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8,190,595 | 12 | 13 | 12. The method of claim 11 , further comprising: determining that K=1; designating the OP node as a unary OP node; and determining whether the candidate match of a single child of the unary OP node is valid for the OP node. | 12. The method of claim 11 , further comprising: determining that K=1; designating the OP node as a unary OP node; and determining whether the candidate match of a single child of the unary OP node is valid for the OP node. 13. The method of claim 12 , further comprising: determining that the candidate match of a single child of the unary OP node is valid for the OP node; and adding the candidate match of the single child to the candidate match results. | 0.5 |
7,640,498 | 30 | 36 | 30. A computer-readable storage medium that includes data and instructions for enabling actions to be performed on a remote platform, comprising: a first component for enabling a request for a document from the remote platform, a type of the platform including a type of an operating system and type of a native browser that are employed to display the document; a second component for enabling a determination of the type of the remote platform and selectively associating a size ratio between a plurality of font sizes with the determined type of the remote platform, the enabling the determination of the type of the remote platform comprising enabling a determination of the type of the operating system and the determination of the type of the native browser, and the selective association being based on the determination of the type of the operating system and the determination of the type of the native browser; a third component for enabling the document with a plurality of font sizes for the document to be provided to the remote platform for display, the document is being locally scaled for display by the operation of the native browser with the size ratio for the plurality of font sizes; and a fourth component for enabling the plurality of font sizes to be changed by an execution of a script included with the document using at least one control of the native browser operating on the remote platform, the size ratio between the plurality of font sizes being determined by the native browser and maintained for a change to a size of at least one font displayed in the document at the remote platform, the execution changes the at least one font for at least one markup language text element displayed within the document. | 30. A computer-readable storage medium that includes data and instructions for enabling actions to be performed on a remote platform, comprising: a first component for enabling a request for a document from the remote platform, a type of the platform including a type of an operating system and type of a native browser that are employed to display the document; a second component for enabling a determination of the type of the remote platform and selectively associating a size ratio between a plurality of font sizes with the determined type of the remote platform, the enabling the determination of the type of the remote platform comprising enabling a determination of the type of the operating system and the determination of the type of the native browser, and the selective association being based on the determination of the type of the operating system and the determination of the type of the native browser; a third component for enabling the document with a plurality of font sizes for the document to be provided to the remote platform for display, the document is being locally scaled for display by the operation of the native browser with the size ratio for the plurality of font sizes; and a fourth component for enabling the plurality of font sizes to be changed by an execution of a script included with the document using at least one control of the native browser operating on the remote platform, the size ratio between the plurality of font sizes being determined by the native browser and maintained for a change to a size of at least one font displayed in the document at the remote platform, the execution changes the at least one font for at least one markup language text element displayed within the document. 36. The computer-readable storage medium of claim 30 , wherein the document is provided in a mark-up language. | 0.859335 |
8,024,425 | 13 | 14 | 13. A system comprising: a processor; and a memory coupled to the processor, the memory to provide functionality including, a deployment service to receive a deployable Web services archive file, wherein the Web services archive file includes: a WSDL file describing a Web service to be deployed, a Web service class implementation file, a Web Service Definition Language (WSDL) mapping file that includes mapping information, a types file specifying a mapping between XML complex types and Java class files, a configuration file, and a metadata descriptor file describing locations of the files in the Web services archive; a deployment manager to deploy the Web services archive file received by the deployment service, the deployment manager to store the mapping information in a web services registry; a runtime data registry to store at least a portion of the Web services archive's contents; and a runtime object to retrieve the mapping information from the Web services registry to cause the mapping information to store as web service data in a cache that is accessible within a message processing runtime framework by the Web service to process messages, the mapping information includes a plurality of mapping descriptors that includes a first mapping descriptor, the first mapping descriptor includes a first value that corresponds to a first message and a first method descriptor that corresponds to a first method. | 13. A system comprising: a processor; and a memory coupled to the processor, the memory to provide functionality including, a deployment service to receive a deployable Web services archive file, wherein the Web services archive file includes: a WSDL file describing a Web service to be deployed, a Web service class implementation file, a Web Service Definition Language (WSDL) mapping file that includes mapping information, a types file specifying a mapping between XML complex types and Java class files, a configuration file, and a metadata descriptor file describing locations of the files in the Web services archive; a deployment manager to deploy the Web services archive file received by the deployment service, the deployment manager to store the mapping information in a web services registry; a runtime data registry to store at least a portion of the Web services archive's contents; and a runtime object to retrieve the mapping information from the Web services registry to cause the mapping information to store as web service data in a cache that is accessible within a message processing runtime framework by the Web service to process messages, the mapping information includes a plurality of mapping descriptors that includes a first mapping descriptor, the first mapping descriptor includes a first value that corresponds to a first message and a first method descriptor that corresponds to a first method. 14. The system of claim 13 , wherein the Web services deployable archive file is a WAR file. | 0.5 |
9,570,047 | 7 | 10 | 7. A method of providing an interactive area representation on a display device with at least one computer, the method comprising simultaneously displaying on the display device: the area representation; a highlighted portion of the area representation indicating a first portion of the area representation that can be positioned on the area representation by a pointing device; outside of the area representation a magnified representation of the first portion of the area representation represented by the highlighted portion; information about one or more specific items associated with the area representation on the area representation, on the magnified representation or both; and outside of the area representation and the magnified representation additional information about at least one specific item of the one or more specific items, wherein the additional information about the at least one specific item includes user-selectable information; the method further comprising: in response to user input to the at least one computer with the pointing device to select user-selectable additional information from the additional information about the at least one specific item, positioning the highlighted portion on the area representation to indicate a second portion of the area representation corresponding to a location on the area representation related to the selected additional information, displaying a magnified representation of the second area representation portion represented by the positioned highlighted portion, and displaying with at least part of the additional information outside the area representation and the magnified representation further information about the at least one specific item; the method further comprising: in response to user input to the at least one computer to the area representation with the pointing device, positioning the highlighted portion on the area representation to indicate a third portion of the area representation, displaying a magnified representation of the third area representation portion indicated by the highlighted portion and displaying outside of the area representation and outside of the magnified representation additional information about at least one specific item indicated on the third area representation portion. | 7. A method of providing an interactive area representation on a display device with at least one computer, the method comprising simultaneously displaying on the display device: the area representation; a highlighted portion of the area representation indicating a first portion of the area representation that can be positioned on the area representation by a pointing device; outside of the area representation a magnified representation of the first portion of the area representation represented by the highlighted portion; information about one or more specific items associated with the area representation on the area representation, on the magnified representation or both; and outside of the area representation and the magnified representation additional information about at least one specific item of the one or more specific items, wherein the additional information about the at least one specific item includes user-selectable information; the method further comprising: in response to user input to the at least one computer with the pointing device to select user-selectable additional information from the additional information about the at least one specific item, positioning the highlighted portion on the area representation to indicate a second portion of the area representation corresponding to a location on the area representation related to the selected additional information, displaying a magnified representation of the second area representation portion represented by the positioned highlighted portion, and displaying with at least part of the additional information outside the area representation and the magnified representation further information about the at least one specific item; the method further comprising: in response to user input to the at least one computer to the area representation with the pointing device, positioning the highlighted portion on the area representation to indicate a third portion of the area representation, displaying a magnified representation of the third area representation portion indicated by the highlighted portion and displaying outside of the area representation and outside of the magnified representation additional information about at least one specific item indicated on the third area representation portion. 10. The method of claim 7 , wherein displaying the information about the one or more items associated with the area representation on the area representation, on the magnified representation or both includes displaying a link to other information. | 0.662568 |
8,091,067 | 1 | 34 | 1. A method for hosting a programming environment and processing user input, the method comprising the step of: (a) receiving, during a first session between a user and an interaction environment, via one of a plurality of media gateways, a definition of an expression type, the definition specifying an expression format and a response type; (b) storing the definition of the expression type; (c) receiving, during a second session between a second user and the interaction environment, via one of a plurality of media gateways, from the second user, an expression having a semantic structure; (d) evaluating the semantic structure of the expression; (e) identifying an expression format of the received expression as the expression format specified by the definition of the expression type, responsive to the evaluation of the semantic structure; and (f) generating a response to the expression based on the identified expression format and responsive to an execution of a computer program associated with the response type specified by the definition of the expression type. | 1. A method for hosting a programming environment and processing user input, the method comprising the step of: (a) receiving, during a first session between a user and an interaction environment, via one of a plurality of media gateways, a definition of an expression type, the definition specifying an expression format and a response type; (b) storing the definition of the expression type; (c) receiving, during a second session between a second user and the interaction environment, via one of a plurality of media gateways, from the second user, an expression having a semantic structure; (d) evaluating the semantic structure of the expression; (e) identifying an expression format of the received expression as the expression format specified by the definition of the expression type, responsive to the evaluation of the semantic structure; and (f) generating a response to the expression based on the identified expression format and responsive to an execution of a computer program associated with the response type specified by the definition of the expression type. 34. The method of claim 1 , wherein step (f) further comprises determining to store the received expression, the response and an identification of the user. | 0.803526 |
9,418,312 | 1 | 7 | 1. A method for coarsely classifying with one or more controllers whether or not an unknown input document belongs to a group with one or more reference documents earlier classified, each defining structured or unstructured formats of text and background, comprising: receiving images at one or more controllers for said each of the unknown input document and the one or more reference documents; determining counts of contours for the images corresponding to the unknown input document and the one or more reference documents; establishing a permissible range for the counts of contours for the images corresponding to the one or more reference documents such that an unknown document belongs or not to the group with the one or more reference documents if falling within the permissible range; comparing the counts of contours between the images corresponding to the unknown input document and the one or more reference documents; and determining inclusion or not of the unknown input document in the group with the one or more referenced documents based on whether the counts of contours for the image corresponding to the unknown input document falls within or not the permissible range for the counts of contours for the images corresponding to the one or more reference documents. | 1. A method for coarsely classifying with one or more controllers whether or not an unknown input document belongs to a group with one or more reference documents earlier classified, each defining structured or unstructured formats of text and background, comprising: receiving images at one or more controllers for said each of the unknown input document and the one or more reference documents; determining counts of contours for the images corresponding to the unknown input document and the one or more reference documents; establishing a permissible range for the counts of contours for the images corresponding to the one or more reference documents such that an unknown document belongs or not to the group with the one or more reference documents if falling within the permissible range; comparing the counts of contours between the images corresponding to the unknown input document and the one or more reference documents; and determining inclusion or not of the unknown input document in the group with the one or more referenced documents based on whether the counts of contours for the image corresponding to the unknown input document falls within or not the permissible range for the counts of contours for the images corresponding to the one or more reference documents. 7. The method of claim 1 , further including coarsely classifying additional unknown documents relative to the one or more reference documents. | 0.822581 |
9,355,360 | 12 | 13 | 12. The system of claim 11 , wherein the data annotation application further configures the processor to generate an annotation task comprising a portion of the set of source data, where the annotation task configures an annotator to annotate one or more features within the set of source data. | 12. The system of claim 11 , wherein the data annotation application further configures the processor to generate an annotation task comprising a portion of the set of source data, where the annotation task configures an annotator to annotate one or more features within the set of source data. 13. The system of claim 12 , wherein the annotation tasks are targeted toward one or more annotator groups. | 0.5 |
7,962,495 | 1 | 2 | 1. A method comprising performing a machine-executed operation involving instructions, wherein said instructions are instructions which, when executed by one or more processors, cause the one or more processors to perform certain steps including: creating and storing an ontology for a data store in response to receiving first user input defining the ontology, wherein the ontology comprises a plurality of data object types and a plurality of object property types; wherein each object property type, of the plurality of object property types, includes a data type of data that is associated with said each object property type; creating one or more parser definitions in response to receiving second user input defining the parser definitions, wherein each of the parser definitions specifies one or more sub-definitions of how to transform first input data into modified input data that is compatible with one of the object property types of the ontology for the data store; storing each of the one or more parser definitions in association with one of the plurality of object property types of the ontology for the data store; wherein the machine-executed operation is at least one of (a) storing said instructions onto a non-transitory machine-readable storage medium, and (b) executing the instructions; wherein the method is performed by one or more computer systems. | 1. A method comprising performing a machine-executed operation involving instructions, wherein said instructions are instructions which, when executed by one or more processors, cause the one or more processors to perform certain steps including: creating and storing an ontology for a data store in response to receiving first user input defining the ontology, wherein the ontology comprises a plurality of data object types and a plurality of object property types; wherein each object property type, of the plurality of object property types, includes a data type of data that is associated with said each object property type; creating one or more parser definitions in response to receiving second user input defining the parser definitions, wherein each of the parser definitions specifies one or more sub-definitions of how to transform first input data into modified input data that is compatible with one of the object property types of the ontology for the data store; storing each of the one or more parser definitions in association with one of the plurality of object property types of the ontology for the data store; wherein the machine-executed operation is at least one of (a) storing said instructions onto a non-transitory machine-readable storage medium, and (b) executing the instructions; wherein the method is performed by one or more computer systems. 2. The method of claim 1 , further comprising: receiving the first input data; determining whether the first input data matches one of the parser sub-definitions; using a matching one of the parser sub-definitions, creating and storing the modified input data; storing the modified input data in a property of the property type that is identified in the matching one of the parser sub-definitions. | 0.727335 |
6,076,061 | 26 | 27 | 26. The speech recognition method according to claim 21, further comprising the step of controlling the weight for each class of recognition information to be used in the recognition process is controlled in accordance with the viewpoint detected in said detecting step and executing the speech recognition using classes of the recognition, wherein said selecting step selects a class of the recognition information based on the weight and recognition results of said executing step and selects an application corresponding to the selected recognition information, and wherein said recognizing step determines the recognition result of the speech recognition corresponding to the selected class of the recognition information as an input command to be subjected to the selected application. | 26. The speech recognition method according to claim 21, further comprising the step of controlling the weight for each class of recognition information to be used in the recognition process is controlled in accordance with the viewpoint detected in said detecting step and executing the speech recognition using classes of the recognition, wherein said selecting step selects a class of the recognition information based on the weight and recognition results of said executing step and selects an application corresponding to the selected recognition information, and wherein said recognizing step determines the recognition result of the speech recognition corresponding to the selected class of the recognition information as an input command to be subjected to the selected application. 27. The speech recognition method according to claim 26, wherein, in said selecting step, a plurality of areas each of which is related to a different class of recognition information are set and the weight for each class of the recognition information is controlled in accordance with relationship between the viewpoint detected in said detecting step and each of the plurality of areas. | 0.5 |
8,856,124 | 16 | 17 | 16. The system of claim 14 , wherein the image classification apparatus is configured to maintain a weighted graph in which the image classification apparatus represents the reference image and the co-selected image as nodes in the weighted graph, each node being connected to other nodes by weighted edges representing sequential selections of the images represented by the nodes connected by the weighted edges. | 16. The system of claim 14 , wherein the image classification apparatus is configured to maintain a weighted graph in which the image classification apparatus represents the reference image and the co-selected image as nodes in the weighted graph, each node being connected to other nodes by weighted edges representing sequential selections of the images represented by the nodes connected by the weighted edges. 17. The system of claim 16 , wherein the image classification apparatus generates the topic scores for the co-selected images represented by nodes in the weighted graph based on the weighted edges for the nodes representing the co-selected images. | 0.5 |
9,672,524 | 20 | 25 | 20. A method for organizing, managing, and reporting data relating to a corporate entity, comprising: retrieving an entity record comprising a value and a lineage entry, the lineage entry comprising a value source, the value source referencing a first document; retrieving a corporate action stored as a computer-readable process definition, the corporate action defining a set of stakeholders; creating a second document based on the entity record and on stakeholder input; applying a status tag to the second document indicating a status of the second document in a document workflow, the status tag being applied as a human-readable, freeform text format data object associated with the second document; and storing the second document record in association with both a hierarchically delimited child tag and additional tags that are hierarchically related as parent tags of the hierarchically delimited child tag, without requiring a user to request storage of both the child tag and the additional parent tags. | 20. A method for organizing, managing, and reporting data relating to a corporate entity, comprising: retrieving an entity record comprising a value and a lineage entry, the lineage entry comprising a value source, the value source referencing a first document; retrieving a corporate action stored as a computer-readable process definition, the corporate action defining a set of stakeholders; creating a second document based on the entity record and on stakeholder input; applying a status tag to the second document indicating a status of the second document in a document workflow, the status tag being applied as a human-readable, freeform text format data object associated with the second document; and storing the second document record in association with both a hierarchically delimited child tag and additional tags that are hierarchically related as parent tags of the hierarchically delimited child tag, without requiring a user to request storage of both the child tag and the additional parent tags. 25. The method of claim 20 , wherein the second document is one of a board resolution, a shareholder consent, a shareholder communication, and a stock plan. | 0.751592 |
9,984,151 | 1 | 6 | 1. A computer system comprising: a processor; a memory device holding an instruction set executable on the processor to cause the computer system to perform operations comprising: receiving a query in a user session, the query comprising one or more search parameters; detecting, in the user session and after receiving the query, a user event associated with an item in search results for the query; determining a property associated with the item in the search results; creating a refinement comprising an association between the property and the one or more search parameters, wherein refinements record hierarchical associations between properties of items and a corresponding one or more search parameters, and wherein the association between the property and the one or more search parameters is associated with a score that is updated based on a plurality of user actions, wherein the score is updated based on changing the score; and ranking search results for a subsequent query based on a plurality of refinements comprising the refinement. | 1. A computer system comprising: a processor; a memory device holding an instruction set executable on the processor to cause the computer system to perform operations comprising: receiving a query in a user session, the query comprising one or more search parameters; detecting, in the user session and after receiving the query, a user event associated with an item in search results for the query; determining a property associated with the item in the search results; creating a refinement comprising an association between the property and the one or more search parameters, wherein refinements record hierarchical associations between properties of items and a corresponding one or more search parameters, and wherein the association between the property and the one or more search parameters is associated with a score that is updated based on a plurality of user actions, wherein the score is updated based on changing the score; and ranking search results for a subsequent query based on a plurality of refinements comprising the refinement. 6. The computer system of claim 1 , wherein a first plurality of refinements comprising the refinement is stored separately from a second plurality of refinements, such that the first plurality of refinements is associated with a first class of users and the second plurality of refinements is associated with a second class of users. | 0.5 |
7,496,746 | 3 | 5 | 3. The apparatus of claim 2 , wherein the processing device is further operative to: prompt the user with a configuration query, using the output device; and receive configuration responses from the input device. | 3. The apparatus of claim 2 , wherein the processing device is further operative to: prompt the user with a configuration query, using the output device; and receive configuration responses from the input device. 5. The apparatus of claim 3 , wherein prompting the user includes displaying the at least one user configuration document on the output device, the document having data fields for user input of the configuration responses into the input device. | 0.5 |
8,306,822 | 10 | 13 | 10. A method of providing reading tutoring, comprising: receiving a textual indication of a story; building a target context free grammar at runtime based on a portion of the textual indication; obtaining a garbage model that is indicative of a list of words in a general domain; prompting a user for an utterance; providing a received acoustic signal of the user's utterance to a speech recognition engine; comparing an output from the speech recognition engine to the target context free grammar; comparing an output from the speech recognition engine to at least a portion of the garbage model; storing an indication of the comparison to at least one of the target context free grammar and the garbage model in a data store including an indication of the user who provided the utterance; utilizing a miscue engine to identify a miscue based on the comparison to at least one of the target context free grammar and the garbage model, wherein identifying the miscue comprises identifying a miscue selected from a group consisting of a stop, a pause, a mispronunciation and a partial pronunciation; reporting progress of the user based at least in part on the stored indication; and wherein reporting progress comprises reporting the miscue. | 10. A method of providing reading tutoring, comprising: receiving a textual indication of a story; building a target context free grammar at runtime based on a portion of the textual indication; obtaining a garbage model that is indicative of a list of words in a general domain; prompting a user for an utterance; providing a received acoustic signal of the user's utterance to a speech recognition engine; comparing an output from the speech recognition engine to the target context free grammar; comparing an output from the speech recognition engine to at least a portion of the garbage model; storing an indication of the comparison to at least one of the target context free grammar and the garbage model in a data store including an indication of the user who provided the utterance; utilizing a miscue engine to identify a miscue based on the comparison to at least one of the target context free grammar and the garbage model, wherein identifying the miscue comprises identifying a miscue selected from a group consisting of a stop, a pause, a mispronunciation and a partial pronunciation; reporting progress of the user based at least in part on the stored indication; and wherein reporting progress comprises reporting the miscue. 13. The method of claim 10 , and further comprising: providing an acoustic model that is trained for use in the speech recognition engine, wherein the data for training the acoustic model includes data from a plurality of children. | 0.502155 |
9,607,340 | 8 | 10 | 8. A computer program product embodied on a computer readable non-transitory medium, the computer readable non-transitory medium having stored thereon a sequence of instructions which, when executed by a processor causes the processor to execute a method for analyzing author data, the method comprising: receiving writings created by a plurality of authors; performing a semantic analysis upon the writings; generating-a plurality of author profiles for the writings using results from the semantic analysis, the plurality of author profiles respectively identifying topics of interest to the plurality of authors; identifying groups of authors from one or more of the topics of interest; identifying a first group of multiple authors that corresponds to a first topical subject and multiple author profiles for the multiple authors, the first group of multiple authors identified from the groups and corresponding to the multiple author profiles identified from the plurality of author profiles; identifying a second topical subject shared among at least some authors of the multiple authors in the first group at least by performing a correlation analysis that analyzes at least some author profiles in the multiple author profiles of the at least some authors; identifying a second group of authors from the plurality of authors that exhibit affinity for the second topical subject at least by identifying author vectors corresponding to the second group of authors with respect to the second topical subject; and correlating the first group of multiple authors with the second group of authors in response to the identification of the second topical subject, wherein the writings are received from the plurality of authors without targeting specific groups of authors; classifying the writings into a plurality of classes based in part or in whole upon topics of interests determined by the semantic analysis, classifying the writing including: creating a set of themes from results of the semantic analysis; analyzing the set of themes created from the results of the semantic analysis; determining subjects of the topics of interest based in part or in whole upon the set of themes; determining similarity among the subjects of the topics of interest at least by analyzing the plurality of author profiles; clustering the topics of interests into the plurality of classes based in part or in whole upon the similarity among the subjects; determining respective strength numbers for the plurality of authors, a strength number for a user indicating relative affinity of the user to a category relative to one or more remaining categories; associating the respective strength numbers that correspond to the plurality of authors with a plurality of categories; creating a vector for each author of the plurality of authors, wherein vectors for the plurality of authors indicate respective affinities among the plurality of authors to one or more common topics of interests or one or more subjects; establishing an author profile for the each author by using the vector for the each author; storing the author profile for the author in the plurality of author profiles; reducing noise in the writings at least by performing a semantic filtering process; improving accuracy of the plurality of classes from classifying the writings at least by reducing false positives, false negatives, and inappropriate contents with the semantic filtering process; identifying an actionable data based in part or in whole upon results of the semantic analysis, wherein the writings created by the plurality of authors include contents transcribed from non-social data; determining, at a rule and workflow module stored at least partially in memory, the plurality of computing systems to receive the actionable data based in part or in whole upon a set of rules that identifies how the actionable data is to be handled and directed; performing the semantic analysis upon the writings at least by performing a statistical language modeling; performing the semantic analysis upon the writings at least by performing a latent semantic analysis; preconfiguring a plurality of types of topics of interest; determining a first set of authors that corresponds to the one or more first types of topics of interest at least by analyzing the plurality of author profiles to identify a first set of author profiles corresponding to the first set of authors; determining commonality of one or more second types of topics of interest without pre-defining the one or more second types of topics of interest; identifying commonality among the plurality of writings in response to the one or more second types of topics of interest based in part or in whole upon results of the semantic analysis; identifying a group of authors that corresponds to a first affinity for a first subject; determining a second affinity and a third affinity shared by at least a threshold percentage of authors of the group of authors at least by analyzing a set of author profiles corresponding to the group of authors and by performing one or more first correlation analyses, wherein the second affinity and the third affinity are not known or expected in advance; generating correlation data based in part or in whole upon results of determining the second affinity and the third affinity; generating an action for the group of authors based on the second affinity and the third affinity; receiving the writings created by the plurality of authors without targeting one or more specific groups of authors; generating the plurality of author profiles for the writings based in part or in whole upon respective strength numbers for the plurality of authors; identifying a plurality of themes from the writings based in part or in whole upon results of the semantic analysis and results of classifying the writings; performing a themes analysis; generating the plurality of author profiles for the writing based in part or in whole upon the plurality of themes; determining a first set of actionable data for the plurality of authors based in part or in whole upon results of correlating an at least one group with the authors; identifying a set of rules from a rulebase; dispatching, at a rules and workflow engine, actionable data for the plurality of authors to a plurality of computing systems based in part or in whole upon the set of rules, wherein a rule provides how the actionable data is to be dispatched; determining, at a computer system, contextual and semantic significance in the writings at least by performing classification and filtering on the writings of the plurality of authors; identifying specific themes within the writings based in part or in whole upon topics and subjects revealed from the semantic analysis and the classification; performing categorization on the topics and the subjects of the writings to create a number of categories; associating a set of strength numbers with the number of categories, a strength number indicating relative affinity of each author of the plurality of authors to a particular topic, a particular subject, or a particular theme; and defining a vector for the each author using at least the set of strength numbers and the number of categories, a vector establishing an author profile for a specific author and being used to describe and analyze the specific author with respect to one or more affinities of the specific author. | 8. A computer program product embodied on a computer readable non-transitory medium, the computer readable non-transitory medium having stored thereon a sequence of instructions which, when executed by a processor causes the processor to execute a method for analyzing author data, the method comprising: receiving writings created by a plurality of authors; performing a semantic analysis upon the writings; generating-a plurality of author profiles for the writings using results from the semantic analysis, the plurality of author profiles respectively identifying topics of interest to the plurality of authors; identifying groups of authors from one or more of the topics of interest; identifying a first group of multiple authors that corresponds to a first topical subject and multiple author profiles for the multiple authors, the first group of multiple authors identified from the groups and corresponding to the multiple author profiles identified from the plurality of author profiles; identifying a second topical subject shared among at least some authors of the multiple authors in the first group at least by performing a correlation analysis that analyzes at least some author profiles in the multiple author profiles of the at least some authors; identifying a second group of authors from the plurality of authors that exhibit affinity for the second topical subject at least by identifying author vectors corresponding to the second group of authors with respect to the second topical subject; and correlating the first group of multiple authors with the second group of authors in response to the identification of the second topical subject, wherein the writings are received from the plurality of authors without targeting specific groups of authors; classifying the writings into a plurality of classes based in part or in whole upon topics of interests determined by the semantic analysis, classifying the writing including: creating a set of themes from results of the semantic analysis; analyzing the set of themes created from the results of the semantic analysis; determining subjects of the topics of interest based in part or in whole upon the set of themes; determining similarity among the subjects of the topics of interest at least by analyzing the plurality of author profiles; clustering the topics of interests into the plurality of classes based in part or in whole upon the similarity among the subjects; determining respective strength numbers for the plurality of authors, a strength number for a user indicating relative affinity of the user to a category relative to one or more remaining categories; associating the respective strength numbers that correspond to the plurality of authors with a plurality of categories; creating a vector for each author of the plurality of authors, wherein vectors for the plurality of authors indicate respective affinities among the plurality of authors to one or more common topics of interests or one or more subjects; establishing an author profile for the each author by using the vector for the each author; storing the author profile for the author in the plurality of author profiles; reducing noise in the writings at least by performing a semantic filtering process; improving accuracy of the plurality of classes from classifying the writings at least by reducing false positives, false negatives, and inappropriate contents with the semantic filtering process; identifying an actionable data based in part or in whole upon results of the semantic analysis, wherein the writings created by the plurality of authors include contents transcribed from non-social data; determining, at a rule and workflow module stored at least partially in memory, the plurality of computing systems to receive the actionable data based in part or in whole upon a set of rules that identifies how the actionable data is to be handled and directed; performing the semantic analysis upon the writings at least by performing a statistical language modeling; performing the semantic analysis upon the writings at least by performing a latent semantic analysis; preconfiguring a plurality of types of topics of interest; determining a first set of authors that corresponds to the one or more first types of topics of interest at least by analyzing the plurality of author profiles to identify a first set of author profiles corresponding to the first set of authors; determining commonality of one or more second types of topics of interest without pre-defining the one or more second types of topics of interest; identifying commonality among the plurality of writings in response to the one or more second types of topics of interest based in part or in whole upon results of the semantic analysis; identifying a group of authors that corresponds to a first affinity for a first subject; determining a second affinity and a third affinity shared by at least a threshold percentage of authors of the group of authors at least by analyzing a set of author profiles corresponding to the group of authors and by performing one or more first correlation analyses, wherein the second affinity and the third affinity are not known or expected in advance; generating correlation data based in part or in whole upon results of determining the second affinity and the third affinity; generating an action for the group of authors based on the second affinity and the third affinity; receiving the writings created by the plurality of authors without targeting one or more specific groups of authors; generating the plurality of author profiles for the writings based in part or in whole upon respective strength numbers for the plurality of authors; identifying a plurality of themes from the writings based in part or in whole upon results of the semantic analysis and results of classifying the writings; performing a themes analysis; generating the plurality of author profiles for the writing based in part or in whole upon the plurality of themes; determining a first set of actionable data for the plurality of authors based in part or in whole upon results of correlating an at least one group with the authors; identifying a set of rules from a rulebase; dispatching, at a rules and workflow engine, actionable data for the plurality of authors to a plurality of computing systems based in part or in whole upon the set of rules, wherein a rule provides how the actionable data is to be dispatched; determining, at a computer system, contextual and semantic significance in the writings at least by performing classification and filtering on the writings of the plurality of authors; identifying specific themes within the writings based in part or in whole upon topics and subjects revealed from the semantic analysis and the classification; performing categorization on the topics and the subjects of the writings to create a number of categories; associating a set of strength numbers with the number of categories, a strength number indicating relative affinity of each author of the plurality of authors to a particular topic, a particular subject, or a particular theme; and defining a vector for the each author using at least the set of strength numbers and the number of categories, a vector establishing an author profile for a specific author and being used to describe and analyze the specific author with respect to one or more affinities of the specific author. 10. The computer program product of claim 8 , wherein the vector comprises strength numbers that correspond to an extent or degree of interest by the author for the topics of interest to the plurality of authors. | 0.903461 |
8,972,233 | 1 | 17 | 1. A method for relating measurable or observable characteristics of hydrocarbon source rocks to estimated conditions at the time of formation of the hydrocarbon source rocks, comprising: (a) selecting a first set of variables representing measurable or observable characteristics describing presence, quantity or quality of hydrocarbon source rocks; (b) selecting a second set of variables representing historical quantities that influence source rock formation, comprising at least one variable representing each of the following three types of influencing factors: (i) geologic age factors; (ii) paleogeographic factors; and (iii) paleoenvironmental conditions, said second set of variables being classifiable according to whether they affect rate of production, destruction or dilution of organic matter that forms hydrocarbon source rocks; (c) forming a network with nodes comprising both sets of variables, said network having directional links connecting causally-related nodes; (d) selecting one or more variables from either set to be unknowns and assigning at least one data value to each of the other variables along with associated probabilities of having the respective data values, said values and probabilities being estimated from measurement, observation or inferred indirectly; and (e) solving the network including the data and probability distributions for at least one of the one or more unknown variables using a Bayesian Network algorithm programmed on a computer and conservation of organic matter expressible as:
organic matter enrichment=production−(destruction+dilution) and downloading or saving results of solving the network to computer memory or storage. | 1. A method for relating measurable or observable characteristics of hydrocarbon source rocks to estimated conditions at the time of formation of the hydrocarbon source rocks, comprising: (a) selecting a first set of variables representing measurable or observable characteristics describing presence, quantity or quality of hydrocarbon source rocks; (b) selecting a second set of variables representing historical quantities that influence source rock formation, comprising at least one variable representing each of the following three types of influencing factors: (i) geologic age factors; (ii) paleogeographic factors; and (iii) paleoenvironmental conditions, said second set of variables being classifiable according to whether they affect rate of production, destruction or dilution of organic matter that forms hydrocarbon source rocks; (c) forming a network with nodes comprising both sets of variables, said network having directional links connecting causally-related nodes; (d) selecting one or more variables from either set to be unknowns and assigning at least one data value to each of the other variables along with associated probabilities of having the respective data values, said values and probabilities being estimated from measurement, observation or inferred indirectly; and (e) solving the network including the data and probability distributions for at least one of the one or more unknown variables using a Bayesian Network algorithm programmed on a computer and conservation of organic matter expressible as:
organic matter enrichment=production−(destruction+dilution) and downloading or saving results of solving the network to computer memory or storage. 17. The method of claim 1 , wherein the network including the data and probability distributions includes at least one intermediate or output node that is connected upstream to at least two other intermediate nodes. | 0.751157 |
8,977,584 | 1 | 18 | 1. A digital conversation generating processor-implemented method, comprising: instantiating a conversational artificial-intelligence agent; identifying an individual target for conversation; initiating a conversational dialogue between the individual target and the artificial-intelligence agent; recording a first dialogue segment from the individual target as part of the conversational dialogue, wherein the first dialogue segment is a subportion of the conversational dialogue; responding to the first dialogue segment from the individual target with an at least one subsequent interactive dialogue segment, wherein the at least one subsequent dialogue segment is a subportion of the conversational dialogue; recording an interactive dialogue comprising the first dialogue segment and the at least one subsequent interactive dialogue segment; retrieving the recorded interactive dialogue between the individual target and the artificial-intelligence agent; allocating a value point to each subsequent interactive dialogue segment of the interactive dialogue; creating a digital conversation asset comprising at least the retrieved interactive dialogue associated with the allocated value point to each subsequent interactive dialogue segment of the interactive dialogue; determining a value for the digital conversation asset at least based on the allocated value point to each subsequent interactive dialogue segment of the interactive dialogue; and providing the created digital conversation asset associated with the determined value for exchange. | 1. A digital conversation generating processor-implemented method, comprising: instantiating a conversational artificial-intelligence agent; identifying an individual target for conversation; initiating a conversational dialogue between the individual target and the artificial-intelligence agent; recording a first dialogue segment from the individual target as part of the conversational dialogue, wherein the first dialogue segment is a subportion of the conversational dialogue; responding to the first dialogue segment from the individual target with an at least one subsequent interactive dialogue segment, wherein the at least one subsequent dialogue segment is a subportion of the conversational dialogue; recording an interactive dialogue comprising the first dialogue segment and the at least one subsequent interactive dialogue segment; retrieving the recorded interactive dialogue between the individual target and the artificial-intelligence agent; allocating a value point to each subsequent interactive dialogue segment of the interactive dialogue; creating a digital conversation asset comprising at least the retrieved interactive dialogue associated with the allocated value point to each subsequent interactive dialogue segment of the interactive dialogue; determining a value for the digital conversation asset at least based on the allocated value point to each subsequent interactive dialogue segment of the interactive dialogue; and providing the created digital conversation asset associated with the determined value for exchange. 18. The method of claim 1 , wherein a portion of the created digital conversation asset associated with the determined value is provided to an ad network. | 0.738095 |
4,362,152 | 5 | 6 | 5. The erector of claim 4 wherein the second end of each rod has a bend, said second ends being separated thereby from each other at a predetermined angle, the second ends for contacting and applying pressure thereby to the penis superficial dorsal vein. | 5. The erector of claim 4 wherein the second end of each rod has a bend, said second ends being separated thereby from each other at a predetermined angle, the second ends for contacting and applying pressure thereby to the penis superficial dorsal vein. 6. The erector of claim 5 wherein the securement means comprises elastomeric means coupled to the second end of each rod and adapted for securement around the scrotum at the root of the penis, the elastomeric means being capable of stretching and retracting in response to corresponding changes in erection of the penis, and wherein expansion of the glans of the penis causes the arms of the yoke to rotate relatively further apart causing the second ends of the rods to rotate relatively closer together stretching thereby the elastomeric means causing the second ends of the rods to exert relatively increasing pressure on the dorsal vein and the elastomeric means causing relatively increasing pressure on the corpora cavernosa without casing relatively increasing pressure on the arterial vessels and corpus cavernosum urethra. | 0.5 |
9,900,429 | 16 | 20 | 16. A system for recording media for a contact center comprising: a processor; a memory, wherein the first memory has stored thereon instructions that, when executed by the processor, cause the processor to: receive a request for a telephony call from a first communication device; invoke a rule based on an attribute of the telephony call, wherein the rule identifies a condition for recording the call; determine whether the condition for recording the call is satisfied; in response to determining that the condition for recording the call is satisfied, establish a first call path with a recording system instead of a second call path, wherein the recording system is configured to receive media transmitted by the first communication device via the first call path instead of the second call path, bridge a media path between the first communication and a second communication device, and record the media in a storage device; and in response to determining that the condition for recording the call is not satisfied, establish the second call path with the second communication device without establishing the first call path, wherein the media transmitted by the first communication device is for being received via the second call path instead of the first call path. | 16. A system for recording media for a contact center comprising: a processor; a memory, wherein the first memory has stored thereon instructions that, when executed by the processor, cause the processor to: receive a request for a telephony call from a first communication device; invoke a rule based on an attribute of the telephony call, wherein the rule identifies a condition for recording the call; determine whether the condition for recording the call is satisfied; in response to determining that the condition for recording the call is satisfied, establish a first call path with a recording system instead of a second call path, wherein the recording system is configured to receive media transmitted by the first communication device via the first call path instead of the second call path, bridge a media path between the first communication and a second communication device, and record the media in a storage device; and in response to determining that the condition for recording the call is not satisfied, establish the second call path with the second communication device without establishing the first call path, wherein the media transmitted by the first communication device is for being received via the second call path instead of the first call path. 20. The system of claim 16 , wherein the metadata includes information on a user of the first or second communication device. | 0.914734 |
8,103,677 | 1 | 3 | 1. A computer-implemented method for searching, comprising: identifying one or more matching objects matching one or more terms of a search request in a search index; executing one or more return path methods associated with each of the one or more matching objects; wherein each of the one or more return path methods traverses an object tree and returns a parent object, wherein the parent object is added to a list of search result parent objects, wherein the data associated with the parent object is stored along with modification dates, wherein the search request further comprises an evaluation date; and wherein the parent object is stored with one or more effective dates, wherein each effective date comprises a past, present or future date; and wherein an effective state of the parent object is determined at the evaluation date by comparing the evaluation date to one or more of the effective dates; ranking the list of search result parent objects according to a ranking function; and providing the ranked list of search result parent objects. | 1. A computer-implemented method for searching, comprising: identifying one or more matching objects matching one or more terms of a search request in a search index; executing one or more return path methods associated with each of the one or more matching objects; wherein each of the one or more return path methods traverses an object tree and returns a parent object, wherein the parent object is added to a list of search result parent objects, wherein the data associated with the parent object is stored along with modification dates, wherein the search request further comprises an evaluation date; and wherein the parent object is stored with one or more effective dates, wherein each effective date comprises a past, present or future date; and wherein an effective state of the parent object is determined at the evaluation date by comparing the evaluation date to one or more of the effective dates; ranking the list of search result parent objects according to a ranking function; and providing the ranked list of search result parent objects. 3. A method as in claim 1 , wherein the object tree comprises a network of objects that store data. | 0.740838 |
9,741,058 | 12 | 22 | 12. A computer-executed method for programmatically analyzing a consumer review, the method comprising: programmatically accessing, via a network device, one or more consumer reviews for a commercial entity or a commercial object; executing a consumer review processing engine to programmatically identify an attribute descriptor in the one or more consumer reviews; executing the consumer review processing engine to programmatically generate a sentiment score associated with the one or more consumer reviews, wherein programmatically generating the sentiment score comprises: using a natural language processing engine to programmatically parse the consumer review into a set of sentences; using the natural language processing engine to programmatically parse each sentence in the set of sentences into a set of words; for each word in the set of words in each sentence, programmatically generating a word sentiment score; for each sentence in the set of sentences, programmatically generating a sentence sentiment score, the sentence sentiment score generated based on word sentiment scores associated with words in the sentence, wherein programmatically generating the sentence sentiment scores includes applying a machine learning algorithm to determine a relationship between the sentence sentiment score and the word sentiment scores associated with the words in the sentence; and programmatically generating the sentiment score by combining sentence sentiment scores associated with the set of sentences in the consumer review; and storing, on a non-transitory computer-readable storage device, the attribute descriptor and the sentiment score in association with the commercial entity or the commercial object. | 12. A computer-executed method for programmatically analyzing a consumer review, the method comprising: programmatically accessing, via a network device, one or more consumer reviews for a commercial entity or a commercial object; executing a consumer review processing engine to programmatically identify an attribute descriptor in the one or more consumer reviews; executing the consumer review processing engine to programmatically generate a sentiment score associated with the one or more consumer reviews, wherein programmatically generating the sentiment score comprises: using a natural language processing engine to programmatically parse the consumer review into a set of sentences; using the natural language processing engine to programmatically parse each sentence in the set of sentences into a set of words; for each word in the set of words in each sentence, programmatically generating a word sentiment score; for each sentence in the set of sentences, programmatically generating a sentence sentiment score, the sentence sentiment score generated based on word sentiment scores associated with words in the sentence, wherein programmatically generating the sentence sentiment scores includes applying a machine learning algorithm to determine a relationship between the sentence sentiment score and the word sentiment scores associated with the words in the sentence; and programmatically generating the sentiment score by combining sentence sentiment scores associated with the set of sentences in the consumer review; and storing, on a non-transitory computer-readable storage device, the attribute descriptor and the sentiment score in association with the commercial entity or the commercial object. 22. The computer-executed method of claim 12 , wherein the attribute descriptor indicates a category or sub-category associated with the commercial entity or the commercial object. | 0.891697 |
9,443,028 | 5 | 8 | 5. The method of claim 1 wherein associating some amount of despair with each clicked URL comprises distributing a despair value between two or more URLs. | 5. The method of claim 1 wherein associating some amount of despair with each clicked URL comprises distributing a despair value between two or more URLs. 8. The method of claim 5 wherein distributing the despair value comprises, for each URL, computing an amount of the despair value based on a dwell time corresponding to that URL and associating the amount of despair value with that URL. | 0.5 |
8,549,314 | 11 | 15 | 11. A computer-implemented method comprising: receiving a string of characters input to a computer device by a user, wherein the string of characters include: a user password having a plurality of characters; a plurality of variable characters; a plurality of terminator characters, each one of the terminator characters separated from one another by a portion of the variable characters; and a plurality of safeguard characters; identifying locations of the plurality of terminator characters; and extracting the user password from the string of characters which included the user password, variable character, the plurality of terminator characters, and the plurality of safeguard characters, wherein the safeguard is number that presents the minimum number of variable characters the user enter after each character in the actual user password and followed by variable characters and terminator characters; based on a one-to-one correspondence of each character of the user password with each one of the terminator characters and the locations of each one of the terminator characters. | 11. A computer-implemented method comprising: receiving a string of characters input to a computer device by a user, wherein the string of characters include: a user password having a plurality of characters; a plurality of variable characters; a plurality of terminator characters, each one of the terminator characters separated from one another by a portion of the variable characters; and a plurality of safeguard characters; identifying locations of the plurality of terminator characters; and extracting the user password from the string of characters which included the user password, variable character, the plurality of terminator characters, and the plurality of safeguard characters, wherein the safeguard is number that presents the minimum number of variable characters the user enter after each character in the actual user password and followed by variable characters and terminator characters; based on a one-to-one correspondence of each character of the user password with each one of the terminator characters and the locations of each one of the terminator characters. 15. A computer-implemented method as recited in claim 11 wherein the plurality of safeguard characters are located at the beginning of the string of characters input by the user. | 0.731118 |
8,847,799 | 2 | 3 | 2. The method according to claim 1 , wherein obtaining the plurality of sequence reads comprises sequencing a nucleic acid from the sample to generate the plurality of sequence reads. | 2. The method according to claim 1 , wherein obtaining the plurality of sequence reads comprises sequencing a nucleic acid from the sample to generate the plurality of sequence reads. 3. The method according to claim 2 , wherein sequencing comprises one selected from the group consisting of single molecule sequencing and sequencing by synthesis. | 0.5 |
8,527,529 | 6 | 8 | 6. A computer program product for displaying search results for a search query comprising a plurality of search terms, said computer program product comprising a non-transitory computer readable medium having computer readable program code embodied therewith, said computer readable program code comprising: computer readable program code configured to receive said search query; computer readable program code configured to obtain at least one document satisfying said search query; computer readable program code configured to determine a relative position of at least two of said search terms in said at least one document; and computer readable program code configured to present at least a portion of said at least one document with a visual indication of said relative position of said at least two search terms in said at least one document, wherein said visual indication indicates a count of one or more intervening elements between said at least two search terms, wherein said relative position is indicated using a predefined character to indicate said one or more intervening elements between said at least two search terms and wherein said one or more intervening elements indicated by each predefined character comprises a given one of a character, word, line, paragraph and page. | 6. A computer program product for displaying search results for a search query comprising a plurality of search terms, said computer program product comprising a non-transitory computer readable medium having computer readable program code embodied therewith, said computer readable program code comprising: computer readable program code configured to receive said search query; computer readable program code configured to obtain at least one document satisfying said search query; computer readable program code configured to determine a relative position of at least two of said search terms in said at least one document; and computer readable program code configured to present at least a portion of said at least one document with a visual indication of said relative position of said at least two search terms in said at least one document, wherein said visual indication indicates a count of one or more intervening elements between said at least two search terms, wherein said relative position is indicated using a predefined character to indicate said one or more intervening elements between said at least two search terms and wherein said one or more intervening elements indicated by each predefined character comprises a given one of a character, word, line, paragraph and page. 8. The computer program product of claim 6 , further comprising the step of presenting a relevance ranking that is based on said relative position of said at least two search terms. | 0.528646 |
8,185,372 | 4 | 6 | 4. The example-based translation apparatus according to claim 1 , wherein the output control unit outputs information indicating the presence of the plurality of the acquired target examples, when the chosen second source example is associated with the plurality of the acquired target examples. | 4. The example-based translation apparatus according to claim 1 , wherein the output control unit outputs information indicating the presence of the plurality of the acquired target examples, when the chosen second source example is associated with the plurality of the acquired target examples. 6. The example-based translation apparatus according to claim 4 , wherein the output control unit outputs an additional chosen second source example corresponding to a single target example, and outputs the additional chosen second source example separately from the chosen second source example. | 0.5 |
8,713,078 | 33 | 35 | 33. The computer system of 32 , the method further comprising: the computer system configured for retrieving keywords associated with a second topic and ranks assigned to the keywords from the taxonomy of topics; the computer system configured for identifying a plurality of videos associated with each keyword associated with the second topic; and the computer system configured for calculating a video-keyword rank for each video associated with each keyword based on a relevancy of the video to the keyword. | 33. The computer system of 32 , the method further comprising: the computer system configured for retrieving keywords associated with a second topic and ranks assigned to the keywords from the taxonomy of topics; the computer system configured for identifying a plurality of videos associated with each keyword associated with the second topic; and the computer system configured for calculating a video-keyword rank for each video associated with each keyword based on a relevancy of the video to the keyword. 35. The computer system of claim 33 , further comprising: the computer system configured for calculating a video-topic rank by summing the video-keyword ranks calculated for each video that match at least one of the keywords of the second topic. | 0.5 |
9,286,295 | 9 | 12 | 9. A method of file and document retrieval comprising; scanning a first layer of a multi-layer scannable tag by a camera or scanning device; or receiving an indication that the multi-layer scannable tag has been scanned by a first user; assigning the first layer of the multi-layer scannable tag to the first user; receiving an image, audio, video, or other file from the first user; storing the image, audio, video, or other file in a location in cloud storage; generating one unique URL link wherein that URL link is associated with the multi-layer scannable tag, the URL link also pointing to the location in cloud storage; linking the multi-layer scannable tag with the location in cloud storage using the URL link; tagging the image, audio, video, or other file with said multi-layer scannable tag; wherein such tagging is accomplished by means of the use of a mobile application, computer program or similar electronic device; retrieving video, audio or other files tagged and associated with said first layer of the multi-layer scannable tag; playing the video, audio or other file tagged with said multi-layer scannable tag by embedded player; scanning another layer of a multi-layer scannable tag by a camera or scanning device; or receiving an indication that the multi-layer scannable tag has been scanned by a second user; assigning the another layer of the multi-layer scannable tag to the second user; receiving an image, audio, video, or other file from the second user; storing the image, audio, video, or other file in a location in cloud storage; generating one unique URL link wherein that URL link is associated with the multi-layer scannable tag, the URL link also pointing to the location in cloud storage; and linking the multi-layer scannable tag with the location in cloud storage using the URL link. | 9. A method of file and document retrieval comprising; scanning a first layer of a multi-layer scannable tag by a camera or scanning device; or receiving an indication that the multi-layer scannable tag has been scanned by a first user; assigning the first layer of the multi-layer scannable tag to the first user; receiving an image, audio, video, or other file from the first user; storing the image, audio, video, or other file in a location in cloud storage; generating one unique URL link wherein that URL link is associated with the multi-layer scannable tag, the URL link also pointing to the location in cloud storage; linking the multi-layer scannable tag with the location in cloud storage using the URL link; tagging the image, audio, video, or other file with said multi-layer scannable tag; wherein such tagging is accomplished by means of the use of a mobile application, computer program or similar electronic device; retrieving video, audio or other files tagged and associated with said first layer of the multi-layer scannable tag; playing the video, audio or other file tagged with said multi-layer scannable tag by embedded player; scanning another layer of a multi-layer scannable tag by a camera or scanning device; or receiving an indication that the multi-layer scannable tag has been scanned by a second user; assigning the another layer of the multi-layer scannable tag to the second user; receiving an image, audio, video, or other file from the second user; storing the image, audio, video, or other file in a location in cloud storage; generating one unique URL link wherein that URL link is associated with the multi-layer scannable tag, the URL link also pointing to the location in cloud storage; and linking the multi-layer scannable tag with the location in cloud storage using the URL link. 12. The document retrieval method of claim 9 , wherein the multi-layer scannable tag is shared through various social media websites and available to view through the use of an embedded player. | 0.643911 |
8,117,178 | 15 | 17 | 15. A method of selecting service based on an incomplete query, comprising: a semantic analyzing step, performed by at least one processor, of analyzing an incomplete query from a user semantically; a service selecting step, performed by the at least one processor, of complementing the incomplete query based on a semantically-analyzed query to complete the incomplete query, and selecting a corresponding selected service from among a plurality of services based on a complete query; and a retrieving step, performed by the at least one processor, of retrieving an answer according to the corresponding selected service, wherein the service selecting step comprises a semi-automatic service selecting step of searching lost content in the incomplete query by using a service mapping rule base and complementing the lost content through an interacting with the user, wherein the semi-automatic service selecting step comprises: a lost content searching step of matching the semantically-analyzed query with a service mapping rule in the service mapping rule base, and extracting a service type to which the incomplete query belongs and a lost parameter in the incomplete query; a user interacting step of prompting the user to input prompt information of a parameter value corresponding to the lost parameter and receiving feedback information including the parameter value from the user; a parameter value extracting step of extracting the parameter value from the feedback information of the user; and a query complementing step of adding the service type, the lost parameter and the parameter value into the semantically-analyzed query to form the complete query. | 15. A method of selecting service based on an incomplete query, comprising: a semantic analyzing step, performed by at least one processor, of analyzing an incomplete query from a user semantically; a service selecting step, performed by the at least one processor, of complementing the incomplete query based on a semantically-analyzed query to complete the incomplete query, and selecting a corresponding selected service from among a plurality of services based on a complete query; and a retrieving step, performed by the at least one processor, of retrieving an answer according to the corresponding selected service, wherein the service selecting step comprises a semi-automatic service selecting step of searching lost content in the incomplete query by using a service mapping rule base and complementing the lost content through an interacting with the user, wherein the semi-automatic service selecting step comprises: a lost content searching step of matching the semantically-analyzed query with a service mapping rule in the service mapping rule base, and extracting a service type to which the incomplete query belongs and a lost parameter in the incomplete query; a user interacting step of prompting the user to input prompt information of a parameter value corresponding to the lost parameter and receiving feedback information including the parameter value from the user; a parameter value extracting step of extracting the parameter value from the feedback information of the user; and a query complementing step of adding the service type, the lost parameter and the parameter value into the semantically-analyzed query to form the complete query. 17. The method according to claim 15 , wherein the parameter value extracting step retrieves the parameter value corresponding to the lost parameter by semantically marking the feedback information of the user. | 0.851695 |
9,910,909 | 1 | 5 | 1. A computer implemented method for performing analysis on data generated by user interactions, comprising: providing a processor executing instructions for receiving text information from at least one interaction between a user and an agent; said processor text mining said interaction information to extract personal information relating to said user automatically; said processor using a topic model to extract lines from said text information to reduce a number of dimensions required to represent the text, wherein all information of interest is highly pronounced, and wherein a resulting lower dimensional representation of the text allows significantly faster computations; said processor extracting said lines of text as anchored text lines that are indicative of personal information that is present in the anchored text lines; said processor identifying said anchored text lines by checking for specific keywords which are present when said user is mentioning personal information during said interaction; said processor applying a statistical technique to said anchored text lines to discover information present in the anchored text lines; said processor using a k nearest neighbor algorithm to discover said information present in the anchored text lines; said processor representing said text in a topic space with a score along each axis to indicate an extent to which said text contains personal information about said user; upon receiving a new data point, which optionally comprises an anchored text line from said text, said processor picking the k closest points to said new data point, determining a predominant class among classes in the k closest points, and assigning said predominant class to said new data point; said processor assigning a user corresponding to said text to at least one class based on said identified personal information; and said processor classifying said user based upon said extracted lines of text. | 1. A computer implemented method for performing analysis on data generated by user interactions, comprising: providing a processor executing instructions for receiving text information from at least one interaction between a user and an agent; said processor text mining said interaction information to extract personal information relating to said user automatically; said processor using a topic model to extract lines from said text information to reduce a number of dimensions required to represent the text, wherein all information of interest is highly pronounced, and wherein a resulting lower dimensional representation of the text allows significantly faster computations; said processor extracting said lines of text as anchored text lines that are indicative of personal information that is present in the anchored text lines; said processor identifying said anchored text lines by checking for specific keywords which are present when said user is mentioning personal information during said interaction; said processor applying a statistical technique to said anchored text lines to discover information present in the anchored text lines; said processor using a k nearest neighbor algorithm to discover said information present in the anchored text lines; said processor representing said text in a topic space with a score along each axis to indicate an extent to which said text contains personal information about said user; upon receiving a new data point, which optionally comprises an anchored text line from said text, said processor picking the k closest points to said new data point, determining a predominant class among classes in the k closest points, and assigning said predominant class to said new data point; said processor assigning a user corresponding to said text to at least one class based on said identified personal information; and said processor classifying said user based upon said extracted lines of text. 5. The method of claim 1 , further comprising: said processor gathering data required to identify said personal information from any of said user's past interactions, a user profile, and from current interactions. | 0.710598 |
7,941,771 | 9 | 10 | 9. The method according to claim 8 , further comprising: generating predictions based on the node address, the presence vector, and one or more input stimuli; eliminating predictions; readjusting incorrect predictions; reducing an amount of valid hypotheses; and terminating collisions. | 9. The method according to claim 8 , further comprising: generating predictions based on the node address, the presence vector, and one or more input stimuli; eliminating predictions; readjusting incorrect predictions; reducing an amount of valid hypotheses; and terminating collisions. 10. The method according to claim 9 , wherein said generating predictions is performed independent from internal operation of said ASIC. | 0.543624 |
8,214,432 | 17 | 20 | 17. A computer program product for differential dynamic content delivery, the computer program product comprising: a non-transitory recording medium; means, recorded on the recording medium, for providing a session document for a presentation, wherein the session document includes a session grammar and a session structured document; means, recorded on the recording medium, for identifying a recording period within a presentation session; means, recorded on the recording medium, for recording, during the recording period, a first presentation control instruction; means, recorded on the recording medium, for selecting from the session structured document a first classified structural element in dependence upon the recorded first presentation control instruction and in dependence upon user classifications of a first user participant in the presentation; means, recorded on the recording medium, for presenting the first classified structural element to the first user on a first display device; selecting from the session structured document a second classified structural element in dependence upon a second presentation control instruction and in dependence upon user classifications of a second user participant in the presentation; and presenting the second classified structural element to the second user on a second display device. | 17. A computer program product for differential dynamic content delivery, the computer program product comprising: a non-transitory recording medium; means, recorded on the recording medium, for providing a session document for a presentation, wherein the session document includes a session grammar and a session structured document; means, recorded on the recording medium, for identifying a recording period within a presentation session; means, recorded on the recording medium, for recording, during the recording period, a first presentation control instruction; means, recorded on the recording medium, for selecting from the session structured document a first classified structural element in dependence upon the recorded first presentation control instruction and in dependence upon user classifications of a first user participant in the presentation; means, recorded on the recording medium, for presenting the first classified structural element to the first user on a first display device; selecting from the session structured document a second classified structural element in dependence upon a second presentation control instruction and in dependence upon user classifications of a second user participant in the presentation; and presenting the second classified structural element to the second user on a second display device. 20. The computer program product of claim 17 further comprising: means, recorded on the recording medium, for transcoding the recorded first presentation control instruction in dependence upon a device type of the first display. | 0.669565 |
7,971,157 | 1 | 12 | 1. A method for predicting a gesture made by a user to a first application, comprising: receiving image data captured by a camera and sound data captured by a microphone, wherein the image data is representative of a gesture performed by the user and the sound data is representative of a sound made by the user; applying a filter to the image data to interpret the gesture, wherein the sound data at least one of: augments, distinguishes or clarifies the gesture and wherein the filter comprises a first parameter about the gesture and a second parameter about the gesture, the first parameter corresponding to an earlier part of the gesture than the second parameter; determining, from the applied filter, an output corresponding to the gesture being performed, wherein determining the output includes determining the output corresponds to a high confidence level when the first parameter corresponds to a high confidence level and the second parameter does not correspond to a high confidence level; and sending the first application the output. | 1. A method for predicting a gesture made by a user to a first application, comprising: receiving image data captured by a camera and sound data captured by a microphone, wherein the image data is representative of a gesture performed by the user and the sound data is representative of a sound made by the user; applying a filter to the image data to interpret the gesture, wherein the sound data at least one of: augments, distinguishes or clarifies the gesture and wherein the filter comprises a first parameter about the gesture and a second parameter about the gesture, the first parameter corresponding to an earlier part of the gesture than the second parameter; determining, from the applied filter, an output corresponding to the gesture being performed, wherein determining the output includes determining the output corresponds to a high confidence level when the first parameter corresponds to a high confidence level and the second parameter does not correspond to a high confidence level; and sending the first application the output. 12. The method of claim 1 , further comprising: applying a second filter to the image data to interpret the gesture, the second filter representing a second gesture and comprising base information about the second gesture; determining, from the applied second filter, a second output corresponding to the second gesture being performed and a context, the second output being indicative of a greater confidence level than the output; and sending the first application the second output. | 0.521696 |
8,166,079 | 1 | 9 | 1. Apparatus for assembling content fragments into a container, wherein the container comprises markup identifying one or more content fragments, comprising: a hardware processor; computer memory that includes a first queue, and a second queue; the computer memory holding computer program instructions that when executed by the hardware processor perform the following method: receiving, by a host process, a request for the container, and placing the request in the second queue; removing from the second queue, by a first execution thread, the request, and processing the request to generate a data object; instantiating a software processor; generating, by the software processor, a parse tree representation of the container, the parse tree representation including an edge side include (ESI) code directive associated with at least one content fragment in the container; cloning the parse tree representation in a cache; processing, by the software processor, and from top to bottom of the parse tree representation, each ESI code directive, wherein, if an ESI code directive in the parse tree representation is an ESI include, placing a request associated with the ESI include in the first queue for handling by a second execution thread; as ESI code directives are processed, having the software processor concatenate results into the data object; after the parse tree representation is parsed from top to bottom, placing the data object on the first queue; retrieving, by the second execution thread, the data object, and building a response to the request for the container; and serving the response. | 1. Apparatus for assembling content fragments into a container, wherein the container comprises markup identifying one or more content fragments, comprising: a hardware processor; computer memory that includes a first queue, and a second queue; the computer memory holding computer program instructions that when executed by the hardware processor perform the following method: receiving, by a host process, a request for the container, and placing the request in the second queue; removing from the second queue, by a first execution thread, the request, and processing the request to generate a data object; instantiating a software processor; generating, by the software processor, a parse tree representation of the container, the parse tree representation including an edge side include (ESI) code directive associated with at least one content fragment in the container; cloning the parse tree representation in a cache; processing, by the software processor, and from top to bottom of the parse tree representation, each ESI code directive, wherein, if an ESI code directive in the parse tree representation is an ESI include, placing a request associated with the ESI include in the first queue for handling by a second execution thread; as ESI code directives are processed, having the software processor concatenate results into the data object; after the parse tree representation is parsed from top to bottom, placing the data object on the first queue; retrieving, by the second execution thread, the data object, and building a response to the request for the container; and serving the response. 9. The apparatus as described in claim 1 wherein the ESI code directive evaluates an expression. | 0.856287 |
7,490,167 | 29 | 30 | 29. The system recited in claim 1 , wherein the data service layer comprises a Simple Object Access Protocol(SOAP) interface for allowing exchanges of information over the network. | 29. The system recited in claim 1 , wherein the data service layer comprises a Simple Object Access Protocol(SOAP) interface for allowing exchanges of information over the network. 30. The system recited in claim 29 , wherein the information is exchanged based on the eXtensible Markup Language(XML) standard. | 0.5 |
8,364,750 | 11 | 13 | 11. A computer-readable storage medium comprising instructions that, when executed on a processor of a device, cause the device to invoke services of a service host by: upon receiving a first logic comprising a language integrated query and at least two service invocations specified in a first language that does not support a batching of service invocations: translating respective service invocations in the first language into translated service invocations specified in a second language that supports the batching of service invocations and translating the language integrated query into an expression tree specified in the second language, wherein the expression tree comprises at least one lambda expression generated from the first logic; generating a batch logic specified in the second language and comprising the at least two service invocations of the service; and sending the batch logic to the service host. | 11. A computer-readable storage medium comprising instructions that, when executed on a processor of a device, cause the device to invoke services of a service host by: upon receiving a first logic comprising a language integrated query and at least two service invocations specified in a first language that does not support a batching of service invocations: translating respective service invocations in the first language into translated service invocations specified in a second language that supports the batching of service invocations and translating the language integrated query into an expression tree specified in the second language, wherein the expression tree comprises at least one lambda expression generated from the first logic; generating a batch logic specified in the second language and comprising the at least two service invocations of the service; and sending the batch logic to the service host. 13. The computer-readable storage medium of claim 11 , the receiving comprising: receiving a service invocation result from the service host before returning from the sending. | 0.5 |
8,140,563 | 1 | 2 | 1. A method for processing a user query entered by a user via a web browser, said user query having a user query format and including search terms to search World Wide Web documents, said method comprising the steps of: translating the user query into a generic query with a generic query format different than said user query format; sending to a first web service a request to identify a document language and a query format of said first web service, and in response, receiving from said first web service a reply indicating that said first web service uses a first document language and a first query format, said first query format being different than said user query format and said generic query format; translating the generic query to a corresponding, first query with said first query format in said first document language; and sending said first query to said first web service for searching World Wide Web documents; sending to a second web service a request to identify a document language and a query format of said second web service, and in response, receiving from said second web service a reply indicating that said second web service uses a second document language and a second query format, said second query format being different than said first query format, said user query format and said generic query format, said second document language being different than said first document language; translating the generic query to a corresponding, second query with said second query format in said second document language; sending said second query to said second web service for searching World Wide Web documents; and receiving and displaying responses to said first query and said second query. | 1. A method for processing a user query entered by a user via a web browser, said user query having a user query format and including search terms to search World Wide Web documents, said method comprising the steps of: translating the user query into a generic query with a generic query format different than said user query format; sending to a first web service a request to identify a document language and a query format of said first web service, and in response, receiving from said first web service a reply indicating that said first web service uses a first document language and a first query format, said first query format being different than said user query format and said generic query format; translating the generic query to a corresponding, first query with said first query format in said first document language; and sending said first query to said first web service for searching World Wide Web documents; sending to a second web service a request to identify a document language and a query format of said second web service, and in response, receiving from said second web service a reply indicating that said second web service uses a second document language and a second query format, said second query format being different than said first query format, said user query format and said generic query format, said second document language being different than said first document language; translating the generic query to a corresponding, second query with said second query format in said second document language; sending said second query to said second web service for searching World Wide Web documents; and receiving and displaying responses to said first query and said second query. 2. A method as set forth in claim 1 wherein said first document language is HTML and said second document language is XML. | 0.934409 |
8,539,510 | 9 | 10 | 9. The method as recited in claim 1 , wherein the materializing the resulting view comprises: formatting the resulting view as a plurality of compound rows that each contain contextual data joined with event data; and outputting the view to a rule engine. | 9. The method as recited in claim 1 , wherein the materializing the resulting view comprises: formatting the resulting view as a plurality of compound rows that each contain contextual data joined with event data; and outputting the view to a rule engine. 10. The method as recited in claim 9 , wherein the capturing and the joining are performed before the outputting, and wherein the resulting view is constructed based on a defined time window. | 0.5 |
7,912,900 | 18 | 21 | 18. A method for providing an educational alert, comprising: monitoring education-related information maintained on a database comprising a performance threshold and a time threshold; receiving a score for an assignment completed by one or more students at a first time and receiving a further score for the same assignment completed by the student during a second time; determining a score difference between the score and the further score and determining a time difference between the first score and the second score; applying the performance threshold to the score difference and applying the time threshold to the time difference; determining an occurrence of suspected cheating as an event when the score difference fails to satisfy the performance threshold and the time difference fails to satisfy the time threshold; generating an alert for the event, comprising: forming a customized group of educational support members and selecting the customized group of educational support members as recipients of the alert; determining a delivery mechanism based on preferences of each recipient; providing an expiration threshold for the alert; selecting a template for the event as the alert, wherein the template comprises a predetermined format with at least one of text, fillable fields, and a blank text box; and providing to the recipients, suggested response actions comprising at least one of producing additional information, initiating a communication, and sending additional alerts, wherein the suggested response actions are each displayed in the alert by an interactive response action element comprising at least one of response buttons, text recommendations, images, sound, and hyperlinks that allows the recipients of the alert to perform an action; delivering the alert to the recipients using the selected delivery mechanism; and removing the alert upon satisfaction of the expiration threshold. | 18. A method for providing an educational alert, comprising: monitoring education-related information maintained on a database comprising a performance threshold and a time threshold; receiving a score for an assignment completed by one or more students at a first time and receiving a further score for the same assignment completed by the student during a second time; determining a score difference between the score and the further score and determining a time difference between the first score and the second score; applying the performance threshold to the score difference and applying the time threshold to the time difference; determining an occurrence of suspected cheating as an event when the score difference fails to satisfy the performance threshold and the time difference fails to satisfy the time threshold; generating an alert for the event, comprising: forming a customized group of educational support members and selecting the customized group of educational support members as recipients of the alert; determining a delivery mechanism based on preferences of each recipient; providing an expiration threshold for the alert; selecting a template for the event as the alert, wherein the template comprises a predetermined format with at least one of text, fillable fields, and a blank text box; and providing to the recipients, suggested response actions comprising at least one of producing additional information, initiating a communication, and sending additional alerts, wherein the suggested response actions are each displayed in the alert by an interactive response action element comprising at least one of response buttons, text recommendations, images, sound, and hyperlinks that allows the recipients of the alert to perform an action; delivering the alert to the recipients using the selected delivery mechanism; and removing the alert upon satisfaction of the expiration threshold. 21. A method according to claim 18 , wherein the event triggers additional events. | 0.826271 |
9,669,291 | 1 | 5 | 1. A computer-implemented method comprising: assigning, via at least one processor, to each alphabet letter a respective distribution weight according to a weighting rule of an online game, wherein each respective distribution weight reflects a frequency the corresponding alphabet letter, to which the respective distribution weight is assigned, is available for a game action in the online game of a game network server system; allocating based on respective assigned distribution weights, for availability in one or more game actions by a particular player, instances of each alphabet letter in a plurality of the alphabet letters; initiating display, to the particular player, of the allocated instances of each alphabet letter in a game interface of the online game; receiving a game action representing completion of a formation of a word, the word based on selection of a subset of the allocated instances of each alphabet letter; determining a losing player being the particular player having a point score in the online game lower than any further player within the online game, wherein each further player has a respective social network connection in a social network server system with the particular player; based on determining the losing player being the particular player: determining a number of remaining instances of the alphabet letters, available for distribution, and yet to be allocated to the losing player, in accordance to the respective distribution weights and the plurality of alphabet letters previously allocated to the losing player; determining the number of the remaining instances of the alphabet letters is less than or equal to a predetermined threshold; comparing a set of played words based on one or more words previously formed in one or more game action selected by the losing player in the online game; determining a prospective word formation, in a subset of the remaining instances of the alphabet letters, matches at least one of the words previously formed; adjusting the respective distribution weight of each letter in the subset of the remaining instances of the alphabet letters, the adjusted respective distribution weight being greater than a prior corresponding distribution weight. | 1. A computer-implemented method comprising: assigning, via at least one processor, to each alphabet letter a respective distribution weight according to a weighting rule of an online game, wherein each respective distribution weight reflects a frequency the corresponding alphabet letter, to which the respective distribution weight is assigned, is available for a game action in the online game of a game network server system; allocating based on respective assigned distribution weights, for availability in one or more game actions by a particular player, instances of each alphabet letter in a plurality of the alphabet letters; initiating display, to the particular player, of the allocated instances of each alphabet letter in a game interface of the online game; receiving a game action representing completion of a formation of a word, the word based on selection of a subset of the allocated instances of each alphabet letter; determining a losing player being the particular player having a point score in the online game lower than any further player within the online game, wherein each further player has a respective social network connection in a social network server system with the particular player; based on determining the losing player being the particular player: determining a number of remaining instances of the alphabet letters, available for distribution, and yet to be allocated to the losing player, in accordance to the respective distribution weights and the plurality of alphabet letters previously allocated to the losing player; determining the number of the remaining instances of the alphabet letters is less than or equal to a predetermined threshold; comparing a set of played words based on one or more words previously formed in one or more game action selected by the losing player in the online game; determining a prospective word formation, in a subset of the remaining instances of the alphabet letters, matches at least one of the words previously formed; adjusting the respective distribution weight of each letter in the subset of the remaining instances of the alphabet letters, the adjusted respective distribution weight being greater than a prior corresponding distribution weight. 5. The method of claim 1 , further comprising: analyzing profile factors included in a user profile of the player; determining a skill level of the player based on the profile factors; and adjusting the respective distribution weights of the alphabet letters based on the skill level of the player, wherein a profile factor is a game history and the adjusting the respective distribution weights includes increasing a distribution weight of high-point alphabet letters and decreasing a distribution weight of low-point alphabet letters when the skill level of the player is determined to be higher than a predetermined threshold, and wherein a high-point alphabet letter is relatively more difficult to use in word formations than a low-point alphabet letter. | 0.5 |
10,127,902 | 3 | 4 | 3. The method of claim 2 , wherein the score threshold is a sum of the best score from a previous frame, a best acoustic score of a current frame and a predefined constant. | 3. The method of claim 2 , wherein the score threshold is a sum of the best score from a previous frame, a best acoustic score of a current frame and a predefined constant. 4. The method of claim 3 , further comprising: for each remaining token, calculating the actual acoustic score for the token; discarding the tokens with a modified score exceeding another score threshold, wherein the modified score is a sum of a cumulative score of that token from the previous frame, the weight of the corresponding arc, and the acoustic score of the current frame; and placing any tokens that have not been discarded in an active token buffer for the next frame. | 0.5 |
9,792,086 | 11 | 16 | 11. A system comprising: a processor; and a computer-readable storage medium having instructions stored which, when executed by the processor, cause the processor to perform operations comprising: constructing a media interconnection graph which models how media are interconnected by connecting disparate categories of the media; weighting the media interconnection graph based on a popularity of the media, to yield a weighted graph; normalizing the weighted graph, to yield a normalized weighted graph; generating a speech recognition model based on the normalized weighted graph; receiving audible speech for searching media content; and converting the audible speech to output a graph using the speech recognition model. | 11. A system comprising: a processor; and a computer-readable storage medium having instructions stored which, when executed by the processor, cause the processor to perform operations comprising: constructing a media interconnection graph which models how media are interconnected by connecting disparate categories of the media; weighting the media interconnection graph based on a popularity of the media, to yield a weighted graph; normalizing the weighted graph, to yield a normalized weighted graph; generating a speech recognition model based on the normalized weighted graph; receiving audible speech for searching media content; and converting the audible speech to output a graph using the speech recognition model. 16. The system of claim 11 , the computer-readable storage medium having additional instructions stored which, when executed by the processor, result in the processor performing operations comprising ranking information used to build the media interconnection graph, wherein the ranking is performed using a web-page ranking algorithm. | 0.5 |
9,159,074 | 1 | 6 | 1. A network device, comprising: a transceiver configured to communicate with a client device over a network; and a processor that is operative to perform actions, including: receiving content and a plurality of target object lists from a content author, wherein each target object list identifies a unique subset of content as target objects within the received content and each unique subset differs by at least one target object; determining whether a user at the client device is validated by an online social network as having a relationship status with the content author; associating at least one of the plurality of target object lists with the validated user of the client device based in part on the subject matter of the target objects, wherein the associating of the at least one target object list with the validated user of the client device is based on a social network relationship definable by the content author, and wherein the associating of the at least one target object list with the validated user of the client device is performed by a third party; enabling display of the received content at the client device, wherein the target objects in each associated target object list are identifiable within the received content as being available for associating comments based on the client device association; receiving from the client device a comment about one of the identifiable target objects; in response to detecting an action, the action being detected as associated with the identifiable target object within the received content, selectively enabling display of the received comment; receiving another input from the client device; and providing an expanded view of the comment with at least one other comment, and information about users having entered the comments. | 1. A network device, comprising: a transceiver configured to communicate with a client device over a network; and a processor that is operative to perform actions, including: receiving content and a plurality of target object lists from a content author, wherein each target object list identifies a unique subset of content as target objects within the received content and each unique subset differs by at least one target object; determining whether a user at the client device is validated by an online social network as having a relationship status with the content author; associating at least one of the plurality of target object lists with the validated user of the client device based in part on the subject matter of the target objects, wherein the associating of the at least one target object list with the validated user of the client device is based on a social network relationship definable by the content author, and wherein the associating of the at least one target object list with the validated user of the client device is performed by a third party; enabling display of the received content at the client device, wherein the target objects in each associated target object list are identifiable within the received content as being available for associating comments based on the client device association; receiving from the client device a comment about one of the identifiable target objects; in response to detecting an action, the action being detected as associated with the identifiable target object within the received content, selectively enabling display of the received comment; receiving another input from the client device; and providing an expanded view of the comment with at least one other comment, and information about users having entered the comments. 6. The network device of claim 1 , wherein selectively enabling display of the received comment further comprises selectively enabling display of a plurality of comments associated with the identifiable target object, wherein at least one of the plurality of comments is received from a different client device than another of the plurality of comments. | 0.565271 |
7,587,309 | 22 | 43 | 22. A computer-implemented method for providing text summarization for use in Web-based content, comprising: determining, using a computer system including one or more computing devices, text responsive to an executed query comprising one or more query terms and identifying at least one phrase within the text; summarizing, using the computer system, at least one of the at least one phrase into summarized text, the act of summarizing including marking at least one word in the at least one of the at least one phrase using at least one of (A) a match of the at least one word with at least one word of the executed query, and (B) a format rule, and placing the at least one marked word into the summarized text subject to space restrictions; and outputting at least some of the summarized text to induce rendering on a networked client device. | 22. A computer-implemented method for providing text summarization for use in Web-based content, comprising: determining, using a computer system including one or more computing devices, text responsive to an executed query comprising one or more query terms and identifying at least one phrase within the text; summarizing, using the computer system, at least one of the at least one phrase into summarized text, the act of summarizing including marking at least one word in the at least one of the at least one phrase using at least one of (A) a match of the at least one word with at least one word of the executed query, and (B) a format rule, and placing the at least one marked word into the summarized text subject to space restrictions; and outputting at least some of the summarized text to induce rendering on a networked client device. 43. A computer-imlemented method according to claim 22 , wherein the computer system includes an ad server, the computer-implemented method further comprising: providing, using the computer system, the summarized text to the ad server as an advertising creative; and serving, using the computer system, the advertising creative to induce rendering of the advertising creative on a client device. | 0.5 |
8,249,858 | 1 | 2 | 1. A method for multilingual administration of enterprise data, the method comprising: retrieving, by at least one device, enterprise data; extracting, by the at least one device, text from the enterprise data for rendering from a digital media file, the extracted text being in a source language; selecting, by the at least one device, a predetermined default target language from among a plurality of target languages based on a data type for the enterprise data; identifying, by the at least one device, that the source language is not the predetermined default target language for rendering the enterprise data; translating, by the at least one device, the extracted text in the source language to translated text in the predetermined default target language; converting, by the at least one device, the translated text to synthesized speech in the predetermined default target language; and recording, by the at least one device, the synthesized speech in the predetermined default target language in a digital media file. | 1. A method for multilingual administration of enterprise data, the method comprising: retrieving, by at least one device, enterprise data; extracting, by the at least one device, text from the enterprise data for rendering from a digital media file, the extracted text being in a source language; selecting, by the at least one device, a predetermined default target language from among a plurality of target languages based on a data type for the enterprise data; identifying, by the at least one device, that the source language is not the predetermined default target language for rendering the enterprise data; translating, by the at least one device, the extracted text in the source language to translated text in the predetermined default target language; converting, by the at least one device, the translated text to synthesized speech in the predetermined default target language; and recording, by the at least one device, the synthesized speech in the predetermined default target language in a digital media file. 2. The method of claim 1 further comprising: storing the media file on a digital audio player; and playing the media file on the digital audio player thereby rendering the synthesized speech in the predetermined default target language. | 0.708642 |
8,423,383 | 1 | 8 | 1. A method of providing a consultation of medical professionals utilizing a computer-implemented system connected to the internet, integrated with human resources provided by professionals affiliated with the system, to form a consensus of opinions by a panel of medical professionals selected by the system but not provided with financial incentives which could bias their decision making, the method comprising the steps of: (a) creating a database of potential participating medical professionals, along with information about each the potential participating medical professionals, including the qualifications of the potential participating medical professionals; (b) user seeking a medical consultation accesses the system; (c) user submits information to the system regarding the desired medical consultation; (d) at least one professional affiliated with the system reviews information submitted by the user and structures one or more questions, based upon the user submitted information, for consideration by a panel of potential participating medical professionals selected from the database; (e) medical professionals qualified to provide response(s) to the structured question(s) are selected by the system to form a panel to provide responses to the structured question(s) based upon information in the database; (f) the structured question(s) are provided electronically to the medical professionals in the selected panel; (g) the medical professionals in the selected panel review the structured question(s) and provide responses thereto; (h) responses from the medical professionals in the selected panel are forwarded electronically to the system; and (i) system compiles responses, calculates the degree of consensus of the responses, and displays the calculated degree of consensus on a system website accessible to the user. | 1. A method of providing a consultation of medical professionals utilizing a computer-implemented system connected to the internet, integrated with human resources provided by professionals affiliated with the system, to form a consensus of opinions by a panel of medical professionals selected by the system but not provided with financial incentives which could bias their decision making, the method comprising the steps of: (a) creating a database of potential participating medical professionals, along with information about each the potential participating medical professionals, including the qualifications of the potential participating medical professionals; (b) user seeking a medical consultation accesses the system; (c) user submits information to the system regarding the desired medical consultation; (d) at least one professional affiliated with the system reviews information submitted by the user and structures one or more questions, based upon the user submitted information, for consideration by a panel of potential participating medical professionals selected from the database; (e) medical professionals qualified to provide response(s) to the structured question(s) are selected by the system to form a panel to provide responses to the structured question(s) based upon information in the database; (f) the structured question(s) are provided electronically to the medical professionals in the selected panel; (g) the medical professionals in the selected panel review the structured question(s) and provide responses thereto; (h) responses from the medical professionals in the selected panel are forwarded electronically to the system; and (i) system compiles responses, calculates the degree of consensus of the responses, and displays the calculated degree of consensus on a system website accessible to the user. 8. The method of claim 1 further comprising the step of at least one professional affiliated with the system administrator determines when case is ready for submission to selected panel of participating medical professionals. | 0.745475 |
6,049,806 | 1 | 16 | 1. A method for managing data on a computer system, said method comprising the steps of: (a) a first party creating a topic record representative of a topic, wherein the topic record includes a plurality of fields for storing instruction data representative of data from a presentation and retained search data representative of data obtained from a storage means accessible to the computer system, wherein each of the plurality of fields includes a plurality of time slots representative of a plurality of time periods; (b) prompting the first party to input instruction data for a plurality of consecutive time slots; (c) for the plurality of consecutive time slots, receiving from the first party the instruction data; (d) storing on the storage means the topic record and instruction data in its respective field and time slot; (e) receiving from the first party a request to search for additional data for a particular time slot; (f) prompting the first party to input a search criteria related to the additional data to be searched; (g) receiving from the first party criteria data representative of the search criteria; (h) searching one or more storage means of the computer system for search data associated with the criteria data; (i) displaying the search data to the first party; (j) prompting the first party to select the search data to be retained; (k) receiving from the first party retained search data representative of the search data to be retained; (l) storing on the storage means the retained search data in its respective time slot of the topic record; (m) making the topic record available to one or more predetermined second parties; and (n) providing the opportunity for the predetermined second parties to perform steps (e)-(l), above. | 1. A method for managing data on a computer system, said method comprising the steps of: (a) a first party creating a topic record representative of a topic, wherein the topic record includes a plurality of fields for storing instruction data representative of data from a presentation and retained search data representative of data obtained from a storage means accessible to the computer system, wherein each of the plurality of fields includes a plurality of time slots representative of a plurality of time periods; (b) prompting the first party to input instruction data for a plurality of consecutive time slots; (c) for the plurality of consecutive time slots, receiving from the first party the instruction data; (d) storing on the storage means the topic record and instruction data in its respective field and time slot; (e) receiving from the first party a request to search for additional data for a particular time slot; (f) prompting the first party to input a search criteria related to the additional data to be searched; (g) receiving from the first party criteria data representative of the search criteria; (h) searching one or more storage means of the computer system for search data associated with the criteria data; (i) displaying the search data to the first party; (j) prompting the first party to select the search data to be retained; (k) receiving from the first party retained search data representative of the search data to be retained; (l) storing on the storage means the retained search data in its respective time slot of the topic record; (m) making the topic record available to one or more predetermined second parties; and (n) providing the opportunity for the predetermined second parties to perform steps (e)-(l), above. 16. The method of claim 1, wherein said storing steps store the data on a storage means selected from the group consisting of: a CD-Rom, a hard disk, a tape and a floppy disk. | 0.780151 |
6,069,978 | 6 | 7 | 6. A method for producing a bitmap document representation from a bitmap image of a portion of a document, the method executing on a digital system, the digital system including a processor, memory, user input device and output device, the bitmap image of the portion of the document including a plurality of instances of a first character and a plurality of instances of a second character, the method comprising the following steps performed by the processor: detecting instances of the first character and instances of the second character in the bitmap image and storing the detected instances in the memory; using the detected instances of the first character to derive a first prototype character, wherein a bitmap of the first prototype character is a function of the bitmaps of the instances of the first character; using the detected instances of the second character to derive a second prototype character, wherein a bitmap of the second prototype character is a function of the bitmaps of the instances of the second text character; generating the bitmap document representation from the bitmap image by performing, for each character in the bitmap image, the following steps: (1) when the character is an instance of the first character, replacing a bitmap of the character in the image with a bitmap of the first prototype character; and (2) when the character is an instance of the second character, replacing a bitmap of the character in the image with a bitmap of the second prototype character; and outputting the bitmap image containing instances of characters replaced with bitmaps of prototype characters as the bitmap document representation. | 6. A method for producing a bitmap document representation from a bitmap image of a portion of a document, the method executing on a digital system, the digital system including a processor, memory, user input device and output device, the bitmap image of the portion of the document including a plurality of instances of a first character and a plurality of instances of a second character, the method comprising the following steps performed by the processor: detecting instances of the first character and instances of the second character in the bitmap image and storing the detected instances in the memory; using the detected instances of the first character to derive a first prototype character, wherein a bitmap of the first prototype character is a function of the bitmaps of the instances of the first character; using the detected instances of the second character to derive a second prototype character, wherein a bitmap of the second prototype character is a function of the bitmaps of the instances of the second text character; generating the bitmap document representation from the bitmap image by performing, for each character in the bitmap image, the following steps: (1) when the character is an instance of the first character, replacing a bitmap of the character in the image with a bitmap of the first prototype character; and (2) when the character is an instance of the second character, replacing a bitmap of the character in the image with a bitmap of the second prototype character; and outputting the bitmap image containing instances of characters replaced with bitmaps of prototype characters as the bitmap document representation. 7. The method of claim 6, wherein the digital system comprises a fax machine and the portion of a document is derived from a fax transmission to the digital system. | 0.810624 |
8,032,448 | 21 | 26 | 21. A method for implementation by one or more data processors comprising: receiving, by at least one data processor, data characterizing a transaction of transactions between a consumer and merchant; linking, by at least one data processor, the merchant with one of a plurality of pre-defined merchant clusters, the merchant clusters defined by a frequency at which merchants historically shared customers, the merchant clusters being generated by: selecting a plurality of high categorical information elements from the transactions, linking each high categorical information element with a context vector in a vector space such that high categorical information elements that co-occur in the transactions have context vectors that are similarly oriented in the vector space, the co-occurrence representing that context vectors corresponding to the co-occurring high categorical information elements are less than a predetermined distance apart in the vector space for more than a predetermined number of transactions, and clustering the context vectors of the high categorical information elements into a number of merchant clusters that is less than number of high categorical information elements, each merchant cluster being a low categorical information cluster; determining, by at least one data processor, an affinity of the customer to an associated merchant cluster; generating, by at least one data processor, a risk score using at least one predictive model and at least the determined affinity; and initiating, by at least one data processor, provision of data characterizing the generated score. | 21. A method for implementation by one or more data processors comprising: receiving, by at least one data processor, data characterizing a transaction of transactions between a consumer and merchant; linking, by at least one data processor, the merchant with one of a plurality of pre-defined merchant clusters, the merchant clusters defined by a frequency at which merchants historically shared customers, the merchant clusters being generated by: selecting a plurality of high categorical information elements from the transactions, linking each high categorical information element with a context vector in a vector space such that high categorical information elements that co-occur in the transactions have context vectors that are similarly oriented in the vector space, the co-occurrence representing that context vectors corresponding to the co-occurring high categorical information elements are less than a predetermined distance apart in the vector space for more than a predetermined number of transactions, and clustering the context vectors of the high categorical information elements into a number of merchant clusters that is less than number of high categorical information elements, each merchant cluster being a low categorical information cluster; determining, by at least one data processor, an affinity of the customer to an associated merchant cluster; generating, by at least one data processor, a risk score using at least one predictive model and at least the determined affinity; and initiating, by at least one data processor, provision of data characterizing the generated score. 26. A method as in claim 21 , wherein the consumer is associated with a consumer cluster, and wherein the determined affinity is based on an affinity statistic derived from the consumer cluster as a whole relative to the associated merchant cluster. | 0.550542 |
7,877,710 | 16 | 17 | 16. The article non-transitory machine accessible storage medium of claim 13 , further comprising instructions which when executed causes the machine to perform: identifying a second semantic structure; assigning a signal activity to an output of the second semantic structure; and performing vectorless estimation on non-semantic structures. | 16. The article non-transitory machine accessible storage medium of claim 13 , further comprising instructions which when executed causes the machine to perform: identifying a second semantic structure; assigning a signal activity to an output of the second semantic structure; and performing vectorless estimation on non-semantic structures. 17. The article non-transitory machine accessible storage medium of claim 16 , wherein assigning the signal activity to the output of the semantic structure comprises assigning a low toggle rate to a reset signal when the semantic structure is an asynchronous reset pin. | 0.537671 |
8,402,427 | 2 | 4 | 2. The method of claim 1 , wherein the source code comprises graphical user interface (GUI) code, application framework code, the event handler code, and application business logic code. | 2. The method of claim 1 , wherein the source code comprises graphical user interface (GUI) code, application framework code, the event handler code, and application business logic code. 4. The method of claim 2 , further comprising providing a framework for finalizing the source code using an event handler skeleton, business logic code, and GUI code. | 0.5 |
9,560,228 | 2 | 3 | 2. The document reading apparatus according to claim 1 , further comprising a receiving unit configured to receive, from the user through the screen displayed by the displaying unit, the instruction not to stop conveyance of the document by the conveying unit, even in the case where the detecting unit detects multi-feed of the document, wherein, in a case where the receiving unit has received the instruction, the stopping unit does not stop the conveyance of the document by the conveying unit, even in the case where the detecting unit detects multi-feed of the document, and wherein, in a case where the receiving unit has not received the instruction, the stopping unit stops the conveyance of the document by the conveying unit in the case where the detecting unit detects multi-feed of the document. | 2. The document reading apparatus according to claim 1 , further comprising a receiving unit configured to receive, from the user through the screen displayed by the displaying unit, the instruction not to stop conveyance of the document by the conveying unit, even in the case where the detecting unit detects multi-feed of the document, wherein, in a case where the receiving unit has received the instruction, the stopping unit does not stop the conveyance of the document by the conveying unit, even in the case where the detecting unit detects multi-feed of the document, and wherein, in a case where the receiving unit has not received the instruction, the stopping unit stops the conveyance of the document by the conveying unit in the case where the detecting unit detects multi-feed of the document. 3. The document reading apparatus according to claim 2 , wherein, in a case where the receiving unit has not received the instruction but has received a particular instruction different from the instruction, the stopping unit does not stop conveyance of a first document by the conveying unit, even in a case where the detecting unit detects multi-feed of the first document, and wherein, in a case where a second document is conveyed by the conveying unit after conveying the first document, the stopping unit stops the conveyance of the second document by the conveying unit in the case where the detecting unit detects multi-feed of the second document. | 0.72437 |
5,404,435 | 44 | 45 | 44. In a data processing system, a method for archiving graphics objects in a document, comprising the steps of: loading an existing index into a data processing system; inputting a graphics object file into said system; inputting a document architecture envelope including a text object and a pointer to said graphics object file into said system; extracting graphics data including embedded text from said graphics object; automatically generating a first key word for said graphics object from said embedded text; generating a link for said first key word to said text object; adding said first key word and said link to said index; storing said document architecture envelope and said graphics object file in said system; storing said index including said first key word in said system; entering a search term into said data processing system; comparing said search term with candidate key words in said index; and retrieving said graphics object if said first key word is found in said comparing step. | 44. In a data processing system, a method for archiving graphics objects in a document, comprising the steps of: loading an existing index into a data processing system; inputting a graphics object file into said system; inputting a document architecture envelope including a text object and a pointer to said graphics object file into said system; extracting graphics data including embedded text from said graphics object; automatically generating a first key word for said graphics object from said embedded text; generating a link for said first key word to said text object; adding said first key word and said link to said index; storing said document architecture envelope and said graphics object file in said system; storing said index including said first key word in said system; entering a search term into said data processing system; comparing said search term with candidate key words in said index; and retrieving said graphics object if said first key word is found in said comparing step. 45. The method of claim 44, which further comprises: generating a second key word for said graphics object from a caption word string in said text object; generating a second link for said second key word to said text object; adding said second key word to said index; storing said index including said first and second key words in said system. | 0.507143 |
9,230,541 | 2 | 5 | 2. The method of claim 1 , wherein a plurality of candidate keywords, including the candidate keyword, are determined for the current frame of the audio frame sequence, and each candidate keyword is associated with at least one word option, and wherein a subset of the plurality of candidate keyword are determined to be included in the audio frame sequence together with their respective at least one word options based on the keyword determination criterion. | 2. The method of claim 1 , wherein a plurality of candidate keywords, including the candidate keyword, are determined for the current frame of the audio frame sequence, and each candidate keyword is associated with at least one word option, and wherein a subset of the plurality of candidate keyword are determined to be included in the audio frame sequence together with their respective at least one word options based on the keyword determination criterion. 5. The method of claim 2 , wherein after the subset of the candidate keywords are determined to be included in the audio frame sequence together with their respective at least one word options, the corresponding confidence score is updated and is determined to exceed a keyword threshold value in accordance with the keyword determination criterion. | 0.528378 |
7,996,384 | 1 | 3 | 1. A computer-implemented method comprising: receiving a rule set container storing a plurality of abstract rules, wherein each abstract rule includes (i) a conditional statement and (ii) a consequential statement defining a result returned by an abstract rule for a data record supplied to the abstract rule satisfying the conditional statement; identifying a first abstract rule among the plurality of abstract rules, wherein the consequential statement of the first abstract rule specifies to reject data records that satisfy the conditional statement of the first abstract rule from being processed by other abstract rules among the plurality of abstract rules; identifying a second abstract rule among the plurality of abstract rules, wherein the consequential statement of the second abstract rule specifies an inference message to return for data records that satisfy the conditional statement of the second abstract rule; transforming the first abstract rule and the second abstract rule into a single executable rule, wherein the single executable rule includes the consequential statement of the second abstract rule and a new conditional statement, the new conditional statement comprising the conditional statement of the second abstract rule and an exclusionary conditional statement that excludes data records satisfying the conditional statement of the first abstract rule; and storing the single executable rule for execution against a database query result. | 1. A computer-implemented method comprising: receiving a rule set container storing a plurality of abstract rules, wherein each abstract rule includes (i) a conditional statement and (ii) a consequential statement defining a result returned by an abstract rule for a data record supplied to the abstract rule satisfying the conditional statement; identifying a first abstract rule among the plurality of abstract rules, wherein the consequential statement of the first abstract rule specifies to reject data records that satisfy the conditional statement of the first abstract rule from being processed by other abstract rules among the plurality of abstract rules; identifying a second abstract rule among the plurality of abstract rules, wherein the consequential statement of the second abstract rule specifies an inference message to return for data records that satisfy the conditional statement of the second abstract rule; transforming the first abstract rule and the second abstract rule into a single executable rule, wherein the single executable rule includes the consequential statement of the second abstract rule and a new conditional statement, the new conditional statement comprising the conditional statement of the second abstract rule and an exclusionary conditional statement that excludes data records satisfying the conditional statement of the first abstract rule; and storing the single executable rule for execution against a database query result. 3. The computer-implemented method of claim 1 , wherein the conditional statement of the first abstract rule and the conditional statement of the second abstract rule are composed from a plurality of logical fields defined in a data abstraction model modeling an underlying physical database. | 0.634085 |
7,921,374 | 12 | 20 | 12. A handheld electronic device comprising: a keyboard having a plurality of keys through which at least one sequence of characters can be input and a termination input through which the at least one sequence of characters can be terminated; a display on which the at least one sequence of characters input is displayed; and a processor comprising means examining the at least one sequence of characters for at least one word at the beginning of the sequence of characters indicative of an interrogatory, and means for adding interrogative punctuation to the sequence of characters on the display when the termination input is actuated and the at least one word at the beginning of the at least one sequence of characters is indicative of an interrogatory. | 12. A handheld electronic device comprising: a keyboard having a plurality of keys through which at least one sequence of characters can be input and a termination input through which the at least one sequence of characters can be terminated; a display on which the at least one sequence of characters input is displayed; and a processor comprising means examining the at least one sequence of characters for at least one word at the beginning of the sequence of characters indicative of an interrogatory, and means for adding interrogative punctuation to the sequence of characters on the display when the termination input is actuated and the at least one word at the beginning of the at least one sequence of characters is indicative of an interrogatory. 20. The device of claim 12 wherein the means examining the at least one sequence of characters further comprises means examining the at least one sequence of characters for at least a first word after a comma or a semicolon indicative of an interrogatory, and the means for adding interrogative punctuation further comprises means adding interrogative punctuation to the sequence of characters when the termination input is actuated and the at least first word after the comma or semicolon is indicative of an interrogatory. | 0.5 |
9,836,458 | 17 | 18 | 17. The system as recited in claim 15 , wherein the program instructions of the computer program further comprise: capturing an action along with generated dynamic content and associated metadata in response to said presenter performing said action on said screen of said host environment. | 17. The system as recited in claim 15 , wherein the program instructions of the computer program further comprise: capturing an action along with generated dynamic content and associated metadata in response to said presenter performing said action on said screen of said host environment. 18. The system as recited in claim 17 , wherein the program instructions of the computer program further comprise: translating said dynamic content into said preferred native language of said attendee using said associated meta; and relaying said action along with said translated dynamic content to said attendee from said virtual environment. | 0.531335 |
8,934,652 | 32 | 35 | 32. The method of claim 1 , wherein the visually presenting the speaker-related information includes: transmitting the speaker-related information from a first device to a second device having a display. | 32. The method of claim 1 , wherein the visually presenting the speaker-related information includes: transmitting the speaker-related information from a first device to a second device having a display. 35. The method of claim 32 , wherein the transmitting the speaker-related information from a first device to a second device includes: transmitting the speaker-related information from a server system to the second device. | 0.546939 |
9,141,704 | 11 | 18 | 11. A method, comprising: providing access to a database of mapping information that links search-related information to a plurality of users of one or more social networks; continually monitoring a plurality of different search processes of the plurality of users for actions indicating shared interest in a first topic and shared interest in a second topic, wherein the first topic and the second topic are different; continually updating, by one or more processors, the mapping information based at least on the actions indicating the shared interest in the first topic and the shared interest in the second topic; creating a first social subnetwork by identifying, based at least in part on the mapping information, a first group of users of the plurality of users that have a common interest in the first topic; creating a second social subnetwork by identifying, based at least in part on the mapping information, a second group of users of the plurality of users that have a common interest in the second topic; monitoring interactions within the first social subnetwork and within the second social subnetwork to determine that a subgroup of users of the first group of users and of the second group of users share a common interest in a third topic; determining that a number of users in the sub-group of users meets or exceeds a threshold level of interest; and creating a third social subnetwork for the sub-group of users based at least in part on the determination that the number of users in the sub-group of users have met or exceeded the threshold level of interest, wherein the third social subnetwork facilitates interactions associated with the third topic for the sub-group of users. | 11. A method, comprising: providing access to a database of mapping information that links search-related information to a plurality of users of one or more social networks; continually monitoring a plurality of different search processes of the plurality of users for actions indicating shared interest in a first topic and shared interest in a second topic, wherein the first topic and the second topic are different; continually updating, by one or more processors, the mapping information based at least on the actions indicating the shared interest in the first topic and the shared interest in the second topic; creating a first social subnetwork by identifying, based at least in part on the mapping information, a first group of users of the plurality of users that have a common interest in the first topic; creating a second social subnetwork by identifying, based at least in part on the mapping information, a second group of users of the plurality of users that have a common interest in the second topic; monitoring interactions within the first social subnetwork and within the second social subnetwork to determine that a subgroup of users of the first group of users and of the second group of users share a common interest in a third topic; determining that a number of users in the sub-group of users meets or exceeds a threshold level of interest; and creating a third social subnetwork for the sub-group of users based at least in part on the determination that the number of users in the sub-group of users have met or exceeded the threshold level of interest, wherein the third social subnetwork facilitates interactions associated with the third topic for the sub-group of users. 18. The method of claim 11 , further comprising implementing at least one of the first social subnetwork, the second social subnetwork or the third social subnetwork in a secure communications environment. | 0.698529 |
9,910,647 | 18 | 19 | 18. The apparatus of claim 17 , the steps further comprising: creating lookups for the one or more program variables; and calculating field size offsets for the one or more program variables. | 18. The apparatus of claim 17 , the steps further comprising: creating lookups for the one or more program variables; and calculating field size offsets for the one or more program variables. 19. The apparatus of claim 18 , the steps further comprising: determining a redefinition of the one or more program variables; calculating a field size offset for the redefinition; and matching the field size offset for the redefinition with the one or more program variables. | 0.5 |
9,626,455 | 6 | 7 | 6. The method of claim 1 , further comprising determining one or more results characteristics indicative of a characteristic of the result set of documents, wherein the estimated relevance score is calculated based on the one or more results characteristics. | 6. The method of claim 1 , further comprising determining one or more results characteristics indicative of a characteristic of the result set of documents, wherein the estimated relevance score is calculated based on the one or more results characteristics. 7. The method of claim 6 , wherein the one or more results characteristics includes: a terms relevance indicative of an extent to which the query terms match one or more terms in at least one document of the result set of documents, a terms relevance precipitation indicative of a difference in relevance between a first document of the result set of documents and a second document of the result set of documents, a best paragraphs terms prevalence indicative of a number of the query terms and synonyms of the query terms included in at least one paragraph of at least one document of the result set of documents, a topical diversity indicative of a variance in topics within the result set of documents, a terms proximity indicative of a proximity of the query terms within a portion of at least one document of the result set of documents, a query to core terms ratio indicative of a degree of overlap between the query terms and core terms in at least one document of the result set of documents, a document recency indicator indicative of a date of at least one document of the result set of documents, or a number of documents in the result set of documents. | 0.5 |
8,312,383 | 13 | 14 | 13. The computer program product as set forth in claim 12 wherein said first widget is selected by detecting a presence of a display screen pointer indicium within a predetermined screen area containing said first widget. | 13. The computer program product as set forth in claim 12 wherein said first widget is selected by detecting a presence of a display screen pointer indicium within a predetermined screen area containing said first widget. 14. The computer program product as set forth in claim 13 wherein method further includes: enabling a user to use a mouse device to move said pointer indicium on said display screen. | 0.521053 |
7,917,584 | 1 | 12 | 1. A method of actively sharing an application configured to be executed on both an originating and destination computing device, the method comprising: binding the application executing on the originating computing device with one or more documents maintained in a data model, the one or more documents representing a state of the executing application; initiating a collaboration session between the originating and destination computing devices, in which the state of the application executing on the originating computing device is exported to the destination computing device, comprising: serializing the state of the application on the originating computing device; propagating a serialized representation of the application state generated on the originating computing device to a server computing device that is configured to manage data exchange between the originating and destination computing devices; and providing the destination computing device with rights to access resources associated with the application and the serialized representation of the application state generated by the originating computing device; in response to the occurrence of a state change to the application executing on the originating computing device: updating the one or more documents bound to the application executing on the originating computing to represent the state change; generating a transaction on the originating computing that provides a description of the state change; and transmitting the transaction that provides the description of the state change to the server computing device. | 1. A method of actively sharing an application configured to be executed on both an originating and destination computing device, the method comprising: binding the application executing on the originating computing device with one or more documents maintained in a data model, the one or more documents representing a state of the executing application; initiating a collaboration session between the originating and destination computing devices, in which the state of the application executing on the originating computing device is exported to the destination computing device, comprising: serializing the state of the application on the originating computing device; propagating a serialized representation of the application state generated on the originating computing device to a server computing device that is configured to manage data exchange between the originating and destination computing devices; and providing the destination computing device with rights to access resources associated with the application and the serialized representation of the application state generated by the originating computing device; in response to the occurrence of a state change to the application executing on the originating computing device: updating the one or more documents bound to the application executing on the originating computing to represent the state change; generating a transaction on the originating computing that provides a description of the state change; and transmitting the transaction that provides the description of the state change to the server computing device. 12. The method as recited in claim 1 , further comprising building the application on the destination computing device includes using an XML virtual machine that accepts application code written in an XML programming language as input and causes the application code to be executed. | 0.789866 |
8,332,359 | 1 | 2 | 1. A computer-implemented method of generating a document revision history for versions of a document managed by a first electronic document management system (EDMS), the method comprising, by a second EDMS: importing, from the first EDMS into a first location of the second EDMS, metadata describing a first document revision history for the versions of the document managed by the first EDMS, wherein the first document revision history comprises metadata attributes in a first format associated with the first EDMS and describes an actual revision history of the document; generating, from the metadata describing the first document revision history, a second document revision history comprising metadata attributes in a second format associated with the second EDMS, wherein the second document revision history provides a mirrored revision history mirroring the actual revision history, and wherein one or more metadata attributes in the second format are distinct from one or more corresponding metadata attributes in the first format; importing the second document revision history from the first location into a repository managed by the second EDMS; and importing the versions of the document from the first location into the repository managed by the second EDMS. | 1. A computer-implemented method of generating a document revision history for versions of a document managed by a first electronic document management system (EDMS), the method comprising, by a second EDMS: importing, from the first EDMS into a first location of the second EDMS, metadata describing a first document revision history for the versions of the document managed by the first EDMS, wherein the first document revision history comprises metadata attributes in a first format associated with the first EDMS and describes an actual revision history of the document; generating, from the metadata describing the first document revision history, a second document revision history comprising metadata attributes in a second format associated with the second EDMS, wherein the second document revision history provides a mirrored revision history mirroring the actual revision history, and wherein one or more metadata attributes in the second format are distinct from one or more corresponding metadata attributes in the first format; importing the second document revision history from the first location into a repository managed by the second EDMS; and importing the versions of the document from the first location into the repository managed by the second EDMS. 2. The method of claim 1 , wherein importing the versions of the document comprises storing a copy of each version of the document into the repository managed by the second EDMS. | 0.860938 |
8,346,879 | 1 | 8 | 1. An electronic out-of-office message analysis method comprising: receiving an electronic out-of-office message generated by a user in a natural language, the electronic out-of-office message including a time window of absence and an alternate named contact; with a computer processor, generating a normalized representation of the time window by identifying and normalizing a temporal expression from text content of the user's out-of-office message and identifying the alternate named contact by recognizing named entities from the text content of the user's out-of-office message and cross-referencing the recognized named entities with a named entity directory for identifying an alternate named contact corresponding to one of the recognized named entities; generating a structured representation of the user's out-of-office message, the structured representation including a reference to the user, a reference to the identified alternate named contact, and the normalized representation of the time window; using a database that stores structured representations of out-of-office messages of other users, determining whether the user's out-of-office message conflicts with an out-of-office message of the identified alternate named contact by comparing the normalized representation of the time window included in the structured representation of the user's out-of-office message with a normalized representation of a time window included in a structured representation of the identified alternate named contact's out-of-office message; and if a conflict is detected, notifying the user of the conflict. | 1. An electronic out-of-office message analysis method comprising: receiving an electronic out-of-office message generated by a user in a natural language, the electronic out-of-office message including a time window of absence and an alternate named contact; with a computer processor, generating a normalized representation of the time window by identifying and normalizing a temporal expression from text content of the user's out-of-office message and identifying the alternate named contact by recognizing named entities from the text content of the user's out-of-office message and cross-referencing the recognized named entities with a named entity directory for identifying an alternate named contact corresponding to one of the recognized named entities; generating a structured representation of the user's out-of-office message, the structured representation including a reference to the user, a reference to the identified alternate named contact, and the normalized representation of the time window; using a database that stores structured representations of out-of-office messages of other users, determining whether the user's out-of-office message conflicts with an out-of-office message of the identified alternate named contact by comparing the normalized representation of the time window included in the structured representation of the user's out-of-office message with a normalized representation of a time window included in a structured representation of the identified alternate named contact's out-of-office message; and if a conflict is detected, notifying the user of the conflict. 8. The method according to claim 1 , further including: updating scheduled events on a user calendar which coincide with the normalized representation of the time window included in the structured representation of the user's out-of-office message. | 0.663043 |
8,090,736 | 21 | 22 | 21. A system comprising: one or more computer devices to: select a first document; represent a first relationship between the first document and a second document as a first link between the first document and the second document, where the first relationship includes at least one of: the first document and the second document sharing a same hierarchical user-defined label, the first document and the second document being associated with a same sub-directory, or the first document and the second document being associated with a same bookmark folder; represent a second relationship between the first document and a third document as a second link between the first document and the third document, where the second relationship includes at least one of: a hierarchical user-defined label associated with the first document and a hierarchical user-defined label associated with the third document being sibling labels, a sub-directory associated with the first document and a sub-directory associated with the third document being sibling sub-directories, or a bookmark folder associated with the first document and a bookmark folder associated with the third document being sibling bookmark folders; and assign a rank score to the first document based on the first link and based on the second link, where the first link contributes more to the rank score than the second link. | 21. A system comprising: one or more computer devices to: select a first document; represent a first relationship between the first document and a second document as a first link between the first document and the second document, where the first relationship includes at least one of: the first document and the second document sharing a same hierarchical user-defined label, the first document and the second document being associated with a same sub-directory, or the first document and the second document being associated with a same bookmark folder; represent a second relationship between the first document and a third document as a second link between the first document and the third document, where the second relationship includes at least one of: a hierarchical user-defined label associated with the first document and a hierarchical user-defined label associated with the third document being sibling labels, a sub-directory associated with the first document and a sub-directory associated with the third document being sibling sub-directories, or a bookmark folder associated with the first document and a bookmark folder associated with the third document being sibling bookmark folders; and assign a rank score to the first document based on the first link and based on the second link, where the first link contributes more to the rank score than the second link. 22. The system of claim 21 , where the hierarchical user-defined label is assigned to the first document by a number of unique users. | 0.883128 |
9,703,847 | 5 | 8 | 5. The computer-implemented method of claim 1 , further comprising: filtering the candidate individuals according to one or more criteria, wherein the criteria comprise soft criteria, which indicate a nonconforming candidate individual is to remain as a candidate individual, and/or hard criteria, which indicate a nonconforming candidate individual is to be removed as a candidate individual. | 5. The computer-implemented method of claim 1 , further comprising: filtering the candidate individuals according to one or more criteria, wherein the criteria comprise soft criteria, which indicate a nonconforming candidate individual is to remain as a candidate individual, and/or hard criteria, which indicate a nonconforming candidate individual is to be removed as a candidate individual. 8. The computer-implemented method of claim 5 , further comprising: determining, for each candidate individual, a likelihood the candidate individual is the individual based on the one or more criteria; and removing one or more candidate individuals with respective likelihoods below a threshold. | 0.5 |
9,659,563 | 10 | 12 | 10. A method comprising: receiving at a client device from a server first content containing regions of the world; generating at the client device a user interface for a user to select of a region from the regions of the world that the user desires to listen to the region-specific pronunciations of phrases of a first language, wherein the server determines that first regions of the regions of the world include at least one voice recording in the first language; transmitting from the client device to the server a region selected from the first regions by the user; receiving at the client device from the server second content containing a list of phrases and voice recordings corresponding to each of the phrases of the first language, wherein the voice recordings contain the region-specific pronunciations of the phrases of the region selected by the user; and generating an output of a voice recording of a phrase selected by the user from the list of phrases. | 10. A method comprising: receiving at a client device from a server first content containing regions of the world; generating at the client device a user interface for a user to select of a region from the regions of the world that the user desires to listen to the region-specific pronunciations of phrases of a first language, wherein the server determines that first regions of the regions of the world include at least one voice recording in the first language; transmitting from the client device to the server a region selected from the first regions by the user; receiving at the client device from the server second content containing a list of phrases and voice recordings corresponding to each of the phrases of the first language, wherein the voice recordings contain the region-specific pronunciations of the phrases of the region selected by the user; and generating an output of a voice recording of a phrase selected by the user from the list of phrases. 12. The method of claim 10 wherein the client device is at least one of a smartphone, a PDA, or a portable computer. | 0.610738 |
8,301,436 | 33 | 38 | 33. A hardware computer readable storage media including instructions readable by a computing device comprising: a language model comprising a combination of an N-gram language model and a context-free grammar language model and storing information related to words and semantic information to be recognized; a module receiving input including commands executable by an application from a user and capturing the input for processing, the module performing recognition on the input by accessing the language model and ascertaining semantic information pertaining to a first portion of the input and outputting a semantic object comprising data including data for executing commands in a format to be processed by a computer application and being in accordance with the input that has been recognized and semantic information for the first portion, wherein performing recognition and outputting the semantic object are performed while capturing continues for subsequent portions of the input; and a second module performing a selected task, the second module receiving semantic objects synchronously in accordance with the user's input, each semantic object comprising data including commands in a format to be processed by a computer application and in accordance with a portion of input from the user and semantic information pertaining to the portion of input from the user, the module taking action as a function of processing the semantic objects synchronously including providing information or utilizing other applications based on at least the data for executing the commands. | 33. A hardware computer readable storage media including instructions readable by a computing device comprising: a language model comprising a combination of an N-gram language model and a context-free grammar language model and storing information related to words and semantic information to be recognized; a module receiving input including commands executable by an application from a user and capturing the input for processing, the module performing recognition on the input by accessing the language model and ascertaining semantic information pertaining to a first portion of the input and outputting a semantic object comprising data including data for executing commands in a format to be processed by a computer application and being in accordance with the input that has been recognized and semantic information for the first portion, wherein performing recognition and outputting the semantic object are performed while capturing continues for subsequent portions of the input; and a second module performing a selected task, the second module receiving semantic objects synchronously in accordance with the user's input, each semantic object comprising data including commands in a format to be processed by a computer application and in accordance with a portion of input from the user and semantic information pertaining to the portion of input from the user, the module taking action as a function of processing the semantic objects synchronously including providing information or utilizing other applications based on at least the data for executing the commands. 38. The hardware computer readable storage media of claim 33 wherein the module captures visual input from the user. | 0.758333 |
8,706,644 | 2 | 3 | 2. A method implemented at least in part by a computing device, the method comprising: responsive to determining that a corpus of text includes a statistically improbable phrase, storing the determined statistically improbable phrase in a corpus of phrases for association with a user account, wherein the statistically improbable phrase, when received before or during a transaction, provides access to a payment instrument for use in a transaction; and causing output of the stored statistically improbable phrase for association with a user account. | 2. A method implemented at least in part by a computing device, the method comprising: responsive to determining that a corpus of text includes a statistically improbable phrase, storing the determined statistically improbable phrase in a corpus of phrases for association with a user account, wherein the statistically improbable phrase, when received before or during a transaction, provides access to a payment instrument for use in a transaction; and causing output of the stored statistically improbable phrase for association with a user account. 3. A method as recited in claim 2 , further comprising: suggesting the statistically improbable phrase to a user of the user account; and responsive to receiving a selection of the statistically improbable phrase from the user, associating the statistically improbable phrase with the user account. | 0.708984 |
7,698,652 | 13 | 14 | 13. A client-sever configuration comprising a client and a server, wherein: the server provides user-access to an ordered list of information items having descriptions; and the client is enabled to interact with the server, the server controlling the client to display a helper character representative of a portion of a description of an item in the ordered list being displayed, the display of the helper character being responsive to continued user actuation of the client, wherein the helper character is displayed in a size which is larger than a size of the descriptions, and wherein a change in the size is made based on a scrolling speed that is responsive to the continued user actuation. | 13. A client-sever configuration comprising a client and a server, wherein: the server provides user-access to an ordered list of information items having descriptions; and the client is enabled to interact with the server, the server controlling the client to display a helper character representative of a portion of a description of an item in the ordered list being displayed, the display of the helper character being responsive to continued user actuation of the client, wherein the helper character is displayed in a size which is larger than a size of the descriptions, and wherein a change in the size is made based on a scrolling speed that is responsive to the continued user actuation. 14. The client-server configuration of claim 13 , wherein the client comprises at least one of a handheld device, a desktop computer, a laptop computer, a wireless telephone handset, a portable media-playing device, and a cell phone. | 0.5 |
9,239,824 | 40 | 47 | 40. An apparatus, comprising: a processor, configured to receive an indication of initiation of a search, of a stored interactive dictionary database, by a user; and an integrated input and display device to display an electronic screen overlay including a plurality of polysemous symbols to the user, the electronic screen overlay further being usable for searching the interactive dictionary database, the processor being further configured to receive an indication of input of text into the electronic screen overlay usable for searching, and determine whether or not at least one entry in the interactive dictionary database includes a previously stored at least one word, sentence, phoneme, message, letter, number, morpheme, command and phrase matching the input text, and the display being further configured to display, upon the processor determining that one or more entries in the interactive dictionary database includes a term corresponding to the text of a previously stored at least one word, sentence, phoneme, message, letter, number, morpheme, command and/or phrase that matches the input text, a definition of the determined one or more identified entries in the interactive dictionary database, the definition including a sequence of symbols including at least one of the plurality of polysemous symbols of the electronic screen overlay, at least a subset of the plurality of polysemous symbol sequences being assignable by a user at least one of an active and an inactive status, wherein when an inactive status is assigned to one of the plurality of polysemous symbol sequences, a corresponding sequence of previously selectable symbols of the keyboard is rendered unselectable by the user. | 40. An apparatus, comprising: a processor, configured to receive an indication of initiation of a search, of a stored interactive dictionary database, by a user; and an integrated input and display device to display an electronic screen overlay including a plurality of polysemous symbols to the user, the electronic screen overlay further being usable for searching the interactive dictionary database, the processor being further configured to receive an indication of input of text into the electronic screen overlay usable for searching, and determine whether or not at least one entry in the interactive dictionary database includes a previously stored at least one word, sentence, phoneme, message, letter, number, morpheme, command and phrase matching the input text, and the display being further configured to display, upon the processor determining that one or more entries in the interactive dictionary database includes a term corresponding to the text of a previously stored at least one word, sentence, phoneme, message, letter, number, morpheme, command and/or phrase that matches the input text, a definition of the determined one or more identified entries in the interactive dictionary database, the definition including a sequence of symbols including at least one of the plurality of polysemous symbols of the electronic screen overlay, at least a subset of the plurality of polysemous symbol sequences being assignable by a user at least one of an active and an inactive status, wherein when an inactive status is assigned to one of the plurality of polysemous symbol sequences, a corresponding sequence of previously selectable symbols of the keyboard is rendered unselectable by the user. 47. The apparatus of claim 40 , wherein the interactive dictionary database includes a plurality of rationales, each respectively relating each of the plurality of symbol sequences to their associated at least one of words, sentences, phonemes, messages, letters, numbers, morphemes, commands and phrases. | 0.5 |
8,799,351 | 10 | 15 | 10. A device for communicating multiple files in a single markup language document, comprising: one or more processors for executing a document interface, the document interface operable to receive electronic data for delivery to a destination address, to receive an electronic file associated with the electronic data, to generate a first markup language document including the electronic data, to store both the first markup language document and the electronic file in a payload of a second markup language document, to generate a header for the second markup language document, the header identifying the existence of both the first markup language document and the electronic file in the payload, the header comprising at least one parameter indicative of one or more relationships between the first markup language document and the electronic file in the payload, and to transmit the second markup language document including the header and the payload to the destination address using a communication network. | 10. A device for communicating multiple files in a single markup language document, comprising: one or more processors for executing a document interface, the document interface operable to receive electronic data for delivery to a destination address, to receive an electronic file associated with the electronic data, to generate a first markup language document including the electronic data, to store both the first markup language document and the electronic file in a payload of a second markup language document, to generate a header for the second markup language document, the header identifying the existence of both the first markup language document and the electronic file in the payload, the header comprising at least one parameter indicative of one or more relationships between the first markup language document and the electronic file in the payload, and to transmit the second markup language document including the header and the payload to the destination address using a communication network. 15. The device of claim 10 , wherein both the first markup language document and the second markup language document conform to a public standard for text-based markup language communications. | 0.793991 |
9,563,624 | 15 | 16 | 15. A non-transitory computer-readable storage device having instructions stored which, when executed by a computing device, result in operations comprising: gathering statistics from a plurality of interactions with a user, wherein the statistics are gathered periodically with a defined frequency, and wherein the statistics identify words in the plurality of interactions and languages associated with the words; identifying, based on the statistics, a target language of the user, the target language being the language having a highest number of words used in the plurality of interactions; receiving a message for the user in a source language which is distinct from the target language; prior to presenting the message to the user, translating the message into the target language, to yield a translated message; and presenting the translated message in the target language to the user. | 15. A non-transitory computer-readable storage device having instructions stored which, when executed by a computing device, result in operations comprising: gathering statistics from a plurality of interactions with a user, wherein the statistics are gathered periodically with a defined frequency, and wherein the statistics identify words in the plurality of interactions and languages associated with the words; identifying, based on the statistics, a target language of the user, the target language being the language having a highest number of words used in the plurality of interactions; receiving a message for the user in a source language which is distinct from the target language; prior to presenting the message to the user, translating the message into the target language, to yield a translated message; and presenting the translated message in the target language to the user. 16. The non-transitory computer-readable storage device of claim 15 , having additional instructions stored which, when executed by the computing device, result in operations comprising: analyzing words in the statistics to determine a subject matter of interest to the user; and determining whether to translate the message based on the subject matter of interest. | 0.5 |
8,016,680 | 7 | 8 | 7. The system as in claim 6 further comprising: a. a character inventory that is arranged to record character possessions; b. selected activities in the first group arranged to provide a character inventory with a possession chosen from the group consisting of PGO, PGO attribute, and character attribute; c. the character object exchange arranged such that a character obtains a possession chosen from the group consisting of PGO, PGO attribute, and character attribute using monetary units; and d. one or more possessions required in the character inventory for successful completion of selected second group activities wherein the learner is motivated to succeed in target education skill practice in order to advance the character in the game and to produce a favorable learner profile. | 7. The system as in claim 6 further comprising: a. a character inventory that is arranged to record character possessions; b. selected activities in the first group arranged to provide a character inventory with a possession chosen from the group consisting of PGO, PGO attribute, and character attribute; c. the character object exchange arranged such that a character obtains a possession chosen from the group consisting of PGO, PGO attribute, and character attribute using monetary units; and d. one or more possessions required in the character inventory for successful completion of selected second group activities wherein the learner is motivated to succeed in target education skill practice in order to advance the character in the game and to produce a favorable learner profile. 8. The system as in claim 7 further comprising: a. selected activities in the first group arranged to provide a character inventory with one or more possessions with a variable performance attribute, the attribute improving with fewer errors in the skill practice; b. the character object exchange arranged such that a character obtains a possession with an improved performance attribute using monetary units; and c. activities in the second group arranged to require one or more possessions with a selected minimum performance attribute to succeed in the activity wherein the learner is provided motivation to succeed in target education skill practice to advance the character in the game and produce a favorable learner profile. | 0.5 |
9,386,256 | 8 | 11 | 8. A hardware-based system for notifying a user when a set of words is identified in a media file, the hardware-based system comprising: a transcription module configured to transcribe the media file to form a transcription; an identification module configured to identify a segment of the media file comprising a user-defined set of words, the identification module further configured to use the transcription to identify the segment of the media file comprising the user-defined set of words; and a notification module configured to notify the user in response to identifying the segment of the media file comprising the user-defined set of words, wherein the identification module is further configured to identify a sub-segment in which the set of characters occurs, wherein the sub-segment is marked by a beginning time point and an ending time point within the segment. | 8. A hardware-based system for notifying a user when a set of words is identified in a media file, the hardware-based system comprising: a transcription module configured to transcribe the media file to form a transcription; an identification module configured to identify a segment of the media file comprising a user-defined set of words, the identification module further configured to use the transcription to identify the segment of the media file comprising the user-defined set of words; and a notification module configured to notify the user in response to identifying the segment of the media file comprising the user-defined set of words, wherein the identification module is further configured to identify a sub-segment in which the set of characters occurs, wherein the sub-segment is marked by a beginning time point and an ending time point within the segment. 11. The hardware-based system of claim 8 , wherein the notification module is configured to notify the user using at least one of an audio or visual alert. | 0.869309 |
8,386,232 | 11 | 27 | 11. The method of claim 1 , wherein the step of applying the model comprises assigning a feature associated with a particular cluster of the clusters of related items to an item in the input data. | 11. The method of claim 1 , wherein the step of applying the model comprises assigning a feature associated with a particular cluster of the clusters of related items to an item in the input data. 27. One or more non-transitory computer readable storage media storing instructions which, when executed by one or more computing devices, cause performance of the method recited in claim 11 . | 0.5 |
8,230,112 | 13 | 14 | 13. A system comprising: a first receiving module configured to receive a first message from a first sender and a second message from a second sender, wherein the first message is in a first character set and a first native format, the second message is in a second character set and a second native format, the first native format and the second native format are each formats for formatting electronic messages, and the first native format differs from the second native format; a first converting module, wherein the first converting module comprises a processor configured to convert the first message from the first native format to an independent format and to convert the second message from the second native format to the independent format; a first storing module configured to store the first message and the second message in the independent format; a first selecting module configured to select a first display format for the first message and a second display format for the second message, wherein the first display format differs from the first native format, and the second display format differs from the second native format; a second converting module configured to convert the first message from the independent format to the first display format and to convert the second message from the independent format to the second display format; a first displaying module configured to display the first message in the first display format, wherein said displaying the first message comprises displaying the first message to a user via an application program client; a second displaying module configured to display the second message in the second display format, wherein said displaying the second message comprises displaying the second message to the user via the application program client; a second receiving module configured to receive, via the application program client, a first response to the first message and to receive a second response to the second message, wherein the first response is in a first response character set and a first response format, the second response is in a second response character set and a second response format, the first response format and the second response format each specify a format for formatting electronic messages, the first response format differs from the first native format, and the second response format differs from the second native format; a third converting module configured to convert the first response from the first response format to the independent format and to convert the second response from the second response format to the independent format; a second selecting module configured to dynamically select a first final response format for the first response and to dynamically select a second final response format for the second response, wherein said dynamically selecting the first final response format comprises retrieving an indicator of the first native format, if the first final response format is to be the same as the first native format, said dynamically selecting the second final response format comprises retrieving an indicator of the second native format, if the second final response format is to be the same as the second native format, and the first final response format and the second final response format each specify a format for formatting electronic messages; a fourth converting module configured to convert the first response from the independent format to the first final response format and to convert the second response from the independent format to the second final response format; an including module configured to include a pre-formulated content in the first response, wherein the pre-formulated content is responsive to a portion of the first message, and the pre-formulated content is provided in the first native format as part of the first response; and a providing module configured to provide the first response in the first final response format to the first sender and to provide the second response in the second final response format to the second sender. | 13. A system comprising: a first receiving module configured to receive a first message from a first sender and a second message from a second sender, wherein the first message is in a first character set and a first native format, the second message is in a second character set and a second native format, the first native format and the second native format are each formats for formatting electronic messages, and the first native format differs from the second native format; a first converting module, wherein the first converting module comprises a processor configured to convert the first message from the first native format to an independent format and to convert the second message from the second native format to the independent format; a first storing module configured to store the first message and the second message in the independent format; a first selecting module configured to select a first display format for the first message and a second display format for the second message, wherein the first display format differs from the first native format, and the second display format differs from the second native format; a second converting module configured to convert the first message from the independent format to the first display format and to convert the second message from the independent format to the second display format; a first displaying module configured to display the first message in the first display format, wherein said displaying the first message comprises displaying the first message to a user via an application program client; a second displaying module configured to display the second message in the second display format, wherein said displaying the second message comprises displaying the second message to the user via the application program client; a second receiving module configured to receive, via the application program client, a first response to the first message and to receive a second response to the second message, wherein the first response is in a first response character set and a first response format, the second response is in a second response character set and a second response format, the first response format and the second response format each specify a format for formatting electronic messages, the first response format differs from the first native format, and the second response format differs from the second native format; a third converting module configured to convert the first response from the first response format to the independent format and to convert the second response from the second response format to the independent format; a second selecting module configured to dynamically select a first final response format for the first response and to dynamically select a second final response format for the second response, wherein said dynamically selecting the first final response format comprises retrieving an indicator of the first native format, if the first final response format is to be the same as the first native format, said dynamically selecting the second final response format comprises retrieving an indicator of the second native format, if the second final response format is to be the same as the second native format, and the first final response format and the second final response format each specify a format for formatting electronic messages; a fourth converting module configured to convert the first response from the independent format to the first final response format and to convert the second response from the independent format to the second final response format; an including module configured to include a pre-formulated content in the first response, wherein the pre-formulated content is responsive to a portion of the first message, and the pre-formulated content is provided in the first native format as part of the first response; and a providing module configured to provide the first response in the first final response format to the first sender and to provide the second response in the second final response format to the second sender. 14. The system of claim 13 , further comprising: a generating module configured to automatically generate the first response. | 0.5 |
8,626,691 | 1 | 5 | 1. A method of detecting a server operating in a network, comprising: collecting Internet Protocol traffic information; merging the Internet Protocol traffic information having a common source address and a common destination address; merging the Internet Protocol traffic information having a source address and an opposing destination address to generate bidirectional flows; separating valid bidirectional flows from invalid bidirectional flows; retrieving a set of heuristic rules from memory for determining the server; determining an output of each heuristic rule in the set of heuristic rules based on the valid bidirectional flows; combining all outputs produced by the set of heuristic rules; and generating a probability that the source address corresponds to the server based on combined outputs produced by the set of heuristic rules. | 1. A method of detecting a server operating in a network, comprising: collecting Internet Protocol traffic information; merging the Internet Protocol traffic information having a common source address and a common destination address; merging the Internet Protocol traffic information having a source address and an opposing destination address to generate bidirectional flows; separating valid bidirectional flows from invalid bidirectional flows; retrieving a set of heuristic rules from memory for determining the server; determining an output of each heuristic rule in the set of heuristic rules based on the valid bidirectional flows; combining all outputs produced by the set of heuristic rules; and generating a probability that the source address corresponds to the server based on combined outputs produced by the set of heuristic rules. 5. The method according to claim 1 , further comprising retrieving an interval of time for collecting the Internet Protocol traffic information. | 0.655502 |
8,568,144 | 1 | 27 | 1. A reading comprehension training system, comprising: a computing device; a game logic portion that generates a reading comprehension challenge that comprises language micro-variables including one or more verb micro-variables, one or more agent micro-variables, and one or more reference micro-variables at a particular level of difficulty to test a user's comprehension of the reading comprehension challenge; a user interface portion that generates a user interface to display the reading comprehension challenge at the particular skill level on the computing device; and wherein the game logic portion comprises a game administrator portion that: receives a response from the user to the reading comprehension challenge based on controlled manipulation of the language micro-variables in the reading comprehension challenge, isolates one or more language micro-variables that are impeding the user's comprehension of the reading comprehension challenge based on the response from the user, provides direct instruction to train the user to become more proficient at the isolated one or more language micro-variables based on controlled manipulation of the isolated one or more language micro-variables, and determines, once the user becomes more proficient at the isolated one or more language micro-variables, a next reading comprehension challenge that comprises language micro-variables including one or more verb micro-variables, one or more agent micro-variables, and one or more reference micro-variables at a particular level of difficulty to test the user's comprehension of the next reading comprehension challenge. | 1. A reading comprehension training system, comprising: a computing device; a game logic portion that generates a reading comprehension challenge that comprises language micro-variables including one or more verb micro-variables, one or more agent micro-variables, and one or more reference micro-variables at a particular level of difficulty to test a user's comprehension of the reading comprehension challenge; a user interface portion that generates a user interface to display the reading comprehension challenge at the particular skill level on the computing device; and wherein the game logic portion comprises a game administrator portion that: receives a response from the user to the reading comprehension challenge based on controlled manipulation of the language micro-variables in the reading comprehension challenge, isolates one or more language micro-variables that are impeding the user's comprehension of the reading comprehension challenge based on the response from the user, provides direct instruction to train the user to become more proficient at the isolated one or more language micro-variables based on controlled manipulation of the isolated one or more language micro-variables, and determines, once the user becomes more proficient at the isolated one or more language micro-variables, a next reading comprehension challenge that comprises language micro-variables including one or more verb micro-variables, one or more agent micro-variables, and one or more reference micro-variables at a particular level of difficulty to test the user's comprehension of the next reading comprehension challenge. 27. The system of claim 1 , wherein the game logic portion further comprises a high frequency phrases training exercise that trains a student on a plurality of frequently occurring n-gram phrases. | 0.857558 |
9,245,027 | 6 | 7 | 6. A computer-readable medium having stored thereon a set of instructions that are executable by a processor to carry out a method, the method comprising: receiving a compound result URL at a target computer system, the compound result URL including a target page identifier and a query; in response to receiving the compound result URL, utilizing the target page identifier to identify a target page on the target computer system; automatically executing a call script causing receipt of a plurality of suggestions based on the query, each suggestion including a text of the suggestion and a suggestion URL; automatically executing a placement script that places the text of each suggestion on the target page, the text of each suggestion having an associated suggestion URL so that selection of the text of the suggestion causes redirection of a user computer based on the suggestion URL, wherein each suggestion URL is a compound suggestion URL that includes a search engine identifier indicating a search engine system to receive the compound suggestion URL and the text of the suggestion enables the search engine system to extract a plurality of answers from a database communicatively coupled to the search engine; and transmitting a user computer system identifier of the user computer system with the compound URL to the search engine transmitting the answers to the user computer system associated with the user computer system identifier, wherein the compound suggestion URL includes a target computer system identifier of the target computer system for use by the search engine system to credit an account corresponding to the target computer system identifier. | 6. A computer-readable medium having stored thereon a set of instructions that are executable by a processor to carry out a method, the method comprising: receiving a compound result URL at a target computer system, the compound result URL including a target page identifier and a query; in response to receiving the compound result URL, utilizing the target page identifier to identify a target page on the target computer system; automatically executing a call script causing receipt of a plurality of suggestions based on the query, each suggestion including a text of the suggestion and a suggestion URL; automatically executing a placement script that places the text of each suggestion on the target page, the text of each suggestion having an associated suggestion URL so that selection of the text of the suggestion causes redirection of a user computer based on the suggestion URL, wherein each suggestion URL is a compound suggestion URL that includes a search engine identifier indicating a search engine system to receive the compound suggestion URL and the text of the suggestion enables the search engine system to extract a plurality of answers from a database communicatively coupled to the search engine; and transmitting a user computer system identifier of the user computer system with the compound URL to the search engine transmitting the answers to the user computer system associated with the user computer system identifier, wherein the compound suggestion URL includes a target computer system identifier of the target computer system for use by the search engine system to credit an account corresponding to the target computer system identifier. 7. The computer-readable medium of claim 6 , the method further comprising: transmitting the target page from the target computer system to the user computer system. | 0.5 |
9,177,557 | 8 | 10 | 8. A method of providing speech recognition functionality for an utterance spoken in a noisy environment having multiple human speakers, the method comprising: extracting feature data from the utterance, wherein the feature data comprises one or more features; processing the feature data to produce speaker dependent feature data and speaker independent feature data; projecting only the speaker independent data into a feature space, the feature space having multiple human speaker subspaces for multiple human speakers, wherein each one of the multiple human speakers is associated with a distinct one of the multiple human speaker subspaces; identifying speaker independent feature data associated with a speaker subspace associated with a primary human speaker; and performing a speech recognition operation restricted to a single one of the multiple human speaker subspaces, wherein the speaker independent feature data includes contributions from at least two speakers, and wherein performing a speech recognition operation restricted to a single one of the multiple human speaker subspaces comprises removing all feature data not associated with the speaker subspace associated with the primary human speaker. | 8. A method of providing speech recognition functionality for an utterance spoken in a noisy environment having multiple human speakers, the method comprising: extracting feature data from the utterance, wherein the feature data comprises one or more features; processing the feature data to produce speaker dependent feature data and speaker independent feature data; projecting only the speaker independent data into a feature space, the feature space having multiple human speaker subspaces for multiple human speakers, wherein each one of the multiple human speakers is associated with a distinct one of the multiple human speaker subspaces; identifying speaker independent feature data associated with a speaker subspace associated with a primary human speaker; and performing a speech recognition operation restricted to a single one of the multiple human speaker subspaces, wherein the speaker independent feature data includes contributions from at least two speakers, and wherein performing a speech recognition operation restricted to a single one of the multiple human speaker subspaces comprises removing all feature data not associated with the speaker subspace associated with the primary human speaker. 10. The method of claim 8 , further comprising: identifying speaker independent feature data associated with a second speaker subspace associated with a second human speaker; and performing a second speech recognition operation restricted to a second one of the multiple human speaker subspaces. | 0.652123 |
7,580,571 | 1 | 2 | 1. An image processing method, comprising: using a processor to perform the steps of: extracting a predetermined number of consecutive characters from a document image; converting the consecutive characters into a set of symbols using layout information obtained from the consecutive characters; and detecting an orientation of the consecutive characters based on occurrence probabilities of the set of symbols obtained using a plurality of reference images, each reference image corresponding to one of the predetermined orientations, wherein the plurality of reference images includes four types of reference images, each type corresponding to one of four orientations, the four types of reference images being prepared for at least one of a vertical character line and a horizontal character line. | 1. An image processing method, comprising: using a processor to perform the steps of: extracting a predetermined number of consecutive characters from a document image; converting the consecutive characters into a set of symbols using layout information obtained from the consecutive characters; and detecting an orientation of the consecutive characters based on occurrence probabilities of the set of symbols obtained using a plurality of reference images, each reference image corresponding to one of the predetermined orientations, wherein the plurality of reference images includes four types of reference images, each type corresponding to one of four orientations, the four types of reference images being prepared for at least one of a vertical character line and a horizontal character line. 2. The method of claim 1 , further comprising the step of: determining an orientation of the document image based on the detected orientation of the consecutive characters. | 0.710438 |
7,624,356 | 19 | 22 | 19. A method of exposing commands in a document-centric application program executed by a computer, the method comprising: automatically displaying, by the computer, a window on a display device, the window generated by the document-centric application program, the window containing a work area and a controls area, the work area containing a document, the controls area not initially containing a context block; storing, by the computer, Hyper-Text Markup Language (HTML) code that specifies a title of the context block and a set of commands of the context block, the set of commands executable by the document-centric application program, the title identifying a task, the set of commands useful to a user in accomplishing the task; storing a tree data structure at the computer, the tree data structure comprising an overall set of nodes, each node in the overall set of nodes being an independent data structure, the overall set of nodes including a root node and a set of child nodes, each node in the set of child nodes being a child of one other node in the overall set of nodes, the overall set of nodes comprising a set of leaf nodes and a set of non-leaf nodes, no node in the overall set of nodes being a child of any node in the set of leaf nodes, each node in the set of non-leaf nodes having at least one child node in the overall set of nodes, the root node not being a child of any node in the overall set of nodes, each node in the overall set of nodes associated with a value, each node in the overall set of nodes associated with a Boolean expression, the Boolean expression associated with each node in the set of non-leaf nodes taking as operands the values associated with each child node of the node, the set of leaf nodes including a first leaf node; automatically ascertaining, at the computer, whether a change has occurred to selected text portions of the document, the selected text portions of the document being portions of the document selected by the user using a cursor the cursor being controlled by a user, where the document is a document the user is working in; in response to ascertaining that the change has occurred to the selected text portions of the document, making, at the computer, a change to the value associated with the first leaf node; in response to a change to the value associated with any non-root node, using, at the computer, a Boolean expression associated with a parent node to make a determination whether to change a value associated with the parent node, the Boolean expression associated with the parent node taking as operands the values associated with each child node of the parent node, the non-root node being in the set of child nodes, the parent node being a parent of the non-root node; in response to making a determination to change the value associated with the parent node, changing, at the computer, the value associated with the parent node; in response to determining that the value associated with the root node has changed from a first value to a second value, automatically causing, at the computer, the controls areas to contain the context block, the context block containing the title of the context block and the set of commands of the context block, the context block not obscuring the document; in response to determining that the value associated with the root node has changed from the second value to the first value, automatically causing, at the computer, the controls area not to contain the context block; and while the controls area contains the context block, enabling, with the computer, the user to select and apply various commands in the set of commands of the context block to the document multiple times. | 19. A method of exposing commands in a document-centric application program executed by a computer, the method comprising: automatically displaying, by the computer, a window on a display device, the window generated by the document-centric application program, the window containing a work area and a controls area, the work area containing a document, the controls area not initially containing a context block; storing, by the computer, Hyper-Text Markup Language (HTML) code that specifies a title of the context block and a set of commands of the context block, the set of commands executable by the document-centric application program, the title identifying a task, the set of commands useful to a user in accomplishing the task; storing a tree data structure at the computer, the tree data structure comprising an overall set of nodes, each node in the overall set of nodes being an independent data structure, the overall set of nodes including a root node and a set of child nodes, each node in the set of child nodes being a child of one other node in the overall set of nodes, the overall set of nodes comprising a set of leaf nodes and a set of non-leaf nodes, no node in the overall set of nodes being a child of any node in the set of leaf nodes, each node in the set of non-leaf nodes having at least one child node in the overall set of nodes, the root node not being a child of any node in the overall set of nodes, each node in the overall set of nodes associated with a value, each node in the overall set of nodes associated with a Boolean expression, the Boolean expression associated with each node in the set of non-leaf nodes taking as operands the values associated with each child node of the node, the set of leaf nodes including a first leaf node; automatically ascertaining, at the computer, whether a change has occurred to selected text portions of the document, the selected text portions of the document being portions of the document selected by the user using a cursor the cursor being controlled by a user, where the document is a document the user is working in; in response to ascertaining that the change has occurred to the selected text portions of the document, making, at the computer, a change to the value associated with the first leaf node; in response to a change to the value associated with any non-root node, using, at the computer, a Boolean expression associated with a parent node to make a determination whether to change a value associated with the parent node, the Boolean expression associated with the parent node taking as operands the values associated with each child node of the parent node, the non-root node being in the set of child nodes, the parent node being a parent of the non-root node; in response to making a determination to change the value associated with the parent node, changing, at the computer, the value associated with the parent node; in response to determining that the value associated with the root node has changed from a first value to a second value, automatically causing, at the computer, the controls areas to contain the context block, the context block containing the title of the context block and the set of commands of the context block, the context block not obscuring the document; in response to determining that the value associated with the root node has changed from the second value to the first value, automatically causing, at the computer, the controls area not to contain the context block; and while the controls area contains the context block, enabling, with the computer, the user to select and apply various commands in the set of commands of the context block to the document multiple times. 22. The method of claim 19 , wherein causing the controls area to contain the context block comprises displaying, by the computer, the context block in a modeless manner. | 0.771505 |
9,183,198 | 1 | 7 | 1. A method for computer-aided translation, comprising: receiving a document comprising one or more sentences to be translated; generating a suggestion pool of possible translations for each sentence in the document using a processor; providing a best suggestion from the suggestion pool to a user for a sentence being translated; updating the suggestion pool based on the user's input of a translation prefix; and providing an updated best suggestion from the updated suggestion pool to the user for the sentence being translated. | 1. A method for computer-aided translation, comprising: receiving a document comprising one or more sentences to be translated; generating a suggestion pool of possible translations for each sentence in the document using a processor; providing a best suggestion from the suggestion pool to a user for a sentence being translated; updating the suggestion pool based on the user's input of a translation prefix; and providing an updated best suggestion from the updated suggestion pool to the user for the sentence being translated. 7. The method of claim 1 , further comprising: transmitting the suggestion pool to a client device, wherein the suggestion pool is generated at a server device; and transmitting a request for additional possible translations based on the translation prefix if the prefix deviates from possible translations in the suggestion pool. | 0.5 |
4,841,387 | 18 | 27 | 18. A machine method for recording information relating to an event on a recording medium and indexing the recorded information to handwritten notations concerning the event, comprising the steps of: making a continuous recording of information on a recording medium throughout a designated time interval; making handwritten notations on a writing surface during said time interval; sensing the relative positions of the recorded information on the recording medium, and of the handwritten notations on the writing surface; correlating the respective positions of the recorded information to the positions of corresponding handwritten notations; and reviewing a portion of the recorded information by identifying the position of a corresponding handwritten notation, and subsequently locating and reproducing a portion of the recorded information which corresponds to the identified handwritten notation. | 18. A machine method for recording information relating to an event on a recording medium and indexing the recorded information to handwritten notations concerning the event, comprising the steps of: making a continuous recording of information on a recording medium throughout a designated time interval; making handwritten notations on a writing surface during said time interval; sensing the relative positions of the recorded information on the recording medium, and of the handwritten notations on the writing surface; correlating the respective positions of the recorded information to the positions of corresponding handwritten notations; and reviewing a portion of the recorded information by identifying the position of a corresponding handwritten notation, and subsequently locating and reproducing a portion of the recorded information which corresponds to the identified handwritten notation. 27. A machine method according to claim 18, wherein the step of sensing the positions of the handwritten notations on the writing surface includes sensing the position of a writing instrument on said writing surface. | 0.52 |
8,874,434 | 17 | 21 | 17. An apparatus for generating a linguistic parse tree for a sentence, the apparatus comprising: a processor and a memory, the memory embodying code that when executed by the processor causes the processor to perform the functions of: code for predicting, via a Graph Transformer Network (GTN), a first level of chunk tags for the sentence, and code for predicting at least a second level of chunk tags for the sentence using the first level or a previous level of chunk tags; code for determining a sum of scores S from the predicted chunk tags in a graph G for a tag path [t] 1 N for words [w] 1 N as S ( [ w ] 1 N , [ t ] 1 N , θ ) = ∑ n = 1 N ( A t n - 1 t n + s ( x n ) t n ) , where N is the number of words, θ represents trained parameters of a neural network of a tagger with a fixed-sized word dictionary W, trained parameter matrices M 1 and M 2 , and transition score A, each node G tn is assigned a score s(x n ) t n from the neural network of the tagger, and given a pair of nodes G tn and G um , an edge is added with a transition score A tu on the graph; and outputting a graph with network scores provided for each G tn of the graph and additional transition scores for the edges of the graph. | 17. An apparatus for generating a linguistic parse tree for a sentence, the apparatus comprising: a processor and a memory, the memory embodying code that when executed by the processor causes the processor to perform the functions of: code for predicting, via a Graph Transformer Network (GTN), a first level of chunk tags for the sentence, and code for predicting at least a second level of chunk tags for the sentence using the first level or a previous level of chunk tags; code for determining a sum of scores S from the predicted chunk tags in a graph G for a tag path [t] 1 N for words [w] 1 N as S ( [ w ] 1 N , [ t ] 1 N , θ ) = ∑ n = 1 N ( A t n - 1 t n + s ( x n ) t n ) , where N is the number of words, θ represents trained parameters of a neural network of a tagger with a fixed-sized word dictionary W, trained parameter matrices M 1 and M 2 , and transition score A, each node G tn is assigned a score s(x n ) t n from the neural network of the tagger, and given a pair of nodes G tn and G um , an edge is added with a transition score A tu on the graph; and outputting a graph with network scores provided for each G tn of the graph and additional transition scores for the edges of the graph. 21. The apparatus of claim 17 , wherein GTN uses long range dependency in the form of a lookup table to predict the levels of chunk tags. | 0.753597 |
8,897,500 | 2 | 3 | 2. The method of claim 1 , wherein the recording of the audio recording and the video recording yields a dynamic image feature. | 2. The method of claim 1 , wherein the recording of the audio recording and the video recording yields a dynamic image feature. 3. The method of claim 2 , wherein the dynamic image feature comprises a pattern of movement. | 0.836842 |
9,292,602 | 1 | 3 | 1. A system comprising: a processor; and memory that stores instructions that, when executed by the processor, cause the processor to perform acts: receiving a query for performing a search over a data repository that comprises messages broadcast by way of a message broadcasting social networking application, at least some of the messages being rebroadcast by way of the message broadcasting social networking application, each message in the messages comprising message content and an identifiable author; performing a search over the messages to output a plurality of messages based upon the query; causing a first set of messages from the plurality of messages to be displayed; causing an interactive graphical object to be displayed together with the first set of messages, the interactive graphical object being representative of content of the plurality of messages; and in response to receipt of a selection of a portion of the interactive graphical object, refining the search and outputting a second set of messages from the plurality of messages, the search refined based upon the selection of the portion of the interactive graphical object. | 1. A system comprising: a processor; and memory that stores instructions that, when executed by the processor, cause the processor to perform acts: receiving a query for performing a search over a data repository that comprises messages broadcast by way of a message broadcasting social networking application, at least some of the messages being rebroadcast by way of the message broadcasting social networking application, each message in the messages comprising message content and an identifiable author; performing a search over the messages to output a plurality of messages based upon the query; causing a first set of messages from the plurality of messages to be displayed; causing an interactive graphical object to be displayed together with the first set of messages, the interactive graphical object being representative of content of the plurality of messages; and in response to receipt of a selection of a portion of the interactive graphical object, refining the search and outputting a second set of messages from the plurality of messages, the search refined based upon the selection of the portion of the interactive graphical object. 3. The system of claim 1 , the acts further comprising: locating phrases that co-occur across messages in the plurality of messages, wherein the interactive graphical object is a phrase cloud that depicts the phrases that co-occur across the messages in the plurality of messages; and responsive to receipt of a selection of a phrase in the phrase cloud, filtering the plurality of messages based upon the phrase. | 0.655259 |
9,971,809 | 1 | 7 | 1. A computer-implemented method for searching unstructured documents for structured data, at least a portion of the method being performed by a computing device comprising at least one processor, the method comprising: receiving a request to search unstructured documents for a document that contains: a value from a first field of a dataset; and a value from a second field of the dataset; generating a secure search index for searching the unstructured documents by, for each record in the dataset: identifying, within the dataset, the record's value from the first field and the record's value from the second field; generating a first hashed key from the record's value from the first field and the record's value from the second field; adding the first hashed key to the secure search index; extracting a first token and a second token from an unstructured document; generating a second hashed key from the first token and the second token; querying the secure search index to determine whether the second hashed key is contained in the secure search index; responding, upon determining that the second hashed key is contained in the secure search index, to the request with information about the unstructured document. | 1. A computer-implemented method for searching unstructured documents for structured data, at least a portion of the method being performed by a computing device comprising at least one processor, the method comprising: receiving a request to search unstructured documents for a document that contains: a value from a first field of a dataset; and a value from a second field of the dataset; generating a secure search index for searching the unstructured documents by, for each record in the dataset: identifying, within the dataset, the record's value from the first field and the record's value from the second field; generating a first hashed key from the record's value from the first field and the record's value from the second field; adding the first hashed key to the secure search index; extracting a first token and a second token from an unstructured document; generating a second hashed key from the first token and the second token; querying the secure search index to determine whether the second hashed key is contained in the secure search index; responding, upon determining that the second hashed key is contained in the secure search index, to the request with information about the unstructured document. 7. The computer-implemented method of claim 1 , wherein generating the first hashed key comprises: generating an intermediate value from a combination of the record's value from the first field and the record's value from the second field; hashing the intermediate value to produce the hashed key. | 0.896588 |
4,842,281 | 1 | 2 | 1. An option board game, comprising: a generally rectangular game board; a peripheral first movement path on said game board, formed by a series of adjacent squares; a vertical second movement path on an interior portion of said game board formed by a series of adjacent squares, said second movement path connecting opposite ends of said first movement path; a horizontal third movement path on an interior portion of said frame board formed by a series of adjacent squares, said third movement path connecting opposite sides of said first movement path and intersecting said second movement path at a central "START" square; a plurality of random consequence charts designated by an associated symbol on an interior portion of said game board, said random consequence charts having numbered boxes indicating various rewards and penalties designated by possible numerical totals obtained by rolling a pair of dice; a first "PAYDAY" group of said series of movement path squares being designated by various monetary rewards; a second "LETTER SALE" group of said series of movement path squares being designated by various letters of a key phrase and by an associated dollar value; a third "FREE LETTER" group of said series of movement path squares being designated by various letters of a key phrase and by the word "FREE"; a fourth "OPTION" group of said series of movement path squares being designated by a choice of two alternative courses of play; a fifth "SYMBOL" group of said series of movement path squares being designated by one of said random consequence chart symbols; a sixth "PENALTY LETTER" group of said series of movement path squares designated by the key word and by one of the letters of the key word; a plurality of player pieces for movement about said movement paths; a pair of dice for randomly determining movement of said player pieces; a plurality of scoreboards, each of said scoreboards having a plurality of recesses designated by the letters of the key phrase and key word; a counter on said scoreboard for indicating a player's bank account balance; a plurality of sets of lettered tiles, each of said sets containing all of the letters of said key phrase and said key word, said lettered tiles dimensioned to be received in said scoreboard recesses; a plurality of position marker chips; and a plurality of "INSURANCE POLICY CARDS". | 1. An option board game, comprising: a generally rectangular game board; a peripheral first movement path on said game board, formed by a series of adjacent squares; a vertical second movement path on an interior portion of said game board formed by a series of adjacent squares, said second movement path connecting opposite ends of said first movement path; a horizontal third movement path on an interior portion of said frame board formed by a series of adjacent squares, said third movement path connecting opposite sides of said first movement path and intersecting said second movement path at a central "START" square; a plurality of random consequence charts designated by an associated symbol on an interior portion of said game board, said random consequence charts having numbered boxes indicating various rewards and penalties designated by possible numerical totals obtained by rolling a pair of dice; a first "PAYDAY" group of said series of movement path squares being designated by various monetary rewards; a second "LETTER SALE" group of said series of movement path squares being designated by various letters of a key phrase and by an associated dollar value; a third "FREE LETTER" group of said series of movement path squares being designated by various letters of a key phrase and by the word "FREE"; a fourth "OPTION" group of said series of movement path squares being designated by a choice of two alternative courses of play; a fifth "SYMBOL" group of said series of movement path squares being designated by one of said random consequence chart symbols; a sixth "PENALTY LETTER" group of said series of movement path squares designated by the key word and by one of the letters of the key word; a plurality of player pieces for movement about said movement paths; a pair of dice for randomly determining movement of said player pieces; a plurality of scoreboards, each of said scoreboards having a plurality of recesses designated by the letters of the key phrase and key word; a counter on said scoreboard for indicating a player's bank account balance; a plurality of sets of lettered tiles, each of said sets containing all of the letters of said key phrase and said key word, said lettered tiles dimensioned to be received in said scoreboard recesses; a plurality of position marker chips; and a plurality of "INSURANCE POLICY CARDS". 2. The option board game of claim 1, wherein said key phrase is "LIFE'S LITTLE PLEASURES" and said key word is "ZONK". | 0.5 |
8,421,805 | 13 | 14 | 13. The method of claim 1 wherein depicting the active movements further comprises: extracting features from an input stream, the features indicative of spoken verbiage; identifying active animations corresponding to the extracted features; and applying the active animations to the rendered image to generate the appearance of the rendered image verbalizing the spoken language corresponding to the extracted features. | 13. The method of claim 1 wherein depicting the active movements further comprises: extracting features from an input stream, the features indicative of spoken verbiage; identifying active animations corresponding to the extracted features; and applying the active animations to the rendered image to generate the appearance of the rendered image verbalizing the spoken language corresponding to the extracted features. 14. The method of claim 13 wherein extracting features from the input stream further comprises: extracting audio features and video features from the input stream, wherein the extracted features further comprise audio features and video features, further comprising applying active animations to affect mouth, eye and profile appearances of the rendered image. | 0.5 |
9,460,711 | 1 | 11 | 1. A computer-implemented method, comprising: receiving training data comprising a respective training data set for each of two or more languages; processing a monolingual deep neural network (DNN) acoustic model on a given training data set of the two or more languages; initializing one or more weights of a multilingual DNN acoustic model based on the processing of the monolingual DNN acoustic model, wherein the multilingual DNN acoustic model comprises a feedforward neural network having multiple layers of one or more nodes, wherein each node of a given layer connects with a respective weight to each node of a subsequent layer, and wherein the multiple layers of one or more nodes comprise one or more hidden layers of nodes that are shared between at least two of the two or more languages and a language-specific output layer of nodes corresponding to each of the two or more languages; after initializing the one or more weights of the multilingual DNN acoustic model based on the processing of the monolingual DNN acoustic model, processing, by one or more computing devices, the multilingual DNN acoustic model based on the training data to generate a trained multilingual DNN acoustic model; and using the trained multilingual DNN acoustic model in an automatic speech recognition (ASR) system. | 1. A computer-implemented method, comprising: receiving training data comprising a respective training data set for each of two or more languages; processing a monolingual deep neural network (DNN) acoustic model on a given training data set of the two or more languages; initializing one or more weights of a multilingual DNN acoustic model based on the processing of the monolingual DNN acoustic model, wherein the multilingual DNN acoustic model comprises a feedforward neural network having multiple layers of one or more nodes, wherein each node of a given layer connects with a respective weight to each node of a subsequent layer, and wherein the multiple layers of one or more nodes comprise one or more hidden layers of nodes that are shared between at least two of the two or more languages and a language-specific output layer of nodes corresponding to each of the two or more languages; after initializing the one or more weights of the multilingual DNN acoustic model based on the processing of the monolingual DNN acoustic model, processing, by one or more computing devices, the multilingual DNN acoustic model based on the training data to generate a trained multilingual DNN acoustic model; and using the trained multilingual DNN acoustic model in an automatic speech recognition (ASR) system. 11. The computer-implemented method of claim 1 , wherein the trained multilingual DNN acoustic model is configured to be used to perform ASR in multiple languages of the two or more languages. | 0.834197 |
9,854,330 | 9 | 13 | 9. A method comprising: generating a fingerprint data using a television, wherein the fingerprint data is any one of an audio fingerprint data and a video fingerprint data; matching primary data generated from the fingerprint data with targeted data based on a relevancy factor using a relevancy-matching server; looking in a data repository for at least one of the targeted data, a reference to the targeted data and a metadata of the targeted data using the relevancy-matching server, wherein the primary data is any one of a content identification data and a content identification history; constraining an executable environment in a security sandbox of a mobile device; executing a sandboxed application in the executable environment of the mobile device; associating the mobile device with the television based on: executing a sandbox-reachable service on the television; automatically announcing, through the television, the sandbox-reachable service to a discovery module executing at least one of: on a pairing server external to the mobile device and as part of an extension of the security sandbox executing on the mobile device; identifying the sandbox-reachable service offered through the television based on receiving, through the discovery module, the automatic announcement to enable the sandboxed application of the mobile device reach the sandbox-reachable service by communicating an identification data of the television via the sandbox-reachable service when a shared computer network is determined to be commonly associated with the mobile device and the television; and establishing bidirectional communication between the mobile device and the television based on the sandboxed application reaching the sandbox-reachable service to render the primary data available across the sandbox-reachable service and the sandboxed application; processing an embedded object within the sandboxed application; and executing the embedded object through the sandboxed application to cause rendering of the targeted data therethrough. | 9. A method comprising: generating a fingerprint data using a television, wherein the fingerprint data is any one of an audio fingerprint data and a video fingerprint data; matching primary data generated from the fingerprint data with targeted data based on a relevancy factor using a relevancy-matching server; looking in a data repository for at least one of the targeted data, a reference to the targeted data and a metadata of the targeted data using the relevancy-matching server, wherein the primary data is any one of a content identification data and a content identification history; constraining an executable environment in a security sandbox of a mobile device; executing a sandboxed application in the executable environment of the mobile device; associating the mobile device with the television based on: executing a sandbox-reachable service on the television; automatically announcing, through the television, the sandbox-reachable service to a discovery module executing at least one of: on a pairing server external to the mobile device and as part of an extension of the security sandbox executing on the mobile device; identifying the sandbox-reachable service offered through the television based on receiving, through the discovery module, the automatic announcement to enable the sandboxed application of the mobile device reach the sandbox-reachable service by communicating an identification data of the television via the sandbox-reachable service when a shared computer network is determined to be commonly associated with the mobile device and the television; and establishing bidirectional communication between the mobile device and the television based on the sandboxed application reaching the sandbox-reachable service to render the primary data available across the sandbox-reachable service and the sandboxed application; processing an embedded object within the sandboxed application; and executing the embedded object through the sandboxed application to cause rendering of the targeted data therethrough. 13. The method of claim 9 , further comprising: processing the fingerprint data from the television using a content identification server; and communicating the primary data from the fingerprint data to any of a number of devices with an access to at least one of: the identification data of the television and an identification data of an automatic content identification service of the television. | 0.598592 |
9,639,602 | 1 | 13 | 1. A system for providing an automated response to a user natural language query (NLQ) made in regard to a subject, said system comprising: a computing platform including communication circuitry, processing circuitry and computer executable code adapted to cause the computing platform to: (a) receive digital data representing the user NLQ; (b) assign a weight value to words in the NLQ, wherein a weight value assigned to a given word of the NLQ is inversely related to a rate of occurrence of the given word in at least one knowledgebase; (c) calculate a query specific significance value for one or more of the words in the NLQ, wherein the query specific significance value for a given word is a ratio between the weight value of the given word and a sum of weight values of a set of other words in the NLQ, such that a query specific significance value of any selected word in any selected NLQ is inversely related to a sum of weight values of words, other than the selected word, in the selected NLQ; (d) search the at least one knowledgebase for one or more candidate matches, which candidate matches include words corresponding to words in the user NLQ; and (e) score matches between the NLQ and the one or more match candidates by performing a mathematical operation using the query significance value of words in the NLQ and the query significance value of corresponding words in the one or more match candidates; (f) compare a context in which the NLQ was submitted to contexts associated with one or more of the one or more match candidates, wherein a context of a NLQ is a parameter relating to the NLQ other than the text of the NLQ. | 1. A system for providing an automated response to a user natural language query (NLQ) made in regard to a subject, said system comprising: a computing platform including communication circuitry, processing circuitry and computer executable code adapted to cause the computing platform to: (a) receive digital data representing the user NLQ; (b) assign a weight value to words in the NLQ, wherein a weight value assigned to a given word of the NLQ is inversely related to a rate of occurrence of the given word in at least one knowledgebase; (c) calculate a query specific significance value for one or more of the words in the NLQ, wherein the query specific significance value for a given word is a ratio between the weight value of the given word and a sum of weight values of a set of other words in the NLQ, such that a query specific significance value of any selected word in any selected NLQ is inversely related to a sum of weight values of words, other than the selected word, in the selected NLQ; (d) search the at least one knowledgebase for one or more candidate matches, which candidate matches include words corresponding to words in the user NLQ; and (e) score matches between the NLQ and the one or more match candidates by performing a mathematical operation using the query significance value of words in the NLQ and the query significance value of corresponding words in the one or more match candidates; (f) compare a context in which the NLQ was submitted to contexts associated with one or more of the one or more match candidates, wherein a context of a NLQ is a parameter relating to the NLQ other than the text of the NLQ. 13. The system according to claim 1 , wherein a context of the NLQ derived from text of the NLQ is treated differently than a context of the NLQ derived from a computational environment in which the NLQ was submitted. | 0.841837 |
8,379,085 | 2 | 3 | 2. The computer-implemented method of claim 1 , wherein identifying one or more segments in the first sequence, comprises: evaluating the subsequences in the first sequence using a sliding window of length (L), wherein an internal entropy expert and a boundary entropy expert each vote a position in each sliding window subsequence at which to split the sliding window sequence; and inducing a segment boundary at each position in the first sequence that receives at least a number of votes satisfying a vote count threshold (V). | 2. The computer-implemented method of claim 1 , wherein identifying one or more segments in the first sequence, comprises: evaluating the subsequences in the first sequence using a sliding window of length (L), wherein an internal entropy expert and a boundary entropy expert each vote a position in each sliding window subsequence at which to split the sliding window sequence; and inducing a segment boundary at each position in the first sequence that receives at least a number of votes satisfying a vote count threshold (V). 3. The computer-implemented method of claim 2 , wherein: the internal entropy expert votes to minimize internal entropy by selecting a position which minimizes internal entropy in each respective sliding window sequence, based on the determined entropies; and the boundary entropy expert votes by selecting a position in each respective sliding window that maximizes entropy between segments in the sliding window subsequence. | 0.557173 |
9,658,988 | 9 | 10 | 9. The method of claim 1 , wherein the client computer receives the block of text from a server. | 9. The method of claim 1 , wherein the client computer receives the block of text from a server. 10. The method of claim 9 , wherein the server provides the client computer with a layout engine configured to define the plurality of regular expressions, segment the block of text, and construct the layout. | 0.5 |
9,747,646 | 1 | 6 | 1. A method comprising: analyzing, by a browser plug-in and during an initial loading of a structured document at a client device associated with a user, one or more elements of an object model representation of the structured document to identify one or more objects from a plurality of objects embedded within the structured document, wherein each of the plurality of objects comprises content and the structured document is a markup-language document that originates from a source external to a social-networking system and is displayable as a webpage; modifying, during the initial loading of the structured document at the client device, the object model representation of the structured document to display one or more controls, associated with the social-networking system, proximal to one or more of the one or more identified objects in the webpage from the source external to the social-networking system; detecting an interaction by the user with one of the one or more controls, in the webpage, associated with a particular one of the one or more identified objects; sending a message to the social-networking system, wherein the message comprises: (1) an identifier associated with the particular identified object and an identifier associated with the user, (2) instructions to augment a social graph associated with the social-networking system, the augmenting comprising adding an edge between a user node associated with the user and a node associated with the particular identified object, and (3) an indication that the user has been authenticated by the social-networking system; and receiving a response from the social-networking system indicating that the edge has been added to the social graph; and modifying the one of the one or more controls to indicate an association between the user and the particular identified object. | 1. A method comprising: analyzing, by a browser plug-in and during an initial loading of a structured document at a client device associated with a user, one or more elements of an object model representation of the structured document to identify one or more objects from a plurality of objects embedded within the structured document, wherein each of the plurality of objects comprises content and the structured document is a markup-language document that originates from a source external to a social-networking system and is displayable as a webpage; modifying, during the initial loading of the structured document at the client device, the object model representation of the structured document to display one or more controls, associated with the social-networking system, proximal to one or more of the one or more identified objects in the webpage from the source external to the social-networking system; detecting an interaction by the user with one of the one or more controls, in the webpage, associated with a particular one of the one or more identified objects; sending a message to the social-networking system, wherein the message comprises: (1) an identifier associated with the particular identified object and an identifier associated with the user, (2) instructions to augment a social graph associated with the social-networking system, the augmenting comprising adding an edge between a user node associated with the user and a node associated with the particular identified object, and (3) an indication that the user has been authenticated by the social-networking system; and receiving a response from the social-networking system indicating that the edge has been added to the social graph; and modifying the one of the one or more controls to indicate an association between the user and the particular identified object. 6. The method of claim 1 , wherein one or more of the interactions comprise one or more of: the user watching or viewing the object; the user liking or disliking the object; the user wanting product associated with the object; the user listening to the object; the user reading the object; or the user commenting on the object. | 0.5 |
7,912,848 | 1 | 3 | 1. A method of managing a statement pool, the method comprising: identifying, from among a plurality of statements in a statement pool utilized by a database, a statement that requests data in a first format from a field in the database that stores the data in a second format; and modifying the identified statement in the statement pool using at least one processor to instruct the database to convert the data to the first format prior to returning the data; and tracking usage of at least a subset of the plurality of statements, wherein the modifying the identified statement is performed based upon the tracked usage, wherein the tracking usage includes tracking at least one of a number of times and a last time that each of the subset of statements is used. | 1. A method of managing a statement pool, the method comprising: identifying, from among a plurality of statements in a statement pool utilized by a database, a statement that requests data in a first format from a field in the database that stores the data in a second format; and modifying the identified statement in the statement pool using at least one processor to instruct the database to convert the data to the first format prior to returning the data; and tracking usage of at least a subset of the plurality of statements, wherein the modifying the identified statement is performed based upon the tracked usage, wherein the tracking usage includes tracking at least one of a number of times and a last time that each of the subset of statements is used. 3. The method of claim 1 , further comprising associating with the identified statement a statement signature, the method further comprising accessing the modified statement in response to a user request to access a statement having a statement signature corresponding to the identified statement. | 0.511513 |
8,874,541 | 6 | 7 | 6. The computer-implemented method of claim 1 , wherein the method further comprises presenting, to the business, an option to publish the selected at least one search keyword on the online information resource by at least one of including the selected at least one search keyword as part of the content of the online information resource that can be viewed by visitors, and incorporating the selected at least one search keyword as part of HTML metadata of the online information resource. | 6. The computer-implemented method of claim 1 , wherein the method further comprises presenting, to the business, an option to publish the selected at least one search keyword on the online information resource by at least one of including the selected at least one search keyword as part of the content of the online information resource that can be viewed by visitors, and incorporating the selected at least one search keyword as part of HTML metadata of the online information resource. 7. The computer-implemented method of claim 6 , wherein the method further comprises receiving, from the business, a selection of the option to publish the selected at least one search keyword on the online information resource. | 0.5 |
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