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8,132,182 | 9 | 10 | 9. A method according to claim 8 and further comprising determining whether any of said values that are associated with any of said triggers meet a condition of said trigger. | 9. A method according to claim 8 and further comprising determining whether any of said values that are associated with any of said triggers meet a condition of said trigger. 10. A method according to claim 9 and further comprising composing a notification if said condition is met. | 0.5 |
9,218,815 | 3 | 6 | 3. The method of claim 1 , wherein the recording of the audio and the video yields a dynamic image feature. | 3. The method of claim 1 , wherein the recording of the audio and the video yields a dynamic image feature. 6. The method of claim 3 , wherein the dynamic image feature relates to one of phonetic content of the user speaking the text challenge, speech prosody, a facial expression of the user in response to content of the text challenge, and a non-facial physically manifested response. | 0.5 |
8,965,126 | 2 | 10 | 2. The character recognition device according to claim 1 , wherein the circuitry is further configured to: receive a keyword from a user as an input and create second character string transition data being character string transition data of the keyword, and determine whether the keyword is present in the image by performing a composition operation of the first character string transition data and the second character string transition data. | 2. The character recognition device according to claim 1 , wherein the circuitry is further configured to: receive a keyword from a user as an input and create second character string transition data being character string transition data of the keyword, and determine whether the keyword is present in the image by performing a composition operation of the first character string transition data and the second character string transition data. 10. The character recognition device according to claim 2 , further comprising: a word database that contains category information for words, wherein the circuitry is further configured to create creates the second character string transition data with the category information added, and output the results with the category information added. | 0.5 |
9,959,324 | 9 | 11 | 9. The computer system of claim 8 , further comprising: clustering a plurality of common relationship clauses according to a plurality of linkages that link a plurality of data sources together; and storing the plurality of common relationship clauses and the plurality of linkages. | 9. The computer system of claim 8 , further comprising: clustering a plurality of common relationship clauses according to a plurality of linkages that link a plurality of data sources together; and storing the plurality of common relationship clauses and the plurality of linkages. 11. The computer system of claim 9 , further comprising: proposing a list comprising the clustered common relationship clauses to a user for validation; and providing a search capability to retrieve at least one probable relationship between at least one of a plurality of data elements, a plurality of business terms, and a plurality of data elements and a plurality of business terms. | 0.5 |
9,465,985 | 1 | 5 | 1. A non-transitory computer-readable media comprising instructions stored thereon, the instructions, when executed by one or more processors, cause the processors to perform operations comprising: receiving a first handwriting input from a user, the first handwriting input comprising a plurality of handwritten strokes distributed along a respective writing direction associated with a handwriting input area of a handwriting input interface; rendering each of the plurality of handwritten strokes in the handwriting input area as the handwritten stroke is provided by the user; starting a respective fading process for the plurality of handwritten strokes of the first handwriting input, wherein during the respective fading process, the rendering of the plurality of handwritten strokes in the handwriting input area becomes increasingly faded; receiving a second handwriting input from the user over a region of the handwriting input area occupied by a faded plurality of handwritten strokes of the first handwriting input; and in response to receiving the second handwriting input: rendering the second handwriting input in the handwriting input area; and clearing all the faded plurality of handwritten strokes of the first handwriting input from the handwriting input area. | 1. A non-transitory computer-readable media comprising instructions stored thereon, the instructions, when executed by one or more processors, cause the processors to perform operations comprising: receiving a first handwriting input from a user, the first handwriting input comprising a plurality of handwritten strokes distributed along a respective writing direction associated with a handwriting input area of a handwriting input interface; rendering each of the plurality of handwritten strokes in the handwriting input area as the handwritten stroke is provided by the user; starting a respective fading process for the plurality of handwritten strokes of the first handwriting input, wherein during the respective fading process, the rendering of the plurality of handwritten strokes in the handwriting input area becomes increasingly faded; receiving a second handwriting input from the user over a region of the handwriting input area occupied by a faded plurality of handwritten strokes of the first handwriting input; and in response to receiving the second handwriting input: rendering the second handwriting input in the handwriting input area; and clearing all the faded plurality of handwritten strokes of the first handwriting input from the handwriting input area. 5. The media of claim 1 , wherein the respective fading process for each recognition unit is started when the user has started inputting the strokes for a next recognition unit after the recognition unit. | 0.862162 |
7,853,601 | 1 | 3 | 1. A method for associating an advertisement with at least one content on Internet, the method comprising: gathering one or more feeds associated with at least one content from a plurality of content; categorizing the at least one content into at least one general web-based category, the at least one general web-based category belonging to a set of general web-based categories, wherein the at least one content is categorized based on the one or more feeds associated with the at least one content; translating the set of general web-based categories to a set of pre-defined categories, wherein one or more general web-based categories from the set of general web-based categories are translated to a pre-defined category in the set of pre-defined categories; associating the advertisement with the at least one content in one or more pre-defined categories from the set of pre-defined categories based on at least one predetermined criterion; and wherein the categorizing step comprises providing a relevance percentage corresponding to the at least one content categorized into each of the at least one general web-based category. | 1. A method for associating an advertisement with at least one content on Internet, the method comprising: gathering one or more feeds associated with at least one content from a plurality of content; categorizing the at least one content into at least one general web-based category, the at least one general web-based category belonging to a set of general web-based categories, wherein the at least one content is categorized based on the one or more feeds associated with the at least one content; translating the set of general web-based categories to a set of pre-defined categories, wherein one or more general web-based categories from the set of general web-based categories are translated to a pre-defined category in the set of pre-defined categories; associating the advertisement with the at least one content in one or more pre-defined categories from the set of pre-defined categories based on at least one predetermined criterion; and wherein the categorizing step comprises providing a relevance percentage corresponding to the at least one content categorized into each of the at least one general web-based category. 3. The method of claim 1 , wherein the at least one predetermined criterion comprises at least one of: a relevance percentage corresponding to a plurality of content categorized into the set of pre-defined categories; an amount of content categorized in each pre-defined category in the set of pre-defined categories; and a demographic data corresponding to a plurality of users viewing a plurality of contents in the set of pre-defined categories. | 0.5 |
7,797,265 | 1 | 4 | 1. A method of clustering a plurality of documents from a data stream comprising: generating a feature vector for a document in the plurality of documents; applying a locality sensitive hashing function to the feature vector; retrieving a set of cluster centroids based on a result of the applied locality sensitive hashing function of the feature vector; determining a distance between the feature vector of the document and each of the cluster centroids; and assigning the document to a cluster based on the determined distances. | 1. A method of clustering a plurality of documents from a data stream comprising: generating a feature vector for a document in the plurality of documents; applying a locality sensitive hashing function to the feature vector; retrieving a set of cluster centroids based on a result of the applied locality sensitive hashing function of the feature vector; determining a distance between the feature vector of the document and each of the cluster centroids; and assigning the document to a cluster based on the determined distances. 4. The method of claim 1 wherein retrieving a set of cluster centroids based on a result of the applied locality sensitive hashing function of the feature vector further comprises: selecting a group of cluster centroids based on a size of clusters associated with the cluster centroids. | 0.757627 |
9,171,083 | 1 | 3 | 1. A computer implemented method for keeping and finding information, comprising: a textual search engine, responsive to a user query comprising a search term, using a semantic vector to promote any of documents and sites that contain other, closely related terms that strongly correlate with said search term, wherein a semantic vector of a term comprises a global frequency of said other, closely related terms within a corpus that is used to compute said semantic vector relative to said search term; a processor generating a social graph for said user in which connections for said user comprise hyper-dimensional relationships based on semantic vectors that link said search term with a collection of said other, closely related terms; said processor applying a personalized semantic vector for said user to said social graph, wherein said personalized semantic vector comprises a subset of said corpus that is personal to said user, said processor determining said personalized semantic vector by taking into account only documents and sites that said user has strong engagement with, and by which said user's personal semantics are determined when related to a specific term; and an expert network applying said user's personalized semantic vector to locate experts in said user's social graph based on a user query topic: wherein said expert network comprises a network between individuals that describes how they are related to each other in terms of expertise; wherein said expert network identifies said user's intent and identifies experts for said term among said user's connections; and wherein when a connection is considered an expert for said user, documents and sites that said connection kept are recommended to said user. | 1. A computer implemented method for keeping and finding information, comprising: a textual search engine, responsive to a user query comprising a search term, using a semantic vector to promote any of documents and sites that contain other, closely related terms that strongly correlate with said search term, wherein a semantic vector of a term comprises a global frequency of said other, closely related terms within a corpus that is used to compute said semantic vector relative to said search term; a processor generating a social graph for said user in which connections for said user comprise hyper-dimensional relationships based on semantic vectors that link said search term with a collection of said other, closely related terms; said processor applying a personalized semantic vector for said user to said social graph, wherein said personalized semantic vector comprises a subset of said corpus that is personal to said user, said processor determining said personalized semantic vector by taking into account only documents and sites that said user has strong engagement with, and by which said user's personal semantics are determined when related to a specific term; and an expert network applying said user's personalized semantic vector to locate experts in said user's social graph based on a user query topic: wherein said expert network comprises a network between individuals that describes how they are related to each other in terms of expertise; wherein said expert network identifies said user's intent and identifies experts for said term among said user's connections; and wherein when a connection is considered an expert for said user, documents and sites that said connection kept are recommended to said user. 3. The method of claim 1 , further comprising: said expert network cross analyzing relationships between said user and said user's peers to identify an expert among said peers. | 0.826772 |
8,971,630 | 12 | 13 | 12. A device for detecting the boundaries of characters in an electronic image, the electronic image including representations of characters, the device comprising: a processor; and a memory configured with processor-executable instructions which, when executed by the processor, implement a method, the method comprising: identifying a line of glyph-based character representations in the electronic image; isolating a plurality of glyph-based character representations; loading a set of character patterns into the memory; loading the plurality of glyph-based character representations into the cache; and recognizing the plurality of glyph-based character representations with the set of character patterns while one or more of the plurality of glyph-based character representations are in the cache. | 12. A device for detecting the boundaries of characters in an electronic image, the electronic image including representations of characters, the device comprising: a processor; and a memory configured with processor-executable instructions which, when executed by the processor, implement a method, the method comprising: identifying a line of glyph-based character representations in the electronic image; isolating a plurality of glyph-based character representations; loading a set of character patterns into the memory; loading the plurality of glyph-based character representations into the cache; and recognizing the plurality of glyph-based character representations with the set of character patterns while one or more of the plurality of glyph-based character representations are in the cache. 13. The device of claim 12 , wherein isolating the first plurality of glyph-based character representations includes: detecting character gaps in the line of glyph-based character representations; creating a histogram of distances for the detected character gaps; and constructing a linear division graph (LDG) according to the detected character gaps by performing steps including: isolating values substantially near maxima values in the histogram of distances, wherein the isolated values are associated with respective detected character gaps; creating arcs for each detected character gap; assigning a penalty to the arcs; creating paths associated with the LDG; calculating aggregate penalties for each path associated with the LDG based on the penalties assigned to the arcs; and selecting a desired path from among the paths associated with the LDG based on the aggregate penalties associated with the paths. | 0.5 |
8,010,345 | 8 | 12 | 8. A method of providing content to a speech enabled device along with associated speech recognition data comprising: receiving, at a computing device comprising hardware and software, a request for a content item from a remotely located speech enabled device; the computing device determining an identifier for the content item; identifying speech recognition data representing a recognition grammar entry for the identifier; the computing device dynamically creating speech recognition data for the identifier if no speech recognition data is identified; and the computing device conveying the content item and the identified or dynamically created speech recognition data to the speech enabled device. | 8. A method of providing content to a speech enabled device along with associated speech recognition data comprising: receiving, at a computing device comprising hardware and software, a request for a content item from a remotely located speech enabled device; the computing device determining an identifier for the content item; identifying speech recognition data representing a recognition grammar entry for the identifier; the computing device dynamically creating speech recognition data for the identifier if no speech recognition data is identified; and the computing device conveying the content item and the identified or dynamically created speech recognition data to the speech enabled device. 12. The method of claim 8 , further comprising: the computing device identifying a set of device specific parameters for the speech enabled device; and the computing device formatting the speech recognition data in accordance with a speech grammar specification standard compatible with the device specific parameters. | 0.649007 |
10,162,852 | 11 | 12 | 11. A computer program product, comprising: a computer readable storage medium having program code embodied therewith, the program code executable by a processor to implement: receiving, from a user via a user interface, a task specification in natural language form; parsing, by the processor, the task specification into a plurality of components by performing a grammatical analysis to identify the plurality of components and relationships among the plurality of components, wherein the plurality of components comprise a primary term, a verb, a subject, and a modifier; creating, by the processor, a search query from the plurality of components and the relationships among the plurality of components, wherein the search query comprises selectable options for determining the relationships; searching, by the processor and using the search query, a database for an existing concept having a pattern that approximates at least a portion of the plurality of components, the concept including semantic meanings that are representable by textual patterns; identifying, by the processor, any components of the plurality of components that are not included in the existing concept; building, by the processor, a new concept that combines the existing concept and the components of the plurality of components that are not included in the existing concept; and displaying, via the user interface, the new concept in natural language form, decomposed components of the new concept, and corresponding relationships between the new concept and the decomposed components of the new concept, wherein the corresponding relationships are displayed through a connective line between the new concept and the decomposed components of the new concept. | 11. A computer program product, comprising: a computer readable storage medium having program code embodied therewith, the program code executable by a processor to implement: receiving, from a user via a user interface, a task specification in natural language form; parsing, by the processor, the task specification into a plurality of components by performing a grammatical analysis to identify the plurality of components and relationships among the plurality of components, wherein the plurality of components comprise a primary term, a verb, a subject, and a modifier; creating, by the processor, a search query from the plurality of components and the relationships among the plurality of components, wherein the search query comprises selectable options for determining the relationships; searching, by the processor and using the search query, a database for an existing concept having a pattern that approximates at least a portion of the plurality of components, the concept including semantic meanings that are representable by textual patterns; identifying, by the processor, any components of the plurality of components that are not included in the existing concept; building, by the processor, a new concept that combines the existing concept and the components of the plurality of components that are not included in the existing concept; and displaying, via the user interface, the new concept in natural language form, decomposed components of the new concept, and corresponding relationships between the new concept and the decomposed components of the new concept, wherein the corresponding relationships are displayed through a connective line between the new concept and the decomposed components of the new concept. 12. The computer program product of claim 11 , wherein the program code executable by the computer further implements displaying, via the user interface: the existing concept in natural language form, decomposed components of the existing concept, and corresponding relationships; and a relationship between the existing concept and the new concept. | 0.5 |
7,783,640 | 1 | 2 | 1. A machine-readable medium having stored thereon machine-executable instructions that when executed by a machine cause the machine to perform a method, the method comprising: computing a term score for a member of a set of terms in a document to be summarized, where the term score is computed according to:
S ( t )=( a−b ( sf t /N−c ) 2 )* f ( ng ) S(t) being the term score; a, b, and c being pre-determined, configurable constants; sf t being the number of sentences in which term t occurs; N being the total number of sentences; and f(ng) being a function that returns a penalizing value for terms having a single uni-gram, a linearly increasing value for terms having two to four uni-grams, and a constant value for terms having more than four uni-grams; computing a sentence score for a member of a set of sentences in the document; computing a set of entries for a term-sentence matrix that relates members of the set of terms to members of the set of sentences, a sentence containing one or more terms, a term appearing in one or more sentences; computing a dominant topic for the document by computing a term eigenvector, where a member of the term eigenvector represents a relevancy of a term to the dominant topic, and by computing a sentence eigenvector, where a member of the sentence eigenvector represents a relevancy of a sentence to the dominant topic; simultaneously ranking the set of terms and the set of sentences based, at least in part, on the dominant topic; and providing a summarization item selected from one or more of, the set of terms, and the set of sentences, the summarization item being selected based, at least in part, on one or more of, a ranking of the set of terms, and a ranking of the set of sentences, where the term score and sentence score are computed in parallel while computing the set of entries for the term-sentence matrix. | 1. A machine-readable medium having stored thereon machine-executable instructions that when executed by a machine cause the machine to perform a method, the method comprising: computing a term score for a member of a set of terms in a document to be summarized, where the term score is computed according to:
S ( t )=( a−b ( sf t /N−c ) 2 )* f ( ng ) S(t) being the term score; a, b, and c being pre-determined, configurable constants; sf t being the number of sentences in which term t occurs; N being the total number of sentences; and f(ng) being a function that returns a penalizing value for terms having a single uni-gram, a linearly increasing value for terms having two to four uni-grams, and a constant value for terms having more than four uni-grams; computing a sentence score for a member of a set of sentences in the document; computing a set of entries for a term-sentence matrix that relates members of the set of terms to members of the set of sentences, a sentence containing one or more terms, a term appearing in one or more sentences; computing a dominant topic for the document by computing a term eigenvector, where a member of the term eigenvector represents a relevancy of a term to the dominant topic, and by computing a sentence eigenvector, where a member of the sentence eigenvector represents a relevancy of a sentence to the dominant topic; simultaneously ranking the set of terms and the set of sentences based, at least in part, on the dominant topic; and providing a summarization item selected from one or more of, the set of terms, and the set of sentences, the summarization item being selected based, at least in part, on one or more of, a ranking of the set of terms, and a ranking of the set of sentences, where the term score and sentence score are computed in parallel while computing the set of entries for the term-sentence matrix. 2. The machine-readable medium of claim 1 , a term score for a term depending, at least in part, on a number of uni-grams in the term and a number of sentences in which the term appears. | 0.868085 |
8,554,800 | 13 | 20 | 13. A data management system, the system comprising: an input interface for acquiring a source document; and a processor configured to: (a) divide the source document into multiple objects in response to content of the source document; the multiple objects comprise sections and fragments, each section comprises a plurality of fragments; (b) analyze the multiple objects to generate multiple low level sub-trees, wherein each of the low level sub-trees is associated with a unique section of the source document and comprises a link to each one of the low level sub-tree that are associated with the plurality of the fragments of the unique section; (c) generate multiple mid- level sub-trees, wherein each of the mid- level sub-trees comprises link to at least one of the low level sub-trees; (d) generate a top level sub-tree that comprises multiple section links, wherein each of the section links links to one of the mid-level sub-trees; (e) create metadata descriptive of at least one of the sub-trees generated, wherein the metadata comprises data which is not comprised in the source document; and (f) generate a structured document that comprises the top level sub-tree, at least some of the mid-level sub-trees and at least some of the low level sub-trees, and the metadata; wherein a generation of the structured document comprises writing the structured document to a tangible memory; wherein the processor is further adapted to: retrieve one of the objects, wherein a retrieval of one of the object comprises acquiring from the to level sub-tree a link to a mid-level sub-tree, acquiring from the mid-level sub-tree a link to a low level sub-tree and retrieving the object from the low level sub-tree; and create an event handler for a sub-tree wherein the event handler is included in the sub-tree; wherein the system comprises an event manager, configured to carry out an action which is indicated in an event handler that is stored in one of the generated sub-trees, if an event that is indicated in the event handler occurred. | 13. A data management system, the system comprising: an input interface for acquiring a source document; and a processor configured to: (a) divide the source document into multiple objects in response to content of the source document; the multiple objects comprise sections and fragments, each section comprises a plurality of fragments; (b) analyze the multiple objects to generate multiple low level sub-trees, wherein each of the low level sub-trees is associated with a unique section of the source document and comprises a link to each one of the low level sub-tree that are associated with the plurality of the fragments of the unique section; (c) generate multiple mid- level sub-trees, wherein each of the mid- level sub-trees comprises link to at least one of the low level sub-trees; (d) generate a top level sub-tree that comprises multiple section links, wherein each of the section links links to one of the mid-level sub-trees; (e) create metadata descriptive of at least one of the sub-trees generated, wherein the metadata comprises data which is not comprised in the source document; and (f) generate a structured document that comprises the top level sub-tree, at least some of the mid-level sub-trees and at least some of the low level sub-trees, and the metadata; wherein a generation of the structured document comprises writing the structured document to a tangible memory; wherein the processor is further adapted to: retrieve one of the objects, wherein a retrieval of one of the object comprises acquiring from the to level sub-tree a link to a mid-level sub-tree, acquiring from the mid-level sub-tree a link to a low level sub-tree and retrieving the object from the low level sub-tree; and create an event handler for a sub-tree wherein the event handler is included in the sub-tree; wherein the system comprises an event manager, configured to carry out an action which is indicated in an event handler that is stored in one of the generated sub-trees, if an event that is indicated in the event handler occurred. 20. The system according to claim 13 , comprising an updating module configured to update a sub-tree selected from a group consisting of the low level sub-trees and the mid-level sub-trees, and to update at least one sub-tree that links to the updated sub-tree, to comprise links to the updated version of the sub-tree, and to an old version of the sub-tree. | 0.634694 |
7,617,492 | 28 | 30 | 28. A computer readable storage medium comprising computer-executable instructions for: receiving an option list of allowable options for an application, the option list comprising a first option, wherein the list of allowable options comprises, for each allowable option, a command line option string, a minimum number of characters that uniquely identify the command line option, a command line option identifier and a parameter having a value indicative of a type of allowable arguments for the command line option string; receiving a command line for the application, the received command line comprising a second option; parsing the received command line to determine if the second option matches the first option of the option list, wherein a success result is returned when it is determined that the first command line option in the command line exactly matches a portion of an option name in the list, a number of characters in the first command line option in the command line being not less than a minimum number of characters of the portion of the option name in the list of allowable options. | 28. A computer readable storage medium comprising computer-executable instructions for: receiving an option list of allowable options for an application, the option list comprising a first option, wherein the list of allowable options comprises, for each allowable option, a command line option string, a minimum number of characters that uniquely identify the command line option, a command line option identifier and a parameter having a value indicative of a type of allowable arguments for the command line option string; receiving a command line for the application, the received command line comprising a second option; parsing the received command line to determine if the second option matches the first option of the option list, wherein a success result is returned when it is determined that the first command line option in the command line exactly matches a portion of an option name in the list, a number of characters in the first command line option in the command line being not less than a minimum number of characters of the portion of the option name in the list of allowable options. 30. The computer readable storage medium of claim 28 , comprising further computer-executable instructions for: returning a failure result in response to determining that a minimum number of characters required to uniquely identify the first option is greater than a plurality of characters comprising a second option name. | 0.642699 |
8,732,097 | 1 | 2 | 1. A computer-implemented method, comprising: computing, by a computing device, a first set of activity probabilities based on contextual information for a first set of historical activities and an activity-prediction model for a target activity, wherein an activity probability indicates a likelihood that the target activity has occurred; comparing a first set of probability thresholds with the first set of activity probabilities to determine a prediction success rate for each probability threshold; computing a utility score for each probability threshold based on the prediction success rates and a utility function, wherein the utility function has the form:
U ( P th )= U 1 (TP)+ U 2 (FP)+ U 3 (FN)+ U 4 (TN); wherein P th is the threshold value used to determine whether a historical activity matches the target activity, wherein U 1 (TP) and U 4 (TN) compute a benefit of making a recommendation based on predicting a true positive and a true negative, respectively, and wherein U 2 (FP) and U 3 (FN) compute a cost of making a recommendation based on predicting a false positive and a false negative, respectively; selecting a first probability threshold whose utility score is greater than or equal to a baseline utility score and other utility scores of the first set of thresholds; and assigning the first probability threshold to the activity-prediction model. | 1. A computer-implemented method, comprising: computing, by a computing device, a first set of activity probabilities based on contextual information for a first set of historical activities and an activity-prediction model for a target activity, wherein an activity probability indicates a likelihood that the target activity has occurred; comparing a first set of probability thresholds with the first set of activity probabilities to determine a prediction success rate for each probability threshold; computing a utility score for each probability threshold based on the prediction success rates and a utility function, wherein the utility function has the form:
U ( P th )= U 1 (TP)+ U 2 (FP)+ U 3 (FN)+ U 4 (TN); wherein P th is the threshold value used to determine whether a historical activity matches the target activity, wherein U 1 (TP) and U 4 (TN) compute a benefit of making a recommendation based on predicting a true positive and a true negative, respectively, and wherein U 2 (FP) and U 3 (FN) compute a cost of making a recommendation based on predicting a false positive and a false negative, respectively; selecting a first probability threshold whose utility score is greater than or equal to a baseline utility score and other utility scores of the first set of thresholds; and assigning the first probability threshold to the activity-prediction model. 2. The method of claim 1 , wherein the prediction success rate includes at least one of: a number of true positive (TP) predictions; a number of true negative (TN) predictions; a number of false positive (FP) predictions; and a number of false negative (FN) predictions. | 0.823529 |
8,464,227 | 1 | 9 | 1. A supervisory process control and manufacturing information application development and execution system for supporting execution of scripts comprising computer-executable instructions stored on a non-transient computer-readable medium and a processor for executing the stored instructions, the system comprising: a script editor interface having a common script editor and at least one language specific editor, the script editor interface facilitating specifying scripts for a plurality of types of objects, and wherein the script editor interface supports multiple distinct user-side script languages, the script editor interface generating output including tags indicating a particular one of multiple distinct user-side script languages wherein the tags are applied to at least one of a particular instruction, a particular group of instructions, and an entire script; a script translation component including routines for rendering execution-side script of a single execution-side scripting language from source script rendered by the script editor and written according to any of a set of user-side script languages, the set of user-side script languages including at least: a first text-based scripting language, and a second graphical object-based scripting language, and a scripting engine for executing the execution-side script in a run-time environment during each scan cycle of a single execution-side scripting language generated by the script translation component for the first scripting language and the second scripting language. | 1. A supervisory process control and manufacturing information application development and execution system for supporting execution of scripts comprising computer-executable instructions stored on a non-transient computer-readable medium and a processor for executing the stored instructions, the system comprising: a script editor interface having a common script editor and at least one language specific editor, the script editor interface facilitating specifying scripts for a plurality of types of objects, and wherein the script editor interface supports multiple distinct user-side script languages, the script editor interface generating output including tags indicating a particular one of multiple distinct user-side script languages wherein the tags are applied to at least one of a particular instruction, a particular group of instructions, and an entire script; a script translation component including routines for rendering execution-side script of a single execution-side scripting language from source script rendered by the script editor and written according to any of a set of user-side script languages, the set of user-side script languages including at least: a first text-based scripting language, and a second graphical object-based scripting language, and a scripting engine for executing the execution-side script in a run-time environment during each scan cycle of a single execution-side scripting language generated by the script translation component for the first scripting language and the second scripting language. 9. The application development and execution system of claim 1 wherein the user-side scripts include a script language tag identifying the type of the user-side script language used to generate the source script. | 0.572581 |
8,966,478 | 17 | 19 | 17. A device according to claim 15 , wherein said programmable hardware component is programmed to execute the software application using the first VM. | 17. A device according to claim 15 , wherein said programmable hardware component is programmed to execute the software application using the first VM. 19. A device according to claim 17 , wherein said programmable hardware component is programmed based on an HDL description by which the software application is certified to be executed, and wherein the certification is applicable to execution of the software application by said programmable hardware component. | 0.54386 |
9,170,821 | 15 | 22 | 15. A method, comprising: receiving, via at least one of one or more computing devices, a test document associated with a workflow definition, the test document comprising a programmatic input source configured to provide an input for an action of the workflow definition and an expected state for the workflow definition based at least in part on the input; delivering, via at least one of the one or more computing devices, the input from the programmatic input source for the action of a workflow instance, the workflow instance being a first instance of the workflow definition executed by a workflow engine, and the action determined based at least in part upon a present state of the workflow instance, the input being determined upon execution of the action of the workflow instance; receiving, via at least one of the one or more computing devices, a next state of the workflow instance, the next state being determined by the workflow engine based at least in part upon the present state, the action, and the input; comparing, via at least one of the one or more computing devices, the next state of the workflow instance to the expected state specified by the test document; and restarting, via at least one of the one or more computing devices, the workflow instance at a beginning of the workflow instance in response to detecting a discrepancy between the next state of the workflow instance and the expected state specified by the test document in response to comparing the next state of the workflow instance to the expected state specified by the test document. | 15. A method, comprising: receiving, via at least one of one or more computing devices, a test document associated with a workflow definition, the test document comprising a programmatic input source configured to provide an input for an action of the workflow definition and an expected state for the workflow definition based at least in part on the input; delivering, via at least one of the one or more computing devices, the input from the programmatic input source for the action of a workflow instance, the workflow instance being a first instance of the workflow definition executed by a workflow engine, and the action determined based at least in part upon a present state of the workflow instance, the input being determined upon execution of the action of the workflow instance; receiving, via at least one of the one or more computing devices, a next state of the workflow instance, the next state being determined by the workflow engine based at least in part upon the present state, the action, and the input; comparing, via at least one of the one or more computing devices, the next state of the workflow instance to the expected state specified by the test document; and restarting, via at least one of the one or more computing devices, the workflow instance at a beginning of the workflow instance in response to detecting a discrepancy between the next state of the workflow instance and the expected state specified by the test document in response to comparing the next state of the workflow instance to the expected state specified by the test document. 22. The method of claim 15 , wherein the action is performed by a remote application, the remote application interfacing with the workflow instance and returning a result. | 0.667315 |
8,862,587 | 8 | 9 | 8. A device, comprising: a communication interface that receives a name of an individual person; a storage element that stores a plurality of names; and a processor that: receiving, for a name of a person and from a plurality of third parties, information indicating a name characteristic that people with the name of the person typically have; calculating a confidence value associated with the name characteristic as the percentage of the third parties that associated the name characteristic with the name; stores the name characteristic and the calculated confidence value in the storage element in association with each of the corresponding plurality of names; determines whether a received name of the individual person matches any of the stored names; and in response to determining that the received name matches a first of the stored names: identifies the name characteristic associated with the first stored name that matches the received name; determines one or more user characteristics of the person associated with the received name based on the identified name characteristic; and returns at least one of the determined one or more user characteristics. | 8. A device, comprising: a communication interface that receives a name of an individual person; a storage element that stores a plurality of names; and a processor that: receiving, for a name of a person and from a plurality of third parties, information indicating a name characteristic that people with the name of the person typically have; calculating a confidence value associated with the name characteristic as the percentage of the third parties that associated the name characteristic with the name; stores the name characteristic and the calculated confidence value in the storage element in association with each of the corresponding plurality of names; determines whether a received name of the individual person matches any of the stored names; and in response to determining that the received name matches a first of the stored names: identifies the name characteristic associated with the first stored name that matches the received name; determines one or more user characteristics of the person associated with the received name based on the identified name characteristic; and returns at least one of the determined one or more user characteristics. 9. The device of claim 8 , wherein the communication interface receives a request for information to be returned, the request for information identifying a particular user characteristic to be returned, and the processor communicates via the communication interface the particular user characteristic identified by the request for information and determined from the one or more name characteristics. | 0.5 |
9,449,095 | 10 | 11 | 10. A system comprising one or more computers and one or more storage devices storing instructions that, when executed by the one or more computers, cause the one or more computers to perform operations comprising: receiving a current search query submitted by a current user of a current user device to a search engine system; determining that the current search query is similar to a first previously submitted search query of a plurality of previously submitted search queries that have previously been submitted by the current user to the search engine system, wherein determining that the current search query is similar to the first previously submitted search query comprises determining that at least one first term from the current search query matches a corresponding term that appears in the first previously submitted search query; determining that a different second term satisfies the condition that: (i) the different second term appears in the first previously submitted search query that is similar to the current search query, (ii) the different second term does not appear in the current search query, and (iii) the different second term appears in at least a threshold number of other distinct search queries of the plurality of previously submitted search queries that have previously been submitted by the current user, wherein each other distinct search query is distinct from both the first previously submitted search query and the current search query; generating a revised search query by adding the different second term to the current search query; obtaining search results for the revised search query from a search engine; and providing the search results to the current user in a response to the current search query. | 10. A system comprising one or more computers and one or more storage devices storing instructions that, when executed by the one or more computers, cause the one or more computers to perform operations comprising: receiving a current search query submitted by a current user of a current user device to a search engine system; determining that the current search query is similar to a first previously submitted search query of a plurality of previously submitted search queries that have previously been submitted by the current user to the search engine system, wherein determining that the current search query is similar to the first previously submitted search query comprises determining that at least one first term from the current search query matches a corresponding term that appears in the first previously submitted search query; determining that a different second term satisfies the condition that: (i) the different second term appears in the first previously submitted search query that is similar to the current search query, (ii) the different second term does not appear in the current search query, and (iii) the different second term appears in at least a threshold number of other distinct search queries of the plurality of previously submitted search queries that have previously been submitted by the current user, wherein each other distinct search query is distinct from both the first previously submitted search query and the current search query; generating a revised search query by adding the different second term to the current search query; obtaining search results for the revised search query from a search engine; and providing the search results to the current user in a response to the current search query. 11. The system of claim 10 , wherein providing the search results to the current user in a response to the current search query comprises: providing the search results for the revised search query to the current user device as part of the response to the current search query. | 0.703863 |
8,361,117 | 6 | 7 | 6. The spinal cross connector of claim 1 , wherein, when the male member and the fastening element are disposed within the female member, the male and female members have first and second points of contact therebetween and the male member and the fastening element have one point of contact therebetween. | 6. The spinal cross connector of claim 1 , wherein, when the male member and the fastening element are disposed within the female member, the male and female members have first and second points of contact therebetween and the male member and the fastening element have one point of contact therebetween. 7. The spinal cross connector of claim 6 , wherein the first and second points of contact between the male and female members are spaced a distance apart from one another. | 0.724194 |
7,707,037 | 1 | 8 | 1. A method of monitoring a location having a plurality of audio sensors and video sensors, comprising: receiving auditory data from at least one of the plurality of audio sensors; comparing at least a first portion of the auditory data to a lexicon comprising a plurality of keywords to determine if there is a match to a first keyword from the lexicon; triggering a policy based on the keyword match; associating at least one video sensor with at least one audio sensor; selecting the at least one video sensor if a match is found; receiving video data from the at least one video sensor; and archiving the auditory data and the video data, wherein archiving the auditory data includes associating the auditory data with data indicating the triggered policy. | 1. A method of monitoring a location having a plurality of audio sensors and video sensors, comprising: receiving auditory data from at least one of the plurality of audio sensors; comparing at least a first portion of the auditory data to a lexicon comprising a plurality of keywords to determine if there is a match to a first keyword from the lexicon; triggering a policy based on the keyword match; associating at least one video sensor with at least one audio sensor; selecting the at least one video sensor if a match is found; receiving video data from the at least one video sensor; and archiving the auditory data and the video data, wherein archiving the auditory data includes associating the auditory data with data indicating the triggered policy. 8. The method as recited in claim 1 , further comprising comparing the first portion of the auditory data to the lexicon to determine if there is a match to a second keyword from the lexicon. | 0.543062 |
9,736,488 | 20 | 21 | 20. A computer system for transcoding a tile based video bitstream, the system comprising: a processor; and a non-transitory computer-readable storage medium storing computer program instructions, executed by the processor, the computer program instructions comprising instructions for: receiving a picture of an input video bitstream, the picture comprising a plurality of coding blocks partitioned into a plurality of tiles, each tile comprising tile rows of coding blocks; parsing the plurality of coding blocks of the picture in a tile scan order to produce a plurality of subsets of entropy coding state data, each subset of entropy coding state data associated with a corresponding tile row of coding blocks of each tile; generating a list of identified coding blocks in the tile scan order based on the parsing of the plurality of coding blocks, wherein the list of identified coding blocks includes a plurality of identifiers, each identifier associated with a corresponding first coding block of each tile row of coding blocks of each tile, each identifier indicating a position of the corresponding first coding block in the input video bitstream; storing the plurality of subsets of entropy coding state data and the list of identified coding blocks in a data repository, wherein each identifier of the list of identified coding locks is associated with a corresponding subset of entropy coding state data; parsing the same plurality of coding blocks of the picture in a raster scan order by using the list of identified coding blocks and the plurality of subsets of entropy coding state data stored in the data repository to produce a first portion of a parsed video bitstream, wherein the parsing the same plurality of coding blocks comprises: sorting the list of identified coding blocks into the raster scan order, wherein a sequence of tile rows in the raster scan order corresponds to a full row of coding blocks that spans the picture, and for each tile row in the full row of coding blocks that spans the picture: identifying a present identifier from the sorted list of identified coding blocks that corresponds to a present position in the input video bitstream, restoring a selected subset of entropy coding state data that corresponds to the present identifier, and decoding syntax elements of a set of coding blocks that correspond to a present tile row using the selected subset of entropy coding state data. | 20. A computer system for transcoding a tile based video bitstream, the system comprising: a processor; and a non-transitory computer-readable storage medium storing computer program instructions, executed by the processor, the computer program instructions comprising instructions for: receiving a picture of an input video bitstream, the picture comprising a plurality of coding blocks partitioned into a plurality of tiles, each tile comprising tile rows of coding blocks; parsing the plurality of coding blocks of the picture in a tile scan order to produce a plurality of subsets of entropy coding state data, each subset of entropy coding state data associated with a corresponding tile row of coding blocks of each tile; generating a list of identified coding blocks in the tile scan order based on the parsing of the plurality of coding blocks, wherein the list of identified coding blocks includes a plurality of identifiers, each identifier associated with a corresponding first coding block of each tile row of coding blocks of each tile, each identifier indicating a position of the corresponding first coding block in the input video bitstream; storing the plurality of subsets of entropy coding state data and the list of identified coding blocks in a data repository, wherein each identifier of the list of identified coding locks is associated with a corresponding subset of entropy coding state data; parsing the same plurality of coding blocks of the picture in a raster scan order by using the list of identified coding blocks and the plurality of subsets of entropy coding state data stored in the data repository to produce a first portion of a parsed video bitstream, wherein the parsing the same plurality of coding blocks comprises: sorting the list of identified coding blocks into the raster scan order, wherein a sequence of tile rows in the raster scan order corresponds to a full row of coding blocks that spans the picture, and for each tile row in the full row of coding blocks that spans the picture: identifying a present identifier from the sorted list of identified coding blocks that corresponds to a present position in the input video bitstream, restoring a selected subset of entropy coding state data that corresponds to the present identifier, and decoding syntax elements of a set of coding blocks that correspond to a present tile row using the selected subset of entropy coding state data. 21. The system of claim 20 , wherein the computer program instructions for parsing the plurality of coding blocks of the picture comprise computer program instructions for: identifying a subset of coding blocks from the plurality of coding blocks; and storing identifiers of the subset of coding blocks in the list of identified coding blocks, wherein the list of identified coding blocks is stored in the data repository. | 0.750885 |
6,076,060 | 12 | 18 | 12. The method of claim 1, wherein the step of providing a plurality of rule sets includes providing a suffix rule set, a prefix rule set and an infix rule set, the suffix rule set having text-to-phonemic data rules for ending portions of input text, the prefix rule set having text-to-phonemic data rules for beginning portions of the input text, and the infix rule set having text-to-phonemic data rules for intermediate portions of the input text; and wherein the step of applying the rules further comprises the steps of: iteratively comparing the input text to the rules in the suffix rule set to ultimately produce phonemic data ending portions based on ending portions of the input text and to produce a first remainder text excluding the ending portions of the input text; iteratively comparing the first remainder text to the rules in the prefix rule set to produce phonemic data beginning portions based on beginning portions of the first remainder text and to ultimately produce a second remainder text excluding the beginning portions of the first remainder text; iteratively comparing the second remainder text to the rules in the infix rule set to produce phonemic data middle portions based on intermediate portions of the input text; and such that the step of combining combines the phonemic data beginning portions, the phonemic data middle portions and the phonemic data ending portions to produce the phonemic data sequence which phonetically represents the input text. | 12. The method of claim 1, wherein the step of providing a plurality of rule sets includes providing a suffix rule set, a prefix rule set and an infix rule set, the suffix rule set having text-to-phonemic data rules for ending portions of input text, the prefix rule set having text-to-phonemic data rules for beginning portions of the input text, and the infix rule set having text-to-phonemic data rules for intermediate portions of the input text; and wherein the step of applying the rules further comprises the steps of: iteratively comparing the input text to the rules in the suffix rule set to ultimately produce phonemic data ending portions based on ending portions of the input text and to produce a first remainder text excluding the ending portions of the input text; iteratively comparing the first remainder text to the rules in the prefix rule set to produce phonemic data beginning portions based on beginning portions of the first remainder text and to ultimately produce a second remainder text excluding the beginning portions of the first remainder text; iteratively comparing the second remainder text to the rules in the infix rule set to produce phonemic data middle portions based on intermediate portions of the input text; and such that the step of combining combines the phonemic data beginning portions, the phonemic data middle portions and the phonemic data ending portions to produce the phonemic data sequence which phonetically represents the input text. 18. The method of claim 12, wherein the step of comparing the first remainder text to the prefix rule set compares the first remainder text beginning at a leftmost part of the first remainder text and compares in a left to right direction, with respect to the first remainder text, against each rule of the prefix rule set. | 0.76492 |
9,665,499 | 13 | 17 | 13. A computer system for facilitating memory access, said computer system comprising: a memory; and a processor in communications with the memory, wherein the computer system is configured to perform a method, said method comprising: providing a first partition within a system configuration, the first partition configured to support an operating system (OS) designed for a first address translation architecture, wherein configuration of the first partition to support the OS designed for the first address translation architecture is indicated in configuration information in a configuration data structure, and wherein the first partition is not configured to support an OS designed for a second address translation architecture; providing a second partition within the system configuration, the second partition configured to support the OS designed for the second address translation architecture, wherein configuration of the second partition to support the OS designed for the second address translation architecture is indicated in the configuration information in the configuration data structure, wherein the second partition is not configured to support the OS designed for the first address translation architecture, and wherein the first address translation architecture is structurally different from the second address translation architecture; based on obtaining, as part of an address translation request of the first partition or second partition, an address for translation, determining, based on the configuration information in the configuration data structure, an address translation architecture to use to translate the address; and translating the address via the determined address translation architecture. | 13. A computer system for facilitating memory access, said computer system comprising: a memory; and a processor in communications with the memory, wherein the computer system is configured to perform a method, said method comprising: providing a first partition within a system configuration, the first partition configured to support an operating system (OS) designed for a first address translation architecture, wherein configuration of the first partition to support the OS designed for the first address translation architecture is indicated in configuration information in a configuration data structure, and wherein the first partition is not configured to support an OS designed for a second address translation architecture; providing a second partition within the system configuration, the second partition configured to support the OS designed for the second address translation architecture, wherein configuration of the second partition to support the OS designed for the second address translation architecture is indicated in the configuration information in the configuration data structure, wherein the second partition is not configured to support the OS designed for the first address translation architecture, and wherein the first address translation architecture is structurally different from the second address translation architecture; based on obtaining, as part of an address translation request of the first partition or second partition, an address for translation, determining, based on the configuration information in the configuration data structure, an address translation architecture to use to translate the address; and translating the address via the determined address translation architecture. 17. The computer system of claim 13 , wherein the first partition and the second partition are supported by a single hypervisor. | 0.803681 |
9,798,768 | 1 | 9 | 1. A method comprising: displaying on a client computing device, via a graphical user interface provided by an application server, a graph comprising one or more graph nodes and one or more graph edges; receiving input from the client computing device via the graphical user interface indicating a selection of the graph, wherein each graph node of the one or more graph nodes represents a data object type, and wherein each graph edge of the one or more graph edges represents a data object link; receiving, via the graphical user interface, a selection of the one or more graph edges; displaying, via the graphical user interface, an interface element which enables input of a link strength value which represents a condition on a number of occurrences of a relationship between two or more graph nodes; receiving, via the interface element of the graphical user interface, input specifying a particular link strength value; based at least on the two or more graph nodes, the one or more graph edges, and the particular link strength value, the application server transforming the graph into a query template; wherein the query template represents one or more database queries which, when executed by the application server, returns a result set from a database, wherein each result in said result set includes a first data object, comprising one or more first data object properties and a first data object type, corresponding to a first corresponding data object type of the one or more graph nodes of the graph, and a second data object, comprising one or more second data object properties and a second data object type, corresponding to a second corresponding data object type of the two or more graph nodes of the graph, wherein the first data object and the second data object satisfy the condition on the number of occurrences of the relationship between the first data object and the second data object represented by the particular link strength value; wherein a data object represents a collection of information as part of a data object model. | 1. A method comprising: displaying on a client computing device, via a graphical user interface provided by an application server, a graph comprising one or more graph nodes and one or more graph edges; receiving input from the client computing device via the graphical user interface indicating a selection of the graph, wherein each graph node of the one or more graph nodes represents a data object type, and wherein each graph edge of the one or more graph edges represents a data object link; receiving, via the graphical user interface, a selection of the one or more graph edges; displaying, via the graphical user interface, an interface element which enables input of a link strength value which represents a condition on a number of occurrences of a relationship between two or more graph nodes; receiving, via the interface element of the graphical user interface, input specifying a particular link strength value; based at least on the two or more graph nodes, the one or more graph edges, and the particular link strength value, the application server transforming the graph into a query template; wherein the query template represents one or more database queries which, when executed by the application server, returns a result set from a database, wherein each result in said result set includes a first data object, comprising one or more first data object properties and a first data object type, corresponding to a first corresponding data object type of the one or more graph nodes of the graph, and a second data object, comprising one or more second data object properties and a second data object type, corresponding to a second corresponding data object type of the two or more graph nodes of the graph, wherein the first data object and the second data object satisfy the condition on the number of occurrences of the relationship between the first data object and the second data object represented by the particular link strength value; wherein a data object represents a collection of information as part of a data object model. 9. The method of claim 1 , wherein the graph includes one or more blank graph elements, wherein each of the one or more blank graph elements is associated with a value to be supplied by a user when the query template is executed. | 0.680168 |
9,747,306 | 30 | 37 | 30. An apparatus, comprising: at least one sensor; and a processor in communication with said sensor; wherein: said processor is adapted to define an actor input and a command associate with said actor input; said sensor is adapted to detect said actor input; said processor is adapted to execute said command in response to said input; said processor is adapted to identify at least one structural geometric salient feature of an actor from said actor input associated with said executed command; said processor is adapted to define a structural geometric actor model of said actor from said at least one structural geometric salient feature; said processor is adapted to retain a data set comprising at least one of said at least one structural geometric salient feature or said structural geometric actor model; and said processor is adapted to use said data set to identify subsequent actor inputs. | 30. An apparatus, comprising: at least one sensor; and a processor in communication with said sensor; wherein: said processor is adapted to define an actor input and a command associate with said actor input; said sensor is adapted to detect said actor input; said processor is adapted to execute said command in response to said input; said processor is adapted to identify at least one structural geometric salient feature of an actor from said actor input associated with said executed command; said processor is adapted to define a structural geometric actor model of said actor from said at least one structural geometric salient feature; said processor is adapted to retain a data set comprising at least one of said at least one structural geometric salient feature or said structural geometric actor model; and said processor is adapted to use said data set to identify subsequent actor inputs. 37. The apparatus of claim 30 , wherein: said actor comprises a stylus. | 0.94914 |
8,812,325 | 6 | 7 | 6. The method of claim 1 wherein receiving a confidence level further comprises: computing, for each of the launched programs, a confidence score indicative of an accuracy estimate of the program; and adjusting, for each of the launched programs, the computed confidence score for comparison consistency across each of the launched programs. | 6. The method of claim 1 wherein receiving a confidence level further comprises: computing, for each of the launched programs, a confidence score indicative of an accuracy estimate of the program; and adjusting, for each of the launched programs, the computed confidence score for comparison consistency across each of the launched programs. 7. The method of claim 6 Further comprising launching dissimilar speech recognition programs to instantiate the speech recognition processes. | 0.5 |
8,706,704 | 5 | 8 | 5. A method of creating a hyperlink together with an associated semantic link between selected text in a first, source document and related text in a second, target document, said source document including descriptive text, the method comprising the steps of: selecting text within the source document; selecting said target document; creating a hyperlink to navigate over the Internet from said selected text in the source document to said target document, wherein said hyperlink includes a URI identifying the target document; selecting a type of semantic link; and creating a semantic link of said type between said selected text in the source document and said target document to identify a specified semantic relationship between said selected text and said target entity, and including in said hyperlink a reference, different from said URI, for identifying said semantic relationship to facilitate using the hyperlink to identify and navigate to documents semantically related to said selected text; and using one or more processing units, executing a hyperlink program and a semantic link program, to perform the creating the hyperlink and the creating the semantic link; and wherein: the selecting said target document includes refining the selected text from the source document to form refined selected text, and putting the refined selected text into the target document; the hyperlink points from the selected text in the source document to the refined selected text in the target document; the source document has a source type and the target document has a target type; and the selecting the type of semantic link includes analyzing said source type and said target type, determining a plurality of candidate types of semantic links based on said analyzing said source type and said target type, and prompting a user to select from among the plurality of candidate types of semantic links, including selecting a word from the selected text, identifying a category for the word, consulting a metamodel to determine a type of relationship between the identified category and the selected text, and using the type of relationship determined from consulting the metamodel as the type of the semantic link between the selected text in the source document and the target document. | 5. A method of creating a hyperlink together with an associated semantic link between selected text in a first, source document and related text in a second, target document, said source document including descriptive text, the method comprising the steps of: selecting text within the source document; selecting said target document; creating a hyperlink to navigate over the Internet from said selected text in the source document to said target document, wherein said hyperlink includes a URI identifying the target document; selecting a type of semantic link; and creating a semantic link of said type between said selected text in the source document and said target document to identify a specified semantic relationship between said selected text and said target entity, and including in said hyperlink a reference, different from said URI, for identifying said semantic relationship to facilitate using the hyperlink to identify and navigate to documents semantically related to said selected text; and using one or more processing units, executing a hyperlink program and a semantic link program, to perform the creating the hyperlink and the creating the semantic link; and wherein: the selecting said target document includes refining the selected text from the source document to form refined selected text, and putting the refined selected text into the target document; the hyperlink points from the selected text in the source document to the refined selected text in the target document; the source document has a source type and the target document has a target type; and the selecting the type of semantic link includes analyzing said source type and said target type, determining a plurality of candidate types of semantic links based on said analyzing said source type and said target type, and prompting a user to select from among the plurality of candidate types of semantic links, including selecting a word from the selected text, identifying a category for the word, consulting a metamodel to determine a type of relationship between the identified category and the selected text, and using the type of relationship determined from consulting the metamodel as the type of the semantic link between the selected text in the source document and the target document. 8. The method according to claim 5 , wherein said reference to said semantic link describe a specific type of relationship in a given direction. | 0.854251 |
8,676,815 | 1 | 3 | 1. A system, comprising: at least one memory having stored therein computer executable instructions; and a processor, coupled to the at least one memory, configured to execute or facilitate execution of the computer executable instructions to at least: create a suffix tree document model that is a representation of a plurality of documents; convert the suffix tree document model into a vector document model that is a representation of a document of the plurality of documents to form the suffix tree document model converted into the vector document model, wherein the vector document model is a vector with M elements and M is a total number of nodes in the suffix tree document model; weight elements of the suffix tree document model converted into the vector document model; and determine a similarity between two or more weighted vector document models, each representing a respective document of the plurality of documents. | 1. A system, comprising: at least one memory having stored therein computer executable instructions; and a processor, coupled to the at least one memory, configured to execute or facilitate execution of the computer executable instructions to at least: create a suffix tree document model that is a representation of a plurality of documents; convert the suffix tree document model into a vector document model that is a representation of a document of the plurality of documents to form the suffix tree document model converted into the vector document model, wherein the vector document model is a vector with M elements and M is a total number of nodes in the suffix tree document model; weight elements of the suffix tree document model converted into the vector document model; and determine a similarity between two or more weighted vector document models, each representing a respective document of the plurality of documents. 3. The system of claim 1 , wherein the elements of the suffix tree document model converted into the vector document model are weighted based on a term frequency of a corresponding suffix tree node, wherein the term frequency of the corresponding suffix tree node with respect to the document is a total number of times the document traverses the corresponding suffix tree node. | 0.623506 |
8,255,351 | 1 | 5 | 1. A system for fault prediction in a home network, the system comprising: a processor and a memory, the memory haying stored thereon: a context generator for generating context information based on status data collected in real time about components of the home network; a specification interpreter for generating knowledge rules for fault detection by using specifications of the components of the home network; a context analyzer for analyzing if the generated context information meet the generated knowledge rules to classify the context information into normal situation contexts and abnormal situation contexts; a context pattern learner for generating new knowledge rules based on the abnormal situation contexts and fault rules corresponding to the abnormal situation contexts; a knowledge rule database for storing and managing the knowledge rules and the new knowledge rules; and a fault predictor for analyzing a correlation between the knowledge rules or the new knowledge rules and the generated context information, thereby predicting faults to be generated. | 1. A system for fault prediction in a home network, the system comprising: a processor and a memory, the memory haying stored thereon: a context generator for generating context information based on status data collected in real time about components of the home network; a specification interpreter for generating knowledge rules for fault detection by using specifications of the components of the home network; a context analyzer for analyzing if the generated context information meet the generated knowledge rules to classify the context information into normal situation contexts and abnormal situation contexts; a context pattern learner for generating new knowledge rules based on the abnormal situation contexts and fault rules corresponding to the abnormal situation contexts; a knowledge rule database for storing and managing the knowledge rules and the new knowledge rules; and a fault predictor for analyzing a correlation between the knowledge rules or the new knowledge rules and the generated context information, thereby predicting faults to be generated. 5. The system of claim 1 , wherein the context analyzer comprises: a context interpreter for interpreting the context information; a condition checker for analyzing if the interpretation results of the context information meet the knowledge rules; and a context classifier for classifying the context information into the normal situation contexts or the abnormal situation contexts depending on the analysis results from the condition checker, and providing the context pattern learner with the abnormal situation contexts and the fault rules corresponding to the abnormal situation contexts. | 0.5 |
8,516,457 | 4 | 5 | 4. The method of claim 1 , further comprising, before said partitioning, generating, by said computer, said dependency graph for said particular programming language; distinguishing, by said computer, groups of cyclically connected grammar rule nodes in said dependency graph from non-cyclically connected grammar rule nodes in said dependency graph; and, after said distinguishing, performing said preprocessing. | 4. The method of claim 1 , further comprising, before said partitioning, generating, by said computer, said dependency graph for said particular programming language; distinguishing, by said computer, groups of cyclically connected grammar rule nodes in said dependency graph from non-cyclically connected grammar rule nodes in said dependency graph; and, after said distinguishing, performing said preprocessing. 5. The method of claim 4 , said partitioning being performed automatically and logically based on said updated dependency graph and as specified in a set of heuristics, said set of heuristics defining at least one of: a maximum number of nodes per subset; and a depth of said updated dependency graph at which said partitioning should begin. | 0.5 |
9,632,989 | 8 | 9 | 8. A system, comprising: a hardware processor; and a memory device, the memory device storing instructions, the instructions when executed causing the hardware processor to perform operations, the operations comprising: storing a hybrid markup language document; determining a partition boundary in the hybrid markup language document; generating a copy of the hybrid markup language document in response to the partition boundary; discarding content in the copy of the hybrid markup language document that precedes the partition boundary; and generating an output markup language document from remaining content occurring in the copy of the hybrid markup language document after the partition boundary. | 8. A system, comprising: a hardware processor; and a memory device, the memory device storing instructions, the instructions when executed causing the hardware processor to perform operations, the operations comprising: storing a hybrid markup language document; determining a partition boundary in the hybrid markup language document; generating a copy of the hybrid markup language document in response to the partition boundary; discarding content in the copy of the hybrid markup language document that precedes the partition boundary; and generating an output markup language document from remaining content occurring in the copy of the hybrid markup language document after the partition boundary. 9. The system of claim 8 , wherein the operations further comprise scanning the hybrid markup language document to determine the partition boundary. | 0.5 |
7,953,736 | 1 | 9 | 1. A non-transitory computer-readable storage medium comprising program code for causing a computer to perform a method for creating a user community consensus of the relevance of a metadata tag to a content item, the method comprising: receiving a metadata tag submitted by a first user of the user community the metadata tag describing an associated content item; receiving a plurality of relevance ratings of the metadata tag submitted by the first user from other users of the user community, the metadata tag relevance ratings each rating the relevance of the metadata tag as pertaining to the associated content item, each user having a respective rating weight that determines the weight afforded to ratings of the user relative to other users in the user community; weighting the relevance ratings submitted by the users relative to one another based on the respective rating weights of the users; calculating an average relevance rating of the metadata tag using the weighted relevance ratings; and storing the relevance ratings and the average relevance rating of the metadata tag. | 1. A non-transitory computer-readable storage medium comprising program code for causing a computer to perform a method for creating a user community consensus of the relevance of a metadata tag to a content item, the method comprising: receiving a metadata tag submitted by a first user of the user community the metadata tag describing an associated content item; receiving a plurality of relevance ratings of the metadata tag submitted by the first user from other users of the user community, the metadata tag relevance ratings each rating the relevance of the metadata tag as pertaining to the associated content item, each user having a respective rating weight that determines the weight afforded to ratings of the user relative to other users in the user community; weighting the relevance ratings submitted by the users relative to one another based on the respective rating weights of the users; calculating an average relevance rating of the metadata tag using the weighted relevance ratings; and storing the relevance ratings and the average relevance rating of the metadata tag. 9. The non-transitory computer-readable storage medium of claim 1 , wherein the content item comprises an image. | 0.888 |
8,145,655 | 30 | 31 | 30. The article of manufacture of claim 27 , wherein the operations further comprise: modifying the at least one query statement in the source code to produce at least one modified query statement; including the at least one modified query statement in the statement descriptor information; and translating the at least one modified query statement into the executable object code. | 30. The article of manufacture of claim 27 , wherein the operations further comprise: modifying the at least one query statement in the source code to produce at least one modified query statement; including the at least one modified query statement in the statement descriptor information; and translating the at least one modified query statement into the executable object code. 31. The article of manufacture of claim 30 , wherein modifying the at least one query statement comprises optimizing the at least one query statement to improve performance of execution of the at least one query statement. | 0.5 |
9,679,043 | 8 | 13 | 8. A system, comprising: a data processing apparatus; and a memory storage apparatus in data communication with the data processing apparatus, the memory storage apparatus storing instructions executable by the data processing apparatus and that upon such execution cause the data processing apparatus to perform operations comprising: identifying, in a set of text sources that were previously published within a specified amount of time of a current time, two or more keywords that co-occur in at least one of the text sources; determining that the two or more identified keywords are not designated as co-occurring keywords in a data structure storing historically linked co-occurring keywords; in response to determining that the two or more identified keywords are not designated as co-occurring keywords and in response to the two or more identified keywords co-occurring in at least one of the text sources, temporarily linking the two or more identified keywords for a limited amount of time; and distributing, during the limited amount of time, content items based on the temporary link between the two or more identified keywords. | 8. A system, comprising: a data processing apparatus; and a memory storage apparatus in data communication with the data processing apparatus, the memory storage apparatus storing instructions executable by the data processing apparatus and that upon such execution cause the data processing apparatus to perform operations comprising: identifying, in a set of text sources that were previously published within a specified amount of time of a current time, two or more keywords that co-occur in at least one of the text sources; determining that the two or more identified keywords are not designated as co-occurring keywords in a data structure storing historically linked co-occurring keywords; in response to determining that the two or more identified keywords are not designated as co-occurring keywords and in response to the two or more identified keywords co-occurring in at least one of the text sources, temporarily linking the two or more identified keywords for a limited amount of time; and distributing, during the limited amount of time, content items based on the temporary link between the two or more identified keywords. 13. The system of claim 8 , wherein the operations further comprise adjusting the limited amount of time based on a performance of content items distributed based on the temporary link between the two or more identified keywords. | 0.789522 |
9,280,525 | 8 | 10 | 8. A non-transitory computer readable medium on which is stored program code for forming a structured document from an unstructured input document, the program code comprising: program code for receiving the input document from a data communication network; program code for storing the received input document in a storage system; program code for extracting a plurality of textual tokens from the input document, each extracted token having a visual style; program code for applying a content classifier to the plurality of tokens to produce, for each token therein, a first probability distribution of the given token with respect to a plurality of textual classes, the first probability distribution comprising a plurality of first probabilities each associated with a corresponding textual class of the plurality of textual classes such that each textual class has one of the plurality of first probabilities associated therewith, each of the plurality of textual classes being related to information conveyed by the textual tokens; program code for applying a context classifier to each token to redistribute the first probability distribution of each token, based on the textual class having the highest first probability of the token's surrounding tokens in context, thereby producing a second probability distribution of the given token with respect to the plurality of textual classes, the second probability distribution comprising a plurality of second probabilities each associated with a corresponding textual class of the plurality of textual classes such that each textual class has one of the plurality of second probabilities associated therewith; program code for applying a visual style classifier to each token based on its visual style and the second probability distribution, thereby producing a third probability distribution of the given token with respect to the plurality of textual classes, the third probability distribution comprising a plurality of third probabilities each associated with a corresponding textual class of the plurality of textual classes such that each textual class has one of the plurality of third probabilities associated therewith; program code for determining a classification for each token into one of the plurality of textual classes as a function of the second and third probability distributions; and program code for forming a structured document from the plurality of classified tokens in the storage system. | 8. A non-transitory computer readable medium on which is stored program code for forming a structured document from an unstructured input document, the program code comprising: program code for receiving the input document from a data communication network; program code for storing the received input document in a storage system; program code for extracting a plurality of textual tokens from the input document, each extracted token having a visual style; program code for applying a content classifier to the plurality of tokens to produce, for each token therein, a first probability distribution of the given token with respect to a plurality of textual classes, the first probability distribution comprising a plurality of first probabilities each associated with a corresponding textual class of the plurality of textual classes such that each textual class has one of the plurality of first probabilities associated therewith, each of the plurality of textual classes being related to information conveyed by the textual tokens; program code for applying a context classifier to each token to redistribute the first probability distribution of each token, based on the textual class having the highest first probability of the token's surrounding tokens in context, thereby producing a second probability distribution of the given token with respect to the plurality of textual classes, the second probability distribution comprising a plurality of second probabilities each associated with a corresponding textual class of the plurality of textual classes such that each textual class has one of the plurality of second probabilities associated therewith; program code for applying a visual style classifier to each token based on its visual style and the second probability distribution, thereby producing a third probability distribution of the given token with respect to the plurality of textual classes, the third probability distribution comprising a plurality of third probabilities each associated with a corresponding textual class of the plurality of textual classes such that each textual class has one of the plurality of third probabilities associated therewith; program code for determining a classification for each token into one of the plurality of textual classes as a function of the second and third probability distributions; and program code for forming a structured document from the plurality of classified tokens in the storage system. 10. A medium according to claim 8 , wherein the visual style includes one or more of the group consisting of: font name, font family, font weight, font size, text color, vertical alignment, horizontal alignment, text justification, text indentation, capitalization type, link type, amount of surrounding white space, and CSS class name. | 0.513043 |
8,250,169 | 16 | 17 | 16. The client device of claim 14 , the view layer to generate and render a task detail toolbar customized to provide access to details of the actionable context data in the desktop widget. | 16. The client device of claim 14 , the view layer to generate and render a task detail toolbar customized to provide access to details of the actionable context data in the desktop widget. 17. The client device of claim 16 , the view layer to further generate and render a transient auxiliary pane to enable the task detail toolbar, the transient auxiliary pane switchable between displaying items related to the actionable context data, including resources, activities, or related persons. | 0.5 |
9,949,103 | 1 | 9 | 1. A method comprising: determining, by a processor and using natural language processing, a writing style of content of a composed message written by a composer; analyzing, by the processor and using natural language processing, a set of previous messages written by the composer; identifying, by the processor and based on the analyzing, writing habits of the composer; identifying, by the processor, a difference between the writing style of the content and the writing habits of the composer; and displaying, by the processor and through a graphical user interface, a notification of the difference to the composer. | 1. A method comprising: determining, by a processor and using natural language processing, a writing style of content of a composed message written by a composer; analyzing, by the processor and using natural language processing, a set of previous messages written by the composer; identifying, by the processor and based on the analyzing, writing habits of the composer; identifying, by the processor, a difference between the writing style of the content and the writing habits of the composer; and displaying, by the processor and through a graphical user interface, a notification of the difference to the composer. 9. The method of claim 1 , wherein displaying a notification of the difference comprises suggesting a content modification to the composer, wherein the modification would reduce the difference. | 0.542654 |
10,157,342 | 7 | 8 | 7. The computer-implemented method of claim 6 , wherein the list of potential responses corresponds to a frequency, wavelength, and amplitude of the waveform. | 7. The computer-implemented method of claim 6 , wherein the list of potential responses corresponds to a frequency, wavelength, and amplitude of the waveform. 8. The computer-implemented method of claim 7 , wherein the list of potential responses corresponds to the frequency, wavelength, and amplitude of the waveform such that a first waveform having a first frequency, a first wavelength, and a first amplitude corresponds to a first list of potential responses that are each more neutral than a second waveform having a second frequency that is higher than the first frequency, a second wavelength that is shorter than the first wavelength, and a second amplitude that is higher than the first amplitude. | 0.5 |
8,070,775 | 10 | 13 | 10. A spine implant comprising: an anchor adapted to be inserted into the bone of a patient the anchor having a longitudinal axis; an anchor head extending from said anchor; said anchor head including a deflection cavity aligned with the longitudinal axis of the anchor; said deflection cavity having a deflection guide cavity wall, a first end which opens through the anchor head, and a second end internal to the anchor head; a deflection rod provided in said deflection cavity; said deflection rod having a distal portion secured within the deflection guide cavity and a proximal portion extending out of the opening of the deflection guide cavity; wherein the spine implant is configured such that, in the absence of a load applied to the proximal portion of the deflection rod, the deflection rod is aligned with the longitudinal axis of the anchor; wherein the spine implant is configured such that a load applied to the proximal portion of the deflection rod causes resilient deflection of the proximal portion of the deflection rod away from alignment with the longitudinal axis of the bone anchor; and wherein resilient deflection of the proximal end of the deflection rod is controlled by contact between the proximal portion of the deflection rod and the deflection guide cavity wall. | 10. A spine implant comprising: an anchor adapted to be inserted into the bone of a patient the anchor having a longitudinal axis; an anchor head extending from said anchor; said anchor head including a deflection cavity aligned with the longitudinal axis of the anchor; said deflection cavity having a deflection guide cavity wall, a first end which opens through the anchor head, and a second end internal to the anchor head; a deflection rod provided in said deflection cavity; said deflection rod having a distal portion secured within the deflection guide cavity and a proximal portion extending out of the opening of the deflection guide cavity; wherein the spine implant is configured such that, in the absence of a load applied to the proximal portion of the deflection rod, the deflection rod is aligned with the longitudinal axis of the anchor; wherein the spine implant is configured such that a load applied to the proximal portion of the deflection rod causes resilient deflection of the proximal portion of the deflection rod away from alignment with the longitudinal axis of the bone anchor; and wherein resilient deflection of the proximal end of the deflection rod is controlled by contact between the proximal portion of the deflection rod and the deflection guide cavity wall. 13. The implant of claim 10 wherein said deflection rod comprises a superelastic material. | 0.782609 |
9,953,631 | 10 | 11 | 10. A non-transitory computer-readable medium having instructions stored thereon that, when executed by one or more processors of a computing device, cause the computing device to perform operations comprising: obtaining a plurality of languages for automatic speech recognition, the plurality of languages being associated with a plurality of users; receiving an input indicative of a request to provide speech input; receiving a speech input from one of the plurality of users; in response to receiving the input: displaying a first indication that the computing device is performing automatic speech recognition in two or more of the plurality of languages, the first indication comprising highlighted icons displaying the two or more of the plurality of languages, performing automatic speech recognition on the speech input in the two or more of the plurality of languages to identify one of the plurality of languages associated with the speech input to obtain a detected language, and in response to obtaining the detected language, displaying a second indication that the computing device is performing automatic speech recognition in the detected language, wherein the second indication is a highlighted icon displaying the detected language and non-highlighted icons displaying a remainder of the two or more of the plurality of languages, respectively; obtaining a transcription of the speech input to obtain a text in the detected language; obtaining a translation of the text from the detected language to another one of the plurality of languages to obtain a translated text; and displaying the translated text. | 10. A non-transitory computer-readable medium having instructions stored thereon that, when executed by one or more processors of a computing device, cause the computing device to perform operations comprising: obtaining a plurality of languages for automatic speech recognition, the plurality of languages being associated with a plurality of users; receiving an input indicative of a request to provide speech input; receiving a speech input from one of the plurality of users; in response to receiving the input: displaying a first indication that the computing device is performing automatic speech recognition in two or more of the plurality of languages, the first indication comprising highlighted icons displaying the two or more of the plurality of languages, performing automatic speech recognition on the speech input in the two or more of the plurality of languages to identify one of the plurality of languages associated with the speech input to obtain a detected language, and in response to obtaining the detected language, displaying a second indication that the computing device is performing automatic speech recognition in the detected language, wherein the second indication is a highlighted icon displaying the detected language and non-highlighted icons displaying a remainder of the two or more of the plurality of languages, respectively; obtaining a transcription of the speech input to obtain a text in the detected language; obtaining a translation of the text from the detected language to another one of the plurality of languages to obtain a translated text; and displaying the translated text. 11. The computer-readable medium of claim 10 , wherein the operations further comprise displaying a third indication of whether automatic speech recognition is currently being performed, wherein the third indication is a highlighted icon from when the request is received until a completion of the speech input, and wherein the third indication is a non-highlighted icon upon the completion of the speech input. | 0.615169 |
9,800,941 | 8 | 15 | 8. A computer program embodied on a tangible, non-transitory computer readable medium for creating an errata report for a transcript, wherein the computer program comprises executable program code executable by a processor, said program comprising: executable program code for providing a first electronic transcript having a total number of alphanumeric characters, wherein said first electronic transcript is organized by pages with a predetermined number of lines per page and a predetermined number of alphanumeric characters per line in the range 1 to x, and wherein each alphanumeric character can be identified by a coordinate page-line-character N, and wherein a portion of said total number of alphanumeric characters forms a sentence that grammatically spans from page 0 -line 0 to page 0 -line 1 ; executable program code for displaying said first electronic transcript with computer logic configured to allow an operator to change said alphanumeric characters in the range 1 to x, wherein alphanumeric characters added in the range 1 to x remain associated with, and are displayable as associated with, page 0 -line 0 , and wherein said changes do not cause said alphanumeric characters to span a line break into subsequent page 0 -line 1 although display of said change appears to cause alphanumeric characters in page 0 -line 0 to wrap; executable program code for compiling a comparison transcript comprising said first electronic transcript and any changed alphanumeric characters; and executable program code for providing an errata report by logic configured to aggregate changes to one or more alphanumeric characters of said first electronic transcript, wherein said errata report comprises a plurality of alphanumeric characters that is substantially smaller in quantity than the total number of alphanumeric characters of said first electronic transcript, and said errata report is distinct from said first electronic transcript. | 8. A computer program embodied on a tangible, non-transitory computer readable medium for creating an errata report for a transcript, wherein the computer program comprises executable program code executable by a processor, said program comprising: executable program code for providing a first electronic transcript having a total number of alphanumeric characters, wherein said first electronic transcript is organized by pages with a predetermined number of lines per page and a predetermined number of alphanumeric characters per line in the range 1 to x, and wherein each alphanumeric character can be identified by a coordinate page-line-character N, and wherein a portion of said total number of alphanumeric characters forms a sentence that grammatically spans from page 0 -line 0 to page 0 -line 1 ; executable program code for displaying said first electronic transcript with computer logic configured to allow an operator to change said alphanumeric characters in the range 1 to x, wherein alphanumeric characters added in the range 1 to x remain associated with, and are displayable as associated with, page 0 -line 0 , and wherein said changes do not cause said alphanumeric characters to span a line break into subsequent page 0 -line 1 although display of said change appears to cause alphanumeric characters in page 0 -line 0 to wrap; executable program code for compiling a comparison transcript comprising said first electronic transcript and any changed alphanumeric characters; and executable program code for providing an errata report by logic configured to aggregate changes to one or more alphanumeric characters of said first electronic transcript, wherein said errata report comprises a plurality of alphanumeric characters that is substantially smaller in quantity than the total number of alphanumeric characters of said first electronic transcript, and said errata report is distinct from said first electronic transcript. 15. The computer program of claim 8 , wherein said comparison transcript is adapted for use as a synchronization index to corresponding multimedia. | 0.786957 |
8,726,254 | 8 | 14 | 8. A method for analyzing global correctness of a program source code, the method comprising the steps of: embedding modular annotation statements in at least one non-code-generative portion of the program source code, the program source code written in a first programming language recognized by a code generation tool for code generation, the annotation statements written in a second programming language which is unrecognized by the first programming language's code generation tool, the second programming language including syntax for numeric operators, syntax for expressions which contain at least one numeric operator, syntax for logical operator, and syntax for expressions which contain at least one logical operator; and submitting the annotated program source code to a dataflow analyzer; and receiving from the dataflow analyzer a verification which reports whether the program source code is globally correct or instead violates one or more conditions specified with the embedded modular annotation statements. | 8. A method for analyzing global correctness of a program source code, the method comprising the steps of: embedding modular annotation statements in at least one non-code-generative portion of the program source code, the program source code written in a first programming language recognized by a code generation tool for code generation, the annotation statements written in a second programming language which is unrecognized by the first programming language's code generation tool, the second programming language including syntax for numeric operators, syntax for expressions which contain at least one numeric operator, syntax for logical operator, and syntax for expressions which contain at least one logical operator; and submitting the annotated program source code to a dataflow analyzer; and receiving from the dataflow analyzer a verification which reports whether the program source code is globally correct or instead violates one or more conditions specified with the embedded modular annotation statements. 14. The method of claim 8 , wherein each routine of the program source code is annotated, and the method further comprises receiving from the dataflow analyzer injection vulnerability warning messages which collectively provide a scalable modular global analysis of the program source code. | 0.766129 |
9,569,553 | 8 | 9 | 8. The method of claim 1 , wherein a bookmark link is generated for the particular user in response to the viewing user requesting a page. | 8. The method of claim 1 , wherein a bookmark link is generated for the particular user in response to the viewing user requesting a page. 9. The method of claim 8 , wherein the requested page is at least one of a home page, a photo album, a message page, an application page, or a profile page. | 0.5 |
9,857,946 | 11 | 12 | 11. A non-transitory computer-readable storage medium comprising a plurality of instructions configured to execute on at least one computer processor to enable the computer processor to control a system for assessing sentiment of text, comprising an input device and a display, to perform operations comprising: receive text input via the input device, the text associated with a review relating to a particular topic; and as the text is being inputted, determine, based on respective scores calculated for each of one or more words included in the received text, a real-time orientation value reflecting a sentiment of the received text; and modify an appearance of a visual display element on the display based on the determined real-time orientation value. | 11. A non-transitory computer-readable storage medium comprising a plurality of instructions configured to execute on at least one computer processor to enable the computer processor to control a system for assessing sentiment of text, comprising an input device and a display, to perform operations comprising: receive text input via the input device, the text associated with a review relating to a particular topic; and as the text is being inputted, determine, based on respective scores calculated for each of one or more words included in the received text, a real-time orientation value reflecting a sentiment of the received text; and modify an appearance of a visual display element on the display based on the determined real-time orientation value. 12. The non-transitory computer-readable storage medium according to claim 11 , wherein the instructions enable the computer processor to control the system to display, on the display, color-based indicators, a color of each of the color-based indicators reflecting a respective orientation value derived from a corresponding block of text associated with a different review relating to the topic, wherein different colors reflect different measures of orientation. | 0.545898 |
9,632,992 | 17 | 18 | 17. The system of claim 13 , further comprising a server coupled to the editing device to provide the text to the editing device. | 17. The system of claim 13 , further comprising a server coupled to the editing device to provide the text to the editing device. 18. The system of claim 17 , wherein the server is coupled to the editing device via a network. | 0.5 |
7,912,703 | 11 | 14 | 11. A computer program product for unsupervised stemming schema learning and lexicon acquisition from corpora, the computer program product comprising a computer usable recordable medium having computer executable program code tangibly embodied thereon, the computer executable program code comprising; computer executable program code for obtaining a corpus from a corpora; computer executable program code for analyzing the corpus to deduce a set of possible stemming schema, wherein the computer executable program code for analyzing the corpus to deduce the set of possible stemming schema further comprises: computer executable program code for generating a first affix count in concepts, wherein each of the concepts is a word unique in the corpus; computer executable program code for generating a second affix count in schemas, wherein each of the schemas contains a transformation from a first affix to a second affix for the word; and computer executable program code for generating a schema score for the each of the schemas from a combination of the first affix count and the second affix count for the possible stemming schemas to identify useful stemming schemas comprising: computer executable program code for identifying a first number of occurrences of the first affix in the corpus for each kernel size; computer executable program code for identifying a second number of occurrences of the second affix in the corpus for the each kernel size; computer executable program code for identifying a third number of occurrences of the each kernel size in the corpus; and computer executable program code for dividing a lesser of the first number of occurrences and the second number of occurrences by the third number of occurrences to form the schema score; computer executable program code for reviewing and revising the set of possible stemming schema to create a pruned set of stemming schema; and computer executable program code for deducing a lexicon from the corpus using the pruned set of stemming schema. | 11. A computer program product for unsupervised stemming schema learning and lexicon acquisition from corpora, the computer program product comprising a computer usable recordable medium having computer executable program code tangibly embodied thereon, the computer executable program code comprising; computer executable program code for obtaining a corpus from a corpora; computer executable program code for analyzing the corpus to deduce a set of possible stemming schema, wherein the computer executable program code for analyzing the corpus to deduce the set of possible stemming schema further comprises: computer executable program code for generating a first affix count in concepts, wherein each of the concepts is a word unique in the corpus; computer executable program code for generating a second affix count in schemas, wherein each of the schemas contains a transformation from a first affix to a second affix for the word; and computer executable program code for generating a schema score for the each of the schemas from a combination of the first affix count and the second affix count for the possible stemming schemas to identify useful stemming schemas comprising: computer executable program code for identifying a first number of occurrences of the first affix in the corpus for each kernel size; computer executable program code for identifying a second number of occurrences of the second affix in the corpus for the each kernel size; computer executable program code for identifying a third number of occurrences of the each kernel size in the corpus; and computer executable program code for dividing a lesser of the first number of occurrences and the second number of occurrences by the third number of occurrences to form the schema score; computer executable program code for reviewing and revising the set of possible stemming schema to create a pruned set of stemming schema; and computer executable program code for deducing a lexicon from the corpus using the pruned set of stemming schema. 14. The computer program product of claim 11 , wherein computer executable program code for reviewing and revising the set of possible stemming schema to create a pruned set of stemming schema further comprises: computer executable program code for analyzing each stemming schema of the set of possible stemming schema; and computer executable program code for identifying stemming schema having a kernel that has a best schema matching a current stemming schema and keeping the kernel, otherwise deleting the stemming schema. | 0.533688 |
9,665,566 | 1 | 16 | 1. A computer-implemented method of automatically generating a coherence score for a text using a scoring model, comprising: identifying a plurality of lexical chains within a text to be scored with a processing system, wherein a lexical chain comprises a set of words spaced within the text, certain words in the lexical chain being non-contiguous; identifying a discourse element within the text with the processing system based on lookup operations with a computer database of discourse elements, wherein the discourse element comprises a word within the text; determining a coherence metric with the processing system based on a relationship between the lexical chains and the discourse element; wherein determining the coherence metric comprises determining: a first count of lexical chains that end before the discourse element; a second count of lexical chains that begin after the discourse element; and a third count of lexical chains that begin before and end after the discourse element; wherein the coherence metric is determined based on the first count, the second count, and the third count; generating a coherence score using the processing system by applying a scoring model to the coherence metric, wherein the scoring model comprises multiple weighted features whose feature weights are determined by training the scoring model relative to a plurality of training texts, the coherence score being combined with other non-lexical chain features by an automated essay evaluation engine to determine a transmitted quality level of the text. | 1. A computer-implemented method of automatically generating a coherence score for a text using a scoring model, comprising: identifying a plurality of lexical chains within a text to be scored with a processing system, wherein a lexical chain comprises a set of words spaced within the text, certain words in the lexical chain being non-contiguous; identifying a discourse element within the text with the processing system based on lookup operations with a computer database of discourse elements, wherein the discourse element comprises a word within the text; determining a coherence metric with the processing system based on a relationship between the lexical chains and the discourse element; wherein determining the coherence metric comprises determining: a first count of lexical chains that end before the discourse element; a second count of lexical chains that begin after the discourse element; and a third count of lexical chains that begin before and end after the discourse element; wherein the coherence metric is determined based on the first count, the second count, and the third count; generating a coherence score using the processing system by applying a scoring model to the coherence metric, wherein the scoring model comprises multiple weighted features whose feature weights are determined by training the scoring model relative to a plurality of training texts, the coherence score being combined with other non-lexical chain features by an automated essay evaluation engine to determine a transmitted quality level of the text. 16. The method of claim 1 , wherein the text is generated using an automated speech recognizer. | 0.764851 |
7,856,350 | 4 | 5 | 4. The computer implemented method of claim 1 wherein the language model is an n-gram model. | 4. The computer implemented method of claim 1 wherein the language model is an n-gram model. 5. The computer implemented method of claim 4 wherein the n-gram model is a bi-gram model. | 0.5 |
7,865,560 | 7 | 8 | 7. The computer program product of claim 6 wherein (A) comprises: (A1) program code for providing a document summarization function for creating a summary of the document, the summary comprising selected content of the document processed by the document summarization function. | 7. The computer program product of claim 6 wherein (A) comprises: (A1) program code for providing a document summarization function for creating a summary of the document, the summary comprising selected content of the document processed by the document summarization function. 8. The computer program product of claim 7 further comprising: (G) program code for presenting the summary document in association with the document processed by the document summarization function. | 0.5 |
8,001,106 | 1 | 3 | 1. A method for processing Uniform Resource Locators (URLs), comprising the steps of: (a) obtaining a plurality of related URLs; (b) parsing the plurality of related URLs to obtain one or more tokens from each URL, each token that is obtained by parsing the plurality of related URLs being included in a set of current tokens; (c) identifying a set of deep tokens, wherein each deep token, of the set of deep tokens, is a portion of at least one token of the set of current tokens; (d) determining a set of anchors for tokens that are currently included in the set of current tokens, wherein each anchor is a deep token from the set of deep tokens; (e) forming a set of patterns for the set of current tokens based on the set of anchors, wherein each pattern of the set of patterns comprises (e1) an anchor from the set of anchors, and (e2) one or more subtokens, wherein each subtoken of the one or more subtokens comprises one or more deep tokens from the set of deep tokens; (f) organizing the set of patterns in a tree of nodes, wherein within the tree each pattern in the set of patterns is a sibling node to at least one other pattern in the set of patterns; (g) selecting a subtoken from a pattern, of the set of patterns, to represent a new set of current tokens, and within the tree, creating for the subtoken a child node of the node corresponding to that pattern; (h) for one or more iterations, repeating steps (d)-(g) by using each new set of current tokens as the set of current tokens; and (i) tagging deep tokens in the set of deep tokens as either keys or values based on organization information from the tree and on initial tag assignments; (j) wherein the steps of the method are performed by one or more computing devices. | 1. A method for processing Uniform Resource Locators (URLs), comprising the steps of: (a) obtaining a plurality of related URLs; (b) parsing the plurality of related URLs to obtain one or more tokens from each URL, each token that is obtained by parsing the plurality of related URLs being included in a set of current tokens; (c) identifying a set of deep tokens, wherein each deep token, of the set of deep tokens, is a portion of at least one token of the set of current tokens; (d) determining a set of anchors for tokens that are currently included in the set of current tokens, wherein each anchor is a deep token from the set of deep tokens; (e) forming a set of patterns for the set of current tokens based on the set of anchors, wherein each pattern of the set of patterns comprises (e1) an anchor from the set of anchors, and (e2) one or more subtokens, wherein each subtoken of the one or more subtokens comprises one or more deep tokens from the set of deep tokens; (f) organizing the set of patterns in a tree of nodes, wherein within the tree each pattern in the set of patterns is a sibling node to at least one other pattern in the set of patterns; (g) selecting a subtoken from a pattern, of the set of patterns, to represent a new set of current tokens, and within the tree, creating for the subtoken a child node of the node corresponding to that pattern; (h) for one or more iterations, repeating steps (d)-(g) by using each new set of current tokens as the set of current tokens; and (i) tagging deep tokens in the set of deep tokens as either keys or values based on organization information from the tree and on initial tag assignments; (j) wherein the steps of the method are performed by one or more computing devices. 3. The method of claim 1 , wherein step (d) comprises using heuristic rules to group the set of deep tokens appearing in the set of current tokens. | 0.754181 |
8,321,413 | 1 | 9 | 1. A method for determining a reputation score representing a reputation of an Internet user comprising: collecting, at a computer, at least one search result from a data source via a search engine based on a search term identifying the Internet user; identifying a contextual token describing the Internet user within a string of words surrounding a relevancy-indicating token in the at least one search result; determining an effect of the at least one search result on the reputation of the Internet user based at least in part on whether the identified contextual token affects the reputation of the user; associating the identified contextual token with a token weight based on the determined effect; and calculating the reputation score representing the reputation of the Internet user based at least in part on the associated token weight. | 1. A method for determining a reputation score representing a reputation of an Internet user comprising: collecting, at a computer, at least one search result from a data source via a search engine based on a search term identifying the Internet user; identifying a contextual token describing the Internet user within a string of words surrounding a relevancy-indicating token in the at least one search result; determining an effect of the at least one search result on the reputation of the Internet user based at least in part on whether the identified contextual token affects the reputation of the user; associating the identified contextual token with a token weight based on the determined effect; and calculating the reputation score representing the reputation of the Internet user based at least in part on the associated token weight. 9. The method of claim 1 , further comprising: calculating at least one reputation sub-score for the Internet user based at least in part on the effect on reputation of the Internet user of the at least one search result from the data source. | 0.625387 |
7,853,557 | 33 | 38 | 33. The computer of claim 32 , wherein the processor is configured to: retrieve the first template data from the database, wherein the first template data correspond to the first language; populate the first template with the first template data to define a first response in the first language; and communicate the first response to a recipient. | 33. The computer of claim 32 , wherein the processor is configured to: retrieve the first template data from the database, wherein the first template data correspond to the first language; populate the first template with the first template data to define a first response in the first language; and communicate the first response to a recipient. 38. The computer of claim 33 , wherein selection of a particular language by an agent is monitored, and the processor switches dynamically to the particular language from any one of the plurality of languages. | 0.642123 |
8,947,355 | 1 | 4 | 1. A computer-implemented method of enabling a user to provide input to an electronic device, comprising: under control of one or more computing systems configured with executable instructions, determining a default relative orientation of the electronic device using at least in part at least one imaging element of the electronic device, wherein the default relative orientation of the electronic device comprises a relative orientation of the electronic device with respect to an aspect of a user of the electronic device; detecting a change in the relative orientation of the electronic device with respect to the default relative orientation, wherein the change in the relative orientation of the electronic device is with respect to the aspect of the user and is caused, at least in part, by a movement of the electronic device by the user, wherein the change in the relative orientation of the electronic device is detected using at least in part the at least one imaging element, and wherein the electronic device displays a plurality of selectable elements in a graphical user interface; if the change in relative orientation meets or exceeds a coarse threshold, moving a selection element of the graphical user interface in a direction corresponding to a direction of the change in relative orientation at a first rate; if the change in relative orientation meets or exceeds a fine threshold, but is less than the coarse threshold, moving the selection element in a direction corresponding to a direction of the change in relative orientation at a second rate less than the first rate; if the change in relative orientation is less than the fine threshold but the detected relative orientation is different from the default relative orientation, maintaining a position of the selection element with respect to one of the selectable elements currently associated with the selection element; and in response to receiving a selection action, providing the selectable element currently associated with the selection element as input to the electronic device. | 1. A computer-implemented method of enabling a user to provide input to an electronic device, comprising: under control of one or more computing systems configured with executable instructions, determining a default relative orientation of the electronic device using at least in part at least one imaging element of the electronic device, wherein the default relative orientation of the electronic device comprises a relative orientation of the electronic device with respect to an aspect of a user of the electronic device; detecting a change in the relative orientation of the electronic device with respect to the default relative orientation, wherein the change in the relative orientation of the electronic device is with respect to the aspect of the user and is caused, at least in part, by a movement of the electronic device by the user, wherein the change in the relative orientation of the electronic device is detected using at least in part the at least one imaging element, and wherein the electronic device displays a plurality of selectable elements in a graphical user interface; if the change in relative orientation meets or exceeds a coarse threshold, moving a selection element of the graphical user interface in a direction corresponding to a direction of the change in relative orientation at a first rate; if the change in relative orientation meets or exceeds a fine threshold, but is less than the coarse threshold, moving the selection element in a direction corresponding to a direction of the change in relative orientation at a second rate less than the first rate; if the change in relative orientation is less than the fine threshold but the detected relative orientation is different from the default relative orientation, maintaining a position of the selection element with respect to one of the selectable elements currently associated with the selection element; and in response to receiving a selection action, providing the selectable element currently associated with the selection element as input to the electronic device. 4. The computer-implemented method of claim 1 , wherein the change in relative orientation is able to meet or exceed at least one additional threshold associated with at least one additional rate of movement of the selection element. | 0.5 |
7,606,794 | 1 | 30 | 1. A method of generating search results in response to a search query, the method comprising the steps of: based on the search query, identifying a plurality of matching resources, wherein the plurality of matching resources includes a particular resource; reading metadata associated with said particular resource, wherein said metadata indicates a plurality of candidate items to include in an abstract for said particular resource; based on filtering criteria, selecting a subset of candidate items from said plurality of candidate items; generating abstracts of each of said plurality of matching resources, wherein the abstract of said particular resource is generated to include the subset of candidate items that were selected based on the filtering criteria; and providing said abstracts as search results of said search query; wherein the subset of candidate items that are included in the abstract generated for the particular resource includes at least one or more selected from the group consisting of: a promoted link which, when activated, causes retrieval of content pointed to by a link that is either contained within the particular resource or is contained within a resource to which the particular resource is directly or indirectly linked by one or more links in the particular resource; a value added service link which, when activated, causes information to be sent to a service that is controlled by a party other than the party that controls the particular resource; a value added information item obtained by a search engine submitting information to a service that is controlled by a party other than the party that controls the particular resource and other than the party that controls the search engine, where that service processes the information; wherein the information is either (a) extracted from the particular resource or (b) about the party that controls the particular resource; and a mid-document link which, when activated, causes retrieval of the particular resource and also jumps to the particular location within the particular resource where content of interest is located, wherein the particular location is such that jumping to the particular location within the particular resource results in hiding the top of the particular resource; wherein the steps are performed on one or more computing devices. | 1. A method of generating search results in response to a search query, the method comprising the steps of: based on the search query, identifying a plurality of matching resources, wherein the plurality of matching resources includes a particular resource; reading metadata associated with said particular resource, wherein said metadata indicates a plurality of candidate items to include in an abstract for said particular resource; based on filtering criteria, selecting a subset of candidate items from said plurality of candidate items; generating abstracts of each of said plurality of matching resources, wherein the abstract of said particular resource is generated to include the subset of candidate items that were selected based on the filtering criteria; and providing said abstracts as search results of said search query; wherein the subset of candidate items that are included in the abstract generated for the particular resource includes at least one or more selected from the group consisting of: a promoted link which, when activated, causes retrieval of content pointed to by a link that is either contained within the particular resource or is contained within a resource to which the particular resource is directly or indirectly linked by one or more links in the particular resource; a value added service link which, when activated, causes information to be sent to a service that is controlled by a party other than the party that controls the particular resource; a value added information item obtained by a search engine submitting information to a service that is controlled by a party other than the party that controls the particular resource and other than the party that controls the search engine, where that service processes the information; wherein the information is either (a) extracted from the particular resource or (b) about the party that controls the particular resource; and a mid-document link which, when activated, causes retrieval of the particular resource and also jumps to the particular location within the particular resource where content of interest is located, wherein the particular location is such that jumping to the particular location within the particular resource results in hiding the top of the particular resource; wherein the steps are performed on one or more computing devices. 30. The method of claim 1 , wherein the abstract generated for the particular resource includes a particular link to the particular resource. | 0.893343 |
5,502,774 | 2 | 3 | 2. The method of claim 1, wherein said trained weighting coefficients are used to produce a new set of parameters and said new set of parameters is applied to generate new said trained weighting coefficients. | 2. The method of claim 1, wherein said trained weighting coefficients are used to produce a new set of parameters and said new set of parameters is applied to generate new said trained weighting coefficients. 3. The method of claim 2, wherein said step of producing a new set of parameters from said trained weighting coefficients is repeated until a stable set of trained weighting coefficients is isolated. | 0.5 |
9,286,041 | 2 | 4 | 2. The system of claim 1 wherein the decompiler and analysis subsystem further comprises means for creating an intermediate representation of the executable software code comprising a complete model of the executable software code based on a data section and the code sections. | 2. The system of claim 1 wherein the decompiler and analysis subsystem further comprises means for creating an intermediate representation of the executable software code comprising a complete model of the executable software code based on a data section and the code sections. 4. The system of claim 2 wherein the means for displaying results of the comparison comprises a graphical user interface rendered on a display device, the graphical user interface for (i) accepting user commands related to the modeling and analysis of the executable software code and (ii) wherein the graphical user interface displays the data flow model and the control flow model on the display device. | 0.5 |
10,101,820 | 1 | 7 | 1. A system for processing user interests, comprising: an interface for receiving an inputted interest and an inputted context from a user, wherein the inputted context includes a natural language input; a gesture management system that receives gesture data from a collection device with the inputted interest to identify a gesture from a set of gestures predefined by the user; a pattern detection system that receives behavior data associated with the inputted interest and determines whether the behavior data includes a recognized behavior pattern based on previously collected behavior data of the user, in which the recognized behavior pattern was not predefined by the user; an interest affinity scoring system that calculates an affinity score for the inputted interest based on an identified gesture and a recognized behavior pattern; a dynamic classification system that assigns a dynamically generated tag to the inputted interest based on the natural language input; and a user interest database that stores structured interest information for the user, including a unique record for the inputted interest that includes the affinity score and dynamically generated tag. | 1. A system for processing user interests, comprising: an interface for receiving an inputted interest and an inputted context from a user, wherein the inputted context includes a natural language input; a gesture management system that receives gesture data from a collection device with the inputted interest to identify a gesture from a set of gestures predefined by the user; a pattern detection system that receives behavior data associated with the inputted interest and determines whether the behavior data includes a recognized behavior pattern based on previously collected behavior data of the user, in which the recognized behavior pattern was not predefined by the user; an interest affinity scoring system that calculates an affinity score for the inputted interest based on an identified gesture and a recognized behavior pattern; a dynamic classification system that assigns a dynamically generated tag to the inputted interest based on the natural language input; and a user interest database that stores structured interest information for the user, including a unique record for the inputted interest that includes the affinity score and dynamically generated tag. 7. The system of claim 1 , wherein the dynamically generated tag and affinity score are periodically reevaluated and updated in response to a received additional inputted context associated with the inputted interest. | 0.5 |
9,122,743 | 19 | 20 | 19. The method of claim 17 , wherein the central processing unit executes program code instructions stored on the computer-readable hardware storage device via the computer readable memory and thereby: presents the plurality of search term search results text words retrieved from the search of at least one database as relevant to the search term to the user on the display device by an implementation of an enhancement to a browser application to retrieve the presented plurality of search term search results text words that is initiated in response to a single click input while a graphical user interface cursor is over the selected text word; and automatically determines whether the selected word is already present within the current search term, generates the modified search term by adding or deleting the selected text word, searches the at least one database for the information relevant to the modified search term, retrieves the modified search term results comprising the plurality of modified search term search results text words and presents the plurality of modified search term search results text words retrieved from the search of the at least one database as relevant to the modified search term to the user on the display device by the implemented browser application enhancement process. | 19. The method of claim 17 , wherein the central processing unit executes program code instructions stored on the computer-readable hardware storage device via the computer readable memory and thereby: presents the plurality of search term search results text words retrieved from the search of at least one database as relevant to the search term to the user on the display device by an implementation of an enhancement to a browser application to retrieve the presented plurality of search term search results text words that is initiated in response to a single click input while a graphical user interface cursor is over the selected text word; and automatically determines whether the selected word is already present within the current search term, generates the modified search term by adding or deleting the selected text word, searches the at least one database for the information relevant to the modified search term, retrieves the modified search term results comprising the plurality of modified search term search results text words and presents the plurality of modified search term search results text words retrieved from the search of the at least one database as relevant to the modified search term to the user on the display device by the implemented browser application enhancement process. 20. The method of claim 19 , wherein the browser application enhancement is a browser plug-in. | 0.5 |
9,734,123 | 6 | 11 | 6. A calculation device comprising: entry keys configured to allow a user to enter at least a formatted mathematical expression; a display configured to: display the formatted mathematical expression, and display an editing cursor that the user can move to various locations within the display, the various locations including a plurality of locations within the formatted mathematical expression; a hardware processor, wherein the hardware processor operates the display in at least a bipositional input mode, wherein in bipositional input mode when an entry key actuated by the user is a character key, a character corresponding to the character key may be inserted in any of the plurality of locations of the formatted mathematical expression. | 6. A calculation device comprising: entry keys configured to allow a user to enter at least a formatted mathematical expression; a display configured to: display the formatted mathematical expression, and display an editing cursor that the user can move to various locations within the display, the various locations including a plurality of locations within the formatted mathematical expression; a hardware processor, wherein the hardware processor operates the display in at least a bipositional input mode, wherein in bipositional input mode when an entry key actuated by the user is a character key, a character corresponding to the character key may be inserted in any of the plurality of locations of the formatted mathematical expression. 11. The calculation device of claim 6 , wherein when the processor operates the display in bipositional input mode and a character most recently entered by the user is a last character of the formatted mathematical expression, then if a next key actuated by the user is a digit key then a digit thus actuated is inserted as a new last character of the formatted expression, but if the next key actuated by the user is one of a plus key and a minus key then a character thus actuated is inserted outside of and immediately following the formatted mathematical expression. | 0.5 |
7,711,573 | 253 | 254 | 253. The system of claim 252 , wherein the storing of the element is to a file. | 253. The system of claim 252 , wherein the storing of the element is to a file. 254. The system of claim 253 , wherein the file comprises an XML file. | 0.5 |
7,725,452 | 1 | 2 | 1. A method of scheduling document indexing, comprising: at a search engine crawler system having one or more processors and memory storing programs for execution by the one or more processors: retrieving a number of document identifiers, each document identifier identifying a corresponding document on a network; and for each retrieved document identifier and its corresponding document, determining a query-independent score indicative of a page rank of the corresponding document relative to other documents in a set of documents; determining a content change frequency of the corresponding document by comparing information stored for successive downloads of the corresponding document; determining an age of the corresponding document, wherein the age is associated with the time of the last download of the corresponding document by the crawler system; determining a first score for the document identifier that is a function of the determined query-independent score and the determined content change frequency and the determined age of the corresponding document; comparing the first score against a threshold value; and conditionally scheduling the document for indexing based on the result of the comparison. | 1. A method of scheduling document indexing, comprising: at a search engine crawler system having one or more processors and memory storing programs for execution by the one or more processors: retrieving a number of document identifiers, each document identifier identifying a corresponding document on a network; and for each retrieved document identifier and its corresponding document, determining a query-independent score indicative of a page rank of the corresponding document relative to other documents in a set of documents; determining a content change frequency of the corresponding document by comparing information stored for successive downloads of the corresponding document; determining an age of the corresponding document, wherein the age is associated with the time of the last download of the corresponding document by the crawler system; determining a first score for the document identifier that is a function of the determined query-independent score and the determined content change frequency and the determined age of the corresponding document; comparing the first score against a threshold value; and conditionally scheduling the document for indexing based on the result of the comparison. 2. The method of claim 1 , wherein the scheduling of a document for indexing includes scheduling the document for a particular index segment indicated by a segment identifier associated with the document identifier. | 0.573413 |
8,489,399 | 3 | 5 | 3. A method of identifying a source of data input to a computing system using prosodic elements of speech comprising: a) presenting a challenge item to an entity, which challenge item is associated with a reference set of words and associated reference prosodic scores; b) receiving speech utterance from an entity related to said challenge item including an input set of words; c) processing said speech utterance with said computing system to compute input prosodic scores of said input set of words; d) comparing said input prosodic scores and said reference prosodic scores; and e) generating a determination of whether said speech utterance originated from a machine or a human based on step (d); wherein said challenge item is supplemented with visual cues, said visual cues being adapted to induce said reference prosodic scores. | 3. A method of identifying a source of data input to a computing system using prosodic elements of speech comprising: a) presenting a challenge item to an entity, which challenge item is associated with a reference set of words and associated reference prosodic scores; b) receiving speech utterance from an entity related to said challenge item including an input set of words; c) processing said speech utterance with said computing system to compute input prosodic scores of said input set of words; d) comparing said input prosodic scores and said reference prosodic scores; and e) generating a determination of whether said speech utterance originated from a machine or a human based on step (d); wherein said challenge item is supplemented with visual cues, said visual cues being adapted to induce said reference prosodic scores. 5. The method of claim 3 , wherein said visual cues are selected from a database of visual cues determined by reference to a database of human vocalizations to most likely result in said reference prosodic scores. | 0.658654 |
9,928,555 | 17 | 21 | 17. A method programmed in a non-transitory memory of a device comprising: a. acquiring a plurality of activity feed stories; b. matching the game of a user and additional users using an implementation to account for translation differences in a title of the game, wherein the implementation to account for translation differences comprises a look up table to match a first title in a first language with a second title in a second language c. condensing the plurality of activity feed stories into a single activity feed story to be displayed for a user while participating in an activity, wherein condensing is based on a type of feed, wherein a property is set to identify how text appears for the single activity feed story. | 17. A method programmed in a non-transitory memory of a device comprising: a. acquiring a plurality of activity feed stories; b. matching the game of a user and additional users using an implementation to account for translation differences in a title of the game, wherein the implementation to account for translation differences comprises a look up table to match a first title in a first language with a second title in a second language c. condensing the plurality of activity feed stories into a single activity feed story to be displayed for a user while participating in an activity, wherein condensing is based on a type of feed, wherein a property is set to identify how text appears for the single activity feed story. 21. The method of claim 17 wherein condensing is further based on relevancy of the activity feed stories to a user. | 0.880457 |
6,112,304 | 35 | 37 | 35. The computer system of claim 26, wherein the transport means includes means for specifying information for building a denizen by using code stored in a library at a destination location. | 35. The computer system of claim 26, wherein the transport means includes means for specifying information for building a denizen by using code stored in a library at a destination location. 37. The computer system of claim 35, wherein the information for building a denizen includes an extension to a class. | 0.52439 |
9,477,749 | 33 | 46 | 33. A non-transitory computer readable storage medium comprising instructions that if executed enables a computing system to: access unstructured data from one or more sources of text; process text from the unstructured data to extract features from the unstructured data; receive an instruction to execute a report from a user; receive an instruction to determine the one or more causal factors associated with an observation selected by the user; determine a baseline for comparison with the selected observation, the baseline being determined by the user as either data comprising one or more features in which the observation is not present or the data originating in a particular time period comprising one or more features in which the observation is present; determine the one or more causal factors associated with the selected observation by calculating an impact of one or more of the features of the unstructured data on the observation selected by the user using the baseline for comparison with the observation selected, at least one of the one or more causal factors comprising one or more of the features, and the impact on a measurable characteristic of the observation selected being calculated based on a comparison of one or more of the features of the unstructured data associated with the presence of the observation and features of the unstructured data associated with the baseline, the measurable characteristic being a volume-based metric, a sentiment metric, a satisfaction metric, or another user-defined metric; rank the one or more causal factors based on a measure of statistical association to the selected observation; and present results to the user. | 33. A non-transitory computer readable storage medium comprising instructions that if executed enables a computing system to: access unstructured data from one or more sources of text; process text from the unstructured data to extract features from the unstructured data; receive an instruction to execute a report from a user; receive an instruction to determine the one or more causal factors associated with an observation selected by the user; determine a baseline for comparison with the selected observation, the baseline being determined by the user as either data comprising one or more features in which the observation is not present or the data originating in a particular time period comprising one or more features in which the observation is present; determine the one or more causal factors associated with the selected observation by calculating an impact of one or more of the features of the unstructured data on the observation selected by the user using the baseline for comparison with the observation selected, at least one of the one or more causal factors comprising one or more of the features, and the impact on a measurable characteristic of the observation selected being calculated based on a comparison of one or more of the features of the unstructured data associated with the presence of the observation and features of the unstructured data associated with the baseline, the measurable characteristic being a volume-based metric, a sentiment metric, a satisfaction metric, or another user-defined metric; rank the one or more causal factors based on a measure of statistical association to the selected observation; and present results to the user. 46. The non-transitory computer readable storage medium of claim 33 , further comprising instructions that if executed enable the computing system to: derive a satisfaction rating from unstructured document metadata; and analyze an aggregation of extracted features to provide a measure of overall satisfaction. | 0.788435 |
7,904,875 | 9 | 15 | 9. At a computer system, the computer system including a processor and system memory, a method for providing technical assistance services for a developing software product, the developing software product being developed by a plurality of different product development groups, one or more other software developers developing other software products that are to depend on at least a portion of the developing software product, the technical assistance service allocated to a software developer to assist the software developer in developing a dependent software product, the method comprising: an act of a service allocation module receiving a service request for technical assistance services from a software developer that is developing another software product that is depend on at least a portion of the functionality of the developing software product, the service allocation module controlling the allocation of service requests to a plurality of different service providers, the developing software product having a functionality defined by the plurality of different development groups, changes to the functionality of the developing software product being determined by at least one group of the plurality of different development groups, such that changes to the functionality of the developing software product is determined independent of the one or more other software developers developing other software products that are to depend on at least a portion of the developing software product and wherein changes to the functionality of the developing software product cause changes in the technical assistance; an act of accessing request allocation criteria for the software developer, at least one request allocation criterion included in the service request, at least one request allocation criterion maintained at the service allocation module; an act of the processor identifying an optimum service provider, from among the plurality of service providers, for servicing the service request by matching the accessed request allocation criteria and service provider characteristics to provide a match in accordance with a routing algorithm; an act of sending the service request to the optimum service provider; an act of receiving an answer to the to the service request from the identified service provider, the answer is based at least in part on the service provider's expertise with respect to the at least one portion of the developing software product's functionality that the other software product is to depend on; and an act of at least notifying the software developer of the existence of the received answer. | 9. At a computer system, the computer system including a processor and system memory, a method for providing technical assistance services for a developing software product, the developing software product being developed by a plurality of different product development groups, one or more other software developers developing other software products that are to depend on at least a portion of the developing software product, the technical assistance service allocated to a software developer to assist the software developer in developing a dependent software product, the method comprising: an act of a service allocation module receiving a service request for technical assistance services from a software developer that is developing another software product that is depend on at least a portion of the functionality of the developing software product, the service allocation module controlling the allocation of service requests to a plurality of different service providers, the developing software product having a functionality defined by the plurality of different development groups, changes to the functionality of the developing software product being determined by at least one group of the plurality of different development groups, such that changes to the functionality of the developing software product is determined independent of the one or more other software developers developing other software products that are to depend on at least a portion of the developing software product and wherein changes to the functionality of the developing software product cause changes in the technical assistance; an act of accessing request allocation criteria for the software developer, at least one request allocation criterion included in the service request, at least one request allocation criterion maintained at the service allocation module; an act of the processor identifying an optimum service provider, from among the plurality of service providers, for servicing the service request by matching the accessed request allocation criteria and service provider characteristics to provide a match in accordance with a routing algorithm; an act of sending the service request to the optimum service provider; an act of receiving an answer to the to the service request from the identified service provider, the answer is based at least in part on the service provider's expertise with respect to the at least one portion of the developing software product's functionality that the other software product is to depend on; and an act of at least notifying the software developer of the existence of the received answer. 15. The method as recited in claim 9 , wherein the act of receiving an answer to the service request from the identified service provider comprises an act receiving an answer to the at least one service question that was formulated through escalation to a product development database. | 0.728053 |
9,251,500 | 12 | 16 | 12. A method comprising: maintaining metapages on a social networking system, each metapage associated with a plurality of pages on the social networking system that describes an equivalent concept; receiving a query for a concept from a user of the social networking system; retrieving, by a processor, a metapage associated with a set of pages corresponding to the concept; determining, by the processor, a best page for the user from among the set of pages corresponding to the concept, the determining based on information about the user comprising: retrieving a language setting for the user; determining the best page of the cluster of pages based at least in part on the retrieved language setting of the user; and providing, as results of the query, the determined best page for the user and the set of pages corresponding to the concept to the user, where the set of pages are collapsed into a selectable link. | 12. A method comprising: maintaining metapages on a social networking system, each metapage associated with a plurality of pages on the social networking system that describes an equivalent concept; receiving a query for a concept from a user of the social networking system; retrieving, by a processor, a metapage associated with a set of pages corresponding to the concept; determining, by the processor, a best page for the user from among the set of pages corresponding to the concept, the determining based on information about the user comprising: retrieving a language setting for the user; determining the best page of the cluster of pages based at least in part on the retrieved language setting of the user; and providing, as results of the query, the determined best page for the user and the set of pages corresponding to the concept to the user, where the set of pages are collapsed into a selectable link. 16. The method of claim 12 , wherein determining, for the user, a best page from among the set of pages corresponding to the concept based on information about the user further comprises: retrieving behavioral information about a plurality of actions of the user inside and outside of the social networking system, the behavioral information including expressions of interest in pages of the set of pages corresponding to the concept and clicks on external websites; and determining the best page based on the retrieved behavioral information about the user, where the best page is determined as the page having a highest number of actions by the user. | 0.5 |
7,529,671 | 1 | 2 | 1. A method of recognizing patterns in an input formed of time-sequenced frames, the method comprising: receiving a plurality of input speech signals; converting the plurality of input speech signals into a plurality of time-sequenced frames; modeling patterns with a plurality of tri-state Hidden Markov Models; and processing with a processor of a computing device, Hidden Markov Model Blocks (HMMBs) to recognize the modeled patterns among the time-sequenced frames to generate a sequence of recognized modeled patterns, wherein each HMMB is a three by three rhombus when depicted on a state vs. time chart. | 1. A method of recognizing patterns in an input formed of time-sequenced frames, the method comprising: receiving a plurality of input speech signals; converting the plurality of input speech signals into a plurality of time-sequenced frames; modeling patterns with a plurality of tri-state Hidden Markov Models; and processing with a processor of a computing device, Hidden Markov Model Blocks (HMMBs) to recognize the modeled patterns among the time-sequenced frames to generate a sequence of recognized modeled patterns, wherein each HMMB is a three by three rhombus when depicted on a state vs. time chart. 2. The method of claim 1 , wherein the time-sequenced frames correspond to speech. | 0.627273 |
8,872,677 | 50 | 53 | 50. The apparatus of claim 47 , wherein: generating a respective input data dictionary-index value comprises generating a respective input data hash value HV N for each N th input data symbol B N in the received sequence of input data symbols, and wherein searching a dictionary-index for an entry corresponding to each input data dictionary-index value DI N comprises searching a hash index for an entry corresponding to each input data hash value HV N , where each hash index entry points to a dictionary data symbol HB and a corresponding location in a dictionary. | 50. The apparatus of claim 47 , wherein: generating a respective input data dictionary-index value comprises generating a respective input data hash value HV N for each N th input data symbol B N in the received sequence of input data symbols, and wherein searching a dictionary-index for an entry corresponding to each input data dictionary-index value DI N comprises searching a hash index for an entry corresponding to each input data hash value HV N , where each hash index entry points to a dictionary data symbol HB and a corresponding location in a dictionary. 53. The apparatus of claim 50 , wherein the entries in the dictionary-index comprise hash values calculated for every M th symbol in the dictionary and wherein N #M. | 0.814189 |
8,704,948 | 1 | 12 | 1. A method of presenting text identified in a presented video image of a media content event, the method comprising: receiving a complete video frame that is associated with a presented video image of a captured scene of a video content event, wherein the presented video image includes text disposed on an object that has been captured in the scene; finding the text on the object that is part of the captured scene in the complete video frame; using an optical character recognition (OCR) algorithm to translate the found text on the object into translated text; and presenting the translated text associated with the text on the object that is part of the captured scene. | 1. A method of presenting text identified in a presented video image of a media content event, the method comprising: receiving a complete video frame that is associated with a presented video image of a captured scene of a video content event, wherein the presented video image includes text disposed on an object that has been captured in the scene; finding the text on the object that is part of the captured scene in the complete video frame; using an optical character recognition (OCR) algorithm to translate the found text on the object into translated text; and presenting the translated text associated with the text on the object that is part of the captured scene. 12. The method of claim 1 , wherein presenting the translated text comprises: presenting the translated text as audible speech emitted from at least one speaker. | 0.801235 |
9,288,543 | 30 | 33 | 30. A system, comprising: one or more memories designed to store computer program code; and one or more processors designed to execute the computer program code stored in the one or more memories, the computer program code designed to cause the one or more processors to perform at least the following: search content on the Internet in order to identify a topic, the topic indicative of relevant news or events, the topic indicative of a type of media content that will be requested for uploading from one or more producers; publishing the topic to the producers; receive and store media content uploaded from the producers that relate to the topic in the one or more memories; enable users to select and download the media content from a website over the Internet; enable the users to upload media content ratings for the media content to the one or more servers over the Internet; determine profiles for respective users; determine a producer rating for each of the producers based at least in part upon the media content ratings and the user profiles; and prevent the download of the media content from a producer from the website over the Internet to a user based at least in part upon the producer rating associated with the producer and a predefined threshold. | 30. A system, comprising: one or more memories designed to store computer program code; and one or more processors designed to execute the computer program code stored in the one or more memories, the computer program code designed to cause the one or more processors to perform at least the following: search content on the Internet in order to identify a topic, the topic indicative of relevant news or events, the topic indicative of a type of media content that will be requested for uploading from one or more producers; publishing the topic to the producers; receive and store media content uploaded from the producers that relate to the topic in the one or more memories; enable users to select and download the media content from a website over the Internet; enable the users to upload media content ratings for the media content to the one or more servers over the Internet; determine profiles for respective users; determine a producer rating for each of the producers based at least in part upon the media content ratings and the user profiles; and prevent the download of the media content from a producer from the website over the Internet to a user based at least in part upon the producer rating associated with the producer and a predefined threshold. 33. The system of claim 30 , wherein the computer program code is further designed to cause the one or more processors to: publish the producer ratings on the website to the users. | 0.705882 |
9,477,450 | 1 | 5 | 1. A non-transitory, computer-readable storage medium storing program instructions that when executed on a computing device cause the computing device to perform: loading a class file comprising a class declaration for a generic class, wherein the generic class is specializable over a plurality of type parameterizations, wherein the class declaration comprises a refinement method specific to a particular one of the plurality of type parameterizations, wherein the refinement method comprises an alternate implementation for a method of the generic class when the generic class is specialized for the particular type parameterization; specializing the generic class for the particular type parameterization; and including the refinement method in the specialized generic class in response to said specializing and based on the particular type parameterization. | 1. A non-transitory, computer-readable storage medium storing program instructions that when executed on a computing device cause the computing device to perform: loading a class file comprising a class declaration for a generic class, wherein the generic class is specializable over a plurality of type parameterizations, wherein the class declaration comprises a refinement method specific to a particular one of the plurality of type parameterizations, wherein the refinement method comprises an alternate implementation for a method of the generic class when the generic class is specialized for the particular type parameterization; specializing the generic class for the particular type parameterization; and including the refinement method in the specialized generic class in response to said specializing and based on the particular type parameterization. 5. The non-transitory, computer-readable storage medium of claim 1 , wherein the class declaration for the generic class comprises information indicating that the refinement method is generic over one or more of the plurality of type parameterizations. | 0.698565 |
9,141,403 | 9 | 14 | 9. A computer system, comprising: at least one processor; and at least one memory, communicatively coupled to the at least one processor and containing computer-readable instructions that, when executed by the at least one processor, perform a method of managing a graphical user interface (GUI), the method comprising: providing a data model that comprises a model object, wherein the model object comprises at least a first task mapped to a first command for performing the first task; providing a user interface (UI) conceptual model that describes at least one UI element for managing the GUI, wherein the at least one UI element references the model object; adding a first reference to the at least one UI element to a first page definition of the UI conceptual model; adding a second reference to the at least one UI element to a second page definition of the UI conceptual model; rendering the at least one UI element on a first corresponding page and a second corresponding page of the GUI, wherein functionality associated with the first corresponding page and the second corresponding page of the GUI is modified upon rendering the at least one UI element; modifying the at least one UI element in the UI conceptual model; automatically modifying the rendering of the at least one UI element on the first corresponding page and the second corresponding page of the GUI without recoding the first page definition or the second page definition; and activating the at least one rendered UI element, wherein activating the at least one rendered UI element includes executing the first task. | 9. A computer system, comprising: at least one processor; and at least one memory, communicatively coupled to the at least one processor and containing computer-readable instructions that, when executed by the at least one processor, perform a method of managing a graphical user interface (GUI), the method comprising: providing a data model that comprises a model object, wherein the model object comprises at least a first task mapped to a first command for performing the first task; providing a user interface (UI) conceptual model that describes at least one UI element for managing the GUI, wherein the at least one UI element references the model object; adding a first reference to the at least one UI element to a first page definition of the UI conceptual model; adding a second reference to the at least one UI element to a second page definition of the UI conceptual model; rendering the at least one UI element on a first corresponding page and a second corresponding page of the GUI, wherein functionality associated with the first corresponding page and the second corresponding page of the GUI is modified upon rendering the at least one UI element; modifying the at least one UI element in the UI conceptual model; automatically modifying the rendering of the at least one UI element on the first corresponding page and the second corresponding page of the GUI without recoding the first page definition or the second page definition; and activating the at least one rendered UI element, wherein activating the at least one rendered UI element includes executing the first task. 14. The computer system of claim 9 , wherein the data model is defined in a markup language. | 0.697368 |
8,635,561 | 11 | 18 | 11. A computer program product including a non-transitory computer readable medium having a plurality of instructions stored thereon which, when executed by at least one processor, cause the processor to perform operations comprising: receiving, by a processor, a plurality of email snippets, including a first email snippet and a second email snippet, each respective email snippet from the plurality of email snippets being based on a respective email from a plurality of emails and including a subject of the respective email, a sender of the respective email, and a respective portion of a body of the respective email, wherein the respective portion of the body of the respective email comprises, at most, a first predetermined maximum amount of the body of the respective email; determining, by the processor and for at least each snippet from the plurality of snippets that is output for display, an expanded view of the snippet, and a condensed view of the snippet, the expanded view of the respective snippet including at least a portion of the subject of the respective email, at least an indication of the sender of the respective email, and an expanded portion of the body of the snippet of the respective email, wherein the expanded portion comprises, at most, a second predetermined maximum amount of the body of the respective email; and the condensed view of the respective snippet including at least a portion of the subject of the respective email, at least an indication of the sender of the respective email, and a condensed portion of the body of the snippet of the respective email, wherein the second portion comprises, at most, a third predetermined maximum amount of the body of the respective email; and outputting, by the processor, and for simultaneous display at a touch-sensitive display: the expanded view for the first snippet, the first snippet based on a first email, and the condensed view for the second snippet, the second snippet based on a second email; receiving an indication of a gesture received at the touch-sensitive display, the gesture received at an area of the touch-sensitive display displaying the expanded view for the first snippet; and responsive to determining the gesture corresponds to one or more of deleting, archiving, and marking actions, sorting the first email based on the corresponding actions. | 11. A computer program product including a non-transitory computer readable medium having a plurality of instructions stored thereon which, when executed by at least one processor, cause the processor to perform operations comprising: receiving, by a processor, a plurality of email snippets, including a first email snippet and a second email snippet, each respective email snippet from the plurality of email snippets being based on a respective email from a plurality of emails and including a subject of the respective email, a sender of the respective email, and a respective portion of a body of the respective email, wherein the respective portion of the body of the respective email comprises, at most, a first predetermined maximum amount of the body of the respective email; determining, by the processor and for at least each snippet from the plurality of snippets that is output for display, an expanded view of the snippet, and a condensed view of the snippet, the expanded view of the respective snippet including at least a portion of the subject of the respective email, at least an indication of the sender of the respective email, and an expanded portion of the body of the snippet of the respective email, wherein the expanded portion comprises, at most, a second predetermined maximum amount of the body of the respective email; and the condensed view of the respective snippet including at least a portion of the subject of the respective email, at least an indication of the sender of the respective email, and a condensed portion of the body of the snippet of the respective email, wherein the second portion comprises, at most, a third predetermined maximum amount of the body of the respective email; and outputting, by the processor, and for simultaneous display at a touch-sensitive display: the expanded view for the first snippet, the first snippet based on a first email, and the condensed view for the second snippet, the second snippet based on a second email; receiving an indication of a gesture received at the touch-sensitive display, the gesture received at an area of the touch-sensitive display displaying the expanded view for the first snippet; and responsive to determining the gesture corresponds to one or more of deleting, archiving, and marking actions, sorting the first email based on the corresponding actions. 18. The method of claim 11 , the third predetermined maximum amount being less than the second predetermined maximum amount. | 0.5 |
8,370,368 | 1 | 4 | 1. A method comprising: defining, via at least one of a server computer and a client electronic device, one or more filter criteria based upon, at least in part, an organizational structure, a member of an organization associated with the organizational structure, and at least one tag that was at least one of added and edited by the member of the organization associated with the organizational structure, wherein the member of the organization associated with the organizational structure that at least one of added and edited the at least one tag is selected by a user; filtering, via at least one of the server computer and the client electronic device, a body of content based upon, at least in part, the defined filter criteria, wherein the body of content includes one or more of a document library, a tag repository, a threaded discussion, a wiki, and a blog, and wherein the tag repository includes a plurality of tags, each tag associated with at least one of web content, documents in the document library, and documents in a team space, wherein filtering includes selecting the at least one tag that was at least one of added and edited by the member of the organization associated with the organizational structure, and wherein the member meets the filter criteria based upon, at least in part, the organizational structure and the member that had at least one of added and edited the at least one tag; providing, via at least one of the server computer and the client electronic device, at least a portion of the filtered body of content, wherein the portion of the filtered body of content is associated with the member of the organization associated with the organizational structure that had at least one of added and edited the at least one tag, and wherein the member meets the filter criteria based upon, at least in part, the organizational structure and the at least one tag that was at least one of added and edited by the member of the organization associated with the organizational structure; and extracting contextually relevant information from the body of content filtered using the defined filter criteria. | 1. A method comprising: defining, via at least one of a server computer and a client electronic device, one or more filter criteria based upon, at least in part, an organizational structure, a member of an organization associated with the organizational structure, and at least one tag that was at least one of added and edited by the member of the organization associated with the organizational structure, wherein the member of the organization associated with the organizational structure that at least one of added and edited the at least one tag is selected by a user; filtering, via at least one of the server computer and the client electronic device, a body of content based upon, at least in part, the defined filter criteria, wherein the body of content includes one or more of a document library, a tag repository, a threaded discussion, a wiki, and a blog, and wherein the tag repository includes a plurality of tags, each tag associated with at least one of web content, documents in the document library, and documents in a team space, wherein filtering includes selecting the at least one tag that was at least one of added and edited by the member of the organization associated with the organizational structure, and wherein the member meets the filter criteria based upon, at least in part, the organizational structure and the member that had at least one of added and edited the at least one tag; providing, via at least one of the server computer and the client electronic device, at least a portion of the filtered body of content, wherein the portion of the filtered body of content is associated with the member of the organization associated with the organizational structure that had at least one of added and edited the at least one tag, and wherein the member meets the filter criteria based upon, at least in part, the organizational structure and the at least one tag that was at least one of added and edited by the member of the organization associated with the organizational structure; and extracting contextually relevant information from the body of content filtered using the defined filter criteria. 4. The method of claim 1 , wherein defining one or more filter criteria includes defining one or more filter criteria based upon, at least in part, an organizational hierarchy. | 0.65625 |
7,822,621 | 1 | 5 | 1. A method of populating a knowledge base, the method comprising: creating at least one claim element based on information related to a field from a claim form for an insurance provider, the at least one claim element comprising a reference claim element; wherein the at least one claim element comprises at least one edit deduced from the information related to the field from the claim form, an edit comprising a directive of an insurance provider to correct or reject an insurance claim under specified circumstances; applying at least one knowledge-base-population rule to the at least one edit to form claim-processing knowledge for the at least one claim element; wherein the application comprises determining a match between a pattern of the at least one edit and a pattern of the at least one knowledge-base-population rule; wherein the claim-processing knowledge comprises one or more conclusions specified by the at least one knowledge-base-population rule based on the determined match; populating the knowledge base with said claim-processing knowledge acquired from said application, the knowledge base being resident in a computer-readable storage medium in a computing system; wherein the population comprises at least one of creating and updating an instance of the at least one claim element with the claim-processing knowledge; and wherein the creating, the performing, and the populating are performed via at least one computer in the computing system comprising a processor and memory. | 1. A method of populating a knowledge base, the method comprising: creating at least one claim element based on information related to a field from a claim form for an insurance provider, the at least one claim element comprising a reference claim element; wherein the at least one claim element comprises at least one edit deduced from the information related to the field from the claim form, an edit comprising a directive of an insurance provider to correct or reject an insurance claim under specified circumstances; applying at least one knowledge-base-population rule to the at least one edit to form claim-processing knowledge for the at least one claim element; wherein the application comprises determining a match between a pattern of the at least one edit and a pattern of the at least one knowledge-base-population rule; wherein the claim-processing knowledge comprises one or more conclusions specified by the at least one knowledge-base-population rule based on the determined match; populating the knowledge base with said claim-processing knowledge acquired from said application, the knowledge base being resident in a computer-readable storage medium in a computing system; wherein the population comprises at least one of creating and updating an instance of the at least one claim element with the claim-processing knowledge; and wherein the creating, the performing, and the populating are performed via at least one computer in the computing system comprising a processor and memory. 5. The method according to claim 1 , further comprising validating a claim using appropriate claim-element knowledge in the populated knowledge base. | 0.686975 |
9,526,994 | 8 | 13 | 8. A computer program product comprising a computer readable medium storing non-transitory signals comprising a computer program, said computer program, when run on a computer hosting a virtual universe, said virtual universe being a computer-based simulated environment having locations therein intended for users to inhabit and interact through the use of avatars and within or between which an avatar can move by teleportation, causing said computer to perform: logically analyzing, using said computer, incoming teleportation invitations on the basis of at least the sender and proposed teleportation location; responsive to results of said logically analyzing step, automatically performing for each teleportation invitation one of: accepting the teleportation invitation for teleporting in accordance with said teleportation invitation, rejecting the teleportation invitation, and deferring response to the teleportation invitation by placing the teleportation invitation in a queue at a queue location having a priority for possible acceptance within said queue based on said logically analyzing step, wherein one or more of the incoming teleportation invitations are deferred and placed in said queue; and teleporting the avatar of a user to the proposed teleportation location of at least one deferred teleportation invitation in said queue, said proposed teleportation location being a geographical location within the topology of a virtual universe, wherein avatars are graphical representations for traversing and interacting within one or more virtual universes. | 8. A computer program product comprising a computer readable medium storing non-transitory signals comprising a computer program, said computer program, when run on a computer hosting a virtual universe, said virtual universe being a computer-based simulated environment having locations therein intended for users to inhabit and interact through the use of avatars and within or between which an avatar can move by teleportation, causing said computer to perform: logically analyzing, using said computer, incoming teleportation invitations on the basis of at least the sender and proposed teleportation location; responsive to results of said logically analyzing step, automatically performing for each teleportation invitation one of: accepting the teleportation invitation for teleporting in accordance with said teleportation invitation, rejecting the teleportation invitation, and deferring response to the teleportation invitation by placing the teleportation invitation in a queue at a queue location having a priority for possible acceptance within said queue based on said logically analyzing step, wherein one or more of the incoming teleportation invitations are deferred and placed in said queue; and teleporting the avatar of a user to the proposed teleportation location of at least one deferred teleportation invitation in said queue, said proposed teleportation location being a geographical location within the topology of a virtual universe, wherein avatars are graphical representations for traversing and interacting within one or more virtual universes. 13. The computer program product as recited in claim 8 , wherein said program further causes the computer to perform: altering order of teleportation invitations or controlling grouping of teleportation invitations in said queue by a user. | 0.540385 |
6,049,339 | 38 | 41 | 38. A graphical processing system comprising: a receiver adapted to receive a page description language representation of graphical objects, the graphical objects having transparency characteristics and color characteristics; and a converter operatively coupled to the receiver, the converter adapted to convert a portion of the page description language representation into a planar map representation, the planar map representation having regions wherein each region is associated with one or more of the graphical objects, and assign a color to a planar map region as a function of the transparency characteristics and color characteristics of the graphical objects associated with the planar map region. | 38. A graphical processing system comprising: a receiver adapted to receive a page description language representation of graphical objects, the graphical objects having transparency characteristics and color characteristics; and a converter operatively coupled to the receiver, the converter adapted to convert a portion of the page description language representation into a planar map representation, the planar map representation having regions wherein each region is associated with one or more of the graphical objects, and assign a color to a planar map region as a function of the transparency characteristics and color characteristics of the graphical objects associated with the planar map region. 41. The system of claim 38 wherein the transparency characteristics are given by a plurality of pixels wherein each pixel provides a transparency value and a color value. | 0.522472 |
8,092,223 | 11 | 12 | 11. A method of implementing written and oral language skills in learners, principally children, by use of flash type cards comprising the steps of: a) providing to a learner, a themed set of robust cards, each comprising a paper sheet coated or laminated between transparent, rigid but flexible, writable plastic sheets, said paper sheet having imprinted thereon defined multiple, associated areas, including: i) a first area on which is disposed a real object image; ii) a second area having a plurality of writing guidelines comprising solid lines defining margins within which writing is to be confined, and including dashed lines between said solid line margins defining orthographic element direction or size; and iii) a third area for free-hand drawing or printing by said learners; iv) said second area includes printed letters or ideographs spelling the word for the object depicted in the first area, said word covering only a small portion of said second writing area, said word being disposed with respect to said solid and dashed guidelines to show the proper location for writing said word, and said second area extending in at least one full strip between opposed side margins of said paper sheet for practice writing of said word by said learner; v) said first, image area is disposed above or to one side of the writing area, and said drawing area is disposed adjacent a bottom margin of said paper sheet; b) permitting said learner to view said real object image and said printed word; c) assisting said learner to say the word representing said real object image; d) providing an erasable marker and guiding said learner to practice writing said word in said second area in proper relation to said guidelines; and e) permitting said learner to draw a picture or to write in said third area relating to said word and real object image, thereby to aid learning in a manner universal with respect to both text and visual learning styles by providing, for predominantly text learners, sufficient space for either a left-handed or right-handed learner to engage in kinesthetic association by practice writing or/and drawing activity on the card without obscuring the text word or the image when practicing the letters on the second, writing area guidelines and in the third, drawing area, and for predominantly visual learners, providing a real object image that permits visual learning association with the word without double inductive reasoning being required. | 11. A method of implementing written and oral language skills in learners, principally children, by use of flash type cards comprising the steps of: a) providing to a learner, a themed set of robust cards, each comprising a paper sheet coated or laminated between transparent, rigid but flexible, writable plastic sheets, said paper sheet having imprinted thereon defined multiple, associated areas, including: i) a first area on which is disposed a real object image; ii) a second area having a plurality of writing guidelines comprising solid lines defining margins within which writing is to be confined, and including dashed lines between said solid line margins defining orthographic element direction or size; and iii) a third area for free-hand drawing or printing by said learners; iv) said second area includes printed letters or ideographs spelling the word for the object depicted in the first area, said word covering only a small portion of said second writing area, said word being disposed with respect to said solid and dashed guidelines to show the proper location for writing said word, and said second area extending in at least one full strip between opposed side margins of said paper sheet for practice writing of said word by said learner; v) said first, image area is disposed above or to one side of the writing area, and said drawing area is disposed adjacent a bottom margin of said paper sheet; b) permitting said learner to view said real object image and said printed word; c) assisting said learner to say the word representing said real object image; d) providing an erasable marker and guiding said learner to practice writing said word in said second area in proper relation to said guidelines; and e) permitting said learner to draw a picture or to write in said third area relating to said word and real object image, thereby to aid learning in a manner universal with respect to both text and visual learning styles by providing, for predominantly text learners, sufficient space for either a left-handed or right-handed learner to engage in kinesthetic association by practice writing or/and drawing activity on the card without obscuring the text word or the image when practicing the letters on the second, writing area guidelines and in the third, drawing area, and for predominantly visual learners, providing a real object image that permits visual learning association with the word without double inductive reasoning being required. 12. A method of implementing written and oral language skills in children as in claim 11 wherein a plurality of said robust cards are provided in a themed set and which includes repeating the steps with each of the cards in said set. | 0.793805 |
7,877,410 | 7 | 11 | 7. A computer implemented method for providing private inference control, comprising: maintaining a query count and a secure database comprising a plurality of records with each record comprising a plurality of attributes, wherein a set of the attributes form one or more inference channels; constructing a regular data structure comprising a set of ciphertext keys, which each relate to one such attribute and record in the secure database; choosing a seed for a pseudorandom function and a secret key for non-malleable encryption; specifying a query by providing indices identifying one such record and attribute and executing a secure function evaluation dependent upon the inference channels, the seed, the secret key, the query count, and the set of ciphertext keys; generating an output from the secure function evaluation comprising the pseudorandom function and an updated set of ciphertext keys subject to sum-consistency of the set of ciphertext keys and a non-inference enabling query; forming a table of entries by combining each of the attributes for each of the records of the database with an output from the pseudorandom function as applied to the seed and the indices; and providing the entry from the table corresponding to the indices. | 7. A computer implemented method for providing private inference control, comprising: maintaining a query count and a secure database comprising a plurality of records with each record comprising a plurality of attributes, wherein a set of the attributes form one or more inference channels; constructing a regular data structure comprising a set of ciphertext keys, which each relate to one such attribute and record in the secure database; choosing a seed for a pseudorandom function and a secret key for non-malleable encryption; specifying a query by providing indices identifying one such record and attribute and executing a secure function evaluation dependent upon the inference channels, the seed, the secret key, the query count, and the set of ciphertext keys; generating an output from the secure function evaluation comprising the pseudorandom function and an updated set of ciphertext keys subject to sum-consistency of the set of ciphertext keys and a non-inference enabling query; forming a table of entries by combining each of the attributes for each of the records of the database with an output from the pseudorandom function as applied to the seed and the indices; and providing the entry from the table corresponding to the indices. 11. A computer implemented method according to claim 7 , further comprising: recovering the secure database entry by upon receipt of the pseudorandom function and the entry from the table. | 0.726744 |
7,689,974 | 1 | 4 | 1. A method of monitoring execution behavior of a program product, the method comprising: (a) providing for the program product a trace tool producing a trace tool output having human-readable trace strings written in a human language, the trace strings including human-readable data fields for recording diagnostic information related to executable instructions of the program product; (b) providing a database storing identifiers of the trace tool, the trace strings, the data fields, and components of the diagnostic information in a binary language and the human language, wherein the database is used to cross-reference the identifiers and the components of the diagnostic information in the binary and human languages for translating contents of the trace tool output from one language into another; (c) using the database, encoding the contents of the trace tool output by: (i) converting the human-readable trace strings and at least portions of the human-readable data fields of the trace tool output into the corresponding binary identifiers stored in the database; and (ii) adapting the trace tool for storing the diagnostic information in the human-readable data fields using the binary identifiers, to produce a a binary trace-tool output; (d) monitoring execution of the instructions of the program product using the adapted trace tool; (e) producing an encoded trace report containing the binary trace-tool output having the diagnostic information in the form of trace strings and data fields replaced with their respective binary identifiers; and (f) decoding the encoded trace report into the human language wherein the corresponding human-readable trace strings of the encoded trace report are found in the database based on the binary identifiers and the binary identifiers are converted into the human-readable trace strings. | 1. A method of monitoring execution behavior of a program product, the method comprising: (a) providing for the program product a trace tool producing a trace tool output having human-readable trace strings written in a human language, the trace strings including human-readable data fields for recording diagnostic information related to executable instructions of the program product; (b) providing a database storing identifiers of the trace tool, the trace strings, the data fields, and components of the diagnostic information in a binary language and the human language, wherein the database is used to cross-reference the identifiers and the components of the diagnostic information in the binary and human languages for translating contents of the trace tool output from one language into another; (c) using the database, encoding the contents of the trace tool output by: (i) converting the human-readable trace strings and at least portions of the human-readable data fields of the trace tool output into the corresponding binary identifiers stored in the database; and (ii) adapting the trace tool for storing the diagnostic information in the human-readable data fields using the binary identifiers, to produce a a binary trace-tool output; (d) monitoring execution of the instructions of the program product using the adapted trace tool; (e) producing an encoded trace report containing the binary trace-tool output having the diagnostic information in the form of trace strings and data fields replaced with their respective binary identifiers; and (f) decoding the encoded trace report into the human language wherein the corresponding human-readable trace strings of the encoded trace report are found in the database based on the binary identifiers and the binary identifiers are converted into the human-readable trace strings. 4. The method of claim 1 , wherein step (f) further comprises outputting the trace strings in the human language. | 0.811667 |
9,569,437 | 10 | 17 | 10. A computer-implemented method of providing annotated electronic documents, the method being executed on a computer and comprising: providing, in a computer processor, access to an electronic storage configured to store at least one annotation as annotation data in a first data storage and at least one document as document data in a second data storage, the first and second data storage being searchable databases; receiving, in the computer processor from the electronic storage, a unitary single logical document for display that includes document data with at least one annotation represented by annotation data embedded seamlessly in the document data, the annotation data being retrieved from the first data storage, the document data being retrieved from the second data storage which is stored separately from the first data storage; and extracting, in the computer processor, by a split component, from the single logical document, the annotation data and the document data; updating the at least one annotation in the first data storage from the extracted annotation data; and updating the at least one document in the second data storage from the extracted document data, wherein the annotation data indexes into a predetermined section within the document as stored in the second data storage into which the annotation is to be embedded as indicated by a document-image-independent data schema, wherein the annotations data further includes, specific to the predetermined section within the document to which the annotation is embedded, a pre-defined conflict indication user-selected from at least two of pass possible and fail, and wherein the processor is further configured to search, responsive to a search request from at least one user, the search request includes annotation search criteria which includes at least one of the pre-defined conflict indications content of the annotation data in the first data storage for the annotation data that satisfies the annotation search criteria, and to output, as a search result, the at least one document indicated by the annotation data that satisfies the annotation search criteria. | 10. A computer-implemented method of providing annotated electronic documents, the method being executed on a computer and comprising: providing, in a computer processor, access to an electronic storage configured to store at least one annotation as annotation data in a first data storage and at least one document as document data in a second data storage, the first and second data storage being searchable databases; receiving, in the computer processor from the electronic storage, a unitary single logical document for display that includes document data with at least one annotation represented by annotation data embedded seamlessly in the document data, the annotation data being retrieved from the first data storage, the document data being retrieved from the second data storage which is stored separately from the first data storage; and extracting, in the computer processor, by a split component, from the single logical document, the annotation data and the document data; updating the at least one annotation in the first data storage from the extracted annotation data; and updating the at least one document in the second data storage from the extracted document data, wherein the annotation data indexes into a predetermined section within the document as stored in the second data storage into which the annotation is to be embedded as indicated by a document-image-independent data schema, wherein the annotations data further includes, specific to the predetermined section within the document to which the annotation is embedded, a pre-defined conflict indication user-selected from at least two of pass possible and fail, and wherein the processor is further configured to search, responsive to a search request from at least one user, the search request includes annotation search criteria which includes at least one of the pre-defined conflict indications content of the annotation data in the first data storage for the annotation data that satisfies the annotation search criteria, and to output, as a search result, the at least one document indicated by the annotation data that satisfies the annotation search criteria. 17. The method of claim 10 , further comprising: determining, in the computer processor, whether the at least one document is read-only; updating, in the computer processor, the at least one document in the second data storage from the extracted document data when the at least one document is determined to not be read-only; and canceling, in the computer processor, an update of the at least one document when the at least one document is determined to be read-only. | 0.578378 |
10,108,984 | 2 | 3 | 2. The method of claim 1 , wherein outputting, by the device, the body language feature to the application comprises outputting, by the device, the body language feature to a context-aware application. | 2. The method of claim 1 , wherein outputting, by the device, the body language feature to the application comprises outputting, by the device, the body language feature to a context-aware application. 3. The method of claim 2 , further comprising: receiving, at the context-aware application being executed by the processor, body language information associated with the body language feature; analyzing, by the context-aware application, the body language information to determine a physical activity being performed by the user; selecting, by the context-aware application, an advertisement appropriate for the physical activity being performed by the user; and providing the advertisement to the user. | 0.5 |
8,953,844 | 3 | 4 | 3. The method of claim 1 , said step (b) of applying one or more computer models comprising the step of applying one or more computer models based on the image data from the field of view captured in a current frame. | 3. The method of claim 1 , said step (b) of applying one or more computer models comprising the step of applying one or more computer models based on the image data from the field of view captured in a current frame. 4. The method of claim 3 , said of applying one or more computer models based on the image data from the field of view captured in a current frame comprising the step of applying one or more computer models based on body part proposals computed from the image data from the current field of view. | 0.5 |
9,785,617 | 12 | 14 | 12. The non-transitory computer readable medium of claim 9 , wherein the other content that replaces the selected content is media content. | 12. The non-transitory computer readable medium of claim 9 , wherein the other content that replaces the selected content is media content. 14. The non-transitory computer readable medium of claim 12 , wherein the operation that provides the media content is an operation that drags the media content from a second field of the page. | 0.5 |
8,935,200 | 10 | 11 | 10. A computer program product for controlling a dump for a database, the computer program product comprising: a non-transitory tangible storage medium readable by a processing circuit and storing instructions for execution by the processing circuit for performing a method comprising: in response to a structured query language (SQL) statement being executed for the database, determining a state of a diagnosis flag associated with the SQL statement, the diagnosis flag indicating whether to perform a dump; performing, by a computer, a dump for the SQL statement m response to determining that the diagnosis flag indicates that a dump is to be performed; and for each of one or more processing steps for the SQL statement: executing the processing step; determining the state of the diagnosis flag in response to executing the processing step; accessing dump configuration information associated with the processing step; and performing the dump for the processing step based on the dump configuration information, in response to the dump configuration information indicating a dump is to be performed. | 10. A computer program product for controlling a dump for a database, the computer program product comprising: a non-transitory tangible storage medium readable by a processing circuit and storing instructions for execution by the processing circuit for performing a method comprising: in response to a structured query language (SQL) statement being executed for the database, determining a state of a diagnosis flag associated with the SQL statement, the diagnosis flag indicating whether to perform a dump; performing, by a computer, a dump for the SQL statement m response to determining that the diagnosis flag indicates that a dump is to be performed; and for each of one or more processing steps for the SQL statement: executing the processing step; determining the state of the diagnosis flag in response to executing the processing step; accessing dump configuration information associated with the processing step; and performing the dump for the processing step based on the dump configuration information, in response to the dump configuration information indicating a dump is to be performed. 11. The computer program product according to claim 10 , wherein the method further comprises generating dump data for the SQL statement based on the dump for the processing step. | 0.643426 |
9,110,944 | 8 | 9 | 8. The article of manufacture according to claim 7 , further comprising: analyzing the input query to determine the information about the input query used to select the model. | 8. The article of manufacture according to claim 7 , further comprising: analyzing the input query to determine the information about the input query used to select the model. 9. The article of manufacture according to claim 8 , wherein the information about the input query comprises a lexical answer type. | 0.5 |
10,083,696 | 1 | 4 | 1. A method for determining user liveness comprising: capturing, by a computing device, voice biometric data of a user during a verification transaction, the user and computing device being a user-computing device pair; calculating a first matrix for the captured voice biometric data; calculating an expansion coefficient matrix based on the first matrix and a record spectral shape matrix, the record spectral shape matrix being for the user-computing device pair; calculating a distortion vector as the average of a ratio between the first matrix and the product of the record spectral shape matrix and the expansion coefficient matrix; calculating a spectral property difference as an element-wise function between the square value of the distortion vector and the square value of a user record normalization vector; inputting the spectral property difference into a machine learning algorithm; calculating an output score with the machine learning algorithm, the output score representing the difference between a probability the voice biometric data was captured from a live user and a probability the voice biometric data was not captured from a live user; and determining the voice biometric data was captured from a live user when the output score satisfies a threshold score. | 1. A method for determining user liveness comprising: capturing, by a computing device, voice biometric data of a user during a verification transaction, the user and computing device being a user-computing device pair; calculating a first matrix for the captured voice biometric data; calculating an expansion coefficient matrix based on the first matrix and a record spectral shape matrix, the record spectral shape matrix being for the user-computing device pair; calculating a distortion vector as the average of a ratio between the first matrix and the product of the record spectral shape matrix and the expansion coefficient matrix; calculating a spectral property difference as an element-wise function between the square value of the distortion vector and the square value of a user record normalization vector; inputting the spectral property difference into a machine learning algorithm; calculating an output score with the machine learning algorithm, the output score representing the difference between a probability the voice biometric data was captured from a live user and a probability the voice biometric data was not captured from a live user; and determining the voice biometric data was captured from a live user when the output score satisfies a threshold score. 4. The method for determining user liveness in accordance with claim 1 further comprising factorizing the first matrix with a non-negative factorization algorithm to estimate the spectral shape matrix. | 0.742308 |
8,990,235 | 13 | 15 | 13. A system comprising: a text analysis component, including one or more processors, that receives text and selects a portion of the received text absent user interaction with the portion of the received text; and a query generation component, including one or more processors, that interacts with the text analysis component and executes instructions that cause the query generation component to perform operations comprising: forming a query based at least in part upon the selected portion of the received text, wherein the query includes a first portion that is associated with the selected portion of the text; and selecting, from among multiple different indexes, at least one index to search based on the query; a communications and routing component that interacts with the query generation component and executes instructions that cause the query generation component to perform operations comprising: transmitting the query to at least one of one or more second computing devices based at least in part on the selected index; and receiving information relevant to the query from at least one of the one or more second computing devices; and a user interface that interacts with the communications and routing component and displays the relevant information. | 13. A system comprising: a text analysis component, including one or more processors, that receives text and selects a portion of the received text absent user interaction with the portion of the received text; and a query generation component, including one or more processors, that interacts with the text analysis component and executes instructions that cause the query generation component to perform operations comprising: forming a query based at least in part upon the selected portion of the received text, wherein the query includes a first portion that is associated with the selected portion of the text; and selecting, from among multiple different indexes, at least one index to search based on the query; a communications and routing component that interacts with the query generation component and executes instructions that cause the query generation component to perform operations comprising: transmitting the query to at least one of one or more second computing devices based at least in part on the selected index; and receiving information relevant to the query from at least one of the one or more second computing devices; and a user interface that interacts with the communications and routing component and displays the relevant information. 15. The system of claim 13 , wherein wherein selecting at least one index comprises selecting one or more dynamic content sources that provide content created during or after the portion of text is received, including content within social networks. | 0.597087 |
9,032,298 | 1 | 6 | 1. A Web-based system for accessing development components, which include an online video clip library and an online music clip library, and enabling online production of custom-integrated media products, said system comprising at least one computer server connected to a computer network, said server including: an upload engine capable of receiving over the computer network a plurality of video and music clips from a plurality of content provider users; a storage engine capable of storing the uploaded plurality of video and music clips provided by said plurality of content provider users in a database and media content storage devices as libraries; a search engine capable of indexing the database and media content storage devices that store the libraries of uploaded video and music clips; a user interface engine capable of providing over the computer network to a plurality of producer users interactive Web formatting screens allowing said producer users to select from said libraries a plurality of video and music clips from among any of the video and music clips uploaded by said plurality of content provider users; and a mixer module capable of allowing said producer users to edit and play said selected video and music clips, wherein said mixer module supports mixing together a plurality of said uploaded video and music clips, such that producer users are able to self-produce video advertisement templates each comprising static content and at least one placeholder, said mixer module further capable of allowing advertiser users to customize said video advertisement templates by uploading a list, such that advertiser users are able to automatically self-produce a set of different customized video advertisements based on an advertisement template, in which the at least one placeholder for each customized video advertisement contains a different item from the list, wherein said mixer module is capable of arranging said video advertisement templates and customized video advertisements as respective XML files on a server, said XML files being accessible by a plurality of users using respective browser applications, such that upon updating an XML file representing a video advertisement template or a customized video advertisement, the updated video advertisement template or customized video advertisement is made accessible to users accessing the updated XML file; said system further comprising a Web application for encoding and formatting video advertisements in particular formats. | 1. A Web-based system for accessing development components, which include an online video clip library and an online music clip library, and enabling online production of custom-integrated media products, said system comprising at least one computer server connected to a computer network, said server including: an upload engine capable of receiving over the computer network a plurality of video and music clips from a plurality of content provider users; a storage engine capable of storing the uploaded plurality of video and music clips provided by said plurality of content provider users in a database and media content storage devices as libraries; a search engine capable of indexing the database and media content storage devices that store the libraries of uploaded video and music clips; a user interface engine capable of providing over the computer network to a plurality of producer users interactive Web formatting screens allowing said producer users to select from said libraries a plurality of video and music clips from among any of the video and music clips uploaded by said plurality of content provider users; and a mixer module capable of allowing said producer users to edit and play said selected video and music clips, wherein said mixer module supports mixing together a plurality of said uploaded video and music clips, such that producer users are able to self-produce video advertisement templates each comprising static content and at least one placeholder, said mixer module further capable of allowing advertiser users to customize said video advertisement templates by uploading a list, such that advertiser users are able to automatically self-produce a set of different customized video advertisements based on an advertisement template, in which the at least one placeholder for each customized video advertisement contains a different item from the list, wherein said mixer module is capable of arranging said video advertisement templates and customized video advertisements as respective XML files on a server, said XML files being accessible by a plurality of users using respective browser applications, such that upon updating an XML file representing a video advertisement template or a customized video advertisement, the updated video advertisement template or customized video advertisement is made accessible to users accessing the updated XML file; said system further comprising a Web application for encoding and formatting video advertisements in particular formats. 6. The system of claim 1 , wherein said media products are ads longer than 9 seconds. | 0.882271 |
9,547,832 | 12 | 15 | 12. A system comprising: one or more processors; a content monitor executable by the one or more processors and configured to: receive a content item from one or more of a plurality of communication channels, and determine the content item is to be processed further, the content item comprising: a communication from an individual, and a statement by the individual, the statement comprising committing language about an intent to attend an event; an analysis engine executable by the one or more processors and configured to determine a commitment score of the individual to attend the event by: identifying the event as a topic of interest in the content item; calculating a strength value of the intent of the individual to attend the event by performing a natural language analysis of the committing language of the statement by the individual in the content item, calculating a sentiment value of the intent of the individual to attend the event by performing a semantic analysis on the content item, the semantic analysis comprising identifying a description of a probability related to the event identified in the content item, calculating a social impact value of the intent of the individual to attend the event by performing a social impact analysis of the content item based on a number of receiving subscribers to the content item on the communication channel, and calculating a magnitude value of the intent of the individual to attend the event by performing a magnitude of commitment analysis of the content item based on a cost of attending the event, wherein: the commitment score comprises a combination of the strength value, the sentiment value, the social impact value, and the magnitude value; and determining an action based on the commitment score of the individual to attend the event. | 12. A system comprising: one or more processors; a content monitor executable by the one or more processors and configured to: receive a content item from one or more of a plurality of communication channels, and determine the content item is to be processed further, the content item comprising: a communication from an individual, and a statement by the individual, the statement comprising committing language about an intent to attend an event; an analysis engine executable by the one or more processors and configured to determine a commitment score of the individual to attend the event by: identifying the event as a topic of interest in the content item; calculating a strength value of the intent of the individual to attend the event by performing a natural language analysis of the committing language of the statement by the individual in the content item, calculating a sentiment value of the intent of the individual to attend the event by performing a semantic analysis on the content item, the semantic analysis comprising identifying a description of a probability related to the event identified in the content item, calculating a social impact value of the intent of the individual to attend the event by performing a social impact analysis of the content item based on a number of receiving subscribers to the content item on the communication channel, and calculating a magnitude value of the intent of the individual to attend the event by performing a magnitude of commitment analysis of the content item based on a cost of attending the event, wherein: the commitment score comprises a combination of the strength value, the sentiment value, the social impact value, and the magnitude value; and determining an action based on the commitment score of the individual to attend the event. 15. The system of claim 12 , wherein the natural language analysis includes identifying an indication of a date or location for the event in the content item. | 0.721831 |
9,336,318 | 7 | 10 | 7. A system, comprising: a data processing apparatus; and a memory storage apparatus connected to the data processing apparatus and storing instruction executable by the data processing apparatus that upon such execution cause the data processing apparatus to perform operations comprising: receiving a query determined to be a question query and a corresponding answer generated in response to the question query, the answer determined to be responsive to the question query so that it is to be provided to a user as an answer to the query, wherein each of the question query and the answer has one or more terms; in response to receiving the question query and the corresponding answer: receiving a first set of rich content items in response to a search process and based on the question query and corresponding answer; for each rich content item in the set of first rich content items, receiving data specifying rich content item labels for the rich content item; determining each rich content item having labels that match terms of the answer and terms of the question query as first rich content items; determining each rich content item having labels that match only the terms of the answer or that match only the terms of the question query as second rich content items; demoting the second rich content items in the order in the first set relative to the first rich content items in the first set so that the rich content items in the first set are ranked according to a revised order; selecting, according to the revised order, a rich content item as a selected rich content item to provide with the answer; and providing, to a user device, the answer to the question query and the selected rich content item with the answer to the question query. | 7. A system, comprising: a data processing apparatus; and a memory storage apparatus connected to the data processing apparatus and storing instruction executable by the data processing apparatus that upon such execution cause the data processing apparatus to perform operations comprising: receiving a query determined to be a question query and a corresponding answer generated in response to the question query, the answer determined to be responsive to the question query so that it is to be provided to a user as an answer to the query, wherein each of the question query and the answer has one or more terms; in response to receiving the question query and the corresponding answer: receiving a first set of rich content items in response to a search process and based on the question query and corresponding answer; for each rich content item in the set of first rich content items, receiving data specifying rich content item labels for the rich content item; determining each rich content item having labels that match terms of the answer and terms of the question query as first rich content items; determining each rich content item having labels that match only the terms of the answer or that match only the terms of the question query as second rich content items; demoting the second rich content items in the order in the first set relative to the first rich content items in the first set so that the rich content items in the first set are ranked according to a revised order; selecting, according to the revised order, a rich content item as a selected rich content item to provide with the answer; and providing, to a user device, the answer to the question query and the selected rich content item with the answer to the question query. 10. The system of claim 7 , further comprising selecting, from among the rich content items in the first set, one or more rich content items to be provided as one or more answer rich content items with the answer to a user device from which the question query was received, the selection based at least in part on the revised order. | 0.733119 |
4,841,478 | 11 | 15 | 11. A document processor comprising: input means for inputting character information; memory means for storing the character information input by said input means; a carrier having a print head mounted thereon; a first scale; print means, having a scale indicator for indicating the position of said carrier relative to said first scale, for moving said carrier in the direction of said scale as indicated by said scale indicator and causing said print head to print the characters onto a print medium; display means for displaying a second scale indicating the carrier position in correspondence with said first scale as indicated by said scale indicator; and control means for controlling said print means such that said carrier is moved, and for controlling said display means such that said second scale of said display means is displayed in correspondence with the characters to be printed. | 11. A document processor comprising: input means for inputting character information; memory means for storing the character information input by said input means; a carrier having a print head mounted thereon; a first scale; print means, having a scale indicator for indicating the position of said carrier relative to said first scale, for moving said carrier in the direction of said scale as indicated by said scale indicator and causing said print head to print the characters onto a print medium; display means for displaying a second scale indicating the carrier position in correspondence with said first scale as indicated by said scale indicator; and control means for controlling said print means such that said carrier is moved, and for controlling said display means such that said second scale of said display means is displayed in correspondence with the characters to be printed. 15. A document processor according to claim 11, further comprising means for setting a print character unit, wherein, in response to the print character unit set by said setting means, said control means controls said print means and said display means such that the characters are printed and displayed. | 0.548961 |
9,092,422 | 3 | 5 | 3. The method of claim 2 , where sampling the category label and the topic comprises sampling the category label and the topic from a distribution that satisfies: P ( u d , i = c , z d , i = k ❘ w d , i = v , w d , - i , z d , - i , u d , - i , y d , α , β ) = C v , k WT + β ∑ v ′ = 1 V C v , k WT + V β C k , c TC + α ∑ k ′ = 1 K C k , c TC + K α ; where u d,i is a category label; c is a particular category; z d,i is a topic; k is a particular topic; w d,i is a sequence of one or more words; v is a particular sequence of one or more words; C v,k WT is a number of times that topic k is assigned to sequence v , not including a current instance of sampling i; C k,c TC is a number of times that topic k is assigned to category c, not including the current instance of sampling i; α is a constant; β is a constant; and d is a document. | 3. The method of claim 2 , where sampling the category label and the topic comprises sampling the category label and the topic from a distribution that satisfies: P ( u d , i = c , z d , i = k ❘ w d , i = v , w d , - i , z d , - i , u d , - i , y d , α , β ) = C v , k WT + β ∑ v ′ = 1 V C v , k WT + V β C k , c TC + α ∑ k ′ = 1 K C k , c TC + K α ; where u d,i is a category label; c is a particular category; z d,i is a topic; k is a particular topic; w d,i is a sequence of one or more words; v is a particular sequence of one or more words; C v,k WT is a number of times that topic k is assigned to sequence v , not including a current instance of sampling i; C k,c TC is a number of times that topic k is assigned to category c, not including the current instance of sampling i; α is a constant; β is a constant; and d is a document. 5. The method of claim 3 , where the determining the first and second probabilities includes: calculating the conditional probabilities that the topic is k given that the category label is c, the sequence is v given that the topic is k, the category label is c given that the topic is k, and the topic is k given that the sequence is v. | 0.60095 |
10,165,307 | 1 | 6 | 1. A computer-implemented method, comprising computer-executable instructions that, when executed by a hardware processor, cause the hardware processor to perform acts of: accessing information related to an event; identifying a named entity and an associated entity attribute from the information related to the event, the associated entity attribute including an entity type and an entity popularity parameter, wherein the entity type includes at least one of an organization, person, or location, and the entity popularity parameter defines at least a popularity of the named entity in the information related to the event; accessing trending information based on the named entity and the associated entity attribute; collecting, by using the trending information, training data for identification of one or more entities in a video related to the event, wherein the training data is image data of at least one entity likely associated with the event; training a model using the training data, to learn features of the one or more entities, while presenting the video; performing recognition processing of the one or more entities in the video to identify the one or more entities while the video is being presented, wherein the recognition processing is performed using the trained model; performing a search to retrieve content relevant to the one or more entities identified by the recognition processing; and presenting, in real-time during presenting of the video, the content relevant to the one or more entities identified. | 1. A computer-implemented method, comprising computer-executable instructions that, when executed by a hardware processor, cause the hardware processor to perform acts of: accessing information related to an event; identifying a named entity and an associated entity attribute from the information related to the event, the associated entity attribute including an entity type and an entity popularity parameter, wherein the entity type includes at least one of an organization, person, or location, and the entity popularity parameter defines at least a popularity of the named entity in the information related to the event; accessing trending information based on the named entity and the associated entity attribute; collecting, by using the trending information, training data for identification of one or more entities in a video related to the event, wherein the training data is image data of at least one entity likely associated with the event; training a model using the training data, to learn features of the one or more entities, while presenting the video; performing recognition processing of the one or more entities in the video to identify the one or more entities while the video is being presented, wherein the recognition processing is performed using the trained model; performing a search to retrieve content relevant to the one or more entities identified by the recognition processing; and presenting, in real-time during presenting of the video, the content relevant to the one or more entities identified. 6. The method of claim 1 , wherein the accessing of the information accesses the information from social media networks and according to a predetermined time window relative to the event. | 0.624498 |
7,562,343 | 11 | 12 | 11. The method of claim 10 , wherein generating proposals comprises: generating proposals from the last matching token; and adding the proposals to a proposal vector. | 11. The method of claim 10 , wherein generating proposals comprises: generating proposals from the last matching token; and adding the proposals to a proposal vector. 12. The method or claim 11 , wherein proposal vectors are generated from multiple cursor engines parsing different parts of the program statements; concatenating the proposal vectors to create a combined proposal vector that is returned; matching the combined proposal vector to determine an image; displaying a window containing the determined image from which the user select a keyword, identifier or constant to continue entry of the partial program statement. | 0.5 |
8,200,780 | 1 | 8 | 1. A computer-implemented method comprising: for entries that have been declared in a form and that identify available connections to data repositories and fields of the form that are associated with the connections, enabling a one-to-many mapping from fields in the form to one or more data repositories using declarative statements that specify a task to be performed, but not how the task is to be performed; inspecting the entries to identify a field from among the fields of the form associated with first and second connections from among the available connections identified by the entries; importing first data from the first connection; associating the imported first data with the field from among the fields of the form; exporting the first data associated with the field from among the fields of the form to the second connection; importing second data, different from the first data associated with the field from among the fields of the form, from the second connection; disassociating the first data from the field from among the fields of the form; and associating the imported second data with the field from among the fields of the form. | 1. A computer-implemented method comprising: for entries that have been declared in a form and that identify available connections to data repositories and fields of the form that are associated with the connections, enabling a one-to-many mapping from fields in the form to one or more data repositories using declarative statements that specify a task to be performed, but not how the task is to be performed; inspecting the entries to identify a field from among the fields of the form associated with first and second connections from among the available connections identified by the entries; importing first data from the first connection; associating the imported first data with the field from among the fields of the form; exporting the first data associated with the field from among the fields of the form to the second connection; importing second data, different from the first data associated with the field from among the fields of the form, from the second connection; disassociating the first data from the field from among the fields of the form; and associating the imported second data with the field from among the fields of the form. 8. The method of claim 1 , wherein the entries comprise: one or more connect elements to indicate if the field from among the fields of the form provides input, output, or both for at least one of the available connections associated with the field from among the fields of the form; and a connection set comprising the at least one of the available connections. | 0.5 |
8,521,755 | 13 | 14 | 13. A non-transitory computer readable medium having stored thereon a computer executable instructions for specifying a new Online Analytical Processing (OLAP) cube from an OLAP cube template, the computer executable instructions, when executed cause a computer system to implement a method comprising: determining the OLAP cube template; retrieving a corresponding template metadata file, the template metadata file including metadata defining the structure of the OLAP cube template; receiving rules for data access, storing the rules, and determining, based on the rules, whether a user has access to a dimension or a level in the dimension in the new OLAP cube, and the rules specify modifiable aspects of dimensions of the new OLAP cube, wherein the rules include a rule to specify that predetermined levels of the dimension must stay grouped in a view; creating a base metadata file from the template metadata file; generating viable options for modifying metadata in the base metadata file to define the new OLAP cube, wherein the viable options for modifying metadata in the base metadata file conforms with rules; presenting the viable options to the user; receiving input from the user indicating a modification to the metadata in the base metadata file based on the presented viable options; and storing the modified base metadata file as a new metadata file defining the new OLAP cube. | 13. A non-transitory computer readable medium having stored thereon a computer executable instructions for specifying a new Online Analytical Processing (OLAP) cube from an OLAP cube template, the computer executable instructions, when executed cause a computer system to implement a method comprising: determining the OLAP cube template; retrieving a corresponding template metadata file, the template metadata file including metadata defining the structure of the OLAP cube template; receiving rules for data access, storing the rules, and determining, based on the rules, whether a user has access to a dimension or a level in the dimension in the new OLAP cube, and the rules specify modifiable aspects of dimensions of the new OLAP cube, wherein the rules include a rule to specify that predetermined levels of the dimension must stay grouped in a view; creating a base metadata file from the template metadata file; generating viable options for modifying metadata in the base metadata file to define the new OLAP cube, wherein the viable options for modifying metadata in the base metadata file conforms with rules; presenting the viable options to the user; receiving input from the user indicating a modification to the metadata in the base metadata file based on the presented viable options; and storing the modified base metadata file as a new metadata file defining the new OLAP cube. 14. The non-transitory computer readable medium of claim 13 , wherein the modification includes a modification to at least one of a hierarchy of a dimension and an order of categories of the dimension. | 0.799801 |
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