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7,752,193 | 2 | 4 | 2. The method of claim 1 , wherein the input query word includes the diacritic symbol, and the query engine is further configured to: strip the input query word of the diacritic symbol; and search the second data structure for the stripped input query word. | 2. The method of claim 1 , wherein the input query word includes the diacritic symbol, and the query engine is further configured to: strip the input query word of the diacritic symbol; and search the second data structure for the stripped input query word. 4. The method of claim 2 , wherein the query engine is configured to receive a command to consider diacritics in the input query word, the method further comprising: storing second information on the diacritic symbol stripped from the input query word, wherein the second information includes a second numeric value indicative of a position of the diacritic symbol in the input query word, and a representation of the diacritic symbol, wherein, in response to the command, the query engine is configured to search the first data structure for information on the diacritic symbol for an indexed word corresponding to the stripped input query word, compare the information on the diacritic symbol with the second information on the diacritic symbol stripped from the input query word, and return a no match in response to a no match of the compared information. | 0.5 |
9,384,423 | 1 | 12 | 1. A method for computing confidence comprising: with a text recognition system, performing character recognition on an input text image to generate a candidate string of characters; generating a first representation based on the candidate string of characters, the generating of the first representation comprising partitioning the candidate character string into a plurality of regions and extracting a representation of each of the regions, the character string representation being derived by aggregating the region representations; generating a second representation based on the input text image; computing a confidence in the candidate string of characters based on a computed similarity between the first and second representations in a common embedding space, at least one of the first and second representations being projected into the common embedding space; and wherein at least one of the performing character recognition, generating the first representation, generating the second representation, and computing the confidence is performed with a computer processor. | 1. A method for computing confidence comprising: with a text recognition system, performing character recognition on an input text image to generate a candidate string of characters; generating a first representation based on the candidate string of characters, the generating of the first representation comprising partitioning the candidate character string into a plurality of regions and extracting a representation of each of the regions, the character string representation being derived by aggregating the region representations; generating a second representation based on the input text image; computing a confidence in the candidate string of characters based on a computed similarity between the first and second representations in a common embedding space, at least one of the first and second representations being projected into the common embedding space; and wherein at least one of the performing character recognition, generating the first representation, generating the second representation, and computing the confidence is performed with a computer processor. 12. The method of claim 1 , wherein the performing character recognition on the input image comprises, with the text recognition system, generating a plurality of candidate strings of characters for the same input text image, the method further comprising ranking the plurality of candidate strings based on the respective computed confidences. | 0.626087 |
9,911,043 | 1 | 4 | 1. A computer-implemented method for analyzing a scene depicted in an input stream of video frames captured by a video camera, the method comprising: receiving at least two sequences, wherein each sequence of the at least two sequences corresponds to a segment of a trajectory taken by a respective object through the scene; determining, via one or more processors, whether the objects interact based on a spatio-temporal proximity of the objects; and if the objects interact: mapping each sequence of the at least two sequences to a respective sequence cluster, retrieving, from an ngram trie, a learned joint probability indicating a likelihood of a given sequence cluster pair of a plurality of sequence cluster pairs occurring in the scene, the ngram trie including a plurality of nodes, the given sequence cluster pair being represented jointly by a first node in a first layer of the ngram trie and a second node in a second layer of the ngram trie, the first node and the second node representing sequence clusters in the given sequence cluster pair, and determining a rareness value for each sequence cluster pair based on the learned joint probability and a frequency of a most frequently observed sequence cluster pair from the scene, the rareness value given by R ij = 1 - f ij f max , where f ij is a frequency with which sequence cluster pair {C i , C j } has been observed and f max is the frequency of the most frequently observed sequence cluster pair; determining, using a statistical anomaly model, an anomaly temperature for the rareness value, wherein the anomaly temperature indicates a frequency of occurrence of the rareness value; and upon determining one or more reporting criteria are met based at least on the anomaly temperature, reporting the interaction of the objects. | 1. A computer-implemented method for analyzing a scene depicted in an input stream of video frames captured by a video camera, the method comprising: receiving at least two sequences, wherein each sequence of the at least two sequences corresponds to a segment of a trajectory taken by a respective object through the scene; determining, via one or more processors, whether the objects interact based on a spatio-temporal proximity of the objects; and if the objects interact: mapping each sequence of the at least two sequences to a respective sequence cluster, retrieving, from an ngram trie, a learned joint probability indicating a likelihood of a given sequence cluster pair of a plurality of sequence cluster pairs occurring in the scene, the ngram trie including a plurality of nodes, the given sequence cluster pair being represented jointly by a first node in a first layer of the ngram trie and a second node in a second layer of the ngram trie, the first node and the second node representing sequence clusters in the given sequence cluster pair, and determining a rareness value for each sequence cluster pair based on the learned joint probability and a frequency of a most frequently observed sequence cluster pair from the scene, the rareness value given by R ij = 1 - f ij f max , where f ij is a frequency with which sequence cluster pair {C i , C j } has been observed and f max is the frequency of the most frequently observed sequence cluster pair; determining, using a statistical anomaly model, an anomaly temperature for the rareness value, wherein the anomaly temperature indicates a frequency of occurrence of the rareness value; and upon determining one or more reporting criteria are met based at least on the anomaly temperature, reporting the interaction of the objects. 4. The method of claim 1 , wherein the ngram trie is updated based on observed sequence cluster pairs. | 0.906934 |
7,761,843 | 22 | 23 | 22. The tangible computer-readable medium having computer-executable instructions of claim 1 wherein defining the programming command further comprises defining each word within the programming command. | 22. The tangible computer-readable medium having computer-executable instructions of claim 1 wherein defining the programming command further comprises defining each word within the programming command. 23. The tangible computer-readable medium having computer-executable instructions of claim 22 wherein defining a word comprises: selecting a word type; and defining the word as the selected word type. | 0.5 |
9,766,879 | 13 | 17 | 13. A system for providing supplemental functionalities for an executable program via an ontology instance, the system comprising: a computer system comprising one or more processors programmed with computer program instructions which, when executed, cause the computer system to: cause an executable program to be run; obtain a general ontology and a domain-specific ontology, wherein the domain-specific ontology is associated with a domain of interest, and the executable program is configured to use at least a portion of the general ontology to interpret the domain-specific ontology; validate the general ontology; obtain an instance of the general ontology, wherein the general ontology instance is based on the domain-specific ontology and corresponds to an application associated with the domain of interest; generate, based on the general ontology instance, supplemental information for the executable program, wherein the supplemental information is related to one or more functionalities of the application to be added to the executable program; and provide the supplemental information as input to the executable program, wherein the supplemental information, at least in part, causes the one or more functionalities of the application be made available via the executable program. | 13. A system for providing supplemental functionalities for an executable program via an ontology instance, the system comprising: a computer system comprising one or more processors programmed with computer program instructions which, when executed, cause the computer system to: cause an executable program to be run; obtain a general ontology and a domain-specific ontology, wherein the domain-specific ontology is associated with a domain of interest, and the executable program is configured to use at least a portion of the general ontology to interpret the domain-specific ontology; validate the general ontology; obtain an instance of the general ontology, wherein the general ontology instance is based on the domain-specific ontology and corresponds to an application associated with the domain of interest; generate, based on the general ontology instance, supplemental information for the executable program, wherein the supplemental information is related to one or more functionalities of the application to be added to the executable program; and provide the supplemental information as input to the executable program, wherein the supplemental information, at least in part, causes the one or more functionalities of the application be made available via the executable program. 17. The system of claim 13 , wherein the computer system is further caused to assign a freeze to the general ontology and the domain-specific ontology that disables further modification to the general ontology and the domain-specific ontology. | 0.887812 |
10,162,885 | 1 | 11 | 1. A method for providing, by a self-service user support software application for assisting customers having a product or service problem, information, received via a search conducted over an Internet computer network using a refined user query, to a user in response to a received input user query, said method comprising: receiving, by a processor of a computer system, an input user query from a user interface component in a screen, said received input user query expressed in a free-form text format, said computer system comprising the screen, said input user query pertaining to a problem of the user which is a problem that the user experiences with a product or service; said processor performing a natural language analysis to generate substrings relevant to the received input user query, wherein said performing the natural language analysis comprises extracting details from the user query, and wherein said performing the natural language analysis comprises identifying a language of text in the input user query, recognizing a misspelling of one word in the input user query, determining a canonical form of another word in the input user query, recognizing a term in the input user query pertaining to a technical support domain, and semantically recognizing an incident expressed in the input user query; after said performing the natural language analysis, said processor performing an ontology analysis to output terms of an ontology of domain-specific information specific to a domain pertaining to products and to further output relationships between pairs of said terms, said outputted terms constrained to match the relevant substrings generated by said performing the natural language analysis; said processor capturing, via an ontology model included in the ontology, elements of a perfect or complete query, wherein the elements of the perfect or complete query include information pertaining to the problem of the user; during said performing the ontology analysis, said processor identifying multiple outputted terms that match one of the relevant substrings, requesting from the user a selection of one outputted term of the multiple outputted terms, and receiving from the user the selection of the one outputted term of the multiple outputted terms; after said performing the ontology analysis, said processor performing a query analysis to analyze the input user query with respect to the outputted terms and relationships between the terms; said processor refining the input user query based on the outputted terms and relationships between the terms; said processor generating a search query based on the refined user query; said processor initiating a search by sending the search query across the Internet computer network to a search engine configured to perform the search, based on the search query, via one or more databases; said processor receiving from the search engine results of the search via the user interface component in the screen; and after said performing the ontology analysis, said processor performing a query analysis to analyze the input user query with respect to the outputted terms and relationships between the terms. | 1. A method for providing, by a self-service user support software application for assisting customers having a product or service problem, information, received via a search conducted over an Internet computer network using a refined user query, to a user in response to a received input user query, said method comprising: receiving, by a processor of a computer system, an input user query from a user interface component in a screen, said received input user query expressed in a free-form text format, said computer system comprising the screen, said input user query pertaining to a problem of the user which is a problem that the user experiences with a product or service; said processor performing a natural language analysis to generate substrings relevant to the received input user query, wherein said performing the natural language analysis comprises extracting details from the user query, and wherein said performing the natural language analysis comprises identifying a language of text in the input user query, recognizing a misspelling of one word in the input user query, determining a canonical form of another word in the input user query, recognizing a term in the input user query pertaining to a technical support domain, and semantically recognizing an incident expressed in the input user query; after said performing the natural language analysis, said processor performing an ontology analysis to output terms of an ontology of domain-specific information specific to a domain pertaining to products and to further output relationships between pairs of said terms, said outputted terms constrained to match the relevant substrings generated by said performing the natural language analysis; said processor capturing, via an ontology model included in the ontology, elements of a perfect or complete query, wherein the elements of the perfect or complete query include information pertaining to the problem of the user; during said performing the ontology analysis, said processor identifying multiple outputted terms that match one of the relevant substrings, requesting from the user a selection of one outputted term of the multiple outputted terms, and receiving from the user the selection of the one outputted term of the multiple outputted terms; after said performing the ontology analysis, said processor performing a query analysis to analyze the input user query with respect to the outputted terms and relationships between the terms; said processor refining the input user query based on the outputted terms and relationships between the terms; said processor generating a search query based on the refined user query; said processor initiating a search by sending the search query across the Internet computer network to a search engine configured to perform the search, based on the search query, via one or more databases; said processor receiving from the search engine results of the search via the user interface component in the screen; and after said performing the ontology analysis, said processor performing a query analysis to analyze the input user query with respect to the outputted terms and relationships between the terms. 11. The method of claim 1 , wherein said performing the natural language analysis comprises assigning a linguistic category to different words of the input user query, wherein each linguistic category is specific to the word to which each linguistic category is assigned, and wherein generation of the substrings by performing the natural language analysis comprises utilizing the linguistic category assigned to the different words of the input user query. | 0.760983 |
10,097,490 | 18 | 19 | 18. The non-transitory computer-readable medium of claim 16 , wherein the another registered user is the service provider providing a service associated with content in the posted communication. | 18. The non-transitory computer-readable medium of claim 16 , wherein the another registered user is the service provider providing a service associated with content in the posted communication. 19. The non-transitory computer-readable medium of claim 18 , the operations further comprising: prior to posting the communication in the sub-forum, performing the text-based analysis of the communication, wherein the text-based analysis includes determining whether the communication complies with a posting rule associated with the sub-forum and the controlled environment. | 0.5 |
9,794,638 | 9 | 12 | 9. A caption replacement service system configured in a computer, the caption replacement service system comprising: at least one storage unit configured to store at least one program; at least one processor configured to process execution of a video loader, a virtual object area adder, an interactive advertisement adder, and an information storage according to a control of the at least one program; the video loader configured to load a video to be augmented, wherein the video comprises a series of frames, each frame being a visual image, and the video is not annotated; the virtual object area adder configured to: automatically identify, in at least one visual image frame of the video, a location in the visual image containing an image of text that comprises textual information and that is original to the video; evaluate the image of text with image text cognition to determine a content of the textual information; determine whether the content of the textual information contains non-current information based on a current context making a meaning of the content outdated, the non-current information being selected from the group consisting of: a news issue, a broadcast schedule, weather information, market information, trademark information, a displayed caption in a human language, and displayed time information; and automatically add, in response to a determination that the content of the textual information contains non-current information, an augmented virtual object area at the location on the video frame of the textual information, the augmented virtual object area comprising an augmentation overlay that hides the non-current information of the content of the textual information; the interactive advertisement adder configured to: dynamically select an interactive advertisement based on a profile of a user; and dynamically overlay the interactive advertisement at the location of the non-current information on top of the augmented virtual object area of the loaded video; and the information storage configured to store information on the added augmented virtual object area, the stored information being used to identify the augmented virtual object area when playing the video. | 9. A caption replacement service system configured in a computer, the caption replacement service system comprising: at least one storage unit configured to store at least one program; at least one processor configured to process execution of a video loader, a virtual object area adder, an interactive advertisement adder, and an information storage according to a control of the at least one program; the video loader configured to load a video to be augmented, wherein the video comprises a series of frames, each frame being a visual image, and the video is not annotated; the virtual object area adder configured to: automatically identify, in at least one visual image frame of the video, a location in the visual image containing an image of text that comprises textual information and that is original to the video; evaluate the image of text with image text cognition to determine a content of the textual information; determine whether the content of the textual information contains non-current information based on a current context making a meaning of the content outdated, the non-current information being selected from the group consisting of: a news issue, a broadcast schedule, weather information, market information, trademark information, a displayed caption in a human language, and displayed time information; and automatically add, in response to a determination that the content of the textual information contains non-current information, an augmented virtual object area at the location on the video frame of the textual information, the augmented virtual object area comprising an augmentation overlay that hides the non-current information of the content of the textual information; the interactive advertisement adder configured to: dynamically select an interactive advertisement based on a profile of a user; and dynamically overlay the interactive advertisement at the location of the non-current information on top of the augmented virtual object area of the loaded video; and the information storage configured to store information on the added augmented virtual object area, the stored information being used to identify the augmented virtual object area when playing the video. 12. The caption replacement service system of claim 9 , wherein information on the virtual object area comprises information on at least one of a start time and an end time for displaying the virtual object area, a size of the virtual object area, a display location of the virtual object area, content of the interactive advertisement to be added to the virtual object area, a URL address of the interactive advertisement, and an event address generated in response to a click on the virtual object area. | 0.5 |
8,180,787 | 1 | 2 | 1. A computer-implemented method of providing access to data having a particular schema, comprising: providing a data abstraction model which models the data having the particular schema and exposes the data to users in a manner that allows the users to compose abstract queries on the basis of the data abstraction model without knowledge of the particular schema; wherein the data abstraction model comprises a plurality of logical field definitions, the plurality of logical field definitions being maintained separately from physical queries, each of the logical field definitions comprising: (i) a logical field name; (ii) at least one location attribute identifying a location of physical data corresponding to the logical field name; and (iii) a reference to an access method for accessing the physical data in response to receiving the abstract query containing the logical field name, wherein at least one of the logical field names is different from a physical field name of the corresponding physical data as defined by the schema; and configuring one or more computer processors to perform an operation comprising: receiving an abstract query that is expressed according to a syntax of a predefined query language, comprising: (i) a user-specified result specification specifying one or more logical field definitions for which results are to be returned; and (ii) at least one user-specified selection criterion specifying conditions to filter the physical data corresponding to the one or more logical field definitions specified by the result specification; and accessing the data abstraction model in response to receiving the abstract query, wherein accessing comprises: invoking an access method of one of the one or more logical field definitions to access the physical data. | 1. A computer-implemented method of providing access to data having a particular schema, comprising: providing a data abstraction model which models the data having the particular schema and exposes the data to users in a manner that allows the users to compose abstract queries on the basis of the data abstraction model without knowledge of the particular schema; wherein the data abstraction model comprises a plurality of logical field definitions, the plurality of logical field definitions being maintained separately from physical queries, each of the logical field definitions comprising: (i) a logical field name; (ii) at least one location attribute identifying a location of physical data corresponding to the logical field name; and (iii) a reference to an access method for accessing the physical data in response to receiving the abstract query containing the logical field name, wherein at least one of the logical field names is different from a physical field name of the corresponding physical data as defined by the schema; and configuring one or more computer processors to perform an operation comprising: receiving an abstract query that is expressed according to a syntax of a predefined query language, comprising: (i) a user-specified result specification specifying one or more logical field definitions for which results are to be returned; and (ii) at least one user-specified selection criterion specifying conditions to filter the physical data corresponding to the one or more logical field definitions specified by the result specification; and accessing the data abstraction model in response to receiving the abstract query, wherein accessing comprises: invoking an access method of one of the one or more logical field definitions to access the physical data. 2. The method of claim 1 , further comprising: receiving logical field selection input to a query composition application that defines an interface to the plurality of logical field definitions of the abstraction model, thereby allowing abstract queries to be composed on the basis of the plurality of logical field definitions. | 0.5 |
9,959,886 | 9 | 10 | 9. The method of claim 1 , wherein generating the first voice activity indicator value includes normalizing a function of the difference between the first value and the second value. | 9. The method of claim 1 , wherein generating the first voice activity indicator value includes normalizing a function of the difference between the first value and the second value. 10. The method of claim 9 , wherein normalizing the difference between the first value and the second value comprises one of: dividing the difference by a function of the sum of the first value and the second value; dividing the difference by a function of an integral value of the spectrum amplitude of the audible signal over a first frequency range that includes the candidate pitch. | 0.5 |
8,374,913 | 11 | 18 | 11. A system, comprising at least one processor and memory, for determining an effect of an audio-visual advertisement, the system comprising: a module to deliver, over a network, the audio-visual advertisement to a user computer; a module to receive a search query comprising one or more keywords submitted over the network by the user; a module to extract advertisement keywords from digitized text corresponding to audio and video from the audio-visual advertisement; and a module to compare, by the processor, the advertisement keywords to the one or more keywords from the search query by determining an advertisement effectiveness rank of the audio-visual advertisement, the advertisement effectiveness rank is based on common keywords between the advertisement keywords and the one or more keywords of the search query and a time difference between the delivering of the audio-visual advertisement to the user and the receiving of the search query from the user. | 11. A system, comprising at least one processor and memory, for determining an effect of an audio-visual advertisement, the system comprising: a module to deliver, over a network, the audio-visual advertisement to a user computer; a module to receive a search query comprising one or more keywords submitted over the network by the user; a module to extract advertisement keywords from digitized text corresponding to audio and video from the audio-visual advertisement; and a module to compare, by the processor, the advertisement keywords to the one or more keywords from the search query by determining an advertisement effectiveness rank of the audio-visual advertisement, the advertisement effectiveness rank is based on common keywords between the advertisement keywords and the one or more keywords of the search query and a time difference between the delivering of the audio-visual advertisement to the user and the receiving of the search query from the user. 18. The system of claim 11 , wherein the comparing is further to determine trigger keywords. | 0.907445 |
8,615,419 | 1 | 9 | 1. A method for calculating an interaction churn score in an organization with which the customer has an interaction, the method comprising: receiving a plurality of categories, each category characterized by an at least one parameter of a voiced expression; capturing or logging the interaction using a capturing or logging component; based on a determined relation of data of the interaction to churning, categorizing the interaction into at least one churning category out of a total number of categories according to an extent to which the data of the interaction belongs to the least one churning category, and determining a number of churning categories into which the interaction is categorized; and determining an interaction churn score for the interaction, wherein the interaction churn score comprises a term directly related to the number of churning categories the interaction is categorized into and inversely related to the total number of churning categories based on a formula as:
A *(maximal score for a churning category)+ B *((the number of churning categories into which the interaction is categorized)/(the number of churning categories)*100), wherein A and B are coefficients that satisfy a condition of A+B=1; and wherein capturing or logging the interaction and determining an interaction churn score for the interaction are carried out using a computing platform provisioned with a memory device. | 1. A method for calculating an interaction churn score in an organization with which the customer has an interaction, the method comprising: receiving a plurality of categories, each category characterized by an at least one parameter of a voiced expression; capturing or logging the interaction using a capturing or logging component; based on a determined relation of data of the interaction to churning, categorizing the interaction into at least one churning category out of a total number of categories according to an extent to which the data of the interaction belongs to the least one churning category, and determining a number of churning categories into which the interaction is categorized; and determining an interaction churn score for the interaction, wherein the interaction churn score comprises a term directly related to the number of churning categories the interaction is categorized into and inversely related to the total number of churning categories based on a formula as:
A *(maximal score for a churning category)+ B *((the number of churning categories into which the interaction is categorized)/(the number of churning categories)*100), wherein A and B are coefficients that satisfy a condition of A+B=1; and wherein capturing or logging the interaction and determining an interaction churn score for the interaction are carried out using a computing platform provisioned with a memory device. 9. The method of claim 1 further comprising a step of performing quality monitoring for an agent associated with the interaction. | 0.825676 |
9,286,386 | 1 | 5 | 1. A method comprising: receiving, from a first user device, a first search query associated with videos available via mobile video-on-demand; receiving, from a second user device, a second search query associated with the videos; retrieving search results according to a combination search query, the combination search query being a combination of the first search query and the second search query; transmitting the search results to the first user device and the second user device; and iteratively: updating a finite state edit machine according to multimodal input, wherein the multimodal input is iteratively received from the first user device to modify the combination search query, to yield a modified combination search query; and transmitting updated search results to the first user device and the second user device, wherein the updated search results are according to the modified combination search query. | 1. A method comprising: receiving, from a first user device, a first search query associated with videos available via mobile video-on-demand; receiving, from a second user device, a second search query associated with the videos; retrieving search results according to a combination search query, the combination search query being a combination of the first search query and the second search query; transmitting the search results to the first user device and the second user device; and iteratively: updating a finite state edit machine according to multimodal input, wherein the multimodal input is iteratively received from the first user device to modify the combination search query, to yield a modified combination search query; and transmitting updated search results to the first user device and the second user device, wherein the updated search results are according to the modified combination search query. 5. The method of claim 1 , wherein the search results comprise a link to additional information related to the search results. | 0.655738 |
8,909,624 | 7 | 9 | 7. One or more non-transitory computer-readable storage media storing instructions that when executed perform a method, the method comprising: receiving results for a search query initiated by a user; evaluating the received results in relation to a personal profile of the user, wherein the personal profile includes a plurality of characteristics associated with the user and wherein the evaluating comprises comparing the plurality of characteristics to the results; evaluating the results based on attributes of the user, wherein the attributes include at least one of the user's gender, the user's place of employment, and the user's position at the user's place of employment; ranking the results to generate a resultant that reflects a ranking of the results in order of likely meaningfulness to the user based on the evaluation; and communicating the resultant to the user; wherein the plurality of characteristics comprise at least one characteristic derived from observing the user's behavioral patterns over a period of time and at least one characteristic declared by the user, and wherein the plurality of characteristics include at least one of a media type preferred by the user, a tag cloud associated with the user, an information flow characteristic associated with the user, past queries associated with the user, previous searches conducted by the user, a topic of interest to the user, a personal vocabulary of the user, and a rating of similar searches. | 7. One or more non-transitory computer-readable storage media storing instructions that when executed perform a method, the method comprising: receiving results for a search query initiated by a user; evaluating the received results in relation to a personal profile of the user, wherein the personal profile includes a plurality of characteristics associated with the user and wherein the evaluating comprises comparing the plurality of characteristics to the results; evaluating the results based on attributes of the user, wherein the attributes include at least one of the user's gender, the user's place of employment, and the user's position at the user's place of employment; ranking the results to generate a resultant that reflects a ranking of the results in order of likely meaningfulness to the user based on the evaluation; and communicating the resultant to the user; wherein the plurality of characteristics comprise at least one characteristic derived from observing the user's behavioral patterns over a period of time and at least one characteristic declared by the user, and wherein the plurality of characteristics include at least one of a media type preferred by the user, a tag cloud associated with the user, an information flow characteristic associated with the user, past queries associated with the user, previous searches conducted by the user, a topic of interest to the user, a personal vocabulary of the user, and a rating of similar searches. 9. The one or more non-transitory computer-readable storage media of claim 7 , further comprising: evaluating the results based on a social network of the user; and evaluating the results based on preferences declared by the user. | 0.5 |
8,261,094 | 43 | 46 | 43. The apparatus of claim 42 wherein the means for encrypting encrypts using a session key. | 43. The apparatus of claim 42 wherein the means for encrypting encrypts using a session key. 46. The apparatus of claim 43 wherein the session key includes scanner identification information. | 0.5 |
7,739,221 | 9 | 14 | 9. A computer-implemented method of performing a multi-dimensional search, comprising: employing a processor to execute computer executable instructions stored on a computer readable storage medium to perform the following acts: receiving an input, the input comprises visual data and at least one of text or audio data, wherein the visual data is from an image file; extracting a plurality of features from the input comprising: utilizing a pattern recognition component to extract a plurality of features from the image file, wherein the features comprise physical attributes that are visually identifiable in the image file; establishing a plurality of search terms based at least in part upon a subset of the extracted features; retrieving a plurality of results based at least in part upon a subset of the search terms; collecting and indexing search-related information across a plurality of dimensions, and building an index based upon features associated with the input; automatically and dynamically extracting features from searchable items and making the features available for search based upon a particular query or set of queries; learning, based on context information, historical data, or feedback, what results are desired in view of a determined and inferred query, as well as how the results should be rendered, and generating a statistical model with the results; and filtering a subset of the plurality of results in accordance with at least one of a user context, a user preference, a relevancy factor with respect to the input, or a device context. | 9. A computer-implemented method of performing a multi-dimensional search, comprising: employing a processor to execute computer executable instructions stored on a computer readable storage medium to perform the following acts: receiving an input, the input comprises visual data and at least one of text or audio data, wherein the visual data is from an image file; extracting a plurality of features from the input comprising: utilizing a pattern recognition component to extract a plurality of features from the image file, wherein the features comprise physical attributes that are visually identifiable in the image file; establishing a plurality of search terms based at least in part upon a subset of the extracted features; retrieving a plurality of results based at least in part upon a subset of the search terms; collecting and indexing search-related information across a plurality of dimensions, and building an index based upon features associated with the input; automatically and dynamically extracting features from searchable items and making the features available for search based upon a particular query or set of queries; learning, based on context information, historical data, or feedback, what results are desired in view of a determined and inferred query, as well as how the results should be rendered, and generating a statistical model with the results; and filtering a subset of the plurality of results in accordance with at least one of a user context, a user preference, a relevancy factor with respect to the input, or a device context. 14. The method of claim 9 , further comprising ranking the subset of the plurality of results based at least in part upon one of a user preference or a relevancy factor. | 0.714527 |
9,189,476 | 1 | 9 | 1. A translation apparatus, comprising: a speech input unit that receives a speech of a first language from a user; a control unit that generates sentences of the first language from the speech of the first language input from the speech input unit; a communication unit that transmits the sentences of the first language to a translation server and receives sentences of a second language from the translation server; a display unit that displays the sentences of the second language along with previously translated sentences; a memory that stores a translation history including the sentences of the first language and the sentences of the second language; and a user input unit that receives an operation input of the previously translated sentences from a user, wherein the sentences of the second language are translated sentences corresponding to the sentences of the first language, wherein the control unit is configured to confirm whether the same words as words included in the sentences of the first language are present within the translation history according to an input of the user and if determined that the same words are present, perform a controls to display the same words. | 1. A translation apparatus, comprising: a speech input unit that receives a speech of a first language from a user; a control unit that generates sentences of the first language from the speech of the first language input from the speech input unit; a communication unit that transmits the sentences of the first language to a translation server and receives sentences of a second language from the translation server; a display unit that displays the sentences of the second language along with previously translated sentences; a memory that stores a translation history including the sentences of the first language and the sentences of the second language; and a user input unit that receives an operation input of the previously translated sentences from a user, wherein the sentences of the second language are translated sentences corresponding to the sentences of the first language, wherein the control unit is configured to confirm whether the same words as words included in the sentences of the first language are present within the translation history according to an input of the user and if determined that the same words are present, perform a controls to display the same words. 9. The translation apparatus of claim 1 , wherein when the first language is translated into the second language according to a request of a first speaker, the sentences of the first language and the sentences of the second language are displayed on one side of a screen, and when the second language is translated into the first language according to a request of a second speaker, the sentences of the second language and sentences translated into the first language are displayed on another side of the screen. | 0.5 |
8,550,299 | 1 | 7 | 1. A toothpaste dispenser having an appearance of a character, the toothpaste dispenser comprising: a base; a support extending from a first end essentially vertically from the base; and a toothpaste tube holder located at a second end of the support opposite the first end, the toothpaste tube holder capable of being removably coupled to a toothpaste tube, wherein the base comprises a plurality of indentations therein each to receive a first end of a toothbrush and the toothpaste holder comprises a plurality of hooks each correspondingly located thereon to receive a second end of the toothbrush, the toothpaste tube comprises at least one of facial and body features, the dispenser comprising a plurality of toothbrushes, each having a shape of the character's leg, the indentations and hooks located on the dispenser for the toothbrushes to appear as legs extending from the toothpaste tube. | 1. A toothpaste dispenser having an appearance of a character, the toothpaste dispenser comprising: a base; a support extending from a first end essentially vertically from the base; and a toothpaste tube holder located at a second end of the support opposite the first end, the toothpaste tube holder capable of being removably coupled to a toothpaste tube, wherein the base comprises a plurality of indentations therein each to receive a first end of a toothbrush and the toothpaste holder comprises a plurality of hooks each correspondingly located thereon to receive a second end of the toothbrush, the toothpaste tube comprises at least one of facial and body features, the dispenser comprising a plurality of toothbrushes, each having a shape of the character's leg, the indentations and hooks located on the dispenser for the toothbrushes to appear as legs extending from the toothpaste tube. 7. The toothpaste dispenser of claim 1 , wherein the toothpaste tube comprises a dispenser having a conduit there through to dispense toothpaste from the toothpaste tube. | 0.67803 |
8,224,836 | 14 | 16 | 14. A computerized method for performing a search in multiple languages comprising: requesting a webpage over a network; providing the webpage for display by an electronic display; receiving, from a user interface, a search query in a default language comprising a first search term and a second search term; receiving, from the user interface, a language selection for transliteration of the first search term; wherein the first search term, the second search term, and the language selection are manually entered via a single text input field, and wherein the language selection comprises a prefix or a suffix for the first search term, the prefix or suffix comprising text adjacent to the first search term within the single text input field; providing a transliteration request over the network to a transliteration database, wherein the transliteration request comprises the first search term and a selected language for the first search term; receiving, from the transliteration database, a transliterated search term in the selected language for the first search term, in response to providing the transliteration request, wherein the transliterated term is a spelling of the first search term in the selected language using one or more corresponding characters from an alphabet of the selected language; and providing search result data for display by the electronic display, the search result data representing the webpage having the transliterated search term in the selected language and the second search term in the default language, wherein the selected language differs from the default language. | 14. A computerized method for performing a search in multiple languages comprising: requesting a webpage over a network; providing the webpage for display by an electronic display; receiving, from a user interface, a search query in a default language comprising a first search term and a second search term; receiving, from the user interface, a language selection for transliteration of the first search term; wherein the first search term, the second search term, and the language selection are manually entered via a single text input field, and wherein the language selection comprises a prefix or a suffix for the first search term, the prefix or suffix comprising text adjacent to the first search term within the single text input field; providing a transliteration request over the network to a transliteration database, wherein the transliteration request comprises the first search term and a selected language for the first search term; receiving, from the transliteration database, a transliterated search term in the selected language for the first search term, in response to providing the transliteration request, wherein the transliterated term is a spelling of the first search term in the selected language using one or more corresponding characters from an alphabet of the selected language; and providing search result data for display by the electronic display, the search result data representing the webpage having the transliterated search term in the selected language and the second search term in the default language, wherein the selected language differs from the default language. 16. The method of claim 14 , wherein search query further comprises a third search term in the default language, the method further comprising: receiving, from the interface, a language selection for the third search term that differs from the language selection for the first search term; providing a second transliteration request over the network to the transliteration database, wherein the second transliteration request comprises the third search term and a selected language for the third search term; receiving, from the transliteration database, a second transliterated search term in the selected language for the third search term, in response to providing the transliteration request; and wherein the search result data is further configured to cause the electronic display to display indicia based in part on whether the webpage contains the second transliterated term, wherein the selected language for the second search term differs than the selected language for the third search term. | 0.5 |
7,913,238 | 2 | 8 | 2. An integrated development environment code completion compiler error recovery system, comprising: a processor; a language module, implemented on the processor, including a parser operable to parse the syntactic structure of a first program in a first programming language, wherein the first program can be represented by a first set of tokens; a client interface through which the language module can communicate with an extensible compiler framework, implemented on the processor; the extensible compiler framework including a namespace component wherein the namespace component is operable to store name and/or type information for one or more language modules; and wherein the parser can correct a syntax error by adding at least one token to the first set of tokens according to one of: 1) a prefix, wherein a prefix is the combination of an opening delimiter with a newly created closing delimiter; and 2) an idiom, wherein an idiom is a specific insertion sequence that can be used to overcome common errors in a given programming language; and wherein an extensible compiler framework detects the syntax error. | 2. An integrated development environment code completion compiler error recovery system, comprising: a processor; a language module, implemented on the processor, including a parser operable to parse the syntactic structure of a first program in a first programming language, wherein the first program can be represented by a first set of tokens; a client interface through which the language module can communicate with an extensible compiler framework, implemented on the processor; the extensible compiler framework including a namespace component wherein the namespace component is operable to store name and/or type information for one or more language modules; and wherein the parser can correct a syntax error by adding at least one token to the first set of tokens according to one of: 1) a prefix, wherein a prefix is the combination of an opening delimiter with a newly created closing delimiter; and 2) an idiom, wherein an idiom is a specific insertion sequence that can be used to overcome common errors in a given programming language; and wherein an extensible compiler framework detects the syntax error. 8. The system of claim 2 wherein: the idiom associates a syntax error with the at least one token. | 0.8 |
8,775,160 | 7 | 9 | 7. The system of claim 1 , wherein calculating the set of part of speech scores for the input string comprises, for each word group from the set of word groups from the dictionary list, calculating a cosine similarity measure between: (a) a first word group corresponding to the input word group corresponding to the invented part of speech; and (b) a second word group corresponding to the word group from the set of word groups from the dictionary list; wherein the cosine similarity measure is weighted by giving exponentially increasing the weight given to the similarity of words as those words approach the end of the first word group and the second word group. | 7. The system of claim 1 , wherein calculating the set of part of speech scores for the input string comprises, for each word group from the set of word groups from the dictionary list, calculating a cosine similarity measure between: (a) a first word group corresponding to the input word group corresponding to the invented part of speech; and (b) a second word group corresponding to the word group from the set of word groups from the dictionary list; wherein the cosine similarity measure is weighted by giving exponentially increasing the weight given to the similarity of words as those words approach the end of the first word group and the second word group. 9. The system of claim 7 , wherein calculating the set of part of speech scores for the input string comprises: (a) defining the first word group by deleting any grouping words from the input word group; and (b) defining the second word group by deleting any grouping words from the word group from the set of word groups from the dictionary list. | 0.703419 |
8,407,041 | 15 | 17 | 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. 17. The method of claim 15 , further comprising deriving the decision variables using Bayesian decision rules. | 0.811644 |
9,921,665 | 9 | 10 | 9. The method as recited in claim 1 , wherein the selecting comprises: pre-selecting one or more qualified applications from the one or more applications that are qualified to run under the scenario of the host application; calculating a score for each of the one or more qualified applications based on the multiple parameters relating to the user input; ranking the one or more qualified applications based on their respective scores; and selecting the application from the one or more qualified applications based on a threshold of score, a threshold of ranking, or both. | 9. The method as recited in claim 1 , wherein the selecting comprises: pre-selecting one or more qualified applications from the one or more applications that are qualified to run under the scenario of the host application; calculating a score for each of the one or more qualified applications based on the multiple parameters relating to the user input; ranking the one or more qualified applications based on their respective scores; and selecting the application from the one or more qualified applications based on a threshold of score, a threshold of ranking, or both. 10. The method as recited in claim 9 , further comprising modifying a ranking or a score of a particular application through machine-learning techniques. | 0.5 |
7,487,094 | 13 | 14 | 13. The method of claim 1 , further comprising: enabling a user to create a category and define it in terms of words, phrases, sentences, events, logical relationship to another category, or a combination thereof. | 13. The method of claim 1 , further comprising: enabling a user to create a category and define it in terms of words, phrases, sentences, events, logical relationship to another category, or a combination thereof. 14. The method of claim 13 , further comprising: automatically or semi-automatically expanding input from said user to generate computer output semantically equivalent to said user input. | 0.633333 |
10,049,663 | 1 | 12 | 1. A system for operating a digital assistant to explore media items, the system comprising: one or more processors; and memory having instructions stored thereon, the instructions, when executed by the one or more processors, cause the one or more processors to: receive, from a user, speech input representing a request for one or more media items; evaluate a text representation of the speech input against a set of rules to determine whether or not the speech input corresponds to a user intent of obtaining personalized recommendations for media items, wherein the evaluating includes determining an actionable intent node by analyzing words in the text representation against words of a vocabulary index associated with a plurality of actionable intent nodes, and wherein the set of rules includes a first rule that the actionable intent node corresponds to an actionable intent of obtaining personalized recommendations for media items and a second rule that one or more words in the text representation refers to the user; in accordance with a determination that the text representation satisfies the set of rules: obtain at least one media item from a user-specific corpus of media items, the user-specific corpus of media items generated according to inferred media preferences of the user; and provide the at least one media item from the user-specific corpus of media items; and in accordance with a determination that the text representation does not satisfy the set of rules: obtain at least one media item from a general corpus of media items, the general corpus of media items generated according to inferred media preferences of a plurality of users; and provide the at least one media item from the general corpus of media items. | 1. A system for operating a digital assistant to explore media items, the system comprising: one or more processors; and memory having instructions stored thereon, the instructions, when executed by the one or more processors, cause the one or more processors to: receive, from a user, speech input representing a request for one or more media items; evaluate a text representation of the speech input against a set of rules to determine whether or not the speech input corresponds to a user intent of obtaining personalized recommendations for media items, wherein the evaluating includes determining an actionable intent node by analyzing words in the text representation against words of a vocabulary index associated with a plurality of actionable intent nodes, and wherein the set of rules includes a first rule that the actionable intent node corresponds to an actionable intent of obtaining personalized recommendations for media items and a second rule that one or more words in the text representation refers to the user; in accordance with a determination that the text representation satisfies the set of rules: obtain at least one media item from a user-specific corpus of media items, the user-specific corpus of media items generated according to inferred media preferences of the user; and provide the at least one media item from the user-specific corpus of media items; and in accordance with a determination that the text representation does not satisfy the set of rules: obtain at least one media item from a general corpus of media items, the general corpus of media items generated according to inferred media preferences of a plurality of users; and provide the at least one media item from the general corpus of media items. 12. The system of claim 1 , wherein the instructions further cause the one or more processors to: determine whether the text representation defines an activity; and in accordance with the determination that the text representation satisfies the set of rules and that the text representation defines an activity, obtain the at least one media item from the user-specific corpus of media items based on the activity, wherein the at least one media item from the user-specific corpus of media items includes metadata indicating the activity. | 0.682783 |
7,552,472 | 24 | 25 | 24. The system of claim 23 , further comprising: means for repeating said applying each of a plurality of functions step for a predetermined number of events to capture a window of events as a window example; and means for sequentially shifting said window down one event at a time until a final event within said database falls within said window. | 24. The system of claim 23 , further comprising: means for repeating said applying each of a plurality of functions step for a predetermined number of events to capture a window of events as a window example; and means for sequentially shifting said window down one event at a time until a final event within said database falls within said window. 25. The system of claim 24 , further comprising: means for applying current policy rules base to determine a labeling for each event window example; means for labeling an event window selected by a user for override of an initial labeling to produce a set of re-labeled event example windows; and means for applying theory refinement to the set of re-labeled event example windows to generate a new policy document that is consistent with the re-labeled event example windows. | 0.5 |
8,144,921 | 1 | 4 | 1. A computer-implemented method for retrieving an electronic document using invisible junction features, the method comprising: receiving an image of an input electronic document; extracting, with a processor, an invisible junction feature descriptor from the image; and retrieving, with the processor, information for an output electronic document using the invisible junction feature descriptor and a geometric constraint. | 1. A computer-implemented method for retrieving an electronic document using invisible junction features, the method comprising: receiving an image of an input electronic document; extracting, with a processor, an invisible junction feature descriptor from the image; and retrieving, with the processor, information for an output electronic document using the invisible junction feature descriptor and a geometric constraint. 4. The method of claim 1 wherein the information is one from the group of a document identification, a point in the document, a page in the document, a viewing region in the document, and the output document itself. | 0.830709 |
8,239,378 | 11 | 15 | 11. A computer-readable memory device storing programming instructions that are executable by one or more processors of one or more devices, the programming instructions comprising: one or more instructions to determine that a document is a search result that is responsive to a plurality of different search queries; one or more instructions to negatively adjust a score for the document based on determining that the document is a search result that is responsive to the plurality of different search queries; one or more instructions to rank the document with regard to at least one other document based on the negatively-adjusted score; one or more instructions to determine that the other particular document is an authoritative document; and one or more instructions to bypass negatively adjusting a score, for the other particular document, based on determining that the other particular document is an authoritative document. | 11. A computer-readable memory device storing programming instructions that are executable by one or more processors of one or more devices, the programming instructions comprising: one or more instructions to determine that a document is a search result that is responsive to a plurality of different search queries; one or more instructions to negatively adjust a score for the document based on determining that the document is a search result that is responsive to the plurality of different search queries; one or more instructions to rank the document with regard to at least one other document based on the negatively-adjusted score; one or more instructions to determine that the other particular document is an authoritative document; and one or more instructions to bypass negatively adjusting a score, for the other particular document, based on determining that the other particular document is an authoritative document. 15. The computer-readable memory device of claim 11 , where the one or more instructions to rank the document include one or more instructions to rank the document with regard to the at least one other document based on the generated score, independent of a relevance of the document to a search query. | 0.734622 |
10,042,921 | 1 | 3 | 1. A method, comprising: receiving a natural language query from a user with an interface; generating multiple dependency parses of the natural language query with a parser device connected to the interface, said generating of the multiple dependency parses including: dividing the natural language query into multiple components by identifying a part of speech of each component, wherein the part of speech includes one of a noun, a verb, an adverb, and an adjective, and creating a single dependency parse by connecting each component with at least one other component; applying rules to all of the multiple dependency parses with a processor connected to the parser device to identify entities and relations in the natural language query, and generating a structured data language query to a database from the entities and relations, wherein the number of multiple dependency parses is greater than the number of words in the natural language query. | 1. A method, comprising: receiving a natural language query from a user with an interface; generating multiple dependency parses of the natural language query with a parser device connected to the interface, said generating of the multiple dependency parses including: dividing the natural language query into multiple components by identifying a part of speech of each component, wherein the part of speech includes one of a noun, a verb, an adverb, and an adjective, and creating a single dependency parse by connecting each component with at least one other component; applying rules to all of the multiple dependency parses with a processor connected to the parser device to identify entities and relations in the natural language query, and generating a structured data language query to a database from the entities and relations, wherein the number of multiple dependency parses is greater than the number of words in the natural language query. 3. The method according to claim 1 , wherein said connecting includes creating a direct link between a verb and two nouns. | 0.894828 |
4,803,641 | 6 | 15 | 6. A knowledge system comprising a computer having a memory, said memory storing a knowledge base including expressions and knowledge for determining values for said expressions, said memory including a cache porton for storing certain ones of said expressions and corresponding determined values for the stored expressions, said memory also storing a control procedure executable by said computer for interpreting the knowledge base to determine values for said expressions, said control procedure including means for recognizing the occurrence of an expression in the knowledge base, means for searching the cache to determine whether the recognized expression is stored in the cache, means for obtaining from the cache the corresponding value of the recognized expression when the recognized expession is in the cache, and means for applying the knowledge in the knowledge base to determine a corresponding value for the recognized expression when the recognized expression is not in the cache and then storing the recognized expression and its corresponding value in the cache. | 6. A knowledge system comprising a computer having a memory, said memory storing a knowledge base including expressions and knowledge for determining values for said expressions, said memory including a cache porton for storing certain ones of said expressions and corresponding determined values for the stored expressions, said memory also storing a control procedure executable by said computer for interpreting the knowledge base to determine values for said expressions, said control procedure including means for recognizing the occurrence of an expression in the knowledge base, means for searching the cache to determine whether the recognized expression is stored in the cache, means for obtaining from the cache the corresponding value of the recognized expression when the recognized expession is in the cache, and means for applying the knowledge in the knowledge base to determine a corresponding value for the recognized expression when the recognized expression is not in the cache and then storing the recognized expression and its corresponding value in the cache. 15. The knowledge system as claimed in claim 6, wherein said cache stores certainty factors and reasons for values corresponding to certain expressions, and said means for applying said knowledge includes means for accumulating evidence from said knowledge base for determining values by combining certainty factors and reasons for values and storing the combined certainty factors and the combined reasons in the cache. | 0.592233 |
8,024,320 | 1 | 2 | 1. A method for querying a database comprising: identifying an interface to the database for receiving a query including path expressions by a database management apparatus; receiving input defining a compliance rule, the input including: i) input identifying a configuration-item type, the identified configuration-item type determining a type of configuration item in an IT infrastructure of different types of configuration items; ii) input defining a rule scope, the rule scope determining which configuration items of the identified type are to be checked by the compliance rule; and iii) input defining a desired state for each of the configuration items to be checked by the rule, the desired state including at least one compliance condition that must be satisfied for a checked configuration item to be in compliance; receiving input identifying at least one path, each path being from an object in an object model to a related object in the object model or to an attribute of a related object in the object model; creating a path expression for each identified path, each path expression being composed from tokens selected from the group consisting of object identifiers, attribute identifiers, a relationship operator, and path qualifiers, the tokens sequentially added together to create the path expression; displaying at least one list of selectable items, each item associated with a token; receiving selection of at least one of the selectable items; including the at least one token associated with the selected at least one item into the path expression for one of the identified paths; creating a query for querying data structured in accordance with the object model, the query including at least one of the created path expressions; and executing the query on the database to query the data. | 1. A method for querying a database comprising: identifying an interface to the database for receiving a query including path expressions by a database management apparatus; receiving input defining a compliance rule, the input including: i) input identifying a configuration-item type, the identified configuration-item type determining a type of configuration item in an IT infrastructure of different types of configuration items; ii) input defining a rule scope, the rule scope determining which configuration items of the identified type are to be checked by the compliance rule; and iii) input defining a desired state for each of the configuration items to be checked by the rule, the desired state including at least one compliance condition that must be satisfied for a checked configuration item to be in compliance; receiving input identifying at least one path, each path being from an object in an object model to a related object in the object model or to an attribute of a related object in the object model; creating a path expression for each identified path, each path expression being composed from tokens selected from the group consisting of object identifiers, attribute identifiers, a relationship operator, and path qualifiers, the tokens sequentially added together to create the path expression; displaying at least one list of selectable items, each item associated with a token; receiving selection of at least one of the selectable items; including the at least one token associated with the selected at least one item into the path expression for one of the identified paths; creating a query for querying data structured in accordance with the object model, the query including at least one of the created path expressions; and executing the query on the database to query the data. 2. The method of claim 1 , wherein the path qualifiers comprise: a particular attribute identifier of the attribute identifiers; a threshold value; and an operator for comparing the threshold value to the identified attribute. | 0.757511 |
8,533,643 | 1 | 2 | 1. A method of a processor performing template-based classification of a circuit design, the method comprising: the processor reading a template file that defines a plurality of channel-connected-region (CCR) templates and super-CCR templates; the processor formatting a graph for each of the CCR templates and super-CCR templates; the processor identifying a plurality of CCRs based on a partitioned netlist file that defines a given circuit design; the processor generating a graph for each of the identified CCRs; the processor identifying a matching CCR template graph for each generated CCR graph; and the processor determining in an interative manner, for each formatted super-CCR template graph, all possible combinations of CCRs and previously-matched super-CCRs that are candidates to match the formatted super-CCR template graph. | 1. A method of a processor performing template-based classification of a circuit design, the method comprising: the processor reading a template file that defines a plurality of channel-connected-region (CCR) templates and super-CCR templates; the processor formatting a graph for each of the CCR templates and super-CCR templates; the processor identifying a plurality of CCRs based on a partitioned netlist file that defines a given circuit design; the processor generating a graph for each of the identified CCRs; the processor identifying a matching CCR template graph for each generated CCR graph; and the processor determining in an interative manner, for each formatted super-CCR template graph, all possible combinations of CCRs and previously-matched super-CCRs that are candidates to match the formatted super-CCR template graph. 2. The method of claim 1 , wherein each of the super-CCR template graphs defines at least one of a plurality of CCRs or a plurality of super-CCRs that are interconnected, the method further comprising: the processor generating a graph for each candidate combination; and the processor determining which of the candidate combinations actually match the formatted super-CCR template graph. | 0.5 |
8,260,817 | 19 | 26 | 19. A method of processing text intervals, comprising: extracting a first proposition from a first text interval; providing a plurality of semantic roles, wherein each role of the plurality of roles defines a different semantic relationship between at least two words; generating a first proposition tree from the first proposition, wherein the first proposition tree comprises at least one node connected to other nodes by at least one edge, wherein each node is respectively associated with at least one word from the first proposition; assigning at least one of the plurality of roles to the at least one edge; determining a first similarity value between the first text interval and a second text interval based on a comparison of the first proposition tree and a second proposition tree corresponding to the second text interval, wherein the second text interval is different from the first text interval and at least one of the first text interval and the second text interval comprises natural language; and selectively outputting, using a processor, the second text interval based the first similarity value. | 19. A method of processing text intervals, comprising: extracting a first proposition from a first text interval; providing a plurality of semantic roles, wherein each role of the plurality of roles defines a different semantic relationship between at least two words; generating a first proposition tree from the first proposition, wherein the first proposition tree comprises at least one node connected to other nodes by at least one edge, wherein each node is respectively associated with at least one word from the first proposition; assigning at least one of the plurality of roles to the at least one edge; determining a first similarity value between the first text interval and a second text interval based on a comparison of the first proposition tree and a second proposition tree corresponding to the second text interval, wherein the second text interval is different from the first text interval and at least one of the first text interval and the second text interval comprises natural language; and selectively outputting, using a processor, the second text interval based the first similarity value. 26. The method of claim 19 , comprising: generating a first plurality of proposition subtrees and a second plurality of proposition subtrees; and determining a second similarity value by matching the first plurality of proposition subtrees to the second plurality of proposition subtrees. | 0.598886 |
9,009,292 | 26 | 27 | 26. A system configured to perform context-based data pre-fetching and notification for an application, comprising: a context modeling module configured to create and maintain a context model that defines a domain of situational information associated with an application, wherein the context model comprises at least one or more context variables and context events, and wherein each of the context variables is associated with an update frequency that controls how frequently changes in the context variables occur; a context variable module configured to populate and update one or more of the context variables within the context model based on a state of the application; a data selection module configured to determine a dataset for the application, wherein the determination is based on values of one or more of the context variables and the context events of at least one instantiated context that is based on the context model, and wherein the dataset is unmodifiable by the application when the application; an inference module configured to maintain an inference engine used by the data selection module to identify a likely set of data needed by the application; an event engine module configured to subscribe to the context events of the instantiated context, wherein the context events are associated with changes in the context variables corresponding to the situational information for the specific mobile device and its user; and a notification module configured to generate a notification for the application, wherein the notification comprises at least a non-modifiable dataset and associated metadata describing data contained within the non-modifiable dataset wherein at least one of the modules is implemented using one or more computer processors. | 26. A system configured to perform context-based data pre-fetching and notification for an application, comprising: a context modeling module configured to create and maintain a context model that defines a domain of situational information associated with an application, wherein the context model comprises at least one or more context variables and context events, and wherein each of the context variables is associated with an update frequency that controls how frequently changes in the context variables occur; a context variable module configured to populate and update one or more of the context variables within the context model based on a state of the application; a data selection module configured to determine a dataset for the application, wherein the determination is based on values of one or more of the context variables and the context events of at least one instantiated context that is based on the context model, and wherein the dataset is unmodifiable by the application when the application; an inference module configured to maintain an inference engine used by the data selection module to identify a likely set of data needed by the application; an event engine module configured to subscribe to the context events of the instantiated context, wherein the context events are associated with changes in the context variables corresponding to the situational information for the specific mobile device and its user; and a notification module configured to generate a notification for the application, wherein the notification comprises at least a non-modifiable dataset and associated metadata describing data contained within the non-modifiable dataset wherein at least one of the modules is implemented using one or more computer processors. 27. The system of claim 26 , wherein the notification module is further configured to populate a variable indicating whether the notification is actionable or informational. | 0.551813 |
8,290,822 | 21 | 26 | 21. A computer-implemented system for efficiently displaying selectable attribute values for a product based on a provided criterion, comprising: at least one memory storage device storing: a set of product records that identify products potentially selectable by a user, wherein the product records comprise product attributes that represent one or more features of the product, wherein the product attributes comprise one or more attribute values; and one or more product configuration rules used to define permissible or impermissible product configurations and attributes of the products; at least one processor programmed to: analyze at least one product configuration rule to determine whether at least one product attribute of at least one product record is used in evaluating the at least one product configuration rule; create an attribute binary decision diagram (BDD) structure representative of the at least one product attribute of the least one product record when the at least one processor determines that the at least one product attribute is used in evaluating the at least one product configuration rule; and evaluate the attribute BDD structure and prepare a customized set of product records for transmission to the user, wherein the customized set of product records contains product attribute values selectable by the user. | 21. A computer-implemented system for efficiently displaying selectable attribute values for a product based on a provided criterion, comprising: at least one memory storage device storing: a set of product records that identify products potentially selectable by a user, wherein the product records comprise product attributes that represent one or more features of the product, wherein the product attributes comprise one or more attribute values; and one or more product configuration rules used to define permissible or impermissible product configurations and attributes of the products; at least one processor programmed to: analyze at least one product configuration rule to determine whether at least one product attribute of at least one product record is used in evaluating the at least one product configuration rule; create an attribute binary decision diagram (BDD) structure representative of the at least one product attribute of the least one product record when the at least one processor determines that the at least one product attribute is used in evaluating the at least one product configuration rule; and evaluate the attribute BDD structure and prepare a customized set of product records for transmission to the user, wherein the customized set of product records contains product attribute values selectable by the user. 26. The computer-implemented system of claim 21 , wherein at least one product record of the set of products records is structured according to a meta-language syntax, wherein the meta-language syntax comprises at least one element of data content and at least one element identifier that describes the type of content of the at least one element of data content. | 0.842311 |
9,747,269 | 6 | 16 | 6. The method as recited in claim 1 , wherein the workflow comprises one or more of a telecommunications application or function; an insurance quote; a health care admission process; a signing ceremony; and a financial services application configured to facilitate one or more of: displaying at least one of an account statement, an account balance, and a payment due date; processing a deposit; preparing a tax return; and processing a loan application. | 6. The method as recited in claim 1 , wherein the workflow comprises one or more of a telecommunications application or function; an insurance quote; a health care admission process; a signing ceremony; and a financial services application configured to facilitate one or more of: displaying at least one of an account statement, an account balance, and a payment due date; processing a deposit; preparing a tax return; and processing a loan application. 16. The method as recited in claim 6 , wherein the context of the optical input is determined to be Internet browsing based at least in part on detecting the optical input comprises a universal resource locator (URL); and wherein the contextually-appropriate workflow comprises a browser application. | 0.6875 |
9,158,811 | 1 | 7 | 1. A method comprising: automatically performing a correlation search in accordance with a defined frequency, the correlation search associated with a service provided by one or more entities that each have corresponding machine data, the service having one or more key performance indicators (KPIs), each KPI defined by a search query that derives a value from the corresponding machine data to indicate a state of the service at a point in time or during a period of time; wherein the correlation search associated with the service comprises search criteria pertaining to the one or more KPIs, and a triggering condition to be applied to data identified by a search query using the search criteria; storing a notable event in response to the data identified by the search query satisfying the triggering condition; and causing display of a graphical user interface presenting information pertaining to the stored notable event, the information comprising an identification of the correlation search that triggered the storing of the notable event and an identification of the service associated with the correlation search; wherein each of the entities corresponds to a stored entity definition having an identification of the corresponding machine data, and the service corresponds to a stored service definition referencing the stored entity definitions; wherein the method is performed by a computer system comprising one or more processing devices coupled to a memory for storing the notable event, the service definition, the entity definitions, and the KPIs. | 1. A method comprising: automatically performing a correlation search in accordance with a defined frequency, the correlation search associated with a service provided by one or more entities that each have corresponding machine data, the service having one or more key performance indicators (KPIs), each KPI defined by a search query that derives a value from the corresponding machine data to indicate a state of the service at a point in time or during a period of time; wherein the correlation search associated with the service comprises search criteria pertaining to the one or more KPIs, and a triggering condition to be applied to data identified by a search query using the search criteria; storing a notable event in response to the data identified by the search query satisfying the triggering condition; and causing display of a graphical user interface presenting information pertaining to the stored notable event, the information comprising an identification of the correlation search that triggered the storing of the notable event and an identification of the service associated with the correlation search; wherein each of the entities corresponds to a stored entity definition having an identification of the corresponding machine data, and the service corresponds to a stored service definition referencing the stored entity definitions; wherein the method is performed by a computer system comprising one or more processing devices coupled to a memory for storing the notable event, the service definition, the entity definitions, and the KPIs. 7. The method of claim 1 , wherein the search criteria pertaining to the one or more KPIs pertains to an aspect KPI characterizing the state of an aspect of the service, and the triggering condition is based at least in part on one or more KPI states indicated by the aspect KPI data satisfying the search criteria. | 0.609181 |
9,449,279 | 22 | 33 | 22. A computer implemented method to process usage data received from a wireless device, the method comprising: processing, by executing an instruction with a processor, the usage data to identify first and second user-invoked applications accessed sequentially on the wireless device in a time period, the first and second applications being accessed sequentially without an intermediary application being accessed after the first application is accessed and prior to the second application being accessed; building, with an aggregator implemented by the processor, a behavior model based on the identified applications, the behavior model to describe user behavior associated with the wireless device; executing the behavior model with a predictor implemented by the processor to predict usage of an application on the wireless device; based on the prediction, monitoring usage of the wireless device with the processor to determine an accuracy of the prediction; and updating the behavior model with the processor based on the accuracy of the prediction by executing an instruction, wherein at least one of the aggregator or the predictor includes a logic circuit. | 22. A computer implemented method to process usage data received from a wireless device, the method comprising: processing, by executing an instruction with a processor, the usage data to identify first and second user-invoked applications accessed sequentially on the wireless device in a time period, the first and second applications being accessed sequentially without an intermediary application being accessed after the first application is accessed and prior to the second application being accessed; building, with an aggregator implemented by the processor, a behavior model based on the identified applications, the behavior model to describe user behavior associated with the wireless device; executing the behavior model with a predictor implemented by the processor to predict usage of an application on the wireless device; based on the prediction, monitoring usage of the wireless device with the processor to determine an accuracy of the prediction; and updating the behavior model with the processor based on the accuracy of the prediction by executing an instruction, wherein at least one of the aggregator or the predictor includes a logic circuit. 33. The method of claim 22 , wherein the executing of the behavior model includes using a Markov model. | 0.834405 |
8,762,225 | 1 | 2 | 1. A system comprising: one or more processors to: receive a search query that includes a search term; identify a first document related to the search term; determine a first score for the first document based on a factor related to the search term; determine that the first document corresponds to a book that has appeared in a best seller list, the best seller list including a list of books that have been purchased a greater number of times than other books in a particular time period; determine a location from which the search query is received; determine a second score for the first document based on the first document corresponding to a book that has appeared in a best seller list in the location from which the search query is received, the second score being higher than a particular score based on the first document corresponding to the book that has appeared in the best seller list in the location from which the search query is received, the particular score being for a second document that appears on another best seller list in another location that does not match the location from which the search query is received; generate a combined score for the first document based on the first score and the second score; and provide information associated with the first document as a search result based on the generated combined score. | 1. A system comprising: one or more processors to: receive a search query that includes a search term; identify a first document related to the search term; determine a first score for the first document based on a factor related to the search term; determine that the first document corresponds to a book that has appeared in a best seller list, the best seller list including a list of books that have been purchased a greater number of times than other books in a particular time period; determine a location from which the search query is received; determine a second score for the first document based on the first document corresponding to a book that has appeared in a best seller list in the location from which the search query is received, the second score being higher than a particular score based on the first document corresponding to the book that has appeared in the best seller list in the location from which the search query is received, the particular score being for a second document that appears on another best seller list in another location that does not match the location from which the search query is received; generate a combined score for the first document based on the first score and the second score; and provide information associated with the first document as a search result based on the generated combined score. 2. The system of claim 1 , where, when determining the second score for the first document, the one or more processors are further to: assign the second score to the first document that is higher than a second score assigned to a third document based on the first document corresponding to the book that has appeared in the best seller list and the third document corresponding to a book that has never appeared in a best seller list. | 0.5 |
10,007,725 | 15 | 17 | 15. A method, comprising: receiving, by at least one computing device, a dialogue search query from a client device; executing, by the at least one computing device, a verbal media content search using the dialogue search query to identify a media content item; identifying, by the at least one computing device, a product discussed in a dialogue of the media content item; sending, by the at least one computing device, a search result listing to the client device, the search result listing including the media content item and a recommendation for the product; receiving, by the at least one computing device, a selection of the media content item from the client device; determining, by the at least one computing device, a relatively popular portion of the media content item based at least in part on a dialogue of the relatively popular portion of the media content item being included in a plurality of dialogue search queries received from a plurality of client devices; causing, by the at least one computing device, the media content item to be rendered via the client device; and causing, by the at least one computing device, the recommendation for the product to be rendered via the client device in response to the relatively popular portion of the media content item being rendered. | 15. A method, comprising: receiving, by at least one computing device, a dialogue search query from a client device; executing, by the at least one computing device, a verbal media content search using the dialogue search query to identify a media content item; identifying, by the at least one computing device, a product discussed in a dialogue of the media content item; sending, by the at least one computing device, a search result listing to the client device, the search result listing including the media content item and a recommendation for the product; receiving, by the at least one computing device, a selection of the media content item from the client device; determining, by the at least one computing device, a relatively popular portion of the media content item based at least in part on a dialogue of the relatively popular portion of the media content item being included in a plurality of dialogue search queries received from a plurality of client devices; causing, by the at least one computing device, the media content item to be rendered via the client device; and causing, by the at least one computing device, the recommendation for the product to be rendered via the client device in response to the relatively popular portion of the media content item being rendered. 17. The method of claim 15 , further comprising identifying, by the at least one computing device, another product that is similar to the product, wherein the search result listing further includes a recommendation for the other product. | 0.68484 |
7,810,026 | 8 | 9 | 8. The computing device of claim 6 , wherein each page record further comprises a word/drawing representation table, and wherein the word/drawing representation table includes references to drawing representations of the contours and vertices for each word on the page. | 8. The computing device of claim 6 , wherein each page record further comprises a word/drawing representation table, and wherein the word/drawing representation table includes references to drawing representations of the contours and vertices for each word on the page. 9. The computing device of claim 8 , wherein the references to drawing representations in the word/drawing representation table comprises references to drawing representations in the global drawing representation table. | 0.5 |
7,516,123 | 1 | 8 | 1. A computer-implemented method for querying semantically linked web pages in a semantic web comprising web pages linked by semantic links, each semantic link characterized as having a label providing a specific semantic link type, the method comprising: receiving a query from a user, the query comprising one or more interest vectors, an interest vector representing an amount of user interest in web pages related to a corresponding semantic link type; based on the received query, searching a plurality of pages, the search identifying semantically linked web pages comprising at least a first page and a second page, the first page semantically linked to a target web page by a first semantic link type, the second page semantically linked to the target web page by a second semantic link type; obtaining a first page rank value related to the first page and a second page rank value related to the second page, the first page rank value indicating a value associated with the first semantic link type and the second page rank value indicating a value associated with the second semantic link type; calculating a first custom page rank value associated with the first page, the calculation based on the obtained first page rank value and the one or more interest vectors; calculating a second custom page rank value associated with the second page, the calculation based on the obtained second page rank value and the one or more interest vectors; and storing in a computer memory, as page rank values related to the target page, the calculated first custom page rank value and the calculated second custom page rank value. | 1. A computer-implemented method for querying semantically linked web pages in a semantic web comprising web pages linked by semantic links, each semantic link characterized as having a label providing a specific semantic link type, the method comprising: receiving a query from a user, the query comprising one or more interest vectors, an interest vector representing an amount of user interest in web pages related to a corresponding semantic link type; based on the received query, searching a plurality of pages, the search identifying semantically linked web pages comprising at least a first page and a second page, the first page semantically linked to a target web page by a first semantic link type, the second page semantically linked to the target web page by a second semantic link type; obtaining a first page rank value related to the first page and a second page rank value related to the second page, the first page rank value indicating a value associated with the first semantic link type and the second page rank value indicating a value associated with the second semantic link type; calculating a first custom page rank value associated with the first page, the calculation based on the obtained first page rank value and the one or more interest vectors; calculating a second custom page rank value associated with the second page, the calculation based on the obtained second page rank value and the one or more interest vectors; and storing in a computer memory, as page rank values related to the target page, the calculated first custom page rank value and the calculated second custom page rank value. 8. The method according to claim 1 wherein the interest vector is derived from a GUI user prompt. | 0.945931 |
5,517,432 | 1 | 5 | 1. In a computer system comprising a formal specification of a logic circuit having at least one finite state machine (FSM) and at least one set of functional vectors for simulating the logic circuit, an apparatus for analyzing and verifying said at least one FSM's design and implementation, said apparatus comprising: a) synthesis means for generating a gate level specification of said logic circuit in response to said formal specification of said logic circuit; b) state table generation means comprising: b.1) command script generation means for generating at least one state table extraction command script file for said at least one FSM in response to said formal specification of said logic circuit: and b.2) state table extraction means for generating said at least one state table for said at least one FSM in response to said gate level specification of said logic circuit and said at least one state table extraction command script file; c) simulation means for simulating and generating simulation results of said at least one FSM in response to said gate level specification of said logic circuit, said at least one state table for said at least one FSM, and said at least one set of functional vectors; and d) reporting means for generating analysis reports in response to said simulation results of said at least one FSM and user inputs. | 1. In a computer system comprising a formal specification of a logic circuit having at least one finite state machine (FSM) and at least one set of functional vectors for simulating the logic circuit, an apparatus for analyzing and verifying said at least one FSM's design and implementation, said apparatus comprising: a) synthesis means for generating a gate level specification of said logic circuit in response to said formal specification of said logic circuit; b) state table generation means comprising: b.1) command script generation means for generating at least one state table extraction command script file for said at least one FSM in response to said formal specification of said logic circuit: and b.2) state table extraction means for generating said at least one state table for said at least one FSM in response to said gate level specification of said logic circuit and said at least one state table extraction command script file; c) simulation means for simulating and generating simulation results of said at least one FSM in response to said gate level specification of said logic circuit, said at least one state table for said at least one FSM, and said at least one set of functional vectors; and d) reporting means for generating analysis reports in response to said simulation results of said at least one FSM and user inputs. 5. The apparatus as set forth in claim 1, wherein said reporting means comprises: d.1) a command interpreter for interpreting user commands; d.2) a loader cooperating with said command interpreter for loading said at least one state table and simulation results for said at least one FSM; d.3) a database for storing said loaded at least one state table and said simulation results; and d.4) a plurality of function routines cooperating with said command interpreter and said database for performing a plurality of reporting and related functions. | 0.515071 |
9,601,112 | 1 | 6 | 1. A speech recognition system using incremental device-based acoustic model adaptation comprising: a model selector configured to select an acoustic model of a multi-model tree by verifying and categorizing a device key transmitted from a user device; a model manager configured to generate and incrementally adapt the multi-model tree by categorizing voice data based on the device key; and a speech recognizer configured to perform speech recognition based on the selected acoustic model and transmit data of which reliability exceeds a predetermined threshold value to the model manager, wherein the device key represents channel features of the user device, and wherein the model manager comprises: a device-based multi-model tree generating part configured to categorize the voice data based on the device key, extract features therefrom and form the multi-model tree, the multi-model tree being categorized by the device key and comprising hierarchical acoustic models, incremental data and device key trees; a data incrementing part configured to receive data of which the reliability exceeds the predetermined threshold value from the speech recognizer, increment phonetic information and data to the multi-model tree, evaluate a degree of the incremented data of each node, and report a result of the evaluation to a model adaptation generating part when the degree exceeds a predetermined reference value; and the model adaptation generating part configured to incrementally adapt acoustic models corresponding to nodes where newly adapted data from the multi-model tree exceeds the predetermined reference value by using the phonetic information transmitted from the data incrementing part. | 1. A speech recognition system using incremental device-based acoustic model adaptation comprising: a model selector configured to select an acoustic model of a multi-model tree by verifying and categorizing a device key transmitted from a user device; a model manager configured to generate and incrementally adapt the multi-model tree by categorizing voice data based on the device key; and a speech recognizer configured to perform speech recognition based on the selected acoustic model and transmit data of which reliability exceeds a predetermined threshold value to the model manager, wherein the device key represents channel features of the user device, and wherein the model manager comprises: a device-based multi-model tree generating part configured to categorize the voice data based on the device key, extract features therefrom and form the multi-model tree, the multi-model tree being categorized by the device key and comprising hierarchical acoustic models, incremental data and device key trees; a data incrementing part configured to receive data of which the reliability exceeds the predetermined threshold value from the speech recognizer, increment phonetic information and data to the multi-model tree, evaluate a degree of the incremented data of each node, and report a result of the evaluation to a model adaptation generating part when the degree exceeds a predetermined reference value; and the model adaptation generating part configured to incrementally adapt acoustic models corresponding to nodes where newly adapted data from the multi-model tree exceeds the predetermined reference value by using the phonetic information transmitted from the data incrementing part. 6. The speech recognition system of claim 1 , wherein the device-based multi-model tree generating part categorizes the voice data by the device key and generates the multi-model tree which generates a device dependent model adapted at a device independent model. | 0.809971 |
10,055,487 | 1 | 13 | 1. A method for making a preference available, the method comprising the steps of: receiving, by a processor, from a censorship device, data generated by an individual person that is within a field-of-censorship; generating, by the processor, historical information regarding a history of an object indicated by text data based on the received individual person generated data; extracting, by the processor, historical text data that satisfies a predetermined historical condition regarding the generated historical information; generating, by the processor, a number of references in connection with a user ID that identifies the individual person who has generated the individual person generated data, the number of references indicating a number of times the text data is at least one of: re-posted, re-tweeted or referred to in an email chain; extracting, by the processor, particular text data that satisfies a predetermined reference condition, based on the number of references, out of the historical text data; transmitting, by the processor, to the censorship device, the particular text data thereby making the particular text data available to the censorship system; and generating, by the censorship device, a censorship control command as a specific executable command for the individual person based on the related text data, wherein the censorship control command causes blocking of information containing the particular text data. | 1. A method for making a preference available, the method comprising the steps of: receiving, by a processor, from a censorship device, data generated by an individual person that is within a field-of-censorship; generating, by the processor, historical information regarding a history of an object indicated by text data based on the received individual person generated data; extracting, by the processor, historical text data that satisfies a predetermined historical condition regarding the generated historical information; generating, by the processor, a number of references in connection with a user ID that identifies the individual person who has generated the individual person generated data, the number of references indicating a number of times the text data is at least one of: re-posted, re-tweeted or referred to in an email chain; extracting, by the processor, particular text data that satisfies a predetermined reference condition, based on the number of references, out of the historical text data; transmitting, by the processor, to the censorship device, the particular text data thereby making the particular text data available to the censorship system; and generating, by the censorship device, a censorship control command as a specific executable command for the individual person based on the related text data, wherein the censorship control command causes blocking of information containing the particular text data. 13. The method of claim 1 , wherein the determined preference depends on at least one of: (i) the fact that the individual person has transmitted information regarding the predetermined object or related terminology many times and (ii) the contents of the transmitted information. | 0.598854 |
8,301,356 | 1 | 4 | 1. Method for estimating NOx creation in a combustion process of a four-stroke internal combustion engine including a variable volume combustion chamber defined by a piston reciprocating within a cylinder between top-dead center and bottom-dead center points, intake and exhaust passages, and intake and exhaust valves controlled during repetitive, sequential exhaust, intake, compression and expansion strokes of said piston, comprising: monitoring engine sensor inputs comprising a cylinder pressure within the combustion chamber; modeling a mass fraction burn value for combustion within the combustion chamber based upon said engine sensor inputs, wherein said mass fraction burn value indexes a crank angle at which a selected percentage of injected fuel is burned in a combustion cycle; estimating a state of combustion within the combustion chamber based upon the mass fraction burn value, the state of combustion comprising a combustion phasing and a combustion strength; and estimating NOx creation within the combustion chamber with an artificial neural network based upon said state of combustion. | 1. Method for estimating NOx creation in a combustion process of a four-stroke internal combustion engine including a variable volume combustion chamber defined by a piston reciprocating within a cylinder between top-dead center and bottom-dead center points, intake and exhaust passages, and intake and exhaust valves controlled during repetitive, sequential exhaust, intake, compression and expansion strokes of said piston, comprising: monitoring engine sensor inputs comprising a cylinder pressure within the combustion chamber; modeling a mass fraction burn value for combustion within the combustion chamber based upon said engine sensor inputs, wherein said mass fraction burn value indexes a crank angle at which a selected percentage of injected fuel is burned in a combustion cycle; estimating a state of combustion within the combustion chamber based upon the mass fraction burn value, the state of combustion comprising a combustion phasing and a combustion strength; and estimating NOx creation within the combustion chamber with an artificial neural network based upon said state of combustion. 4. The method of claim 1 , wherein said modeling said mass fraction burn value includes analyzing said cylinder pressure through spectral analysis comprising a Fast Fourier Transform. | 0.782143 |
8,745,725 | 11 | 12 | 11. The system of claim 5 , wherein said particular movement detecting module comprises: a moving away detecting module configured to detect that the computing device has moved in the particular manner when the moving away detecting module at least detects that the computing device has moved away from the first user. | 11. The system of claim 5 , wherein said particular movement detecting module comprises: a moving away detecting module configured to detect that the computing device has moved in the particular manner when the moving away detecting module at least detects that the computing device has moved away from the first user. 12. The system of claim 11 , wherein said moving away detecting module comprises: a moving away detecting module configured to detect that the computing device has moved away from the first user by at least detecting that the computing device has moved a predefined distance away from the first user. | 0.5 |
9,501,571 | 1 | 2 | 1. A computer-implemented method for associating categories with business names for generalizing search queries, the method comprising: receiving, using one or more computing devices, an indication of a search query from a user containing one or more search terms or phrases; identifying, using the one or more computing devices, one or more businesses within a first geographic region associated with the user; determining, using the one or more computing devices, a business name and one or more categories associated with each of the one or more businesses; generating, using the one or more computing devices, one or more name components for each of the one or more businesses, each name component comprising a subset of the business name of the business; generating, using the one or more computing devices, one or more name component groups from the name components of the one or more businesses, wherein each name component group comprises one or more identical name components; determining, using the one or more computing devices, for each name component group, if the one or more name components within the name component group share one or more common categories; associating, using the one or more computing devices, the one or more common categories with the name component of the name component group, when the one or more name components within the name component group share one or more common categories; and providing, using the one or more computing devices, the one or more common categories to the user for inclusion within the query. | 1. A computer-implemented method for associating categories with business names for generalizing search queries, the method comprising: receiving, using one or more computing devices, an indication of a search query from a user containing one or more search terms or phrases; identifying, using the one or more computing devices, one or more businesses within a first geographic region associated with the user; determining, using the one or more computing devices, a business name and one or more categories associated with each of the one or more businesses; generating, using the one or more computing devices, one or more name components for each of the one or more businesses, each name component comprising a subset of the business name of the business; generating, using the one or more computing devices, one or more name component groups from the name components of the one or more businesses, wherein each name component group comprises one or more identical name components; determining, using the one or more computing devices, for each name component group, if the one or more name components within the name component group share one or more common categories; associating, using the one or more computing devices, the one or more common categories with the name component of the name component group, when the one or more name components within the name component group share one or more common categories; and providing, using the one or more computing devices, the one or more common categories to the user for inclusion within the query. 2. The method of claim 1 , further comprising: discarding the one or more name components of the name component group if the one or more name components within the name component group do not share one or more common categories. | 0.828313 |
4,675,840 | 13 | 14 | 13. A computer system comprising: a programmable computer with an address bus, a data bus, means for generating control signals, and means for generating a clock signal; a speech processor having a voice synthesizer, speech memory, and a programmable microcomputer having means for connecting said speech memory to said voice synthesizer and programmed with control programs to scan said speech memory and respond to data entries therein by transferring data from said speech memory to said voice synthesizer; means for generating a memory read data signal, a memory write data signal, and a memory address signal; causing the selective transfer of data from said computer into said speech memory or from said speech memory into said computer; said control signal generating means including means for generating an enable signal which connects said computer to said microcomputer and is arranged to initiate operation of the control programs stored in the microcomputer when said enable signal is generated; and a program set controlling the operation of said computer including data write command sequences which cause data to be transferred to said speech memory from said computer and said write signal to be generated, data read command sequences which cause data to be transferred from said speech memory to said computer and said read signal to be generated, and sound processor enabling command sequences which cause said control signal generating means to generate said enable signal. | 13. A computer system comprising: a programmable computer with an address bus, a data bus, means for generating control signals, and means for generating a clock signal; a speech processor having a voice synthesizer, speech memory, and a programmable microcomputer having means for connecting said speech memory to said voice synthesizer and programmed with control programs to scan said speech memory and respond to data entries therein by transferring data from said speech memory to said voice synthesizer; means for generating a memory read data signal, a memory write data signal, and a memory address signal; causing the selective transfer of data from said computer into said speech memory or from said speech memory into said computer; said control signal generating means including means for generating an enable signal which connects said computer to said microcomputer and is arranged to initiate operation of the control programs stored in the microcomputer when said enable signal is generated; and a program set controlling the operation of said computer including data write command sequences which cause data to be transferred to said speech memory from said computer and said write signal to be generated, data read command sequences which cause data to be transferred from said speech memory to said computer and said read signal to be generated, and sound processor enabling command sequences which cause said control signal generating means to generate said enable signal. 14. A computer system as defined in claim 13 wherein said means for generating a write data signal includes: means for decoding the coincidence of a write control signal from said computer and a speech memory select signal from said computer. | 0.5 |
9,953,055 | 12 | 14 | 12. A system for optimization of content selection infrastructure, comprising: an entity engine executing on one or more processors of a data processing system that retrieves a search query report that includes 1) a plurality of queries corresponding to selected content items of a content campaign, and 2) a performance metric for each of the plurality of queries determined based on a performance of the selected content items of the content campaign; the entity engine determines, from a database, an entity for each query of the plurality of queries, the entity having a unique identifier indicating a classification based on a domain, a type and a property that establishes a relationship to at least one other entity stored in the database; a cluster engine executing on the data processing system that generates, based on a clustering technique applied to the unique identifier indicating the classification of the entity for each query of the plurality of queries, a first subset of the plurality of queries and a second subset of the plurality of queries, wherein the plurality of queries are separated into the first subset and the second subset based on the classification indicated by the unique identifier of the entity for each query of the plurality of queries; the cluster engine generates, based on the performance metric for each of the plurality of queries, a first performance metric for the first subset and a second performance metric for the second subset, the first performance metric different from the second performance metric; an interface of the data processing system that provides, for display on a display device, the first performance metric and the second performance metric; a campaign generator executing on the data processing system that receives, based on the first performance metric, a selection of a semantic criterion associated with the first subset generated based on the classification indicated by the unique identifier of the entity for each query of the plurality of queries; and the campaign generator updates the content campaign to include the semantic criterion. | 12. A system for optimization of content selection infrastructure, comprising: an entity engine executing on one or more processors of a data processing system that retrieves a search query report that includes 1) a plurality of queries corresponding to selected content items of a content campaign, and 2) a performance metric for each of the plurality of queries determined based on a performance of the selected content items of the content campaign; the entity engine determines, from a database, an entity for each query of the plurality of queries, the entity having a unique identifier indicating a classification based on a domain, a type and a property that establishes a relationship to at least one other entity stored in the database; a cluster engine executing on the data processing system that generates, based on a clustering technique applied to the unique identifier indicating the classification of the entity for each query of the plurality of queries, a first subset of the plurality of queries and a second subset of the plurality of queries, wherein the plurality of queries are separated into the first subset and the second subset based on the classification indicated by the unique identifier of the entity for each query of the plurality of queries; the cluster engine generates, based on the performance metric for each of the plurality of queries, a first performance metric for the first subset and a second performance metric for the second subset, the first performance metric different from the second performance metric; an interface of the data processing system that provides, for display on a display device, the first performance metric and the second performance metric; a campaign generator executing on the data processing system that receives, based on the first performance metric, a selection of a semantic criterion associated with the first subset generated based on the classification indicated by the unique identifier of the entity for each query of the plurality of queries; and the campaign generator updates the content campaign to include the semantic criterion. 14. The system of claim 12 , wherein at least one of the selected content items was displayed via a computing device that input a query of the plurality of queries. | 0.795511 |
8,094,948 | 1 | 3 | 1. A method for classifying digital images, comprising: hierarchically clustering the digital images into a set of meaningful clusters based on at least two levels of clustering optical parameters, including: clustering the digital images based on determined light content of the digital images and clustering the digital images based on depth of field associated with the digital images; associating the set of meaningful clusters to a set of associated classes used by a user; and classifying the digital images according to the set of associated classes. | 1. A method for classifying digital images, comprising: hierarchically clustering the digital images into a set of meaningful clusters based on at least two levels of clustering optical parameters, including: clustering the digital images based on determined light content of the digital images and clustering the digital images based on depth of field associated with the digital images; associating the set of meaningful clusters to a set of associated classes used by a user; and classifying the digital images according to the set of associated classes. 3. The method for classifying digital images of claim 1 , further comprising: automatically annotating each digital image with a set of text for further classification. | 0.629956 |
9,946,749 | 19 | 20 | 19. A computer program product, encoded on one or more non-transitory computer storage media, comprising instructions that when executed by one or more computers cause the one or more computers to perform operations comprising: generating, for an original attribute of a relation maintained in a database system, a respective auxiliary attribute for each interval size of a plurality of interval sizes, each interval size corresponding to a different respective power of a particular exponent base; computing, for each data entry of the relation and for each interval size of the plurality of interval sizes, a respective interval number for the interval size to which an original attribute value of the data entry belongs; storing each respective computed interval number for each data entry in the database system as an auxiliary attribute value of a corresponding auxiliary attribute for the data entry, receiving, by a query rewriter of a user device in communication with the database system, an original query having an inequality expression for the original attribute, generating a new query that replaces the inequality expression with multiple equality expressions, wherein each equality expression references a different respective auxiliary attribute, each auxiliary attribute representing a different respective interval size for values of the original attribute; providing, by the user device to the database system, the new query having the multiple equality expressions instead of the original query; and receiving, by the user device from the database system, query results that satisfy the inequality expression for the original attribute. | 19. A computer program product, encoded on one or more non-transitory computer storage media, comprising instructions that when executed by one or more computers cause the one or more computers to perform operations comprising: generating, for an original attribute of a relation maintained in a database system, a respective auxiliary attribute for each interval size of a plurality of interval sizes, each interval size corresponding to a different respective power of a particular exponent base; computing, for each data entry of the relation and for each interval size of the plurality of interval sizes, a respective interval number for the interval size to which an original attribute value of the data entry belongs; storing each respective computed interval number for each data entry in the database system as an auxiliary attribute value of a corresponding auxiliary attribute for the data entry, receiving, by a query rewriter of a user device in communication with the database system, an original query having an inequality expression for the original attribute, generating a new query that replaces the inequality expression with multiple equality expressions, wherein each equality expression references a different respective auxiliary attribute, each auxiliary attribute representing a different respective interval size for values of the original attribute; providing, by the user device to the database system, the new query having the multiple equality expressions instead of the original query; and receiving, by the user device from the database system, query results that satisfy the inequality expression for the original attribute. 20. The computer program product of claim 19 , wherein generating the new query that replaces the inequality expression with a bounded number of equality expressions comprises: generating a disjunct of equality expressions including determining, for each interval size of a plurality of interval sizes other than a maximum interval size, whether respective equality expressions that test for an auxiliary attribute value belonging to a first interval at the interval size, a last interval at the interval size, or both, should be added to the disjunct of equality expressions. | 0.736746 |
4,723,290 | 2 | 3 | 2. A speech recognition apparatus according to claim 1, wherein said compatibility coefficient generating means comprises a memory for storing a plurality of relative recognition coefficient data respectively representing the compatibility coefficients between two preselected continuous phoneme symbol data. | 2. A speech recognition apparatus according to claim 1, wherein said compatibility coefficient generating means comprises a memory for storing a plurality of relative recognition coefficient data respectively representing the compatibility coefficients between two preselected continuous phoneme symbol data. 3. A speech recognition apparatus according to claim 2, wherein said data generating means comprises a segment detecting circuit connected to said parameter generating means and for detecting each segment on the basis of the acoustic parameter data from said parameter generating means, reference pattern generating means for generating a plurality of reference pattern data representing a plurality of reference phonetic symbols, and score calculating circuit connected to said segment detecting circuit and reference pattern generating means and for generating corresponding phonetic symbol data and score data when the score having a value higher than a predetermined value is obtained by calculating the score corresponding to the similarity between the acoustic pattern data composed of the acoustic parameter data generated from said parameter generating means and the reference pattern data from said reference pattern generating means in each segment detected by said segment detecting circuit. | 0.5 |
9,372,540 | 1 | 12 | 1. An electronic device for performing a function based on gesture recognition, the electronic device comprising: a camera configured to capture an image; a display; and a controller configured to: divide the display into a plurality of display regions, wherein at least two regions among the plurality of display regions are assigned respectively to a plurality of users and at least one common control region among the plurality of display regions is assigned to all users, recognize gestures performed by the plurality of users based on the image, control the plurality of display regions respectively assigned to the plurality of users performing the gestures, according to the respective gestures, control the at least one common control region according to at least one of the all users'gestures to the common control region regardless of regions assigned respectively, display at least one content on one region of the plurality of display regions, move at least a portion of the at least one content to an outer side of the one region of the plurality of display regions when receiving a corresponding user's gesture, wherein the at least the portion of the at least one content overlapping with at least one other region of the plurality of display regions is not displayed, and remove at least one region of the plurality of display regions when a user's gesture corresponding to the at least one region of the plurality of display regions is not received during a pre-set time interval, wherein the pre-set time interval is determined according to a type of a content displayed on the at least one region. | 1. An electronic device for performing a function based on gesture recognition, the electronic device comprising: a camera configured to capture an image; a display; and a controller configured to: divide the display into a plurality of display regions, wherein at least two regions among the plurality of display regions are assigned respectively to a plurality of users and at least one common control region among the plurality of display regions is assigned to all users, recognize gestures performed by the plurality of users based on the image, control the plurality of display regions respectively assigned to the plurality of users performing the gestures, according to the respective gestures, control the at least one common control region according to at least one of the all users'gestures to the common control region regardless of regions assigned respectively, display at least one content on one region of the plurality of display regions, move at least a portion of the at least one content to an outer side of the one region of the plurality of display regions when receiving a corresponding user's gesture, wherein the at least the portion of the at least one content overlapping with at least one other region of the plurality of display regions is not displayed, and remove at least one region of the plurality of display regions when a user's gesture corresponding to the at least one region of the plurality of display regions is not received during a pre-set time interval, wherein the pre-set time interval is determined according to a type of a content displayed on the at least one region. 12. The electronic device of claim 1 , wherein when a pre-set event occurs while the display is in a divided state having the plurality of display regions, the controller releases the divided state of the display. | 0.691304 |
8,903,754 | 8 | 12 | 8. A computer program product for reporting identified items of interest associated with a brand associated with an identity of an entity, the computer program product comprising: a computer readable storage medium having computer readable program code embodied thereon, the computer readable program code comprising: computer readable program code for generating, by a computer, a seed document containing criteria representative of items of interest representative of a brand associated with an identity of a selected entity, wherein the items of interest are associated with the identity of the selected entity by a policy for associating items of interest with brand indicia of predetermined entities; computer readable program code for receiving, by the computer, the seed document containing the criteria into a repository to initialize the repository, wherein the repository comprises information describing brand indicia representative of the selected entity; computer readable program code for analyzing, by the computer, a selected source material using the criteria in the seed document in combination with the repository, by selectively applying adapters associated with specific types of content contained within the selected source material to perform analysis including semantic analysis and pattern matching; computer readable program code responsive to the analysis, for identifying, by the computer, a set of items of interest in the selected source material that meet the criteria representative of items of interest associated with the selected entity to form an identified set of items of interest; and computer readable program code for generating, by the computer, a report wherein the report includes the identified set of items of interest, and wherein the computer readable program code for generating further comprises computer readable program code for: filtering a result, by the computer, using a set of rules to form a filtered result; prompting a user, by the computer, to accept or reject an identified item of interest in the filtered result; responsive to receiving an acceptance, the computer increasing a relevancy score associated with the identified item of interest; responsive to receiving a rejection, the computer decreasing the relevancy score associated with the identified item of interest; determining, by the computer, whether a relevancy score associated with the identified item of interest meets a predetermined threshold value; responsive to the relevancy score associated with the identified item of interest not meeting the predetermined threshold value, the computer filtering the result to remove the identified item of interest from the identified set of items of interest in the filtered result to form a remaining set of identified items of interest in the filtered result; linking an identified item of interest in the remaining set of identified items of interest in the filtered result, by the computer, to a corresponding document in the selected source in which the identified item of interest is located; marking the identified item of interest in the remaining set of identified items of interest in the filtered result for review; and updating the repository, by the computer, using information associated with the remaining set of identified items of interest in the filtered result including respective relevancy scores. | 8. A computer program product for reporting identified items of interest associated with a brand associated with an identity of an entity, the computer program product comprising: a computer readable storage medium having computer readable program code embodied thereon, the computer readable program code comprising: computer readable program code for generating, by a computer, a seed document containing criteria representative of items of interest representative of a brand associated with an identity of a selected entity, wherein the items of interest are associated with the identity of the selected entity by a policy for associating items of interest with brand indicia of predetermined entities; computer readable program code for receiving, by the computer, the seed document containing the criteria into a repository to initialize the repository, wherein the repository comprises information describing brand indicia representative of the selected entity; computer readable program code for analyzing, by the computer, a selected source material using the criteria in the seed document in combination with the repository, by selectively applying adapters associated with specific types of content contained within the selected source material to perform analysis including semantic analysis and pattern matching; computer readable program code responsive to the analysis, for identifying, by the computer, a set of items of interest in the selected source material that meet the criteria representative of items of interest associated with the selected entity to form an identified set of items of interest; and computer readable program code for generating, by the computer, a report wherein the report includes the identified set of items of interest, and wherein the computer readable program code for generating further comprises computer readable program code for: filtering a result, by the computer, using a set of rules to form a filtered result; prompting a user, by the computer, to accept or reject an identified item of interest in the filtered result; responsive to receiving an acceptance, the computer increasing a relevancy score associated with the identified item of interest; responsive to receiving a rejection, the computer decreasing the relevancy score associated with the identified item of interest; determining, by the computer, whether a relevancy score associated with the identified item of interest meets a predetermined threshold value; responsive to the relevancy score associated with the identified item of interest not meeting the predetermined threshold value, the computer filtering the result to remove the identified item of interest from the identified set of items of interest in the filtered result to form a remaining set of identified items of interest in the filtered result; linking an identified item of interest in the remaining set of identified items of interest in the filtered result, by the computer, to a corresponding document in the selected source in which the identified item of interest is located; marking the identified item of interest in the remaining set of identified items of interest in the filtered result for review; and updating the repository, by the computer, using information associated with the remaining set of identified items of interest in the filtered result including respective relevancy scores. 12. The computer program product of claim 8 , wherein computer readable program code generating the report, further comprises: computer readable program code for associating a relevancy score, by the computer, with each respective item of the identified set of items of interest, according to a degree of confidence associated with the analysis of the selected source, for each item of the identified set of items of interest. | 0.645 |
8,676,563 | 1 | 8 | 1. A method for providing a trusted translation, comprising: receiving a human-generated translation of a document from a source language to a target language, the human-generated translation being produced by a person; generating a trust level prediction of the human-generated translation based at least in part on a mapping by executing a quality-prediction engine stored in memory, the trust level prediction of the human-generated translation associated with translational accuracy of the human-generated translation, the quality-prediction engine being calibrated, the calibration including: obtaining a plurality of opinions for a plurality of sample translations performed by the person, each of the opinions from a human and indicating a perceived trust level of corresponding sample translations, and using the quality prediction-engine to determine a trust level of each of the plurality of sample translations, determining a relationship between the plurality of opinions and the trust levels of each of the plurality of sample translations, and tuning the mapping to minimize any difference between the plurality of opinions and the trust levels of each of the plurality of sample translations; and outputting the human-generated translation and the trust level prediction of the human-generated translation. | 1. A method for providing a trusted translation, comprising: receiving a human-generated translation of a document from a source language to a target language, the human-generated translation being produced by a person; generating a trust level prediction of the human-generated translation based at least in part on a mapping by executing a quality-prediction engine stored in memory, the trust level prediction of the human-generated translation associated with translational accuracy of the human-generated translation, the quality-prediction engine being calibrated, the calibration including: obtaining a plurality of opinions for a plurality of sample translations performed by the person, each of the opinions from a human and indicating a perceived trust level of corresponding sample translations, and using the quality prediction-engine to determine a trust level of each of the plurality of sample translations, determining a relationship between the plurality of opinions and the trust levels of each of the plurality of sample translations, and tuning the mapping to minimize any difference between the plurality of opinions and the trust levels of each of the plurality of sample translations; and outputting the human-generated translation and the trust level prediction of the human-generated translation. 8. The method of claim 1 , further comprising receiving configuration information for a translation to be performed by humans. | 0.813056 |
9,341,492 | 1 | 11 | 1. A navigation device that includes a voice acquirer that acquires an inputted voice, a voice recognizer that carries out a voice recognition process on voice data acquired by said voice acquirer, and a position acquirer that acquires a position of a moving object, said navigation device providing route guidance on a basis of a result of the recognition by said voice recognizer, the position of the moving object which is acquired by said position acquirer, and map data, said navigation device comprising: a route guidance expression storage that stores route guidance expressions; a route guidance expression extractor that refers to said route guidance expression storage to extract a route guidance expression from the result of the recognition by said voice recognizer; a route guidance expression interpreter that interprets the route guidance expression extracted by said route guidance expression extractor to determine a concrete route guidance expression including a travelling direction, wherein the concrete route guidance expression does not include a destination; a route guidance expression information to be presented storage that stores visual information to be presented corresponding to said concrete route guidance expression while bringing the visual information to be presented into correspondence with said concrete route guidance expression; a route guidance expression information to be presented retriever that refers to said route guidance expression information to be presented storage to retrieve the corresponding visual information to be presented as a real-time visual representation of the concrete route guidance expression determined by said route guidance expression interpreter; and a presentation control outputter that outputs the visual information to be presented retrieved by said route guidance expression information to be presented retriever, wherein the real-time visual representation includes graphical data of an arrow or a pointer which points in the travelling direction included in the concrete route guidance expression. | 1. A navigation device that includes a voice acquirer that acquires an inputted voice, a voice recognizer that carries out a voice recognition process on voice data acquired by said voice acquirer, and a position acquirer that acquires a position of a moving object, said navigation device providing route guidance on a basis of a result of the recognition by said voice recognizer, the position of the moving object which is acquired by said position acquirer, and map data, said navigation device comprising: a route guidance expression storage that stores route guidance expressions; a route guidance expression extractor that refers to said route guidance expression storage to extract a route guidance expression from the result of the recognition by said voice recognizer; a route guidance expression interpreter that interprets the route guidance expression extracted by said route guidance expression extractor to determine a concrete route guidance expression including a travelling direction, wherein the concrete route guidance expression does not include a destination; a route guidance expression information to be presented storage that stores visual information to be presented corresponding to said concrete route guidance expression while bringing the visual information to be presented into correspondence with said concrete route guidance expression; a route guidance expression information to be presented retriever that refers to said route guidance expression information to be presented storage to retrieve the corresponding visual information to be presented as a real-time visual representation of the concrete route guidance expression determined by said route guidance expression interpreter; and a presentation control outputter that outputs the visual information to be presented retrieved by said route guidance expression information to be presented retriever, wherein the real-time visual representation includes graphical data of an arrow or a pointer which points in the travelling direction included in the concrete route guidance expression. 11. The navigation device according to claim 1 , wherein said navigation device further includes a route guidance expression appropriateness determinator that determines whether or not the concrete route guidance expression determined by said route guidance expression interpreter is appropriate, and said presentation control outputter does not output said visual information to be presented when said route guidance expression appropriateness determinator determines that said concrete route guidance expression is not appropriate. | 0.627793 |
8,000,957 | 11 | 12 | 11. A computer program product that includes a non-transitory computer readable medium useable by a processor, the medium having stored thereon a sequence of instructions which, when executed by the processor, causes the processor to translate an interpretation of a keyword query into a grammatically correct plain-language query, wherein the computer program product executes the steps of: acquiring at least one keyword to perform a keyword query search upon; generating a keyword query in order to semantically interpret the acquired keyword, further including the step of building a translation index to determine matching elements, wherein matching elements are derived from information comprising type names, attribute names, and atomic attributes values that are associated with a specific keyword; merging the matching elements in the event that differing keywords comprise a same matching element and type alias; providing a clause template for the customization of a plain-language sentence clause, wherein the plain-language sentence clause is based upon the matching elements that are selected for customization; generating at least one plain-language sentence clause for each of the matching elements, wherein the matching elements relate to matches including a type match, a path patch, a value match and a word match; determining if the plain-language sentence clauses can be merged, wherein the determination is based upon the attributes matched for a given type element; specifying the plain-language sentence clauses that are to be merged, the plain-language sentence clause mergers being based upon the attributes matched for a given matching element; merging the plain-language sentence clauses, wherein the merging occurs for at least one of the path match, the value match and a combination of the path match and the value match, and wherein the merging is not possible for the type match and the word match; generating at least one grammatically valid plain-language sentence interpretation for the keyword query from the generated plain-language sentence clauses, wherein the grammatically valid plain-language sentence is based upon differing matching elements; presenting the at least one grammatically valid plain-language sentence interpretation for the keyword query to a keyword query system user for the user's review. | 11. A computer program product that includes a non-transitory computer readable medium useable by a processor, the medium having stored thereon a sequence of instructions which, when executed by the processor, causes the processor to translate an interpretation of a keyword query into a grammatically correct plain-language query, wherein the computer program product executes the steps of: acquiring at least one keyword to perform a keyword query search upon; generating a keyword query in order to semantically interpret the acquired keyword, further including the step of building a translation index to determine matching elements, wherein matching elements are derived from information comprising type names, attribute names, and atomic attributes values that are associated with a specific keyword; merging the matching elements in the event that differing keywords comprise a same matching element and type alias; providing a clause template for the customization of a plain-language sentence clause, wherein the plain-language sentence clause is based upon the matching elements that are selected for customization; generating at least one plain-language sentence clause for each of the matching elements, wherein the matching elements relate to matches including a type match, a path patch, a value match and a word match; determining if the plain-language sentence clauses can be merged, wherein the determination is based upon the attributes matched for a given type element; specifying the plain-language sentence clauses that are to be merged, the plain-language sentence clause mergers being based upon the attributes matched for a given matching element; merging the plain-language sentence clauses, wherein the merging occurs for at least one of the path match, the value match and a combination of the path match and the value match, and wherein the merging is not possible for the type match and the word match; generating at least one grammatically valid plain-language sentence interpretation for the keyword query from the generated plain-language sentence clauses, wherein the grammatically valid plain-language sentence is based upon differing matching elements; presenting the at least one grammatically valid plain-language sentence interpretation for the keyword query to a keyword query system user for the user's review. 12. The computer program product of claim 11 , further comprising the step of providing a template for the overall structure of the at least one grammatically valid plain-language sentence. | 0.5 |
9,569,178 | 1 | 3 | 1. A method for recommending streams application actors for fusion, wherein the streams application actors are dispersed on an operator graph within a streaming environment, the method comprising: generating, for each of two or more streams application actors in the operator graph, a streams application actor profile; determining, from streams application actor profiles for two or more streams application actors, the two or more streams application actors are fusion candidates, wherein the determining is based on streams application actor profile data, including historical runtime data and real-time processing data, and based on the streams application actors satisfying at least one fusion candidate rule from a set of fusion candidate rules, each fusion candidate rule associated with one or more fusion recommendations, wherein the fusion recommendation includes reconfiguration data for a particular portion of the operator graph; identifying, in response to the determining, a fusion recommendation from the one or more fusion recommendations associated with the at least one fusion candidate rule; displaying, in response to the identifying, an identity of each of the two or more streams application actors, the fusion recommendation, and the reconfiguration data for a particular portion of the operator graph, wherein the displayed fusion recommendation shows a table indicating the current performance of the two or more streams application actors and one or more predicted performance of future processing cycles of the two or more streams application actors each performance associated with the implementation of the fusion recommendation; and accept the fusion recommendation, and automatically apply, by a compiler, the accepted fusion recommendation to the two or more streams application actors and reconfiguring the particular portion of the operator graph. | 1. A method for recommending streams application actors for fusion, wherein the streams application actors are dispersed on an operator graph within a streaming environment, the method comprising: generating, for each of two or more streams application actors in the operator graph, a streams application actor profile; determining, from streams application actor profiles for two or more streams application actors, the two or more streams application actors are fusion candidates, wherein the determining is based on streams application actor profile data, including historical runtime data and real-time processing data, and based on the streams application actors satisfying at least one fusion candidate rule from a set of fusion candidate rules, each fusion candidate rule associated with one or more fusion recommendations, wherein the fusion recommendation includes reconfiguration data for a particular portion of the operator graph; identifying, in response to the determining, a fusion recommendation from the one or more fusion recommendations associated with the at least one fusion candidate rule; displaying, in response to the identifying, an identity of each of the two or more streams application actors, the fusion recommendation, and the reconfiguration data for a particular portion of the operator graph, wherein the displayed fusion recommendation shows a table indicating the current performance of the two or more streams application actors and one or more predicted performance of future processing cycles of the two or more streams application actors each performance associated with the implementation of the fusion recommendation; and accept the fusion recommendation, and automatically apply, by a compiler, the accepted fusion recommendation to the two or more streams application actors and reconfiguring the particular portion of the operator graph. 3. The method of claim 1 , wherein the fusion recommendation is to separate the two or more streams applications actors from a same processing element. | 0.690574 |
8,200,495 | 15 | 21 | 15. An apparatus for recognizing speech and implementing a speech recognition function, the apparatus comprising: circuitry for initiating a speech dialog with at least one point in the dialog where there is a grammar of possible responses and a set of at least one expected response and wherein the set is a subset of the grammar and the set includes the most likely response or responses expected to be uttered by a user at the at least one point in the speech dialog, the set of at least one expected response for the at least one point being known in the speech recognition system before receiving input speech from the user; circuitry operable for receiving input speech from the user for progressing through the speech dialog; circuitry configured for generating acoustic features of the input speech received from a user; processing circuitry including a match/search algorithm having acoustic models, the acoustic models including acoustic models that are associated with the set of at least one expected response; the processing circuitry operable for comparing the generated input speech acoustic features to acoustic models associated with words in the grammar to generate a hypothesis and further operable for comparing the hypothesis with at least one expected response in the set to determine if the hypothesis matches the at least one expected response in the set; the processing circuitry further operable, if the hypothesis matches the at least one expected response in the set to adapt at least one acoustic model corresponding to the matched expected response using the acoustic features of the input speech to use the at least one adapted model with future input speech in the speech recognition system, otherwise, not adapting the at least one acoustic model corresponding to the expected response. | 15. An apparatus for recognizing speech and implementing a speech recognition function, the apparatus comprising: circuitry for initiating a speech dialog with at least one point in the dialog where there is a grammar of possible responses and a set of at least one expected response and wherein the set is a subset of the grammar and the set includes the most likely response or responses expected to be uttered by a user at the at least one point in the speech dialog, the set of at least one expected response for the at least one point being known in the speech recognition system before receiving input speech from the user; circuitry operable for receiving input speech from the user for progressing through the speech dialog; circuitry configured for generating acoustic features of the input speech received from a user; processing circuitry including a match/search algorithm having acoustic models, the acoustic models including acoustic models that are associated with the set of at least one expected response; the processing circuitry operable for comparing the generated input speech acoustic features to acoustic models associated with words in the grammar to generate a hypothesis and further operable for comparing the hypothesis with at least one expected response in the set to determine if the hypothesis matches the at least one expected response in the set; the processing circuitry further operable, if the hypothesis matches the at least one expected response in the set to adapt at least one acoustic model corresponding to the matched expected response using the acoustic features of the input speech to use the at least one adapted model with future input speech in the speech recognition system, otherwise, not adapting the at least one acoustic model corresponding to the expected response. 21. The apparatus of claim 15 wherein the at least one expected response is obtained by at least one of evaluating an expression or retrieving the expected response from a table or data structure. | 0.570175 |
7,505,968 | 28 | 36 | 28. The method of claim 25 , wherein using the search linkages and the organizational linkages to calculate a relevance factor for each potentially relevant document comprises determining a baseline relevance factor and thereafter adjusting the relevance factor based on one or more specific comparisons. | 28. The method of claim 25 , wherein using the search linkages and the organizational linkages to calculate a relevance factor for each potentially relevant document comprises determining a baseline relevance factor and thereafter adjusting the relevance factor based on one or more specific comparisons. 36. The method of claim 28 , wherein adjusting the relevance factor based on one or more specific comparisons comprises adjusting the baseline relevance factor based on a comparison between a parcel associated with the particular document and a parcel supplied by a user. | 0.507273 |
9,679,250 | 1 | 17 | 1. A method programmed in a non-transitory memory of a device comprising: a. automatically fact checking target information by comparing the target information with source information to generate a result, wherein the target information comprises web page information or social networking information, wherein comparing includes at least one of: i. searching for an exact match of the target information in the source information and returning the result of the exact match search if the exact match is found; ii. utilizing pattern matching for fact checking and returning the result of the pattern matching fact check if a pattern matching result confidence score is above a pattern matching result confidence threshold; and iii. utilizing a natural language search for fact checking and returning the result of the natural language fact check if a natural language result confidence score is above a natural language result confidence threshold; and b. automatically affecting the target information and presenting a status of the target information in real-time based on the result of the comparison of the target information with the source information, wherein searching for the exact match begins searching the source information located on a fastest access time hardware device and continues to slower access time hardware devices; wherein utilizing pattern matching begins utilizing the source information located on the fastest access time hardware device and continues to the slower access time hardware devices; and wherein the natural language search begins searching the source information located on the fastest access time hardware device and continues to the slower access time hardware devices, wherein searching for the exact match begins searching the source information classified by a plurality of keywords found in the target information, then using the source information classified by a single keyword found in the target information, and then using the source information classified by keywords related to the keywords found in the target information; wherein utilizing pattern matching begins utilizing the source information classified by the plurality of keywords found in the target information, then using the source information classified by the single keyword found in the target information, and then using the source information classified by the keywords related to the keywords found in the target information; and wherein the natural language search begins searching the source information classified by the plurality of keywords found in the target information, then using the source information classified by the single keyword found in the target information, and then using the source information classified by the keywords related to the keywords found in the target information. | 1. A method programmed in a non-transitory memory of a device comprising: a. automatically fact checking target information by comparing the target information with source information to generate a result, wherein the target information comprises web page information or social networking information, wherein comparing includes at least one of: i. searching for an exact match of the target information in the source information and returning the result of the exact match search if the exact match is found; ii. utilizing pattern matching for fact checking and returning the result of the pattern matching fact check if a pattern matching result confidence score is above a pattern matching result confidence threshold; and iii. utilizing a natural language search for fact checking and returning the result of the natural language fact check if a natural language result confidence score is above a natural language result confidence threshold; and b. automatically affecting the target information and presenting a status of the target information in real-time based on the result of the comparison of the target information with the source information, wherein searching for the exact match begins searching the source information located on a fastest access time hardware device and continues to slower access time hardware devices; wherein utilizing pattern matching begins utilizing the source information located on the fastest access time hardware device and continues to the slower access time hardware devices; and wherein the natural language search begins searching the source information located on the fastest access time hardware device and continues to the slower access time hardware devices, wherein searching for the exact match begins searching the source information classified by a plurality of keywords found in the target information, then using the source information classified by a single keyword found in the target information, and then using the source information classified by keywords related to the keywords found in the target information; wherein utilizing pattern matching begins utilizing the source information classified by the plurality of keywords found in the target information, then using the source information classified by the single keyword found in the target information, and then using the source information classified by the keywords related to the keywords found in the target information; and wherein the natural language search begins searching the source information classified by the plurality of keywords found in the target information, then using the source information classified by the single keyword found in the target information, and then using the source information classified by the keywords related to the keywords found in the target information. 17. The method of claim 1 further comprising analyzing a validity rating of the entity, wherein if the validity rating of the entity is below a threshold, then the source information is limited to sources with a rating above a reliability threshold. | 0.880288 |
8,713,462 | 11 | 12 | 11. The system of claim 8 , further comprising instructions to cause the one or more processors to perform operations, including: displaying previews of the plurality of files, wherein the previews of the plurality of files are arranged in an overlapping manner, and wherein using the displayed previews of the plurality of files includes moving backwards or forwards through the displayed previews. | 11. The system of claim 8 , further comprising instructions to cause the one or more processors to perform operations, including: displaying previews of the plurality of files, wherein the previews of the plurality of files are arranged in an overlapping manner, and wherein using the displayed previews of the plurality of files includes moving backwards or forwards through the displayed previews. 12. The system of claim 11 , wherein selecting a particular preview of a particular file in the plurality of files causes the particular preview of the particular file to become a focal point among the displayed previews. | 0.5 |
9,367,591 | 1 | 6 | 1. A server having a CPU, a storage section for storing computer program which is readable by the CPU, and a communication section, wherein the storage section includes: a question information storing region for storing accumulated questions; and an answer information storing region for storing accumulated answers to the accumulated questions independently from the accumulated questions, the accumulated answers being associated with the accumulated questions; wherein the accumulated questions are associated with question support numbers for each type of member, the question support numbers being counted when the accumulated questions are supported by the member, wherein the accumulated answers are associated with answer support numbers for each type of member, the answer support numbers being counted when the accumulated answers are supported by the member, wherein the communication section receives search information for searching the accumulated questions and the accumulated answers, and a user ID of a searcher; wherein the CPU identifies a searcher type based on the user ID of the searcher received by the communication section, searches for questions and answers including the search information received by the communication section from the accumulated questions and the accumulated answers, extracts questions and answers, from the searched questions and the searched answers, supported by member of a same type as the identified searcher type, arranges the extracted questions and extracted answers, as an order for displaying the extracted questions and the extracted answers, in an order of higher values of the question support numbers and the answer support numbers corresponding to the identified searcher type, and prepares a display screen in which the extracted questions and the extracted answers are arranged based on the order for displaying. | 1. A server having a CPU, a storage section for storing computer program which is readable by the CPU, and a communication section, wherein the storage section includes: a question information storing region for storing accumulated questions; and an answer information storing region for storing accumulated answers to the accumulated questions independently from the accumulated questions, the accumulated answers being associated with the accumulated questions; wherein the accumulated questions are associated with question support numbers for each type of member, the question support numbers being counted when the accumulated questions are supported by the member, wherein the accumulated answers are associated with answer support numbers for each type of member, the answer support numbers being counted when the accumulated answers are supported by the member, wherein the communication section receives search information for searching the accumulated questions and the accumulated answers, and a user ID of a searcher; wherein the CPU identifies a searcher type based on the user ID of the searcher received by the communication section, searches for questions and answers including the search information received by the communication section from the accumulated questions and the accumulated answers, extracts questions and answers, from the searched questions and the searched answers, supported by member of a same type as the identified searcher type, arranges the extracted questions and extracted answers, as an order for displaying the extracted questions and the extracted answers, in an order of higher values of the question support numbers and the answer support numbers corresponding to the identified searcher type, and prepares a display screen in which the extracted questions and the extracted answers are arranged based on the order for displaying. 6. The server according to claim 1 , further comprising other sites extraction section for extracting other sites, wherein: the CPU searches for questions from accumulated questions in the question information accumulation section of extracted other Question and Answer (Q&A) sites, and searches for answers from accumulated answers in the answer information accumulation section of the other Q&A sites searched by the other sites search section, and the communication section also transmits other sites search result question information searched by the CPU and other sites search result answer information searched by the CPU. | 0.5 |
8,260,817 | 6 | 16 | 6. The system of claim 1 , further comprising: an augmentation module configured to, for at least one node in the first proposition tree, associate, with the at least one node, a word having a relationship to the at least one node to form a first augmented proposition tree. | 6. The system of claim 1 , further comprising: an augmentation module configured to, for at least one node in the first proposition tree, associate, with the at least one node, a word having a relationship to the at least one node to form a first augmented proposition tree. 16. The system of claim 6 , wherein the second proposition tree comprises an augmented proposition tree. | 0.892562 |
9,666,184 | 8 | 12 | 8. An apparatus for training a language model, the apparatus comprising: a processor configured to convert training data into error-containing training data, and train the neutral network language model using the error-containing training data, wherein the processor is configured to select a word to be replaced with an erroneous word from words in the training data, and generate the error-containing training data by replacing the selected word with the erroneous word, wherein the neural network language model is used to estimate a connection relationship between words, wherein the processor is configured to randomly select the word from the words in the training data, wherein the processor is configured to use the trained language model to convert a speech into output data. | 8. An apparatus for training a language model, the apparatus comprising: a processor configured to convert training data into error-containing training data, and train the neutral network language model using the error-containing training data, wherein the processor is configured to select a word to be replaced with an erroneous word from words in the training data, and generate the error-containing training data by replacing the selected word with the erroneous word, wherein the neural network language model is used to estimate a connection relationship between words, wherein the processor is configured to randomly select the word from the words in the training data, wherein the processor is configured to use the trained language model to convert a speech into output data. 12. The apparatus of claim 8 , wherein the processor is configured to use the trained language model to convert a speech received from a microphone into output data. | 0.738924 |
8,326,622 | 15 | 21 | 15. A computer program medium having program code stored therein, said medium not being a signal, said program code configured to be executed by processor of a computer system to implement a method for filling out a form from a dialog, said method comprising: said processor providing a dialog having elements relevant for filing out said form; said processor providing a list of named entities; said processor separating said elements from said dialog using said list of named entities; said processor displaying the separated elements and said form on a computer screen display; and said processor transferring the separated elements to fill out said form on said computer screen display. | 15. A computer program medium having program code stored therein, said medium not being a signal, said program code configured to be executed by processor of a computer system to implement a method for filling out a form from a dialog, said method comprising: said processor providing a dialog having elements relevant for filing out said form; said processor providing a list of named entities; said processor separating said elements from said dialog using said list of named entities; said processor displaying the separated elements and said form on a computer screen display; and said processor transferring the separated elements to fill out said form on said computer screen display. 21. The computer program product of claim 15 , wherein the list of named entities consists of the named entities. | 0.802448 |
8,656,294 | 12 | 13 | 12. The method of claim 9 wherein copying and pasting the arbitrary text selected by the user from the selected user document into the text composition area comprises automatically copying and pasting the arbitrary text from the selected user document into the text composition area responsive to detecting a touch and release action performed by the user. | 12. The method of claim 9 wherein copying and pasting the arbitrary text selected by the user from the selected user document into the text composition area comprises automatically copying and pasting the arbitrary text from the selected user document into the text composition area responsive to detecting a touch and release action performed by the user. 13. The method of claim 12 wherein automatically copying and pasting the arbitrary text comprises automatically copying the arbitrary text from the selected user document into memory responsive to the user touching the arbitrary text. | 0.5 |
7,930,179 | 8 | 9 | 8. A system as defined in claim 2 , wherein each estimated segment is initially in a separate group of estimated segments, wherein the fourth module further: models each estimated segment by a low-order Gaussian mixture model; generates table of pairwise distances using the low-order Gaussian mixture models, wherein the table of pairwise distances includes a distance between each estimated segment and every other estimated segment; and merges at least two groups of estimated segments to produce a new group of estimated segments such that a merger of the at least two groups of estimated segments produces a smallest increase in the distance. | 8. A system as defined in claim 2 , wherein each estimated segment is initially in a separate group of estimated segments, wherein the fourth module further: models each estimated segment by a low-order Gaussian mixture model; generates table of pairwise distances using the low-order Gaussian mixture models, wherein the table of pairwise distances includes a distance between each estimated segment and every other estimated segment; and merges at least two groups of estimated segments to produce a new group of estimated segments such that a merger of the at least two groups of estimated segments produces a smallest increase in the distance. 9. A system as defined in claim 8 , further comprising a fifth module configured to merge new groups of estimated segments until all estimated segments are merged into a final group. | 0.77193 |
9,183,194 | 11 | 12 | 11. A method comprising: identifying a first term in a document structure instance matching a first permissible term in a glossary; identifying an attribute requirement assignable to the first permissible term, the attribute requirement identified by an attribute phrase; analyzing, with a processor, the document structure instance to find a target phrase in the document structure instance that matches the attribute phrase; determining that the document structure instance satisfies the attribute requirement in response to identifying the matching target phrase in said document structure instance; and generating an attribute report identifying whether the attribute requirement for the first permissible term has been satisfied. | 11. A method comprising: identifying a first term in a document structure instance matching a first permissible term in a glossary; identifying an attribute requirement assignable to the first permissible term, the attribute requirement identified by an attribute phrase; analyzing, with a processor, the document structure instance to find a target phrase in the document structure instance that matches the attribute phrase; determining that the document structure instance satisfies the attribute requirement in response to identifying the matching target phrase in said document structure instance; and generating an attribute report identifying whether the attribute requirement for the first permissible term has been satisfied. 12. The method of claim 11 , where the glossary includes an activatable element indicating whether the document structure instance must satisfy the attribute requirement. | 0.760563 |
8,959,167 | 10 | 14 | 10. One or more computer-readable non-transitory storage media embodying software that is operable when executed to: provide an electronic document; receive an initial set of designated recipients for the electronic document from a user; evaluate content of the electronic document to identify at least one topic associated with the content; compare data associated with at least one recipient in the initial set to data associated with one or more other individuals to identify one or more other individual with characteristics that match or overlap with the at least one recipient; suggest the identified individuals as an additional recipient for the electronic document; and form a final set of designated recipients. | 10. One or more computer-readable non-transitory storage media embodying software that is operable when executed to: provide an electronic document; receive an initial set of designated recipients for the electronic document from a user; evaluate content of the electronic document to identify at least one topic associated with the content; compare data associated with at least one recipient in the initial set to data associated with one or more other individuals to identify one or more other individual with characteristics that match or overlap with the at least one recipient; suggest the identified individuals as an additional recipient for the electronic document; and form a final set of designated recipients. 14. The media of claim 10 , wherein a first set of the identified individuals determined to be correlated above a first specified threshold value with the initial set of designated recipients. | 0.555556 |
7,783,644 | 8 | 11 | 8. A computer program product stored on a non-transitory computer-readable storage medium having executable computer program instructions for presenting entities mentioned in books, comprising: an entity importance engine for assigning query-independent importance scores to entities mentioned by books in a corpus, the entity importance engine comprising a library classification module for determining whether library classification data mention an entity in a book and calculating an importance score for the entity responsive at least in part to the library classification data, wherein the importance scores of entities mentioned in the library classification data are elevated relative to importance scores of entities not mentioned in the library classification data; a search module for receiving a search query from a requestor and identifying a list of a plurality of books in the corpus that at least partially satisfy the query, and ranking the books in the list in an order based at least in part on the query-independent importance scores assigned to entities mentioned by the books; and a presentation module for presenting the plurality of books to the requestor in the ranked order. | 8. A computer program product stored on a non-transitory computer-readable storage medium having executable computer program instructions for presenting entities mentioned in books, comprising: an entity importance engine for assigning query-independent importance scores to entities mentioned by books in a corpus, the entity importance engine comprising a library classification module for determining whether library classification data mention an entity in a book and calculating an importance score for the entity responsive at least in part to the library classification data, wherein the importance scores of entities mentioned in the library classification data are elevated relative to importance scores of entities not mentioned in the library classification data; a search module for receiving a search query from a requestor and identifying a list of a plurality of books in the corpus that at least partially satisfy the query, and ranking the books in the list in an order based at least in part on the query-independent importance scores assigned to entities mentioned by the books; and a presentation module for presenting the plurality of books to the requestor in the ranked order. 11. The computer program product of claim 8 , wherein the entity importance engine comprises: a ranking module for calculating final importance scores as weighted sums of individual importance scores assigned to the entities and ranking the entities in order of importance responsive to the entities' final importance scores. | 0.892597 |
8,000,538 | 15 | 29 | 15. A method for performing classification through generative models of features occurring in an image, comprising: assigning each of a plurality of training images to one of a plurality of image categories; identifying features occurring in each training image; determining category-conditional probabilities of the features for each of the training images for their respective image categories; maintaining the category-conditional probability distributions of features with one such category-conditional probability distribution assigned to each of the image categories; retrieving an unclassified image and identifying the features occurring in the unclassified image; representing each of the identified features as an element in a feature list having a variable length, each element comprising a value in a chosen space of features that comprises one or more dimensions and the value comprising measurements along each of the dimensions being either continuous or discrete valued; evaluating the identified features against the category-conditional probability distributions for each of the image categories; assigning the unclassified image to one image category by maximizing the category-conditional likelihood of the category-conditional probability distribution of the identified features; and processing the unclassified image based on the one image category by converting the unclassified image. | 15. A method for performing classification through generative models of features occurring in an image, comprising: assigning each of a plurality of training images to one of a plurality of image categories; identifying features occurring in each training image; determining category-conditional probabilities of the features for each of the training images for their respective image categories; maintaining the category-conditional probability distributions of features with one such category-conditional probability distribution assigned to each of the image categories; retrieving an unclassified image and identifying the features occurring in the unclassified image; representing each of the identified features as an element in a feature list having a variable length, each element comprising a value in a chosen space of features that comprises one or more dimensions and the value comprising measurements along each of the dimensions being either continuous or discrete valued; evaluating the identified features against the category-conditional probability distributions for each of the image categories; assigning the unclassified image to one image category by maximizing the category-conditional likelihood of the category-conditional probability distribution of the identified features; and processing the unclassified image based on the one image category by converting the unclassified image. 29. A computer-readable storage medium holding code for performing the method according to claim 15 . | 0.898594 |
9,336,184 | 18 | 19 | 18. The computer-readable storage medium of claim 14 , wherein the method further comprises: receiving a user input identifying a deployment environment, the deployment environment comprising a plurality of computing devices; and converting the user input defining the interactive document into a plurality of executable components, each of the executable components configured for execution on a computing device of the plurality of computing devices. | 18. The computer-readable storage medium of claim 14 , wherein the method further comprises: receiving a user input identifying a deployment environment, the deployment environment comprising a plurality of computing devices; and converting the user input defining the interactive document into a plurality of executable components, each of the executable components configured for execution on a computing device of the plurality of computing devices. 19. The computer-readable storage medium of claim 18 , wherein: each executable component in a first portion of the executable components pulls data from another executable component; and each executable component in a second portion of the executable components pushes data to another executable component. | 0.5 |
9,607,436 | 1 | 13 | 1. A system to display augmented data, comprising: a processor; and a memory communicatively coupled to the processor, the memory bearing processor instructions that, when executed by the processor, cause the system to at least: determine augmentation data based on a context associated with a user device, the augmentation data comprising a plurality of augmentations, each of the plurality of augmentations associated with one of a plurality of physical venues including a certain physical venue, and wherein the context includes information regarding the user's environment; generate one or more clusters, each cluster of the one or more clusters comprising a subset of the plurality of augmentations, wherein each cluster of the one or more clusters represents one of the plurality of physical venues; grouping each of the plurality of augmentations into one of the one or more clusters based on a respective location of the plurality of physical venues; determine rendering formats for each of the one or more clusters, wherein the rendering formats determine at least a look of conceptual representations of the one or more clusters, wherein the look of the conceptual representation of a cluster is based on at least a first property of the subset of the plurality of augmentations grouped into the cluster, and wherein the conceptual representation is different from individual augmentations within the cluster, and wherein a respective rendering format for a certain cluster of the one or more clusters associated with the certain physical venue is based on the subset of the plurality of augmentations associated with the certain physical venue, and wherein the certain cluster of the one or more clusters comprises at least one lower-level cluster, wherein the rendering formats for the at least one lower-level cluster is based on an at least one second property of a second subset of the subset of the plurality of augmentations. | 1. A system to display augmented data, comprising: a processor; and a memory communicatively coupled to the processor, the memory bearing processor instructions that, when executed by the processor, cause the system to at least: determine augmentation data based on a context associated with a user device, the augmentation data comprising a plurality of augmentations, each of the plurality of augmentations associated with one of a plurality of physical venues including a certain physical venue, and wherein the context includes information regarding the user's environment; generate one or more clusters, each cluster of the one or more clusters comprising a subset of the plurality of augmentations, wherein each cluster of the one or more clusters represents one of the plurality of physical venues; grouping each of the plurality of augmentations into one of the one or more clusters based on a respective location of the plurality of physical venues; determine rendering formats for each of the one or more clusters, wherein the rendering formats determine at least a look of conceptual representations of the one or more clusters, wherein the look of the conceptual representation of a cluster is based on at least a first property of the subset of the plurality of augmentations grouped into the cluster, and wherein the conceptual representation is different from individual augmentations within the cluster, and wherein a respective rendering format for a certain cluster of the one or more clusters associated with the certain physical venue is based on the subset of the plurality of augmentations associated with the certain physical venue, and wherein the certain cluster of the one or more clusters comprises at least one lower-level cluster, wherein the rendering formats for the at least one lower-level cluster is based on an at least one second property of a second subset of the subset of the plurality of augmentations. 13. The system of claim 1 , further comprising processor instructions that, when executed, cause the system to render the certain cluster of the one or more clusters as an exemplar based on the respective rendering format; and merge the exemplar of the certain cluster with an image of a scene to generate a virtual image, wherein the exemplar includes avatars based on the subset of the plurality of augmentations. | 0.5 |
9,584,662 | 1 | 2 | 1. A method comprising: converting, via a processor, a call flow into a context free grammar notation; converting the context free grammar notation into a finite state machine; generating test dialogs associated with the call flow according to paths through the finite state machine; extracting key data from a dialog call detail record from a dialog in the test dialogs; transmitting, to the finite state machine, the key data; and determining, based on the key data being accepted by the finite state machine, that the dialog is a valid dialog for the call flow. | 1. A method comprising: converting, via a processor, a call flow into a context free grammar notation; converting the context free grammar notation into a finite state machine; generating test dialogs associated with the call flow according to paths through the finite state machine; extracting key data from a dialog call detail record from a dialog in the test dialogs; transmitting, to the finite state machine, the key data; and determining, based on the key data being accepted by the finite state machine, that the dialog is a valid dialog for the call flow. 2. The method of claim 1 , wherein the dialog call detail record comprises a prompt issued to a user and a response from the user. | 0.575163 |
8,914,769 | 1 | 3 | 1. A system for generating source code to enable communication between a server defined according to a first programming language and a client defined according to a second programming language, the system comprising: a code generator, implemented by a processor, operable to identify a server data structure defined according to the first programming language, to determine types of the data structure that are not accessible via a runtime conversion library for communications between the server and the client, and to generate a revised data structure in the first programming language comprising types that are accessible via the runtime conversion library and that may be used to manipulate the inaccessible types; the code generator further operable to generate source code in the second programming language for the client to access the revised data structure via the runtime conversion library, the source code correlating types of the revised data structure to the inaccessible types of the original data structure. | 1. A system for generating source code to enable communication between a server defined according to a first programming language and a client defined according to a second programming language, the system comprising: a code generator, implemented by a processor, operable to identify a server data structure defined according to the first programming language, to determine types of the data structure that are not accessible via a runtime conversion library for communications between the server and the client, and to generate a revised data structure in the first programming language comprising types that are accessible via the runtime conversion library and that may be used to manipulate the inaccessible types; the code generator further operable to generate source code in the second programming language for the client to access the revised data structure via the runtime conversion library, the source code correlating types of the revised data structure to the inaccessible types of the original data structure. 3. The system of claim 1 wherein: the code generator is further operable to generate an interface for accessing the original data structure via the revised data structure, the interface comprising source code in the first programming language that implements the revised data structure and further correlates the accessible types of the revised data structure with the inaccessible types of the original data structure. | 0.5 |
9,430,829 | 13 | 14 | 13. The non-transitory computer-readable storage medium of claim 12 , the method comprising extracting the set of intensity features from a set of channels of the candidate mitosis patch, the set of channels including a blue-ratio channel, a red channel, a blue channel, a green channel, an L channel in LAB color space, a V channel in CIE 1976 (L*, u*, v*) (LUV) color space, or an L channel in LUV color space, and where the set of intensity features includes mean intensity, median intensity, variance, maximum/minimum ratio, range, interquartile range, kurtosis, or skewness. | 13. The non-transitory computer-readable storage medium of claim 12 , the method comprising extracting the set of intensity features from a set of channels of the candidate mitosis patch, the set of channels including a blue-ratio channel, a red channel, a blue channel, a green channel, an L channel in LAB color space, a V channel in CIE 1976 (L*, u*, v*) (LUV) color space, or an L channel in LUV color space, and where the set of intensity features includes mean intensity, median intensity, variance, maximum/minimum ratio, range, interquartile range, kurtosis, or skewness. 14. The non-transitory computer-readable storage medium of claim 13 , the method comprising extracting the set of texture features from a set of channels of the candidate mitosis patch, the set of channels including a blue-ratio channel, a red channel, a blue channel, a green channel, an L channel in LAB color space, a V channel in CIE 1976 (L*, u*, v*) (LUV) color space, or an L channel in LUV color space, where the set of texture features includes a subset of concurrence features and a subset of run-length features, where the subset of concurrence features includes the mean and standard deviation of 13 Haralick gray-level concurrence features obtained from the candidate mitosis patch at four orientations, and where the subset of run-length features includes the mean and standard deviation of a set of gray-level run-length matrices, where the set of gray-level run-length matrices correspond to four orientations. | 0.5 |
9,026,542 | 10 | 11 | 10. A method for generating feature vectors of documents in different languages, the method comprising: receiving at a processing unit a document and identifying the language of the document as one of a base language or a second language; selecting a corresponding tokenizer based on the identified language to parse the received document and produce a feature vector of the received document, the tokenizer selected from a plurality of tokenizers stored in a memory unit, each tokenizer of the plurality of tokenizers associated with a language and a respective keyword set of a plurality of keyword sets stored in a keyword repository of the memory unit; parsing the received document using the selected tokenizer to identify keywords occurring in the received document, the keywords stored in a keyword set associated with the language of the selected tokenizer and an identifier (ID) of a corresponding keyword in a base language keyword set, wherein each respective ID is unique for each keyword of the base language keyword set; and generating a feature vector from a plurality of ID:score pairs, each pair associating a score with an ID of a keyword in the associated keyword set occurring in the document, the score based on the frequency of occurrence of the ID corresponding to the keyword in the document and a relevance weighting associated with the keyword, wherein the relevance weighting is based on a frequency of occurrence of the keyword in a set of previously collected documents, the feature vector providing scores associated with keywords defined in a base language for use by a profiler for generating or updating a user profile defining user preferences. | 10. A method for generating feature vectors of documents in different languages, the method comprising: receiving at a processing unit a document and identifying the language of the document as one of a base language or a second language; selecting a corresponding tokenizer based on the identified language to parse the received document and produce a feature vector of the received document, the tokenizer selected from a plurality of tokenizers stored in a memory unit, each tokenizer of the plurality of tokenizers associated with a language and a respective keyword set of a plurality of keyword sets stored in a keyword repository of the memory unit; parsing the received document using the selected tokenizer to identify keywords occurring in the received document, the keywords stored in a keyword set associated with the language of the selected tokenizer and an identifier (ID) of a corresponding keyword in a base language keyword set, wherein each respective ID is unique for each keyword of the base language keyword set; and generating a feature vector from a plurality of ID:score pairs, each pair associating a score with an ID of a keyword in the associated keyword set occurring in the document, the score based on the frequency of occurrence of the ID corresponding to the keyword in the document and a relevance weighting associated with the keyword, wherein the relevance weighting is based on a frequency of occurrence of the keyword in a set of previously collected documents, the feature vector providing scores associated with keywords defined in a base language for use by a profiler for generating or updating a user profile defining user preferences. 11. The method of claim 10 , wherein parsing the received document further comprises identifying words in the received document according to grammar rules of the language associated with the parser, the identified words compared to the keywords from the keyword set associated with the selected tokenizer. | 0.647806 |
8,190,990 | 7 | 8 | 7. The method of claim 1 further comprising: informing the user associated with the electronic device of one or more additional annotations collections being available at the annotations repository system, the one or more additional annotations collections having been authored by corresponding one or more other authors different from the user associated with the electronic device, and being associated with the webpage, each of the one or more additional annotations collections including one or more annotations relating to corresponding one or more portions of webpage content of the webpage; receiving, from the user associated with the electronic device in response to said informing, a request to access an additional annotations collection from among the additional annotations collections; in response to said receiving, from the user, of the request to access the additional annotations collection, requesting, by the electronic device from the annotations repository system, the additional annotations collection; receiving, by the electronic device, a response from the annotations repository system including the additional annotations collection; and concurrently displaying, by the electronic device, the received current instance of the webpage, the received additional annotations collections and the initially received annotations collection, such that the one or more annotations included in the initially received annotations collection and the one or more annotations included in the received additional annotations collection are overlaid on the corresponding portions of the webpage content of the received current instance of the webpage. | 7. The method of claim 1 further comprising: informing the user associated with the electronic device of one or more additional annotations collections being available at the annotations repository system, the one or more additional annotations collections having been authored by corresponding one or more other authors different from the user associated with the electronic device, and being associated with the webpage, each of the one or more additional annotations collections including one or more annotations relating to corresponding one or more portions of webpage content of the webpage; receiving, from the user associated with the electronic device in response to said informing, a request to access an additional annotations collection from among the additional annotations collections; in response to said receiving, from the user, of the request to access the additional annotations collection, requesting, by the electronic device from the annotations repository system, the additional annotations collection; receiving, by the electronic device, a response from the annotations repository system including the additional annotations collection; and concurrently displaying, by the electronic device, the received current instance of the webpage, the received additional annotations collections and the initially received annotations collection, such that the one or more annotations included in the initially received annotations collection and the one or more annotations included in the received additional annotations collection are overlaid on the corresponding portions of the webpage content of the received current instance of the webpage. 8. The method of claim 7 further comprising: receiving, from the user associated with the electronic device in response to said informing, another request to access another additional annotations collection from among the additional annotations collections; in response to said receiving, from the user, of the other request to access the other additional annotations collection, requesting, by the electronic device from the annotations repository system, the other additional annotations collection; and causing the electronic device to issue an alert if a permission to access the other additional annotations collection at the annotations repository system is denied, the permission being included in the other additional annotations collection. | 0.5 |
9,075,870 | 11 | 15 | 11. A method for detecting and tracing related topics and competition topics for a target topic, which is executed by a processor to control one or more processor-executable units, the method comprising: recognizing, by a processor, a type of the target topic to detect and trace related topics appropriate to the target topic based on the properties of topic templates; filtering association words of the target topic based on the properties of the topic templates to extract competition topics of the target topic; searching the topic templates for the extracted competition topics and topic templates for the target topic to provide topic tracing results; and ranking topics that are related to the target topic and that become issues among the association words of the target topic, wherein the competition topics are topics which compete with the target topic, wherein the related topics are displayed depending on time and importance. | 11. A method for detecting and tracing related topics and competition topics for a target topic, which is executed by a processor to control one or more processor-executable units, the method comprising: recognizing, by a processor, a type of the target topic to detect and trace related topics appropriate to the target topic based on the properties of topic templates; filtering association words of the target topic based on the properties of the topic templates to extract competition topics of the target topic; searching the topic templates for the extracted competition topics and topic templates for the target topic to provide topic tracing results; and ranking topics that are related to the target topic and that become issues among the association words of the target topic, wherein the competition topics are topics which compete with the target topic, wherein the related topics are displayed depending on time and importance. 15. The method of claim 11 , wherein said searching of all the topic templates comprises: searching association words of the target topic; filtering out topics that are not included in the competition topics of the target topic from among the association word search results; ranking the filtered association words using frequency and source reliability measurements to select a first ranked competition topic; searching the topic templates to find related topics to the first ranked competition topic; searching the topic templates to find related topics to the target topic; and providing search results for the first ranked competition topic and search results for the target topic through a user interface. | 0.5 |
8,037,084 | 1 | 7 | 1. A method of transcoding a web page of a web site, the method comprising: receiving a request from a client device for the web page of the web site; retrieving a signature schema for the web site, said signature schema comprising one or more instructions to identify a web page family for the web page and to extract a subset of data from the web page using one or more signatures previously identified within at least one web page of a same web page family of the web site; obtaining the web page; and applying the one or more instructions to the web page for presentation of the web page by a browser of the client device; wherein at least some of the instructions include one or more directional references relative to the signatures to locate and extract some of the subset of data within the web page. | 1. A method of transcoding a web page of a web site, the method comprising: receiving a request from a client device for the web page of the web site; retrieving a signature schema for the web site, said signature schema comprising one or more instructions to identify a web page family for the web page and to extract a subset of data from the web page using one or more signatures previously identified within at least one web page of a same web page family of the web site; obtaining the web page; and applying the one or more instructions to the web page for presentation of the web page by a browser of the client device; wherein at least some of the instructions include one or more directional references relative to the signatures to locate and extract some of the subset of data within the web page. 7. The method of claim 1 wherein the one or more instructions are interpreted by a transcoding engine component of a computing device configured for transcoding web pages to a target format. | 0.736842 |
9,940,933 | 28 | 30 | 28. The apparatus of claim 26 , wherein, for the second recognition, the processor is configured to obtain the candidate words based on the target word, and select the one or more of sampled candidate words for improving the accuracy of the sentence. | 28. The apparatus of claim 26 , wherein, for the second recognition, the processor is configured to obtain the candidate words based on the target word, and select the one or more of sampled candidate words for improving the accuracy of the sentence. 30. The apparatus of claim 28 , wherein the second linguistic model is a recurrent neural network linguistic model. | 0.826284 |
7,512,533 | 7 | 11 | 7. An apparatus for creating Chinese language data, comprising: means for generating identifiers for a plurality of Chinese Pinyin syllables; means for storing the identifier and an array index for each of the plurality of Chinese Pinyin syllables in an array of identifiers; means for generating a plurality of Hanzi character candidate lists, each of the plurality of Hanzi character candidate lists comprising a plurality of Hanzi character candidates that are associated with one of the plurality of Chinese Pinyin syllables, and each Hanzi character candidate having and a candidate index in the Hanzi character candidate list; and means for generating and storing in a computer-readable memory data records for a plurality of words having multiple Pinyin syllables, the data records for each of the plurality of words comprising a key and a value, wherein each key comprises the array index and tone information for each of the multiple Pinyin syllables in one of the plurality of words, and each value comprises a candidate index to identify a Hanzi character candidate for each of the multiple Pinyin syllables in one of the plurality of words. | 7. An apparatus for creating Chinese language data, comprising: means for generating identifiers for a plurality of Chinese Pinyin syllables; means for storing the identifier and an array index for each of the plurality of Chinese Pinyin syllables in an array of identifiers; means for generating a plurality of Hanzi character candidate lists, each of the plurality of Hanzi character candidate lists comprising a plurality of Hanzi character candidates that are associated with one of the plurality of Chinese Pinyin syllables, and each Hanzi character candidate having and a candidate index in the Hanzi character candidate list; and means for generating and storing in a computer-readable memory data records for a plurality of words having multiple Pinyin syllables, the data records for each of the plurality of words comprising a key and a value, wherein each key comprises the array index and tone information for each of the multiple Pinyin syllables in one of the plurality of words, and each value comprises a candidate index to identify a Hanzi character candidate for each of the multiple Pinyin syllables in one of the plurality of words. 11. The apparatus of claim 7 , further comprising means for storing the data records in one of a plurality of data record arrays, wherein the data record arrays store data records corresponding to words having a predetermined number of Pinyin syllables. | 0.5 |
7,529,753 | 5 | 6 | 5. The computer accessible storage hardware of claim 1 , wherein a single nonblocking control thread drives the decoders and the application according to message events in an event queue. | 5. The computer accessible storage hardware of claim 1 , wherein a single nonblocking control thread drives the decoders and the application according to message events in an event queue. 6. The computer accessible storage hardware of claim 5 , wherein, to drive the decoders, the nonblocking control thread communicates function calls to the decoders comprising buffers pointing to frames of database messages in memory at the first network location without communicating the frames of the database messages to the decoders or assembling the database messages and communicating the database messages to the decoders. | 0.5 |
8,577,726 | 5 | 7 | 5. The method of claim 2 wherein the financial benefit is generated from purchases of items within a category during a session initiated with the selection of an advertisement for the keyword and the determining of the bid amount includes accumulating combinations for each category of the financial benefit for that category and the category-specific advertising expense factor for that category and normalizing the accumulated combinations by number of sessions resulting in the financial benefit. | 5. The method of claim 2 wherein the financial benefit is generated from purchases of items within a category during a session initiated with the selection of an advertisement for the keyword and the determining of the bid amount includes accumulating combinations for each category of the financial benefit for that category and the category-specific advertising expense factor for that category and normalizing the accumulated combinations by number of sessions resulting in the financial benefit. 7. The method of claim 5 wherein the determining of the bid amount includes further multiplying the combination for a category by a category-specific forecast conversion rate before accumulating the combinations. | 0.5 |
8,244,539 | 1 | 4 | 1. A method, comprising: performing by one or more computers: receiving an indication of a request for content; identifying the requested content, wherein the requested content includes first audio data having a first set of phonemes; matching one or more of a plurality of advertising files to the requested content, wherein the one or more of the plurality of advertising files includes second audio data having a second set of phonemes, and wherein the matching is based, at least in part, upon a comparison between the first and second sets of phonemes; and causing the one or more of the plurality of advertising files to be delivered in response to the request. | 1. A method, comprising: performing by one or more computers: receiving an indication of a request for content; identifying the requested content, wherein the requested content includes first audio data having a first set of phonemes; matching one or more of a plurality of advertising files to the requested content, wherein the one or more of the plurality of advertising files includes second audio data having a second set of phonemes, and wherein the matching is based, at least in part, upon a comparison between the first and second sets of phonemes; and causing the one or more of the plurality of advertising files to be delivered in response to the request. 4. The method of claim 1 , wherein the requested content is an audio file that includes the first audio data. | 0.652866 |
9,715,542 | 23 | 29 | 23. A system for returning a search results list in response to a search query, the system comprising: a tag database for storing user-entered tags associated with objects, wherein one or more objects is associated with tags as a result of user input and each tag comprises one or more tag terms, each tag term comprising text, and wherein each association of an object with a tag comprises a tag object pair, and each term of a tag comprises a tag term pair; a storage device containing computer-executable instructions comprising a tag analyzer coupled to the tag database, wherein the tag analyzer is programmed to use the associations of tags with objects to compute a relevance score for each of the objects for the search query, wherein the relevance score for a tag object pair is computed by determining a tag term score indicating a degree of relevance between the term and the object, for user-entered strings of one and more terms in a tag, and combining the tag term scores from the term object pairs for each tag term in the tag, wherein a tag term score for an object X and a term A is a function of a combination comprising a total number of different terms in the tag database storing the tags, a total number of tags present in the tag database, a frequency with which the term A is present in the tag database, a number of different terms with which the object X has been tagged, a total number of tags associated with the object X, and a number of different objects that have been tagged with the term A; and a hardware-implemented search engine for receiving the search query and for presenting the results list in response to the search query, the results list comprising references to one or more of the objects, wherein the order of the multiple objects in the results list is influenced by the relevance scores. | 23. A system for returning a search results list in response to a search query, the system comprising: a tag database for storing user-entered tags associated with objects, wherein one or more objects is associated with tags as a result of user input and each tag comprises one or more tag terms, each tag term comprising text, and wherein each association of an object with a tag comprises a tag object pair, and each term of a tag comprises a tag term pair; a storage device containing computer-executable instructions comprising a tag analyzer coupled to the tag database, wherein the tag analyzer is programmed to use the associations of tags with objects to compute a relevance score for each of the objects for the search query, wherein the relevance score for a tag object pair is computed by determining a tag term score indicating a degree of relevance between the term and the object, for user-entered strings of one and more terms in a tag, and combining the tag term scores from the term object pairs for each tag term in the tag, wherein a tag term score for an object X and a term A is a function of a combination comprising a total number of different terms in the tag database storing the tags, a total number of tags present in the tag database, a frequency with which the term A is present in the tag database, a number of different terms with which the object X has been tagged, a total number of tags associated with the object X, and a number of different objects that have been tagged with the term A; and a hardware-implemented search engine for receiving the search query and for presenting the results list in response to the search query, the results list comprising references to one or more of the objects, wherein the order of the multiple objects in the results list is influenced by the relevance scores. 29. The system of claim 23 , wherein the relevance score between a search query containing terms and an object is determined from a number of tags that contain tag terms in the search query, a number of times that a tag term included in the search query is included in the tag database, a number of tags that have been associated with the object, a number of tag terms in the tag and in the search query that match, a number of times that the object has been bookmarked, a number of times that the object has been rated, or any combination of these. | 0.5 |
8,676,836 | 10 | 12 | 10. A computer system comprising a processor and a computer readable memory unit coupled to the processor, said computer readable memory unit containing instructions that when executed by the processor implement a method for searching a web service registry system by use of a search controller, said method comprising: said processor performing a first search of a service registry program product with a service name received by the search controller from a user of the web service registry system, wherein the web service registry system comprises a search module and the service registry program product, wherein the search module comprises the search controller, a name parser, a dictionary, and a name composer, and wherein the service registry program product comprises at least one service description searchable by a respectively associated service name; after said performing the first search, said processor determining that the received service name does not have a service description associated with the received service name in the service registry program product; said processor coordinating a second search of the service registry program product with a candidate service name by use of the search module, wherein the candidate service name is semantically and syntactically interchangeable with the received service name such that the candidate service name identifies the service description associated with the received service name within the service registry program product; and said processor discovering that the service description is associated with the candidate service name within the service registry program product and subsequently returning the discovered service description to the user, said coordinating comprising: sending the received service name to the name parser and subsequently receiving a component word list from the name parser, wherein the component word list comprises all words constituting the received service name; sending the component word list to the dictionary and subsequently receiving a respective synonym list for each word in the component word list from the dictionary, wherein the respective synonym list comprises at least one synonym of said each word in the component word list; sending the respective synonym list to the name composer and subsequently receiving the candidate service name from the name composer; and sending a second search request for the service description associated with the candidate service name to the service registry program product and subsequently receiving the service description in response to the second search request. | 10. A computer system comprising a processor and a computer readable memory unit coupled to the processor, said computer readable memory unit containing instructions that when executed by the processor implement a method for searching a web service registry system by use of a search controller, said method comprising: said processor performing a first search of a service registry program product with a service name received by the search controller from a user of the web service registry system, wherein the web service registry system comprises a search module and the service registry program product, wherein the search module comprises the search controller, a name parser, a dictionary, and a name composer, and wherein the service registry program product comprises at least one service description searchable by a respectively associated service name; after said performing the first search, said processor determining that the received service name does not have a service description associated with the received service name in the service registry program product; said processor coordinating a second search of the service registry program product with a candidate service name by use of the search module, wherein the candidate service name is semantically and syntactically interchangeable with the received service name such that the candidate service name identifies the service description associated with the received service name within the service registry program product; and said processor discovering that the service description is associated with the candidate service name within the service registry program product and subsequently returning the discovered service description to the user, said coordinating comprising: sending the received service name to the name parser and subsequently receiving a component word list from the name parser, wherein the component word list comprises all words constituting the received service name; sending the component word list to the dictionary and subsequently receiving a respective synonym list for each word in the component word list from the dictionary, wherein the respective synonym list comprises at least one synonym of said each word in the component word list; sending the respective synonym list to the name composer and subsequently receiving the candidate service name from the name composer; and sending a second search request for the service description associated with the candidate service name to the service registry program product and subsequently receiving the service description in response to the second search request. 12. The computer system of claim 10 , wherein the received service description is employed in the SOA business application that provides a service described in the received service description. | 0.908617 |
9,691,389 | 15 | 16 | 15. The method as claimed in claim 14 , wherein the method further includes: performing respectively, by a word detector, a detection on the at least one second speech segment of the one or more repeated new words and the first speech segment of the at least one preset word, and marking each of the at least one second speech segment and the first speech segment, thereby obtaining at least one speech segment marked as an unknown word and at least one speech segment marked as the preset word. | 15. The method as claimed in claim 14 , wherein the method further includes: performing respectively, by a word detector, a detection on the at least one second speech segment of the one or more repeated new words and the first speech segment of the at least one preset word, and marking each of the at least one second speech segment and the first speech segment, thereby obtaining at least one speech segment marked as an unknown word and at least one speech segment marked as the preset word. 16. The method as claimed in claim 15 , wherein the method further includes: performing, by a model trainer, a model training on the at least one speech segment marked as the unknown word, and obtain at least one new word model. | 0.5 |
8,682,989 | 1 | 3 | 1. A method for making document changes using electronic messages, comprising: creating an electronic message that includes a change made to a document that is viewable within a body of the electronic message, wherein the document is collaborated on by reviewers; sending the electronic message to at least a portion of the reviewers that includes the change made to the document within the body of the electronic message; receiving a reply to the electronic message that includes a received change made directly from within the electronic message without editing the document that is to be incorporated into the document; and after receiving the reply, automatically incorporating the received change into the document. | 1. A method for making document changes using electronic messages, comprising: creating an electronic message that includes a change made to a document that is viewable within a body of the electronic message, wherein the document is collaborated on by reviewers; sending the electronic message to at least a portion of the reviewers that includes the change made to the document within the body of the electronic message; receiving a reply to the electronic message that includes a received change made directly from within the electronic message without editing the document that is to be incorporated into the document; and after receiving the reply, automatically incorporating the received change into the document. 3. The method of claim 1 , further comprising accessing the document from a shared data location. | 0.850769 |
7,634,546 | 20 | 24 | 20. A computer system for enhancing communication within a community, the computer system comprising: a storage medium containing code instructions that when executed on a processor in the computer system provide: an application platform running an application that organizes a plurality of communications, said application further comprising: a database for storing said plurality of communications; an inherited parameters responsibility module for establishing a hierarchical structure for said plurality of communications and for distributing control of said hierarchical structure to a plurality of users within the community, through selection of inherited parameters comprising access parameters defining access by said plurality of users to said plurality of communications organized within said hierarchical structure and wherein said access parameters are selected from the group consisting of an inclusive access in which access to each of said stored communications in said hierarchical structure is allowed except where excluded by said inherited parameters and an exclusive access in which access to each of said stored communications in said hierarchical structure is allowed only where explicitly assigned; an input module for capturing said plurality of communications within said hierarchical structure sent by said plurality of users from a plurality of communication devices and storing at least a portion of said plurality of communications in relation to at least one of a plurality of topics that is user selected, wherein said plurality of communications comprises at least one link to a resource associated with said at least a portion of said plurality of communications that is stored, wherein said link is available for access by authorized users; a thread synchronization module for synchronizing said plurality of communications within said hierarchical structure; an initial priority-based content placement module for determining a priority assignment for an initial communication of said plurality of communications; an authorization module for authorizing each of said plurality of users to access a portion of said plurality of communications stored in said database to which each of said plurality of users have access rights based upon an access status and in conjunction with said inherited parameters responsibility module and wherein said access status is selected from the group consisting of an inclusive access in which access to each of said stored communications in said hierarchical structure is allowed and an exclusive access in which access to each of said stored communications in said hierarchical structure is allowed only where explicitly assigned; a response priority-based content placement module for determining a priority assignment for a response communication of said plurality of communications, wherein said priority assignment for a response communication is lower than said priority assignment for an initial communication; a reviewing module for presenting said synchronized plurality of communications in said hierarchical structure to said plurality of users for dynamic interaction enabled through further contributions of communications by said plurality of users, wherein said further contributions of communications are stored and accessed within said hierarchical structure in relation to said at least one of a plurality of topics that is user selected, wherein said further contributions are associated with at least one discussion thread comprising recorded communication under said at least one of a plurality of topics that is conducted between participating users of said plurality of users; and an output module for outputting a plurality of responses to said plurality of communications from said plurality of users to said plurality of communication devices. | 20. A computer system for enhancing communication within a community, the computer system comprising: a storage medium containing code instructions that when executed on a processor in the computer system provide: an application platform running an application that organizes a plurality of communications, said application further comprising: a database for storing said plurality of communications; an inherited parameters responsibility module for establishing a hierarchical structure for said plurality of communications and for distributing control of said hierarchical structure to a plurality of users within the community, through selection of inherited parameters comprising access parameters defining access by said plurality of users to said plurality of communications organized within said hierarchical structure and wherein said access parameters are selected from the group consisting of an inclusive access in which access to each of said stored communications in said hierarchical structure is allowed except where excluded by said inherited parameters and an exclusive access in which access to each of said stored communications in said hierarchical structure is allowed only where explicitly assigned; an input module for capturing said plurality of communications within said hierarchical structure sent by said plurality of users from a plurality of communication devices and storing at least a portion of said plurality of communications in relation to at least one of a plurality of topics that is user selected, wherein said plurality of communications comprises at least one link to a resource associated with said at least a portion of said plurality of communications that is stored, wherein said link is available for access by authorized users; a thread synchronization module for synchronizing said plurality of communications within said hierarchical structure; an initial priority-based content placement module for determining a priority assignment for an initial communication of said plurality of communications; an authorization module for authorizing each of said plurality of users to access a portion of said plurality of communications stored in said database to which each of said plurality of users have access rights based upon an access status and in conjunction with said inherited parameters responsibility module and wherein said access status is selected from the group consisting of an inclusive access in which access to each of said stored communications in said hierarchical structure is allowed and an exclusive access in which access to each of said stored communications in said hierarchical structure is allowed only where explicitly assigned; a response priority-based content placement module for determining a priority assignment for a response communication of said plurality of communications, wherein said priority assignment for a response communication is lower than said priority assignment for an initial communication; a reviewing module for presenting said synchronized plurality of communications in said hierarchical structure to said plurality of users for dynamic interaction enabled through further contributions of communications by said plurality of users, wherein said further contributions of communications are stored and accessed within said hierarchical structure in relation to said at least one of a plurality of topics that is user selected, wherein said further contributions are associated with at least one discussion thread comprising recorded communication under said at least one of a plurality of topics that is conducted between participating users of said plurality of users; and an output module for outputting a plurality of responses to said plurality of communications from said plurality of users to said plurality of communication devices. 24. A computer system for enhancing communication within a community according to claim 20 further comprising: a recording module accessible by said plurality of communication devices, wherein said recording module, after a user input is received in a one of said plurality of communication devices on a record option, queries said database causing said database to deliver to said one of said plurality of communication devices said hierarchical structure of said plurality of communications, and further wherein said recording module receives a user selection input of a topic within said hierarchical structure with which to associate a communication from said one of said plurality of communication devices, and further wherein said recording module records and stores in said database said communication sent from said one of said plurality of communication devices. | 0.604809 |
7,725,504 | 7 | 10 | 7. An apparatus for forming a structured diagram from an unstructured information source, wherein at least one artifact is formed in the structured diagram to represent at least one information element included in the unstructured information source, the information element being objects or interactive relations among the objects involved in the unstructured information source, the apparatus comprising: a receiving device for receiving a search item which is inputted by a user and represents an information element; a searching device for searching for contents related to the information elements represented by the search item in the unstructured information source based on the search item inputted by the user; a linkage creating device for creating a linkage between the corresponding artifact formed in the structured diagram and a position of the related content searched in the unstructured information source, for each information element; a linkage distribution computing device for computing the distribution of the linkages in the unstructured information source; and a warning generating device for generating warnings for the parts with few linkages or no linkage at all. | 7. An apparatus for forming a structured diagram from an unstructured information source, wherein at least one artifact is formed in the structured diagram to represent at least one information element included in the unstructured information source, the information element being objects or interactive relations among the objects involved in the unstructured information source, the apparatus comprising: a receiving device for receiving a search item which is inputted by a user and represents an information element; a searching device for searching for contents related to the information elements represented by the search item in the unstructured information source based on the search item inputted by the user; a linkage creating device for creating a linkage between the corresponding artifact formed in the structured diagram and a position of the related content searched in the unstructured information source, for each information element; a linkage distribution computing device for computing the distribution of the linkages in the unstructured information source; and a warning generating device for generating warnings for the parts with few linkages or no linkage at all. 10. The apparatus according to claim 7 , wherein the warning generating device comprises: a linkage distribution classifying device for classifying the respective parts in the unstructured information source into a plurality of levels based on the linkage distribution density of the respective parts; and a classified warning generating device for generating various levels of warnings for various parts based on different linkage distribution levels. | 0.653905 |
6,119,086 | 7 | 8 | 7. The speech coding system of claim 6, further comprising comparison means, responsive to the measures associated with the at least one phonetic token generated by the speech recognition means and the at least one phonetic token generated by the second speech transcribing means, the comparison means comparing the respective measures, for a given speech segment, and generating a comparison signal indicative of which measure is higher. | 7. The speech coding system of claim 6, further comprising comparison means, responsive to the measures associated with the at least one phonetic token generated by the speech recognition means and the at least one phonetic token generated by the second speech transcribing means, the comparison means comparing the respective measures, for a given speech segment, and generating a comparison signal indicative of which measure is higher. 8. The speech coding system of claim 7, further comprising combining means, responsive to the comparison signal and the at least one phonetic token generated by the speech recognition means and the at least one phonetic token generated by the second speech transcribing means, the combining means selecting, for the given speech segment, the phonetic token having the higher measure and combining phonetic tokens from other segments therewith. | 0.5 |
10,095,696 | 11 | 17 | 11. A method that generates recommendations of post-capture users to edit digital media content, the method comprising: obtaining contextual parameters of digital media content, the digital media content being associated with a content capture user and/or an end user, the contextual parameters defining one or more temporal attributes and/or spatial attributes associated with capture of the digital media content; receiving editing parameters selected by the content capture user and/or the end user, the editing parameters defining one or more editing attributes of an edited version of the digital media content to be created; obtaining post-capture user profiles, individual post-capture user profiles including expertise attributes associated with individual post-capture users, the expertise attributes including stated information and feedback information, the stated information being provided by the post-capture users themselves and the feedback information including information provided by one or more of content capture users and/or end users for whom the individual post-capture users have created edited versions of other digital media content; identifying a set of post-capture users as potential matches for creating the edited version of the digital media content based upon the contextual parameters, the editing parameters, and the one or more expertise attributes of the post-capture user profiles; and effectuate presentation of the set of post-capture users to the content capture user and/or the end user for selection by the content capture user and/or the end user of one of the post-capture users from the set of post-capture users to create the edited version of the digital media content. | 11. A method that generates recommendations of post-capture users to edit digital media content, the method comprising: obtaining contextual parameters of digital media content, the digital media content being associated with a content capture user and/or an end user, the contextual parameters defining one or more temporal attributes and/or spatial attributes associated with capture of the digital media content; receiving editing parameters selected by the content capture user and/or the end user, the editing parameters defining one or more editing attributes of an edited version of the digital media content to be created; obtaining post-capture user profiles, individual post-capture user profiles including expertise attributes associated with individual post-capture users, the expertise attributes including stated information and feedback information, the stated information being provided by the post-capture users themselves and the feedback information including information provided by one or more of content capture users and/or end users for whom the individual post-capture users have created edited versions of other digital media content; identifying a set of post-capture users as potential matches for creating the edited version of the digital media content based upon the contextual parameters, the editing parameters, and the one or more expertise attributes of the post-capture user profiles; and effectuate presentation of the set of post-capture users to the content capture user and/or the end user for selection by the content capture user and/or the end user of one of the post-capture users from the set of post-capture users to create the edited version of the digital media content. 17. The method of claim 11 , further comprising: receiving a selection of one of the post-capture users from the set of post-capture users to create the edited version of the digital media content. | 0.840615 |
8,423,351 | 21 | 30 | 21. A system for correcting one or more typed words on an electronic device, the system comprising: a text input device configured to receive multiple typed words; a language model builder configured to generate one or more candidate words for each one of the multiple typed words; a microphone configured to receive a single audio stream containing multiple spoken words that correspond to the multiple typed words or a portion of the multiple typed words; a speech recognizer configured to: translate the multiple spoken words into text using the one or more candidate words, wherein translation of the multiple spoken words comprises generation of a digital representation of each of the multiple spoken words; for each of the multiple spoken words, assign a confidence score to each of the corresponding one or more candidate words by comparing the digital representation of the spoken word to the corresponding one or more candidate words; and, for each of the multiple spoken words, select a candidate word from among the corresponding one or more candidate words based on the confidence score assigned to each of the corresponding one or more candidate words; and a text update manager configured to replace, using the text, one or more of the multiple typed words with the corresponding selected candidate word when the confidence score of the selected candidate word is above a predetermined threshold value. | 21. A system for correcting one or more typed words on an electronic device, the system comprising: a text input device configured to receive multiple typed words; a language model builder configured to generate one or more candidate words for each one of the multiple typed words; a microphone configured to receive a single audio stream containing multiple spoken words that correspond to the multiple typed words or a portion of the multiple typed words; a speech recognizer configured to: translate the multiple spoken words into text using the one or more candidate words, wherein translation of the multiple spoken words comprises generation of a digital representation of each of the multiple spoken words; for each of the multiple spoken words, assign a confidence score to each of the corresponding one or more candidate words by comparing the digital representation of the spoken word to the corresponding one or more candidate words; and, for each of the multiple spoken words, select a candidate word from among the corresponding one or more candidate words based on the confidence score assigned to each of the corresponding one or more candidate words; and a text update manager configured to replace, using the text, one or more of the multiple typed words with the corresponding selected candidate word when the confidence score of the selected candidate word is above a predetermined threshold value. 30. The system of claim 21 , wherein the text update manager is configured to display a correction in the one or more of the multiple typed words using the selected candidate word with the confidence score above the predetermined threshold value. | 0.583051 |
7,668,787 | 10 | 15 | 10. An apparatus having a central processing unit (CPU) and a memory coupled to said CPU comprising: a user interface logic configured to present a workspace window responsive to a relationship data structure that represents relationships between pieces of information; the user interface logic further configured to present a presentation set of an ordered set of text strings from an electronic document, said presentation set including one or more identified strings; a quick-click command invocation logic configured to receive a quick-click command invocation on said one or more identified strings from the user interface logic; a relationship space edit logic configured to modify said relationship data structure by adding an entity/relationship object to said relationship data structure responsive to said quick-click command invocation logic and said one or more identified strings; a detecting logic configured to detect a drag-and-drop operation dragging a first instance representation to a drop point; a combining logic configured to combine the first instance representation with a second instance representation, the second instance representation determined to be nearest to the drop point and within a threshold distance from the drop point, wherein the threshold distance is a multidimensional vector, a selection of strength of a relationship being responsive to weighted values of the multidimensional vector's elements, so that: if the nearest instance representation is an entity object, a new composite object is created that includes the entity object and an entity/relationship object represented by the dragged instance representation, and if the nearest instance representation is a first composite object, the entity/relationship object represented by the dragged instance representation is added to the composite object. | 10. An apparatus having a central processing unit (CPU) and a memory coupled to said CPU comprising: a user interface logic configured to present a workspace window responsive to a relationship data structure that represents relationships between pieces of information; the user interface logic further configured to present a presentation set of an ordered set of text strings from an electronic document, said presentation set including one or more identified strings; a quick-click command invocation logic configured to receive a quick-click command invocation on said one or more identified strings from the user interface logic; a relationship space edit logic configured to modify said relationship data structure by adding an entity/relationship object to said relationship data structure responsive to said quick-click command invocation logic and said one or more identified strings; a detecting logic configured to detect a drag-and-drop operation dragging a first instance representation to a drop point; a combining logic configured to combine the first instance representation with a second instance representation, the second instance representation determined to be nearest to the drop point and within a threshold distance from the drop point, wherein the threshold distance is a multidimensional vector, a selection of strength of a relationship being responsive to weighted values of the multidimensional vector's elements, so that: if the nearest instance representation is an entity object, a new composite object is created that includes the entity object and an entity/relationship object represented by the dragged instance representation, and if the nearest instance representation is a first composite object, the entity/relationship object represented by the dragged instance representation is added to the composite object. 15. The apparatus of claim 10 , further comprising: a rule logic configured to identify one or more identified strings within an ordered set of text strings from said electronic document, and wherein said entity/relationship object incorporates at least one of said one or more identified strings. | 0.5 |
10,021,161 | 1 | 7 | 1. A method for transmitting video data comprising: capturing a plurality of sets of graphical command tokens respectively renderable into a plurality of frames of video data; and responsive to determining that a length of a current set of graphical command tokens of the plurality of sets of graphical command tokens is different than a length of a previous set of the plurality of sets of graphical command tokens: determining a token prediction map that indicates, for each graphical command token of the current set of graphical command tokens, whether a similar graphical command token can be located in the previous set of graphical command tokens; and responsive to determining, based on the token prediction map, that the current set of graphical command tokens is sufficiently similar to the previous set of graphical command tokens, outputting, by a source device and to a sink device, a compressed version of the current set of graphical command tokens. | 1. A method for transmitting video data comprising: capturing a plurality of sets of graphical command tokens respectively renderable into a plurality of frames of video data; and responsive to determining that a length of a current set of graphical command tokens of the plurality of sets of graphical command tokens is different than a length of a previous set of the plurality of sets of graphical command tokens: determining a token prediction map that indicates, for each graphical command token of the current set of graphical command tokens, whether a similar graphical command token can be located in the previous set of graphical command tokens; and responsive to determining, based on the token prediction map, that the current set of graphical command tokens is sufficiently similar to the previous set of graphical command tokens, outputting, by a source device and to a sink device, a compressed version of the current set of graphical command tokens. 7. The method of claim 1 , further comprising: responsive to determining that a length of a second current set of graphical command tokens is the same as a length of a second previous set of graphical command tokens, outputting, by the source device and to the sink device, a compressed version of the second current set of graphical command tokens. | 0.816122 |
9,547,854 | 6 | 7 | 6. The system of claim 1 , wherein the operations further comprise receiving a second user gesture input through the user interface that indicates that the user would like to view available funding sources for a transaction. | 6. The system of claim 1 , wherein the operations further comprise receiving a second user gesture input through the user interface that indicates that the user would like to view available funding sources for a transaction. 7. The system of claim 6 , wherein the operations further comprise displaying the available funding sources on a third page of the user interface. | 0.5 |
9,666,184 | 1 | 6 | 1. A method of training a language model, the method comprising: converting, using a processor, training data into error-containing training data; and training a neural network language model using the error-containing training data wherein the converting comprises selecting a word to be replaced with an erroneous word from words in the training data, and generating the error-containing training data by replacing the selected word with the erroneous word, wherein the neural network language model is used to estimate a connection relationship between words, wherein the selecting comprises randomly selecting the word from the words in the training data, wherein the processor is configured to use the trained language model to convert a speech into output data. | 1. A method of training a language model, the method comprising: converting, using a processor, training data into error-containing training data; and training a neural network language model using the error-containing training data wherein the converting comprises selecting a word to be replaced with an erroneous word from words in the training data, and generating the error-containing training data by replacing the selected word with the erroneous word, wherein the neural network language model is used to estimate a connection relationship between words, wherein the selecting comprises randomly selecting the word from the words in the training data, wherein the processor is configured to use the trained language model to convert a speech into output data. 6. The method of claim 1 , wherein the neural network language model generates a probability value. | 0.703593 |
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