based version comparer and said semantic matching comparer; a version merger to create an integrated version of said two versions of said website based on said difference tree; and a processor and a memory unit, said processor to activate said component based version comparer and said version merger. 17. The device of claim 1 and wherein said coordination is based on a combined metric of results returned from said structural version comparer, said order based version comparer and said semantic matching comparer. | 0.825487 |
8,015,204 | 13 | 16 | 13. A computer storage medium storing a particular data structure comprising: a scope element that contains criteria for determining a plurality of objects the particular data structure applies to for controlling what users may access the plurality of objects, wherein the criteria of the scope element defines a portion of a directory hierarchy indicating that the particular data structure provides access rights for a plurality of file objects located under the portion of the directory hierarchy; and one or more rule elements that define access rights for accessing the plurality of file objects, including: a first rule element that contains (1) first user rules that define a first set of one or more users to whom the first rule element applies and who may access the plurality of file objects, including a first rule that defines the first set of one or more users as users that have been authenticated, and (2) first access rules that define what access rights the first set of one or more users are granted for accessing any one of the plurality of file objects; and a second rule element that contains (1) second user rules that define a second set of one or more users to whom the second rule element applies and who may also access the plurality of file objects, and (2) second access rules that define what different access rights the second set of one or more users are granted for accessing any one of the plurality of file objects, the computer storage medium further storing computer-executable instructions that, when executed by at least one processor of a computer system, implement a method, comprising: an act of the computer system receiving a request from a user to access the one of the plurality of file objects, the user included in at least the first set of one or more users; an act of the computer system determining that the particular data structure controls what users may access the plurality of file objects, as defined by the criteria of the scope element of the particular data structure; an act of the computer system determining that the user is included in the first set of one or more users and that the user has been authenticated, as defined by the first user rules of the first rule element of the particular data structure; and an act of the computer system granting the user access to the one of the plurality of file objects, as defined by the first access rules of the first rule element of the particular data structure. | 13. A computer storage medium storing a particular data structure comprising: a scope element that contains criteria for determining a plurality of objects the particular data structure applies to for controlling what users may access the plurality of objects, wherein the criteria of the scope element defines a portion of a directory hierarchy indicating that the particular data structure provides access rights for a plurality of file objects located under the portion of the directory hierarchy; and one or more rule elements that define access rights for accessing the plurality of file objects, including: a first rule element that contains (1) first user rules that define a first set of one or more users to whom the first rule element applies and who may access the plurality of file objects, including a first rule that defines the first set of one or more users as users that have been authenticated, and (2) first access rules that define what access rights the first set of one or more users are granted for accessing any one of the plurality of file objects; and a second rule element that contains (1) second user rules that define a second set of one or more users to whom the second rule element applies and who may also access the plurality of file objects, and (2) second access rules that define what different access rights the second set of one or more users are granted for accessing any one of the plurality of file objects, the computer storage medium further storing computer-executable instructions that, when executed by at least one processor of a computer system, implement a method, comprising: an act of the computer system receiving a request from a user to access the one of the plurality of file objects, the user included in at least the first set of one or more users; an act of the computer system determining that the particular data structure controls what users may access the plurality of file objects, as defined by the criteria of the scope element of the particular data structure; an act of the computer system determining that the user is included in the first set of one or more users and that the user has been authenticated, as defined by the first user rules of the first rule element of the particular data structure; and an act of the computer system granting the user access to the one of the plurality of file objects, as defined by the first access rules of the first rule element of the particular data structure. 16. The computer storage medium of claim 13 , wherein the one or more rule elements contain references to rules for defining the range of users such that the rules are not directly contained within the data structure. | 0.641914 |
7,596,755 | 1 | 7 | 1. A method of displaying multimedia information stored in a multimedia document on a display, the method comprising: displaying a graphical user interface (GUI) on the display; displaying, in a first area of the GUI, a first visual representation of the multimedia information stored in the multimedia document, the first visual representation including a first representation of information of a first type stored in the multimedia document and a first representation of information of a second type stored in the multimedia document; displaying, in the first area of the GUI, a first lens positionable over a plurality of portions of the first visual representation displayed within the first area of the GUI, the first lens covering a first portion of the first visual representation within the first area; displaying, in a second area of the GUI, a second visual representation of the multimedia information stored in the multimedia document based on the first lens covering the first portion of the first visual representation within the first area, the second visual representation including a second representation of the information of the first type stored in the multimedia document and a second representation of the information of the second type stored in the multimedia document; displaying, in the second area of the GUI, a second lens positionable over a plurality of portions of the second visual representation displayed within the second area of the GUI, the second lens covering a first portion of the second visual representation within the second area; and displaying, in a third area of the GUI, a third visual representation of the multimedia information stored in the multimedia document based on the second lens covering the first portion of the second visual representation within the second area, the third visual representation including a third representation of the information of the first type and a third representation of the information of the second type, wherein displaying the first visual representation of the multimedia information stored in the multimedia document in the first area of the GUI comprises: displaying a first thumbnail image in the first area of the GUI, the first thumbnail image comprising the first representation of the information of the first type; and displaying a second thumbnail image in the first area of the GUI, the second thumbnail image comprising the first representation of the information of the second type, wherein displaying the second visual representation of the multimedia information stored in the multimedia document in the second area of the GUI comprises: displaying, in a first sub-area of the second area of the GUI, the portion of the first representation of the information of the first type covered by the first lens as the second representation of the information of the first type; and displaying, in a second sub-area of the second area of the GUI, the portion of the first representation of the information of the second type covered by the first lens as the second representation of the information of the second type, wherein displaying the third visual representation of the multimedia information stored in the multimedia document in the third area of the GUI comprises: displaying, in a first sub-area of the third area of the GUI, the portion of the second representation of the information of the first type covered by the second lens as the third representation of the information of the first type; and displaying, in a second sub-area of the third area of the GUI, the portion of the second representation of the information of the second type covered by the second lens as the third representation of the information of the first type. | 1. A method of displaying multimedia information stored in a multimedia document on a display, the method comprising: displaying a graphical user interface (GUI) on the display; displaying, in a first area of the GUI, a first visual representation of the multimedia information stored in the multimedia document, the first visual representation including a first representation of information of a first type stored in the multimedia document and a first representation of information of a second type stored in the multimedia document; displaying, in the first area of the GUI, a first lens positionable over a plurality of portions of the first visual representation displayed within the first area of the GUI, the first lens covering a first portion of the first visual representation within the first area; displaying, in a second area of the GUI, a second visual representation of the multimedia information stored in the multimedia document based on the first lens covering the first portion of the first visual representation within the first area, the second visual representation including a second representation of the information of the first type stored in the multimedia document and a second representation of the information of the second type stored in the multimedia document; displaying, in the second area of the GUI, a second lens positionable over a plurality of portions of the second visual representation displayed within the second area of the GUI, the second lens covering a first portion of the second visual representation within the second area; and displaying, in a third area of the GUI, a third visual representation of the multimedia information stored in the multimedia document based on the second lens covering the first portion of the second visual representation within the second area, the third visual representation including a third representation of the information of the first type and a third representation of the information of the second type, wherein displaying the first visual representation of the multimedia information stored in the multimedia document in the first area of the GUI comprises: displaying a first thumbnail image in the first area of the GUI, the first thumbnail image comprising the first representation of the information of the first type; and displaying a second thumbnail image in the first area of the GUI, the second thumbnail image comprising the first representation of the information of the second type, wherein displaying the second visual representation of the multimedia information stored in the multimedia document in the second area of the GUI comprises: displaying, in a first sub-area of the second area of the GUI, the portion of the first representation of the information of the first type covered by the first lens as the second representation of the information of the first type; and displaying, in a second sub-area of the second area of the GUI, the portion of the first representation of the information of the second type covered by the first lens as the second representation of the information of the second type, wherein displaying the third visual representation of the multimedia information stored in the multimedia document in the third area of the GUI comprises: displaying, in a first sub-area of the third area of the GUI, the portion of the second representation of the information of the first type covered by the second lens as the third representation of the information of the first type; and displaying, in a second sub-area of the third area of the GUI, the portion of the second representation of the information of the second type covered by the second lens as the third representation of the information of the first type. 7. The method of claim 1 further comprising: receiving user input moving the second lens over the second visual representation displayed within the second area to cover a second portion of the second visual representation within the second area; and responsive to the user input, automatically changing the third visual representation displayed in the third area of the GUI such that the third visual representation of the multimedia information stored in the multimedia document displayed in the third area of the GUI corresponds to the second portion of the second visual representation of the multimedia information stored in the multimedia document covered by the second lens. | 0.672762 |
4,610,025 | 5 | 6 | 5. The system of claim 4, wherein said sensory input means comprises means for providing a bit-mapped representation of the glyphs appearing in said document. | 5. The system of claim 4, wherein said sensory input means comprises means for providing a bit-mapped representation of the glyphs appearing in said document. 6. The system of claim 5, wherein said sensory input means comprises means for producing a binary representation of the glyphs appearing on said document. | 0.77937 |
10,127,582 | 1 | 4 | 1. An apparatus comprising: a processing platform implementing a unified framework for representation and processing of trigger, context, action and result (TCAR) associations and constituent elements thereof in relation to customer communications in an enterprise; wherein the processing platform is configured: to capture events by detecting one or more triggers associated with customer-related events, finding context for the one or more triggers by capturing historical and ongoing events for one or more customers associated with the customer-related events, and generating one or more action-response links each comprising at least one action specifying one or more responses to a given trigger based on its associated context and at least one response comprising one or more events that plausibly occurred responsive to the given action based on the given trigger and its associated context; to transmogrify corresponding TCAR associations for storage in a TCAR repository by transforming the triggers, context and action-response links for the captured events into a unified representation governed by a specified TCAR ontology; to perform one or more reasoning operations over selected ones of the TCAR associations stored in the TCAR repository utilizing one or more policies stored in the TCAR repository to identify one or more actions to orchestrate based on analysis of the selected TCAR associations and the policies stored in the TCAR repository; and to orchestrate the one or more actions determined at least in part by the one or more reasoning operations to control one or more of content, channel, and timing of ongoing customer communications, the one or more actions being selected from an action repertoire stored in the TCAR repository; wherein the processing platform comprises one or more processing devices each comprising a processor coupled to a memory; wherein the processing platform is further configured to implement an integrated development environment for performing an operations configuration loop and an optimization configuration loop; wherein the operations configuration loop comprises capturing the events, developing the specified TCAR ontology, and orchestrating the actions based on reasoning over the TCAR repository; and wherein the optimization configuration loop comprises monitoring impacts of the orchestrated actions using one or more analytic tools and developing the action repertoire and the policy base by analyzing: (i) alignment or other correspondence between elements of multiple TCAR associations stored in the TCAR repository; and (ii) the monitored impacts of the orchestration actions. | 1. An apparatus comprising: a processing platform implementing a unified framework for representation and processing of trigger, context, action and result (TCAR) associations and constituent elements thereof in relation to customer communications in an enterprise; wherein the processing platform is configured: to capture events by detecting one or more triggers associated with customer-related events, finding context for the one or more triggers by capturing historical and ongoing events for one or more customers associated with the customer-related events, and generating one or more action-response links each comprising at least one action specifying one or more responses to a given trigger based on its associated context and at least one response comprising one or more events that plausibly occurred responsive to the given action based on the given trigger and its associated context; to transmogrify corresponding TCAR associations for storage in a TCAR repository by transforming the triggers, context and action-response links for the captured events into a unified representation governed by a specified TCAR ontology; to perform one or more reasoning operations over selected ones of the TCAR associations stored in the TCAR repository utilizing one or more policies stored in the TCAR repository to identify one or more actions to orchestrate based on analysis of the selected TCAR associations and the policies stored in the TCAR repository; and to orchestrate the one or more actions determined at least in part by the one or more reasoning operations to control one or more of content, channel, and timing of ongoing customer communications, the one or more actions being selected from an action repertoire stored in the TCAR repository; wherein the processing platform comprises one or more processing devices each comprising a processor coupled to a memory; wherein the processing platform is further configured to implement an integrated development environment for performing an operations configuration loop and an optimization configuration loop; wherein the operations configuration loop comprises capturing the events, developing the specified TCAR ontology, and orchestrating the actions based on reasoning over the TCAR repository; and wherein the optimization configuration loop comprises monitoring impacts of the orchestrated actions using one or more analytic tools and developing the action repertoire and the policy base by analyzing: (i) alignment or other correspondence between elements of multiple TCAR associations stored in the TCAR repository; and (ii) the monitored impacts of the orchestration actions. 4. The apparatus of claim 1 wherein the TCAR repository comprises a data repository and a metadata repository. | 0.832317 |
8,204,896 | 18 | 19 | 18. An image processing apparatus comprising: a data generating unit configured to analyze a file generated as a predetermined format to generate bitmap data, the file including character addition information associated with at least one word contained in the file, the character addition information added manually to the file; an analyzing unit configured to extract layout information regarding character regions and the character addition information from the bitmap data generated by the data generating unit; an optical character recognition (OCR) processing unit configured to convert the character regions included in the layout information extracted by the analyzing unit into character information; an extracting unit configured to extract the at least one word from the character information converted by the OCR processing unit in response to the character addition information having a predefined image characteristic; a searching unit configured to perform a search based on the at least one word extracted by the extracting unit and generate meta-information in accordance with information retrieved by the search; and an electronic document generating unit configured to generate an electronic document according to a description of a predetermined format by adding the meta-information to the character information. | 18. An image processing apparatus comprising: a data generating unit configured to analyze a file generated as a predetermined format to generate bitmap data, the file including character addition information associated with at least one word contained in the file, the character addition information added manually to the file; an analyzing unit configured to extract layout information regarding character regions and the character addition information from the bitmap data generated by the data generating unit; an optical character recognition (OCR) processing unit configured to convert the character regions included in the layout information extracted by the analyzing unit into character information; an extracting unit configured to extract the at least one word from the character information converted by the OCR processing unit in response to the character addition information having a predefined image characteristic; a searching unit configured to perform a search based on the at least one word extracted by the extracting unit and generate meta-information in accordance with information retrieved by the search; and an electronic document generating unit configured to generate an electronic document according to a description of a predetermined format by adding the meta-information to the character information. 19. The apparatus according to claim 18 , wherein the data generating unit is further configured to generate tag information for displaying object information from the file generated as the predetermined format. | 0.5 |
7,844,957 | 32 | 33 | 32. The method of claim 31 , wherein said generating step includes: generating source code for a parser specifically optimized for parsing messages of said particular message type. | 32. The method of claim 31 , wherein said generating step includes: generating source code for a parser specifically optimized for parsing messages of said particular message type. 33. The method of claim 32 , wherein said generating step includes: generating source code for a serializer specifically optimized for serializing message data parsed from messages of said particular message type. | 0.5 |
8,209,320 | 11 | 19 | 11. An article of manufacture comprising a data storage device having machine executable instructions embedded thereon, which when executed by a machine, cause the machine to: place an object in a web page, the web page displayed to a user on a client device with a processor having access to a network, the web page is an affiliate web page, the object is an executable code component configured to execute a network communication when the web page is accessed; invoke a keyword extraction service at a host site via a network access in response to activation of the object in the web page when the web page is accessed by the user; obtain information related to user activity on the client device, the information obtained in response to activation of the object in the web page when the web page is accessed by the user, the information related to user activity on the client device including impressions viewed by the user and user click-throughs received, wherein the information related to user activity on the client device is based on information selected from the group: user behavior on a web site, frequency of user queries, listings availability, post-search user activity, and catalog data; use the keyword extraction service to extract relevant keywords from content of the web page, the information related to user activity on the client device used to determine relevancy of the extracted keywords; identify items relevant to the extracted keywords, the relevancy of the extracted keywords to the items is based on information from the group consisting of: measures of item popularity, measures of web site popularity, aggregate user behavior on the web site; user feedback, listings availability, and catalog data; and rank the relevant items. | 11. An article of manufacture comprising a data storage device having machine executable instructions embedded thereon, which when executed by a machine, cause the machine to: place an object in a web page, the web page displayed to a user on a client device with a processor having access to a network, the web page is an affiliate web page, the object is an executable code component configured to execute a network communication when the web page is accessed; invoke a keyword extraction service at a host site via a network access in response to activation of the object in the web page when the web page is accessed by the user; obtain information related to user activity on the client device, the information obtained in response to activation of the object in the web page when the web page is accessed by the user, the information related to user activity on the client device including impressions viewed by the user and user click-throughs received, wherein the information related to user activity on the client device is based on information selected from the group: user behavior on a web site, frequency of user queries, listings availability, post-search user activity, and catalog data; use the keyword extraction service to extract relevant keywords from content of the web page, the information related to user activity on the client device used to determine relevancy of the extracted keywords; identify items relevant to the extracted keywords, the relevancy of the extracted keywords to the items is based on information from the group consisting of: measures of item popularity, measures of web site popularity, aggregate user behavior on the web site; user feedback, listings availability, and catalog data; and rank the relevant items. 19. The article of manufacture as claimed in claim 11 to use the extracted keywords to produce a contextual advertisement placement. | 0.627119 |
8,477,095 | 5 | 6 | 5. The system of claim 1 wherein a modification of said operational parameter causes said pen-based computer to produce a human-audible output corresponding to more than one human viewable images on said media. | 5. The system of claim 1 wherein a modification of said operational parameter causes said pen-based computer to produce a human-audible output corresponding to more than one human viewable images on said media. 6. The system of claim 5 wherein said human-audible output comprises music. | 0.71374 |
8,479,149 | 2 | 3 | 2. The computer-implemented method of claim 1 , further comprising: lifting at least one of the one of more viewing instances relationships associated with at least one of the one or more viewing instances not associated with one of the one or more viewing concepts. | 2. The computer-implemented method of claim 1 , further comprising: lifting at least one of the one of more viewing instances relationships associated with at least one of the one or more viewing instances not associated with one of the one or more viewing concepts. 3. The computer-implemented method of claim 2 , wherein the at least one lifted relationship is lifted up along viewing instances hierarchy defined by member relationships between the one or more viewing instances. | 0.5 |
8,699,852 | 1 | 22 | 1. A method for determining a semantic concept classification for a digital video clip including a temporal sequence of video frames and a corresponding audio soundtrack, comprising: determining, by a processing device, reference video codeword similarity scores for each reference video clip in a set of reference video clips, wherein the determining reference video codeword similarity scores comprises: analyzing a temporal sequence of video frames for a particular reference video clip to determine a set of reference video visual features; analyzing an audio soundtrack for the particular reference video clip to determine a set of reference video audio features; comparing the set of reference video visual features to distinct visual background codewords and distinct visual foreground codewords from audio-visual grouplets of an audio-visual dictionary, wherein the audio-visual grouplets include distinct visual background codewords representing visual background content, distinct visual foreground codewords representing visual foreground content, distinct audio background codewords representing audio background content, and distinct audio foreground codewords representing audio foreground content; and comparing the set of reference video audio features to the distinct audio background codewords and the distinct audio foreground codewords from the audio-visual grouplets of the audio-visual dictionary; determining, by the prosessing device, codeword similarity scores for the digital video clip, wherein the determining codeword similarity scores comprises: analyzing the temporal sequence of video frames in the digital video clip to determine a set of visual features; analyzing the audio soundtrack in the digital video clip to determine a set of audio features; comparing the set of visual features to the distinct visual background codewords and the distinct visual foreground codewords; and comparing the set of audio features to the distinct audio background codewords and the distinct audio foreground codewords; determining, by the prosessing device, a reference video similarity score for each reference video clip representing a similarity between the digital video clip and the respective reference video clip responsive to the audio-visual grouplets, the codeword similarity scores, and the reference video codeword similarity scores; determining, by the prosessing device, a concept classification using trained semantic classifiers responsive to the determined reference video similarity scores; storing, by the prosessing device, an indication of the concept classification in a processor-accessible memory; wherein the distinct visual background codewords and the distinct foreground codewords are separate and distinct from each other, wherein the distinct audio background codewords and the distinct audio foreground codewords are separate and distinct from each other, and wherein the distinct visual background codewords and the distinct visual foreground codewords are separate and distinct from the distinct audio background codewords and the distinct audio foreground codewords. | 1. A method for determining a semantic concept classification for a digital video clip including a temporal sequence of video frames and a corresponding audio soundtrack, comprising: determining, by a processing device, reference video codeword similarity scores for each reference video clip in a set of reference video clips, wherein the determining reference video codeword similarity scores comprises: analyzing a temporal sequence of video frames for a particular reference video clip to determine a set of reference video visual features; analyzing an audio soundtrack for the particular reference video clip to determine a set of reference video audio features; comparing the set of reference video visual features to distinct visual background codewords and distinct visual foreground codewords from audio-visual grouplets of an audio-visual dictionary, wherein the audio-visual grouplets include distinct visual background codewords representing visual background content, distinct visual foreground codewords representing visual foreground content, distinct audio background codewords representing audio background content, and distinct audio foreground codewords representing audio foreground content; and comparing the set of reference video audio features to the distinct audio background codewords and the distinct audio foreground codewords from the audio-visual grouplets of the audio-visual dictionary; determining, by the prosessing device, codeword similarity scores for the digital video clip, wherein the determining codeword similarity scores comprises: analyzing the temporal sequence of video frames in the digital video clip to determine a set of visual features; analyzing the audio soundtrack in the digital video clip to determine a set of audio features; comparing the set of visual features to the distinct visual background codewords and the distinct visual foreground codewords; and comparing the set of audio features to the distinct audio background codewords and the distinct audio foreground codewords; determining, by the prosessing device, a reference video similarity score for each reference video clip representing a similarity between the digital video clip and the respective reference video clip responsive to the audio-visual grouplets, the codeword similarity scores, and the reference video codeword similarity scores; determining, by the prosessing device, a concept classification using trained semantic classifiers responsive to the determined reference video similarity scores; storing, by the prosessing device, an indication of the concept classification in a processor-accessible memory; wherein the distinct visual background codewords and the distinct foreground codewords are separate and distinct from each other, wherein the distinct audio background codewords and the distinct audio foreground codewords are separate and distinct from each other, and wherein the distinct visual background codewords and the distinct visual foreground codewords are separate and distinct from the distinct audio background codewords and the distinct audio foreground codewords. 22. The method of claim 1 , wherein the determining the reference video similarity score comprises: determining audio-visual grouplet similarity scores for a set of audio visual grouplets representing a similarity between the codeword similarity scores and the corresponding reference video codeword similarity scores for the particular reference video clip; and aggregating the audio-visual grouplet similarity scores to determine the reference video similarity score for the particular reference video clip. | 0.743189 |
9,477,446 | 1 | 5 | 1. A method of building an integrated system using a formal language, the method comprising: designing one or more models for one or more software components to be included in the integrated system, wherein the one or more models describe one or more requirements for the one or more software components; assigning one or more contracts to the one or more models, wherein the one or more contracts are written in the formal language and the one or more contracts include one or more low-level contracts and one or more high-level contracts; integrating, by an electronic device, the one or more models based on the composition of the one or more contracts to form an integrated model, wherein the integrated model includes each requirement for the one or more software components which is described by the one or more models which form the integrated model; and analyzing, by the electronic device, the one or more contracts and the integrated model to determine whether the one or more contracts include each requirement described by the integrated model, wherein the one or more low-level contracts are designed relative to the one or more high-level contracts so that analysis of the one or more low-level contracts alone indicates whether an error will be present in the one or more high-level contracts. | 1. A method of building an integrated system using a formal language, the method comprising: designing one or more models for one or more software components to be included in the integrated system, wherein the one or more models describe one or more requirements for the one or more software components; assigning one or more contracts to the one or more models, wherein the one or more contracts are written in the formal language and the one or more contracts include one or more low-level contracts and one or more high-level contracts; integrating, by an electronic device, the one or more models based on the composition of the one or more contracts to form an integrated model, wherein the integrated model includes each requirement for the one or more software components which is described by the one or more models which form the integrated model; and analyzing, by the electronic device, the one or more contracts and the integrated model to determine whether the one or more contracts include each requirement described by the integrated model, wherein the one or more low-level contracts are designed relative to the one or more high-level contracts so that analysis of the one or more low-level contracts alone indicates whether an error will be present in the one or more high-level contracts. 5. The method of claim 1 , wherein the integrated system includes an embedded system. | 0.844891 |
8,923,630 | 11 | 13 | 11. A data mining system, comprising: an input configured to receive receiving a set of multimodal data objects comprising semantically interrelated information of a first type and information of a second type, each of the first type and the second type being different and being selected from the group consisting of image information, audio information, video information, and semantic information; an automated processor, configured to: represent at least the first type of information of the multimodal data objects as feature vectors within a feature space comprising the first type of information and the second type of information, and the semantic interrelation between the first type of information and the second type of information; cluster the feature vectors according to at least one clustering criterion, to thereby determine a classification of the respective feature vectors; associate data objects comprising information of a third type semantically interrelated to the second type of information, selected from the group consisting of images, audio, video and semantic information, wherein the type of information of the third type is distinct from the type of information of the first type, with respective multimodal data objects based on the clustering; estimate a joint feature representation of the set of multimodal data objects and the associated data objects; optimize the joint feature representation to provide a structured output space of interdependent objects, based on at least a prediction error criterion, by iteratively solving a dual problem by selectively partitioning data objects into a working set and a non-working set, comprising: moving the data objects in the non-working set that can be moved without changing an objective function to the working set, and moving the data objects in the working set that can be moved with a decrease in the objective function to the non-working set; receive a query represented according to the first type of information; and identify data objects from the set of multimodal data objects that correspond to the query by the at least one automated processor, based on at least the structured output space of interdependent multimodal objects; and an output port from the automated processor, configured to communicate at least one of the identified data objects and identifiers of the identified data objects. | 11. A data mining system, comprising: an input configured to receive receiving a set of multimodal data objects comprising semantically interrelated information of a first type and information of a second type, each of the first type and the second type being different and being selected from the group consisting of image information, audio information, video information, and semantic information; an automated processor, configured to: represent at least the first type of information of the multimodal data objects as feature vectors within a feature space comprising the first type of information and the second type of information, and the semantic interrelation between the first type of information and the second type of information; cluster the feature vectors according to at least one clustering criterion, to thereby determine a classification of the respective feature vectors; associate data objects comprising information of a third type semantically interrelated to the second type of information, selected from the group consisting of images, audio, video and semantic information, wherein the type of information of the third type is distinct from the type of information of the first type, with respective multimodal data objects based on the clustering; estimate a joint feature representation of the set of multimodal data objects and the associated data objects; optimize the joint feature representation to provide a structured output space of interdependent objects, based on at least a prediction error criterion, by iteratively solving a dual problem by selectively partitioning data objects into a working set and a non-working set, comprising: moving the data objects in the non-working set that can be moved without changing an objective function to the working set, and moving the data objects in the working set that can be moved with a decrease in the objective function to the non-working set; receive a query represented according to the first type of information; and identify data objects from the set of multimodal data objects that correspond to the query by the at least one automated processor, based on at least the structured output space of interdependent multimodal objects; and an output port from the automated processor, configured to communicate at least one of the identified data objects and identifiers of the identified data objects. 13. The system according to claim 11 , wherein the first type of information comprises at least one of image information, audio information and video information, and the second type of information comprises semantic information which represents an annotation of the first type of information for the respective multimodal data object after the association. | 0.822211 |
9,154,575 | 1 | 6 | 1. A method comprising: receiving a plurality of data items imported into a social-networking system by a first user of the social-networking system, the plurality of data items being related to an entity; accessing, by one or more processors associated with one or more computer servers associated with the social-networking system, one or more data stores storing a social graph of the social-networking system, the social graph comprising a plurality of nodes and a plurality of edges between nodes, the nodes comprising user nodes corresponding to users of the social-networking system and concept nodes corresponding to concepts; identifying, by the one or more processors, one or more nodes of the social graph that likely match the entity, each of the one or more nodes having at least one matching attribute that matches one of the plurality of data items; and updating, by the one or more processors, an unmatched attribute, different from the at least one matching attribute, of at least one of the identified nodes with at least one of the data items. | 1. A method comprising: receiving a plurality of data items imported into a social-networking system by a first user of the social-networking system, the plurality of data items being related to an entity; accessing, by one or more processors associated with one or more computer servers associated with the social-networking system, one or more data stores storing a social graph of the social-networking system, the social graph comprising a plurality of nodes and a plurality of edges between nodes, the nodes comprising user nodes corresponding to users of the social-networking system and concept nodes corresponding to concepts; identifying, by the one or more processors, one or more nodes of the social graph that likely match the entity, each of the one or more nodes having at least one matching attribute that matches one of the plurality of data items; and updating, by the one or more processors, an unmatched attribute, different from the at least one matching attribute, of at least one of the identified nodes with at least one of the data items. 6. The method of claim 1 , wherein the identifying one or more nodes of the social graph that likely match the entity is further based on a respective measure of affinity between the nodes and the first user. | 0.610487 |
8,897,486 | 6 | 7 | 6. A method comprising: recognizing a plurality of textual strings within a written work, wherein each textual string is associated with a character identity of a plurality of character identities within the written work; for the character identity; calculating, by one or more hardware processors, a significance value based at least in part on a frequency of occurrence of one or more textual strings associated with the character identity; determining that the character identity is included in other written works; updating the significance value for the character identity based at least in part on the inclusion of the character identity in the other written works; and selecting a primary textual string from the one or more textual strings associated with the character identity; and providing a list of at least a portion of the plurality of character identities, the list including the primary textual string and other primary textual strings for the at least the portion of the plurality of character identities and the list being sorted based at least in part on the significance value. | 6. A method comprising: recognizing a plurality of textual strings within a written work, wherein each textual string is associated with a character identity of a plurality of character identities within the written work; for the character identity; calculating, by one or more hardware processors, a significance value based at least in part on a frequency of occurrence of one or more textual strings associated with the character identity; determining that the character identity is included in other written works; updating the significance value for the character identity based at least in part on the inclusion of the character identity in the other written works; and selecting a primary textual string from the one or more textual strings associated with the character identity; and providing a list of at least a portion of the plurality of character identities, the list including the primary textual string and other primary textual strings for the at least the portion of the plurality of character identities and the list being sorted based at least in part on the significance value. 7. The method as recited in claim 6 , further comprising: causing a display of the list of the at least the portion of the plurality of character identities on a device associated with a user; receiving, from the device associated with the user, an indication that at least one character identity with the written work is a proper character identity; and adjusting the significance value of the at least one character identity based on the indication. | 0.61453 |
8,332,390 | 1 | 7 | 1. A computer system including instructions recorded on a computer-readable medium, the system comprising: at least one processor processor; and a query handler configured to cause the at least one processor to receive a query for application against different combinations of a plurality of remote databases and a corresponding plurality of replica databases including at least some replicated data of respective ones of the remote databases, wherein each replica database is synchronized with a corresponding remote database at a plurality of scheduled synchronization times and the different combinations include future versions of the replica databases defined by corresponding synchronization times; and a query plan generator configured to cause the at least one processor to determine information values associated with at least a subset of the different combinations using an information value calculator that comprises: a computational latency (CL) calculator configured to cause the at least one processor to determine a time between a receipt of a result of the query and an issuance of the query for a particular combination; a synchronization latency (SL) calculator configured to cause the at least one processor to determine a time, for the particular combination, between the receipt of the result of the query and a relevant synchronization time of the plurality of scheduled synchronization times that is prior to or concurrent with the issuance of the query, and a parameter manager configured to cause the at least one processor to determine decay rates λ CL and λ SL for defining an extent of diminishment associated with each of the computational latency and the synchronization latency, respectively, wherein the information value calculator calculates the information value (IV) for the particular combination using the formula IV=QV(1-λ CL ) CL (1-λ SL ) SL , where QV refers to a query value associated with the query, and further configured to cause the at least one processor to generate, based on the information values, a query plan including at least one combination of the different combinations for executing the query therewith. | 1. A computer system including instructions recorded on a computer-readable medium, the system comprising: at least one processor processor; and a query handler configured to cause the at least one processor to receive a query for application against different combinations of a plurality of remote databases and a corresponding plurality of replica databases including at least some replicated data of respective ones of the remote databases, wherein each replica database is synchronized with a corresponding remote database at a plurality of scheduled synchronization times and the different combinations include future versions of the replica databases defined by corresponding synchronization times; and a query plan generator configured to cause the at least one processor to determine information values associated with at least a subset of the different combinations using an information value calculator that comprises: a computational latency (CL) calculator configured to cause the at least one processor to determine a time between a receipt of a result of the query and an issuance of the query for a particular combination; a synchronization latency (SL) calculator configured to cause the at least one processor to determine a time, for the particular combination, between the receipt of the result of the query and a relevant synchronization time of the plurality of scheduled synchronization times that is prior to or concurrent with the issuance of the query, and a parameter manager configured to cause the at least one processor to determine decay rates λ CL and λ SL for defining an extent of diminishment associated with each of the computational latency and the synchronization latency, respectively, wherein the information value calculator calculates the information value (IV) for the particular combination using the formula IV=QV(1-λ CL ) CL (1-λ SL ) SL , where QV refers to a query value associated with the query, and further configured to cause the at least one processor to generate, based on the information values, a query plan including at least one combination of the different combinations for executing the query therewith. 7. The system of claim 1 further comprising a workload manager configured to cause the at least one processor to include the query within a group of queries and to determine the query plan as part of an optimization of an information value of the group of queries as a whole. | 0.674941 |
9,426,160 | 2 | 5 | 2. The method of claim 1 , further comprising: engaging a crawler to search content for content apparently authored an author in the database associated with the user; and for found content, if it the source is trusted according to a trust policy, indexing the found content into the database by author in the database; and for found content, if the source is not trusted according to a trust policy, verifying the identity of the purported author of the found content, in which if the author of the found content is verified, indexing the found content into the database by author in the database. | 2. The method of claim 1 , further comprising: engaging a crawler to search content for content apparently authored an author in the database associated with the user; and for found content, if it the source is trusted according to a trust policy, indexing the found content into the database by author in the database; and for found content, if the source is not trusted according to a trust policy, verifying the identity of the purported author of the found content, in which if the author of the found content is verified, indexing the found content into the database by author in the database. 5. The method of claim 2 , further comprising: monitoring the indexed found content for updates; and notifying the user when indexed found content is updated. | 0.790451 |
8,671,104 | 1 | 7 | 1. A computer-implemented system according to for providing orientation into digital information; comprising: a memory; and a processor operatively coupled to the memory and configured to execute computer executable program modules, comprising: an information storage module maintaining a plurality of evergreen indexes on a server for topically-limited subject areas, each of the subject areas comprising electronically-stored digital information and, for each of the evergreen indexes, comprising: a hierarchy of stored topics; and a stored topic model matched to each of the topics in the topic hierarchy, each of the topic models comprising a pattern evaluable against the digital information, wherein the pattern identifies such digital information matching the topic model's topic; a guide generator receiving a user interest in the digital information for the subject area of at least one of the evergreen indexes; a topic model matcher evaluating each of the patterns for the identified topic models against the digital information; a visual display providing access to the digital information organized according to each of the topics in the subject area; a query evaluator receiving a query comprising topic search terms and to match the topic search terms to the topics in the topic hierarchy; and a characteristic word evaluator designating at least one of the chosen topics and the topic search terms as characteristic words, examining all of the evergreen indexes, and identifying those evergreen indexes in the visual display that comprise the characteristic words. | 1. A computer-implemented system according to for providing orientation into digital information; comprising: a memory; and a processor operatively coupled to the memory and configured to execute computer executable program modules, comprising: an information storage module maintaining a plurality of evergreen indexes on a server for topically-limited subject areas, each of the subject areas comprising electronically-stored digital information and, for each of the evergreen indexes, comprising: a hierarchy of stored topics; and a stored topic model matched to each of the topics in the topic hierarchy, each of the topic models comprising a pattern evaluable against the digital information, wherein the pattern identifies such digital information matching the topic model's topic; a guide generator receiving a user interest in the digital information for the subject area of at least one of the evergreen indexes; a topic model matcher evaluating each of the patterns for the identified topic models against the digital information; a visual display providing access to the digital information organized according to each of the topics in the subject area; a query evaluator receiving a query comprising topic search terms and to match the topic search terms to the topics in the topic hierarchy; and a characteristic word evaluator designating at least one of the chosen topics and the topic search terms as characteristic words, examining all of the evergreen indexes, and identifying those evergreen indexes in the visual display that comprise the characteristic words. 7. A system according to claim 1 , wherein the digital information comprises one or more of printed documents, Web pages, and material written in a digital media. | 0.838 |
8,147,520 | 4 | 5 | 4. The system of claim 1 including: a third horizontal rod having a third end portion adapted to mount a third pedicle screw and a fourth end portion adapted to mount a fourth pedicle screw; the first vertical rod being fixedly connected to the third horizontal rod medial of the third end portion, and the second vertical rod being fixedly connected to the third horizontal rod medial of the fourth end portion; and whereby the third horizontal rod is immobilized relative to the second horizontal rod. | 4. The system of claim 1 including: a third horizontal rod having a third end portion adapted to mount a third pedicle screw and a fourth end portion adapted to mount a fourth pedicle screw; the first vertical rod being fixedly connected to the third horizontal rod medial of the third end portion, and the second vertical rod being fixedly connected to the third horizontal rod medial of the fourth end portion; and whereby the third horizontal rod is immobilized relative to the second horizontal rod. 5. The system of claim 4 wherein said deflection rod includes a super elastic material. | 0.537234 |
8,165,987 | 1 | 6 | 1. An automatic rule generation system, comprising: a hardware computer that executes a computer program that implements the automatic rule generation system, the computer program including a rule generation module, a rule relaxation module, a rule testing module, an information extraction module, and a candidate suggestion module, wherein: the rule generation module receives a sample and generates a rule from the sample; the rule relaxation module generates a relaxed rule from the rule; the rule testing module generates a reverse index from a corpus, applies the relaxed rule to the reverse index to determine a superset of documents from the corpus that satisfy the relaxed rule as compared to a set of documents that satisfy the rules, and generates text segments from the superset of documents; the information extraction module generates modified text segments from the relaxed rule and the text segments; and the candidate suggestion module performs a candidate generation process using the modified text segments, wherein: if the candidate generation process generates no candidates from the modified text segments, the candidate suggestion module signals the rule relaxation module to generate a further relaxed rule to use as the relaxed rule, and if the candidate generation process generates a candidate from the modified text segments, the candidate suggestion module provides the candidate as an additional sample for the automatic rule generation system to generate another rule to use as the rule. | 1. An automatic rule generation system, comprising: a hardware computer that executes a computer program that implements the automatic rule generation system, the computer program including a rule generation module, a rule relaxation module, a rule testing module, an information extraction module, and a candidate suggestion module, wherein: the rule generation module receives a sample and generates a rule from the sample; the rule relaxation module generates a relaxed rule from the rule; the rule testing module generates a reverse index from a corpus, applies the relaxed rule to the reverse index to determine a superset of documents from the corpus that satisfy the relaxed rule as compared to a set of documents that satisfy the rules, and generates text segments from the superset of documents; the information extraction module generates modified text segments from the relaxed rule and the text segments; and the candidate suggestion module performs a candidate generation process using the modified text segments, wherein: if the candidate generation process generates no candidates from the modified text segments, the candidate suggestion module signals the rule relaxation module to generate a further relaxed rule to use as the relaxed rule, and if the candidate generation process generates a candidate from the modified text segments, the candidate suggestion module provides the candidate as an additional sample for the automatic rule generation system to generate another rule to use as the rule. 6. The automatic rule generation system of claim 1 , wherein the rule relaxation module stores a current rule. | 0.84058 |
9,547,832 | 23 | 25 | 23. A non-transitory machine-readable medium having computer-executable instructions stored thereon that when executed, causes one or more processors to perform operations comprising: receiving a content item from a communication channel, wherein: the content item comprises: a communication from an individual, and a statement by the individual, the statement comprising committing language about an intent to attend an event; identifying the event as a topic of interest in the content item; determining a commitment score of the individual to attend the event by: calculating a strength value of the intent of the individual to attend the event by performing a natural language analysis of the committing language of the statement by the individual in the content item; calculating a sentiment value of the intent of the individual to attend the event by performing a semantic analysis on the content item, the semantic analysis comprising identifying a description of a probability related to the event identified in the content item; calculating a social impact value of the intent of the individual to attend the event by performing a social impact analysis of the content item based on a number of receiving subscribers to the content item on the communication channel; and calculating a magnitude value of the intent of the individual to attend the event by performing a magnitude of commitment analysis of the content item based on a cost of attending the event, wherein: the commitment score comprises a combination of the strength value, the sentiment value, the social impact value, and the magnitude value; and determining an action based on the commitment score of the individual to attend the event. | 23. A non-transitory machine-readable medium having computer-executable instructions stored thereon that when executed, causes one or more processors to perform operations comprising: receiving a content item from a communication channel, wherein: the content item comprises: a communication from an individual, and a statement by the individual, the statement comprising committing language about an intent to attend an event; identifying the event as a topic of interest in the content item; determining a commitment score of the individual to attend the event by: calculating a strength value of the intent of the individual to attend the event by performing a natural language analysis of the committing language of the statement by the individual in the content item; calculating a sentiment value of the intent of the individual to attend the event by performing a semantic analysis on the content item, the semantic analysis comprising identifying a description of a probability related to the event identified in the content item; calculating a social impact value of the intent of the individual to attend the event by performing a social impact analysis of the content item based on a number of receiving subscribers to the content item on the communication channel; and calculating a magnitude value of the intent of the individual to attend the event by performing a magnitude of commitment analysis of the content item based on a cost of attending the event, wherein: the commitment score comprises a combination of the strength value, the sentiment value, the social impact value, and the magnitude value; and determining an action based on the commitment score of the individual to attend the event. 25. The non-transitory machine-readable medium of claim 23 , wherein determining the commitment score further comprises weighting the strength value, the sentiment value, the social impact value, and the magnitude value. | 0.791667 |
8,082,264 | 9 | 10 | 9. The article of manufacture according to claim 7 , wherein the operations further comprise: identifying at least one question class that includes at least one concept; identifying words in the current user query that are associated with the concept; modifying the identified question class by replacing the concept with the identified words in the current user query; and responding to the current user query with the modified question class. | 9. The article of manufacture according to claim 7 , wherein the operations further comprise: identifying at least one question class that includes at least one concept; identifying words in the current user query that are associated with the concept; modifying the identified question class by replacing the concept with the identified words in the current user query; and responding to the current user query with the modified question class. 10. The article of manufacture according to claim 9 , wherein the operations further comprise: identifying confidence factors for the question classes; and displaying the question classes according to the identified confidence factors. | 0.664286 |
8,903,174 | 47 | 48 | 47. A computer implemented method of processing text data to obtain processed text usable for serial text presentation on an electronic display, each step of the method using one or more computers, the method comprising: parsing the text data to identify at least words and sentences; creating respective display elements for displaying respective words identified from the text data; associating respective display data with the respective display elements, the respective display data being usable to display the respective display elements such that, for at least a plurality of display elements of the respective display elements, an optimal recognition position of each of the plurality of display elements is displayed at a substantially same location on the electronic display, referred to as a fixed display location; and electronically communicating the respective display elements and the respective display data for serially displaying the respective display elements on the electronic display. | 47. A computer implemented method of processing text data to obtain processed text usable for serial text presentation on an electronic display, each step of the method using one or more computers, the method comprising: parsing the text data to identify at least words and sentences; creating respective display elements for displaying respective words identified from the text data; associating respective display data with the respective display elements, the respective display data being usable to display the respective display elements such that, for at least a plurality of display elements of the respective display elements, an optimal recognition position of each of the plurality of display elements is displayed at a substantially same location on the electronic display, referred to as a fixed display location; and electronically communicating the respective display elements and the respective display data for serially displaying the respective display elements on the electronic display. 48. The method of claim 47 wherein the display data includes data identifying an optimal recognition character of the display element, the optimal recognition character to be displayed at the fixed display location. | 0.73192 |
8,484,031 | 1 | 3 | 1. A computer-implemented system for processing an interaction, the interaction including an utterance requiring recognition before being usable for further computer-implemented processing, the system comprising: an application configured to provide the utterance; a proxy processing subsystem in communication with the application, the proxy processing subsystem configured to receive the utterance and initiate processing thereof; a recognition decision engine configured to receive from the proxy processing system an utterance for recognition and ancillary information regarding the utterance for recognition, the recognition decision engine selecting, responsive to the ancillary information, one or more recognizers from a first type of recognizer subsystems and a second type of recognizer subsystems; and a results decision engine operably coupled with the one or more recognizers and configured to return to the proxy processing subsystem a recognition result, the results decision engine further automatically updating a statistics database responsive to results of processing by the one or more recognizers. | 1. A computer-implemented system for processing an interaction, the interaction including an utterance requiring recognition before being usable for further computer-implemented processing, the system comprising: an application configured to provide the utterance; a proxy processing subsystem in communication with the application, the proxy processing subsystem configured to receive the utterance and initiate processing thereof; a recognition decision engine configured to receive from the proxy processing system an utterance for recognition and ancillary information regarding the utterance for recognition, the recognition decision engine selecting, responsive to the ancillary information, one or more recognizers from a first type of recognizer subsystems and a second type of recognizer subsystems; and a results decision engine operably coupled with the one or more recognizers and configured to return to the proxy processing subsystem a recognition result, the results decision engine further automatically updating a statistics database responsive to results of processing by the one or more recognizers. 3. The system of claim 1 , wherein the ancillary information comprises recognition parameters provided by the application. | 0.743697 |
9,471,668 | 15 | 16 | 15. The computer program product set forth in claim 14 , wherein the Alchemy API service is configured to provide a set of synonyms associated with the first generation question, and wherein the concept-tagging API is configured to provide a set of keywords associated with at least one concept associated with the first generation answer. | 15. The computer program product set forth in claim 14 , wherein the Alchemy API service is configured to provide a set of synonyms associated with the first generation question, and wherein the concept-tagging API is configured to provide a set of keywords associated with at least one concept associated with the first generation answer. 16. The computer program product set forth in claim 15 , wherein the second generation subsystem includes a compare process configured to omit words from the set of keywords that are found in the set of synonyms. | 0.5 |
8,577,131 | 1 | 6 | 1. A method comprising: receiving a plurality of query images; matching the plurality of query images to a plurality of objects using a visual object recognition module, wherein the visual object recognition module is configured to utilize information from a training corpus to match query images to one or more training images of the plurality of objects, wherein the training corpus comprises one or more training images associated with the plurality of objects; associating match scores with matches between the query images and one or more matched training images, wherein the visual object recognition module is configured to determine match scores indicating a level of similarity between the query images and one or more matched training images; determining matched and unmatched query images based on the match scores associated with the query images, wherein query images with match scores above a score threshold are identified as matched query images and query images with match scores below the score threshold are identified as unmatched query images; and based on the determination, expanding the training corpus utilized by the visual object recognition module to include the matched query images, wherein the matched query images are added as additional training images associated with the objects to which the matched training images are associated, and the matched query images are used as training images when re-training the visual object recognition module on the expanded training corpus. | 1. A method comprising: receiving a plurality of query images; matching the plurality of query images to a plurality of objects using a visual object recognition module, wherein the visual object recognition module is configured to utilize information from a training corpus to match query images to one or more training images of the plurality of objects, wherein the training corpus comprises one or more training images associated with the plurality of objects; associating match scores with matches between the query images and one or more matched training images, wherein the visual object recognition module is configured to determine match scores indicating a level of similarity between the query images and one or more matched training images; determining matched and unmatched query images based on the match scores associated with the query images, wherein query images with match scores above a score threshold are identified as matched query images and query images with match scores below the score threshold are identified as unmatched query images; and based on the determination, expanding the training corpus utilized by the visual object recognition module to include the matched query images, wherein the matched query images are added as additional training images associated with the objects to which the matched training images are associated, and the matched query images are used as training images when re-training the visual object recognition module on the expanded training corpus. 6. The method of claim 1 , further comprising: receiving a plurality of candidate image corpora; matching the plurality of candidate image corpora to the unmatched query images using a second visual object recognition module, wherein the second visual object recognition module is configured to utilize information from a second training corpus comprising the unmatched query images to match images of the plurality of candidate image corpora to one or more of the unmatched query images; determining match statistics associated with the plurality of candidate image corpora; and based on the match statistics, selecting one or more candidate image corpora to add to the training corpus as training images. | 0.5 |
5,434,777 | 22 | 24 | 22. A method as recited in claim 20 wherein said mapping routine is a dynamic mapping routine. | 22. A method as recited in claim 20 wherein said mapping routine is a dynamic mapping routine. 24. A method as recited in claim 22 wherein said mapping routine includes a database query processor. | 0.605469 |
9,852,192 | 15 | 19 | 15. A non-transitory computer-readable medium containing computer-executable instructions that, when executed by a processor, cause the processor to perform a method for recommending media content, the method comprising: determining that a session including presentation of at least a first media content item and a second media content item is likely to have ended, wherein the second media content item is presented within a given span of the presentation of the first media content item; in response to determining that the session is likely to have ended, determining a first plurality of topics associated with the first media content item and the second media content item; determining a second plurality of topics associated with the media content presentation session based on distance information for pairs of topics in the first plurality of topics, wherein each of the pairs of topics includes a first topic associated with the first media content item and a second topic associated with the second media content item; and transmitting an indication of a plurality of media content items that correspond to at least a portion of the second plurality of topics. | 15. A non-transitory computer-readable medium containing computer-executable instructions that, when executed by a processor, cause the processor to perform a method for recommending media content, the method comprising: determining that a session including presentation of at least a first media content item and a second media content item is likely to have ended, wherein the second media content item is presented within a given span of the presentation of the first media content item; in response to determining that the session is likely to have ended, determining a first plurality of topics associated with the first media content item and the second media content item; determining a second plurality of topics associated with the media content presentation session based on distance information for pairs of topics in the first plurality of topics, wherein each of the pairs of topics includes a first topic associated with the first media content item and a second topic associated with the second media content item; and transmitting an indication of a plurality of media content items that correspond to at least a portion of the second plurality of topics. 19. The non-transitory computer-readable medium of claim 15 , wherein the method further comprises, for each of the first media content item and the second media content item, generating a single rank-ordered list of the second plurality of topics. | 0.5 |
8,374,983 | 9 | 11 | 9. The method of claim 1 , wherein receiving a request to classify an object comprises receiving a request to classify a Website of an advertiser for which advertisements are presented with online media. | 9. The method of claim 1 , wherein receiving a request to classify an object comprises receiving a request to classify a Website of an advertiser for which advertisements are presented with online media. 11. The method of claim 9 , wherein receiving a request to classify a Website of an advertiser comprises: receiving a periodic request to classify a previously identified Website; and receiving a request to classify a newly identified Website. | 0.5 |
9,207,666 | 1 | 9 | 1. A method to display localized process control objects, the method comprising: in response to a request to monitor a process control object associated with a process control system, selecting a device description file based on the process control object, the device description file including a first tag and instructions for displaying information generated by the process control object; selecting a set of locale templates based on a locale associated with the request, wherein each of the locale templates includes a reference to process control information; selecting a locale template from the set of locale templates by: determining which of the set of locale templates includes a second tag matching the first tag; identifying a type of the process control object; and matching the type to the locale template by identifying an indicator that specifies the locale template is configured to display the type of the process control object; and processing, via a logic circuit, the process control object for display by inserting portions of the selected locale template into the first tag in the device description file. | 1. A method to display localized process control objects, the method comprising: in response to a request to monitor a process control object associated with a process control system, selecting a device description file based on the process control object, the device description file including a first tag and instructions for displaying information generated by the process control object; selecting a set of locale templates based on a locale associated with the request, wherein each of the locale templates includes a reference to process control information; selecting a locale template from the set of locale templates by: determining which of the set of locale templates includes a second tag matching the first tag; identifying a type of the process control object; and matching the type to the locale template by identifying an indicator that specifies the locale template is configured to display the type of the process control object; and processing, via a logic circuit, the process control object for display by inserting portions of the selected locale template into the first tag in the device description file. 9. A method as defined in claim 1 , wherein processing the process control object for display includes rendering data related to the process control object. | 0.808354 |
8,577,893 | 1 | 2 | 1. A method performed by a device, comprising: identifying a link in a first document, the link being associated with a second document; analyzing a first portion of text to the left of the link in the first document; analyzing a second portion of text to the right of the link in the first document; identifying a first rare word from the text in the first portion, where the first rare word is identified as a rare word based on a frequency of occurrence of the first rare word in a set of documents; identifying a second rare word from the text in the second portion, where the second rare word is identified as a rare word based on a frequency of occurrence of the second rare word in the set of documents; creating a context identifier based only on the first and second rare words; and ranking the second document within a list of search results based on the context identifier. | 1. A method performed by a device, comprising: identifying a link in a first document, the link being associated with a second document; analyzing a first portion of text to the left of the link in the first document; analyzing a second portion of text to the right of the link in the first document; identifying a first rare word from the text in the first portion, where the first rare word is identified as a rare word based on a frequency of occurrence of the first rare word in a set of documents; identifying a second rare word from the text in the second portion, where the second rare word is identified as a rare word based on a frequency of occurrence of the second rare word in the set of documents; creating a context identifier based only on the first and second rare words; and ranking the second document within a list of search results based on the context identifier. 2. The method of claim 1 , where identifying a first rare word and identifying a second rare word comprise: comparing words in the first and second portions to a table that identifies occurrences of a plurality of words in the set of documents, and determining which of the words in the first and second portions occurred least often in the set of documents based on the table. | 0.545783 |
9,171,058 | 8 | 17 | 8. A program product comprising a computer readable physically tangible storage device storing program code, said program code configured to be executed by a processor to implement a method, said method comprising the steps of: creating a semantic entity repository comprising (a) a structured entity set of entities and properties thereof; (b) reference ranges describing possible values of said properties; and (c) a plurality of mappings between said entities, said properties, and a data structure of a data warehouse; selecting, from said semantic entity repository, entities, properties and/or property values to be analyzed; defining how to calculate at least one measure; loading, from said data warehouse, a plurality of data corresponding to the selected entities, properties, and property values according to said mappings; calculating at least one of the defined measures; and marking a time-dependent property and defining mappings to the data warehouse for tracking the variation of the property, wherein said step of defining comprises incorporating an adjusting item related to said variation into the calculation of a measure related to said time-dependent property. | 8. A program product comprising a computer readable physically tangible storage device storing program code, said program code configured to be executed by a processor to implement a method, said method comprising the steps of: creating a semantic entity repository comprising (a) a structured entity set of entities and properties thereof; (b) reference ranges describing possible values of said properties; and (c) a plurality of mappings between said entities, said properties, and a data structure of a data warehouse; selecting, from said semantic entity repository, entities, properties and/or property values to be analyzed; defining how to calculate at least one measure; loading, from said data warehouse, a plurality of data corresponding to the selected entities, properties, and property values according to said mappings; calculating at least one of the defined measures; and marking a time-dependent property and defining mappings to the data warehouse for tracking the variation of the property, wherein said step of defining comprises incorporating an adjusting item related to said variation into the calculation of a measure related to said time-dependent property. 17. The program product of claim 8 , where A denotes a first characteristic of the entities; where B denotes a second characteristic of the entities; wherein the time-dependent property comprises a first time-dependent component having a property value A 1 associated with the first characteristic A at a first time t 1 and a property value A 2 associated with the first characteristic A at a second time t 2 >t 1 ; wherein the time-dependent property comprises a second time-dependent component having a property value B 1 associated with the second characteristic B at the first time t 1 and a property value B 2 associated with the second characteristic B at the second time t 2 ; wherein the measure has a first component (M A ) and a second component (M B ); wherein M A has a value M A1 at the first time t 1 and a value M A2 at the second time t 2 ; wherein M B has a value M B1 at the first time t 1 and a value M B2 at the second time t 2 ; wherein the adjusting item has an adjustment value Δ; wherein the method further comprises calculating M A1 , M A2 , M B1 , and M B2 via
M A1 =A 1 ,
M A2 =A 1 +A 2 −Δ,
M B1 =B 1 ,
M B2 =B 1 +B 2 +Δ; and wherein Δ=M A1 . | 0.5 |
9,858,260 | 1 | 11 | 1. A method for analyzing items using lexical analysis and filtering process comprising of: storing a plurality of items in a data storage unit, wherein said plurality of items are represented by source data and said source data is one of structured data and unstructured data; parsing the unstructured data of the source data to extract at least One textual data along with any available structured supporting information; parsing the structured data of the source data to extract a set of associated data in a tuple structure, said tuple structure being formed by each a subject being the conceptual information representing each item of said plurality of items, a predicate including information representing one or more categories of each item of said plurality of items, and an object including information representing the extracted data itself; processing the extracted data from each item of said plurality of items, wherein said extracted data is associated with an item of said plurality of items; processing the extracted data from each item of said plurality of items, wherein said extracted data is matched against a list of synonyms associated with said plurality of items; displaying a first group of said items based on said extracted data of said items on an electronic display presented in at least one of a tabular view and a geospatial view, wherein said electronic display is electrically connected to at least one processor in electronic communication with said source data, wherein said first group of said items represents items having at least one common characteristic of said extracted data; mapping each of said plurality of items with at least one lexicon term, wherein said extracted data is analyzed to identify a match between said plurality of items and lexicon terms, wherein said lexicon terms are represented as a network of a plurality of nodes and each node of said plurality of nodes represents a lexicon term, which is subordinate to at least one of a parent node and a child node; mapping each of said plurality of items with at least one lexicon term based on an associated synonym, wherein said extracted data is analyzed to identify a match between said plurality of items and synonyms of said lexicon terms, wherein said lexicon terms are represented as said network of said plurality of nodes and each node of said plurality of nodes represents said lexicon term, said associated synonyms corresponding with at least one lexicon term identified at each node of said plurality of nodes; and displaying a second group of said items, wherein said second group of items represent said items mapped to a first matching lexicon term of said plurality of lexicon terms on said electronic display presented in at least one of said tabular view and said geospatial view, wherein said electronic display is electrically connected to at least one processor in electronic communication with said source data. | 1. A method for analyzing items using lexical analysis and filtering process comprising of: storing a plurality of items in a data storage unit, wherein said plurality of items are represented by source data and said source data is one of structured data and unstructured data; parsing the unstructured data of the source data to extract at least One textual data along with any available structured supporting information; parsing the structured data of the source data to extract a set of associated data in a tuple structure, said tuple structure being formed by each a subject being the conceptual information representing each item of said plurality of items, a predicate including information representing one or more categories of each item of said plurality of items, and an object including information representing the extracted data itself; processing the extracted data from each item of said plurality of items, wherein said extracted data is associated with an item of said plurality of items; processing the extracted data from each item of said plurality of items, wherein said extracted data is matched against a list of synonyms associated with said plurality of items; displaying a first group of said items based on said extracted data of said items on an electronic display presented in at least one of a tabular view and a geospatial view, wherein said electronic display is electrically connected to at least one processor in electronic communication with said source data, wherein said first group of said items represents items having at least one common characteristic of said extracted data; mapping each of said plurality of items with at least one lexicon term, wherein said extracted data is analyzed to identify a match between said plurality of items and lexicon terms, wherein said lexicon terms are represented as a network of a plurality of nodes and each node of said plurality of nodes represents a lexicon term, which is subordinate to at least one of a parent node and a child node; mapping each of said plurality of items with at least one lexicon term based on an associated synonym, wherein said extracted data is analyzed to identify a match between said plurality of items and synonyms of said lexicon terms, wherein said lexicon terms are represented as said network of said plurality of nodes and each node of said plurality of nodes represents said lexicon term, said associated synonyms corresponding with at least one lexicon term identified at each node of said plurality of nodes; and displaying a second group of said items, wherein said second group of items represent said items mapped to a first matching lexicon term of said plurality of lexicon terms on said electronic display presented in at least one of said tabular view and said geospatial view, wherein said electronic display is electrically connected to at least one processor in electronic communication with said source data. 11. The method for analyzing items using lexical analysis and filtering process of claim 1 , further comprising concurrently presenting said tabular view and said geospatial view on said electronic display with said processor. | 0.786792 |
7,734,650 | 6 | 8 | 6. A data display server connected to a user terminal to display prescribed data in response to a request through the user terminal, said data display server comprising: a reference database that holds item data configured to be referred to by a user; message creating means for permitting the user to create, through the user terminal, a message to be posted; keyword input means for permitting the user to input, through the user terminal, a keyword of reference data about contents of the message; item data retrieving means for retrieving the item data from the reference database by the keyword; item data juxtaposing means for juxtaposing and displaying, on a display of the user terminal, one or more pieces of item data resulting from the retrieval; item data selecting means for permitting the user to select, through the user terminal, the item data attached to posting data from the displayed item data; posting means for permitting the user to post, through the user terminal, the posting data containing an item data ID of the item data selected by the item data selecting means; a posting database that holds the posting data including (i) the posting message, a posting ID identifying the posting message, and the item data ID having been posted through the user terminal and (ii) responsive posting data including a responsive posting message, a posting ID identifying the responsive posting message, and an item data ID; posting browsing means for displaying, on the display of the user terminal in response to a posting data browsing request from the user, the posting data and the item data specified by the item data ID contained in the posting data; relational metadata generating means for extracting the item data ID one by one from the posting data and the responsive posting data according to a relationship between the posting data and the responsive posting data to generate relational metadata with the extracted item data IDs contained therein, said responsive posting data posted in response to the posting data posted by said user terminal; and a relational database configured to hold said generated relational metadata; wherein said item data is one or more pieces of information selected from a group comprising the item data ID, an item data name, an alias item data name, a model number, a manufacturer name, a category, a descriptive text, an image URL, a price, and a release date, said data display device further comprising relational data juxtaposing means for juxtaposing and displaying, on a display of said user terminal in response to an item data browsing request from the user, said item data and relational data associated with said item data by said relational metadata wherein said time of relationship to said item data includes one or more relationships selected from a group comprising a way to use the item data, a function, an effect, a combination, similarity and a purchase history, and said relational metadata associates the item data specified by the extracted item data IDs. | 6. A data display server connected to a user terminal to display prescribed data in response to a request through the user terminal, said data display server comprising: a reference database that holds item data configured to be referred to by a user; message creating means for permitting the user to create, through the user terminal, a message to be posted; keyword input means for permitting the user to input, through the user terminal, a keyword of reference data about contents of the message; item data retrieving means for retrieving the item data from the reference database by the keyword; item data juxtaposing means for juxtaposing and displaying, on a display of the user terminal, one or more pieces of item data resulting from the retrieval; item data selecting means for permitting the user to select, through the user terminal, the item data attached to posting data from the displayed item data; posting means for permitting the user to post, through the user terminal, the posting data containing an item data ID of the item data selected by the item data selecting means; a posting database that holds the posting data including (i) the posting message, a posting ID identifying the posting message, and the item data ID having been posted through the user terminal and (ii) responsive posting data including a responsive posting message, a posting ID identifying the responsive posting message, and an item data ID; posting browsing means for displaying, on the display of the user terminal in response to a posting data browsing request from the user, the posting data and the item data specified by the item data ID contained in the posting data; relational metadata generating means for extracting the item data ID one by one from the posting data and the responsive posting data according to a relationship between the posting data and the responsive posting data to generate relational metadata with the extracted item data IDs contained therein, said responsive posting data posted in response to the posting data posted by said user terminal; and a relational database configured to hold said generated relational metadata; wherein said item data is one or more pieces of information selected from a group comprising the item data ID, an item data name, an alias item data name, a model number, a manufacturer name, a category, a descriptive text, an image URL, a price, and a release date, said data display device further comprising relational data juxtaposing means for juxtaposing and displaying, on a display of said user terminal in response to an item data browsing request from the user, said item data and relational data associated with said item data by said relational metadata wherein said time of relationship to said item data includes one or more relationships selected from a group comprising a way to use the item data, a function, an effect, a combination, similarity and a purchase history, and said relational metadata associates the item data specified by the extracted item data IDs. 8. The data display server according to claim 6 , wherein said relational metadata has a parameter on a degree of relevancy, and sets the degree of relevancy high depending on the number of pieces of relational metadata containing the item data IDs equal to each other. | 0.5 |
9,881,516 | 9 | 10 | 9. The server recited in claim 8 , wherein each seed site domain includes a listener engine for tracking listener events. | 9. The server recited in claim 8 , wherein each seed site domain includes a listener engine for tracking listener events. 10. The server recited in claim 9 , wherein the pool of watermarked questions are submitted to a learning management system as a replacement for original questions to be used for an assessment. | 0.5 |
9,665,643 | 1 | 10 | 1. A computer-implemented method to identify search results based on entity-based knowledge, the method comprising: receiving a search query that includes one or more entities; enumerating one or more entities from an entity-based knowledge store that may match entities in the received query; identifying one or more potentially matching entities from the enumerated entities, wherein a matching entity is one that may be a target of the query; ranking the identified potentially matching entities to distinguish a relative level of match between each identified entity and one or more entities in the received query; selecting one or more of the identified potentially matching entities as matching entities with which to go forward with a search; performing an entity-based search that narrows results by applying one or more top ranked, selected matching entities; ranking multiple results returned from the entity-based search so as to order the results by relevance to the received search query, by (i) dynamically determining entity identifiers by: identifying a first group of one or more results each without an entity identifier; identifying a second group of one or more results, different from the first group, each with an entity identifier; and comparing members of the first group with members of the second group, and then (ii) grouping results by entities with which the results are associated; and providing the ranked search results in response to the received query, wherein the preceding steps are performed by at least one processor. | 1. A computer-implemented method to identify search results based on entity-based knowledge, the method comprising: receiving a search query that includes one or more entities; enumerating one or more entities from an entity-based knowledge store that may match entities in the received query; identifying one or more potentially matching entities from the enumerated entities, wherein a matching entity is one that may be a target of the query; ranking the identified potentially matching entities to distinguish a relative level of match between each identified entity and one or more entities in the received query; selecting one or more of the identified potentially matching entities as matching entities with which to go forward with a search; performing an entity-based search that narrows results by applying one or more top ranked, selected matching entities; ranking multiple results returned from the entity-based search so as to order the results by relevance to the received search query, by (i) dynamically determining entity identifiers by: identifying a first group of one or more results each without an entity identifier; identifying a second group of one or more results, different from the first group, each with an entity identifier; and comparing members of the first group with members of the second group, and then (ii) grouping results by entities with which the results are associated; and providing the ranked search results in response to the received query, wherein the preceding steps are performed by at least one processor. 10. The method of claim 1 wherein performing the entity-based search comprises applying the identified entities as well as any additional information in the query to find search results relevant for the identified entities. | 0.591575 |
8,713,054 | 65 | 68 | 65. A system to assist an information security classification process of an organization for security classification and marking of an electronic document, said system comprising at least one computer system, where said at least one computer system comprising at least one electronic storage medium, where said at least one electronic storage medium comprising at least one software engine, where said at least one software engine comprising: a. establish an electronic document security regimen comprising at least one criterion of an information security classification process, b. display a user classification dialogue for at least one informational portion of an electronic document, where said user classification dialogue comprising a menu of choices, where said menu of choices comprising at least one element for selection, and where said at least one element is associated with said at least one criterion of said electronic document security regimen, c. retrieve said at least one element, where said at least one element is selected, d. establish a classification mark from said at least one criterion associated with the retrieved said at least one element, and e. insert said classification mark into said electronic document. | 65. A system to assist an information security classification process of an organization for security classification and marking of an electronic document, said system comprising at least one computer system, where said at least one computer system comprising at least one electronic storage medium, where said at least one electronic storage medium comprising at least one software engine, where said at least one software engine comprising: a. establish an electronic document security regimen comprising at least one criterion of an information security classification process, b. display a user classification dialogue for at least one informational portion of an electronic document, where said user classification dialogue comprising a menu of choices, where said menu of choices comprising at least one element for selection, and where said at least one element is associated with said at least one criterion of said electronic document security regimen, c. retrieve said at least one element, where said at least one element is selected, d. establish a classification mark from said at least one criterion associated with the retrieved said at least one element, and e. insert said classification mark into said electronic document. 68. The system of claim 65 , wherein said at least one software engine further comprising insert a location storage path for said electronic document into said electronic document. | 0.822835 |
8,868,420 | 14 | 18 | 14. A non-transitory computer-readable medium storing instructions that, when executed by a processor on a computing device, cause the computing device to at least: receive a first transcription comprising first text and second text, wherein the first transcription was created by transcribing first audio data using a speech recognition engine configured to filter the first transcription by automatically replacing one or more words with corresponding numbers or digits formatted as a telephone number; receive a first value associated with the first text and a second confidence value associated with the second text; and cause presentation of the first text with a first graphical element indicating the first value and presentation of the second text with a second graphical element indicating the second value. | 14. A non-transitory computer-readable medium storing instructions that, when executed by a processor on a computing device, cause the computing device to at least: receive a first transcription comprising first text and second text, wherein the first transcription was created by transcribing first audio data using a speech recognition engine configured to filter the first transcription by automatically replacing one or more words with corresponding numbers or digits formatted as a telephone number; receive a first value associated with the first text and a second confidence value associated with the second text; and cause presentation of the first text with a first graphical element indicating the first value and presentation of the second text with a second graphical element indicating the second value. 18. The non-transitory computer-readable medium of claim 14 , further comprising instructions to present the telephone number as a hyperlink. | 0.757732 |
8,407,667 | 8 | 14 | 8. A method comprising: extracting metadata from server-side source code of a server project of an application under development on a software development computer, the application comprising server-side software generated from the server-side source code and client-side software generated from client-side source code, wherein the extracted metadata comprises metadata associated with a set of program entities comprising a transitive closure of program entities referenced in the extracted metadata, wherein the program entities are entities exposed by the server-side software to the client-side software and wherein the extracted metadata does not comprise a program entity that is not exposed to the client-side software by the server-side software; determining program entities within the set of program entities for which a definition is missing in the server-side source code; replacing each of the program entities within the set of program entities for which the definition is missing with a placeholder entity; marking each placeholder entity; generating a library from the extracted metadata without compilation of the server project, wherein the library comprises metadata associated with a program entity of the set of program entities and does not comprise an executable; receiving the generated library and generating client-side source code and documentation and disambiguation information associated with the program entity of the set of program entities from the generated library by reflection; and displaying the documentation and disambiguation information in a client source code editor dynamically during client-side software development on the software development computer. | 8. A method comprising: extracting metadata from server-side source code of a server project of an application under development on a software development computer, the application comprising server-side software generated from the server-side source code and client-side software generated from client-side source code, wherein the extracted metadata comprises metadata associated with a set of program entities comprising a transitive closure of program entities referenced in the extracted metadata, wherein the program entities are entities exposed by the server-side software to the client-side software and wherein the extracted metadata does not comprise a program entity that is not exposed to the client-side software by the server-side software; determining program entities within the set of program entities for which a definition is missing in the server-side source code; replacing each of the program entities within the set of program entities for which the definition is missing with a placeholder entity; marking each placeholder entity; generating a library from the extracted metadata without compilation of the server project, wherein the library comprises metadata associated with a program entity of the set of program entities and does not comprise an executable; receiving the generated library and generating client-side source code and documentation and disambiguation information associated with the program entity of the set of program entities from the generated library by reflection; and displaying the documentation and disambiguation information in a client source code editor dynamically during client-side software development on the software development computer. 14. The method of claim 8 , further comprising: extracting source code from the server project, the extracted source code comprising an undefined class that exposes an API to the client-side software, wherein documentation and disambiguation information for the undefined class is not dynamically displayed in the client source code editor during the client-side software development. | 0.551402 |
4,396,906 | 19 | 20 | 19. An encoder for converting fixed length digital words into variable length code words comprising, a memory unit addressed by said fixed length digital words to be encoded, said memory unit having stored therein a plurality of fixed length words having different numbers of 0's in adjacent bit positions of the words, a multiplexer connected to said memory unit for sequentially scanning outputs therefrom for generating said code words, said multiplexing scanning starting at an initial multiplexer address, means under control of the output from the multiplexer output for stopping multiplexer scanning when the output from the multiplexer is a 1's bit, and for returning to the initial multiplexer address in preparation for the next scanning operation. | 19. An encoder for converting fixed length digital words into variable length code words comprising, a memory unit addressed by said fixed length digital words to be encoded, said memory unit having stored therein a plurality of fixed length words having different numbers of 0's in adjacent bit positions of the words, a multiplexer connected to said memory unit for sequentially scanning outputs therefrom for generating said code words, said multiplexing scanning starting at an initial multiplexer address, means under control of the output from the multiplexer output for stopping multiplexer scanning when the output from the multiplexer is a 1's bit, and for returning to the initial multiplexer address in preparation for the next scanning operation. 20. An encoder as defined in claim 19 including, a shift register into which said multiplexer output is shifted for holding variable length code words from the multiplexer. | 0.5 |
7,624,277 | 4 | 5 | 4. The method of claim 1 further comprising delivering the resulting image to a client for rendering to the user in response to a user request for access to a server via the client, said client and said server being coupled to a data communication network. | 4. The method of claim 1 further comprising delivering the resulting image to a client for rendering to the user in response to a user request for access to a server via the client, said client and said server being coupled to a data communication network. 5. The method of claim 4 wherein altering the characters, concatenating the altered characters into the character string, generating the original image, performing an operation to the original image, and generating the resulting image occurs directly in response to the user request. | 0.5 |
8,224,672 | 1 | 12 | 1. A computer implemented method of preparing an executable representation of a rating model, the method comprising: defining an actuary-manipulable representation of a rating model, the actuary-manipulable representation embodied in computer readable media and encoding therein variables, factor tables and calculation sequences of the rating model, the factor tables having one or more axes bound to respective ones of the variables and the calculation sequences defined in terms of steps operative on values of the variables and cells of the factor tables; and transforming the actuary-manipulable representation to the executable representation, the executable representation embodied in computer readable media and encoding therein resultant computer program code including a runtime lookup facility for identification of runtime identifiers in the executable representation corresponding to ones of the variables and a calculate method executable to generate a quote based on inputs supplied via a predefined input interface, wherein the transforming is performed at least in part by a compiler that executes on a computational machine. | 1. A computer implemented method of preparing an executable representation of a rating model, the method comprising: defining an actuary-manipulable representation of a rating model, the actuary-manipulable representation embodied in computer readable media and encoding therein variables, factor tables and calculation sequences of the rating model, the factor tables having one or more axes bound to respective ones of the variables and the calculation sequences defined in terms of steps operative on values of the variables and cells of the factor tables; and transforming the actuary-manipulable representation to the executable representation, the executable representation embodied in computer readable media and encoding therein resultant computer program code including a runtime lookup facility for identification of runtime identifiers in the executable representation corresponding to ones of the variables and a calculate method executable to generate a quote based on inputs supplied via a predefined input interface, wherein the transforming is performed at least in part by a compiler that executes on a computational machine. 12. The computer implemented method of claim 1 , wherein the transforming includes a two-step compilation, a first step thereof producing a platform independent source form from the actuary-manipulable representation, and a second step thereof producing the executable representation from the platform independent source form and encoding same as the resultant computer program code. | 0.794748 |
9,690,815 | 6 | 7 | 6. The method of claim 5 , further comprising: receiving a predictive query or a latent structure query requesting a result from the indices generated by processing the dataset; and executing the query against the generated indices prior to terminating processing of the dataset. | 6. The method of claim 5 , further comprising: receiving a predictive query or a latent structure query requesting a result from the indices generated by processing the dataset; and executing the query against the generated indices prior to terminating processing of the dataset. 7. The method of claim 6 , further comprising: returning a predictive record set responsive to the predictive query or the latent structure query requesting the result; and returning a notification with the result indicating processing of the dataset has not yet completed or a notification with the result indicating the confidence quality measure is below the specified threshold, or both. | 0.5 |
10,043,367 | 15 | 16 | 15. A system comprising: a memory; one or more processor in communication with memory; and program instructions executable by the one or more processor via the memory to perform a method comprising: collecting user data from the user; analyzing a context of an event from the user data, wherein the event comprises one or more actions; identifying subsequent actions of the event based on the context of the event and participants of the event; creating one or more context-personality-cognitive state (CPC) mapping; adding the one or more CPC mapping to a knowledgebase by machine learning; predicting a first cognitive state of the user while performing a first subsequent action amongst the subsequent actions of the event by use of the knowledgebase; and generating an alarm for a first subsequent action based on the predicted first cognitive state of the user and notifying the generated alarm to the user. | 15. A system comprising: a memory; one or more processor in communication with memory; and program instructions executable by the one or more processor via the memory to perform a method comprising: collecting user data from the user; analyzing a context of an event from the user data, wherein the event comprises one or more actions; identifying subsequent actions of the event based on the context of the event and participants of the event; creating one or more context-personality-cognitive state (CPC) mapping; adding the one or more CPC mapping to a knowledgebase by machine learning; predicting a first cognitive state of the user while performing a first subsequent action amongst the subsequent actions of the event by use of the knowledgebase; and generating an alarm for a first subsequent action based on the predicted first cognitive state of the user and notifying the generated alarm to the user. 16. The system of claim 15 , wherein the collecting is performed by use of one or more data collection agent sending the user data, wherein the user data includes at least one of the following selected from the group consisting of event data, personality data, and cognitive state data. | 0.761667 |
8,731,617 | 1 | 2 | 1. A method for initiating voice calls from a communication device, comprising: causing, without user intervention, each number string in text of a data item which matches first predetermined criteria to be displayed in a first format and each number string in the text of the data item which does not match the first predetermined criteria to be displayed in a second format; causing a voice call to be initiated to a number string displayed in the first format when the number string is selected and first predetermined user input is detected; causing a list of user selectable functions to be displayed in response to detecting second predetermined user input when a position marker is located within a number string, the list of user selectable functions including a voice call function for initiating a voice call to the number string when the number string matches second predetermined criteria, wherein the second predetermined criteria are different from the first predetermined criteria; and causing a voice call to be initiated to a number string when the voice call function for the number string is selected from the list of user selectable functions. | 1. A method for initiating voice calls from a communication device, comprising: causing, without user intervention, each number string in text of a data item which matches first predetermined criteria to be displayed in a first format and each number string in the text of the data item which does not match the first predetermined criteria to be displayed in a second format; causing a voice call to be initiated to a number string displayed in the first format when the number string is selected and first predetermined user input is detected; causing a list of user selectable functions to be displayed in response to detecting second predetermined user input when a position marker is located within a number string, the list of user selectable functions including a voice call function for initiating a voice call to the number string when the number string matches second predetermined criteria, wherein the second predetermined criteria are different from the first predetermined criteria; and causing a voice call to be initiated to a number string when the voice call function for the number string is selected from the list of user selectable functions. 2. The method of claim 1 , wherein the second predetermined criteria are less stringent than the first predetermined criteria. | 0.853828 |
8,473,971 | 11 | 14 | 11. A method comprising: employing at least one processor executing computer executable instructions stored on a memory to implement the following acts: supplying a user with an option, prior to compiling at least a portion of software code in a computing system, the software code portion including at least one variable of a changeable static type, that allows the user to determine whether to opt-in to utilize late binding during compilation of the software code portion, whether to opt-out and utilize non late binding and determine what type of late binding to implement on the software code portion during compilation of the software code portion associated with a programming language in which the software code portion was written, wherein the type for variables with changeable static types is inferred based on the use of the variable, wherein the at least one variable has one static type in one software code region and the same at least one variable has a different static type in another software code region, and wherein the option to opt-in or opt-out allows the same at least one variable name to be used with different static types in a plurality of different software code segments of the software code portion; determining that one of the late binding is to be utilized or the non late binding is to be utilized based at least in part on an indication regarding the option obtained from the user; performing the one of the late binding or the non late binding based at least in part on the determination; inferring a type of a variable; and changing a static type of the variable as part of the programming language. | 11. A method comprising: employing at least one processor executing computer executable instructions stored on a memory to implement the following acts: supplying a user with an option, prior to compiling at least a portion of software code in a computing system, the software code portion including at least one variable of a changeable static type, that allows the user to determine whether to opt-in to utilize late binding during compilation of the software code portion, whether to opt-out and utilize non late binding and determine what type of late binding to implement on the software code portion during compilation of the software code portion associated with a programming language in which the software code portion was written, wherein the type for variables with changeable static types is inferred based on the use of the variable, wherein the at least one variable has one static type in one software code region and the same at least one variable has a different static type in another software code region, and wherein the option to opt-in or opt-out allows the same at least one variable name to be used with different static types in a plurality of different software code segments of the software code portion; determining that one of the late binding is to be utilized or the non late binding is to be utilized based at least in part on an indication regarding the option obtained from the user; performing the one of the late binding or the non late binding based at least in part on the determination; inferring a type of a variable; and changing a static type of the variable as part of the programming language. 14. The method of claim 11 further comprising designating type of late binding for the programming language. | 0.64 |
7,856,446 | 1 | 3 | 1. A method for identifying, extracting using a processor, capturing, and leveraging expertise and knowledge comprising: observing, between and among peers and experts who show high affinity with regard to any of the users, assets, and topics/terms, a user heartbeat which comprises user activity, including mouse movement and stable pauses on an asset, while the asset is in a user display foreground; based upon the observing, detecting user think time for the asset; employing automatic techniques to extract patterns from at least the user think time; and learning affinities between and among any of the users, assets and topics/terms from the extracted patterns for any of: automatically determining each user's peer group, predicting a desired destination of the users in a navigation context, calculating an expert and peer impact factor, an asset impact factor, or rareness, determining importance of an asset and/or expertise that individuals possess, without asking the individuals directly, automatically disambiguating query terms in an online search, and/or effecting a predictive query by suggesting search terms to the users or automatically inserting search terms into user queries to expand a search, wherein learning affinities includes applying a formula to lower weights of the term as the terms become associated with more assets. | 1. A method for identifying, extracting using a processor, capturing, and leveraging expertise and knowledge comprising: observing, between and among peers and experts who show high affinity with regard to any of the users, assets, and topics/terms, a user heartbeat which comprises user activity, including mouse movement and stable pauses on an asset, while the asset is in a user display foreground; based upon the observing, detecting user think time for the asset; employing automatic techniques to extract patterns from at least the user think time; and learning affinities between and among any of the users, assets and topics/terms from the extracted patterns for any of: automatically determining each user's peer group, predicting a desired destination of the users in a navigation context, calculating an expert and peer impact factor, an asset impact factor, or rareness, determining importance of an asset and/or expertise that individuals possess, without asking the individuals directly, automatically disambiguating query terms in an online search, and/or effecting a predictive query by suggesting search terms to the users or automatically inserting search terms into user queries to expand a search, wherein learning affinities includes applying a formula to lower weights of the term as the terms become associated with more assets. 3. The method of claim 1 , further comprising: providing a significantly greater weighting to the importance of implicit observations over the weighting provided to explicit observations. | 0.829068 |
8,545,538 | 8 | 9 | 8. A method as in claim 1 , wherein the second portion of the interconnecting member comprises a spherical end segment. | 8. A method as in claim 1 , wherein the second portion of the interconnecting member comprises a spherical end segment. 9. A method as in claim 8 , further comprising articulating the second portion of the interconnecting member within the first housing via a ball-in-socket articulation thereof. | 0.5 |
8,700,625 | 1 | 4 | 1. A computer-implemented method for identifying alternative merchant items, the method comprising: maintaining, by a computer, information regarding a plurality of merchant items; analyzing, by the computer, information regarding a plurality of queries to identify a plurality of merchant item-query pairs, each merchant item-query pair comprising a query and a merchant item that was previously selected from results for the query; for each merchant item-query pair, determining, by the computer, a number of times that the merchant item was selected from results for the query; for each merchant item-query pair, determining, by the computer, whether the query of the merchant item-query pair is associated with the merchant item of the merchant item-query pair based on the number of times that the merchant item was selected from results for the query relative to a number of times that results for the query were presented; analyzing, by the computer, the information regarding the plurality of queries to identify comparison queries directed to a comparison between two or more of the plurality of merchant items; and determining, by the computer, whether a first merchant item is an alternative to a second merchant item based on a number of times that a query associated with the first merchant item is included in a comparison query with a query associated with the second merchant item. | 1. A computer-implemented method for identifying alternative merchant items, the method comprising: maintaining, by a computer, information regarding a plurality of merchant items; analyzing, by the computer, information regarding a plurality of queries to identify a plurality of merchant item-query pairs, each merchant item-query pair comprising a query and a merchant item that was previously selected from results for the query; for each merchant item-query pair, determining, by the computer, a number of times that the merchant item was selected from results for the query; for each merchant item-query pair, determining, by the computer, whether the query of the merchant item-query pair is associated with the merchant item of the merchant item-query pair based on the number of times that the merchant item was selected from results for the query relative to a number of times that results for the query were presented; analyzing, by the computer, the information regarding the plurality of queries to identify comparison queries directed to a comparison between two or more of the plurality of merchant items; and determining, by the computer, whether a first merchant item is an alternative to a second merchant item based on a number of times that a query associated with the first merchant item is included in a comparison query with a query associated with the second merchant item. 4. The computer-implemented method of claim 1 , wherein determining, for each merchant item-query pair, whether the query of the merchant item-query pair is associated with the merchant item of the merchant item-query pair further comprises: computing a ratio between the number of times that the merchant item of the merchant item-query pair was selected from results for the query of the merchant item-query pair and a number of times that the query was received; determining whether the ratio meets or exceeds a threshold; and in response to the ratio meeting or exceeding the threshold, determining that the query of the merchant item-query pair is associated with the merchant item of the merchant item-query pair. | 0.693782 |
8,874,447 | 1 | 4 | 1. A method for allowing multimodal communication with a first device executing a speech-enabled application during a communication session with a user, comprising: with the first device, at a first time during the communication session, receiving a first signal from a voice server via a communication channel, the first signal corresponding to speech recognition results generated by the voice server of a voice input originating from a voice interface operated by the user during the communication session; with the first device, processing the first signal with the speech-enabled application during the communication session with the user to generate a first responsive output; with the first device, at a second time during the communication session with the user, receiving a second signal from the voice server via the communication channel, the second signal corresponding to a text input originating from a text interface operated by the user during the communication session, the voice server having received the text input via a communications network; and with the first device, processing the second signal with the speech-enabled application during the communication session with the user to generate a second responsive output, and communicating a third signal corresponding to the second responsive output to the text interface via a communication path exclusive of the voice server. | 1. A method for allowing multimodal communication with a first device executing a speech-enabled application during a communication session with a user, comprising: with the first device, at a first time during the communication session, receiving a first signal from a voice server via a communication channel, the first signal corresponding to speech recognition results generated by the voice server of a voice input originating from a voice interface operated by the user during the communication session; with the first device, processing the first signal with the speech-enabled application during the communication session with the user to generate a first responsive output; with the first device, at a second time during the communication session with the user, receiving a second signal from the voice server via the communication channel, the second signal corresponding to a text input originating from a text interface operated by the user during the communication session, the voice server having received the text input via a communications network; and with the first device, processing the second signal with the speech-enabled application during the communication session with the user to generate a second responsive output, and communicating a third signal corresponding to the second responsive output to the text interface via a communication path exclusive of the voice server. 4. The method of claim 1 , wherein: the voice server is capable of communicating with each of the voice interface and the text interface, and the method further comprises: with the first device, receiving each of the first signal and the second signal from the voice server via the communication channel. | 0.556851 |
9,305,543 | 8 | 12 | 8. A method for converting text to speech, the method comprising: at an electronic device with a processor and memory storing one or more programs for execution by the processor: parsing a document to identify a subset of text to be converted to speech, the subset of text having a context; creating an announcement comprising a spoken description of the context; determining, by the processor, an order in which the announcement and a spoken form of the subset of text are to be spoken, wherein the determined order comprises speaking the announcement prior to the spoken form of the subset of text; and generating audio that includes the spoken form of the subset of text and the announcement, wherein the announcement is spoken prior to the spoken form of the subset of text. | 8. A method for converting text to speech, the method comprising: at an electronic device with a processor and memory storing one or more programs for execution by the processor: parsing a document to identify a subset of text to be converted to speech, the subset of text having a context; creating an announcement comprising a spoken description of the context; determining, by the processor, an order in which the announcement and a spoken form of the subset of text are to be spoken, wherein the determined order comprises speaking the announcement prior to the spoken form of the subset of text; and generating audio that includes the spoken form of the subset of text and the announcement, wherein the announcement is spoken prior to the spoken form of the subset of text. 12. The method of claim 8 , wherein the document does not include text corresponding to the announcement. | 0.893509 |
8,166,392 | 27 | 28 | 27. The storage device of claim 23 wherein outputting the priority comprises: determining an expected loss of non-review of the subsequent message at a current time; determining an expected cost of alerting the user of the subsequent message at the current time; and, alerting the user of the subsequent message upon determining that the expected loss is greater than the expected cost. | 27. The storage device of claim 23 wherein outputting the priority comprises: determining an expected loss of non-review of the subsequent message at a current time; determining an expected cost of alerting the user of the subsequent message at the current time; and, alerting the user of the subsequent message upon determining that the expected loss is greater than the expected cost. 28. The storage device of claim 27 , wherein determining an expected loss of non-review of the subsequent message at a current time considers the expected loss of non-review of the subsequent message at a future time when the user would otherwise review the message. | 0.5 |
8,140,499 | 1 | 3 | 1. A method, in a data processing hardware system having a processor, comprising: receiving, from a user, a query to a root context of a context tree, the query including a name and value pair; traversing, upon detecting the query to the root context of the context tree, the context tree for a parent context of a subcontext corresponding to the name and value pair; and determining, by the processor, whether the parent context caches all query results. | 1. A method, in a data processing hardware system having a processor, comprising: receiving, from a user, a query to a root context of a context tree, the query including a name and value pair; traversing, upon detecting the query to the root context of the context tree, the context tree for a parent context of a subcontext corresponding to the name and value pair; and determining, by the processor, whether the parent context caches all query results. 3. The method of claim 1 , further comprising: iterating, upon the parent context caching all query results, each query result, and filtering out remaining name and value pairs. | 0.805495 |
9,189,180 | 8 | 13 | 8. A system for converting an electronic document for output by a multifunction peripheral comprising: a converter peripheral comprising: a network interface for receiving the electronic document, the electronic document in a page description language unsupported by the multifunction peripheral; a processor for determining that conversion of the electronic document by the converter peripheral is unlicensed, generating a single-use license for the converter peripheral enabling the converter peripheral to output only the electronic document, and outputting, via the multifunction peripheral, a physical document including configuration data for the converter peripheral, thus consuming the single-use license; the processor further for accessing configuration data in order to determine at least one page description language supported by the multifunction peripheral, for accessing local license data to confirm that the converter peripheral is authorized to perform a conversion, and for converting the electronic document into a page description language supported by the multifunction peripheral; and an output interface for transmitting the converted electronic document to the multifunction peripheral for output. | 8. A system for converting an electronic document for output by a multifunction peripheral comprising: a converter peripheral comprising: a network interface for receiving the electronic document, the electronic document in a page description language unsupported by the multifunction peripheral; a processor for determining that conversion of the electronic document by the converter peripheral is unlicensed, generating a single-use license for the converter peripheral enabling the converter peripheral to output only the electronic document, and outputting, via the multifunction peripheral, a physical document including configuration data for the converter peripheral, thus consuming the single-use license; the processor further for accessing configuration data in order to determine at least one page description language supported by the multifunction peripheral, for accessing local license data to confirm that the converter peripheral is authorized to perform a conversion, and for converting the electronic document into a page description language supported by the multifunction peripheral; and an output interface for transmitting the converted electronic document to the multifunction peripheral for output. 13. The system of claim 8 wherein the electronic document is in a format other than printer command language XL (PCL XL) format and the converted electronic document is in printer command language XL (PCL XL) format. | 0.654952 |
8,442,931 | 14 | 20 | 14. A system for searching a data set for one or more data patterns, comprising: a receiver computer configured to obtain at least one data block of the data set; a rule computer configured to generate a graph rule set that represents a set of rules as a graph, wherein said set of rules describes the one or more data patterns; a search computer configured to traverse said graph rule set as a function of a current state of said graph rule set and said at least one data block, wherein a value of said data block falls within a predefined range of values of said graph rule set, and identifies a rule of said set of rules based upon traversal of said graph rule set; and a mechanism configured to read said identified rule and modify said data set by attaching a flag to said data set based on at least in part on said identified rule. | 14. A system for searching a data set for one or more data patterns, comprising: a receiver computer configured to obtain at least one data block of the data set; a rule computer configured to generate a graph rule set that represents a set of rules as a graph, wherein said set of rules describes the one or more data patterns; a search computer configured to traverse said graph rule set as a function of a current state of said graph rule set and said at least one data block, wherein a value of said data block falls within a predefined range of values of said graph rule set, and identifies a rule of said set of rules based upon traversal of said graph rule set; and a mechanism configured to read said identified rule and modify said data set by attaching a flag to said data set based on at least in part on said identified rule. 20. The system of claim 14 , further comprising a mechanism configured to transmit an alert to a user. | 0.819149 |
8,532,989 | 1 | 2 | 1. A command recognition device comprising: an utterance understanding unit that determines or selects word sequence information from speech information; speech confidence degree calculating unit that calculates degree of speech confidence based on the speech information and the word sequence information; a phrase confidence degree calculating unit that calculates a degree of phrase confidence based on image information and phrase information included in the word sequence information; an image analysis unit that calculates a trajectory-of-motion of an object from the image information, wherein the trajectory of motion is calculated based on time-series data of position coordinates of a trajectory in a motion of an object, where the position coordinates are variable in time; and a motion control instructing unit that determines whether a command of the word sequence information is to be executed based on a command estimation value which is calculated using the degree of speech confidence and the degree of phrase confidence, wherein the phrase confidence degree calculating unit calculates a degree of motion confidence representing the confidence that the trajectory-of-motion comprises a motion of the phrase information as the degree of phrase confidence. | 1. A command recognition device comprising: an utterance understanding unit that determines or selects word sequence information from speech information; speech confidence degree calculating unit that calculates degree of speech confidence based on the speech information and the word sequence information; a phrase confidence degree calculating unit that calculates a degree of phrase confidence based on image information and phrase information included in the word sequence information; an image analysis unit that calculates a trajectory-of-motion of an object from the image information, wherein the trajectory of motion is calculated based on time-series data of position coordinates of a trajectory in a motion of an object, where the position coordinates are variable in time; and a motion control instructing unit that determines whether a command of the word sequence information is to be executed based on a command estimation value which is calculated using the degree of speech confidence and the degree of phrase confidence, wherein the phrase confidence degree calculating unit calculates a degree of motion confidence representing the confidence that the trajectory-of-motion comprises a motion of the phrase information as the degree of phrase confidence. 2. The command recognition device according to claim 1 , wherein the image analysis unit calculates a feature quantity of an object from the image information, and wherein the phrase confidence degree calculating unit calculates an degree of image confidence representing the confidence that the object having the feature quantity is an object of the phrase information as the degree of phrase confidence. | 0.5 |
7,962,331 | 13 | 16 | 13. The method of claim 1 , further comprising determining, based at least in part on the transcript and the information associated with the decode, a modification of the speech recognizer to improve its performance. | 13. The method of claim 1 , further comprising determining, based at least in part on the transcript and the information associated with the decode, a modification of the speech recognizer to improve its performance. 16. The method of claim 13 , wherein the modification comprises modifying a word pronunciation, dictionary, or acoustic model of the speech recognizer. | 0.5 |
7,617,224 | 1 | 4 | 1. A method for managing hierarchically related software components, comprising: creating a first software component descriptor containing information about a first software component of a plurality of software components; creating a second software component descriptor containing information about a second software component of the plurality of software components; creating a plurality of aggregate descriptors, each descriptor containing information about relationships among the plurality of software components and aggregates of the plurality of software components; defining hierarchical interrelationships between the plurality of software components and the aggregate descriptors to produce a component hierarchy; managing lifecycles, access controls, interrelationships, versioning and a list of the plurality of software components to maintain the consistency of the component hierarchy; filtering the list of software components based upon the component hierarchy to produce a filtered list of software components; selecting a particular software component from the filtered list of software components; and integrating the particular software component into a software application; and modifying the component hierarchy based upon associations generated by the filtering. | 1. A method for managing hierarchically related software components, comprising: creating a first software component descriptor containing information about a first software component of a plurality of software components; creating a second software component descriptor containing information about a second software component of the plurality of software components; creating a plurality of aggregate descriptors, each descriptor containing information about relationships among the plurality of software components and aggregates of the plurality of software components; defining hierarchical interrelationships between the plurality of software components and the aggregate descriptors to produce a component hierarchy; managing lifecycles, access controls, interrelationships, versioning and a list of the plurality of software components to maintain the consistency of the component hierarchy; filtering the list of software components based upon the component hierarchy to produce a filtered list of software components; selecting a particular software component from the filtered list of software components; and integrating the particular software component into a software application; and modifying the component hierarchy based upon associations generated by the filtering. 4. The method of claim 1 , wherein the component hierarchy is made up of a plurality of layers, each layer of the plurality of layers defining a different scope of connectivity between corresponding software components or aggregates of software components. | 0.5 |
8,520,982 | 3 | 5 | 3. The method of claim 2 , wherein associating one or more of the keywords from the reference advertisement with the first advertisement comprises: for each of the one or more keywords, determining a performance of the keyword with the reference advertisement; comparing the performances of the one or more keywords; and selecting a keyword from the one or more keywords to associate with the first advertisement based on the performances. | 3. The method of claim 2 , wherein associating one or more of the keywords from the reference advertisement with the first advertisement comprises: for each of the one or more keywords, determining a performance of the keyword with the reference advertisement; comparing the performances of the one or more keywords; and selecting a keyword from the one or more keywords to associate with the first advertisement based on the performances. 5. The method of claim 3 , wherein the performance is a click-through rate. | 0.735915 |
8,275,769 | 20 | 21 | 20. A method for identifying users relevant to a topic of interest, comprising: executing a query comprising one or more topics against a corpus of messages and to identify voting users associated with the messages matching the query; generating a set of candidate users comprising further users connected to the voting users; computing a relevancy score for each candidate user; ranking the candidate users by their respective relevancy score; identifying one or more messages of each candidate user and to apply a topic model to the identified messages; and re-ranking each candidate user based on the topic model in accordance with:
Score Combined =W LinkStructure *Score LinkStructure +W LDA *Score LDA , where Score Linkstructure equals the relevancy score, Score LDA equals the topic model, and 0<W LinkStructure , W LDA <1 and W LinkStructure +W LDA =1. | 20. A method for identifying users relevant to a topic of interest, comprising: executing a query comprising one or more topics against a corpus of messages and to identify voting users associated with the messages matching the query; generating a set of candidate users comprising further users connected to the voting users; computing a relevancy score for each candidate user; ranking the candidate users by their respective relevancy score; identifying one or more messages of each candidate user and to apply a topic model to the identified messages; and re-ranking each candidate user based on the topic model in accordance with:
Score Combined =W LinkStructure *Score LinkStructure +W LDA *Score LDA , where Score Linkstructure equals the relevancy score, Score LDA equals the topic model, and 0<W LinkStructure , W LDA <1 and W LinkStructure +W LDA =1. 21. A method according to claim 20 , further comprising: calculating a number of the voting users for each candidate user; and calculating a number of total users comprising the voting users and non-voting users connected to each candidate user. | 0.5 |
9,026,427 | 1 | 2 | 1. A computer-implemented method for generating side information for grammar-based data compression systems, the method comprising: obtaining an admissible grammar (G) for an input sequence (A(S 0 )) having a finite set of terminal symbols, the admissible grammar having a finite set of variables (S(j)), including a starting variable (S 0 ) representing the input sequence (A(S 0 )), and a production rule for each variable in the finite set of variables (S(j))); constructing a graph representation of the admissible grammar (G), the graph representation including nodes for each variable in the finite set of variables and each terminal symbol in the finite set of terminal symbols, including a root node representing the starting variable (S 0 ) and directed edges linking the nodes, each directed edge being directed to a node and representing an instance of a variable or a terminal symbol corresponding to the node to which it is directed in the admissible grammar (G) as defined by the production rules, and each directed edge having an expansion frequency, wherein the expansion frequency of directed edges originating from the root node has a value of ‘1’, and expansion frequencies of directed edges emanating from each non-root node are determined in accordance with summing of expansion frequencies of directed edges input to the non-root node; pruning, from the graph representation, a directed edge having a lowest expansion frequency to generate a pruned graph representation; deriving a pruned grammar (Gi); expanding a starting variable (S 0,i ) of the pruned grammar (Gi) to generate the side information; and storing the side information in a computer memory device; wherein constructing the graph representation of the admissible grammar further comprises determining, for each non-terminal node, a shortest path from the root node to the non-terminal node, and assigning a shortest distance (SD) value to each non-terminal node in accordance with its respective shortest path; wherein, when two or more directed edges are identified as having the same lowest expansion frequency, pruning the directed edge having the lowest expansion frequency comprises applying tie-breaking rules to select the directed edge to prune; wherein the tie-breaking rules comprise at least one of selecting the one of the two or more directed edges with the greatest shortest distance (SD) value, selecting the one of the two or more directed edges leading to a node with the shortest expanded sequence length. | 1. A computer-implemented method for generating side information for grammar-based data compression systems, the method comprising: obtaining an admissible grammar (G) for an input sequence (A(S 0 )) having a finite set of terminal symbols, the admissible grammar having a finite set of variables (S(j)), including a starting variable (S 0 ) representing the input sequence (A(S 0 )), and a production rule for each variable in the finite set of variables (S(j))); constructing a graph representation of the admissible grammar (G), the graph representation including nodes for each variable in the finite set of variables and each terminal symbol in the finite set of terminal symbols, including a root node representing the starting variable (S 0 ) and directed edges linking the nodes, each directed edge being directed to a node and representing an instance of a variable or a terminal symbol corresponding to the node to which it is directed in the admissible grammar (G) as defined by the production rules, and each directed edge having an expansion frequency, wherein the expansion frequency of directed edges originating from the root node has a value of ‘1’, and expansion frequencies of directed edges emanating from each non-root node are determined in accordance with summing of expansion frequencies of directed edges input to the non-root node; pruning, from the graph representation, a directed edge having a lowest expansion frequency to generate a pruned graph representation; deriving a pruned grammar (Gi); expanding a starting variable (S 0,i ) of the pruned grammar (Gi) to generate the side information; and storing the side information in a computer memory device; wherein constructing the graph representation of the admissible grammar further comprises determining, for each non-terminal node, a shortest path from the root node to the non-terminal node, and assigning a shortest distance (SD) value to each non-terminal node in accordance with its respective shortest path; wherein, when two or more directed edges are identified as having the same lowest expansion frequency, pruning the directed edge having the lowest expansion frequency comprises applying tie-breaking rules to select the directed edge to prune; wherein the tie-breaking rules comprise at least one of selecting the one of the two or more directed edges with the greatest shortest distance (SD) value, selecting the one of the two or more directed edges leading to a node with the shortest expanded sequence length. 2. The method of claim 1 further comprising updating expansion frequencies of each directed edge in accordance with the pruned representation. | 0.755172 |
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