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9,055,074 | 1 | 5 | 1. A method for aggregating social media content items that are relevant to geographically definable locations, the method being implemented in a computer that includes one or more processors programmed with computer program instructions that, when executed by the one or more physical processors, programs the one or more physical processors to perform the method, the method comprising: obtaining, by the one or more physical processors, at least a first parameter that specifies one or more geographically definable locations; generating, by the one or more physical processors, a first request that specifies the one or more geographically definable locations in a first format used by a first social media content provider; generating, by the one or more physical processors, a second request that specifies the one or more geographically definable locations in a second format used by a second social media content provider; communicating, by the one or more physical processors, the first request to the first social media content provider; communicating, by the one or more physical processors, the second request to the second social media content provider; receiving, by the one or more physical processors, a first set of social media content items from the first social media content provider, wherein the first set of social media content items includes at least a first social media content item associated with information that indicates that the first social media content item is relevant to the one or more geographically definable locations; receiving, by the one or more physical processors, a second set of social media content items from the second social media content provider, wherein the second set of social media content items includes at least a second social media item associated with information that indicates that the second social media content item is relevant to the one or more geographically definable locations; and communicating, by the one or more physical processors, at least a portion of the first set of social media content items and at least a portion of the second set of social media content items. | 1. A method for aggregating social media content items that are relevant to geographically definable locations, the method being implemented in a computer that includes one or more processors programmed with computer program instructions that, when executed by the one or more physical processors, programs the one or more physical processors to perform the method, the method comprising: obtaining, by the one or more physical processors, at least a first parameter that specifies one or more geographically definable locations; generating, by the one or more physical processors, a first request that specifies the one or more geographically definable locations in a first format used by a first social media content provider; generating, by the one or more physical processors, a second request that specifies the one or more geographically definable locations in a second format used by a second social media content provider; communicating, by the one or more physical processors, the first request to the first social media content provider; communicating, by the one or more physical processors, the second request to the second social media content provider; receiving, by the one or more physical processors, a first set of social media content items from the first social media content provider, wherein the first set of social media content items includes at least a first social media content item associated with information that indicates that the first social media content item is relevant to the one or more geographically definable locations; receiving, by the one or more physical processors, a second set of social media content items from the second social media content provider, wherein the second set of social media content items includes at least a second social media item associated with information that indicates that the second social media content item is relevant to the one or more geographically definable locations; and communicating, by the one or more physical processors, at least a portion of the first set of social media content items and at least a portion of the second set of social media content items. 5. The method of claim 1 , further comprising: spatially arranging, by the one or more processors, at least the first social media content item and the second social media content item on a map display. | 0.897462 |
9,183,197 | 11 | 17 | 11. A system for translating word sequences in a source language to translations in a target language, the system comprising: a processor; and a memory storing: a word index comprising, for respective words of the language: the word stored at an index location in the word index, and a word mapping that identifies the index location of the word in the word index; a translation mapping identifying, for a word index sequence comprising at least two word indices, the translation of the words of the word sequence mapping to the respective index locations of the words of the word index sequence; and instructions that, when executed by the processor, provide a translator that, upon receiving a word sequence in the source language to be translated into the target language: for respective words of the word sequence, identifies the source index location of the word in the source word index; using the translation mapping, identifies a translation of the source index locations of the words of the word sequence, the translation comprising at least one target index location in the target word index; for respective target index locations, retrieves a translated word in the target language at the target index location in the target word index; and presents the translated words in the target language. | 11. A system for translating word sequences in a source language to translations in a target language, the system comprising: a processor; and a memory storing: a word index comprising, for respective words of the language: the word stored at an index location in the word index, and a word mapping that identifies the index location of the word in the word index; a translation mapping identifying, for a word index sequence comprising at least two word indices, the translation of the words of the word sequence mapping to the respective index locations of the words of the word index sequence; and instructions that, when executed by the processor, provide a translator that, upon receiving a word sequence in the source language to be translated into the target language: for respective words of the word sequence, identifies the source index location of the word in the source word index; using the translation mapping, identifies a translation of the source index locations of the words of the word sequence, the translation comprising at least one target index location in the target word index; for respective target index locations, retrieves a translated word in the target language at the target index location in the target word index; and presents the translated words in the target language. 17. The system of claim 11 wherein: the device includes a word mapping function configured to, for respective words, identify a word mapping value; and storing the word mapping of the word index includes: for respective words, using the word mapping function, compute the word mapping value; and store the word mapping as an association of the word mapping function and the word mapping location. | 0.744516 |
8,989,485 | 1 | 6 | 1. A method for detecting a junction in a received image of a line of text to update a junction list with descriptive data, the method comprising: creating a color histogram based on a number of color pixels in the received image of the line of text; detecting, based at least in part on the received image of the line of text, a rung within the received image of the line of text; identifying a horizontal position of the detected rung in the received image of the line of text; additionally identifying a gateway on the color histogram, wherein the identified gateway is associated with the detected rung; and updating the junction list with data including a description of the identified gateway. | 1. A method for detecting a junction in a received image of a line of text to update a junction list with descriptive data, the method comprising: creating a color histogram based on a number of color pixels in the received image of the line of text; detecting, based at least in part on the received image of the line of text, a rung within the received image of the line of text; identifying a horizontal position of the detected rung in the received image of the line of text; additionally identifying a gateway on the color histogram, wherein the identified gateway is associated with the detected rung; and updating the junction list with data including a description of the identified gateway. 6. The method of claim 1 , wherein identifying the gateway further comprises identifying a plateau on the created color histogram, wherein the plateau corresponds to a low level on the created color histogram. | 0.743873 |
7,784,026 | 2 | 4 | 2. The method of claim 1 wherein said data-descriptive metalanguage representation is configured into a tree structure. | 2. The method of claim 1 wherein said data-descriptive metalanguage representation is configured into a tree structure. 4. The method of claim 2 further including the step of: executing, by the processor, an algorithm to search said tree structure for said translatable content item. | 0.956833 |
8,515,212 | 13 | 16 | 13. A system, comprising: a first data store storing query data, the query data defining a plurality of queries; one or more processors that interact with the first data store and perform operations comprising: identifying a query defined by the query data; selecting training images for training an image relevance model, the training images comprising: a first image having a first relevance measure, for the query, that satisfies a first relevance threshold; and a second image having a second relevance measure, for a different query in the plurality of queries, that satisfies a second relevance threshold; for each of the training images, identifying content feature values, each content feature value representing a characteristic of an aspect of the training image; and training the image relevance model to generate relevance measures of content feature values of images to the query based on the content feature values of the training images, wherein the image relevance model comprises a vector of weights corresponding to the content feature values, the training comprising: initializing the vector of weights to default values; generating a first training score based on the image relevance model and the content feature values of the first image; generating a second training score based on the image relevance model and the content feature values of the second image; comparing the first training score and the second training score; in response to a difference between the first training score and the second training score not satisfying a training score margin, adjusting values of the vector of weights; determining whether a training condition has occurred; and repeating the selecting training images, the generating the first training score, the generating the second training score and the comparing when the training condition has not occurred. | 13. A system, comprising: a first data store storing query data, the query data defining a plurality of queries; one or more processors that interact with the first data store and perform operations comprising: identifying a query defined by the query data; selecting training images for training an image relevance model, the training images comprising: a first image having a first relevance measure, for the query, that satisfies a first relevance threshold; and a second image having a second relevance measure, for a different query in the plurality of queries, that satisfies a second relevance threshold; for each of the training images, identifying content feature values, each content feature value representing a characteristic of an aspect of the training image; and training the image relevance model to generate relevance measures of content feature values of images to the query based on the content feature values of the training images, wherein the image relevance model comprises a vector of weights corresponding to the content feature values, the training comprising: initializing the vector of weights to default values; generating a first training score based on the image relevance model and the content feature values of the first image; generating a second training score based on the image relevance model and the content feature values of the second image; comparing the first training score and the second training score; in response to a difference between the first training score and the second training score not satisfying a training score margin, adjusting values of the vector of weights; determining whether a training condition has occurred; and repeating the selecting training images, the generating the first training score, the generating the second training score and the comparing when the training condition has not occurred. 16. The system of claim 13 , wherein the one or more processors perform operations comprising assigning an image relevance score to each of a plurality of images based on the image relevance model and the content feature values of the images, the image relevance score being a relevancy measure of the image to the query. | 0.560274 |
7,738,778 | 19 | 24 | 19. A system for producing a multimedia summary of at least one multimedia stream, the summary comprising key elements selected from said at last one multimedia stream, the system comprising: a modality recognition and division (MRAD) module comprising a story segment identifier (SSI) module, an audio identifier (AI) module and a text identifier (TI) module, the MRAD module communicatively coupled to a first external source for receiving said at least one multimedia stream, the MRAD module communicatively coupled to a second external source for receiving said at least one multimedia stream, the MRAD module dividing said at least one multimedia stream into a video, an audio and a text sub-stream and outputting said video, audio and text sub-streams to a key element identifier (KEI) module, the KEI module comprising a feature extraction (FE) module and an importance value (IV) module for identifying key elements from within said video, audio and text sub-streams and assigning importance values thereto, the KEI module communicatively coupled to a key element filter (KEF) for receiving the identified key elements and filtering said key elements that exceed a pre-determined threshold criteria, the KEF module communicatively coupled to a user profile filter (UPF) for receiving filtered key elements and further filtering said filtered key elements in accordance with a user profile, the UPF module communicatively coupled to a network and device constraint (NADC) module, said NADC module receiving said further filtered key elements and further filtering said further filtered key elements in accordance with network and/or user device constraints, the NADC module outputting a multimedia summary of said at least one multimedia stream which comprises key elements remaining after said further filtering in the NADC module. | 19. A system for producing a multimedia summary of at least one multimedia stream, the summary comprising key elements selected from said at last one multimedia stream, the system comprising: a modality recognition and division (MRAD) module comprising a story segment identifier (SSI) module, an audio identifier (AI) module and a text identifier (TI) module, the MRAD module communicatively coupled to a first external source for receiving said at least one multimedia stream, the MRAD module communicatively coupled to a second external source for receiving said at least one multimedia stream, the MRAD module dividing said at least one multimedia stream into a video, an audio and a text sub-stream and outputting said video, audio and text sub-streams to a key element identifier (KEI) module, the KEI module comprising a feature extraction (FE) module and an importance value (IV) module for identifying key elements from within said video, audio and text sub-streams and assigning importance values thereto, the KEI module communicatively coupled to a key element filter (KEF) for receiving the identified key elements and filtering said key elements that exceed a pre-determined threshold criteria, the KEF module communicatively coupled to a user profile filter (UPF) for receiving filtered key elements and further filtering said filtered key elements in accordance with a user profile, the UPF module communicatively coupled to a network and device constraint (NADC) module, said NADC module receiving said further filtered key elements and further filtering said further filtered key elements in accordance with network and/or user device constraints, the NADC module outputting a multimedia summary of said at least one multimedia stream which comprises key elements remaining after said further filtering in the NADC module. 24. The system of claim 19 , wherein the NADC module is communicatively connected to an external network coupled to a user device. | 0.877127 |
8,478,581 | 1 | 8 | 1. A system for representing natural languages in a common machine-readable form, called interlingua, comprising a lexicon and a grammar, where: a. said lexicon comprises: 1. a system of specifically designed classification codes for prototypical words of noun, adjective, verb, and adverb respectively, 2. virtual codes for each kind of derived words, 3. a system of synonymous feature set for synonymous word and metaphorical feature set for metaphorical sense of word, b. said grammar comprises: 1. a system of classification code and composition for prototypical clause, 2. a system of time feature set, space feature set, and adverb feature set, 3. a system of variational feature set for variational clause and synonymous feature set for synonymous clause, and 4. a system of metaphor processing procedure, and c. said prototypical verb word and said prototypical clause comprising said prototypical verb word share the same classification code, whereby a sense of a word of a language will be: a. matched to a unique interlingua classification code if it is prototypical, or b. if it is synonymous to a prototypical word then matched to the same classification code of said prototypical word plus a feature of synonymy, or c. if it is a derived word then matched to a virtual code plus the interlingua classification code of its stem word and a feature of derivation, or d. if it is a fixed extended sense then matched to an interlingua classification code of a word corresponding to said extended sense plus a feature of extension, or e. if it is a multiple use case then matched to an interlingua classification code of a word corresponding to said multiple use plus a feature of multiple use, or f. if it is used in a special clause or idiom then treated according to the corresponding rule governing said special clause or idiom respectively, and whereby a clause of a language will be: a. matched to a unique interlingua classification code of its comprised verb if both said clause and said verb are prototypical, or b. if said clause is variational and its comprised verb is prototypical then matched to the same interlingua classification code of its associated prototypical clause plus a feature of variation, or c. if said clause is prototypical and its comprised verb is not prototypical then matched to an interlingua classification code of a verb corresponding to said verb according to said verb being derived, fixed extended, or multiple use plus a corresponding feature of said verb, or d. if said clause is variational and its comprised verb is not prototypical then matched to an interlingua classification code of a verb corresponding to said verb according to said verb being derived, fixed extended, or multiple use plus a corresponding feature of said verb and a variational feature of said clause, or e. if said clause is a special clause then matched to an interlingua classification code for special clause plus a feature of special clause. | 1. A system for representing natural languages in a common machine-readable form, called interlingua, comprising a lexicon and a grammar, where: a. said lexicon comprises: 1. a system of specifically designed classification codes for prototypical words of noun, adjective, verb, and adverb respectively, 2. virtual codes for each kind of derived words, 3. a system of synonymous feature set for synonymous word and metaphorical feature set for metaphorical sense of word, b. said grammar comprises: 1. a system of classification code and composition for prototypical clause, 2. a system of time feature set, space feature set, and adverb feature set, 3. a system of variational feature set for variational clause and synonymous feature set for synonymous clause, and 4. a system of metaphor processing procedure, and c. said prototypical verb word and said prototypical clause comprising said prototypical verb word share the same classification code, whereby a sense of a word of a language will be: a. matched to a unique interlingua classification code if it is prototypical, or b. if it is synonymous to a prototypical word then matched to the same classification code of said prototypical word plus a feature of synonymy, or c. if it is a derived word then matched to a virtual code plus the interlingua classification code of its stem word and a feature of derivation, or d. if it is a fixed extended sense then matched to an interlingua classification code of a word corresponding to said extended sense plus a feature of extension, or e. if it is a multiple use case then matched to an interlingua classification code of a word corresponding to said multiple use plus a feature of multiple use, or f. if it is used in a special clause or idiom then treated according to the corresponding rule governing said special clause or idiom respectively, and whereby a clause of a language will be: a. matched to a unique interlingua classification code of its comprised verb if both said clause and said verb are prototypical, or b. if said clause is variational and its comprised verb is prototypical then matched to the same interlingua classification code of its associated prototypical clause plus a feature of variation, or c. if said clause is prototypical and its comprised verb is not prototypical then matched to an interlingua classification code of a verb corresponding to said verb according to said verb being derived, fixed extended, or multiple use plus a corresponding feature of said verb, or d. if said clause is variational and its comprised verb is not prototypical then matched to an interlingua classification code of a verb corresponding to said verb according to said verb being derived, fixed extended, or multiple use plus a corresponding feature of said verb and a variational feature of said clause, or e. if said clause is a special clause then matched to an interlingua classification code for special clause plus a feature of special clause. 8. A system for using a computer to convert a text of a natural language into a coded text of the interlingua representation of claim 1 , this part of said system called input module of said language, and conversely to convert a coded text of said interlingua representation into a text of said language, this part of said system called output module of said language, said system called interlingua engine and said language called being incorporated in said interlingua engine, comprising: a. a computer capable of doing word-processing of said language, b. said interlingua representation stored in said computer, c. a matching lexicon of said language compiled in accordance with said interlingua representation and stored in said computer, d. a database of clause structure list with respect to said feature of variation of said interlingua representation, compiled for said language and stored in said computer, e. a database of synonymous clause list with respect to said feature of synonymy of said interlingua representation, compiled for said language and stored in said computer, f. a database of semantic rule of structure, compiled for said interlingua representation, updated for said language, and stored in said computer, g. a database of semantic code group compiled for said interlingua representation, updated for said language, and stored in said computer, h. a database of metaphor processing procedure compiled for said system of metaphor processing procedure, updated for said language, and stored in said computer, i. supplementary knowledge databases in the format of said interlingua representation and stored in said computer, and j. computer programs for said input and output modules of said language, stored in said computer and based on said interlingua representation, on said databases of clause structure list, synonymous clause list, semantic rule of structure, semantic code group, and metaphor processing procedure, and on said knowledge databases, whereby said input module will convert a text of said language into said interlingua representation by solving the two fundamental problems of ambiguity and matching senses, where the ambiguity problem is solved with the aid of said databases, in particular said databases of clause structure list, semantic rule of structure, and semantic code group, and the problem of matching senses is solved by said interlingua representation and said databases, in particular said database of metaphor processing procedure, and said output module will convert an interlingua coded text into a text of said language by first generating a text using said database of clause structure list and then improving the readability of the text with the aid of said databases, in particular said database of synonymous clause list. | 0.635593 |
6,081,665 | 24 | 27 | 24. The RTVMM of claim 12 wherein the implementing step comprises the steps: partitioning memory into at least three demi-spaces, at least one of the demi-spaces being a static space excluded from the garbage collection process; designating two of the demi-spaces as to-space and from-space at the beginning of a garbage collection cycle, live objects residing in from-space subsequently being copied into to-space; designating the remaining demi-spaces as mark-and-sweep spaces at the beginning of a garbage collection cycle, the mark-and-sweep spaces being garbage collected using a mark-and-sweep technique. | 24. The RTVMM of claim 12 wherein the implementing step comprises the steps: partitioning memory into at least three demi-spaces, at least one of the demi-spaces being a static space excluded from the garbage collection process; designating two of the demi-spaces as to-space and from-space at the beginning of a garbage collection cycle, live objects residing in from-space subsequently being copied into to-space; designating the remaining demi-spaces as mark-and-sweep spaces at the beginning of a garbage collection cycle, the mark-and-sweep spaces being garbage collected using a mark-and-sweep technique. 27. The RTVMM of claim 24 wherein the implementing step comprises the step: including a "signature pointer" field for each object in memory, the "signature pointer" field containing a pointer to a structure that represents the internal organization of the O-OPL data within the object. | 0.925704 |
10,089,639 | 1 | 3 | 1. A computer implemented method for capturing user data across interactions using a unique user identification, the method comprising: providing a processor for implementing a user management module, said user management module receiving a request for a service from the user; said user management module creating a plurality of linkages across a plurality of channels of interaction and a plurality of devices and within a session and across a plurality of sessions, wherein the plurality of linkages is made probabilistically based on machine learning and statistical models driven by behavior and attributes of said user's journeys on the plurality of channels including a web-based channel, a voice-based channel, and a text-based channel; said user management module either querying said user for at least one personal identifier or automatically identifying at least one of a plurality of unique user identifiers when said user interacts with said user management module, wherein the plurality of unique user identifiers is created, captured, and passed among the plurality of channels of interaction and across a plurality of organizations with which said user interacts; said user management module generating a unique ID for said user when said user management module receives said at least one personal identifier from the user or identifies the at least one unique user identifier, wherein said unique ID is common for said user across all of the plurality of channels of interaction; said user management module querying said user regarding the service that said user is requesting once said user has been identified; said user management module tracking said user's interaction journey by using the plurality of unique user identifiers to facilitate collecting data across a plurality of said channels and from a plurality of data sources, and storing relevant information of said interaction journey including any of a time of interaction, a channel of interaction, content or nature of interaction, or user location of interaction in a database; said user management module using said relevant information of said interaction journey for any of building, updating, and modifying a continuously generated user profile that is linked to said unique ID; evaluating said relevant information of said interaction journey stored in said user profile to personalize the service or access to the service by the user based on the user profile that is linked to said unique ID; and said user management module routing the user to the service over one of said plurality of channels based on the user profile that is linked to said unique ID. | 1. A computer implemented method for capturing user data across interactions using a unique user identification, the method comprising: providing a processor for implementing a user management module, said user management module receiving a request for a service from the user; said user management module creating a plurality of linkages across a plurality of channels of interaction and a plurality of devices and within a session and across a plurality of sessions, wherein the plurality of linkages is made probabilistically based on machine learning and statistical models driven by behavior and attributes of said user's journeys on the plurality of channels including a web-based channel, a voice-based channel, and a text-based channel; said user management module either querying said user for at least one personal identifier or automatically identifying at least one of a plurality of unique user identifiers when said user interacts with said user management module, wherein the plurality of unique user identifiers is created, captured, and passed among the plurality of channels of interaction and across a plurality of organizations with which said user interacts; said user management module generating a unique ID for said user when said user management module receives said at least one personal identifier from the user or identifies the at least one unique user identifier, wherein said unique ID is common for said user across all of the plurality of channels of interaction; said user management module querying said user regarding the service that said user is requesting once said user has been identified; said user management module tracking said user's interaction journey by using the plurality of unique user identifiers to facilitate collecting data across a plurality of said channels and from a plurality of data sources, and storing relevant information of said interaction journey including any of a time of interaction, a channel of interaction, content or nature of interaction, or user location of interaction in a database; said user management module using said relevant information of said interaction journey for any of building, updating, and modifying a continuously generated user profile that is linked to said unique ID; evaluating said relevant information of said interaction journey stored in said user profile to personalize the service or access to the service by the user based on the user profile that is linked to said unique ID; and said user management module routing the user to the service over one of said plurality of channels based on the user profile that is linked to said unique ID. 3. The method of claim 1 , wherein said unique ID comprises any of: a unique alphanumeric user name; a unique telephone number that is specifically assigned for use by said user across any organization and any channel of communication; and a unique Web link that is specifically assigned for use by said user and wherein a landing page of said Web link is customized for said user. | 0.501309 |
8,457,416 | 11 | 12 | 11. The system as recited in claim 10 , wherein providing the first and the second image representation sets representing the first word and the second word comprises: conducting an image search using the respective first word or second word as query word; and selecting a third plurality of images from search results. | 11. The system as recited in claim 10 , wherein providing the first and the second image representation sets representing the first word and the second word comprises: conducting an image search using the respective first word or second word as query word; and selecting a third plurality of images from search results. 12. The system as recited in claim 11 , wherein the image search is conducted on the Internet using an image search engine. | 0.965116 |
7,537,170 | 19 | 21 | 19. A method comprising: using a printing device: i) providing a first set of print structures on a surface with first ink, and ii) providing a second set of print structures on the surface with optical variable ink, the second set of print structures comprises breaks in one or more lines, with the second set of print structures conveying a machine-readable plural-bit auxiliary signal, the second set of print structure are provided to cooperate with the first set of print structures so that at a first observation angle the first set of print structures and the second set of print structures appear to provide a first visibly perceptible feature, and at a second observation angle the second set of print structures appear less observable so that the first set of print structures and the second set of print structures provide a second visibly perceptible feature. | 19. A method comprising: using a printing device: i) providing a first set of print structures on a surface with first ink, and ii) providing a second set of print structures on the surface with optical variable ink, the second set of print structures comprises breaks in one or more lines, with the second set of print structures conveying a machine-readable plural-bit auxiliary signal, the second set of print structure are provided to cooperate with the first set of print structures so that at a first observation angle the first set of print structures and the second set of print structures appear to provide a first visibly perceptible feature, and at a second observation angle the second set of print structures appear less observable so that the first set of print structures and the second set of print structures provide a second visibly perceptible feature. 21. The method of claim 19 where the breaks in one or more lines are due to the appearance of the optical variable ink at the second observation angle. | 0.582873 |
9,064,210 | 10 | 13 | 10. A method comprising the steps of: processing data associated with a security information and event management system in a computational semantic parser to generate a plurality of logical descriptors, the data comprising log data of the security information and event management system; generating a plurality of behavioral security descriptors based at least in part on at least a subset of the logical descriptors; and utilizing the behavioral security descriptors to generate one or more security alerts; wherein the processing step comprises: syntactically decomposing at least a portion of the log data into component elements comprising respective atomic syntactic units; assigning lexical meanings to the component elements utilizing metadata associated with the component elements and a lexicon of syntactic types the metadata comprising position information and attributes associated with the atomic syntactic units; assigning context denotation information to the component elements; and applying semantic recomposition to generate a given logical descriptor based on at least one combinatorial tree having nodes associated with respective Ones of the component elements and a tree structure determined at least in part using the assigned lexical meanings and context denotation information. | 10. A method comprising the steps of: processing data associated with a security information and event management system in a computational semantic parser to generate a plurality of logical descriptors, the data comprising log data of the security information and event management system; generating a plurality of behavioral security descriptors based at least in part on at least a subset of the logical descriptors; and utilizing the behavioral security descriptors to generate one or more security alerts; wherein the processing step comprises: syntactically decomposing at least a portion of the log data into component elements comprising respective atomic syntactic units; assigning lexical meanings to the component elements utilizing metadata associated with the component elements and a lexicon of syntactic types the metadata comprising position information and attributes associated with the atomic syntactic units; assigning context denotation information to the component elements; and applying semantic recomposition to generate a given logical descriptor based on at least one combinatorial tree having nodes associated with respective Ones of the component elements and a tree structure determined at least in part using the assigned lexical meanings and context denotation information. 13. The method of claim 10 wherein the utilizing step comprises generating a given one of the security alerts upon detection of an event having particular characteristics associated with one or more of the behavioral security descriptors. | 0.897237 |
9,613,618 | 6 | 7 | 6. The method as claimed in claim 2 , wherein determining the language of the segment of the voice input signal based on the context information comprises: determining whether a history of recognizing the segment of the voice input signal exists in the non-primary language database; and immediately recognizing, by the apparatus for recognizing the voice input signal, the language of the segment of the voice input signal based on a result of the recognition corresponding to the history of recognizing the segment of the voice input, when the history of recognizing the segment of the voice input signal exists in the non-primary language database. | 6. The method as claimed in claim 2 , wherein determining the language of the segment of the voice input signal based on the context information comprises: determining whether a history of recognizing the segment of the voice input signal exists in the non-primary language database; and immediately recognizing, by the apparatus for recognizing the voice input signal, the language of the segment of the voice input signal based on a result of the recognition corresponding to the history of recognizing the segment of the voice input, when the history of recognizing the segment of the voice input signal exists in the non-primary language database. 7. The method as claimed in claim 6 , further comprising receiving the non-primary language database from an outside. | 0.968068 |
9,563,399 | 31 | 40 | 31. A computer system for compiling a pattern into a non-deterministic finite automata (NFA) graph, the system comprising: a memory; and a processor, the processor coupled to the memory and configured to examine the pattern for a plurality of elements and a plurality of node types, each node type corresponding with an element, each element of the pattern to be matched at least zero times, the element representing a character, character class or string; and wherein the processor is further configured to generate a plurality of nodes of the NFA graph, each node of the plurality of nodes configured to match with one of the plurality of elements and store the node type corresponding to the element, a next node address in the NFA graph, a count value, and the element, wherein the next node address and the count value are applicable as a function of the node type stored and wherein the plurality of nodes generated enable a graph walk engine to identify the pattern in a payload with less nodes relative to another NFA graph representing the pattern and employed by the graph walk engine to identify the pattern in the payload. | 31. A computer system for compiling a pattern into a non-deterministic finite automata (NFA) graph, the system comprising: a memory; and a processor, the processor coupled to the memory and configured to examine the pattern for a plurality of elements and a plurality of node types, each node type corresponding with an element, each element of the pattern to be matched at least zero times, the element representing a character, character class or string; and wherein the processor is further configured to generate a plurality of nodes of the NFA graph, each node of the plurality of nodes configured to match with one of the plurality of elements and store the node type corresponding to the element, a next node address in the NFA graph, a count value, and the element, wherein the next node address and the count value are applicable as a function of the node type stored and wherein the plurality of nodes generated enable a graph walk engine to identify the pattern in a payload with less nodes relative to another NFA graph representing the pattern and employed by the graph walk engine to identify the pattern in the payload. 40. The system of claim 31 , wherein the plurality of node types includes a variable count node type and the examining includes examining the pattern for the variable count node type, and wherein examining the pattern for the variable count node type includes determining whether a portion of the pattern indicates matching for the element a variable number of times. | 0.749659 |
7,590,535 | 14 | 17 | 14. The method of claim 13 , wherein the current editing mode comprises a cursor mode, and wherein selecting the word comprises locating a word relative to a cursor position. | 14. The method of claim 13 , wherein the current editing mode comprises a cursor mode, and wherein selecting the word comprises locating a word relative to a cursor position. 17. The method of claim 14 , wherein the word relative to the cursor position comprises determining if a cursor that indicates the cursor position is placed on a word having alternates associated therewith, and wherein determining if the cursor is placed on a word having alternates associated therewith comprises moving a pointer to the beginning of the word. | 0.906054 |
8,938,455 | 18 | 25 | 18. A method comprising: maintaining a URL; identifying, using at least one processor and without user intervention, a factor with which to analyze the URL; analyzing the URL based on the factor, wherein analyzing the URL based on the factor comprises comparing the directory path to a list of ISP client directory paths to determine if the directory path is a known ISP client directory path; determining, based on the analysis of the URL, whether the URL is a root URL or a leaf URL; updating a URL index to reflect the determination of whether the URL is a root URL or a leaf URL; facilitating one or more queries of the URL index; and providing, in response to the one or more queries, one or more results that reflect the determination of whether the URL is a root URL or a leaf URL. | 18. A method comprising: maintaining a URL; identifying, using at least one processor and without user intervention, a factor with which to analyze the URL; analyzing the URL based on the factor, wherein analyzing the URL based on the factor comprises comparing the directory path to a list of ISP client directory paths to determine if the directory path is a known ISP client directory path; determining, based on the analysis of the URL, whether the URL is a root URL or a leaf URL; updating a URL index to reflect the determination of whether the URL is a root URL or a leaf URL; facilitating one or more queries of the URL index; and providing, in response to the one or more queries, one or more results that reflect the determination of whether the URL is a root URL or a leaf URL. 25. The method of claim 18 , wherein if the URL is determined to be a root URL, the method further comprises: retrieving an electronic document associated with the root URL; and identifying geographic location information from the electronic document. | 0.679028 |
7,953,590 | 9 | 10 | 9. A non-transitory computer readable medium comprising a computer readable program, wherein the computer readable program when executed on a computer causes the computer to perform the steps of: designating separate input channels for each of a plurality of speakers; assigning an expected language to each of the input channels; in response to speech from a first channel in a first language, translating the speech from the first channel to a second language; and in response to speech from a second channel in a second language, translating the speech from the second channel to the first language; wherein the steps of translating the speech from the first channel and translating the speech from the second channel are performed concurrently; and monitoring each of the input channels to determine whether speech received by a particular input channel is in a language that matches the expected language assigned to the particular input channel. | 9. A non-transitory computer readable medium comprising a computer readable program, wherein the computer readable program when executed on a computer causes the computer to perform the steps of: designating separate input channels for each of a plurality of speakers; assigning an expected language to each of the input channels; in response to speech from a first channel in a first language, translating the speech from the first channel to a second language; and in response to speech from a second channel in a second language, translating the speech from the second channel to the first language; wherein the steps of translating the speech from the first channel and translating the speech from the second channel are performed concurrently; and monitoring each of the input channels to determine whether speech received by a particular input channel is in a language that matches the expected language assigned to the particular input channel. 10. The non-transitory computer readable medium as recited in claim 9 , further comprising in response to speech from the first channel in the first language, outputting the speech from the first channel in the second language. | 0.622924 |
8,095,582 | 4 | 22 | 4. The method of claim 1 further comprising: using terms from the title and display text corresponding to objects skipped by a user as negative subordinate keywords; and reducing the ranking of search results objects containing said negative subordinate keywords. | 4. The method of claim 1 further comprising: using terms from the title and display text corresponding to objects skipped by a user as negative subordinate keywords; and reducing the ranking of search results objects containing said negative subordinate keywords. 22. The method of claim 4 further comprising: assigning weights to said negative subordinate keywords, such that search result objects having higher weighted subordinate keywords are given decreased preference in the ranking. | 0.961643 |
7,996,379 | 19 | 43 | 19. The system of claim 11 , further comprising instructions to: identify a plurality of terms in a first document; determine a score for each of the identified terms; select a subset of the identified terms based on the scores of the identified terms; and identify local term relationships among the selected subset of terms. | 19. The system of claim 11 , further comprising instructions to: identify a plurality of terms in a first document; determine a score for each of the identified terms; select a subset of the identified terms based on the scores of the identified terms; and identify local term relationships among the selected subset of terms. 43. The system of claim 19 , wherein selecting a subset of the identified terms based on the scores of the identified terms includes selecting a number of the highest scoring terms. | 0.939098 |
8,385,955 | 1 | 6 | 1. A method, comprising: a computer system receiving, via a web interface, a subscription preference relating to one or more message topics and a telephone number corresponding to a portable communication device capable of receiving text messages; in response to receiving the telephone number, the computer system generating an authorization code and causing a text message including the authorization code to be sent to the telephone number; receiving at the computer system, via the web interface, input that includes the authorization code; and in response to authenticating the authorization code, the computer system storing the subscription preference relating to the one or more message topics on a non-transitory computer readable storage medium, wherein the stored subscription preference indicates the computer system has permission to cause one or more text messages that include content directed to the one or more message topics to be sent to the telephone number corresponding to the portable communication device. | 1. A method, comprising: a computer system receiving, via a web interface, a subscription preference relating to one or more message topics and a telephone number corresponding to a portable communication device capable of receiving text messages; in response to receiving the telephone number, the computer system generating an authorization code and causing a text message including the authorization code to be sent to the telephone number; receiving at the computer system, via the web interface, input that includes the authorization code; and in response to authenticating the authorization code, the computer system storing the subscription preference relating to the one or more message topics on a non-transitory computer readable storage medium, wherein the stored subscription preference indicates the computer system has permission to cause one or more text messages that include content directed to the one or more message topics to be sent to the telephone number corresponding to the portable communication device. 6. The method of claim 1 , further comprising receiving, via the web interface, an email address that is associated with a user having the subscription preference. | 0.835685 |
9,311,528 | 1 | 4 | 1. A method for teaching gestures performable on a multi touch interface, the method comprising: presenting a display on a touch sensing touch screen, the display comprising a first display area and a second display area, the second display area comprising a touch monitor window graphically distinct from and in an area of the touch screen non-overlapping with the first display area; detecting a practice gesture currently being performed on the touch sensing touch screen in the first display area; and presenting in the touch monitor window an interactive feedback mechanism that indicates an accuracy of the practice gesture currently being performed. | 1. A method for teaching gestures performable on a multi touch interface, the method comprising: presenting a display on a touch sensing touch screen, the display comprising a first display area and a second display area, the second display area comprising a touch monitor window graphically distinct from and in an area of the touch screen non-overlapping with the first display area; detecting a practice gesture currently being performed on the touch sensing touch screen in the first display area; and presenting in the touch monitor window an interactive feedback mechanism that indicates an accuracy of the practice gesture currently being performed. 4. The method of claim 1 wherein the touch monitor window is displayed separately from the first display area. | 0.916667 |
7,536,673 | 12 | 13 | 12. The framework of claim 7 , wherein the processing engine is further operable to track business object instances. | 12. The framework of claim 7 , wherein the processing engine is further operable to track business object instances. 13. The framework of claim 12 , wherein the business object instances are tracked in a running object table. | 0.967391 |
9,225,679 | 1 | 2 | 1. A system comprising: a server in communication with a vehicle computing system (VCS) via a transceiver and configured to: in response to an electronic-mail message identifying the VCS, transmit information from the message received at the server to an application on the VCS, the information pre-specified for utilization by the application and associated with a predefined category identified via a classification model classifying an element corresponding to the predefined category in text of the message. | 1. A system comprising: a server in communication with a vehicle computing system (VCS) via a transceiver and configured to: in response to an electronic-mail message identifying the VCS, transmit information from the message received at the server to an application on the VCS, the information pre-specified for utilization by the application and associated with a predefined category identified via a classification model classifying an element corresponding to the predefined category in text of the message. 2. The system of claim 1 , wherein the element is a word identified as navigation data. | 0.788835 |
8,095,476 | 13 | 22 | 13. A memory device having stored thereon instructions that, when executed, result in: receiving entries in a plurality of web page fields of a single web page form; inspecting the received entries; and according to the inspection, causing a first level of on-line support to be provided for a first one of the plurality of web page fields responsive to the inspection and causing a second different level of on-line support to be provided responsive to the inspection for a second one of the plurality of web page fields; wherein the first level of on-line support includes human support, and wherein the second different level of on-line support does not include human support. | 13. A memory device having stored thereon instructions that, when executed, result in: receiving entries in a plurality of web page fields of a single web page form; inspecting the received entries; and according to the inspection, causing a first level of on-line support to be provided for a first one of the plurality of web page fields responsive to the inspection and causing a second different level of on-line support to be provided responsive to the inspection for a second one of the plurality of web page fields; wherein the first level of on-line support includes human support, and wherein the second different level of on-line support does not include human support. 22. The memory device according to claim 13 , further comprising instructions that, when executed, result in: saving information from a plurality of web page fields of a previously opened web page form in a prior on-line web-session; detecting a same user opening up the current web page form; and filling in the plurality of web page fields in the currently opened web page form with the saved information. | 0.751526 |
9,971,760 | 1 | 5 | 1. A computer program product for parallelizing document processing in an information handling system, the computer program product comprising: one or more computer readable storage media and program instructions stored on the one or more computer readable storage media, executable by a computer processor that can perform reordering operations when executing program instructions in parallel, the program instructions comprising: program instructions to receive a document, wherein the document includes text content, given a particular granularity scope; program instructions to extract information from the text content, utilizing natural language processing and semantic analysis, to form tokenized semantic partitions, comprising a plurality of sub-documents, wherein: the tokenized semantic partitions each have a particular data type; the plurality of sub-documents are annotated to represent an order of occurrence within the document; and the annotated plurality of sub-documents allows reconstruction to the particular granularity scope at any point during the extraction; program instructions to reconstruct the document by scheduling a process for the annotated plurality of sub-documents, wherein: the scheduling drives each of the annotated sub-documents in parallel by using a memory barrier to enforce an ordering constraint on the annotated plurality of sub-documents based on a data dependent scheduling order using the data types of the sub-documents and a type dependency flow graph for the annotated sub-documents given the particular granularity scope, the dependency flow graph comprises information about which data types are dependent on other data types in a dependency order, and by using the type dependency flow graph, the sub-documents that have data types that do not depend upon each other can be driven in parallel and processed out of order of occurrence, while the sub-documents that have data types that depend on each other are constrained and processed according to the dependency order using the memory barrier; and retrieving, by one or more processors, numbered annotation data within the scheduled and annotated plurality of sub-documents, representing the order of occurrence, wherein the reconstructed document preserves the order of occurrence of previous extractions based on the retrieved numbered annotation data. | 1. A computer program product for parallelizing document processing in an information handling system, the computer program product comprising: one or more computer readable storage media and program instructions stored on the one or more computer readable storage media, executable by a computer processor that can perform reordering operations when executing program instructions in parallel, the program instructions comprising: program instructions to receive a document, wherein the document includes text content, given a particular granularity scope; program instructions to extract information from the text content, utilizing natural language processing and semantic analysis, to form tokenized semantic partitions, comprising a plurality of sub-documents, wherein: the tokenized semantic partitions each have a particular data type; the plurality of sub-documents are annotated to represent an order of occurrence within the document; and the annotated plurality of sub-documents allows reconstruction to the particular granularity scope at any point during the extraction; program instructions to reconstruct the document by scheduling a process for the annotated plurality of sub-documents, wherein: the scheduling drives each of the annotated sub-documents in parallel by using a memory barrier to enforce an ordering constraint on the annotated plurality of sub-documents based on a data dependent scheduling order using the data types of the sub-documents and a type dependency flow graph for the annotated sub-documents given the particular granularity scope, the dependency flow graph comprises information about which data types are dependent on other data types in a dependency order, and by using the type dependency flow graph, the sub-documents that have data types that do not depend upon each other can be driven in parallel and processed out of order of occurrence, while the sub-documents that have data types that depend on each other are constrained and processed according to the dependency order using the memory barrier; and retrieving, by one or more processors, numbered annotation data within the scheduled and annotated plurality of sub-documents, representing the order of occurrence, wherein the reconstructed document preserves the order of occurrence of previous extractions based on the retrieved numbered annotation data. 5. The computer program product of claim 1 , further comprising: program instructions, stored on the one or more computer readable storage media, to annotate each sub-document, wherein the annotation allows the determination of document domain, document layout, and document structural components; program instructions, stored on the one or more computer readable storage media, to store each annotated sub-document; and program instructions, stored on the one or more computer readable storage media, to reconstruct the document to the granularity scope using each sub document, based on information in the annotated sub-document. | 0.556259 |
10,031,766 | 1 | 5 | 1. A method comprising: generating JAVA™ objects from one or more initial Extensible Mark-up Language (XML) schema definition (XSD) files; identifying namespaces within the JAVA™ objects; grouping the JAVA™ objects by namespaces, wherein the JAVA™ objects included in each group have the same namespace, and wherein the namespaces included in each group are different; creating each new XSD file for each group of JAVA™ objects, wherein each new XSD file includes references to the initial XSD files that include the same namespace; generating each new JAVA™ class from each new XSD file; compiling each new JAVA™ class into bytecode; storing the bytecode into a memory; receiving, from the memory, the bytecode, wherein the bytecode is loaded into a ClassLoader, wherein the ClassLoader is available to a JAVA™ Virtual Machine (JVM) during runtime; and dynamically loading one or more XSD files into the JVM during runtime. | 1. A method comprising: generating JAVA™ objects from one or more initial Extensible Mark-up Language (XML) schema definition (XSD) files; identifying namespaces within the JAVA™ objects; grouping the JAVA™ objects by namespaces, wherein the JAVA™ objects included in each group have the same namespace, and wherein the namespaces included in each group are different; creating each new XSD file for each group of JAVA™ objects, wherein each new XSD file includes references to the initial XSD files that include the same namespace; generating each new JAVA™ class from each new XSD file; compiling each new JAVA™ class into bytecode; storing the bytecode into a memory; receiving, from the memory, the bytecode, wherein the bytecode is loaded into a ClassLoader, wherein the ClassLoader is available to a JAVA™ Virtual Machine (JVM) during runtime; and dynamically loading one or more XSD files into the JVM during runtime. 5. The method of claim 1 , further comprising searching for references in the JAVA™ objects of the QName type to determine references to other XSD types. | 0.855932 |
7,854,009 | 4 | 13 | 4. The system of claim 3 , wherein the security system of a LAN assigns a security rating to a LAN port site based on a security level for a particular user previously assigned that port site. | 4. The system of claim 3 , wherein the security system of a LAN assigns a security rating to a LAN port site based on a security level for a particular user previously assigned that port site. 13. The system of claim 4 , wherein a LAN security system is run on a DHCP. | 0.986617 |
7,788,265 | 11 | 19 | 11. A computer program product comprising computer-executable instructions, tangibly stored on a computer readable medium, for execution by a processor to perform a method for classifying an object in a taxonomy, the taxonomy including a plurality of nodes associated with a plurality of classes, the object being external to the taxonomy, the method comprising: (A) identifying a first plurality of search strings based on a plurality of class keywords associated with the plurality of nodes, wherein identifying comprises, for at least one particular node N in the plurality of nodes: (A)(1) traversing a first branch in the taxonomy linking a root node of the taxonomy to node N; and (A)(2) for each node M in the first branch, selecting a class keyword associated with node M and adding the selected class keyword to a first one of the plurality of search strings associated with node N, whereby the first one of the plurality of search strings contains a second plurality of class keywords; (B) performing a plurality of searches on the object using the plurality of search strings to produce a plurality of search scores corresponding to the plurality of search strings; (C) identifying one of the plurality of nodes based on the plurality of search scores; and (D) classifying the object in a class associated with the identified node. | 11. A computer program product comprising computer-executable instructions, tangibly stored on a computer readable medium, for execution by a processor to perform a method for classifying an object in a taxonomy, the taxonomy including a plurality of nodes associated with a plurality of classes, the object being external to the taxonomy, the method comprising: (A) identifying a first plurality of search strings based on a plurality of class keywords associated with the plurality of nodes, wherein identifying comprises, for at least one particular node N in the plurality of nodes: (A)(1) traversing a first branch in the taxonomy linking a root node of the taxonomy to node N; and (A)(2) for each node M in the first branch, selecting a class keyword associated with node M and adding the selected class keyword to a first one of the plurality of search strings associated with node N, whereby the first one of the plurality of search strings contains a second plurality of class keywords; (B) performing a plurality of searches on the object using the plurality of search strings to produce a plurality of search scores corresponding to the plurality of search strings; (C) identifying one of the plurality of nodes based on the plurality of search scores; and (D) classifying the object in a class associated with the identified node. 19. The computer program product of claim 11 , wherein (A) comprises: (A)(3) identifying a first plurality of search strings based on the plurality of class keywords associated with the plurality of nodes; (A)(4) identifying a plurality of rankings of the first plurality of search strings; and (A)(5) identifying a subset of the first plurality of search strings based on the plurality of rankings; and wherein (B) comprises performing the plurality of searches on the object using the subset of the first plurality of search strings to produce the plurality of search scores. | 0.500865 |
7,823,123 | 1 | 2 | 1. A method comprising: providing two or more distinct information systems, each information system containing an information system ontology and corresponding information system data model; providing a context ontology, the context ontology capturing common concepts and relating the various representations of a common concept within the concepts in the distinct information system ontologies; mapping the concepts of each of the two or more information system ontologies to each other and to the concepts within the context ontology; mapping a translator web service ontology representing a translator web service having one or more structured inputs and outputs to the context ontology to create an augmented ontology; providing a service agent to interpret mappings and to reason with mapped ontologies; specifying one or more data instances from a source information system of the distinct information systems as inputs to the translator web service; specifying one or more concepts on a target information system of the distinct information systems as outputs to the translator web service; searching the mapped ontologies for an execution path between the one or more desired input data instances on the source information system and the corresponding output concepts on the target information system, the execution path traversing through concepts of the translator web service ontology; and generating executable code that accepts one or more desired input data instances from a source information system and invokes the execution path to create the corresponding output data instance in the specified target information system. | 1. A method comprising: providing two or more distinct information systems, each information system containing an information system ontology and corresponding information system data model; providing a context ontology, the context ontology capturing common concepts and relating the various representations of a common concept within the concepts in the distinct information system ontologies; mapping the concepts of each of the two or more information system ontologies to each other and to the concepts within the context ontology; mapping a translator web service ontology representing a translator web service having one or more structured inputs and outputs to the context ontology to create an augmented ontology; providing a service agent to interpret mappings and to reason with mapped ontologies; specifying one or more data instances from a source information system of the distinct information systems as inputs to the translator web service; specifying one or more concepts on a target information system of the distinct information systems as outputs to the translator web service; searching the mapped ontologies for an execution path between the one or more desired input data instances on the source information system and the corresponding output concepts on the target information system, the execution path traversing through concepts of the translator web service ontology; and generating executable code that accepts one or more desired input data instances from a source information system and invokes the execution path to create the corresponding output data instance in the specified target information system. 2. The method of claim 1 , wherein said context ontology captures at least one of the commonly held Position, Time, Types of Things, Geometric Shapes, Roles, Status, or Units of Measure concepts. | 0.761614 |
9,472,209 | 8 | 9 | 8. The method of claim 1 , further comprising the steps of: the computer receiving a search query; the computer matching the search query to the searchable tag; and the computer responding to the search query with the recorded audio and an indication of the time of occurrence of the non-speech sound. | 8. The method of claim 1 , further comprising the steps of: the computer receiving a search query; the computer matching the search query to the searchable tag; and the computer responding to the search query with the recorded audio and an indication of the time of occurrence of the non-speech sound. 9. The method of claim 8 , wherein the step of matching the search query to the searchable tag comprises: the computer identifying a type of sound associated with a search term of the search query; the computer identifying a plurality of terms associated with the identified type of sound; and the computer searching the recorded audio for a searchable tag matching a term from the plurality of terms. | 0.8255 |
9,792,355 | 1 | 2 | 1. A method of searching for similar documents, the method comprising: accessing a first document; identifying one or more terms from a metamodel semantic network; identifying one or more terms from the metamodel semantic network that are also found in the first document, wherein the identification of the one or more terms from the metamodel semantic network comprises: identifying a user that created the first document; retrieving context information associated with the user; identifying business functional data associated with the context information; identifying, from a number of domains, the domain associated with the business functional data, each domain from the number of domains including a different grouping of terms; and selecting terms that are associated with the identified domain for the analysis; identifying a weighted frequency of occurrence in the first document for each of the one or more identified terms, each weighted frequency of occurrence being a count of occurrences of the corresponding term in the first document multiplied by a weight based on a length of the first document; and searching for another document having one or more weighted frequencies of occurrences that are within a predefined range of a corresponding weighted frequency of occurrence of the corresponding term in the first document, the other document having been previously analyzed using terms from the metamodel semantic network. | 1. A method of searching for similar documents, the method comprising: accessing a first document; identifying one or more terms from a metamodel semantic network; identifying one or more terms from the metamodel semantic network that are also found in the first document, wherein the identification of the one or more terms from the metamodel semantic network comprises: identifying a user that created the first document; retrieving context information associated with the user; identifying business functional data associated with the context information; identifying, from a number of domains, the domain associated with the business functional data, each domain from the number of domains including a different grouping of terms; and selecting terms that are associated with the identified domain for the analysis; identifying a weighted frequency of occurrence in the first document for each of the one or more identified terms, each weighted frequency of occurrence being a count of occurrences of the corresponding term in the first document multiplied by a weight based on a length of the first document; and searching for another document having one or more weighted frequencies of occurrences that are within a predefined range of a corresponding weighted frequency of occurrence of the corresponding term in the first document, the other document having been previously analyzed using terms from the metamodel semantic network. 2. The method of claim 1 , wherein the business functional data is a business object. | 0.956321 |
7,945,896 | 1 | 7 | 1. A method for facilitating communications between components of a distributed application comprising the steps of: receiving a request by a middleware program from a first distributed application component, wherein a second distributed application component is identified in said request as a recipient of said request; identifying by the middleware program a publish/subscribe topic by identifying a first property of said second distributed application component; sending the request by the middleware program to a publisher associated with the first publish/subscribe topic; publishing by the publisher said request on the first publish/subscribe request topic; and in response to said publishing said request on the first publish/subscribe topic: sending the message to the second distributed application component, wherein the distributed application, the middleware program, the publisher and the publish/subscribe topic, are embodied in communicating computing devices. | 1. A method for facilitating communications between components of a distributed application comprising the steps of: receiving a request by a middleware program from a first distributed application component, wherein a second distributed application component is identified in said request as a recipient of said request; identifying by the middleware program a publish/subscribe topic by identifying a first property of said second distributed application component; sending the request by the middleware program to a publisher associated with the first publish/subscribe topic; publishing by the publisher said request on the first publish/subscribe request topic; and in response to said publishing said request on the first publish/subscribe topic: sending the message to the second distributed application component, wherein the distributed application, the middleware program, the publisher and the publish/subscribe topic, are embodied in communicating computing devices. 7. The method of claim 1 , further comprising the steps of: subscribing by the middleware program to a second publish/subscribe request topic, wherein said second publish/subscribe request topic is identified by a type of said first distributed application component; forwarding by the middleware program a request posted on said second publish/subscribe request topic to said first distributed application component, wherein said request is generated by a third distributed application component; receiving by the middleware program a reply from said first distributed application component, wherein a recipient of said reply is said third distributed application component; and publishing by the middleware program said reply on a second publish/subscribe reply topic, wherein said second publish/subscribe reply topic is identified by a type of said third distributed application component. | 0.500559 |
7,890,877 | 1 | 7 | 1. A method for generating a portal, comprising: providing a first development environment having a plurality of portal designer tools capable of simultaneously obtaining portal configuration information; providing a second development environment having an administration tool to construct a portal for a particular user or group of users wherein the plurality of portal designer tools in the first development environment and the administration tool in the second development environment, communicate via a network, and wherein each one of the portal designer tools includes a graphical user interface that obtains the portal configuration information by dragging and dropping a portal component from a palette to a display within the graphical user interface, and wherein the portal component includes one of a portlet, page and book; receiving, by the administration tool, the portal configuration from each one of the plurality of portal designer tools via the network, and preparing a portal description in accordance with the portal configuration information received; wherein the administration tool aggregates the portal configuration information received from the plurality of portal designer tools located in the first development environment to construct the portal for the particular user or group of users; providing a design view, a source view and a hierarchical view as part of the graphical user interface, wherein the design view is a display that gives a graphical indication of the portal components in the portal, the source view is a display of the portal description and the hierarchical view provides a graphical indication of all the portal components arranged in a hierarchy; detecting a modification of the portal description by any of the design tools, wherein the modification is detected by detecting at least one of a drag and drop by one of the plurality of design tools of a new portal component from the palette into the display within the graphical user interface, and editing properties of the selected portal component; and automatically synchronizing the portal description, design view, source view and hierarchical view across the portal designer tools and the administration tool, via the network, to reflect the modification of the portal description, wherein upon detecting the modification of the portal description, the design view, source view and hierarchical view of each one of the plurality of design tools are updated to reflect the modification. | 1. A method for generating a portal, comprising: providing a first development environment having a plurality of portal designer tools capable of simultaneously obtaining portal configuration information; providing a second development environment having an administration tool to construct a portal for a particular user or group of users wherein the plurality of portal designer tools in the first development environment and the administration tool in the second development environment, communicate via a network, and wherein each one of the portal designer tools includes a graphical user interface that obtains the portal configuration information by dragging and dropping a portal component from a palette to a display within the graphical user interface, and wherein the portal component includes one of a portlet, page and book; receiving, by the administration tool, the portal configuration from each one of the plurality of portal designer tools via the network, and preparing a portal description in accordance with the portal configuration information received; wherein the administration tool aggregates the portal configuration information received from the plurality of portal designer tools located in the first development environment to construct the portal for the particular user or group of users; providing a design view, a source view and a hierarchical view as part of the graphical user interface, wherein the design view is a display that gives a graphical indication of the portal components in the portal, the source view is a display of the portal description and the hierarchical view provides a graphical indication of all the portal components arranged in a hierarchy; detecting a modification of the portal description by any of the design tools, wherein the modification is detected by detecting at least one of a drag and drop by one of the plurality of design tools of a new portal component from the palette into the display within the graphical user interface, and editing properties of the selected portal component; and automatically synchronizing the portal description, design view, source view and hierarchical view across the portal designer tools and the administration tool, via the network, to reflect the modification of the portal description, wherein upon detecting the modification of the portal description, the design view, source view and hierarchical view of each one of the plurality of design tools are updated to reflect the modification. 7. The method of claim 1 , wherein the graphical user interface is part of the portal designer. | 0.858631 |
9,600,842 | 1 | 10 | 1. An apparatus, comprising: a device including at least one input device, at least one display, and memory in communication with at least one hardware processor; and a browser installed on the memory of the device for allowing access, utilizing the at least one input device and the at least one hardware processor, to a system including a hardware server, the system configured for: identifying at least parts of a plurality of original documents including a plurality of original values, the plurality of original documents including a first document including first values and a second document including second values; processing at least a part of the first document and at least a part of the second document, resulting in at least one data structure including at least one of the plurality of original values of at least one of the plurality of original documents; receiving one or more indications for one or more of the original values for adding, in connection with at least one computer-readable Extensible Markup Language (XML)-compliant data document, a corresponding one or more computer-readable semantic tags in association with the one or more original values; associating the one or more computer-readable semantic tags with the one or more original values; causing output of a presentation that is based on at least a portion of the at least one data structure, the presentation capable of including at least a portion of the original values including the at least one original value, where the system is configured such that, based on the at least one data structure, a change to the at least one original value results in a corresponding change in a subsequent output of the presentation; and causing output of the at least one computer-readable XML-compliant data document that is eXtensible Business Reporting Language (XBRL)-compliant and is based on at least a portion of at least one data structure, the at least one computer-readable XML-compliant data document capable of including a plurality of line items at least one of which utilizes at least a portion of the original values including the at least one original value and at least some of the one or more computer-readable semantic tags, where the system is configured such that, based on the at least one data structure, a change to the at least one original value results in a corresponding change in a subsequent output of the at least one computer-readable XML-compliant data document; said apparatus configured for: receiving user input utilizing the browser, and displaying the at least one computer-readable XML-compliant data document utilizing the browser, after the user input. | 1. An apparatus, comprising: a device including at least one input device, at least one display, and memory in communication with at least one hardware processor; and a browser installed on the memory of the device for allowing access, utilizing the at least one input device and the at least one hardware processor, to a system including a hardware server, the system configured for: identifying at least parts of a plurality of original documents including a plurality of original values, the plurality of original documents including a first document including first values and a second document including second values; processing at least a part of the first document and at least a part of the second document, resulting in at least one data structure including at least one of the plurality of original values of at least one of the plurality of original documents; receiving one or more indications for one or more of the original values for adding, in connection with at least one computer-readable Extensible Markup Language (XML)-compliant data document, a corresponding one or more computer-readable semantic tags in association with the one or more original values; associating the one or more computer-readable semantic tags with the one or more original values; causing output of a presentation that is based on at least a portion of the at least one data structure, the presentation capable of including at least a portion of the original values including the at least one original value, where the system is configured such that, based on the at least one data structure, a change to the at least one original value results in a corresponding change in a subsequent output of the presentation; and causing output of the at least one computer-readable XML-compliant data document that is eXtensible Business Reporting Language (XBRL)-compliant and is based on at least a portion of at least one data structure, the at least one computer-readable XML-compliant data document capable of including a plurality of line items at least one of which utilizes at least a portion of the original values including the at least one original value and at least some of the one or more computer-readable semantic tags, where the system is configured such that, based on the at least one data structure, a change to the at least one original value results in a corresponding change in a subsequent output of the at least one computer-readable XML-compliant data document; said apparatus configured for: receiving user input utilizing the browser, and displaying the at least one computer-readable XML-compliant data document utilizing the browser, after the user input. 10. The apparatus of claim 1 , wherein the system is configured such that the at least one computer-readable XML-compliant data document is encapsulated, in machine-readable form, with at least one reusable document including routines that are capable of being utilized for data value formatting and data value collating in connection with the at least one computer-readable XML-compliant data document as well as other computer-readable XML-compliant data documents insofar as the other computer-readable XML-compliant data documents meet requirements set forth in the at least one reusable document. | 0.910057 |
9,092,463 | 7 | 12 | 7. A system comprising: one or more data processing apparatus; and memory storing instructions that, when executed by the one or more data processing apparatus, cause the one or more data processing apparatus to perform operations comprising: receiving structured data describing a content item, the structured data including one or more data elements comprising one or more descriptions and values for the one or more data elements, the structured data indicating a category for the content item; retrieving stored data for the category, the stored data identifying one or more domains; forming a first query based on data elements in the structured data; searching one or more of the domains using the first query to identify resources associated with the one or more domains; determining one or more queries based on data reflecting past search queries, where each of the one or more queries resulted in one or more of the resources being returned as part of a search result; determining keywords based on the one or more queries; transmitting or storing the keywords for use in impression allocation decisions; determining an allocation score for the content item based at least in part on comparison of the keywords to a term associated with a request for an impression, where the allocation score is used to determine whether the content item will be selected for the impression; selecting the content item for display in response to the request, based on the allocation score; and transmitting data specifying the content item in response to the request. | 7. A system comprising: one or more data processing apparatus; and memory storing instructions that, when executed by the one or more data processing apparatus, cause the one or more data processing apparatus to perform operations comprising: receiving structured data describing a content item, the structured data including one or more data elements comprising one or more descriptions and values for the one or more data elements, the structured data indicating a category for the content item; retrieving stored data for the category, the stored data identifying one or more domains; forming a first query based on data elements in the structured data; searching one or more of the domains using the first query to identify resources associated with the one or more domains; determining one or more queries based on data reflecting past search queries, where each of the one or more queries resulted in one or more of the resources being returned as part of a search result; determining keywords based on the one or more queries; transmitting or storing the keywords for use in impression allocation decisions; determining an allocation score for the content item based at least in part on comparison of the keywords to a term associated with a request for an impression, where the allocation score is used to determine whether the content item will be selected for the impression; selecting the content item for display in response to the request, based on the allocation score; and transmitting data specifying the content item in response to the request. 12. The system of claim 7 , in which determining the keywords comprises appending terms from the stored data for the category to a query from the one or more queries. | 0.815145 |
8,407,041 | 15 | 19 | 15. A computer-implemented training method, comprising acts of: deriving probabilistic decision variables based on decision rules as an integrated scoring framework to evaluate translated output of a machine translation process; training the probabilistic decision variables based on an objective function that integrates a speech recognition process and the machine translation process; updating the decision variables based on gradient-based training; and utilizing a processor to execute the objective function. | 15. A computer-implemented training method, comprising acts of: deriving probabilistic decision variables based on decision rules as an integrated scoring framework to evaluate translated output of a machine translation process; training the probabilistic decision variables based on an objective function that integrates a speech recognition process and the machine translation process; updating the decision variables based on gradient-based training; and utilizing a processor to execute the objective function. 19. The method of claim 15 , further comprising iteratively updating the probability decision variables of the speech recognition process and translation process jointly. | 0.879603 |
8,984,165 | 18 | 19 | 18. The system of claim 9 , further comprising: a web server coupled to the processing device, the web server comprising: a second memory; and a second processing device coupled to the second memory to execute a servlet generated from the web server type page file to generate a web page to render content of the file in the webpage. | 18. The system of claim 9 , further comprising: a web server coupled to the processing device, the web server comprising: a second memory; and a second processing device coupled to the second memory to execute a servlet generated from the web server type page file to generate a web page to render content of the file in the webpage. 19. The system of claim 18 , further comprising: a client machine communicably coupled to the web server via a network to request and to receive the webpage from the web server. | 0.856331 |
10,089,295 | 1 | 3 | 1. A method for generating a digital magazine, the method comprising: storing a plurality of page templates, each page template including one or more regions, each region configured to present one or more content items, one or more of the plurality of page templates including one or more regions, each region associated with a height that is based on a width of a display area; receiving a request from a client device to present one or more content items from one or more sources in the digital magazine to a user; retrieving information describing content items associated with the digital magazine; retrieving information describing user interaction with one or more content items associated with the digital magazine; identifying one or more page templates previously associated with the digital magazine from the one or more page templates; determining weights associated with characteristics of page templates based at least in part on characteristics of the identified one or more page templates previously associated with the digital magazine; selecting one or more candidate page templates by applying the determined weights to one or more selected from a group consisting of: the identified one or more page templates previously associated with the digital magazine, one or more characteristics of the content items associated with the digital magazine, the user interaction with the one or more content items associated with the digital magazine, and any combination thereof; generating a score associated with each of the one or more candidate page templates, where a score associated with a candidate page template is based on a number of the content items, characteristics of the one or more content items, and a number of regions in the page template; selecting a display page template based on the scores associated with the one or more candidate page templates; and generating a section of the digital magazine for presentation via the client device, the section including one or more regions each presenting one or more content items placed in positions specified by the one or more regions of the display page template. | 1. A method for generating a digital magazine, the method comprising: storing a plurality of page templates, each page template including one or more regions, each region configured to present one or more content items, one or more of the plurality of page templates including one or more regions, each region associated with a height that is based on a width of a display area; receiving a request from a client device to present one or more content items from one or more sources in the digital magazine to a user; retrieving information describing content items associated with the digital magazine; retrieving information describing user interaction with one or more content items associated with the digital magazine; identifying one or more page templates previously associated with the digital magazine from the one or more page templates; determining weights associated with characteristics of page templates based at least in part on characteristics of the identified one or more page templates previously associated with the digital magazine; selecting one or more candidate page templates by applying the determined weights to one or more selected from a group consisting of: the identified one or more page templates previously associated with the digital magazine, one or more characteristics of the content items associated with the digital magazine, the user interaction with the one or more content items associated with the digital magazine, and any combination thereof; generating a score associated with each of the one or more candidate page templates, where a score associated with a candidate page template is based on a number of the content items, characteristics of the one or more content items, and a number of regions in the page template; selecting a display page template based on the scores associated with the one or more candidate page templates; and generating a section of the digital magazine for presentation via the client device, the section including one or more regions each presenting one or more content items placed in positions specified by the one or more regions of the display page template. 3. The method of claim 1 , wherein a weight associated with a characteristic of the page template is based on a number of page templates previously selected to present content from the digital magazine having the characteristic. | 0.884732 |
8,285,542 | 1 | 6 | 1. A method of generating a language model from a corpus of directory assistance listings, the language model used to estimate a desired directory assistance listing based on a listing request input, the method comprising: for each word in each listing in the corpus, generating, using a processing unit, language model counts attributable to the word by: determining, based on one or more characteristics of the word in the listing, whether the word is likely to be omitted from the listing request input when the desired directory assistance listing is a listing that contains the word; generating the language model counts attributable to the word based on whether the word is likely to be omitted from the listing request input when the desired directory assistance listing is a listing that contains the word; and generating the language model counts attributable to the word based on a characteristic indicative of how well the word operates to distinguish the listing that contains the word from other listings in the corpus; and storing the language model with the language model counts. | 1. A method of generating a language model from a corpus of directory assistance listings, the language model used to estimate a desired directory assistance listing based on a listing request input, the method comprising: for each word in each listing in the corpus, generating, using a processing unit, language model counts attributable to the word by: determining, based on one or more characteristics of the word in the listing, whether the word is likely to be omitted from the listing request input when the desired directory assistance listing is a listing that contains the word; generating the language model counts attributable to the word based on whether the word is likely to be omitted from the listing request input when the desired directory assistance listing is a listing that contains the word; and generating the language model counts attributable to the word based on a characteristic indicative of how well the word operates to distinguish the listing that contains the word from other listings in the corpus; and storing the language model with the language model counts. 6. The method of claim 1 wherein the one or more characteristics of the word in the listing comprises a word position of the word in the listing that contains the word. | 0.774799 |
8,364,685 | 5 | 6 | 5. The method of claim 1 , comprising displaying the reference framework as an annotation that may comprise one or more subjective attributes. | 5. The method of claim 1 , comprising displaying the reference framework as an annotation that may comprise one or more subjective attributes. 6. The method of claim 5 , comprising generating the annotation via NLP synthesis. | 0.978657 |
7,603,272 | 1 | 14 | 1. A system for generating a block diagonal matrix from a lattice, the system comprising: (1) a processor; (2) a module configured to control the processor to compute posterior probability of all transitions T in a graph, if a lattice having transitions T is weighted; (3) a module configured to control the processor to extract a pivot baseline path from the lattice; and (4) a module configured to control the processor to align the transitions T in the lattice with the transitions in the pivot baseline path. | 1. A system for generating a block diagonal matrix from a lattice, the system comprising: (1) a processor; (2) a module configured to control the processor to compute posterior probability of all transitions T in a graph, if a lattice having transitions T is weighted; (3) a module configured to control the processor to extract a pivot baseline path from the lattice; and (4) a module configured to control the processor to align the transitions T in the lattice with the transitions in the pivot baseline path. 14. The system of claim 1 , wherein the block diagonal matrix has the computational property. | 0.949013 |
9,817,824 | 1 | 3 | 1. A computer-implemented method of providing an electronic target document in a data communication network, the method comprising: providing, by a first domain on a first server system, a link to open a digital first form in the first domain; receiving, by the first domain, an activation of the link by a user from a user computer device; redirecting, by the first domain, to a second domain on a second server system upon activation of the link, and providing a digital second form in the second domain, the second form comprising a retrieval field whereby, when the retrieval field is activated by the user from the user computer device, the second domain is configured to perform the following steps: providing a plurality of domain access fields; receiving an activation of a selected one of the domain access fields by the user from the user computer device; accessing a third domain on a third server system linked to the selected domain access field; and retrieving target document data from the third domain, uploading, by the second domain, the target document associated with the target document data to the first form of the first domain. | 1. A computer-implemented method of providing an electronic target document in a data communication network, the method comprising: providing, by a first domain on a first server system, a link to open a digital first form in the first domain; receiving, by the first domain, an activation of the link by a user from a user computer device; redirecting, by the first domain, to a second domain on a second server system upon activation of the link, and providing a digital second form in the second domain, the second form comprising a retrieval field whereby, when the retrieval field is activated by the user from the user computer device, the second domain is configured to perform the following steps: providing a plurality of domain access fields; receiving an activation of a selected one of the domain access fields by the user from the user computer device; accessing a third domain on a third server system linked to the selected domain access field; and retrieving target document data from the third domain, uploading, by the second domain, the target document associated with the target document data to the first form of the first domain. 3. The method of claim 1 , wherein the second form is provided by the second domain by: retrieving the first form from the first domain; and converting the first form into the second form, wherein the retrieval field is included in the second form. | 0.821583 |
9,363,560 | 15 | 17 | 15. A method, comprising: providing, by one or more computing devices, a blending of user-selectable content for a content category in at least two levels of a hierarchy of levels, the blending of user-selectable content for the content category comprising at least two of linear content, non-linear content or managed content, the at least two of the linear content, the non-linear content or the managed content being presented together within the at least two levels. | 15. A method, comprising: providing, by one or more computing devices, a blending of user-selectable content for a content category in at least two levels of a hierarchy of levels, the blending of user-selectable content for the content category comprising at least two of linear content, non-linear content or managed content, the at least two of the linear content, the non-linear content or the managed content being presented together within the at least two levels. 17. The method of claim 15 , wherein the blending of user-selectable content for the content category comprises linear content and non-linear content. | 0.787535 |
8,949,811 | 9 | 10 | 9. One or more computer-readable non-transitory storage media embodying software operable when executed by one or more computer systems to: construct a lambda object-oriented scripting language (“λ JS ”) model for a software program written in object-oriented scripting language; convert the λ JS model to a continuation-passing style (CPS) model for the software program; construct a control flow graph (CFG) for the software program based on the CPS model; and optimize the CPS model of the software program, comprising merging a sequence of two or more “let” operations so that they are represented by a single node in the CFG, the two or more “let” operations in the CPS model and generated based on the λ JS model. | 9. One or more computer-readable non-transitory storage media embodying software operable when executed by one or more computer systems to: construct a lambda object-oriented scripting language (“λ JS ”) model for a software program written in object-oriented scripting language; convert the λ JS model to a continuation-passing style (CPS) model for the software program; construct a control flow graph (CFG) for the software program based on the CPS model; and optimize the CPS model of the software program, comprising merging a sequence of two or more “let” operations so that they are represented by a single node in the CFG, the two or more “let” operations in the CPS model and generated based on the λ JS model. 10. The media of claim 9 , wherein the software is further operable when executed by the one or more computer systems to parse object-oriented scripting language source code of the software program. | 0.694444 |
8,572,488 | 14 | 17 | 14. A computer program product, comprising: a computer-readable medium; and computer program instructions encoded on the computer-readable medium, wherein the computer program instructions, when processed by a computer, instruct the computer to perform a method for editing time-based media that includes recorded speech, the method comprising: receiving the script or transcript; receiving timing information comprising, for each of a plurality of words or phrases within the script or transcript, a temporal location within the time-based media program where that word or phrase has been matched with a corresponding spoken word or phrase recognized in the recorded speech, and a confidence level for a match of the word or phrase from the selected portion of the transcript to the spoken word or phrase recognized in the recorded speech from the associated temporal location within the time-based media program; displaying a selected portion of the script or transcript; using the timing information, displaying, along with the word or phrases of the displayed selected portion of the script or transcript to which the confidence level corresponds, a graphical representation of the confidence levels for the matches of the words or phrases from the displayed selected portion of the script or transcript to the corresponding words or phrases recognized in the recorded speech from the temporal location within the time-based media program according to the received timing information, wherein at least one of the words or phrases within the selected portion has a confidence level equal to or lower than a predetermined threshold confidence level, indicating that said at least one of the words or phrases in the selected portion do not match the words or phrases recognized in the recorded speech; retrieving a portion of the time-based media program corresponding to the temporal location associated with the selected portion of the script or transcript; playing back the retrieved portion of the time-based media program, while the selected portion of the script or transcript and graphical representation of the corresponding confidence levels are displayed, to enable a user to compare the retrieved portion of the time-based media program and the selected portion of the script or transcript; and in response to input received from the user, making corrections as indicated by the user to the text of the selected portion of the script or transcript, so as to have the corrected text match the words or phrases in the recorded speech, such corrections being made while text from the selected portion of the script or transcript and corresponding graphical representations of the confidence levels are displayed and the corresponding portion of the time-based media is played back. | 14. A computer program product, comprising: a computer-readable medium; and computer program instructions encoded on the computer-readable medium, wherein the computer program instructions, when processed by a computer, instruct the computer to perform a method for editing time-based media that includes recorded speech, the method comprising: receiving the script or transcript; receiving timing information comprising, for each of a plurality of words or phrases within the script or transcript, a temporal location within the time-based media program where that word or phrase has been matched with a corresponding spoken word or phrase recognized in the recorded speech, and a confidence level for a match of the word or phrase from the selected portion of the transcript to the spoken word or phrase recognized in the recorded speech from the associated temporal location within the time-based media program; displaying a selected portion of the script or transcript; using the timing information, displaying, along with the word or phrases of the displayed selected portion of the script or transcript to which the confidence level corresponds, a graphical representation of the confidence levels for the matches of the words or phrases from the displayed selected portion of the script or transcript to the corresponding words or phrases recognized in the recorded speech from the temporal location within the time-based media program according to the received timing information, wherein at least one of the words or phrases within the selected portion has a confidence level equal to or lower than a predetermined threshold confidence level, indicating that said at least one of the words or phrases in the selected portion do not match the words or phrases recognized in the recorded speech; retrieving a portion of the time-based media program corresponding to the temporal location associated with the selected portion of the script or transcript; playing back the retrieved portion of the time-based media program, while the selected portion of the script or transcript and graphical representation of the corresponding confidence levels are displayed, to enable a user to compare the retrieved portion of the time-based media program and the selected portion of the script or transcript; and in response to input received from the user, making corrections as indicated by the user to the text of the selected portion of the script or transcript, so as to have the corrected text match the words or phrases in the recorded speech, such corrections being made while text from the selected portion of the script or transcript and corresponding graphical representations of the confidence levels are displayed and the corresponding portion of the time-based media is played back. 17. The computer program product of claim 14 , wherein the script or transcript includes metadata associated with the time-based media program in addition to the timing information. | 0.502747 |
8,612,231 | 1 | 6 | 1. A method of history tracking edits to an electronic document, wherein said electronic document is a speech-based document comprising one or more sections of text derived from speech dictated by a user, said method comprising: storing, in a data structure, at least one first speech attribute associated with a section of text in said speech-based document, said at least one first speech attribute comprising information related to a first edit performed within said section of text, wherein the data structure comprises a tree-result representation; detecting a second edit being performed within said section of text; and updating the data structure to include information related to said second edit detected within said section of text, wherein updating the data structure comprises adding at least one second speech attribute to the tree result representation, wherein the at least one second speech attribute is related to the second edit detected within said section of text. | 1. A method of history tracking edits to an electronic document, wherein said electronic document is a speech-based document comprising one or more sections of text derived from speech dictated by a user, said method comprising: storing, in a data structure, at least one first speech attribute associated with a section of text in said speech-based document, said at least one first speech attribute comprising information related to a first edit performed within said section of text, wherein the data structure comprises a tree-result representation; detecting a second edit being performed within said section of text; and updating the data structure to include information related to said second edit detected within said section of text, wherein updating the data structure comprises adding at least one second speech attribute to the tree result representation, wherein the at least one second speech attribute is related to the second edit detected within said section of text. 6. The method according to claim 1 , wherein said second edit is performed by a different user than said user. | 0.903169 |
8,656,371 | 2 | 7 | 2. The method of claim 1 , wherein generating the representation code comprises: for each page in the report, and for each respective object in the page, generating instructions of the different language that describe the respective object. | 2. The method of claim 1 , wherein generating the representation code comprises: for each page in the report, and for each respective object in the page, generating instructions of the different language that describe the respective object. 7. The method of claim 2 , further comprising for each page in the report, generating subroutines global to each page in the report. | 0.971267 |
10,055,103 | 11 | 12 | 11. The method of claim 9 , further comprising: determining if the first proposed word is to be selected; and transitioning from the first cycling state to a second cycling state when the first proposed word is determined not to be selected, wherein the second cycling state represents the state of the application when the cycling operation is active for a second time. | 11. The method of claim 9 , further comprising: determining if the first proposed word is to be selected; and transitioning from the first cycling state to a second cycling state when the first proposed word is determined not to be selected, wherein the second cycling state represents the state of the application when the cycling operation is active for a second time. 12. The method of claim 11 , further comprising: receiving a second input gesture within the input field with autocomplete, the second input gesture being received subsequent of the first input gesture; shifting the characters during the duration of the second input gesture; selecting a second character among the shifted characters; and performing a second autocomplete operation to present one or more proposed words based on the first and second characters. | 0.855938 |
8,326,826 | 17 | 23 | 17. A system, comprising: a data processing apparatus having accesses to a data store storing: a query log storing query sequences for search sessions, each query sequence being a sequence including an initial query and one or more revised queries and defining an order in which the queries were submitted for a search session; and a click log storing selection data defining actions taken responsive to search results provided for the search sessions, the search results provided in response to the queries and each search result including a corresponding resource locator that specifies the location of a corresponding resource; a computer-readable medium storing instructions executable by the data processing apparatus and upon such execution cause the data processing apparatus to perform operations comprising: selecting a candidate query in a query sequence; selecting a revised query subsequent to the candidate query in the order; determining a quality score for the revised query; determining a navigation score for the revised query; and determining that the quality score for the revised query is greater than a quality score threshold and that the navigation score for the revised query is greater than a navigation score threshold, and in response: identifying a navigational resource for the revised query; and associating the navigational resource with the candidate query, the association specifying the navigational resource as being relevant to the candidate query in a search operation. | 17. A system, comprising: a data processing apparatus having accesses to a data store storing: a query log storing query sequences for search sessions, each query sequence being a sequence including an initial query and one or more revised queries and defining an order in which the queries were submitted for a search session; and a click log storing selection data defining actions taken responsive to search results provided for the search sessions, the search results provided in response to the queries and each search result including a corresponding resource locator that specifies the location of a corresponding resource; a computer-readable medium storing instructions executable by the data processing apparatus and upon such execution cause the data processing apparatus to perform operations comprising: selecting a candidate query in a query sequence; selecting a revised query subsequent to the candidate query in the order; determining a quality score for the revised query; determining a navigation score for the revised query; and determining that the quality score for the revised query is greater than a quality score threshold and that the navigation score for the revised query is greater than a navigation score threshold, and in response: identifying a navigational resource for the revised query; and associating the navigational resource with the candidate query, the association specifying the navigational resource as being relevant to the candidate query in a search operation. 23. The system of claim 17 , wherein determining a navigation score for the revised query comprises determining navigational metrics for each resource identified by a search engine in response to the revised query, the navigational metrics including one or more of a cross linkage score, traffic proportion, and click-through rate. | 0.847886 |
9,715,490 | 2 | 3 | 2. The method of claim 1 , further comprising: responsive to determining the at least one language associated with the text of the one or more previous conversations between the first user and the at least one second user is not detected with the second confidence level that exceeds the second pre-defined threshold, retrieving, by the one or more computer processors, text from one or more previous conversations by at least one of the first user and the at least one second user; detecting, by the one or more computer processors, at least one language associated with the text of the one or more previous conversations by at least one of the first user and the at least one second user; and determining, by the one or more computer processors, the at least one language associated with the text of the one or more previous conversations by at least one of the first user and the at least one second user is detected with a third confidence level that exceeds a third pre-defined threshold. | 2. The method of claim 1 , further comprising: responsive to determining the at least one language associated with the text of the one or more previous conversations between the first user and the at least one second user is not detected with the second confidence level that exceeds the second pre-defined threshold, retrieving, by the one or more computer processors, text from one or more previous conversations by at least one of the first user and the at least one second user; detecting, by the one or more computer processors, at least one language associated with the text of the one or more previous conversations by at least one of the first user and the at least one second user; and determining, by the one or more computer processors, the at least one language associated with the text of the one or more previous conversations by at least one of the first user and the at least one second user is detected with a third confidence level that exceeds a third pre-defined threshold. 3. The method of claim 2 , further comprising, responsive to determining the at least one language associated with the text of the one or more previous conversations by at least one of the first user and the at least one second user is not detected with the second confidence level that exceeds the second pre-defined threshold, retrieving, by the one or more computer processors, one or more preferred languages of the first user and the at least one second user. | 0.911888 |
9,846,744 | 11 | 14 | 11. A computer implemented method of generating a list of playable media objects, the method comprising the steps of: querying at least one internet search engine with the search query object; generating additional terms related to the search query object based on results returned by the internet search engine, wherein generating additional terms comprises: receiving a page identified in the result returned by the internet search engine, parsing the received page to identify a plurality of sections in the page, extracting terms from each section of the plurality of sections, scoring each of the plurality of sections based at least in part on the respective extracted terms to generate a plurality of scores, and selecting additional terms from a subset of the plurality of sections based at least in part on the plurality of scores; identifying one or more media storage web sites having playable media objects related to the generated additional terms; and generating a list of playable media objects from the playable media objects at the media storage web sites. | 11. A computer implemented method of generating a list of playable media objects, the method comprising the steps of: querying at least one internet search engine with the search query object; generating additional terms related to the search query object based on results returned by the internet search engine, wherein generating additional terms comprises: receiving a page identified in the result returned by the internet search engine, parsing the received page to identify a plurality of sections in the page, extracting terms from each section of the plurality of sections, scoring each of the plurality of sections based at least in part on the respective extracted terms to generate a plurality of scores, and selecting additional terms from a subset of the plurality of sections based at least in part on the plurality of scores; identifying one or more media storage web sites having playable media objects related to the generated additional terms; and generating a list of playable media objects from the playable media objects at the media storage web sites. 14. The method of claim 11 , wherein the additional terms are ranked. | 0.950714 |
8,666,730 | 1 | 2 | 1. A method for question-answering based on automatic semantic labeling of text documents and user questions, the method comprising: electronically receiving natural language text documents using at least one computer processor coupled to at least one non-transitory storage medium; electronically receiving a user question formulated in a natural language; performing a basic linguistic analysis of the text documents and the user question; performing semantic labeling of the text documents through semantic analysis, including identifying target words in the text documents using linguistic patterns stored in a database and assigning question types to the target words in the text documents; storing the semantically labeled text documents in a labeled text documents database; performing semantic labeling of the user question through semantic analysis, including identifying one or more target words in the user question using linguistic patterns stored in a database and assigning a question type to each of the one or more target words in the user question; searching the labeled text documents database for text fragments relevant to the semantically labeled user question at least in part by matching a question type assigned to a target word in the labeled text documents to a question type assigned to a target word in the user question, wherein relevance is based on a ranking of the text fragments relative to the semantically labeled user question; and synthesizing answers to the user question from the relevant text fragments, and electronically presenting the synthesized answer to the user. | 1. A method for question-answering based on automatic semantic labeling of text documents and user questions, the method comprising: electronically receiving natural language text documents using at least one computer processor coupled to at least one non-transitory storage medium; electronically receiving a user question formulated in a natural language; performing a basic linguistic analysis of the text documents and the user question; performing semantic labeling of the text documents through semantic analysis, including identifying target words in the text documents using linguistic patterns stored in a database and assigning question types to the target words in the text documents; storing the semantically labeled text documents in a labeled text documents database; performing semantic labeling of the user question through semantic analysis, including identifying one or more target words in the user question using linguistic patterns stored in a database and assigning a question type to each of the one or more target words in the user question; searching the labeled text documents database for text fragments relevant to the semantically labeled user question at least in part by matching a question type assigned to a target word in the labeled text documents to a question type assigned to a target word in the user question, wherein relevance is based on a ranking of the text fragments relative to the semantically labeled user question; and synthesizing answers to the user question from the relevant text fragments, and electronically presenting the synthesized answer to the user. 2. The method according to claim 1 , further comprising: applying parts-of-speech tags to the text documents and user question to generate tagged text documents and user question; parsing the tagged text documents and user question to generate parsed and tagged text documents and user question; and semantically analyzing the parsed and tagged text documents and user question to generate semantically analyzed, parsed, and tagged text documents and user question. | 0.535928 |
6,137,041 | 7 | 8 | 7. A music score reading method according to claim 1 wherein said notation estimating step estimates a drum notation with respect to drum instruments of cymbals such that, under a condition that drum heads other than a black head exist above a fourth space of the staff, drum notations are classified into a case where the drum heads exist at one staff position and a case where the drum heads exist at two staff positions, said classification is further divided depending on kinds of the drum heads and still further divided depending on tone lengths determined by flags of the drum notes and other tone lengths determined by the kinds of the heads based on existence of the tone lengths of the drum notes derived by said flags, a conversion table is prepared depending on said still further divided classification, and kinds of the drum instruments of cymbals estimated depending on the staff positions of the drum heads, the kinds of the drum heads, a hi-hat open sign relating to the drum notes, a hi-hat close sign relating to the drum notes, an accent sign relating to the drum notes and character strings for designation of drum tones of the notes are specified in the conversion table so as to estimate the drum notation based on said conversion table. | 7. A music score reading method according to claim 1 wherein said notation estimating step estimates a drum notation with respect to drum instruments of cymbals such that, under a condition that drum heads other than a black head exist above a fourth space of the staff, drum notations are classified into a case where the drum heads exist at one staff position and a case where the drum heads exist at two staff positions, said classification is further divided depending on kinds of the drum heads and still further divided depending on tone lengths determined by flags of the drum notes and other tone lengths determined by the kinds of the heads based on existence of the tone lengths of the drum notes derived by said flags, a conversion table is prepared depending on said still further divided classification, and kinds of the drum instruments of cymbals estimated depending on the staff positions of the drum heads, the kinds of the drum heads, a hi-hat open sign relating to the drum notes, a hi-hat close sign relating to the drum notes, an accent sign relating to the drum notes and character strings for designation of drum tones of the notes are specified in the conversion table so as to estimate the drum notation based on said conversion table. 8. A music score reading method according to claim 7, characterized in that, upon allocating the actual tone generating musical instruments to the recognized signs of the drum part according to the drum notation estimated by said notation estimating step, if a value of said conversion table designates a half note relative to the drum note originally recognized as a quarter note before estimation, said drum note is converted to the half note. | 0.778607 |
9,443,254 | 17 | 21 | 17. A product placement system for selecting at least one product record for display in a user interface rendered by a computing device, the system comprising: a computing device adapted to analyze at least a portion of a document for at least a frequency of words in the document; a computing device adapted to construct a query search string based on the analysis of the document, the query search string at least partially based on words of the document having the highest frequencies; a computing device adapted to apply the query search string to a products database, the products database including a plurality of product records which include information regarding products, to identify at least one product record in the products database that satisfies the query search string; a computing device adapted to select at least one of the identified product records for embedding into the document and display in the user interface, and a computing device adapted to embed at least one of the selected product records into the document for display in the user interface, wherein the document is not stored within the products database. | 17. A product placement system for selecting at least one product record for display in a user interface rendered by a computing device, the system comprising: a computing device adapted to analyze at least a portion of a document for at least a frequency of words in the document; a computing device adapted to construct a query search string based on the analysis of the document, the query search string at least partially based on words of the document having the highest frequencies; a computing device adapted to apply the query search string to a products database, the products database including a plurality of product records which include information regarding products, to identify at least one product record in the products database that satisfies the query search string; a computing device adapted to select at least one of the identified product records for embedding into the document and display in the user interface, and a computing device adapted to embed at least one of the selected product records into the document for display in the user interface, wherein the document is not stored within the products database. 21. The system of claim 17 , wherein the user interface is a web page graphically rendered by a browser. | 0.718919 |
10,015,213 | 10 | 11 | 10. The non-transitory computer readable medium of claim 9 , wherein the computer instructions when executed on a computer further causes the computer to: generate an identification of coordinates of a location of the electronic content in the appropriate version from all the versions of the electronic content. | 10. The non-transitory computer readable medium of claim 9 , wherein the computer instructions when executed on a computer further causes the computer to: generate an identification of coordinates of a location of the electronic content in the appropriate version from all the versions of the electronic content. 11. The non-transitory computer readable medium of claim 10 further including a book discovery system configured to allow users to browse through shelves of friends and discover books that may be of interest. | 0.976119 |
8,005,814 | 2 | 8 | 2. The system as defined in claim 1 , further comprising: a set of reusable software components. | 2. The system as defined in claim 1 , further comprising: a set of reusable software components. 8. The system as defined in claim 2 , wherein the reusable software components comprise at least one of software objects, data public functions, and private functions, and wherein said data public functions are accessible through derived classes of objects. | 0.893006 |
8,571,606 | 15 | 16 | 15. The method of claim 14 , wherein the bookmark repository comprises a hierarchical structure of bookmarks comprising folders. | 15. The method of claim 14 , wherein the bookmark repository comprises a hierarchical structure of bookmarks comprising folders. 16. The method of claim 15 , wherein the second browser is configured to render menus based on the hierarchical structure. | 0.960261 |
10,134,397 | 11 | 13 | 11. At least one non-transitory computer readable media storing instructions that, when executed by one or more processors, cause the one or more processors to: determine, when a multimodal interface of an electronic device is at a first modality, that a context satisfies a criterion, wherein determining that the context satisfies the criterion is based on one or more signals from a sensor of the electronic device, and wherein the sensor is in addition to a microphone of the electronic device; and responsive to determining that the context satisfies the criterion: preemptively establish a session between the electronic device and a query processor configured to process input received at a second modality of the multimodal interface; receive second modality input at the second modality of the multimodal interface; initiate processing of at least a portion of the second modality input at the query processor within the session; and build a complete query based on output from the query processor. | 11. At least one non-transitory computer readable media storing instructions that, when executed by one or more processors, cause the one or more processors to: determine, when a multimodal interface of an electronic device is at a first modality, that a context satisfies a criterion, wherein determining that the context satisfies the criterion is based on one or more signals from a sensor of the electronic device, and wherein the sensor is in addition to a microphone of the electronic device; and responsive to determining that the context satisfies the criterion: preemptively establish a session between the electronic device and a query processor configured to process input received at a second modality of the multimodal interface; receive second modality input at the second modality of the multimodal interface; initiate processing of at least a portion of the second modality input at the query processor within the session; and build a complete query based on output from the query processor. 13. The non-transitory computer readable media of claim 11 , wherein the sensor is an accelerometer. | 0.847095 |
8,725,518 | 11 | 15 | 11. A method for providing quality management related to an accent of a call responder handling a call in a contact center, comprising: creating one or more statistical accent models from one or more training speech data, each statistical accent model associated with an accent, based on accent related details from collections of speech instances that are further normalized relative to differences therebetween for accent conformity, and with a model accent score representing the conformity of the statistical accent model to the associated accent; recording by a recording system a speech sample of a call responder having a call responder accent; inputting the speech sample for analysis; preparing a statistical speech model representing the speech sample of the call responder; comparing the statistical speech model with said statistical accent models; determining a closest statistical accent model to said statistical speech model; assigning an accent score for the statistical speech model, the accent score corresponding to the model accent score of the closest statistical accent model; automatically amending in the speech sample by replacement waveforms, sections determined as having known errors, whereby the amended speech sample replaces the speech sample to conform to the closest accent model; and providing during the call conducted by the call responder an immediate visual feedback indicating the level of deviation of the agent from the required accent. | 11. A method for providing quality management related to an accent of a call responder handling a call in a contact center, comprising: creating one or more statistical accent models from one or more training speech data, each statistical accent model associated with an accent, based on accent related details from collections of speech instances that are further normalized relative to differences therebetween for accent conformity, and with a model accent score representing the conformity of the statistical accent model to the associated accent; recording by a recording system a speech sample of a call responder having a call responder accent; inputting the speech sample for analysis; preparing a statistical speech model representing the speech sample of the call responder; comparing the statistical speech model with said statistical accent models; determining a closest statistical accent model to said statistical speech model; assigning an accent score for the statistical speech model, the accent score corresponding to the model accent score of the closest statistical accent model; automatically amending in the speech sample by replacement waveforms, sections determined as having known errors, whereby the amended speech sample replaces the speech sample to conform to the closest accent model; and providing during the call conducted by the call responder an immediate visual feedback indicating the level of deviation of the agent from the required accent. 15. A method according to claim 11 , further comprising notifying a speaker if the determined closest statistical accent changes during a conversation. | 0.658371 |
7,831,491 | 9 | 10 | 9. A computer-readable medium containing computer-executable instructions that, when executed, cause a computer to perform a method comprising: (a) creating a first template at a computer, the first template defining a market data message format that includes a plurality of fields separated by delimiters; (b) transmitting the first template from the computer; (c) creating a first market data message formatted in accordance with the first template; (d) creating a second template at the computer, the second template defining a market data message format that includes a plurality of fields separated by delimiters and being different from the first template; (e) transmitting the second template from the computer; and (f) creating a second market data message formatted in accordance with the second template. | 9. A computer-readable medium containing computer-executable instructions that, when executed, cause a computer to perform a method comprising: (a) creating a first template at a computer, the first template defining a market data message format that includes a plurality of fields separated by delimiters; (b) transmitting the first template from the computer; (c) creating a first market data message formatted in accordance with the first template; (d) creating a second template at the computer, the second template defining a market data message format that includes a plurality of fields separated by delimiters and being different from the first template; (e) transmitting the second template from the computer; and (f) creating a second market data message formatted in accordance with the second template. 10. The computer-readable medium of claim 9 , wherein the orders of the plurality of fields is defined by the first and second templates. | 0.881076 |
9,984,065 | 13 | 17 | 13. A computer system for optimizing generation of a regular expression utilized for entity extraction, the computer system comprising: one or more processors, one or more computer readable memories, one or more computer readable storage media, and program instructions stored on the one or more storage media for execution by the one or more processors via the one or more memories, the program instructions comprising: a computer readable tangible storage device and program instructions stored on the computer readable tangible storage device, the program instructions include: program instructions to receive at a server, an input from a user of the server, the input enabling at least a first performance optimization parameter; program instructions to receive, from a user of a client computer, a query comprising a plain text word; program instructions to receive, at the server, data extracted from an electronic repository that is communicatively connected to the server, the data describing probabilities of spelling errors based, at least in part, on a number of syllables in the plain text word; program instructions to initialize, at the server, the first performance optimization parameter based, at least in part, on the received data and the input enabling at least the first performance optimization parameter; program instructions to optimize performance of generating the regular expression, at the server, by, at least in part, executing program instructions to identify, using the first performance optimization parameter, a syllable within the plain text word that has a high probability of at least one of an incorrectly substituted and transposed character within a spelling of a word having a same number of syllables as the plain text word; program instructions to select, at the server, a character in the syllable identified; program instructions to identify, at the server, a group of characters from a confusion matrix that are commonly confused with the character selected; program instructions to generate, at the server, a set of characters for the character selected, wherein the set of characters begins with the character selected followed by and ending with the group of characters from the confusion matrix; program instructions to determine, at the server, that a probability of omitting the character selected exceeds a threshold, and in response, associating, at the server, a tag with the set of characters; program instructions to generate, at the server, a regular expression by concatenating the set of characters with one or more additional sets of characters; program instructions to, based, at least in part, on the tag and the regular expression, search, at the server, the electronic repository for text data describing a spelling of the plain text word in which at least one of (i) the character selected and (ii) one or more characters of the group of characters from the confusion matrix is omitted; and program instructions to provide, to the user of the client computer, search results based on the regular expression. | 13. A computer system for optimizing generation of a regular expression utilized for entity extraction, the computer system comprising: one or more processors, one or more computer readable memories, one or more computer readable storage media, and program instructions stored on the one or more storage media for execution by the one or more processors via the one or more memories, the program instructions comprising: a computer readable tangible storage device and program instructions stored on the computer readable tangible storage device, the program instructions include: program instructions to receive at a server, an input from a user of the server, the input enabling at least a first performance optimization parameter; program instructions to receive, from a user of a client computer, a query comprising a plain text word; program instructions to receive, at the server, data extracted from an electronic repository that is communicatively connected to the server, the data describing probabilities of spelling errors based, at least in part, on a number of syllables in the plain text word; program instructions to initialize, at the server, the first performance optimization parameter based, at least in part, on the received data and the input enabling at least the first performance optimization parameter; program instructions to optimize performance of generating the regular expression, at the server, by, at least in part, executing program instructions to identify, using the first performance optimization parameter, a syllable within the plain text word that has a high probability of at least one of an incorrectly substituted and transposed character within a spelling of a word having a same number of syllables as the plain text word; program instructions to select, at the server, a character in the syllable identified; program instructions to identify, at the server, a group of characters from a confusion matrix that are commonly confused with the character selected; program instructions to generate, at the server, a set of characters for the character selected, wherein the set of characters begins with the character selected followed by and ending with the group of characters from the confusion matrix; program instructions to determine, at the server, that a probability of omitting the character selected exceeds a threshold, and in response, associating, at the server, a tag with the set of characters; program instructions to generate, at the server, a regular expression by concatenating the set of characters with one or more additional sets of characters; program instructions to, based, at least in part, on the tag and the regular expression, search, at the server, the electronic repository for text data describing a spelling of the plain text word in which at least one of (i) the character selected and (ii) one or more characters of the group of characters from the confusion matrix is omitted; and program instructions to provide, to the user of the client computer, search results based on the regular expression. 17. The computer system of claim 13 , wherein the program instructions to identify the group of characters comprise program instructions to search the confusion matrix for three characters most commonly confused with the character selected and program instructions to search the confusion matrix for a percentage of characters commonly confused with the character selected. | 0.623992 |
9,473,634 | 1 | 2 | 1. A system for monitoring compliance by an agent of a contact center on a call to a remote party comprising: a processor configured to: receive a first event notification from a speech analytics component indicating detection of a first keyword from a first keyword set in speech associated with the call from the remote party; start a timer after receipt of the first event notification; receive a second event notification from the speech analytics component after receiving the first event notification, the second event notification indicating detection of a second keyword from a second keyword set in speech associated with the call from the agent; and perform an action in response to determining the second event notification is not received prior to expiry of the timer, wherein the action comprises displaying a visual indication on a display of a computer terminal used by the agent informing the agent of a non-compliant response. | 1. A system for monitoring compliance by an agent of a contact center on a call to a remote party comprising: a processor configured to: receive a first event notification from a speech analytics component indicating detection of a first keyword from a first keyword set in speech associated with the call from the remote party; start a timer after receipt of the first event notification; receive a second event notification from the speech analytics component after receiving the first event notification, the second event notification indicating detection of a second keyword from a second keyword set in speech associated with the call from the agent; and perform an action in response to determining the second event notification is not received prior to expiry of the timer, wherein the action comprises displaying a visual indication on a display of a computer terminal used by the agent informing the agent of a non-compliant response. 2. The system of claim 1 , wherein the processor is further configured to: receive a third event notification from the speech analytics component indicating detection of a third keyword from the second keyword set in speech from the agent, wherein the third event notification is received after expiry of the timer. | 0.642045 |
8,260,756 | 1 | 9 | 1. A computer-implemented method of providing a comprehensive coordinated electronic document system (CCEDS), comprising: providing a website portal, wherein a customer accesses the website portal, and wherein a financial institution stores at least one non-personalized electronic document and at least one personalized electronic document of the customer, wherein the non-personalized electronic document is selected from the group consisting of blank forms, informational documents, new account applications, transfers, payments, insurance documents, student center documents, tax documents, legal documents, disclosure statements, and agreements; accessing a database comprising non-personalized electronic documents, at least one list of actions, at least one list of customer service interaction triggers, and at least one record of document actions; providing access for the customer to the at least one non-personalized electronic document stored in the database; determining, through the use of a processor, at least one action from the list of actions performed by the customer with regard to the at least one non-personalized electronic document, wherein the action consists of at least one of completing at least a portion of a blank form, submitting a form, performing a document search, adding notes to a document, saving a document, emailing a document, viewing a personalized document, and initiating a customer service interaction regarding a document, wherein the non-personalized electronic document becomes a personalized document after the customer takes the at least one action on the non-personalized document; identifying a trigger from the list of customer service interaction triggers, wherein the trigger is associated with the action taken by the customer, and wherein the trigger is a predefined feature that is correlated to a customer service interaction; initiating the customer service interaction between the customer and a specialized employee of the financial institution in response to the trigger, wherein the customer service interaction is routed to the specialized employee based on the personalized document, and wherein the customer and the specialized employee access the personalized document; and creating a record of the at least one action taken, wherein the record comprises a link to a customer service history record for the customer service interactions pertaining to the personalized electronic document. | 1. A computer-implemented method of providing a comprehensive coordinated electronic document system (CCEDS), comprising: providing a website portal, wherein a customer accesses the website portal, and wherein a financial institution stores at least one non-personalized electronic document and at least one personalized electronic document of the customer, wherein the non-personalized electronic document is selected from the group consisting of blank forms, informational documents, new account applications, transfers, payments, insurance documents, student center documents, tax documents, legal documents, disclosure statements, and agreements; accessing a database comprising non-personalized electronic documents, at least one list of actions, at least one list of customer service interaction triggers, and at least one record of document actions; providing access for the customer to the at least one non-personalized electronic document stored in the database; determining, through the use of a processor, at least one action from the list of actions performed by the customer with regard to the at least one non-personalized electronic document, wherein the action consists of at least one of completing at least a portion of a blank form, submitting a form, performing a document search, adding notes to a document, saving a document, emailing a document, viewing a personalized document, and initiating a customer service interaction regarding a document, wherein the non-personalized electronic document becomes a personalized document after the customer takes the at least one action on the non-personalized document; identifying a trigger from the list of customer service interaction triggers, wherein the trigger is associated with the action taken by the customer, and wherein the trigger is a predefined feature that is correlated to a customer service interaction; initiating the customer service interaction between the customer and a specialized employee of the financial institution in response to the trigger, wherein the customer service interaction is routed to the specialized employee based on the personalized document, and wherein the customer and the specialized employee access the personalized document; and creating a record of the at least one action taken, wherein the record comprises a link to a customer service history record for the customer service interactions pertaining to the personalized electronic document. 9. The method of claim 1 , wherein the specialized employee and the customer take the action on a single personalized document. | 0.884755 |
9,965,540 | 1 | 2 | 1. A system configured to facilitate associating semantic labels with content, the system comprising: one or more processors configured by machine readable instructions to: obtain matched sets of documents, wherein individual matched sets of documents include a structured document and an unstructured document having related content; identify numeric instances present in the documents obtained by the document module such that, responsive to obtaining a first matched set of documents including a first structured document and a first unstructured document, the fact module identifies a first set of numeric instances present in the first structured document and a second set of numeric instances present in the first unstructured document, wherein the individual numeric instances represent numbers; correlate numeric instances in different documents in a common matched set of documents that express matching numbers such that, responsive to the first set of numeric instances including a first numeric instance expressing a first number and the second set of numeric instances including a second numeric instance expressing the first number, the first numeric instance and the second numeric instance are correlated based on the common expression of the first number; determine, responsive to identification of the first set of numeric instances in the first structured document and to correlation of the first numeric instance with the second numeric instance, structured contextual information for the first numeric instance, such structured contextual information labeling the first numeric instance and/or content associated with the first numeric instance in the first structured document, such structured contextual information including one or more of a semantic label, a dimension, or an attribute of the first numeric instance and/or the content associated with the first numeric instance; analyze associated structured contextual information for the first numeric instance and content appearing with the second numeric instance to determine one or more trends in the associated contextual information; determine unstructured contextual information for correlated numeric instances such that, responsive to correlation of the first numeric instance with the second numeric instance, unstructured contextual information for the second numeric instance is determined, the unstructured contextual information including the content appearing with the second numeric instance in the first unstructured document; facilitate user entry of content into a second unstructured document being authored by a user through a graphical user interface presented to the user subsequent to correlation of the numeric instances in the first structured document and the first unstructured document; and determine and present to the user, through the graphical user interface concurrent with user entry of content, suggested semantic labels for content being entered to the second unstructured document by the user based on the trends in the associated contextual information, such presentation being performed during the user entry of the content into the second unstructured document through the graphical user interface. | 1. A system configured to facilitate associating semantic labels with content, the system comprising: one or more processors configured by machine readable instructions to: obtain matched sets of documents, wherein individual matched sets of documents include a structured document and an unstructured document having related content; identify numeric instances present in the documents obtained by the document module such that, responsive to obtaining a first matched set of documents including a first structured document and a first unstructured document, the fact module identifies a first set of numeric instances present in the first structured document and a second set of numeric instances present in the first unstructured document, wherein the individual numeric instances represent numbers; correlate numeric instances in different documents in a common matched set of documents that express matching numbers such that, responsive to the first set of numeric instances including a first numeric instance expressing a first number and the second set of numeric instances including a second numeric instance expressing the first number, the first numeric instance and the second numeric instance are correlated based on the common expression of the first number; determine, responsive to identification of the first set of numeric instances in the first structured document and to correlation of the first numeric instance with the second numeric instance, structured contextual information for the first numeric instance, such structured contextual information labeling the first numeric instance and/or content associated with the first numeric instance in the first structured document, such structured contextual information including one or more of a semantic label, a dimension, or an attribute of the first numeric instance and/or the content associated with the first numeric instance; analyze associated structured contextual information for the first numeric instance and content appearing with the second numeric instance to determine one or more trends in the associated contextual information; determine unstructured contextual information for correlated numeric instances such that, responsive to correlation of the first numeric instance with the second numeric instance, unstructured contextual information for the second numeric instance is determined, the unstructured contextual information including the content appearing with the second numeric instance in the first unstructured document; facilitate user entry of content into a second unstructured document being authored by a user through a graphical user interface presented to the user subsequent to correlation of the numeric instances in the first structured document and the first unstructured document; and determine and present to the user, through the graphical user interface concurrent with user entry of content, suggested semantic labels for content being entered to the second unstructured document by the user based on the trends in the associated contextual information, such presentation being performed during the user entry of the content into the second unstructured document through the graphical user interface. 2. The system of claim 1 , wherein the one or more processors are further configured to correlate numeric instances in the structured documents with numeric instances in the unstructured documents responsive to the numeric instances in the structured documents expressing numbers that are unique on a per document basis such that the first numeric instance is correlated to the second numeric instance responsive to the first number being unique in the first unstructured document and/or the first structured document. | 0.608169 |
8,127,220 | 33 | 41 | 33. A system, comprising: means for identifying a document based on an address associated with the document, the document including links that point to linked documents; means for determining scores for a plurality of the links in the identified document; means for comparing the determined scores to a threshold; means for determining that a score for one of the plurality of links is greater than the threshold; means for determining additional information regarding the linked document pointed to by the one of the plurality of links; and means for providing the identified document with the additional information to a user. | 33. A system, comprising: means for identifying a document based on an address associated with the document, the document including links that point to linked documents; means for determining scores for a plurality of the links in the identified document; means for comparing the determined scores to a threshold; means for determining that a score for one of the plurality of links is greater than the threshold; means for determining additional information regarding the linked document pointed to by the one of the plurality of links; and means for providing the identified document with the additional information to a user. 41. The system of claim 33 , wherein the means for determining the scores includes at least two of: means for: determining, for each of the linked documents, scores for one or more linking documents that contain links to the linked document, determining a score for each of the linked documents based on the scores of the one or more linking documents, and associating the determined scores for the linked documents with the corresponding links in the identified document; means for: determining a clickthrough rate for each of the linked documents, determining a score for each of the linked documents based on the determined clickthrough rates, and associating the determined scores for the linked documents with the corresponding links in the identified document; means for: determining a measure of popularity associated with each of the linked documents, determining a score for each of the linked documents based on the determined measure of popularity, and associating the determined scores for the linked documents with the corresponding links in the identified document; or means for: receiving input from the user, determining a score for each of the linked documents based on the received input, and associating the determined scores for the linked documents with the corresponding links in the identified document. | 0.628987 |
7,849,148 | 8 | 15 | 8. The method of claim 7 , and further comprising, utilizing the at least one window, displaying, in response to a second user interaction, the second additional information associated with the second message. | 8. The method of claim 7 , and further comprising, utilizing the at least one window, displaying, in response to a second user interaction, the second additional information associated with the second message. 15. The method of claim 8 , wherein the first additional information and the second additional information are displayed utilizing a graphical user interface element of variable size that is determined by a user. | 0.949452 |
9,837,071 | 5 | 8 | 5. The method of claim 1 , further comprising storing a speaker personalization profile having information for the modified speech interface. | 5. The method of claim 1 , further comprising storing a speaker personalization profile having information for the modified speech interface. 8. The method of claim 5 , wherein multiple speakers are associated with the speaker personalization profile. | 0.953853 |
9,292,522 | 9 | 16 | 9. A system for performing operations on structured computer text, the system comprising: a processor; a storage device; a user input device; a user display; and computer executable instructions operative on the processor for: converting structured text in a computing system into strings of tokens representing text formats; identifying repeating patterns of said text formats within said structured computer text; determining pattern transformation procedures for transforming text strings within said structured computer text; building transformation algorithms for performing said pattern transformation procedures on said text strings; applying said algorithms to said text strings within said structured computer text that match a pattern; whereby said structured computer text is transformed from a first pattern to a second pattern; accepting a first input array of strings containing actual lexeme types; determining all possible text patterns within said first input array; building a third output array of strings representing text patterns in said structured computer text; accepting said third output array of strings representing text patterns in said structured computer text; removing all text patterns within said third output array containing text patterns of smaller size; removing all patterns within said third output array containing text patterns that can be generated by shifting elements in other text patterns. | 9. A system for performing operations on structured computer text, the system comprising: a processor; a storage device; a user input device; a user display; and computer executable instructions operative on the processor for: converting structured text in a computing system into strings of tokens representing text formats; identifying repeating patterns of said text formats within said structured computer text; determining pattern transformation procedures for transforming text strings within said structured computer text; building transformation algorithms for performing said pattern transformation procedures on said text strings; applying said algorithms to said text strings within said structured computer text that match a pattern; whereby said structured computer text is transformed from a first pattern to a second pattern; accepting a first input array of strings containing actual lexeme types; determining all possible text patterns within said first input array; building a third output array of strings representing text patterns in said structured computer text; accepting said third output array of strings representing text patterns in said structured computer text; removing all text patterns within said third output array containing text patterns of smaller size; removing all patterns within said third output array containing text patterns that can be generated by shifting elements in other text patterns. 16. The system according to claim 9 , further including: accepting sixth, seventh, eighth, and ninth input arrays of text strings; interfacing with structured computer text edited by a text editing software application; identifying regions within said structured computer text being currently edited by said text editing software application; implementing said transformation algorithms to effect pattern transformations within said structured computer text. | 0.501089 |
8,457,996 | 1 | 4 | 1. A system comprising: at least one processor; a non-transitory computer-readable medium including instructions, when executed by the at least one processor, are configured to implement, a business process model (BPM) handler configured to cause the at least one processor to determine a business process model including tasks arranged according to a directed graph, at least some of the tasks associated with requirements for executing the tasks; an information technology topology model (ITTM) handler configured to cause the at least one processor to determine an information technology topology model with connected resources used to perform at least some of the tasks; and a model converter configured to cause the at least one processor to convert the business process model and the information technology topology model into a format compatible for input to a continuity analyzer, including, a behavior model generator configured to cause the at least one processor to determine behaviors of the resources from a behavior information library, and to generate a behavior model in which the tasks and their respective requirements are connected to the resources and to their respective behaviors, the behavior model having the format compatible for input to the continuity analyzer, wherein the continuity analyzer is configured to cause the at least one processor to provide a continuity analysis, based on the behavior model, the continuity analysis providing information related to potential risks, impacts, or recovery operations associated with predicted or potential business discontinuities. | 1. A system comprising: at least one processor; a non-transitory computer-readable medium including instructions, when executed by the at least one processor, are configured to implement, a business process model (BPM) handler configured to cause the at least one processor to determine a business process model including tasks arranged according to a directed graph, at least some of the tasks associated with requirements for executing the tasks; an information technology topology model (ITTM) handler configured to cause the at least one processor to determine an information technology topology model with connected resources used to perform at least some of the tasks; and a model converter configured to cause the at least one processor to convert the business process model and the information technology topology model into a format compatible for input to a continuity analyzer, including, a behavior model generator configured to cause the at least one processor to determine behaviors of the resources from a behavior information library, and to generate a behavior model in which the tasks and their respective requirements are connected to the resources and to their respective behaviors, the behavior model having the format compatible for input to the continuity analyzer, wherein the continuity analyzer is configured to cause the at least one processor to provide a continuity analysis, based on the behavior model, the continuity analysis providing information related to potential risks, impacts, or recovery operations associated with predicted or potential business discontinuities. 4. The system of claim 1 , wherein the ITTM handler comprises a business continuity (BC) transformer configured to modify the ITTM to filter information therefrom which is not relevant to the connected resources. | 0.706371 |
7,543,237 | 13 | 16 | 13. A method of collaborating across a computing network comprising: generating, at a terminal collaborative gateway graphical user interface for at least one of a plurality of collaboration applications, the at least one of the plurality of collaboration applications including at least one of a plurality of collaboration options on a display of the terminal; background text scanning, at the terminal, a plurality of open documents displayed on the terminal to detect an unparsed, or unscanned, or new, document among all the displayed documents; determining, at the terminal, whether the at least one unparsed, or unscanned, or new, document from among all the displayed documents is an active document; in response to determination that the at least one unparsed document is the active document, context parsing, or scanning, the active document at the terminal to identify a document context; detecting, at the terminal, that the document context of the active document is unknown; retrieving a user context profile via the computer network stored in a context profile database from a server, wherein the user context profile is associated with a user account of a user of the terminal, and wherein at least a portion of the user context profile is at least partially defined by the user; comparing, at the terminal, the detected document context of the active document to the retrieved user context profile to determine a correlation, or a match, between the detected document context of the active document and the retrieved context profile; determining, at the terminal, whether the detected document context includes a relevant context based upon the correlation or the match of the detected document context of the active document to the retrieved context profile of the user; in response to determination that the detected document context includes the relevant context, t identifying, at the terminal, a subject matter related context in which the terminal is being used by the user based upon the correlation between the detected document context and the relevant context; generating, at the terminal, a context message including a user identifier and a context indication based upon the identified subject matter related context; sending, from the terminal, the context message to a collaboration assistance application resident on the server; receiving, at the terminal, a new context notification generated by the collaboration assistant application in response to the context message; and adjusting the display of the at least one of the collaboration options in the collaborative gateway graphical user interface based upon the new context notification. | 13. A method of collaborating across a computing network comprising: generating, at a terminal collaborative gateway graphical user interface for at least one of a plurality of collaboration applications, the at least one of the plurality of collaboration applications including at least one of a plurality of collaboration options on a display of the terminal; background text scanning, at the terminal, a plurality of open documents displayed on the terminal to detect an unparsed, or unscanned, or new, document among all the displayed documents; determining, at the terminal, whether the at least one unparsed, or unscanned, or new, document from among all the displayed documents is an active document; in response to determination that the at least one unparsed document is the active document, context parsing, or scanning, the active document at the terminal to identify a document context; detecting, at the terminal, that the document context of the active document is unknown; retrieving a user context profile via the computer network stored in a context profile database from a server, wherein the user context profile is associated with a user account of a user of the terminal, and wherein at least a portion of the user context profile is at least partially defined by the user; comparing, at the terminal, the detected document context of the active document to the retrieved user context profile to determine a correlation, or a match, between the detected document context of the active document and the retrieved context profile; determining, at the terminal, whether the detected document context includes a relevant context based upon the correlation or the match of the detected document context of the active document to the retrieved context profile of the user; in response to determination that the detected document context includes the relevant context, t identifying, at the terminal, a subject matter related context in which the terminal is being used by the user based upon the correlation between the detected document context and the relevant context; generating, at the terminal, a context message including a user identifier and a context indication based upon the identified subject matter related context; sending, from the terminal, the context message to a collaboration assistance application resident on the server; receiving, at the terminal, a new context notification generated by the collaboration assistant application in response to the context message; and adjusting the display of the at least one of the collaboration options in the collaborative gateway graphical user interface based upon the new context notification. 16. The method of claim 13 , wherein adjusting the display of the at least one of the collaboration applications in the collaborative gateway graphical user interface further comprises: displaying a list of calendared events, a user email list, and a task list that are each related to the identified subject matter related context. | 0.869906 |
8,832,542 | 10 | 17 | 10. An apparatus for providing a hyperlink on a network comprising: a communication device for receiving an image of at least one character fixed in a medium; a processor coupled to a memory for storing a control program, the control program renders the apparatus to function as: a first module for determining at least one letter of an alphabet corresponding to the at least one character; a decoding module for identifying at least one symbol applied onto at least a portion of the determined letter, determining a type of the identified at least one symbol and a location of the identified at least one symbol on the determined letter and determining a numerical value for the identified at least one symbol based on the determined letter, the determined type of the at least one symbol and location of the identified at least one symbol on the determined letter; and a lookup module for looking up in a database a hyperlink corresponding to the numerical value and presenting the hyperlink on a display device. | 10. An apparatus for providing a hyperlink on a network comprising: a communication device for receiving an image of at least one character fixed in a medium; a processor coupled to a memory for storing a control program, the control program renders the apparatus to function as: a first module for determining at least one letter of an alphabet corresponding to the at least one character; a decoding module for identifying at least one symbol applied onto at least a portion of the determined letter, determining a type of the identified at least one symbol and a location of the identified at least one symbol on the determined letter and determining a numerical value for the identified at least one symbol based on the determined letter, the determined type of the at least one symbol and location of the identified at least one symbol on the determined letter; and a lookup module for looking up in a database a hyperlink corresponding to the numerical value and presenting the hyperlink on a display device. 17. The apparatus as in claim 10 , wherein the decoding module is further adapted for segmenting the at least one character into at least two segments and determining a symbol in each of the at least two segments. | 0.672308 |
7,752,046 | 15 | 16 | 15. The method of claim 14 , wherein splitting the leaf with the largest likelihood gain is iterative. | 15. The method of claim 14 , wherein splitting the leaf with the largest likelihood gain is iterative. 16. The method of claim 15 , wherein one the likelihood gain of a best leaf split falls below a threshold value, terminating the iterative splitting process, wherein the unigram tree defines N leaf sets. | 0.913764 |
9,147,392 | 2 | 7 | 2. The speech synthesis device according to claim 1 , wherein the executable instructions, when executed by said processor, cause said speech synthesis device to further function as an agreement degree calculation unit configured to, for each of the phonemes generated from the text, select a piece of segment information having a phoneme type that matches the type of the phoneme from among the pieces of segment information stored in the segment storage unit, and calculate a degree of agreement between the mouth opening degree generated by the mouth opening degree generation unit and the mouth opening degree included in the selected piece of segment information, wherein the segment selection unit is configured to select, for each of the phonemes generated from the text, the piece of segment information corresponding to the phoneme, based on the degree of agreement calculated for the phoneme. | 2. The speech synthesis device according to claim 1 , wherein the executable instructions, when executed by said processor, cause said speech synthesis device to further function as an agreement degree calculation unit configured to, for each of the phonemes generated from the text, select a piece of segment information having a phoneme type that matches the type of the phoneme from among the pieces of segment information stored in the segment storage unit, and calculate a degree of agreement between the mouth opening degree generated by the mouth opening degree generation unit and the mouth opening degree included in the selected piece of segment information, wherein the segment selection unit is configured to select, for each of the phonemes generated from the text, the piece of segment information corresponding to the phoneme, based on the degree of agreement calculated for the phoneme. 7. The speech synthesis device according to claim 2 , wherein the agreement degree calculation unit is configured to, for each of the phonemes generated from the text, normalize, on a phoneme type basis, (i) the mouth opening degree included in the piece of segment information stored in the segment storage unit and having the phoneme type that matches the type of the phoneme and (ii) the mouth opening degree generated by the mouth opening degree generation unit, and calculate, as the degree of agreement, a degree of agreement between the normalized mouth opening degrees. | 0.83486 |
8,676,565 | 34 | 35 | 34. A method implemented by one or more computer processors, the method comprising: clustering a plurality of semantic graphs that were formed based on a linguistic analysis of a corpus of user utterances into a plurality of semantic clusters through use of one or more proximity metrics; identifying which of the plurality of semantic clusters include divergent sub-clusters; and offering the identified semantic clusters for review in a user interface. | 34. A method implemented by one or more computer processors, the method comprising: clustering a plurality of semantic graphs that were formed based on a linguistic analysis of a corpus of user utterances into a plurality of semantic clusters through use of one or more proximity metrics; identifying which of the plurality of semantic clusters include divergent sub-clusters; and offering the identified semantic clusters for review in a user interface. 35. A method as described in claim 34 , wherein the offering is performed for both divergent and convergent sub-clusters in the identified semantic clusters. | 0.908933 |
8,788,991 | 2 | 6 | 2. The method of claim 1 , wherein the instances of the netlist include a state machine element (SME) instance corresponding to SME hardware elements and a SME group instance corresponding to a hardware element comprising a group of SMEs, and wherein grouping the states of the automaton together includes grouping the states of the automaton into a SME group instance. | 2. The method of claim 1 , wherein the instances of the netlist include a state machine element (SME) instance corresponding to SME hardware elements and a SME group instance corresponding to a hardware element comprising a group of SMEs, and wherein grouping the states of the automaton together includes grouping the states of the automaton into a SME group instance. 6. The method of claim 2 , wherein a SME group instance includes a group of two (GOT) instance containing two SME instances, and wherein the physical design used in grouping the states of the automaton together includes a limitation that the SMEs in each GOT are coupled to a common output. | 0.917332 |
9,195,373 | 1 | 3 | 1. A method for navigating in an electronic book comprising: displaying at least a portion of a current page in a current chapter of the electronic book on a display screen of an electronic device; storing a position of the current page as P and the current chapter as C in a memory of the electronic device. detecting simultaneous multiple touches on a touch sensitive surface of the electronic device; detecting a gesture comprised of the movement of the simultaneous multiple touches; interpreting the detected gesture as a command to navigate to a different page of the electronic book, the different page being more than one page away from the current page P if P is more than one page away from a beginning or end of the current chapter C; and displaying at least a portion of the different page of the electronic book in response to the detection and interpretation of the gesture. | 1. A method for navigating in an electronic book comprising: displaying at least a portion of a current page in a current chapter of the electronic book on a display screen of an electronic device; storing a position of the current page as P and the current chapter as C in a memory of the electronic device. detecting simultaneous multiple touches on a touch sensitive surface of the electronic device; detecting a gesture comprised of the movement of the simultaneous multiple touches; interpreting the detected gesture as a command to navigate to a different page of the electronic book, the different page being more than one page away from the current page P if P is more than one page away from a beginning or end of the current chapter C; and displaying at least a portion of the different page of the electronic book in response to the detection and interpretation of the gesture. 3. The method according to claim 1 , wherein the act of detecting the gesture further comprises detecting a left to right swipe of the simultaneous multiple touches. | 0.939338 |
9,542,947 | 1 | 3 | 1. A computer-implemented method comprising: defining, in an automated speech recognizer in which audio data is processed by a signal conditioning stage followed by a noise suppression stage followed by a language modeling stage, the signal conditioning stage including quantity i processing alternatives, the noise suppression stage including quantity j processing alternatives, and the language modeling stage including quantity k processing alternatives, quantity (i*j*k) alternative paths for processing the audio data through the multiple stages of the automated speech recognizer, i, j, and k being greater than one; generating, for each of the quantity (i*j*k) alternative paths, a transcription of particular audio data based on processing the particular audio data through each of the stages of the automated speech recognizer according to the alternative path; and selecting a particular transcription from among the respective transcriptions that are generated for the quantity (i*j*k) alternative paths; and providing the particular transcription for output. | 1. A computer-implemented method comprising: defining, in an automated speech recognizer in which audio data is processed by a signal conditioning stage followed by a noise suppression stage followed by a language modeling stage, the signal conditioning stage including quantity i processing alternatives, the noise suppression stage including quantity j processing alternatives, and the language modeling stage including quantity k processing alternatives, quantity (i*j*k) alternative paths for processing the audio data through the multiple stages of the automated speech recognizer, i, j, and k being greater than one; generating, for each of the quantity (i*j*k) alternative paths, a transcription of particular audio data based on processing the particular audio data through each of the stages of the automated speech recognizer according to the alternative path; and selecting a particular transcription from among the respective transcriptions that are generated for the quantity (i*j*k) alternative paths; and providing the particular transcription for output. 3. The method of claim 1 , comprising: generating, for each of the transcriptions, a confidence score, wherein selecting the particular transcription is based on the confidence scores. | 0.801296 |
8,688,434 | 1 | 38 | 1. A computer program product comprising: a plurality of processor-executable instructions for automatically generating a narrative story from data and information, the instructions being resident on a non-transitory computer-readable storage medium and being configured, upon execution by a processor, to: receive domain related data and information, wherein the domain related data and information is representative of at least one member from the group consisting of (1) an event, (2) a circumstance, and (3) an entity; process the received domain related data and information; based on the processed domain related data and information, identify at least one angle for the narrative story from among a plurality of angles, wherein the angles comprise a plurality of data representations that connect a plurality of events, circumstances and entities as models of a thematic nature, wherein the identified at least one angle comprises an angle deemed to accurately characterize the processed domain related data and information; determine at least one point for the narrative story based on the identified at least one angle; and render a narrative story that expresses the identified at least one angle and the determined at least one point. | 1. A computer program product comprising: a plurality of processor-executable instructions for automatically generating a narrative story from data and information, the instructions being resident on a non-transitory computer-readable storage medium and being configured, upon execution by a processor, to: receive domain related data and information, wherein the domain related data and information is representative of at least one member from the group consisting of (1) an event, (2) a circumstance, and (3) an entity; process the received domain related data and information; based on the processed domain related data and information, identify at least one angle for the narrative story from among a plurality of angles, wherein the angles comprise a plurality of data representations that connect a plurality of events, circumstances and entities as models of a thematic nature, wherein the identified at least one angle comprises an angle deemed to accurately characterize the processed domain related data and information; determine at least one point for the narrative story based on the identified at least one angle; and render a narrative story that expresses the identified at least one angle and the determined at least one point. 38. The computer program product as recited in claim 1 , wherein the instructions are further configured, upon execution by a processor, to: generate a point list for the narrative story based on the identified at least one angle, the point list comprising a plurality of points for the narrative story including the determined at least one point; order the points in the point list based on the identified at least one angle; and render text for the narrative story based on an application of the ordered point list to a natural language generator. | 0.624487 |
7,743,317 | 19 | 20 | 19. The system of claim 18 , wherein the processing unit is further operative to, in response to pasting the spreadsheet element in the target document, display a recovery action user interface having at least one selectable recovery action. | 19. The system of claim 18 , wherein the processing unit is further operative to, in response to pasting the spreadsheet element in the target document, display a recovery action user interface having at least one selectable recovery action. 20. The system of claim 19 , wherein the processing unit is further operative to, in response to receiving a recovery action selection from the recovery action user interface: remove the spreadsheet element from the target document, and paste the spreadsheet element as a table with a third set of formatting properties corresponding to the target document applied thereto. | 0.896042 |
8,676,787 | 1 | 2 | 1. A system, comprising: a processor; and a memory containing a program that, when executed by the processor, performs an operation for incorporating query results into an abstract database, comprising: receiving a first set of query results produced by executing a first abstract query using a first data abstraction model against a first database; determining one or more mappings between the first set of query results and one or more logical fields in a second data abstraction model, wherein the second data abstraction model models underlying physical data in a manner making a schema of the physical data transparent to a user of the second data abstraction model, further comprising: determining similarities between at least a portion of the first set of query results and at least one field in the second database; and determining at least one logical field that maps to the at least one field in the second database; and modifying one or more logical field definitions within the second data abstraction model to further map to the at least a portion of the first set of query results, based on the determined one or more mappings, wherein the one or more logical field definitions correspond to the one or more logical fields, such that abstract queries can be executed against both a second database and the first set of query results using the modified second data abstraction model, wherein the first database is distinct from the second database, and wherein the first data abstraction model is distinct from the second data abstraction model. | 1. A system, comprising: a processor; and a memory containing a program that, when executed by the processor, performs an operation for incorporating query results into an abstract database, comprising: receiving a first set of query results produced by executing a first abstract query using a first data abstraction model against a first database; determining one or more mappings between the first set of query results and one or more logical fields in a second data abstraction model, wherein the second data abstraction model models underlying physical data in a manner making a schema of the physical data transparent to a user of the second data abstraction model, further comprising: determining similarities between at least a portion of the first set of query results and at least one field in the second database; and determining at least one logical field that maps to the at least one field in the second database; and modifying one or more logical field definitions within the second data abstraction model to further map to the at least a portion of the first set of query results, based on the determined one or more mappings, wherein the one or more logical field definitions correspond to the one or more logical fields, such that abstract queries can be executed against both a second database and the first set of query results using the modified second data abstraction model, wherein the first database is distinct from the second database, and wherein the first data abstraction model is distinct from the second data abstraction model. 2. The system of claim 1 , wherein the first abstract query comprises a sub-query from a first step of a multi-step query, and further comprising: executing a second abstract query comprising a second sub-query from a second step of the multi-step query against both the second database and the first set of query results to produce a second set of query results. | 0.818862 |
9,911,052 | 17 | 22 | 17. A system for providing handwriting recognition for a superimposed stroke input to a computing device, the computing device comprising a processor and at least one computer readable program for recognizing the input under control of the processor, said at least one program configured to: create, with a segmentation expert, a segmentation graph based on a plurality of input strokes, at least two of the strokes being at least partially superimposed on one another, wherein the segmentation graph consists of nodes and paths corresponding to character hypotheses formed by segmenting the input strokes to take into account the at least partially superimposed strokes; assign, with a recognition expert, a recognition score to each node of the segmentation graph based on language recognition information; generate, with a language expert, linguistic meaning of the input strokes by optimizing the recognition scores of the node paths of the segmentation graph based on a language model; and provide an output based on the collaborative analysis of the segmentation graph, the recognition score, and the language model by the segmentation, recognition and language experts. | 17. A system for providing handwriting recognition for a superimposed stroke input to a computing device, the computing device comprising a processor and at least one computer readable program for recognizing the input under control of the processor, said at least one program configured to: create, with a segmentation expert, a segmentation graph based on a plurality of input strokes, at least two of the strokes being at least partially superimposed on one another, wherein the segmentation graph consists of nodes and paths corresponding to character hypotheses formed by segmenting the input strokes to take into account the at least partially superimposed strokes; assign, with a recognition expert, a recognition score to each node of the segmentation graph based on language recognition information; generate, with a language expert, linguistic meaning of the input strokes by optimizing the recognition scores of the node paths of the segmentation graph based on a language model; and provide an output based on the collaborative analysis of the segmentation graph, the recognition score, and the language model by the segmentation, recognition and language experts. 22. A system according to claim 17 , wherein the language model includes linguistic information specific to one or more languages. | 0.679803 |
8,326,826 | 12 | 13 | 12. The computer-implemented method of claim 1 , wherein determining a navigation score for the revised query comprises: determining a click-through rate for each resource identified by a search engine in response to the revised query, the click-through rate being a rate at which search results generated in response to the query and referencing the resource were selected; and wherein the navigation score threshold is a click-through rate threshold. | 12. The computer-implemented method of claim 1 , wherein determining a navigation score for the revised query comprises: determining a click-through rate for each resource identified by a search engine in response to the revised query, the click-through rate being a rate at which search results generated in response to the query and referencing the resource were selected; and wherein the navigation score threshold is a click-through rate threshold. 13. The computer-implemented method of claim 12 , wherein identifying the navigational resource for the revised query comprises identifying as the navigational resource the resource having a click-through rate that exceeds the click-through rate threshold. | 0.940243 |
9,466,081 | 11 | 15 | 11. A system comprising: a processor; and a computer-readable storage device storing instructions which, when executed by the processor, cause the processor to perform operations comprising: establishing, from a merchant site, communication between the merchant site and a generalized search entity via a communication interface, wherein the generalized search entity: presents an input field on a user interface of a generalized search entity, wherein the generalized search entity processes data using a generalized search engine that indexes and searches both merchant sites and non-merchant sites; receives a text-based query in the input field; correlates the text-based query against a product database of products for sale from merchants to yield a correlation; determines, based at least in part on the correlation, that the text-based query is associated with one of a search intent and a purchase intent to yield a determination; and when the determination indicates the search intent: presents a search result comprising a non-merchant site; receives a search interaction associated with the non-merchant site; and transitions, based on the search interaction, to the non-merchant site; and when the determination indicates the purchase intent: presents a purchase-related search result comprising a buy option associated with the text-based query, wherein the purchase-related search result is configured such that when a user interacts with the purchase-related search result and confirms a purchase via interacting with the buy option, the generalized search entity initiates processing of the purchase of an item; and receives an interaction from the user associated with the purchase-related search result. | 11. A system comprising: a processor; and a computer-readable storage device storing instructions which, when executed by the processor, cause the processor to perform operations comprising: establishing, from a merchant site, communication between the merchant site and a generalized search entity via a communication interface, wherein the generalized search entity: presents an input field on a user interface of a generalized search entity, wherein the generalized search entity processes data using a generalized search engine that indexes and searches both merchant sites and non-merchant sites; receives a text-based query in the input field; correlates the text-based query against a product database of products for sale from merchants to yield a correlation; determines, based at least in part on the correlation, that the text-based query is associated with one of a search intent and a purchase intent to yield a determination; and when the determination indicates the search intent: presents a search result comprising a non-merchant site; receives a search interaction associated with the non-merchant site; and transitions, based on the search interaction, to the non-merchant site; and when the determination indicates the purchase intent: presents a purchase-related search result comprising a buy option associated with the text-based query, wherein the purchase-related search result is configured such that when a user interacts with the purchase-related search result and confirms a purchase via interacting with the buy option, the generalized search entity initiates processing of the purchase of an item; and receives an interaction from the user associated with the purchase-related search result. 15. The system of claim 11 , wherein the buy option comprises a one-click purchasing option. | 0.89755 |
7,860,722 | 26 | 27 | 26. A system comprising: a plurality of telephone system switches or routers, wherein each telephone system switches or router is operable to capture voice signals from telephone communications within one of a plurality of geographically distributed controlled-environment facilities; and a centralized hybrid keyword detection system connected to each of the plurality of telephone system switches or routers, where the hybrid keyword detection system is operable to use both phonetic-based keyword detection and acoustic-based keyword detection for detecting a keyword within the voice signals captured by the telephone system switches or routers, the hybrid keyword detection system first filtering the captured voice signals using a phonetic-based algorithm to identify conversations potentially containing predefined keywords, the phonetic-based algorithm producing a first result, then filtering only the captured voice signals within the first result using an acoustic-based algorithm to eliminate erroneous keyword detections by the phonetic-based algorithm, the acoustic-based algorithm producing a second result analyzing the first and second result to determining a keyword matching probability, and determining whether the keyword matching probability is greater than a threshold. | 26. A system comprising: a plurality of telephone system switches or routers, wherein each telephone system switches or router is operable to capture voice signals from telephone communications within one of a plurality of geographically distributed controlled-environment facilities; and a centralized hybrid keyword detection system connected to each of the plurality of telephone system switches or routers, where the hybrid keyword detection system is operable to use both phonetic-based keyword detection and acoustic-based keyword detection for detecting a keyword within the voice signals captured by the telephone system switches or routers, the hybrid keyword detection system first filtering the captured voice signals using a phonetic-based algorithm to identify conversations potentially containing predefined keywords, the phonetic-based algorithm producing a first result, then filtering only the captured voice signals within the first result using an acoustic-based algorithm to eliminate erroneous keyword detections by the phonetic-based algorithm, the acoustic-based algorithm producing a second result analyzing the first and second result to determining a keyword matching probability, and determining whether the keyword matching probability is greater than a threshold. 27. The system of claim 26 where the hybrid keyword detection system comprises: a hybrid keyword detection server; and a database connected to the hybrid keyword detection server. | 0.876039 |
9,565,521 | 21 | 30 | 21. A non-transitory processor-readable medium that includes a program that when executed by a processor performs a method comprising: recognizing an activity performed at a first place based on sensor data of an electronic device, wherein the first place comprises an unlabeled semantic place without an assigned semantic place label; determining a location for the first place by performing localization for the electronic device; determining an observed mapping between the activity and the location for the first place; determining a typical mapping between the activity and a second place, wherein the second place comprises a labeled semantic place with an assigned semantic place label; based on the observed mapping and the typical mapping, assigning the same sematic place label assigned to the labeled semantic place to the location for the first place; and updating a semantic place map to include the semantic place label assigned to the location for the first place. | 21. A non-transitory processor-readable medium that includes a program that when executed by a processor performs a method comprising: recognizing an activity performed at a first place based on sensor data of an electronic device, wherein the first place comprises an unlabeled semantic place without an assigned semantic place label; determining a location for the first place by performing localization for the electronic device; determining an observed mapping between the activity and the location for the first place; determining a typical mapping between the activity and a second place, wherein the second place comprises a labeled semantic place with an assigned semantic place label; based on the observed mapping and the typical mapping, assigning the same sematic place label assigned to the labeled semantic place to the location for the first place; and updating a semantic place map to include the semantic place label assigned to the location for the first place. 30. The non-transitory processor-readable medium of claim 21 , further comprising: reducing sampling rate for a sensor of the electronic device based on the activity and the location for the first place. | 0.787657 |
10,073,536 | 8 | 9 | 8. A computing device, comprising: a presence-sensitive display device; one or more processors coupled to the presence-sensitive display device; and a non-transitory computer-readable storage medium storing instructions that, when executed by the one or more processors, cause the one or more processors to perform operations, the operations comprising: outputting, via the presence-sensitive display device, a graphical keyboard comprising a plurality of keys associated with characters of a first alphabet of a first language, receiving a user input comprising one or more touches on the presence-sensitive display device, constructing a character lattice corresponding to the user input based on a spatial model, the character lattice being indicative of a spatial probability of one or more potential characters corresponding to the user input, constructing a token lattice corresponding to the user input based on the character lattice, the token lattice being indicative of a collective spatial probability of one or more potential tokens corresponding to the user input, wherein each of the one or more potential tokens corresponds to a character candidate string comprising a group of characters representing a semantic or phonetic unit, constructing a word lattice corresponding to the user input based on the token lattice and a language model, the word lattice being indicative of a probability of one or more potential words corresponding to the user input, the one or more potential words comprising one or more characters of a second alphabet of a second language, selecting at least one particular potential word of the one or more potential words based on the word lattice, and outputting, via the presence-sensitive display device, the at least one particular potential word. | 8. A computing device, comprising: a presence-sensitive display device; one or more processors coupled to the presence-sensitive display device; and a non-transitory computer-readable storage medium storing instructions that, when executed by the one or more processors, cause the one or more processors to perform operations, the operations comprising: outputting, via the presence-sensitive display device, a graphical keyboard comprising a plurality of keys associated with characters of a first alphabet of a first language, receiving a user input comprising one or more touches on the presence-sensitive display device, constructing a character lattice corresponding to the user input based on a spatial model, the character lattice being indicative of a spatial probability of one or more potential characters corresponding to the user input, constructing a token lattice corresponding to the user input based on the character lattice, the token lattice being indicative of a collective spatial probability of one or more potential tokens corresponding to the user input, wherein each of the one or more potential tokens corresponds to a character candidate string comprising a group of characters representing a semantic or phonetic unit, constructing a word lattice corresponding to the user input based on the token lattice and a language model, the word lattice being indicative of a probability of one or more potential words corresponding to the user input, the one or more potential words comprising one or more characters of a second alphabet of a second language, selecting at least one particular potential word of the one or more potential words based on the word lattice, and outputting, via the presence-sensitive display device, the at least one particular potential word. 9. The computing device of claim 8 , wherein: each of the one or more touches of the user input is associated with a location of the presence-sensitive display device; the spatial model is configured to determine a likelihood that each of the locations of the one or more touches corresponds to one or more particular potential characters; and constructing the character lattice corresponding to the user input based on the spatial model is based on the likelihoods and the locations. | 0.642012 |
8,566,154 | 39 | 43 | 39. A machine-readable medium storing instructions adapted to be executed by a processor to: receive a description of online activities for a collection of online identities for users accessing one or more affiliate web sites; identify a desired behavior, the desired behavior describing user interaction that indicates that an online identity demonstrating the desired behavior is more likely to be responsive to a re-targeted advertisement; analyze the description of online activities to determine whether a particular online identity appearing in the description of the online activities demonstrates the desired behavior; generate a watch list of users to receive advertisements based on analyzing the description of online activities; monitor, in real-time and from the one or more affiliate web sites, information related to user interaction with the one or more affiliate web sites; receive a request to display advertising content to a user; determine that the user appears in the watch list of users to receive re-targeted advertisements; and select, in response to the request, advertising content for display based upon determining that the user appears in the watch list of users to receive re-targeted advertisements. | 39. A machine-readable medium storing instructions adapted to be executed by a processor to: receive a description of online activities for a collection of online identities for users accessing one or more affiliate web sites; identify a desired behavior, the desired behavior describing user interaction that indicates that an online identity demonstrating the desired behavior is more likely to be responsive to a re-targeted advertisement; analyze the description of online activities to determine whether a particular online identity appearing in the description of the online activities demonstrates the desired behavior; generate a watch list of users to receive advertisements based on analyzing the description of online activities; monitor, in real-time and from the one or more affiliate web sites, information related to user interaction with the one or more affiliate web sites; receive a request to display advertising content to a user; determine that the user appears in the watch list of users to receive re-targeted advertisements; and select, in response to the request, advertising content for display based upon determining that the user appears in the watch list of users to receive re-targeted advertisements. 43. The medium according to claim 39 , wherein the description of online activities is a tag included in a redirect message from the Web site, the tag identifying a specific Web page and indicating a prior activity of the user at the Web site. | 0.75355 |
7,852,499 | 8 | 9 | 8. The method as set forth in claim 1 , further comprising: for each of a plurality of selected portions of the document, identifying a normal signature as a most commonly assigned signature for text fragments of that selected portion; and excluding text fragments assigned the normal signature from at least he identifying and detecting. | 8. The method as set forth in claim 1 , further comprising: for each of a plurality of selected portions of the document, identifying a normal signature as a most commonly assigned signature for text fragments of that selected portion; and excluding text fragments assigned the normal signature from at least he identifying and detecting. 9. The method as set forth in claim 8 , wherein the plurality of selected portions of the document are pages of the document. | 0.946213 |
7,877,349 | 2 | 3 | 2. The apparatus as in claim 1 , wherein the transformer module also transforms reference free-form text entries into reference rephrased objects, and the compiler module further comprises a patternization engine having patternization rules for converting each reference rephrased object into a reference pattern. | 2. The apparatus as in claim 1 , wherein the transformer module also transforms reference free-form text entries into reference rephrased objects, and the compiler module further comprises a patternization engine having patternization rules for converting each reference rephrased object into a reference pattern. 3. The apparatus as in claim 2 , wherein the transformer module comprises: a rephrased object engine, wherein a free-form text entry is transformed into a master rephrased object; and a rephrasing engine, wherein rephrasing rules are applied to the master rephrased object to generate rephrased objects. | 0.927754 |
9,531,649 | 20 | 21 | 20. The one or more non-transitory computer-readable medium of claim 14 , wherein: querying the first domain to determine that the username in the electronic message is not a valid username for the first domain is performed without an author of the electronic message specifying that the username in the electronic message is not a valid username for the first domain, and querying the second domain to determine that the username in the electronic message is a valid username for the second domain is performed without the author of the electronic message specifying that the username in the electronic message is a valid username for the second domain. | 20. The one or more non-transitory computer-readable medium of claim 14 , wherein: querying the first domain to determine that the username in the electronic message is not a valid username for the first domain is performed without an author of the electronic message specifying that the username in the electronic message is not a valid username for the first domain, and querying the second domain to determine that the username in the electronic message is a valid username for the second domain is performed without the author of the electronic message specifying that the username in the electronic message is a valid username for the second domain. 21. The one or more non-transitory computer-readable medium of claim 20 , wherein the operations further comprise selecting the first domain as a domain to use in the determination that the username in the electronic message is not a valid username for the first domain, as a result of the computing system identifying that the electronic message was authored by a first user of a messaging service that logged into the messaging service using a particular user account that included a particular username and the first domain. | 0.863965 |
10,073,881 | 15 | 18 | 15. The non-transitory computer-readable medium of claim 10 , wherein receiving the client workflow comprises receiving a plurality of client payloads representing a plurality of interactions with the client workflow, each client payload representing a particular interaction with the client workflow. | 15. The non-transitory computer-readable medium of claim 10 , wherein receiving the client workflow comprises receiving a plurality of client payloads representing a plurality of interactions with the client workflow, each client payload representing a particular interaction with the client workflow. 18. The non-transitory computer-readable medium of claim 15 , wherein a client payload is not executable by the graph database. | 0.930373 |
9,760,630 | 8 | 9 | 8. A system, comprising: a processor; and a memory storing a program, which, when executed on the processor, performs a method for generating a synonym list from a natural language query, the method comprising: preparing a first feature vector from a natural language query and preparing a second feature vector from a result of the natural language query; determining, using a processor, whether a combination of a first feature from the first feature vector and a second feature from the second feature vector is included as a synonym pair in the existing thesaurus; and generating the synonym list by adding the combination to the synonym list when the determination is positive. | 8. A system, comprising: a processor; and a memory storing a program, which, when executed on the processor, performs a method for generating a synonym list from a natural language query, the method comprising: preparing a first feature vector from a natural language query and preparing a second feature vector from a result of the natural language query; determining, using a processor, whether a combination of a first feature from the first feature vector and a second feature from the second feature vector is included as a synonym pair in the existing thesaurus; and generating the synonym list by adding the combination to the synonym list when the determination is positive. 9. The system according to claim 8 , wherein the result of the natural language query is identified by a user browsing action or by a positive feedback from a user. | 0.87404 |
9,613,054 | 14 | 16 | 14. A computer program product comprising a non-transitory computer-readable storage medium including instructions that, when executed by a processor, cause the processor to perform steps including: generating a location store comprising a plurality of entries maintained by a social networking system, each entry including a physical location description and one or more terms associated with the physical location description; selecting entries from the plurality of entries associated with a physical location; determining a global frequency of each term in an entry from the selected entries, the global frequency of each term in the entry based at least in part on a number of occurrences of the term in all of the entries of the location store; identifying candidate descriptive terms by identifying a candidate descriptive term associated with each of the selected entries, the candidate descriptive term associated with each of the selected entries being a term in an entry having a minimum global frequency of the one or more terms in the entry; determining a frequency that a first candidate descriptive term occurs in the candidate descriptive terms; modifying the global frequency of first candidate descriptive term by the frequency of first candidate descriptive term to obtain a modified global frequency for the first candidate descriptive term in the entry: identifying additional candidate descriptive terms, wherein the identifying comprises: identifying a second candidate descriptive term having a minimum modified global frequency of the one or more terms in an entry from the selected entries as an additional candidate descriptive term, and determining whether a frequency of occurrence of the additional candidate descriptive term has changed in a current iteration in comparison to a preceding iteration; responsive to determining that the frequency of occurrence of the additional candidate descriptive term is unchanged, identifying one or more the additional candidate descriptive term as a descriptive term associated with the physical location description; receiving a physical location description from a client device; retrieving, from the location store, a plurality of entries for the physical location description; and providing for display, from the plurality of retrieved entries, one or more entries to the client device for presentation to a user of the client device, wherein the one or more entries being presented on the client device are based on the additional candidate descriptive term associated with the physical location description. | 14. A computer program product comprising a non-transitory computer-readable storage medium including instructions that, when executed by a processor, cause the processor to perform steps including: generating a location store comprising a plurality of entries maintained by a social networking system, each entry including a physical location description and one or more terms associated with the physical location description; selecting entries from the plurality of entries associated with a physical location; determining a global frequency of each term in an entry from the selected entries, the global frequency of each term in the entry based at least in part on a number of occurrences of the term in all of the entries of the location store; identifying candidate descriptive terms by identifying a candidate descriptive term associated with each of the selected entries, the candidate descriptive term associated with each of the selected entries being a term in an entry having a minimum global frequency of the one or more terms in the entry; determining a frequency that a first candidate descriptive term occurs in the candidate descriptive terms; modifying the global frequency of first candidate descriptive term by the frequency of first candidate descriptive term to obtain a modified global frequency for the first candidate descriptive term in the entry: identifying additional candidate descriptive terms, wherein the identifying comprises: identifying a second candidate descriptive term having a minimum modified global frequency of the one or more terms in an entry from the selected entries as an additional candidate descriptive term, and determining whether a frequency of occurrence of the additional candidate descriptive term has changed in a current iteration in comparison to a preceding iteration; responsive to determining that the frequency of occurrence of the additional candidate descriptive term is unchanged, identifying one or more the additional candidate descriptive term as a descriptive term associated with the physical location description; receiving a physical location description from a client device; retrieving, from the location store, a plurality of entries for the physical location description; and providing for display, from the plurality of retrieved entries, one or more entries to the client device for presentation to a user of the client device, wherein the one or more entries being presented on the client device are based on the additional candidate descriptive term associated with the physical location description. 16. The computer program product of claim 14 , wherein identifying the additional candidate descriptive terms associated with the physical location comprises: ranking the candidate descriptive terms based at least in part on frequencies that each candidate descriptive term occurs in the candidate descriptive terms; and selecting one or more candidate descriptive terms having at least a threshold position in the ranking as the one or more descriptive terms. | 0.584087 |
8,886,587 | 11 | 12 | 11. A system comprising: a user device; and one or more computers operable to interact with the user device, the one or more computers being further operable to perform operations including: providing data that cause presentation of a model development user interface; receiving first model rule data through the user interface, the first model rule data specifying a first model rule that specifies a first characteristic of a violating resource and a threshold score for the first characteristic, wherein the first model rule data specifies a phrase and a threshold number of instances of the phrase that, when included in resource, are indicative of the resource being a violating resource; receiving additional model rule data through the user interface, the additional model rule data specifying one or more additional model rules, each of the additional model rules specifying an additional characteristic of the violating resource and an additional threshold for the additional characteristic; receiving, for each of the additional model rules, relationship data through the user interface, the relationship data specifying sets of the additional model rules that violating resources satisfy; and providing data that cause a hierarchical presentation of the first model rule and the additional model rules, the first model rule being presented at a highest hierarchical position and each of the additional model rules being presented at a descendent hierarchical position based on the relationship data, the data further causing presentation of a relationship indicator for each of the additional model rules, the relationship indicator specifying the sets of additional model rules that must be satisfied to classify a resource as a violating resource. | 11. A system comprising: a user device; and one or more computers operable to interact with the user device, the one or more computers being further operable to perform operations including: providing data that cause presentation of a model development user interface; receiving first model rule data through the user interface, the first model rule data specifying a first model rule that specifies a first characteristic of a violating resource and a threshold score for the first characteristic, wherein the first model rule data specifies a phrase and a threshold number of instances of the phrase that, when included in resource, are indicative of the resource being a violating resource; receiving additional model rule data through the user interface, the additional model rule data specifying one or more additional model rules, each of the additional model rules specifying an additional characteristic of the violating resource and an additional threshold for the additional characteristic; receiving, for each of the additional model rules, relationship data through the user interface, the relationship data specifying sets of the additional model rules that violating resources satisfy; and providing data that cause a hierarchical presentation of the first model rule and the additional model rules, the first model rule being presented at a highest hierarchical position and each of the additional model rules being presented at a descendent hierarchical position based on the relationship data, the data further causing presentation of a relationship indicator for each of the additional model rules, the relationship indicator specifying the sets of additional model rules that must be satisfied to classify a resource as a violating resource. 12. The system of claim 11 , wherein the one or more computers are further operable to perform operations including: receiving additional model rule data that specify one or more rule subsets that each include two or more different model rules; receiving, for each rule subset, relationship data specifying a set of the two or more different model rules in the rule subset that are satisfied by the violating resource; and providing data that cause presentation of each rule subset and a relationship indicator for the model rules in the rule subset, the relationship indicator specifying combinations of the model rules in the rule subset that must be satisfied to classify a resource as a violating resource. | 0.536554 |
8,015,204 | 18 | 19 | 18. A method for determining whether a user has access to a requested object, comprising: receiving, at a computing system which includes at least one processor, a request from a user to access a particular file object; accessing an access control metadata element stored on the computing system to determine whether the user is authorized to access the particular file object, comprising: determining that the access control metadata element provides access rights to the particular file object based on a resource scope statement that identifies a plurality of file objects, including the particular file object, for which the access control metadata element provides access rights by defining a portion of a directory hierarchy indicating that the scoped access control metadata element provides access rights for the plurality of file objects, which are located at or below the specified portion of the directory hierarchy, including the particular file object; determining that the access control metadata element provides access rights for the user based on one or more rule statements, the one or more rule statements including: a first rule statement that includes (i) a first statement scope that identifies a first set of one or more users, including the user, to whom the first rule statement applies, the first statement scope including a first rule that defines the first set of one or more users as users that have been authenticated, and (ii) a first grant statement that defines what access rights the first set of one or more users are granted for accessing any one of the plurality of file objects; and a second rule statement that includes (i) a second statement scope that identifies a second set of one or more users to whom the second rule statement applies, and (ii) a second grant statement that defines what different access rights the second set of one or more users are granted for accessing any one of the plurality of file objects; determining that at least the first rule statement grants the user access to the particular file object based on the first statement scope and the first grant statement; and upon determining that the first rule statement grants the user access to the particular file object, and upon determining that the particular file object is within the plurality of file objects identified by the resource scope statement, granting the user access to the particular file object in accordance with the first grant statement defined in the first rule statement of the access control metadata element. | 18. A method for determining whether a user has access to a requested object, comprising: receiving, at a computing system which includes at least one processor, a request from a user to access a particular file object; accessing an access control metadata element stored on the computing system to determine whether the user is authorized to access the particular file object, comprising: determining that the access control metadata element provides access rights to the particular file object based on a resource scope statement that identifies a plurality of file objects, including the particular file object, for which the access control metadata element provides access rights by defining a portion of a directory hierarchy indicating that the scoped access control metadata element provides access rights for the plurality of file objects, which are located at or below the specified portion of the directory hierarchy, including the particular file object; determining that the access control metadata element provides access rights for the user based on one or more rule statements, the one or more rule statements including: a first rule statement that includes (i) a first statement scope that identifies a first set of one or more users, including the user, to whom the first rule statement applies, the first statement scope including a first rule that defines the first set of one or more users as users that have been authenticated, and (ii) a first grant statement that defines what access rights the first set of one or more users are granted for accessing any one of the plurality of file objects; and a second rule statement that includes (i) a second statement scope that identifies a second set of one or more users to whom the second rule statement applies, and (ii) a second grant statement that defines what different access rights the second set of one or more users are granted for accessing any one of the plurality of file objects; determining that at least the first rule statement grants the user access to the particular file object based on the first statement scope and the first grant statement; and upon determining that the first rule statement grants the user access to the particular file object, and upon determining that the particular file object is within the plurality of file objects identified by the resource scope statement, granting the user access to the particular file object in accordance with the first grant statement defined in the first rule statement of the access control metadata element. 19. The method of claim 18 , further comprising: receiving, at a computing system, a request from the user to modify the access control metadata element; and determining whether the user is authenticated to modify the access control metadata element based on one or more security statements that define authentication measures to be applied when a user attempts to modify the access control metadata element. | 0.501222 |
10,133,560 | 1 | 6 | 1. A method for optimizing source code, the method comprising: optimizing, at a compiler, the source code from files of a computer program at link-time; receiving, at a linker, a customized linker script, wherein the customized linker script is provided by an embedded application developer and overrides a default linker script existing within the linker, the customized liker script defining output sections for files of an executable version of the files of the computer program; adding, by the compiler, to intermediate representation files having global or local symbols, metadata comprising default section assignment information for the symbols; recording, by the linker, for symbols in machine code files, an origin path and an output section; sending, from the linker to the compiler, detailed global scope and use information, then; parsing, by the compiler, based on a request and the detailed global scope and use information from the linker, the intermediate representation files; recording, by the compiler, the symbols and related symbol information comprising the default section assignment information and dependency information of the intermediate representation files, then; assigning output sections to the symbols based on both the default section assignment information and instructions from the customized linker script; and linking optimized code of the files of the computer program based on the assigned output sections. | 1. A method for optimizing source code, the method comprising: optimizing, at a compiler, the source code from files of a computer program at link-time; receiving, at a linker, a customized linker script, wherein the customized linker script is provided by an embedded application developer and overrides a default linker script existing within the linker, the customized liker script defining output sections for files of an executable version of the files of the computer program; adding, by the compiler, to intermediate representation files having global or local symbols, metadata comprising default section assignment information for the symbols; recording, by the linker, for symbols in machine code files, an origin path and an output section; sending, from the linker to the compiler, detailed global scope and use information, then; parsing, by the compiler, based on a request and the detailed global scope and use information from the linker, the intermediate representation files; recording, by the compiler, the symbols and related symbol information comprising the default section assignment information and dependency information of the intermediate representation files, then; assigning output sections to the symbols based on both the default section assignment information and instructions from the customized linker script; and linking optimized code of the files of the computer program based on the assigned output sections. 6. The method of claim 1 , wherein the method further comprises: optimizing, at the compiler, each of the intermediate representation files based on the output section information for each symbol associated with the intermediate representation files. | 0.830163 |
9,946,706 | 13 | 15 | 13. An electronic device, comprising: one or more processors; memory; and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, the one or more programs including instructions for: obtaining a document including text; receiving, from an automatic language identifier service, a first language identification for the document; in response to receiving the first language identification, automatically invoking a modifying operation; performing the modifying operation on the document in accordance with the first language identification; determining, based at least in part on results from the modifying operation, whether the first language identification for the document is correct, wherein the results from the modifying operation include at least one of the amount of errors or the nature of the errors associated with the modifying operation; and in accordance with a determination that the first language identification is correct, providing the first language identification to a user application; in accordance with a determination that the first language identification is incorrect, determining a second language identification of the document, and performing a modifying function on the document in accordance with one or more alternate languages different from the first language, wherein the second language identification of the document is determined based at least in part on the results from performing the modifying function on the document in accordance with the one or more alternate languages. | 13. An electronic device, comprising: one or more processors; memory; and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, the one or more programs including instructions for: obtaining a document including text; receiving, from an automatic language identifier service, a first language identification for the document; in response to receiving the first language identification, automatically invoking a modifying operation; performing the modifying operation on the document in accordance with the first language identification; determining, based at least in part on results from the modifying operation, whether the first language identification for the document is correct, wherein the results from the modifying operation include at least one of the amount of errors or the nature of the errors associated with the modifying operation; and in accordance with a determination that the first language identification is correct, providing the first language identification to a user application; in accordance with a determination that the first language identification is incorrect, determining a second language identification of the document, and performing a modifying function on the document in accordance with one or more alternate languages different from the first language, wherein the second language identification of the document is determined based at least in part on the results from performing the modifying function on the document in accordance with the one or more alternate languages. 15. The electronic device as in claim 13 , wherein the one or more programs include instructions for: receiving an accuracy confidence ranking associated with the first language identification; and wherein the determining is based on the results from the modifying operation and the accuracy confidence ranking. | 0.525915 |
8,606,575 | 8 | 11 | 8. An apparatus, comprising: a receiver configured to receive a plurality of spoken utterances and record them in a database memory; and a processor configured to transcribe at least a portion of the plurality of spoken utterances occurring during a call, automatically assign each of the plurality of spoken utterances with a corresponding set of first classifications, determine a confidence rating associated with each of the plurality of spoken utterances and the assigned set of first classifications, and perform at least one of reclassify the plurality of spoken utterances with new classifications based on at least one additional classification operation, and add the assigned first classifications and the corresponding plurality of spoken utterances to a training data set. | 8. An apparatus, comprising: a receiver configured to receive a plurality of spoken utterances and record them in a database memory; and a processor configured to transcribe at least a portion of the plurality of spoken utterances occurring during a call, automatically assign each of the plurality of spoken utterances with a corresponding set of first classifications, determine a confidence rating associated with each of the plurality of spoken utterances and the assigned set of first classifications, and perform at least one of reclassify the plurality of spoken utterances with new classifications based on at least one additional classification operation, and add the assigned first classifications and the corresponding plurality of spoken utterances to a training data set. 11. The apparatus of claim 8 , wherein if the determined confidence ratings associated with each of the plurality of spoken utterances produces confidence ratings that are above a predefined threshold then the processor is configured to add the labeled plurality of spoken utterances to the training data set. | 0.847933 |
8,612,223 | 3 | 4 | 3. The voice processing device according to claim 1 , wherein the pre-score calculation means adjusts the pre-score for each of the plural pieces of intention information in response to a context at the time when the voice signal is input. | 3. The voice processing device according to claim 1 , wherein the pre-score calculation means adjusts the pre-score for each of the plural pieces of intention information in response to a context at the time when the voice signal is input. 4. The voice processing device according to claim 3 , wherein the score calculation means calculates the score of a voice zone in the voice signal. | 0.954234 |
8,185,397 | 12 | 13 | 12. The method of claim 9 , further comprising comparing a degree of relation among the mapped lower domain entities with a preset reference level, wherein, in the recognizing of the extracted input speech entity information, the input speech is recognized if the degree of relation is greater than the reference level. | 12. The method of claim 9 , further comprising comparing a degree of relation among the mapped lower domain entities with a preset reference level, wherein, in the recognizing of the extracted input speech entity information, the input speech is recognized if the degree of relation is greater than the reference level. 13. The method of claim 12 , wherein the comparing of the degree of relation further comprises determining whether a combination of selected plural lower domain entities form one of a plurality of preset combinations, and in the recognizing of the extracted entity information, the input speech is recognized if the combination of the selected plurality of lower domain entities, of the lower domain entities, form one of the plurality of preset combinations. | 0.864921 |
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