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1. A method of automatic, computer based identification of a significant phrase in a document, the method comprising: storing the document, a threshold score, a verbosity setting, and a significant phrases data structure in a memory; accessing the memory to read a sequence of words from the document; determining by a processing unit a score for each word in the sequence based on the length of each word; operating the processing unit to compare the score for each word in the sequence against the threshold score; adding the sequence of words as a significant phrase to the significant phrase data structure if: the number of words in the sequence that have the score greater than the threshold score equals or exceeds a predetermined number and the number of words in the sequence satisfies the verbosity setting; retrieving a sentence from the document, in the memory if the sentence contains a significant phrase stored in the significant phrases data structure; and operating the processing unit to search an abstract of the document to determine whether the sentence is included in the abstract. | 1. A method of automatic, computer based identification of a significant phrase in a document, the method comprising: storing the document, a threshold score, a verbosity setting, and a significant phrases data structure in a memory; accessing the memory to read a sequence of words from the document; determining by a processing unit a score for each word in the sequence based on the length of each word; operating the processing unit to compare the score for each word in the sequence against the threshold score; adding the sequence of words as a significant phrase to the significant phrase data structure if: the number of words in the sequence that have the score greater than the threshold score equals or exceeds a predetermined number and the number of words in the sequence satisfies the verbosity setting; retrieving a sentence from the document, in the memory if the sentence contains a significant phrase stored in the significant phrases data structure; and operating the processing unit to search an abstract of the document to determine whether the sentence is included in the abstract. 6. The method of claim 1 , wherein the score for the word is the length of the word plus the number of capitalized letters in the word. | 0.611265 |
6. The teaching method of claim 1 wherein the second displaying step includes the step of sequentially displaying said chosen words at said main portion. | 6. The teaching method of claim 1 wherein the second displaying step includes the step of sequentially displaying said chosen words at said main portion. 9. The teaching method of claim 6 further comprising the step of retaining said sequentially displayed chosen words in an altered state at the display area. | 0.925755 |
1. A method programmed in a non-transitory memory of a first device, the first device comprising: receiving, at the first device, broadcast information; converting at least a portion of the broadcast information into searchable information; automatically performing a first fact check for factual accuracy of the broadcast information using the first device, the first fact check including comparing the searchable information with information from one or more first sources; automatically performing a second fact check for factual accuracy of the broadcast information in parallel with the first fact check, the second fact check including comparing the searchable information with information from one or more second sources; wherein automatically performing the first fact check results in generating a first result of the first fact check; wherein automatically performing the second fact check results in generating a second result of the second fact check; causing to be displayed, on a second device, an indication of the first result of the first fact check and the second result of the second fact check. | 1. A method programmed in a non-transitory memory of a first device, the first device comprising: receiving, at the first device, broadcast information; converting at least a portion of the broadcast information into searchable information; automatically performing a first fact check for factual accuracy of the broadcast information using the first device, the first fact check including comparing the searchable information with information from one or more first sources; automatically performing a second fact check for factual accuracy of the broadcast information in parallel with the first fact check, the second fact check including comparing the searchable information with information from one or more second sources; wherein automatically performing the first fact check results in generating a first result of the first fact check; wherein automatically performing the second fact check results in generating a second result of the second fact check; causing to be displayed, on a second device, an indication of the first result of the first fact check and the second result of the second fact check. 4. The method of claim 1 further comprising automatically processing the broadcast information including parsing the searchable information into fact checkable portions. | 0.669783 |
27. A portable electronic device configured to process voice commands, comprising: one or more input devices; one or more processors; memory storing one or more programs configured to be executed by the one or more processors, the one or more programs including instructions for: in response to user input, recording a voice command on the portable electronic device; processing at least a portion of the voice command using a speech recognition engine to determine at least a portion of contextual information that is relevant to the voice command; storing the portion of the contextual information that is relevant to the voice command; transmitting the recorded voice command and the portion of the contextual information that is relevant to the voice command from the portable electronic device to remote computing equipment; receiving, from the remote computing equipment, results associated with the recorded voice command and the stored portion of the contextual information; and presenting the results. | 27. A portable electronic device configured to process voice commands, comprising: one or more input devices; one or more processors; memory storing one or more programs configured to be executed by the one or more processors, the one or more programs including instructions for: in response to user input, recording a voice command on the portable electronic device; processing at least a portion of the voice command using a speech recognition engine to determine at least a portion of contextual information that is relevant to the voice command; storing the portion of the contextual information that is relevant to the voice command; transmitting the recorded voice command and the portion of the contextual information that is relevant to the voice command from the portable electronic device to remote computing equipment; receiving, from the remote computing equipment, results associated with the recorded voice command and the stored portion of the contextual information; and presenting the results. 29. The portable electronic device of claim 27 , wherein the voice command comprises a request from a user to perform a search and wherein processing the voice command and the portion of the contextual information that is relevant comprises performing the search using the portion of the contextual information that is relevant. | 0.526128 |
1. A computer readable storage medium having a method encoded thereon, the method represented by computer readable programming code, executed by a computer to perform the method comprising the steps of: classifying input sensor data by comparing one or more measured target attributes with one or more known attributes of a finite set of uniquely identified targets; generating an initial set of one or more candidate targets based upon a comparison of the classified input sensor data with the known attributes of the finite set of uniquely identified targets; calculating a minimum required speed for each candidate target to travel between a geolocation history location and a location provided by the input sensor data, the minimum required speed subject to both obstacle avoidance and status transition time constraints; assigning a statistical weight to each candidate target based upon its calculated minimum required speed; calculating a data association probability of each candidate target with the classified input sensor data; and generating a final set of candidate targets by selecting the candidate targets from the initial set of candidate targets having calculated data association probabilities that exceed a predetermined threshold value. | 1. A computer readable storage medium having a method encoded thereon, the method represented by computer readable programming code, executed by a computer to perform the method comprising the steps of: classifying input sensor data by comparing one or more measured target attributes with one or more known attributes of a finite set of uniquely identified targets; generating an initial set of one or more candidate targets based upon a comparison of the classified input sensor data with the known attributes of the finite set of uniquely identified targets; calculating a minimum required speed for each candidate target to travel between a geolocation history location and a location provided by the input sensor data, the minimum required speed subject to both obstacle avoidance and status transition time constraints; assigning a statistical weight to each candidate target based upon its calculated minimum required speed; calculating a data association probability of each candidate target with the classified input sensor data; and generating a final set of candidate targets by selecting the candidate targets from the initial set of candidate targets having calculated data association probabilities that exceed a predetermined threshold value. 9. The computer readable storage medium of claim 1 , wherein a weight w j for a j th candidate target is based upon a minimal required speed s j =max[s 1 ,s 2 ], where s 1 is the speed-of-advance for the candidate target to travel from a point P 1 to a point P that is subject to both obstacle avoidance and status transition time constraints, where point P 1 is the “just before target history location” for the j th candidate target and where point P is a target location provided by the sensor data, and s 2 is the speed-of-advance for the candidate target to travel from the point P to a point P 2 that is subject to both obstacle avoidance and status transition time constraints, where point P 2 is the “just after target location” for the j th candidate target. | 0.711701 |
11. The method of claim 10 , wherein: the feature is associated with a feature type, identifying the feature in the plurality of training documents further comprises identifying a corresponding feature type for the feature, and a feature type decision tree is generated that comprises the feature type. | 11. The method of claim 10 , wherein: the feature is associated with a feature type, identifying the feature in the plurality of training documents further comprises identifying a corresponding feature type for the feature, and a feature type decision tree is generated that comprises the feature type. 12. The method of claim 11 , further comprising generating a second node corresponding to the class associated with the first decision tree. | 0.938596 |
16. The server system of claim 15 wherein the fabrication set and the family set have a many-to-many relationship. | 16. The server system of claim 15 wherein the fabrication set and the family set have a many-to-many relationship. 17. The server system of claim 16 wherein a family of the family set and corresponding device set form a parent-child relationship, respectively and a device of the device set and corresponding lot set form another parent-child relationship, respectively. | 0.921134 |
1. A computer program product, the computer program product comprising: a non-transitory computer readable storage medium having computer readable program code embodied therewith, the computer readable program code, when executed by at least one processor of a computer, is configured to perform: dynamically generating an environment dictionary for a document that is being viewed based on information from one or more social networks associated with the user; and in response to receiving a portion of a word for the document, receiving a list of words for use in completing the portion of the word, wherein each word in the list of words has an associated weight; for at least one word in the list of words, obtaining an environment weight from the dynamically created environment dictionary; updating the associated weight of the at least one word using the obtained environment weight; and ordering the words in the list of words based on the updated, associated weight of each of the words. | 1. A computer program product, the computer program product comprising: a non-transitory computer readable storage medium having computer readable program code embodied therewith, the computer readable program code, when executed by at least one processor of a computer, is configured to perform: dynamically generating an environment dictionary for a document that is being viewed based on information from one or more social networks associated with the user; and in response to receiving a portion of a word for the document, receiving a list of words for use in completing the portion of the word, wherein each word in the list of words has an associated weight; for at least one word in the list of words, obtaining an environment weight from the dynamically created environment dictionary; updating the associated weight of the at least one word using the obtained environment weight; and ordering the words in the list of words based on the updated, associated weight of each of the words. 3. The computer program product of claim 1 , the computer readable program code, when executed by the at least one processor of the computer, is configured to perform: collecting the information from the one or more social networks associated with the user. | 0.627095 |
1. A system that facilitates analyzing content of a multi-dimensional structure, the system comprising: an interface component that collects statements in a declarative language and relays the statements; a calculation component that receives relayed statements from the interface component, the statements being in a declarative language relating to modifying data, and executes such statements against the multi-dimensional structure, the calculation component recognizes that the statements relate to a recursive calculation assigned as a value of a cell in the multi-dimensional structure, the recursive calculation including a recursive reference back to the cell, the execution of the relayed statements modifying a portion of the data stored within the multi-dimensional structure; a pass generation component that, in response to the calculation component receiving the relayed statements and prior to the execution of the relayed statements by the calculation component, creates at least one pass, each pass including the portion of the data stored within the multi-dimensional structure as the portion of the data existed prior to the calculation component executed the relayed statements; and a pass analysis component that analyzes a previous pass and selects a value within a previous pass that enables the recursive calculation to complete through utilization of cells at multiple prior passes to complete a calculation or assignment, wherein storage operatively coupled to a processor retains at least a portion of the calculation component or the pass generation component. | 1. A system that facilitates analyzing content of a multi-dimensional structure, the system comprising: an interface component that collects statements in a declarative language and relays the statements; a calculation component that receives relayed statements from the interface component, the statements being in a declarative language relating to modifying data, and executes such statements against the multi-dimensional structure, the calculation component recognizes that the statements relate to a recursive calculation assigned as a value of a cell in the multi-dimensional structure, the recursive calculation including a recursive reference back to the cell, the execution of the relayed statements modifying a portion of the data stored within the multi-dimensional structure; a pass generation component that, in response to the calculation component receiving the relayed statements and prior to the execution of the relayed statements by the calculation component, creates at least one pass, each pass including the portion of the data stored within the multi-dimensional structure as the portion of the data existed prior to the calculation component executed the relayed statements; and a pass analysis component that analyzes a previous pass and selects a value within a previous pass that enables the recursive calculation to complete through utilization of cells at multiple prior passes to complete a calculation or assignment, wherein storage operatively coupled to a processor retains at least a portion of the calculation component or the pass generation component. 11. The system of claim 1 , further comprising a contingency analysis component that determines whether the received statements relate to a calculation that is defined as a contingent calculation and restricts user access to resultant values of the calculation if such calculation is a contingent calculation. | 0.502518 |
17. The one or more computer-storage media as recited in claim 15 , the acts further comprise: receiving a selection gesture to select one or more segments from the area corresponding to the indication; and instantiating a search query based on the one or more selected segments. | 17. The one or more computer-storage media as recited in claim 15 , the acts further comprise: receiving a selection gesture to select one or more segments from the area corresponding to the indication; and instantiating a search query based on the one or more selected segments. 18. The one or more computer-storage media as recited in claim 17 , the acts further comprising: sending the search query to a search engine; and receiving search results from the search engine. | 0.859307 |
1. A method for providing automated assistance for a user using a computing device selected from a group consisting of: a telephone; a wireless communicator; a tablet computer; a laptop computer; a personal digital assistant; a desktop computer; a processor with memory; a kiosk; a consumer electronic device; a consumer entertainment device; a music player; a camera; a television; an electronic gaming unit; and a set-top box, the method comprising: receiving a user request for assistance spoken in a first language; translating the user request spoken in the first language to a second language; determining semantics of the user request and identifying at least one domain, at least one task, and at least one parameter for the user request; searching a semantic database on the Internet for the at least one matching domain, task, and parameter; compensating for translation errors based on user history; generating a response in the second language; and translating the response to the first language and rendering the response to the user and providing information from one of: music, audiobooks, news, weather, traffic, sports, and processing the user request by an assistant software on a computing cloud to purchase, reserve, or order products or services, wherein the assistant software automatically accesses semantic data and services having one or more triples including subject, predicate, and object available over the Internet to find one or more of: movies, events, performances, exhibits, shows, attractions, travel destinations, hotels, restaurants, bars, pubs, entertainment sites, landmarks, summer camps, resorts, places. | 1. A method for providing automated assistance for a user using a computing device selected from a group consisting of: a telephone; a wireless communicator; a tablet computer; a laptop computer; a personal digital assistant; a desktop computer; a processor with memory; a kiosk; a consumer electronic device; a consumer entertainment device; a music player; a camera; a television; an electronic gaming unit; and a set-top box, the method comprising: receiving a user request for assistance spoken in a first language; translating the user request spoken in the first language to a second language; determining semantics of the user request and identifying at least one domain, at least one task, and at least one parameter for the user request; searching a semantic database on the Internet for the at least one matching domain, task, and parameter; compensating for translation errors based on user history; generating a response in the second language; and translating the response to the first language and rendering the response to the user and providing information from one of: music, audiobooks, news, weather, traffic, sports, and processing the user request by an assistant software on a computing cloud to purchase, reserve, or order products or services, wherein the assistant software automatically accesses semantic data and services having one or more triples including subject, predicate, and object available over the Internet to find one or more of: movies, events, performances, exhibits, shows, attractions, travel destinations, hotels, restaurants, bars, pubs, entertainment sites, landmarks, summer camps, resorts, places. 5. The method of claim 1 , wherein the receiving the user request comprises recognizing user voice. | 0.597027 |
19. The computer program of claim 18 , further comprising: determining, responsive to the at least one user, the at least one annotation is applied to at least one document, including to select at least the predetermined section of the at least one document and to associate the at least one annotation with the predetermined section. | 19. The computer program of claim 18 , further comprising: determining, responsive to the at least one user, the at least one annotation is applied to at least one document, including to select at least the predetermined section of the at least one document and to associate the at least one annotation with the predetermined section. 21. The computer program of claim 19 , wherein determining the at least one annotation includes at least one of: (i) receiving a reference to another document; (ii) selecting at least one pre-defined notation; (iii) receiving input text; (iv) selecting at least one user-defined attribute; (v) receiving a reference to a URL; and (vi) receiving a reference to a file. | 0.922494 |
10. A method comprising: receiving, for an input media file, an input annotation; identifying, in a second database, (1) a set of co-occurring annotations that occur for media files associated with the input annotation, and (2) a count associated with each co-occurring annotation from the set of annotations indicating for how many media files in a first database the co-occurring annotation occurs with the input annotation, wherein the second database comprises records, each record in the comprising the count indicating the number of media files from the first database associated with the annotation and the respective co-occurring annotation; identifying, in a first database, media files similar to the input media file by retrieving media files associated with annotations, from the set of co-occurring annotations, having an associated count meeting a predefined criterion indicating a minimum number of media files in the first database for which the co-occurring annotation occurs with the input annotation; and selecting annotations associated with the similar media files that have the associated count meeting the predefined criterion to present as a list of recommended annotations for the input media file. | 10. A method comprising: receiving, for an input media file, an input annotation; identifying, in a second database, (1) a set of co-occurring annotations that occur for media files associated with the input annotation, and (2) a count associated with each co-occurring annotation from the set of annotations indicating for how many media files in a first database the co-occurring annotation occurs with the input annotation, wherein the second database comprises records, each record in the comprising the count indicating the number of media files from the first database associated with the annotation and the respective co-occurring annotation; identifying, in a first database, media files similar to the input media file by retrieving media files associated with annotations, from the set of co-occurring annotations, having an associated count meeting a predefined criterion indicating a minimum number of media files in the first database for which the co-occurring annotation occurs with the input annotation; and selecting annotations associated with the similar media files that have the associated count meeting the predefined criterion to present as a list of recommended annotations for the input media file. 15. The method of claim 10 , wherein the input annotation is provided by a user. | 0.604194 |
1. A method, comprising: setting, with a processor executing on a computer, one or more breakpoints in source code of a client application based on locations of Application Programming Interface (API) calls in the source code; while running the client application through a debugger, upon reaching each of the one or more breakpoints, identifying one or more debugger rules associated with a query at a breakpoint; in response to determining that conditions of the one or more debugger rules are satisfied, obtaining a stack trace before the query makes a call to a database; deriving query text of the query and a location of the query in the source code of the client application; parsing the query text to identify database objects used by the query; and storing correlator results for the query that identify a source file of the client application, locations of an API call in the source code, parameters of the API call, and the database objects, wherein one of the parameters is the query text of the query; and displaying user interface views in a user interface to present the correlator results for problem determination and where used analysis. | 1. A method, comprising: setting, with a processor executing on a computer, one or more breakpoints in source code of a client application based on locations of Application Programming Interface (API) calls in the source code; while running the client application through a debugger, upon reaching each of the one or more breakpoints, identifying one or more debugger rules associated with a query at a breakpoint; in response to determining that conditions of the one or more debugger rules are satisfied, obtaining a stack trace before the query makes a call to a database; deriving query text of the query and a location of the query in the source code of the client application; parsing the query text to identify database objects used by the query; and storing correlator results for the query that identify a source file of the client application, locations of an API call in the source code, parameters of the API call, and the database objects, wherein one of the parameters is the query text of the query; and displaying user interface views in a user interface to present the correlator results for problem determination and where used analysis. 2. The method of claim 1 , further comprising: in response to determining that conditions of the one or more debugger rules are not satisfied, continuing to run the client application through the debugger until another breakpoint is reached or execution of the client application is completed. | 0.595035 |
5. The method of claim 1 wherein analyzing log data comprises: gathering user identifying information associated with the first query and the related queries from the log data stored on the memory; and removing duplicates of the first query and the related queries having the same user identifying information submitted within a defined period of time. | 5. The method of claim 1 wherein analyzing log data comprises: gathering user identifying information associated with the first query and the related queries from the log data stored on the memory; and removing duplicates of the first query and the related queries having the same user identifying information submitted within a defined period of time. 18. The method of claim 5 , wherein removing duplicates of the first query and the related queries having the same user identifying information comprises removing duplicates of the first query and the related queries having the same user identifying information submitted within a period of time defined by a non-temporal event. | 0.911321 |
12. A computer system comprising: a parser to parse a search query into one or more constituent terms; a retrieving engine to retrieve a first member of one or more domains based upon a correspondence between the one or more constituent terms and the first member of the one or more domains, the first member of the one or more domains corresponding to an attribute in a database table; a relation engine implemented by one or more processors to automatically relate the first member of the one or more domains to a semantic phrase, based on a probability value associated with the semantic phrase, the semantic phrase representing a semantic relationship between the first member and a second member of the one or more domains; and a generator to generate a semantic query using the semantic phrase and the first and second members of the one or more domains. | 12. A computer system comprising: a parser to parse a search query into one or more constituent terms; a retrieving engine to retrieve a first member of one or more domains based upon a correspondence between the one or more constituent terms and the first member of the one or more domains, the first member of the one or more domains corresponding to an attribute in a database table; a relation engine implemented by one or more processors to automatically relate the first member of the one or more domains to a semantic phrase, based on a probability value associated with the semantic phrase, the semantic phrase representing a semantic relationship between the first member and a second member of the one or more domains; and a generator to generate a semantic query using the semantic phrase and the first and second members of the one or more domains. 15. The computer system of claim 12 , wherein the semantic query is a Natural Language (NL) statement. | 0.892034 |
17. The EPG generating apparatus according to claim 16 , wherein the processor compares the optimum keyword groups with the program description to generate some keywords of the optimum keyword group in a plurality of occurrence frequencies of the program description, the processor divides the occurrence frequencies by the keyword counts of the optimum keyword groups respectively to generate a plurality of values, and calculates an average value of the values to generate the match score. | 17. The EPG generating apparatus according to claim 16 , wherein the processor compares the optimum keyword groups with the program description to generate some keywords of the optimum keyword group in a plurality of occurrence frequencies of the program description, the processor divides the occurrence frequencies by the keyword counts of the optimum keyword groups respectively to generate a plurality of values, and calculates an average value of the values to generate the match score. 18. The EPG generating apparatus according to claim 17 , wherein the processor constructs a relation matrix of the undirected graph, constructs at least one sub-relation matrix according to the relation matrix, the dimension of the sub-relation matrix is less than the dimension of the relation matrix, calculates a sum of matrix elements of the sub-relation matrix, and determines whether the sum of matrix elements is equal the square of the dimension of the sub-relation matrix, and the sub-relation matrix is one of the maximum cliques when the sum of matrix elements is equal to the square of the dimension of the sub-relation matrix. | 0.652174 |
15. At least one non-transitory machine-readable medium comprising a plurality of instructions, executed on a computing device, to facilitate the computing device to: receive, via one or more capturing/sensing components at a computing device, one or more media items relating to an event; capture a theme from the one or more media items, wherein the theme is captured based on at least one of activities, textual content, and scenes associated with the event; and form a plurality of story elements to generate a story relating to the event, wherein the plurality of story elements are formed based on at least one of one or more characters, the theme associated with the event, and one or more emotions associated with the one or more characters, wherein the story is presented, via one or more display devices, to one or more users having access to the one or more display devices; extract the one or more characters from the one or more media items, wherein the one or more characters having assigned one or more roles representing one or more individuals associated with the event; determine the one or more emotions from the one or more media items, wherein the one or more emotions are determined based on one or more expressions associated with the one or more characters; generate the story based on the plurality of story elements, wherein the story is posted at one or more websites, wherein the story is posted as at least one of a social posting at a social networking website, a blog posting at a news or blogging website, and a template posting having one or more story templates posted at a philanthropic website or a commercial website, wherein the one or more story templates are downloadable by the one or more users to auto-generate stories using the one or more story templates having the plurality of elements associated with the story; monitor the one or more media items being received from one or more media sources over a communication medium, wherein the one or more media sources include at least one of a website, a media feed, a media player, a computing device, a sensor array, a camera, and a microphone, wherein the one or more media items include at least one of pictures, videos, audios, live chatter, text messages, postings, comments, feedbacks, and blogs; extract, from the one or more media items, one or more identities or the one or more roles associated with the one or more characters wherein the one or more identities are extracted based on at least one of comments or descriptions associated with the one or more characters such that an identity associated with a character is detected based on at least one of a role, a comment, and a description associated with the character, wherein the identity refers to one or more of a parent, a child, a relative, a friend, a neighbor, a teammate, a coach, a boss, an employee, and a stranger; resolve one or more references relating to the one or more characters, wherein the one or more references include one or more pronouns associated with the one or more characters; discover one or more locations of the event, wherein the one or more locations are discovered based on global positioning system (GPS) coordinates relating to one or more computing devices accessible to the one or more characters; and determine the one or more roles associated with the one or more characters, wherein a role is assigned to a character of the one or more characters based on a comment regarding the character, wherein the one or more roles further refer to one or more relationships between two or more characters, wherein the one or more relationships include one or more of parent-child, brother-sister, aunt-nephew, grandfather-grandson, teammate-teammate, coach-player, neighbor-neighbor, boss-subordinate, owner-employee, partner-partner, and stranger-stranger. | 15. At least one non-transitory machine-readable medium comprising a plurality of instructions, executed on a computing device, to facilitate the computing device to: receive, via one or more capturing/sensing components at a computing device, one or more media items relating to an event; capture a theme from the one or more media items, wherein the theme is captured based on at least one of activities, textual content, and scenes associated with the event; and form a plurality of story elements to generate a story relating to the event, wherein the plurality of story elements are formed based on at least one of one or more characters, the theme associated with the event, and one or more emotions associated with the one or more characters, wherein the story is presented, via one or more display devices, to one or more users having access to the one or more display devices; extract the one or more characters from the one or more media items, wherein the one or more characters having assigned one or more roles representing one or more individuals associated with the event; determine the one or more emotions from the one or more media items, wherein the one or more emotions are determined based on one or more expressions associated with the one or more characters; generate the story based on the plurality of story elements, wherein the story is posted at one or more websites, wherein the story is posted as at least one of a social posting at a social networking website, a blog posting at a news or blogging website, and a template posting having one or more story templates posted at a philanthropic website or a commercial website, wherein the one or more story templates are downloadable by the one or more users to auto-generate stories using the one or more story templates having the plurality of elements associated with the story; monitor the one or more media items being received from one or more media sources over a communication medium, wherein the one or more media sources include at least one of a website, a media feed, a media player, a computing device, a sensor array, a camera, and a microphone, wherein the one or more media items include at least one of pictures, videos, audios, live chatter, text messages, postings, comments, feedbacks, and blogs; extract, from the one or more media items, one or more identities or the one or more roles associated with the one or more characters wherein the one or more identities are extracted based on at least one of comments or descriptions associated with the one or more characters such that an identity associated with a character is detected based on at least one of a role, a comment, and a description associated with the character, wherein the identity refers to one or more of a parent, a child, a relative, a friend, a neighbor, a teammate, a coach, a boss, an employee, and a stranger; resolve one or more references relating to the one or more characters, wherein the one or more references include one or more pronouns associated with the one or more characters; discover one or more locations of the event, wherein the one or more locations are discovered based on global positioning system (GPS) coordinates relating to one or more computing devices accessible to the one or more characters; and determine the one or more roles associated with the one or more characters, wherein a role is assigned to a character of the one or more characters based on a comment regarding the character, wherein the one or more roles further refer to one or more relationships between two or more characters, wherein the one or more relationships include one or more of parent-child, brother-sister, aunt-nephew, grandfather-grandson, teammate-teammate, coach-player, neighbor-neighbor, boss-subordinate, owner-employee, partner-partner, and stranger-stranger. 18. The non-transitory machine-readable medium of claim 15 , wherein the computing device is further to: extract goals and sequence of elements of the story; facilitate editing of contents of the story; and associate one or more hashtags to the story. | 0.645263 |
1. A visual cue system associated with a plurality of consumer product packages, comprising: a first visual cue having at least a first symbol and first text associated therewith and being affixed to a first consumer product package, wherein a first product therein is adapted to perform a first function; a second visual cue having at least a second symbol and second text associated therewith and being affixed to a second consumer product package, wherein a second product therein is adapted to perform a second, different function; and a regimen key disposed on at least one of the first or second consumer product packages, wherein the first and second consumer product packages are different. | 1. A visual cue system associated with a plurality of consumer product packages, comprising: a first visual cue having at least a first symbol and first text associated therewith and being affixed to a first consumer product package, wherein a first product therein is adapted to perform a first function; a second visual cue having at least a second symbol and second text associated therewith and being affixed to a second consumer product package, wherein a second product therein is adapted to perform a second, different function; and a regimen key disposed on at least one of the first or second consumer product packages, wherein the first and second consumer product packages are different. 4. The visual cue system of claim 1 , wherein the first visual cue and the second visual cue are disposed on a front surface of the first and second consumer product packages, respectively, and the regimen key is disposed on a rear surface of both of the first and the second consumer product packages. | 0.591874 |
81. A electronic device comprising: one or more input devices; one or more processors; and memory storing one or more programs configured to be executed by the one or more processors, the one or more programs including instructions for: receiving user input; in response to receiving user input, recording at least a portion of a voice command; storing contextual information of the electronic device, the contextual information related to a state of the electronic device at a time the at least a portion of the voice command is recorded; and after recording the at least a portion of the voice command and storing the contextual information, transmitting the at least a portion of the recorded voice command and the stored contextual information from the electronic device to remote computing equipment; and receiving, from the remote computing equipment, data related to processing the voice command. | 81. A electronic device comprising: one or more input devices; one or more processors; and memory storing one or more programs configured to be executed by the one or more processors, the one or more programs including instructions for: receiving user input; in response to receiving user input, recording at least a portion of a voice command; storing contextual information of the electronic device, the contextual information related to a state of the electronic device at a time the at least a portion of the voice command is recorded; and after recording the at least a portion of the voice command and storing the contextual information, transmitting the at least a portion of the recorded voice command and the stored contextual information from the electronic device to remote computing equipment; and receiving, from the remote computing equipment, data related to processing the voice command. 111. The electronic device of claim 81 , wherein incomplete speech recognition on the at least a portion of the recorded voice command is performed at the electronic device prior to transmitting the at least a portion of the recorded voice command and the stored contextual information from the electronic device to the remote computing equipment. | 0.5 |
1. A computer-implemented method for processing information in a closed document residing on a computer file system, comprising: displaying, in a computer file system user interface, a name or icon of an electronic file, wherein the electronic file is in a closed state, wherein the electronic file is an object in the computer file system, wherein the computer file system comprises one or more folders or subfolders and at least one file in a tree structure; allowing a user to act on the name or icon of the electronic file, or on a user interface object associated with the name or icon of the electronic file, wherein the user action comprises moving a pointing device over, clicking, or touching, or a voice or visually activated action; in response to a user action, receiving a first term and a second term extracted from a text content associated with the electronic file; determining a two-part display format that represents a hierarchical relation between the first term and the second term, wherein the two-part display format comprises a first part and a second part; displaying the first term in the first part; and displaying the second term in the second part, wherein the second term is displayed as an item subordinate to the first term in the hierarchical format, wherein the subordinate relationship is defined by a visual format including a heading-body relation, or a difference in size, color or character style, or position, or annotation, wherein the first term and the second term are obtained by: (a) receiving a user-generated text content in the electronic file, (b) tokenizing the text content into terms, each term comprising a word or a phrase or a sentence, (c) identifying a first term in the text content, (d) identifying an attribute associated the first term using a machine-based algorithm, wherein the attribute comprises a grammatical, semantic, positional, or frequency attribute, (e) assigning an importance measure to the first term based on the attribute, (f) selecting the first term for extraction if the importance measure is above a threshold, (g) identifying a sentence containing the first term and the second term, (h) identifying a grammatical structure in the sentence, wherein the grammatical structure comprises components and one or more types of relations between the components, wherein the components and relations comprise a grammatical subject in relation to a non-subject portion of the sentence, or a multi-word phrase comprising a head term in relation to a modifier term, (i) determining the first term and the second term as two components in one of the one or more types of relations in the grammatical structure, and (j) extracting the first term and the second term based on the type of relation. | 1. A computer-implemented method for processing information in a closed document residing on a computer file system, comprising: displaying, in a computer file system user interface, a name or icon of an electronic file, wherein the electronic file is in a closed state, wherein the electronic file is an object in the computer file system, wherein the computer file system comprises one or more folders or subfolders and at least one file in a tree structure; allowing a user to act on the name or icon of the electronic file, or on a user interface object associated with the name or icon of the electronic file, wherein the user action comprises moving a pointing device over, clicking, or touching, or a voice or visually activated action; in response to a user action, receiving a first term and a second term extracted from a text content associated with the electronic file; determining a two-part display format that represents a hierarchical relation between the first term and the second term, wherein the two-part display format comprises a first part and a second part; displaying the first term in the first part; and displaying the second term in the second part, wherein the second term is displayed as an item subordinate to the first term in the hierarchical format, wherein the subordinate relationship is defined by a visual format including a heading-body relation, or a difference in size, color or character style, or position, or annotation, wherein the first term and the second term are obtained by: (a) receiving a user-generated text content in the electronic file, (b) tokenizing the text content into terms, each term comprising a word or a phrase or a sentence, (c) identifying a first term in the text content, (d) identifying an attribute associated the first term using a machine-based algorithm, wherein the attribute comprises a grammatical, semantic, positional, or frequency attribute, (e) assigning an importance measure to the first term based on the attribute, (f) selecting the first term for extraction if the importance measure is above a threshold, (g) identifying a sentence containing the first term and the second term, (h) identifying a grammatical structure in the sentence, wherein the grammatical structure comprises components and one or more types of relations between the components, wherein the components and relations comprise a grammatical subject in relation to a non-subject portion of the sentence, or a multi-word phrase comprising a head term in relation to a modifier term, (i) determining the first term and the second term as two components in one of the one or more types of relations in the grammatical structure, and (j) extracting the first term and the second term based on the type of relation. 3. The method of claim 1 , wherein multiple second terms are extracted from the text content, wherein the first term is displayed as a heading and the multiple second terms are displayed as a list of elements under the heading, or displayed as elements in a cloud or group format under the heading represented by the first term. | 0.553796 |
9. A computer-implemented system comprising: at least one processor coupled to a memory; a share event detector to detect, using the at least one processor, a publication that was shared by a member of an on-line social networking system; a name phrase detector to determine, using the at least one processor, that the publication includes a name entity, the name entity comprising a string of characters; a candidate list generator to select, using the at least one processor, one or more candidate profiles from a plurality of member profiles in the on-line social networking system, based on the name entity; a disambiguation module to select, using the at least one processor, a matching profile from the candidate profiles, utilizing one or more disambiguation techniques, the one or more disambiguation techniques comprising utilizing data from a candidate profile from the one or more candidate profiles and data from one or more profiles of connections of the candidate profile; and a name recognition module to identify, using the at least one processor, the matching profile from the candidate profiles as a member profile in the on-line social networking system that represents a member referenced by the name entity. | 9. A computer-implemented system comprising: at least one processor coupled to a memory; a share event detector to detect, using the at least one processor, a publication that was shared by a member of an on-line social networking system; a name phrase detector to determine, using the at least one processor, that the publication includes a name entity, the name entity comprising a string of characters; a candidate list generator to select, using the at least one processor, one or more candidate profiles from a plurality of member profiles in the on-line social networking system, based on the name entity; a disambiguation module to select, using the at least one processor, a matching profile from the candidate profiles, utilizing one or more disambiguation techniques, the one or more disambiguation techniques comprising utilizing data from a candidate profile from the one or more candidate profiles and data from one or more profiles of connections of the candidate profile; and a name recognition module to identify, using the at least one processor, the matching profile from the candidate profiles as a member profile in the on-line social networking system that represents a member referenced by the name entity. 10. The system of claim 9 , wherein the one or more disambiguation techniques comprises determining whether a candidate profile from the one or more candidate profiles is connected to a further member profile that is identified by name in the publication, the further member profile being from the member profiles in the on-line social networking system. | 0.509705 |
1. A computer-implemented method for performing an analysis of model metadata in a modeling environment, said method including: reading, by a computer-based system for performing said analysis of said model metadata in said modeling environment, a request from a client, wherein said request includes a model identifier and a presentation parameter; reading, by said computer-based system, a variable identifier, wherein said variable identifier is associated with said model identifier; reading, by said computer-based system, variable metadata, wherein said variable metadata is associated with said variable identifier; and, formatting, by said computer-based system, said variable identifier and said variable metadata in accordance with said presentation parameter to create model metadata. | 1. A computer-implemented method for performing an analysis of model metadata in a modeling environment, said method including: reading, by a computer-based system for performing said analysis of said model metadata in said modeling environment, a request from a client, wherein said request includes a model identifier and a presentation parameter; reading, by said computer-based system, a variable identifier, wherein said variable identifier is associated with said model identifier; reading, by said computer-based system, variable metadata, wherein said variable metadata is associated with said variable identifier; and, formatting, by said computer-based system, said variable identifier and said variable metadata in accordance with said presentation parameter to create model metadata. 7. The method of claim 1 , wherein said model metadata is color-coded according to at least one of: status, modeler, model owner, business unit, model type, variable type, decommissioning status, decommissioning date, and deployment date. | 0.673837 |
1. A computer accessible storage hardware having thereon stored a system for providing application-layer functionality between one or more database clients and one or more database servers, the system comprising: one or more decoders residing at a decoding layer above a network layer, the decoders residing at a first network location between one or more database clients residing at one or more second network locations and one or more database servers residing at one or more third network locations, the decoders being operable to: receive database messages communicated from the database clients and intended for the database servers and database messages communicated from the database servers and intended for the database clients; decode the database messages; extract query-language statements from the database messages; a caching application residing at an application layer above the decoding layer, the caching application residing at the first network location, the caching application being operable to: receive query-language statements extracted at the decoders comprising queries; receive query-language statements extracted at the decoders comprising query results corresponding to the queries; record the queries and the query results corresponding to the queries in a cache residing at the first network location wherein the queries are associated with a corresponding query result; a monitoring application operable to receive query-language statements extracted at the decoders and record observations on the database messages based at least in part on the query-language statements extracted at the decoders, wherein at least one observation is associated with a query result stored in the cache and communicate one or more observations associated with the queries to one or more computing systems at a fourth network location according to the needs of the one or more computer systems, wherein at least one of the computer systems maintains a web cache and is operable to modify the web cache based upon the communicated observations wherein observations on the database messages based at least in part on the query-language statement extracted at the decoders comprise the following: subject database instances of the query-language statements; network protocols and versions of the network protocols used to communicate the database messages; devices hosting the subject database instances of the query-language statements; hostnames, Internet Protocol (IP) addresses, Media Access Control (MAC) addresses, and network ports of the database servers; operating systems (OSs), versions of the OSs, and attributes of the OSs of devices hosting the subject database instances; devices hosting the clients; and a number of queries communicated from each of the clients to each of one or more database instances; and an application residing at an application layer above the decoding layer, the application residing at the first network location, the application being operable to receive and process query-language statements extracted at the decoders. | 1. A computer accessible storage hardware having thereon stored a system for providing application-layer functionality between one or more database clients and one or more database servers, the system comprising: one or more decoders residing at a decoding layer above a network layer, the decoders residing at a first network location between one or more database clients residing at one or more second network locations and one or more database servers residing at one or more third network locations, the decoders being operable to: receive database messages communicated from the database clients and intended for the database servers and database messages communicated from the database servers and intended for the database clients; decode the database messages; extract query-language statements from the database messages; a caching application residing at an application layer above the decoding layer, the caching application residing at the first network location, the caching application being operable to: receive query-language statements extracted at the decoders comprising queries; receive query-language statements extracted at the decoders comprising query results corresponding to the queries; record the queries and the query results corresponding to the queries in a cache residing at the first network location wherein the queries are associated with a corresponding query result; a monitoring application operable to receive query-language statements extracted at the decoders and record observations on the database messages based at least in part on the query-language statements extracted at the decoders, wherein at least one observation is associated with a query result stored in the cache and communicate one or more observations associated with the queries to one or more computing systems at a fourth network location according to the needs of the one or more computer systems, wherein at least one of the computer systems maintains a web cache and is operable to modify the web cache based upon the communicated observations wherein observations on the database messages based at least in part on the query-language statement extracted at the decoders comprise the following: subject database instances of the query-language statements; network protocols and versions of the network protocols used to communicate the database messages; devices hosting the subject database instances of the query-language statements; hostnames, Internet Protocol (IP) addresses, Media Access Control (MAC) addresses, and network ports of the database servers; operating systems (OSs), versions of the OSs, and attributes of the OSs of devices hosting the subject database instances; devices hosting the clients; and a number of queries communicated from each of the clients to each of one or more database instances; and an application residing at an application layer above the decoding layer, the application residing at the first network location, the application being operable to receive and process query-language statements extracted at the decoders. 14. The computer accessible storage hardware of claim 1 , wherein at least some of the query-language statements are Structured Query Language (SQL) statements. | 0.590384 |
1. A computer-implemented method for defining a model comprising: at a computer system having one or more processors and memory storing one or more programs that when executed by the one or more processors cause the computer system to perform the method: analyzing one or more images of a physical space that include a plurality of distinctive visual features, wherein: the plurality of distinctive visual features include a first marker associated with first semantic information and a second marker associated with second semantic information; the first semantic information and the second semantic information are defined in accordance with a markup language that specifies rules for combining semantic information from a plurality of markers; and analyzing the one or more images includes: determining a pose of the first marker; and determining a pose of the second marker; and defining a model based at least in part on the pose of the first marker, the pose of the second marker, the first semantic information and the second semantic information, wherein defining the model includes: approximating a first model component based on the pose of the first marker and the first semantic information; and modifying the first model component based on the pose of the second marker and the second semantic information. | 1. A computer-implemented method for defining a model comprising: at a computer system having one or more processors and memory storing one or more programs that when executed by the one or more processors cause the computer system to perform the method: analyzing one or more images of a physical space that include a plurality of distinctive visual features, wherein: the plurality of distinctive visual features include a first marker associated with first semantic information and a second marker associated with second semantic information; the first semantic information and the second semantic information are defined in accordance with a markup language that specifies rules for combining semantic information from a plurality of markers; and analyzing the one or more images includes: determining a pose of the first marker; and determining a pose of the second marker; and defining a model based at least in part on the pose of the first marker, the pose of the second marker, the first semantic information and the second semantic information, wherein defining the model includes: approximating a first model component based on the pose of the first marker and the first semantic information; and modifying the first model component based on the pose of the second marker and the second semantic information. 4. The method of claim 1 , wherein: the model includes a plurality of model aspects; and at least one of the model aspects is specified in accordance with semantic information associated with a subset of the markers, the subset including at least two markers. | 0.512786 |
8. A computer-readable medium storing instructions, the instructions comprising: one or more instructions that, when executed by one or more processors, cause the one or more processors to: obtain a document, the document including a set of words or a set of characters; identify a skip value for the document, the skip value relating to a quantity of words or a quantity of characters that are to be skipped in an n-gram; determine one or more skip n-grams using the skip value for the document, a skip n-gram, of the one or more skip n-grams, including a sequence of one or more words or one or more characters with a plurality of occurrences in the document, the sequence of one or more words or one or more characters including a skip value quantity of words or characters within the sequence; extract one or more terms from the document based on the one or more skip n-grams, a term associated with the skip n-gram corresponding to the skip value quantity of words or characters within the sequence; generate a functional diagram representing the document using the one or more terms based on extracting the one or more terms; and provide, via a user interface, information identifying the functional diagram. | 8. A computer-readable medium storing instructions, the instructions comprising: one or more instructions that, when executed by one or more processors, cause the one or more processors to: obtain a document, the document including a set of words or a set of characters; identify a skip value for the document, the skip value relating to a quantity of words or a quantity of characters that are to be skipped in an n-gram; determine one or more skip n-grams using the skip value for the document, a skip n-gram, of the one or more skip n-grams, including a sequence of one or more words or one or more characters with a plurality of occurrences in the document, the sequence of one or more words or one or more characters including a skip value quantity of words or characters within the sequence; extract one or more terms from the document based on the one or more skip n-grams, a term associated with the skip n-gram corresponding to the skip value quantity of words or characters within the sequence; generate a functional diagram representing the document using the one or more terms based on extracting the one or more terms; and provide, via a user interface, information identifying the functional diagram. 11. The computer-readable medium of claim 8 , where the one or more instructions, when executed by the one or more processors, further cause the one or more processors to: determine that a plurality of terms of the one or more terms are duplicate terms; merge the plurality of terms into a single term; and where the one or more instructions, that cause the one or more processors to provide information identifying the one or more terms, cause the one or more processors to: provide information identifying the single term. | 0.534551 |
14. The non-transitory computer-readable storage medium according to claim 13 , wherein the plurality of pages are included in document data, which is generated by an application. | 14. The non-transitory computer-readable storage medium according to claim 13 , wherein the plurality of pages are included in document data, which is generated by an application. 15. The non-transitory computer-readable storage medium according to claim 14 , wherein a view representing a structure of the document data is displayed together with the preview. | 0.929424 |
1. A system for rendition of multi-modal data, comprising: a plurality of sources of multi-modal data configured to collect data from an environment wherein each of the plurality of sources is associated with a distinct sensor modality having distinct data modalities; a processor communicatively coupled to each of the plurality of sources of multi-modal data; and a storage medium communicatively coupled to the processor and tangibly embodying a plurality of executable modules of instructions wherein each module of instructions is connected to the processor via a bus, the plurality of executable modules including a data collection module, configured to asynchronously collect event data across the plurality of data modalities from each of the plurality of sources of multi-modal data and store the collected event data in memory, an anomaly detection module, configured to independently detect from the collected event data one or more event anomalies for each of a plurality of data modalities against background/historical data and to associate each event anomaly with a data modality temporal identifier and a data modality spatial identifier, an event anomaly recognition module configured to identify a spatial and a temporal relationship between each of the one or more event anomalies among the plurality of data modalities, an anomaly correlation module configured to combine identified event anomalies to form a coherent common event representation that is cross-correlated based on a predetermined modality temporal window and a predetermined spatial window, and a rendition module configured to render cross-correlated common representations of detected event anomalies and the environment from a plurality of perspectives. | 1. A system for rendition of multi-modal data, comprising: a plurality of sources of multi-modal data configured to collect data from an environment wherein each of the plurality of sources is associated with a distinct sensor modality having distinct data modalities; a processor communicatively coupled to each of the plurality of sources of multi-modal data; and a storage medium communicatively coupled to the processor and tangibly embodying a plurality of executable modules of instructions wherein each module of instructions is connected to the processor via a bus, the plurality of executable modules including a data collection module, configured to asynchronously collect event data across the plurality of data modalities from each of the plurality of sources of multi-modal data and store the collected event data in memory, an anomaly detection module, configured to independently detect from the collected event data one or more event anomalies for each of a plurality of data modalities against background/historical data and to associate each event anomaly with a data modality temporal identifier and a data modality spatial identifier, an event anomaly recognition module configured to identify a spatial and a temporal relationship between each of the one or more event anomalies among the plurality of data modalities, an anomaly correlation module configured to combine identified event anomalies to form a coherent common event representation that is cross-correlated based on a predetermined modality temporal window and a predetermined spatial window, and a rendition module configured to render cross-correlated common representations of detected event anomalies and the environment from a plurality of perspectives. 4. The system for rendition of multi-modal data according to claim 1 , wherein the collected event data collected from the plurality of sources includes a spatial and temporal reference. | 0.509706 |
34. The method of claim 33 , wherein the selecting is performed in response to user input. | 34. The method of claim 33 , wherein the selecting is performed in response to user input. 35. The method of claim 34 , wherein the user input specifies the plurality of entities to select using a multi-criteria search mechanism. | 0.960801 |
30. A computer-readable computer memory medium selected from the group consisting of: application-specific integrated circuits, standard integrated circuits, field-programmable gate arrays, complex programmable logic devices, hard disks, and memory, wherein the computer-readable computer memory medium is storing or executing instructions that, when executed, controls a computer processor to facilitate patent related searches from a patent corpus of patent related publications, by automatically performing citation analysis upon each iteration of a patent related search, the citation analysis comprising citations from a respective face of each patent publication, which lists backward references as well as forward references to patents and/or patent publications, by performing a method comprising: receiving an indication of input text and/or patent related publications as input; automatically analyzing the indicated input using semantic analysis of the indicated source input to automatically extract a first set of search-based keywords and/or phrases that are present in the indicated input, wherein the automatically analyzing the indicated input using semantic analysis parses the indicated source input to determine grammatical usage to automatically extract the first set of search-based keywords and/or phrases; from the automatically determined first set of keywords, performing an initial search iteration automatically, and wherein the initial search iteration is performed without additional user input, by performing the steps of: automatically determining an initial set of patent related publications that include the automatically extracted first set of search-based keywords; automatically determining a correlated set of patent related publications that are correlated to the initial set of patent related publications using automatic citation analysis of the initial set of patent related publications, wherein the correlated set is determined to be one or more patent related publications from the corpus that have unique citation relationships to any one of the patent related publications of the initial set, and wherein the correlated set is automatically sorted based upon the correlated patent related publications that involve the most number of citation paths with the initial set of patent related publications; and automatically extracting from the automatically determined initial set of patent related publications a set of related keywords not found in the first set of keywords or in the source input; and presenting indicators to the determined initial set and the sorted determined correlated set of patent related publications and the set of related keywords as output from the initial search iteration. | 30. A computer-readable computer memory medium selected from the group consisting of: application-specific integrated circuits, standard integrated circuits, field-programmable gate arrays, complex programmable logic devices, hard disks, and memory, wherein the computer-readable computer memory medium is storing or executing instructions that, when executed, controls a computer processor to facilitate patent related searches from a patent corpus of patent related publications, by automatically performing citation analysis upon each iteration of a patent related search, the citation analysis comprising citations from a respective face of each patent publication, which lists backward references as well as forward references to patents and/or patent publications, by performing a method comprising: receiving an indication of input text and/or patent related publications as input; automatically analyzing the indicated input using semantic analysis of the indicated source input to automatically extract a first set of search-based keywords and/or phrases that are present in the indicated input, wherein the automatically analyzing the indicated input using semantic analysis parses the indicated source input to determine grammatical usage to automatically extract the first set of search-based keywords and/or phrases; from the automatically determined first set of keywords, performing an initial search iteration automatically, and wherein the initial search iteration is performed without additional user input, by performing the steps of: automatically determining an initial set of patent related publications that include the automatically extracted first set of search-based keywords; automatically determining a correlated set of patent related publications that are correlated to the initial set of patent related publications using automatic citation analysis of the initial set of patent related publications, wherein the correlated set is determined to be one or more patent related publications from the corpus that have unique citation relationships to any one of the patent related publications of the initial set, and wherein the correlated set is automatically sorted based upon the correlated patent related publications that involve the most number of citation paths with the initial set of patent related publications; and automatically extracting from the automatically determined initial set of patent related publications a set of related keywords not found in the first set of keywords or in the source input; and presenting indicators to the determined initial set and the sorted determined correlated set of patent related publications and the set of related keywords as output from the initial search iteration. 36. The computer-readable computer memory medium of claim 30 wherein the citation analysis considers only patent related publications that have more than one unique citation relationship to any one of the intermediate set of patent related publications. | 0.638481 |
4. The method according to claim 1 , wherein the application is further configured to add a CMIS item object type. | 4. The method according to claim 1 , wherein the application is further configured to add a CMIS item object type. 5. The method according to claim 4 , wherein the secondary type object type and the CMIS item object type for the application are primary object types such that CMIS secondary types are attachable to the secondary type object type and the CMIS item object type for the application. | 0.930721 |
1. A method for properly displaying paragraphs of text that use a foreign paragraph delimiter, the foreign paragraph delimiter being different than a native paragraph delimiter of documents created on a word processing system, said method comprising the steps of: (a) producing a character position array in which each character of a document that is open on the word processing system is assigned a position, said character position array being divided into a plurality of pieces, each piece comprising a string of characters that are stored adjacent to one another in a file and which have identical format properties; (b) producing an array of data records including entries that correspond to each piece of the character position array, each entry including a file number and a file position within a file at which the string of characters comprising the piece are stored; (c) producing a file control block for each file storing text used in the document when the file is initially opened by the word processing system; (d) inserting delimiter identification data in the file control block of each file, said delimiter identification data indicating a type of paragraph delimiter used by the text stored in the file; (e) each time that a character of the document is displayed, referring to the character position array and to the array of data records to determine a specific file in which the character is stored, the delimiter identification data in the file control block for said specific file indicating the type of paragraph delimiter that is used for a paragraph containing the character; and (f) if the paragraph containing the character uses a foreign paragraph delimiter, translating the foreign paragraph delimiter to the native paragraph delimiter in a display buffer, so that the paragraph containing the character is properly displayed to the user. | 1. A method for properly displaying paragraphs of text that use a foreign paragraph delimiter, the foreign paragraph delimiter being different than a native paragraph delimiter of documents created on a word processing system, said method comprising the steps of: (a) producing a character position array in which each character of a document that is open on the word processing system is assigned a position, said character position array being divided into a plurality of pieces, each piece comprising a string of characters that are stored adjacent to one another in a file and which have identical format properties; (b) producing an array of data records including entries that correspond to each piece of the character position array, each entry including a file number and a file position within a file at which the string of characters comprising the piece are stored; (c) producing a file control block for each file storing text used in the document when the file is initially opened by the word processing system; (d) inserting delimiter identification data in the file control block of each file, said delimiter identification data indicating a type of paragraph delimiter used by the text stored in the file; (e) each time that a character of the document is displayed, referring to the character position array and to the array of data records to determine a specific file in which the character is stored, the delimiter identification data in the file control block for said specific file indicating the type of paragraph delimiter that is used for a paragraph containing the character; and (f) if the paragraph containing the character uses a foreign paragraph delimiter, translating the foreign paragraph delimiter to the native paragraph delimiter in a display buffer, so that the paragraph containing the character is properly displayed to the user. 7. The method of claim 1, further comprising the steps of determining a beginning paragraph file position for a paragraph in which a specific character of text is found; determining a limit character position of said paragraph; and reporting the size and type of the paragraph delimiter found at the end of said paragraph to determine the delimiter identification data that is inserted into the file control block for the file. | 0.574363 |
8. A system comprising: a processor; and a computer-readable storage device having instructions stored which, when executed by the processor, result in the processor performing operations comprising: receiving a voice message intended for delivery to a device associated with a recipient, the voice message being in a first language; receiving, from the recipient, an access number specific to a second language; translating the voice message into the second language, to yield a translated voice message; and transmitting the translated voice message to the device associated with the recipient. | 8. A system comprising: a processor; and a computer-readable storage device having instructions stored which, when executed by the processor, result in the processor performing operations comprising: receiving a voice message intended for delivery to a device associated with a recipient, the voice message being in a first language; receiving, from the recipient, an access number specific to a second language; translating the voice message into the second language, to yield a translated voice message; and transmitting the translated voice message to the device associated with the recipient. 11. The system of claim 8 , the computer-readable storage device having additional instructions stored which result in the operations further comprising selecting a type of voice to be used in the translating of the voice message based on a preference designated by the recipient in advance. | 0.502212 |
7. The one or more hardware memory of claim 1 , wherein the first set of data items includes data items randomly sampled from a larger set of data items. | 7. The one or more hardware memory of claim 1 , wherein the first set of data items includes data items randomly sampled from a larger set of data items. 8. The one or more hardware memory of claim 7 , wherein prior to scoring the first set of data items with the classifier, the classifier is pre-trained based on data items that are results of a user query. | 0.956282 |
13. The display device of claim 9 , wherein the processor is further configured to voice-recognize the predetermined amount of the audio data; extract at least one query term candidate from a corresponding voice recognition result; output the at least one query term candidate; and receive a command for selecting the query term from the at least one query term candidate. | 13. The display device of claim 9 , wherein the processor is further configured to voice-recognize the predetermined amount of the audio data; extract at least one query term candidate from a corresponding voice recognition result; output the at least one query term candidate; and receive a command for selecting the query term from the at least one query term candidate. 14. The display device of claim 13 , wherein the processor is further configured to provide the user with the at least one query term candidate in a chronological order; and provide the user with an image of the media data while the at least one query term candidate being outputted. | 0.89403 |
7. The method of claim 6 wherein the essential data elements include an identification data element, invoice adjustment base data element, a billing data element, a status data element, and a list of invoice adjustment line item details data element. | 7. The method of claim 6 wherein the essential data elements include an identification data element, invoice adjustment base data element, a billing data element, a status data element, and a list of invoice adjustment line item details data element. 8. The method of claim 7 wherein the common invoice adjustment data object format includes at least one complex data element. | 0.953398 |
10. An apparatus comprising: one or more processors; and a computer readable storage medium having computer readable program code embodied therewith and executable by the one or more processors, the computer readable program code comprising: computer readable program code configured to accept input of a key word; computer readable program code configured to present a list of possible synonyms of the key word; computer readable program code configured to solicit user feedback on whether a possible synonym is a synonym candidate for the key word or not a synonym candidate for the key word, and repeat the soliciting of feedback until a defined endpoint is reached; computer readable program code configured to determine a match score of each of the possible synonyms, the match score incorporating the user feedback as input; computer readable program code configured to retain a number of the possible synonyms up to and including a target number and discarding a number of the possible synonyms in excess of the target number, the discarded synonyms generally having lower match scores than the retained synonyms; wherein said computer readable program code is further configured to: solicit feedback via accepting input of one or more additional key words; and generate an output synonym list subsequent to the inputting of one or more additional key words, the output synonym list including possible synonyms of one or more additional key words; wherein the output synonym list is derived from comparing, between pairs of words, a context of each instance of each one of the one or more key words among a set of documents. | 10. An apparatus comprising: one or more processors; and a computer readable storage medium having computer readable program code embodied therewith and executable by the one or more processors, the computer readable program code comprising: computer readable program code configured to accept input of a key word; computer readable program code configured to present a list of possible synonyms of the key word; computer readable program code configured to solicit user feedback on whether a possible synonym is a synonym candidate for the key word or not a synonym candidate for the key word, and repeat the soliciting of feedback until a defined endpoint is reached; computer readable program code configured to determine a match score of each of the possible synonyms, the match score incorporating the user feedback as input; computer readable program code configured to retain a number of the possible synonyms up to and including a target number and discarding a number of the possible synonyms in excess of the target number, the discarded synonyms generally having lower match scores than the retained synonyms; wherein said computer readable program code is further configured to: solicit feedback via accepting input of one or more additional key words; and generate an output synonym list subsequent to the inputting of one or more additional key words, the output synonym list including possible synonyms of one or more additional key words; wherein the output synonym list is derived from comparing, between pairs of words, a context of each instance of each one of the one or more key words among a set of documents. 15. The apparatus according to claim 10 , wherein said computer readable program code is configured to solicit manually input user feedback. | 0.531737 |
8. A non-transitory computer-readable storage medium storing computer-readable instructions, which when executed, cause a computing device to: store, by at least one processor, first data associated with prior communications sent to a user, the first data comprising a first profile for a caller that creates a voice message for the user, and the prior communications including at least one prior communication received from the caller; send, by the at least one processor, to a speech recognition system, the voice message for transcribing using at least a portion of the first data to provide a transcribed message; receive, from the speech recognition system, the transcribed message; and cause a presentation on a display, the presentation comprising the transcribed message, and the presentation further comprising options for selection of a corrected word by the user to correct a misspelled word in the transcribed message. | 8. A non-transitory computer-readable storage medium storing computer-readable instructions, which when executed, cause a computing device to: store, by at least one processor, first data associated with prior communications sent to a user, the first data comprising a first profile for a caller that creates a voice message for the user, and the prior communications including at least one prior communication received from the caller; send, by the at least one processor, to a speech recognition system, the voice message for transcribing using at least a portion of the first data to provide a transcribed message; receive, from the speech recognition system, the transcribed message; and cause a presentation on a display, the presentation comprising the transcribed message, and the presentation further comprising options for selection of a corrected word by the user to correct a misspelled word in the transcribed message. 9. The storage medium of claim 8 , wherein the first data comprises a plurality of person profiles, including a second profile for a person referenced in the voice message other than the user and the caller. | 0.507225 |
2. The system of claim 1 , further comprising a system management repository that stores server, network and storage information. | 2. The system of claim 1 , further comprising a system management repository that stores server, network and storage information. 4. The system of claim 2 , wherein the meta information module records ontologies to describe the type of information stored in the system management repository. | 0.935044 |
19. A non-transitory computer readable recordable medium comprising computer program instructions which, when executed, cause performance of a method comprising: associating a set of vocal demeanors with a sponsor of a multimodal application, the set of vocal demeanors comprising at least two distinct vocal demeanors; establishing a right, wherein the right is a right to exclude from use within at least a portion of the multimodal application vocal demeanors not within the set of vocal demeanors for presentation of audio content; and providing to a multimodal device an indication of the set of vocal demeanors associated with the sponsor for presentation of audio content of the sponsor and/or an indication of the vocal demeanors covered by the right to exclude. | 19. A non-transitory computer readable recordable medium comprising computer program instructions which, when executed, cause performance of a method comprising: associating a set of vocal demeanors with a sponsor of a multimodal application, the set of vocal demeanors comprising at least two distinct vocal demeanors; establishing a right, wherein the right is a right to exclude from use within at least a portion of the multimodal application vocal demeanors not within the set of vocal demeanors for presentation of audio content; and providing to a multimodal device an indication of the set of vocal demeanors associated with the sponsor for presentation of audio content of the sponsor and/or an indication of the vocal demeanors covered by the right to exclude. 25. The non-transitory computer readable recordable medium of claim 19 , wherein the at least a portion of the multimodal application is accessed via an advertisement of the sponsor within a different portion of the multimodal application. | 0.681491 |
1. A token stitcher for determining whether an input string of characters matches a regular expression comprising a number of sub-expressions, the token stitcher comprising: an input line for receiving tokens, where each token indicates a partial match between the input string and the regular expression; a flag bank storing a number of flags, where each flag, when activated, identifies one or more of the sub-expressions that match the input string; a program memory storing a number of programs, where each program comprises instructions for processing one or more tokens; a token stitcher engine, coupled to a deterministic finite state automaton (DFA) engine and a non-deterministic finite state automaton (NFA) engine which are external to the token stitcher engine, configured to process the tokens generated from the DFA engine or the NFA engine and identify one or more programs stored in the program memory that are associated with a new token received over the input line, wherein the token stitcher engine is implemented by at least one processor-based computing device; and an output line upon which an output match signal may be asserted, wherein a particular program in the program memory is configured to assert the output match signal on the output line when a particular set of flags in the flag bank are asserted. | 1. A token stitcher for determining whether an input string of characters matches a regular expression comprising a number of sub-expressions, the token stitcher comprising: an input line for receiving tokens, where each token indicates a partial match between the input string and the regular expression; a flag bank storing a number of flags, where each flag, when activated, identifies one or more of the sub-expressions that match the input string; a program memory storing a number of programs, where each program comprises instructions for processing one or more tokens; a token stitcher engine, coupled to a deterministic finite state automaton (DFA) engine and a non-deterministic finite state automaton (NFA) engine which are external to the token stitcher engine, configured to process the tokens generated from the DFA engine or the NFA engine and identify one or more programs stored in the program memory that are associated with a new token received over the input line, wherein the token stitcher engine is implemented by at least one processor-based computing device; and an output line upon which an output match signal may be asserted, wherein a particular program in the program memory is configured to assert the output match signal on the output line when a particular set of flags in the flag bank are asserted. 28. The token stitcher of claim 1 , wherein the token stitcher engine processes the tokens generated from the DFA or NFA engines in the same order as the input characters in the input string that resulted in their generation, so that the token stitcher engine does not need to re-order the tokens generated from the DFA or NFA engines. | 0.560013 |
22. An ontology generating system comprising: first software, recorded on a non-transitory computer readable medium, that extracts and stores phrases from at least one text source independent of a domain of the text source; second software, recorded on a non-transitory computer readable medium, that extracts and stores a plurality of core noun phrases from the extracted phrases, wherein the plurality of core noun phrases is identified at least in part based on an absence of each of the plurality of core noun phrases from each of an adjective word list, a verb word list, and a barrier word list; third software, recorded on a computer readable medium, that extracts and stores links from the extracted phrases based at least in part on the plurality of core noun phrases; and fourth software, recorded on a computer readable medium, that generates an ontology for the at least one text source. | 22. An ontology generating system comprising: first software, recorded on a non-transitory computer readable medium, that extracts and stores phrases from at least one text source independent of a domain of the text source; second software, recorded on a non-transitory computer readable medium, that extracts and stores a plurality of core noun phrases from the extracted phrases, wherein the plurality of core noun phrases is identified at least in part based on an absence of each of the plurality of core noun phrases from each of an adjective word list, a verb word list, and a barrier word list; third software, recorded on a computer readable medium, that extracts and stores links from the extracted phrases based at least in part on the plurality of core noun phrases; and fourth software, recorded on a computer readable medium, that generates an ontology for the at least one text source. 23. A system as in claim 22 where the fourth software generates the ontology substantially automatically irrespective of a subject matter of the at least one text source. | 0.54649 |
11. A system comprising: one or more computers and one or more storage devices storing instructions that are operable, when executed by the one or more computers, to cause the one or more computers to perform operations comprising: receiving a query having an original term; determining one or more substitution contexts for the original term, wherein a substitution context includes one or more conditions for substituting an original term with a substitute term, wherein the one or more conditions specify one or more context terms from the query and an indication of a position in the query of the original term relative to the one or more context terms; generating a context hierarchy including the one or more substitution contexts for the original term, wherein any conditions of a parent context in the context hierarchy also apply to each of one or more child contexts of a parent context, and wherein each child context in the context hierarchy includes all of the context terms of a parent context of the child context as well as an additional context term that does not occur in the parent context of the child context; determining a respective score for each substitution context of the one or more substitution contexts including comparing the substitution context to its parent substitution context to compute a measure of how much an additional term of the substitution context adds meaning to the original term when choosing substitute terms for the original term; classifying each of the substitution contexts into a first category or a second category based on a respective score of each substitution context; associating the original term with one or more substitution contexts in the first category; and providing only substitution contexts in the first category to a substitute term generation process that generates substitute terms for the original term in the query. | 11. A system comprising: one or more computers and one or more storage devices storing instructions that are operable, when executed by the one or more computers, to cause the one or more computers to perform operations comprising: receiving a query having an original term; determining one or more substitution contexts for the original term, wherein a substitution context includes one or more conditions for substituting an original term with a substitute term, wherein the one or more conditions specify one or more context terms from the query and an indication of a position in the query of the original term relative to the one or more context terms; generating a context hierarchy including the one or more substitution contexts for the original term, wherein any conditions of a parent context in the context hierarchy also apply to each of one or more child contexts of a parent context, and wherein each child context in the context hierarchy includes all of the context terms of a parent context of the child context as well as an additional context term that does not occur in the parent context of the child context; determining a respective score for each substitution context of the one or more substitution contexts including comparing the substitution context to its parent substitution context to compute a measure of how much an additional term of the substitution context adds meaning to the original term when choosing substitute terms for the original term; classifying each of the substitution contexts into a first category or a second category based on a respective score of each substitution context; associating the original term with one or more substitution contexts in the first category; and providing only substitution contexts in the first category to a substitute term generation process that generates substitute terms for the original term in the query. 20. The system of claim 11 , wherein the operations comprise: determining that no substitution contexts are classified in the first category; and in response to determining that no substitution contexts are in the first category, classifying a general context into the first category. | 0.687003 |
1. A broadcast signal receiver comprising: a text data receiver configured to receive broadcast text data and to transmit the broadcast text data to a user interface, wherein the broadcast text data includes at least one word; a text-to-speech (TTS) converter configured to convert received text data into an audio speech sound, wherein the TTS converter is configured to: detect whether the at least one word is also included in a stored list of words, and when the at least one word is also included in the stored list of words, convert the at least one word according to a conversion defined by the stored list, and when the at least one word is not included in the stored list of words, convert the at least one word according to a set of predetermined conversion rules; a conversion memory configured to store the list of words as initial data; an update receiver configured to receive, from a conversion repository, and via a network connection, update data, wherein the update data includes updated words, associated conversions, and updated conversion rules, and configured to store, in the conversion memory, the update data; and a commander circuitry configured to control an operation of the broadcast signal receiver, wherein the commander circuitry is configured to receive a user control input, wherein the user control input indicates an incorrect conversion carried out by the TTS converter; and wherein the broadcast signal receiver is configured to, in response to the user control input, send a message to a data provider, and thereby request update data, wherein the message indicates a conversion problem and indicates text which was converted, by the TTS converter, into speech. | 1. A broadcast signal receiver comprising: a text data receiver configured to receive broadcast text data and to transmit the broadcast text data to a user interface, wherein the broadcast text data includes at least one word; a text-to-speech (TTS) converter configured to convert received text data into an audio speech sound, wherein the TTS converter is configured to: detect whether the at least one word is also included in a stored list of words, and when the at least one word is also included in the stored list of words, convert the at least one word according to a conversion defined by the stored list, and when the at least one word is not included in the stored list of words, convert the at least one word according to a set of predetermined conversion rules; a conversion memory configured to store the list of words as initial data; an update receiver configured to receive, from a conversion repository, and via a network connection, update data, wherein the update data includes updated words, associated conversions, and updated conversion rules, and configured to store, in the conversion memory, the update data; and a commander circuitry configured to control an operation of the broadcast signal receiver, wherein the commander circuitry is configured to receive a user control input, wherein the user control input indicates an incorrect conversion carried out by the TTS converter; and wherein the broadcast signal receiver is configured to, in response to the user control input, send a message to a data provider, and thereby request update data, wherein the message indicates a conversion problem and indicates text which was converted, by the TTS converter, into speech. 15. The receiver according to claim 1 , wherein the commander circuitry is remote from the broadcast signal receiver. | 0.582093 |
18. A method for controlling a display device, the method comprising: receiving a signal including video data and supplementary information, the supplementary information including text data, position information of the text data relative to the video data, and size information of the text data; displaying the received signal so that the text data overlaps the video data according to the position information and the size information; detecting visual characteristics of the text data; selecting a portion of the video data based on the position information and the size information; detecting visual characteristics of the selected portion; determining a relationship between the video data and the text data based on the detected visual characteristics of the text data and the detected visual characteristics of the selected portion; comparing the determined relationship with at least one reference value; and modifying a criterion of the visual characteristics for the text data or the video data depending on a result of said comparing. | 18. A method for controlling a display device, the method comprising: receiving a signal including video data and supplementary information, the supplementary information including text data, position information of the text data relative to the video data, and size information of the text data; displaying the received signal so that the text data overlaps the video data according to the position information and the size information; detecting visual characteristics of the text data; selecting a portion of the video data based on the position information and the size information; detecting visual characteristics of the selected portion; determining a relationship between the video data and the text data based on the detected visual characteristics of the text data and the detected visual characteristics of the selected portion; comparing the determined relationship with at least one reference value; and modifying a criterion of the visual characteristics for the text data or the video data depending on a result of said comparing. 20. The method according to claim 18 , wherein said criterion modifying comprises at least one of: controlling a color difference between the text data and the video data by controlling a color of the displayed text data; and controlling a luminance of the displayed text data. | 0.639815 |
12. The method of claim 11 wherein a display page is represented as a tag tree with nodes representing elements and the identifying of repeated patterns identifies a reference explanatory text node as a collection of adjacent, sibling nodes with a subtree of one node containing a reference node with associated text. | 12. The method of claim 11 wherein a display page is represented as a tag tree with nodes representing elements and the identifying of repeated patterns identifies a reference explanatory text node as a collection of adjacent, sibling nodes with a subtree of one node containing a reference node with associated text. 13. The method of claim 12 wherein the identifying of repeated patterns identifies a reference explanatory text region as a collection of adjacent, sibling reference explanatory text nodes that have the same length and are similar. | 0.894124 |
12. The apparatus of claim 9 , wherein the data structure in the response identifies at least one entity and includes accessor lambda functions for accessing the at least one entity via respective access protocols. | 12. The apparatus of claim 9 , wherein the data structure in the response identifies at least one entity and includes accessor lambda functions for accessing the at least one entity via respective access protocols. 13. The apparatus of claim 12 , wherein: the data structure identifies a plurality of the entities responsive to a query in the request; the interface circuit configured for receiving a second request from the user interface for executing one of the accessor lambda functions associated with the entities responsive to the query; the execution circuit configured for optimizing the second request based on initiating a shared communication session between the entities responsive to the query and the user interface, according to a prescribed device access protocol associated with the one accessor lambda function. | 0.880861 |
10. The computer-implemented method of claim 1 , wherein determining a navigation score for the revised query comprises: determining a traffic proportion for each resource identified by a search engine in response to the revised query, the traffic proportion being a proportion of traffic from search results generated in response to the query; and the navigation score threshold is a traffic proportion threshold. | 10. The computer-implemented method of claim 1 , wherein determining a navigation score for the revised query comprises: determining a traffic proportion for each resource identified by a search engine in response to the revised query, the traffic proportion being a proportion of traffic from search results generated in response to the query; and the navigation score threshold is a traffic proportion threshold. 11. The computer-implemented method of claim 10 , wherein identifying the navigational resource for the revised query comprises identifying as the navigational resource a resource having a traffic proportion that exceeds the traffic proportion threshold. | 0.914335 |
10. A system for providing a graphical representation of feedback associated with an electronic content item, comprising: a processing unit; and a memory that including computer-readable instructions that, when executed by the processing unit, cause the system to: display a content item in a computer-enabled interface; provide access to the content item for a plurality of reviewers via a collaborative environment; display a feedback interface component within the computer-enabled interface, in response to receiving an instruction to launch the feedback interface component; receive, in the feedback interface component, feedback from a reviewer, wherein the feedback indicates a satisfaction associated with a portion of a plurality of portions in the content item; and display a feedback indicator and comment icon in the feedback interface component, wherein the feedback indicator graphically represents the satisfaction associated with a respective, selected portion of the plurality of portions in the content item, the feedback interface component, including the feedback indicator and comment icon, being displayed at a location depending on the respective, selected portion of the plurality of portions that is associated with the feedback; display, in response to selection of the comment icon in the feedback interface component, a comment user interface for receiving a comment relating to the feedback. | 10. A system for providing a graphical representation of feedback associated with an electronic content item, comprising: a processing unit; and a memory that including computer-readable instructions that, when executed by the processing unit, cause the system to: display a content item in a computer-enabled interface; provide access to the content item for a plurality of reviewers via a collaborative environment; display a feedback interface component within the computer-enabled interface, in response to receiving an instruction to launch the feedback interface component; receive, in the feedback interface component, feedback from a reviewer, wherein the feedback indicates a satisfaction associated with a portion of a plurality of portions in the content item; and display a feedback indicator and comment icon in the feedback interface component, wherein the feedback indicator graphically represents the satisfaction associated with a respective, selected portion of the plurality of portions in the content item, the feedback interface component, including the feedback indicator and comment icon, being displayed at a location depending on the respective, selected portion of the plurality of portions that is associated with the feedback; display, in response to selection of the comment icon in the feedback interface component, a comment user interface for receiving a comment relating to the feedback. 17. The system of claim 10 , wherein display of the feedback indicator is to the plurality of reviewers. | 0.537313 |
10. A handheld electronic device, comprising: a number of keys; an output apparatus; a processor apparatus comprising a processor and a memory in electronic communication with one another, said processor apparatus having stored therein a number of routines which, when executed on said processor, cause said handheld electronic device to perform operations comprising: receiving an input reflecting selection of one of the keys; based at least in part on the key selection, determining whether to output (i) a non-diacritical character or (ii) a diacritical character in, the determination comprising: determining whether the selection corresponds to a first alphanumeric input, based upon a determination that the selection corresponds to the first alphanumeric input, determining to output the non-diacritical character, and based upon a determination that there have been previous alphanumeric inputs, determining whether to output the non-diacritical character or the diacritical character based on whether the previous alphanumeric inputs satisfy a predetermined condition; and outputting the determined output using the output apparatus. | 10. A handheld electronic device, comprising: a number of keys; an output apparatus; a processor apparatus comprising a processor and a memory in electronic communication with one another, said processor apparatus having stored therein a number of routines which, when executed on said processor, cause said handheld electronic device to perform operations comprising: receiving an input reflecting selection of one of the keys; based at least in part on the key selection, determining whether to output (i) a non-diacritical character or (ii) a diacritical character in, the determination comprising: determining whether the selection corresponds to a first alphanumeric input, based upon a determination that the selection corresponds to the first alphanumeric input, determining to output the non-diacritical character, and based upon a determination that there have been previous alphanumeric inputs, determining whether to output the non-diacritical character or the diacritical character based on whether the previous alphanumeric inputs satisfy a predetermined condition; and outputting the determined output using the output apparatus. 12. The handheld electronic device according to claim 10 , wherein the number of routines cause the handheld electronic device to perform operations further comprising detecting an operative language of the handheld electronic device, wherein determining whether to output the non-diacritical character or the diacritical character is at least in part based on the detected operative language. | 0.5 |
8. A system comprising: a communication network providing data communication services to a user device communicatively coupled thereto; and an application server communicatively coupled to the communication network and configured to: receive, from the user device via the communication network, data storing hand-written information obtained from a user of the user device; identify a first gap in the received data storing the hand-written information and a second gap in the received data storing the hand-written information, the second gap being subsequent to the first gap; process, in response to the identifying of the second gap, a portion of the received data storing the hand-written information that is between the first gap and the second gap to identify one or more hand-written characters included in the portion of the received data that is between the first gap and the second gap; determine, based on the identified one or more hand-written characters, whether the identified one or more characters include a command for initiating an action across the communication network; and responsive to determining that the identified one or more characters include the command, automatically perform the action identified by the command included in the one or more hand-written characters across the communication network. | 8. A system comprising: a communication network providing data communication services to a user device communicatively coupled thereto; and an application server communicatively coupled to the communication network and configured to: receive, from the user device via the communication network, data storing hand-written information obtained from a user of the user device; identify a first gap in the received data storing the hand-written information and a second gap in the received data storing the hand-written information, the second gap being subsequent to the first gap; process, in response to the identifying of the second gap, a portion of the received data storing the hand-written information that is between the first gap and the second gap to identify one or more hand-written characters included in the portion of the received data that is between the first gap and the second gap; determine, based on the identified one or more hand-written characters, whether the identified one or more characters include a command for initiating an action across the communication network; and responsive to determining that the identified one or more characters include the command, automatically perform the action identified by the command included in the one or more hand-written characters across the communication network. 14. The system of claim 8 , wherein the user device is a tablet-type user device, and the received data stores hand-written information obtained from the user through an input interface of a display of the tablet-type user device. | 0.6361 |
2. The method of claim 1 further comprising: verifying that the new best guess includes the correct account number by: sending a proposed account number associated with the new best guess to a financial institution; and receiving, from the financial institution, a confirmation that the proposed account number associated with the new best guess indicates valid account data. | 2. The method of claim 1 further comprising: verifying that the new best guess includes the correct account number by: sending a proposed account number associated with the new best guess to a financial institution; and receiving, from the financial institution, a confirmation that the proposed account number associated with the new best guess indicates valid account data. 3. The method of claim 2 further comprising: sending the verified correct number associated with the new best guess to a server, wherein the server is configured to link the financial transaction card to a service provided by a payment service system by storing the verified correct account number associated with the new best guess, in a database, with an association to a user and the service provided by the payment service system. | 0.89312 |
6. The method according to claim 1 , further comprising: generating group layout information for inclusion in layout information used to identify one or more elements of the element group to be rendered for display in the display area. | 6. The method according to claim 1 , further comprising: generating group layout information for inclusion in layout information used to identify one or more elements of the element group to be rendered for display in the display area. 13. The method according to claim 6 , further comprising: storing the group layout information; processing the stored group layout information to identify one or more elements to be rendered for display in the display area, and rendering the identified elements when the one or more elements are to be rendered in a first display state; and re-processing the stored group layout information to identify one or more elements to be rendered for display in the display area, and rendering the identified elements, when the one or more elements are to be rendered in a second, different, display state. | 0.889292 |
6. A system for selecting content for display on a user device via a computer network, comprising: an interface module of a data processing system having one or more processors configured to: receive, from a content provider associated with a content item, content selection criteria specifying types of queries that make the content item eligible to be selected for display along with search results responsive to queries matching the specified types of queries; and receive a search query provided via a user device; a query reference module of the data processing system configured to: determine via a data structure having information about entities, a content selection criteria entity associated with the content selection criteria and one or more related entities that do not appear in the content selection criteria but are related to the content selection criteria entity in the data structure; generate, using the data structure, a content selection criteria structure that includes an entry for the content selection criteria entity, an entry for each entity related to the content selection criteria entity, and a connection between each pair of related entities in the content selection criteria structure, the generated content selection criteria structure being separate from the data structure; determine, via the data structure, a search query entity, and one or more related entities that do not appear in the search query but are related, in the data structure, to the search query entity; generate a query structure that includes an entry for the search query entity, an entry for each entity related to the search query entity, and a connection between each pair of related entities in the query structure, the generated query structure being separate from the content selection criteria structure and the data structure; a matching module of the data processing system configured to determine a match between the content selection criteria structure and the query structure, including matching a topology and content of the content selection criteria structure to a topology and content of the query structure; and a content selector of the data processing system configured to select the content item as a candidate for display on the user device based on the match between the content selection criteria structure and the query structure. | 6. A system for selecting content for display on a user device via a computer network, comprising: an interface module of a data processing system having one or more processors configured to: receive, from a content provider associated with a content item, content selection criteria specifying types of queries that make the content item eligible to be selected for display along with search results responsive to queries matching the specified types of queries; and receive a search query provided via a user device; a query reference module of the data processing system configured to: determine via a data structure having information about entities, a content selection criteria entity associated with the content selection criteria and one or more related entities that do not appear in the content selection criteria but are related to the content selection criteria entity in the data structure; generate, using the data structure, a content selection criteria structure that includes an entry for the content selection criteria entity, an entry for each entity related to the content selection criteria entity, and a connection between each pair of related entities in the content selection criteria structure, the generated content selection criteria structure being separate from the data structure; determine, via the data structure, a search query entity, and one or more related entities that do not appear in the search query but are related, in the data structure, to the search query entity; generate a query structure that includes an entry for the search query entity, an entry for each entity related to the search query entity, and a connection between each pair of related entities in the query structure, the generated query structure being separate from the content selection criteria structure and the data structure; a matching module of the data processing system configured to determine a match between the content selection criteria structure and the query structure, including matching a topology and content of the content selection criteria structure to a topology and content of the query structure; and a content selector of the data processing system configured to select the content item as a candidate for display on the user device based on the match between the content selection criteria structure and the query structure. 9. The system of claim 6 , wherein the data processing system is further configured to: match one or more entities related to the content selection criteria entity with one or more entities related to the search query entity. | 0.52501 |
14. A computer-readable storage device having stored thereon computer-executable instructions that, when executed by at least one processor, perform a method of multilingual asynchronous communications, the method comprising: receiving, by a recipient multilingual communications application of a recipient computing device, from a sender multilingual communications application of a sender computing device, a first speech message recorded in a first digital media file, wherein the first speech message is received via the sender multilingual communications application from a first user; converting, by the recipient multilingual communications application, the first speech message to a text representation of the first speech message; identifying, by the recipient multilingual communications application, that the text representation of the first speech message is in a source language that is not a predetermined target language; translating, by the recipient multilingual communications application in the recipient computing device of a second user, the text representation of the first speech message in the source language to a translated text representation of the first speech message in the target language, wherein the recipient multilingual communications application in the recipient computing device of the second user translates the text representation of the first speech message to the translated text representation of the first speech message in the target language based on the received first digital media file; converting, by the recipient multilingual communications application, the translated text representation of the first speech message to synthesized speech in the target language; recording, by the recipient multilingual communications application, the synthesized speech in the target language in a second digital media file; playing the second digital media file thereby rendering the synthesized speech to the second user, receiving, by the recipient multilingual communications application, from the second user, a second speech message in the target language comprising a response to the synthesized speech; and transmitting the second speech message to the sender multilingual communications application. | 14. A computer-readable storage device having stored thereon computer-executable instructions that, when executed by at least one processor, perform a method of multilingual asynchronous communications, the method comprising: receiving, by a recipient multilingual communications application of a recipient computing device, from a sender multilingual communications application of a sender computing device, a first speech message recorded in a first digital media file, wherein the first speech message is received via the sender multilingual communications application from a first user; converting, by the recipient multilingual communications application, the first speech message to a text representation of the first speech message; identifying, by the recipient multilingual communications application, that the text representation of the first speech message is in a source language that is not a predetermined target language; translating, by the recipient multilingual communications application in the recipient computing device of a second user, the text representation of the first speech message in the source language to a translated text representation of the first speech message in the target language, wherein the recipient multilingual communications application in the recipient computing device of the second user translates the text representation of the first speech message to the translated text representation of the first speech message in the target language based on the received first digital media file; converting, by the recipient multilingual communications application, the translated text representation of the first speech message to synthesized speech in the target language; recording, by the recipient multilingual communications application, the synthesized speech in the target language in a second digital media file; playing the second digital media file thereby rendering the synthesized speech to the second user, receiving, by the recipient multilingual communications application, from the second user, a second speech message in the target language comprising a response to the synthesized speech; and transmitting the second speech message to the sender multilingual communications application. 16. The computer-readable storage device of claim 14 , wherein the method further comprises: recording the second speech response message in the target language. | 0.81326 |
12. The computing system of claim 11 where the triple consolidation logic deletes duplicate triples. | 12. The computing system of claim 11 where the triple consolidation logic deletes duplicate triples. 13. The computing system of claim 12 comprising a partitioned temporary table in remote access memory in which triples asserted in the semantic model and triples inferred using inference rules in the semantic model are stored by the inference engine. | 0.934431 |
1. A computer-implemented data mining method, comprising: storing, in an electronic data repository, user activity data associated with each of a plurality of users of an online system that provides access to an electronic catalog, said user activity data reflecting user-generated events associated with particular items represented in the electronic catalog; programmatically identifying, among the plurality of users, a subset of users whose email addresses are associated with a particular organization; programmatically analyzing the user activity data associated with the plurality of users, including the subset of users, by execution of code by a computer processor, to identify a set of items that have experienced significantly higher levels of user activity among the subset of users than among the plurality of users; and creating, in computer storage, an association between the organization and the identified set of items. | 1. A computer-implemented data mining method, comprising: storing, in an electronic data repository, user activity data associated with each of a plurality of users of an online system that provides access to an electronic catalog, said user activity data reflecting user-generated events associated with particular items represented in the electronic catalog; programmatically identifying, among the plurality of users, a subset of users whose email addresses are associated with a particular organization; programmatically analyzing the user activity data associated with the plurality of users, including the subset of users, by execution of code by a computer processor, to identify a set of items that have experienced significantly higher levels of user activity among the subset of users than among the plurality of users; and creating, in computer storage, an association between the organization and the identified set of items. 15. The method of claim 1 , wherein the items include movie titles rented by users. | 0.627724 |
1. A method of determining a relation between search queries, the method comprising: maintaining a database that associates a search session with at least one search query which has been received from a user terminal during said search session, wherein the database is updated at predetermined time intervals, said database being stored in a memory; determining a total number of search sessions for each user terminal during a first time interval, by referring to said database; determining a first number of search sessions where a first search query is received from said each user terminal during said first time interval, by referring to said database; determining a second number of search sessions where a second search query is received from said each user terminal during said first time interval, by referring to said database; determining a third number of search sessions where both said first search query and said second search query are received from said each user terminal during said first time interval, by referring to said database; calculating conditional probability from comparing said determined first number of search sessions where said first search query is received with said determined third number of search sessions where both said first search query and said second search query are received; calculating correlation by using said total number of search sessions, said first number of search sessions, said second number of search sessions, and said third number of search sessions; and determining a relation between said first search query and said second search query, based, at least in part, upon said calculated conditional probability and said calculated correlation, wherein said steps of calculating conditional probability and calculating correlation are performed by a processor. | 1. A method of determining a relation between search queries, the method comprising: maintaining a database that associates a search session with at least one search query which has been received from a user terminal during said search session, wherein the database is updated at predetermined time intervals, said database being stored in a memory; determining a total number of search sessions for each user terminal during a first time interval, by referring to said database; determining a first number of search sessions where a first search query is received from said each user terminal during said first time interval, by referring to said database; determining a second number of search sessions where a second search query is received from said each user terminal during said first time interval, by referring to said database; determining a third number of search sessions where both said first search query and said second search query are received from said each user terminal during said first time interval, by referring to said database; calculating conditional probability from comparing said determined first number of search sessions where said first search query is received with said determined third number of search sessions where both said first search query and said second search query are received; calculating correlation by using said total number of search sessions, said first number of search sessions, said second number of search sessions, and said third number of search sessions; and determining a relation between said first search query and said second search query, based, at least in part, upon said calculated conditional probability and said calculated correlation, wherein said steps of calculating conditional probability and calculating correlation are performed by a processor. 5. The method of claim 1 , wherein a close relation between said first search query and said second search query is determined if the click rate information is greater than a predetermined numerical value. | 0.65825 |
20. The system of claim 19 , wherein the scene recognition technology comprises image recognition. | 20. The system of claim 19 , wherein the scene recognition technology comprises image recognition. 22. The system of claim 20 , wherein the image recognition comprises recognition of a sports apparatus. | 0.978369 |
9. A method comprising: identifying a term of a search request as a meta keyword, the meta-keyword having a relationship with one or more different words, the relationship being an “is-a” relationship between the one or more different words and the meta-keywords; obtaining a plurality of keywords associated with the meta-keyword; providing the plurality of keywords for presentation; receiving a keyword selection from the plurality of keywords; performing a search using the keyword selection to obtain a result, and providing the result to a client machine of performing the search for presentation, the result being provided in a plurality of tabbed pages, a first tabbed page of the plurality of tabbed pages including a first keyword of the plurality of keywords and a first portion of the result corresponding to the first keyword, a second tabbed page of the plurality of tabbed pages including a second keyword of the plurality of keywords and a second portion of the result corresponding to the second keyword, wherein the plurality of the linguistically transformed keywords comprises at least one of a hyponym keyword, a hypernym keyword, a meronym keyword, a holonym keyword, a derived keyword, a sounds-like keyword, or combination thereof. | 9. A method comprising: identifying a term of a search request as a meta keyword, the meta-keyword having a relationship with one or more different words, the relationship being an “is-a” relationship between the one or more different words and the meta-keywords; obtaining a plurality of keywords associated with the meta-keyword; providing the plurality of keywords for presentation; receiving a keyword selection from the plurality of keywords; performing a search using the keyword selection to obtain a result, and providing the result to a client machine of performing the search for presentation, the result being provided in a plurality of tabbed pages, a first tabbed page of the plurality of tabbed pages including a first keyword of the plurality of keywords and a first portion of the result corresponding to the first keyword, a second tabbed page of the plurality of tabbed pages including a second keyword of the plurality of keywords and a second portion of the result corresponding to the second keyword, wherein the plurality of the linguistically transformed keywords comprises at least one of a hyponym keyword, a hypernym keyword, a meronym keyword, a holonym keyword, a derived keyword, a sounds-like keyword, or combination thereof. 10. The method of claim 9 , wherein the identifying comprises: determining whether the term matches the meta-keyword on a list including a plurality of meta-keywords. | 0.648028 |
13. The portable electronic device of claim 12 wherein the first voice model is associated with the document prior to the user-based selection of the first portions. | 13. The portable electronic device of claim 12 wherein the first voice model is associated with the document prior to the user-based selection of the first portions. 14. The portable electronic device of claim 13 wherein the first voice model comprises a default voice model. | 0.943727 |
24. A method of writing a block of user data to a tape storage medium, said method comprising: arranging said block of user data into an array of bytes, said array arranged as a plurality of rows and a plurality of columns of said bytes; and applying an error correction code to individual ones of said rows of bytes, wherein applying the error correction code to each said individual row of bytes results in the individual row having four interleaved code words, wherein each of the four interleaved code words in the corresponding error correction coded row comprises data bytes and error correcting bytes, each of said rows comprising 128 bytes, each of said columns comprising 124 bytes; and writing said error correction coded rows each comprising four interleaved code words into a diagonal track that extends diagonally across a width of the tape storage medium. | 24. A method of writing a block of user data to a tape storage medium, said method comprising: arranging said block of user data into an array of bytes, said array arranged as a plurality of rows and a plurality of columns of said bytes; and applying an error correction code to individual ones of said rows of bytes, wherein applying the error correction code to each said individual row of bytes results in the individual row having four interleaved code words, wherein each of the four interleaved code words in the corresponding error correction coded row comprises data bytes and error correcting bytes, each of said rows comprising 128 bytes, each of said columns comprising 124 bytes; and writing said error correction coded rows each comprising four interleaved code words into a diagonal track that extends diagonally across a width of the tape storage medium. 32. The method of claim 24 , further comprising applying error correction coding to each of the columns to form two code words in each column, wherein the two code words in each column are interleaved such that portions of the two code words are interleaved along the column. | 0.661323 |
13. A server device, comprising: a processor; a computer-readable memory device including a document identification index and a document action map; and a network connection that receives from a network a sequence of characters optically or acoustically captured from a rendered document by a capture device and transmitted to the network connection via the network, wherein the processor identifies, from the document identification index, a document that that includes a sequence of characters that matches the captured sequence of characters, wherein the processor identifies, from the document identification index, a position, within the identified document, of the sequence of characters that matches the captured sequence of characters, and wherein the processor identifies, from the document action map, a word, phrase or symbol that is within the sequence of characters at the identified position within the identified document and that is associated with an action. | 13. A server device, comprising: a processor; a computer-readable memory device including a document identification index and a document action map; and a network connection that receives from a network a sequence of characters optically or acoustically captured from a rendered document by a capture device and transmitted to the network connection via the network, wherein the processor identifies, from the document identification index, a document that that includes a sequence of characters that matches the captured sequence of characters, wherein the processor identifies, from the document identification index, a position, within the identified document, of the sequence of characters that matches the captured sequence of characters, and wherein the processor identifies, from the document action map, a word, phrase or symbol that is within the sequence of characters at the identified position within the identified document and that is associated with an action. 15. The server device of claim 13 , further comprising: a user profile stored in the computer-readable memory device, wherein the user profile comprises data about a person, wherein the processor uses the user profile to select between alternative actions that are available to be performed for the identified word, phrase or symbol, and wherein the processor performs an alternative action selected by the processor. | 0.511691 |
12. The method of claim 1 , wherein the summary information comprises weighted frequency information. | 12. The method of claim 1 , wherein the summary information comprises weighted frequency information. 13. The method of claim 12 , wherein query predicates, a relevance calculation, an aggregation, or query refinements are defined at least partly in terms of one of Java™ source code or byte code, XPatch or XQuery, or ontology languages. | 0.934997 |
1. A method performed by one or more devices, the method comprising: determining, by one or more processors of the one or more devices, an amount or rate that a document moves positions in search result rankings over time, compared to one or more prior positions of the document in the search result rankings; generating, by one or more processors of the one or more devices, a score for the document based on the amount or rate that the document moves in the search result rankings over time, compared to the one or more prior positions of the document in the search result rankings; and ranking, by one or more processors of the one or more devices, the document with regard to at least one other document based on the score. | 1. A method performed by one or more devices, the method comprising: determining, by one or more processors of the one or more devices, an amount or rate that a document moves positions in search result rankings over time, compared to one or more prior positions of the document in the search result rankings; generating, by one or more processors of the one or more devices, a score for the document based on the amount or rate that the document moves in the search result rankings over time, compared to the one or more prior positions of the document in the search result rankings; and ranking, by one or more processors of the one or more devices, the document with regard to at least one other document based on the score. 4. The method of claim 1 , where the score is a first score, the method further comprising: determining a frequency at which the document is selected over time when the document is included in a set of search results; generating a second score for the document based on the frequency at which the document is selected over time when the document is included in a set of search results; and ranking the document with regard to at least one other document based on the second score. | 0.527747 |
2. The method of claim 1 , wherein determining the measure of specificity for the selected hypernym comprises: determining the probability distribution for co-occurrence of the terms in the set of queries that are hyponyms of the selected hypernym; determining the background probability distribution for the occurrence of the terms in the set of queries; calculating the measure of specificity for the selected hypernym, based on comparing the probability distribution of the co-occurrence of the terms in the set of queries and the background probability distribution. | 2. The method of claim 1 , wherein determining the measure of specificity for the selected hypernym comprises: determining the probability distribution for co-occurrence of the terms in the set of queries that are hyponyms of the selected hypernym; determining the background probability distribution for the occurrence of the terms in the set of queries; calculating the measure of specificity for the selected hypernym, based on comparing the probability distribution of the co-occurrence of the terms in the set of queries and the background probability distribution. 3. The method of claim 2 , wherein the measure of specificity for the selected hypernym is measured using Kullback-Leibler (KL) divergence between the probability distribution for co-occurrence of the terms in the set of queries and the background probability distribution. | 0.82772 |
1. A method executed on a computer system comprising: Receiving one or more initial search terms describing one or more objects in a server management system; Automatically determining one or more suggested search terms in response to the receiving the one or more initial search terms; Displaying the one or more suggested search terms to the user; Receiving a user selection of a subset of the one or more suggested search terms; Searching for object definitions which match the one or more search terms; Determining one or more matching objects corresponding to the object definitions which match the one or more search terms; and Reporting the one or more matching objects, wherein reporting the one or more matching objects comprises reporting that a first matching object is defined in at least a first management context and a second management context, wherein the first management context relates to management of a first category of resources, and wherein the second management context relates to management of a second category of resources. | 1. A method executed on a computer system comprising: Receiving one or more initial search terms describing one or more objects in a server management system; Automatically determining one or more suggested search terms in response to the receiving the one or more initial search terms; Displaying the one or more suggested search terms to the user; Receiving a user selection of a subset of the one or more suggested search terms; Searching for object definitions which match the one or more search terms; Determining one or more matching objects corresponding to the object definitions which match the one or more search terms; and Reporting the one or more matching objects, wherein reporting the one or more matching objects comprises reporting that a first matching object is defined in at least a first management context and a second management context, wherein the first management context relates to management of a first category of resources, and wherein the second management context relates to management of a second category of resources. 19. The method of claim 1 , wherein the first management context comprises a server management context; wherein the first category of resources comprises a plurality of objects usable for server management; wherein the second management context comprises a cluster management context; and wherein the second category of resources comprises a plurality of objects usable for cluster management. | 0.652579 |
1. A harmonized governance system for a heterogeneous agile environment, comprising: one or more computing devices configured as: a computer-based policy administration element (PAE) communicatively coupled to respective management platforms of a plurality of individual agile environments that make up the heterogeneous agile environment, the PAE configured to administer and report governance policies, including rules, roles and assignment to resources of the heterogeneous agile environment according to abstracted and normalized (i) representations of the resources, (ii) operations which are performed by and on said resources, and (iii) roles assignable to one or more subjects that will interact with said resources, and (iv) respective attributes of said representations, operations and roles; and a computer-based policy decision element (PDE) communicatively coupled to receive indications of attempted governance operations by the one or more subjects to resources within the individual agile environments that make up the heterogeneous agile environment, the PDE configured to determine and report whether the attempted governance operations should be permitted or not; one or more data sources accessible to the PAE and the PDE storing information about (i) the one or more subjects and respective attributes thereof, and (ii) resources of the heterogeneous agile environment and respective attributes of said resources, wherein different respective ones of the individual agile environments that make up the heterogeneous agile environment have individual, associated access policies for resources within the respective individual agile environments; each respective individual agile environment has an associated, respective access control system for subjects, resources, and operations of the respective individual agile environment; and the resources of each respective individual agile environment comprise one or more of computer systems, network systems, application containers, application systems, management systems, and storage systems, wherein the PAE is further configured to (i) in response to receiving a new attribute concerning a resource of an individual agile environment that is not yet mapped to an abstracted, normalized attribute of the heterogeneous agile environment, mapping the new attribute to the abstracted, normalized attribute, and saving the mapping of the new attribute to the one or more data sources, (ii) in response to receiving a new operation concerning a resource of the individual agile environment that is not yet mapped to the abstracted, normalized operation of the heterogeneous agile environment, mapping the new operation to the abstracted, normalized operation, and saving the mapping of the new operation to the one or more data sources, and (iii) define new abstracted access control policies based on the abstracted roles, abstracted operations and abstracted resources. | 1. A harmonized governance system for a heterogeneous agile environment, comprising: one or more computing devices configured as: a computer-based policy administration element (PAE) communicatively coupled to respective management platforms of a plurality of individual agile environments that make up the heterogeneous agile environment, the PAE configured to administer and report governance policies, including rules, roles and assignment to resources of the heterogeneous agile environment according to abstracted and normalized (i) representations of the resources, (ii) operations which are performed by and on said resources, and (iii) roles assignable to one or more subjects that will interact with said resources, and (iv) respective attributes of said representations, operations and roles; and a computer-based policy decision element (PDE) communicatively coupled to receive indications of attempted governance operations by the one or more subjects to resources within the individual agile environments that make up the heterogeneous agile environment, the PDE configured to determine and report whether the attempted governance operations should be permitted or not; one or more data sources accessible to the PAE and the PDE storing information about (i) the one or more subjects and respective attributes thereof, and (ii) resources of the heterogeneous agile environment and respective attributes of said resources, wherein different respective ones of the individual agile environments that make up the heterogeneous agile environment have individual, associated access policies for resources within the respective individual agile environments; each respective individual agile environment has an associated, respective access control system for subjects, resources, and operations of the respective individual agile environment; and the resources of each respective individual agile environment comprise one or more of computer systems, network systems, application containers, application systems, management systems, and storage systems, wherein the PAE is further configured to (i) in response to receiving a new attribute concerning a resource of an individual agile environment that is not yet mapped to an abstracted, normalized attribute of the heterogeneous agile environment, mapping the new attribute to the abstracted, normalized attribute, and saving the mapping of the new attribute to the one or more data sources, (ii) in response to receiving a new operation concerning a resource of the individual agile environment that is not yet mapped to the abstracted, normalized operation of the heterogeneous agile environment, mapping the new operation to the abstracted, normalized operation, and saving the mapping of the new operation to the one or more data sources, and (iii) define new abstracted access control policies based on the abstracted roles, abstracted operations and abstracted resources. 7. The harmonized governance system of claim 1 , further comprising: a computer-based policy provisioning element (PPE) configured to translate the abstracted, normalized access control policies defined by the PAE into respective management platform-specific access control policies, and provision the management platform-specific access control policies to the respective management platforms. | 0.521613 |
1. A device that processes MPEG-4 data having a scene description graph and data related to at least one object, the device comprising: means for interacting with a user configured for basic user interaction via control signals from at least one user input device; a binary format of scene description graph interpreter connected to the means for interacting with the user for interpreting the MPEG-4 data to yield interpreted MPEG-4 data; and a media decoder, compositor and renderer that receives the interpreted MPEG-4 data and presents at least one object on the means for interacting with the user, wherein at least one of the binary format of scene description graph interpreter and the media decoder, compositor and renderer comprises at least one programmer interface accessible via the means for interacting with the user, and wherein at least one of the means for interacting with the user and the binary format of scene description graph interpreter is further configured for local user interaction via at least one script obtained from a JavaScript interpreter. | 1. A device that processes MPEG-4 data having a scene description graph and data related to at least one object, the device comprising: means for interacting with a user configured for basic user interaction via control signals from at least one user input device; a binary format of scene description graph interpreter connected to the means for interacting with the user for interpreting the MPEG-4 data to yield interpreted MPEG-4 data; and a media decoder, compositor and renderer that receives the interpreted MPEG-4 data and presents at least one object on the means for interacting with the user, wherein at least one of the binary format of scene description graph interpreter and the media decoder, compositor and renderer comprises at least one programmer interface accessible via the means for interacting with the user, and wherein at least one of the means for interacting with the user and the binary format of scene description graph interpreter is further configured for local user interaction via at least one script obtained from a JavaScript interpreter. 21. The device of claim 1 , further comprising an adaptive audio visual session connected to the means for interacting with the user. | 0.657225 |
1. A computer generated entity, comprising: a plurality of attributes, wherein at least one such attribute defines the vitality of the entity; and a plurality of actions, at least one of which will affect the vitality of the entity; wherein said actions simulate actions by the entity on objects in an environment; the environment is a computer generated simulated environment; and the computer generated entity identifies the objects by calculating one or more percepts identified with the objects. | 1. A computer generated entity, comprising: a plurality of attributes, wherein at least one such attribute defines the vitality of the entity; and a plurality of actions, at least one of which will affect the vitality of the entity; wherein said actions simulate actions by the entity on objects in an environment; the environment is a computer generated simulated environment; and the computer generated entity identifies the objects by calculating one or more percepts identified with the objects. 3. The computer generated entity of claim 1 , wherein: vitality level is determined by a quantity of energy packets. | 0.700559 |
3. The method of claim 2 , wherein each language model rules includes one or more adjustment factors for adjusting a probability value of a word sequence in the base language model. | 3. The method of claim 2 , wherein each language model rules includes one or more adjustment factors for adjusting a probability value of a word sequence in the base language model. 4. The method of claim 3 , wherein a magnitude of each adjustment factor depends on query frequency information. | 0.936517 |
21. A non-transitory computer-readable storage medium with an executable program stored thereon, wherein the program instructs a microprocessor to: enable, via a user interface of a message communication device, a first message configuration to be used when replying to a first electronic message received from a source internal to a particular organization, the first message configuration including a first text, wherein the particular organization represents a category, users internal to the particular organization are included in the category and users external to the particular organization are not included in the category, and the category is one of personal, customer, and supplier; enable, via the user interface of the message communication device, a second message configuration to be used when replying to a second electronic message received from a source external to the particular organization, the second message configuration including a second text; store the first message configuration and the second message configuration; receive a message from a source; after receiving the message, receive, from a user of the message communication device, a third text, wherein the third text is a new reply electronic message corresponding to the received message, and the third text is different than text of the received message; and automatically append one of the first text of the first message configuration or the second text of the second message configuration to the third text for the new reply electronic message based on the source of the received message associated with the new reply electronic message. | 21. A non-transitory computer-readable storage medium with an executable program stored thereon, wherein the program instructs a microprocessor to: enable, via a user interface of a message communication device, a first message configuration to be used when replying to a first electronic message received from a source internal to a particular organization, the first message configuration including a first text, wherein the particular organization represents a category, users internal to the particular organization are included in the category and users external to the particular organization are not included in the category, and the category is one of personal, customer, and supplier; enable, via the user interface of the message communication device, a second message configuration to be used when replying to a second electronic message received from a source external to the particular organization, the second message configuration including a second text; store the first message configuration and the second message configuration; receive a message from a source; after receiving the message, receive, from a user of the message communication device, a third text, wherein the third text is a new reply electronic message corresponding to the received message, and the third text is different than text of the received message; and automatically append one of the first text of the first message configuration or the second text of the second message configuration to the third text for the new reply electronic message based on the source of the received message associated with the new reply electronic message. 28. The computer-readable storage medium of claim 21 , wherein the program instructs the microprocessor to: receive, by an associated message server, the first message configuration and the second message configuration; and transmit, by the associated message server, automatic reply electronic messages in accordance with the first message configuration and the second message configuration. | 0.504854 |
1. A computer implemented method for analyzing performance of components of a database cluster by transforming discrete events into a time series to identify dominant signals, the method comprising: sampling, using a measurement instrument, a plurality of discrete event measurements of the database cluster to produce a set of timestamped events, the database cluster comprising a plurality of nodes that share a shared resource, and the plurality of discrete event measurements obtained from multiple ones of the plurality of nodes; tagging at least one of the timestamped events sampled by one or more hardware components or one or more software components of the database cluster with a semantic tag, wherein tagging the at least one of the timestamped events with the semantic tag comprises assigning a state corresponding to the shared resource of the database cluster, the semantic tag includes at least a first state of waiting for the shared resource and a second state of obtaining access to the shared resource; generating a single magnitude value for a related set of the timestamped events for multiple sessions with respect to the semantic tag for the first state of waiting for the shared resource or the second state of obtaining access to the shared resource by applying different weighting factors to some or all of the sessions of the timestamped events corresponding to the first and second state to derive the single magnitude value; formatting the set of timestamped events into a time series, wherein a time series entry comprises a time indication and a plurality of values, at least one of the plurality of values corresponding to the single magnitude value generated for the related set of the semantic tag for the multiple sessions in the database cluster; and processing the time series to identify at least one state signal. | 1. A computer implemented method for analyzing performance of components of a database cluster by transforming discrete events into a time series to identify dominant signals, the method comprising: sampling, using a measurement instrument, a plurality of discrete event measurements of the database cluster to produce a set of timestamped events, the database cluster comprising a plurality of nodes that share a shared resource, and the plurality of discrete event measurements obtained from multiple ones of the plurality of nodes; tagging at least one of the timestamped events sampled by one or more hardware components or one or more software components of the database cluster with a semantic tag, wherein tagging the at least one of the timestamped events with the semantic tag comprises assigning a state corresponding to the shared resource of the database cluster, the semantic tag includes at least a first state of waiting for the shared resource and a second state of obtaining access to the shared resource; generating a single magnitude value for a related set of the timestamped events for multiple sessions with respect to the semantic tag for the first state of waiting for the shared resource or the second state of obtaining access to the shared resource by applying different weighting factors to some or all of the sessions of the timestamped events corresponding to the first and second state to derive the single magnitude value; formatting the set of timestamped events into a time series, wherein a time series entry comprises a time indication and a plurality of values, at least one of the plurality of values corresponding to the single magnitude value generated for the related set of the semantic tag for the multiple sessions in the database cluster; and processing the time series to identify at least one state signal. 6. The method of claim 1 , further comprising extracting a dominant signal from the time series. | 0.949689 |
1. A method for use in converting semantic information from a source form to a target form, comprising the steps of: obtaining an input string comprising a portion of the semantic information for conversion from said source form to said target form; first identifying a source term of said input string for conversion, wherein a context of said source term is ambiguous; second identifying a plurality of potential subject matter contexts of said input string including a plurality of different usage contexts for said source term in said source form from a portion of the semantic information other than said input string, wherein said plurality of different usage contexts represent identified potential usage contexts of said contextually ambiguous source term that are identified from said semantic information other than said input string in said source form of said semantic information; based on said plurality of subject matter contexts, establishing a set of at least two alternative candidate conversion terms in said target form for said source term, wherein said alternative candidate conversion terms comprise different possible representations of said contextually ambiguous source term in said target form corresponding to different ones of said plurality of different potential usage contexts; performing, using a computer based system, a statistical analysis at least partially based on said plurality of different usage contexts corresponding to said alternative candidate conversion terms, said statistical analysis including establishing a statistical probability for each of said alternative candidate conversion terms and selecting a selected one of said alternative candidate conversion terms having a highest probability of corresponding to a correct usage context of the source term in said string; and using said selected one of said alternative conversion terms to convert said source term from said source form to said target form. | 1. A method for use in converting semantic information from a source form to a target form, comprising the steps of: obtaining an input string comprising a portion of the semantic information for conversion from said source form to said target form; first identifying a source term of said input string for conversion, wherein a context of said source term is ambiguous; second identifying a plurality of potential subject matter contexts of said input string including a plurality of different usage contexts for said source term in said source form from a portion of the semantic information other than said input string, wherein said plurality of different usage contexts represent identified potential usage contexts of said contextually ambiguous source term that are identified from said semantic information other than said input string in said source form of said semantic information; based on said plurality of subject matter contexts, establishing a set of at least two alternative candidate conversion terms in said target form for said source term, wherein said alternative candidate conversion terms comprise different possible representations of said contextually ambiguous source term in said target form corresponding to different ones of said plurality of different potential usage contexts; performing, using a computer based system, a statistical analysis at least partially based on said plurality of different usage contexts corresponding to said alternative candidate conversion terms, said statistical analysis including establishing a statistical probability for each of said alternative candidate conversion terms and selecting a selected one of said alternative candidate conversion terms having a highest probability of corresponding to a correct usage context of the source term in said string; and using said selected one of said alternative conversion terms to convert said source term from said source form to said target form. 11. The method as set forth in claim 1 , wherein said step of second identifying comprises determining said plurality of usage contexts from analyzing metadata associated with said input string describing a semantic information content of said input string. | 0.501422 |
1. A method for automatically generating a text message from an arbitrary speech input, comprising steps for: receiving a statistical language model trained using one or more sets of real-world text messages as training input; receiving a text message database constructed using a subset including some or all of the text messages in the one or more sets of real-world text messages received as the training input; receiving an arbitrary user speech input; evaluating the speech input relative to the probabilistic model and text message database to return a set of one or more probable speech recognition hypotheses corresponding to the arbitrary user speech input; identifying a set of one or more text messages from the text message database as probabilistic matches to one or more of the speech recognition hypotheses; ranking the probabilistically matching text messages in an order corresponding to a probabilistic confidence score associated with each speech recognition hypothesis; selecting the highest ranked text message to paraphrase the arbitrary user speech input; and transmitting the single selected text message to one or more recipients. | 1. A method for automatically generating a text message from an arbitrary speech input, comprising steps for: receiving a statistical language model trained using one or more sets of real-world text messages as training input; receiving a text message database constructed using a subset including some or all of the text messages in the one or more sets of real-world text messages received as the training input; receiving an arbitrary user speech input; evaluating the speech input relative to the probabilistic model and text message database to return a set of one or more probable speech recognition hypotheses corresponding to the arbitrary user speech input; identifying a set of one or more text messages from the text message database as probabilistic matches to one or more of the speech recognition hypotheses; ranking the probabilistically matching text messages in an order corresponding to a probabilistic confidence score associated with each speech recognition hypothesis; selecting the highest ranked text message to paraphrase the arbitrary user speech input; and transmitting the single selected text message to one or more recipients. 10. The method of claim 1 wherein the text messages in the text message database are clustered into classes, and wherein no more than one text message is selected from each class when identifying the set of text messages as probabilistic matches to the speech recognition hypotheses. | 0.587036 |
15. An annotator according to claim 13, further comprising transformation means for transforming a natural language between sound and text representations, wherein the transformation means includes means for resolving ambivalent representations of words by selection of the word whose tag is consistent with the syntactic context of the ambivalent word. | 15. An annotator according to claim 13, further comprising transformation means for transforming a natural language between sound and text representations, wherein the transformation means includes means for resolving ambivalent representations of words by selection of the word whose tag is consistent with the syntactic context of the ambivalent word. 17. An annotator according to claim 15, wherein the transformation means is a sound-to-text transformation system and the ambivalent representations are homonyms. | 0.941619 |
1. A method comprising: transforming an audio input signal, using one or more processors of a system, into a first sequence of feature vectors and a second sequence of feature vectors, both the first and second sequences of feature vectors corresponding in common to a sequence of temporal frames of the audio input signal, wherein each respective feature vector of the first sequence and a corresponding respective feature vector of the second sequence bear quantitative measures of acoustic properties of a corresponding, respective temporal frame of the sequence of temporal frames of the audio input signal; processing the first sequence of feature vectors with a neural network (NN) implemented by the one or more processors of the system to generate a NN-based set of emission probabilities for a plurality of hidden Markov models (HMMs) implemented by the one or more processors of the system; processing the second sequence of feature vectors with a Gaussian mixture model (GMM) implemented by the one or more processors of the system to generate a GMM-based set of emission probabilities for the plurality of HMMs; by computing, for each temporal frame, weighted sums of the NN-based emission probabilities and the GMM-based emission probabilities, merging the NN-based set of emission probabilities with the GMM-based set of emission probabilities to generate a merged set of emission probabilities for the plurality of HMMs; and applying the merged set of emission probabilities to the plurality of HMMs to determine speech content corresponding to the sequence of temporal frames of the audio input signal, wherein the weighted sums are computed according to weights computationally-determined by at least one processor during to a training process that minimizes a computationally-determined difference between computationally-predicted speech in training temporal frames and predetermined speech in the training temporal frames. | 1. A method comprising: transforming an audio input signal, using one or more processors of a system, into a first sequence of feature vectors and a second sequence of feature vectors, both the first and second sequences of feature vectors corresponding in common to a sequence of temporal frames of the audio input signal, wherein each respective feature vector of the first sequence and a corresponding respective feature vector of the second sequence bear quantitative measures of acoustic properties of a corresponding, respective temporal frame of the sequence of temporal frames of the audio input signal; processing the first sequence of feature vectors with a neural network (NN) implemented by the one or more processors of the system to generate a NN-based set of emission probabilities for a plurality of hidden Markov models (HMMs) implemented by the one or more processors of the system; processing the second sequence of feature vectors with a Gaussian mixture model (GMM) implemented by the one or more processors of the system to generate a GMM-based set of emission probabilities for the plurality of HMMs; by computing, for each temporal frame, weighted sums of the NN-based emission probabilities and the GMM-based emission probabilities, merging the NN-based set of emission probabilities with the GMM-based set of emission probabilities to generate a merged set of emission probabilities for the plurality of HMMs; and applying the merged set of emission probabilities to the plurality of HMMs to determine speech content corresponding to the sequence of temporal frames of the audio input signal, wherein the weighted sums are computed according to weights computationally-determined by at least one processor during to a training process that minimizes a computationally-determined difference between computationally-predicted speech in training temporal frames and predetermined speech in the training temporal frames. 2. The method of claim 1 , wherein at least two of (i) the NN, (ii) the GMMs, and (iii) the HMMs are implemented by at least one common processor from among the one or more processors of the system. | 0.724973 |
1. Computerized apparatus useful for locating an organization or entity, the organization or entity being disposed within a building or structure, the apparatus comprising: a wireless interface; data processing apparatus; a touch-screen input and display device; a speech digitization apparatus in data communication with the data processing apparatus; and a storage apparatus in data communication with the data processing apparatus, said storage apparatus comprising at least one computer program, said at least one program being configured to: receive a digitized speech input via the speech digitization apparatus, the input relating to an organization or entity which a user wishes to locate; based at least in part on the input, causing recognition of at least one word therein relating to the organization or entity, and identification of a location associated with the organization or entity based at least in part on the at least one recognized word, the location being inside of the building or structure; and provide a graphical or visual representation of the location on the touch screen input and display device in order to aid a user in finding the organization or entity, the graphical or visual representation of the location also comprising a graphical or visual representation of at least the immediate surroundings of the organization or entity, the immediate surroundings being inside the building or structure. | 1. Computerized apparatus useful for locating an organization or entity, the organization or entity being disposed within a building or structure, the apparatus comprising: a wireless interface; data processing apparatus; a touch-screen input and display device; a speech digitization apparatus in data communication with the data processing apparatus; and a storage apparatus in data communication with the data processing apparatus, said storage apparatus comprising at least one computer program, said at least one program being configured to: receive a digitized speech input via the speech digitization apparatus, the input relating to an organization or entity which a user wishes to locate; based at least in part on the input, causing recognition of at least one word therein relating to the organization or entity, and identification of a location associated with the organization or entity based at least in part on the at least one recognized word, the location being inside of the building or structure; and provide a graphical or visual representation of the location on the touch screen input and display device in order to aid a user in finding the organization or entity, the graphical or visual representation of the location also comprising a graphical or visual representation of at least the immediate surroundings of the organization or entity, the immediate surroundings being inside the building or structure. 12. The apparatus of claim 1 , wherein the identification of the location comprises accessing a local storage device which is part of the computerized apparatus. | 0.688695 |
8. A computer program product, stored on a computer-readable storage device that, when executed by data processing apparatus, is operable to cause the data processing apparatus to perform operations comprising: obtaining images from first image results responsive to a first query, wherein each of a plurality of the obtained images is associated with a score and user behavior data wherein the user behavior data represents interactions of users with the obtained image when the obtained image was presented as a search result for the first query; selecting a plurality of the obtained images as a plurality of selected images, each image of the plurality of selected images having respective user behavior data that satisfies a threshold; associating each image of the plurality of the selected images with one or more annotations based on analysis of content of the selected image, the associating comprising: providing the plurality of the selected images to each of a plurality of different computer image annotators that each visually analyze an image to identify particular visual features in the images; receiving, from the plurality of computer image annotators, the annotations derived from visual analysis of the images to identify particular visual features in the images; and providing the first query and the annotations to a plurality of different machine learning system generated classifiers to associate the first query with one or more categories wherein a respective plurality of the annotations is provided as input to each of the classifiers, and wherein at least one of the categories specifies a presence of one of the particular visual features in an image; receiving a second query, wherein the second query is the same or similar to the first query; obtaining second images responsive to the second query, wherein each of the second images is associated with a respective first rank so that the second images are arranged according to a first order; modifying the respective first rank of one or more of the second images based on one or more of the categories associated with the first query so that the second images are re-ordered according to a second order. | 8. A computer program product, stored on a computer-readable storage device that, when executed by data processing apparatus, is operable to cause the data processing apparatus to perform operations comprising: obtaining images from first image results responsive to a first query, wherein each of a plurality of the obtained images is associated with a score and user behavior data wherein the user behavior data represents interactions of users with the obtained image when the obtained image was presented as a search result for the first query; selecting a plurality of the obtained images as a plurality of selected images, each image of the plurality of selected images having respective user behavior data that satisfies a threshold; associating each image of the plurality of the selected images with one or more annotations based on analysis of content of the selected image, the associating comprising: providing the plurality of the selected images to each of a plurality of different computer image annotators that each visually analyze an image to identify particular visual features in the images; receiving, from the plurality of computer image annotators, the annotations derived from visual analysis of the images to identify particular visual features in the images; and providing the first query and the annotations to a plurality of different machine learning system generated classifiers to associate the first query with one or more categories wherein a respective plurality of the annotations is provided as input to each of the classifiers, and wherein at least one of the categories specifies a presence of one of the particular visual features in an image; receiving a second query, wherein the second query is the same or similar to the first query; obtaining second images responsive to the second query, wherein each of the second images is associated with a respective first rank so that the second images are arranged according to a first order; modifying the respective first rank of one or more of the second images based on one or more of the categories associated with the first query so that the second images are re-ordered according to a second order. 13. The program product of claim 8 , wherein the user behavior data is a count of times users selected the obtained image in search results for the first query. | 0.650812 |
15. The computer system of claim 14 , wherein the graphic element indicating the duration of time that the first video was viewed comprises highlighting applied to the first portion of the displayed text. | 15. The computer system of claim 14 , wherein the graphic element indicating the duration of time that the first video was viewed comprises highlighting applied to the first portion of the displayed text. 16. The computer system of claim 15 , wherein a gradient is applied to the highlighting at the last word of the first portion of displayed text. | 0.900739 |
2. Apparatus as defined in claim 1 wherein said means for processing the stored segment bits and interval bits includes a shift register means having cells equal in number to at least one more than the number of interval bits in each of said input digital words, means responsive to the stored segment bits for entering a digital value into at least one cell of said shift register means, and means for coupling the stored interval bits into other cells of said shift register means. | 2. Apparatus as defined in claim 1 wherein said means for processing the stored segment bits and interval bits includes a shift register means having cells equal in number to at least one more than the number of interval bits in each of said input digital words, means responsive to the stored segment bits for entering a digital value into at least one cell of said shift register means, and means for coupling the stored interval bits into other cells of said shift register means. 4. Apparatus as defined in claim 2 wherein said means for processing the stored segment bits and interval bits includes means for selectively enabling said shift register means. | 0.863969 |
10. A computer program product comprising: one or more computer readable storage media and program instructions stored on the one or more computer readable storage media, wherein the one or more computer readable storage media are not transitory signals per se, the program instructions comprising: program instructions to identify a set of vocal variables for a user, by a voice recognition system, based, at least in part, on a user interaction with the voice recognition system, wherein the user interaction includes the user selecting a first language and a second language, and adjusting a level of accent, wherein the level of accent indicates an amount by which the second language affects the user's speaking of the first language; program instructions to generate a voice model of speech patterns that represent the user's speaking of the first language using the identified set of vocal variables, wherein the voice model is adapted to improve recognition of the user's voice by the voice recognition system; program instructions to match the generated voice model to a catalog of speech patterns, and identify a voice model code that represents speech patterns in the catalog that match the generated voice model; program instructions to provide the identified voice model code to the user; program instructions to receive voice input from the user; and program instructions to utilize the generated voice model to improve recognition of the received voice input, based on the user providing the identified voice model code. | 10. A computer program product comprising: one or more computer readable storage media and program instructions stored on the one or more computer readable storage media, wherein the one or more computer readable storage media are not transitory signals per se, the program instructions comprising: program instructions to identify a set of vocal variables for a user, by a voice recognition system, based, at least in part, on a user interaction with the voice recognition system, wherein the user interaction includes the user selecting a first language and a second language, and adjusting a level of accent, wherein the level of accent indicates an amount by which the second language affects the user's speaking of the first language; program instructions to generate a voice model of speech patterns that represent the user's speaking of the first language using the identified set of vocal variables, wherein the voice model is adapted to improve recognition of the user's voice by the voice recognition system; program instructions to match the generated voice model to a catalog of speech patterns, and identify a voice model code that represents speech patterns in the catalog that match the generated voice model; program instructions to provide the identified voice model code to the user; program instructions to receive voice input from the user; and program instructions to utilize the generated voice model to improve recognition of the received voice input, based on the user providing the identified voice model code. 12. The computer program product of claim 10 , wherein the program instructions to match the generated voice model to a catalog of speech patterns comprise: program instructions to determine that a speech pattern of the generated voice model does not match any of the speech patterns in the catalog; and program instructions to save to the catalog, the speech pattern of the generated voice model that does not match any of the speech patterns in the catalog. | 0.5 |
2. The module generating apparatus according to claim 1 , wherein the macroblocking analyzing unit appends, to a number identifying a variable for a statement in each block, a virtual portion representing a number unique in the statement, the virtual portion being appended as the appendant information and to express the number for identifying the variable by a combination of a lower portion representing a number unique in the source code entirely and an upper portion made up of the virtual portion. | 2. The module generating apparatus according to claim 1 , wherein the macroblocking analyzing unit appends, to a number identifying a variable for a statement in each block, a virtual portion representing a number unique in the statement, the virtual portion being appended as the appendant information and to express the number for identifying the variable by a combination of a lower portion representing a number unique in the source code entirely and an upper portion made up of the virtual portion. 4. The module generating apparatus according to claim 2 , wherein the similar portion merging/restructuring unit compares the merged block information by identifying a variable based on the virtual portion. | 0.914865 |
19. A non-transitory computer readable medium operating with system hardware for dynamically integrating a business logic rule into an application, the non-transitory computer readable medium including program instructions for performing the steps of: stating the business logic rule as an expression in a functional language; parsing the expression directly into an executable routine by associating with the expression one or more functions and defined operators that correspond to one or more pre-coded subroutines and associating values with the one or more functions by calling the functions and parameters in the expression with associated values passed in; and calling, by the application, the executable routine. | 19. A non-transitory computer readable medium operating with system hardware for dynamically integrating a business logic rule into an application, the non-transitory computer readable medium including program instructions for performing the steps of: stating the business logic rule as an expression in a functional language; parsing the expression directly into an executable routine by associating with the expression one or more functions and defined operators that correspond to one or more pre-coded subroutines and associating values with the one or more functions by calling the functions and parameters in the expression with associated values passed in; and calling, by the application, the executable routine. 21. The non-transitory computer readable medium of claim 19 wherein the functional language comprises parameters that correspond to lookup fields in an associated database. | 0.634615 |
1. A method for reconciling detailed user transaction feedback with a numerical transaction rating by a user that rates a seller of an item, comprising: detecting, by one or more computer processors, that the transaction rating indicates a negative experience; using a positive sentiment mining tool, mining a sentiment of words in the feedback and detecting that the words indicate positive sentiment; responsive to detecting that the words indicate positive sentiment, preparing confirmatory content to present to the user for confirming that the transaction rating indicates a negative experience; displaying the confirmatory content to the user on a first user interface via the Internet; receiving from the user, via the Internet, responsive to displaying the confirmatory content, confirmatory information that confirms that the transaction rating indicates a negative experience; responsive to receiving the confirmatory information, transforming a state of the transaction rating to a state that reconciles the transaction rating and the positive sentiment; using the reconciled transaction rating, preparing content that measures trustworthiness of the seller; and displaying the content that measures trustworthiness of the seller to buyers on a second user interface via the Internet. | 1. A method for reconciling detailed user transaction feedback with a numerical transaction rating by a user that rates a seller of an item, comprising: detecting, by one or more computer processors, that the transaction rating indicates a negative experience; using a positive sentiment mining tool, mining a sentiment of words in the feedback and detecting that the words indicate positive sentiment; responsive to detecting that the words indicate positive sentiment, preparing confirmatory content to present to the user for confirming that the transaction rating indicates a negative experience; displaying the confirmatory content to the user on a first user interface via the Internet; receiving from the user, via the Internet, responsive to displaying the confirmatory content, confirmatory information that confirms that the transaction rating indicates a negative experience; responsive to receiving the confirmatory information, transforming a state of the transaction rating to a state that reconciles the transaction rating and the positive sentiment; using the reconciled transaction rating, preparing content that measures trustworthiness of the seller; and displaying the content that measures trustworthiness of the seller to buyers on a second user interface via the Internet. 3. The method of claim 1 wherein the confirmatory content comprises a clarification survey. | 0.576079 |
1. A computer-implemented method comprising: obtaining a query image that has been submitted by a user of an image search system; determining, by the image search system, that the query image is indicated to be associated with an object; obtaining, for the query image: (i) one or more training images of a corpus of training images that are indicated to be associated with the object, and (ii) for each one of the one or more training images that are indicated to be associated with the object, a similarity score that reflects a level of similarity between the query image and the respective training image; determining to add the query image to the corpus of training images that are indicated to be associated with the object in response to the similarity score that reflects the level of similarity between the query image and the respective training image satisfying a threshold; and training the image search system to recognize the object in subsequently received query images, using the corpus of training images that are indicated to be associated with the object. | 1. A computer-implemented method comprising: obtaining a query image that has been submitted by a user of an image search system; determining, by the image search system, that the query image is indicated to be associated with an object; obtaining, for the query image: (i) one or more training images of a corpus of training images that are indicated to be associated with the object, and (ii) for each one of the one or more training images that are indicated to be associated with the object, a similarity score that reflects a level of similarity between the query image and the respective training image; determining to add the query image to the corpus of training images that are indicated to be associated with the object in response to the similarity score that reflects the level of similarity between the query image and the respective training image satisfying a threshold; and training the image search system to recognize the object in subsequently received query images, using the corpus of training images that are indicated to be associated with the object. 2. The method of claim 1 , wherein obtaining one or more training images comprises: matching the query image to the object using a visual object recognition module; and identifying the one or more training images based on the object. | 0.630584 |
1. A method for identifying optimized malicious search engine results comprising: receiving a search item result; analyzing, using at least one computer processor of a server, the search item result in a secure environment to detect malware hidden using network redirection, wherein analyzing comprises automatically navigating to a network location associated with the search item result using a network request generated by the server and configured to appear to the network location as a network request from a user of the search result; determining that the search item result is associated with malware; and providing an indicator that the search item result is associated with malware. | 1. A method for identifying optimized malicious search engine results comprising: receiving a search item result; analyzing, using at least one computer processor of a server, the search item result in a secure environment to detect malware hidden using network redirection, wherein analyzing comprises automatically navigating to a network location associated with the search item result using a network request generated by the server and configured to appear to the network location as a network request from a user of the search result; determining that the search item result is associated with malware; and providing an indicator that the search item result is associated with malware. 2. The method of claim 1 , wherein the network request comprises a network request containing at least one of: a referring search engine Uniform Resource Locator (URL); a user agent set as a browser; and a source id set as a browser. | 0.52921 |
21. A method for querying an examinee, the method comprising: establishing baseline neural responses for the examinee, the baseline neural responses comprising at least one known truthful response and at least one known false response; asking the examinee a plurality of questions, wherein at least one of the plurality questions is repeated a plurality of times; measuring a respective neural response of the examinee associated with the examinee's response to each of the plurality of questions; directly in response to a previous one of the plurality of questions, providing, to the examinee, a visual cue of an affirmation attestation, wherein the affirmation attestation is indicative of a query as to the truthfulness of the response, provided by the examinee, to the previous question; measuring a neural response of the examinee associated with the examinee's response to the cue of the attestation affirmation; and comparing neural responses associated with the plurality of questions and the visual cue of the affirmation attestation with the baseline neural responses to determine if the examinee at least one of conducted deception in response to a question or malingered in response to a question. | 21. A method for querying an examinee, the method comprising: establishing baseline neural responses for the examinee, the baseline neural responses comprising at least one known truthful response and at least one known false response; asking the examinee a plurality of questions, wherein at least one of the plurality questions is repeated a plurality of times; measuring a respective neural response of the examinee associated with the examinee's response to each of the plurality of questions; directly in response to a previous one of the plurality of questions, providing, to the examinee, a visual cue of an affirmation attestation, wherein the affirmation attestation is indicative of a query as to the truthfulness of the response, provided by the examinee, to the previous question; measuring a neural response of the examinee associated with the examinee's response to the cue of the attestation affirmation; and comparing neural responses associated with the plurality of questions and the visual cue of the affirmation attestation with the baseline neural responses to determine if the examinee at least one of conducted deception in response to a question or malingered in response to a question. 23. The method in accordance with claim 21 , wherein the visual cue of an affirmation attestation comprises a displayed icon. | 0.714757 |
1. A method for managing a configuration for a computer system, comprising: exporting configuration data corresponding to a plurality of configurable components to a central data repository during pre-boot; determining whether script engine is running; if the script is running, then in response to a script request, extracting requested resource information; searching a plurality of keywords to determine settings to be affected by the received script request; determining at least one action to be performed in response to the script request; and performing the at least one action. | 1. A method for managing a configuration for a computer system, comprising: exporting configuration data corresponding to a plurality of configurable components to a central data repository during pre-boot; determining whether script engine is running; if the script is running, then in response to a script request, extracting requested resource information; searching a plurality of keywords to determine settings to be affected by the received script request; determining at least one action to be performed in response to the script request; and performing the at least one action. 5. The method as recited in claim 1 , wherein the at least one action is selected from the group consisting of storing configuration settings in a non-volatile variable, creating an encapsulation of configuration variable changes, initiating a caps tile change update for add-in card updates, executing an add-in card abstraction to set add-in card configuration data, and stating configuration updates in non-volatile random access memory (NVRAM) on a motherboard. | 0.5435 |
1. A computer-implemented poet's assistant method, comprising: loading a word processing program; receiving a word in the word processing program provided by a user; displaying a plurality of poet windows in response to receiving the word, the poet windows corresponding to underlying models that represent pre-defined poet personalities; the plurality of poet windows comprising a finish word window, a finish line window and a finish poem window; and processing the word in each of the plurality of poet windows with processing the word in the finish word window comprises: loading an author analysis model; locating the word in the author analysis model; and generating a proposed word in conjunction with the author analysis model. | 1. A computer-implemented poet's assistant method, comprising: loading a word processing program; receiving a word in the word processing program provided by a user; displaying a plurality of poet windows in response to receiving the word, the poet windows corresponding to underlying models that represent pre-defined poet personalities; the plurality of poet windows comprising a finish word window, a finish line window and a finish poem window; and processing the word in each of the plurality of poet windows with processing the word in the finish word window comprises: loading an author analysis model; locating the word in the author analysis model; and generating a proposed word in conjunction with the author analysis model. 13. The method of claim 1 wherein processing the word in the finish word window comprises: choosing a poet personality and a finish poem display to provide a completed poem after the user types a word in the word processing program. | 0.807756 |
1. A method, comprising: executing, by a first computer system, a first collaboration framework and an instance of an application, wherein executing the instance of the application comprises displaying an instance of a graphical user interface of the application on the first computer system; the first collaboration framework intercepting, via an operating system event handling mechanism on the first computer system, a local user input event targeted to the instance of the application, wherein the instance of the application applies a modification to the instance of the graphical user interface in response to receiving the user input event; in response to said intercepting, the first collaboration framework sending a message including the user input event to one or more other collaboration frameworks each executing on a respective other computer system that is executing a respective other instance of the application, wherein said executing each respective other instance of the application comprises displaying a respective other instance of the graphical user interface of the application on the respective other computer system; in response to receiving the message, each of the one or more other collaboration frameworks delivering, via an operating system event handling mechanism on the respective other computer system, the user input event to the respective other instance of the application executing on the respective other computer system, displays a respective other user interface; wherein the operating system event handling mechanism delivers the user input event to the respective other application as if the user input event originated locally from the respective other user interface displayed by the respective other application; and in response to receiving the user input event, the respective other instance of the application applying the modification to the respective other instance of the graphical user interface of the application displayed by the respective other computer system. | 1. A method, comprising: executing, by a first computer system, a first collaboration framework and an instance of an application, wherein executing the instance of the application comprises displaying an instance of a graphical user interface of the application on the first computer system; the first collaboration framework intercepting, via an operating system event handling mechanism on the first computer system, a local user input event targeted to the instance of the application, wherein the instance of the application applies a modification to the instance of the graphical user interface in response to receiving the user input event; in response to said intercepting, the first collaboration framework sending a message including the user input event to one or more other collaboration frameworks each executing on a respective other computer system that is executing a respective other instance of the application, wherein said executing each respective other instance of the application comprises displaying a respective other instance of the graphical user interface of the application on the respective other computer system; in response to receiving the message, each of the one or more other collaboration frameworks delivering, via an operating system event handling mechanism on the respective other computer system, the user input event to the respective other instance of the application executing on the respective other computer system, displays a respective other user interface; wherein the operating system event handling mechanism delivers the user input event to the respective other application as if the user input event originated locally from the respective other user interface displayed by the respective other application; and in response to receiving the user input event, the respective other instance of the application applying the modification to the respective other instance of the graphical user interface of the application displayed by the respective other computer system. 14. The method of claim 1 , wherein the input event corresponds to a document opening in the instance of the application, the method further comprising: the first collaboration framework sending the document opened in the respective other instance of the application to each of the other collaboration frameworks; and in response to receiving the document, each of the one or more other collaboration frameworks instructing the respective other instance of the application to open the document. | 0.525911 |
23. A method according to claim 22 , wherein the annotating step comprises: achieving information about network characteristics to be observed comprising said semantic information; and annotating the first formal model using the formal ontologies of the second formal model to provide an annotated formal model describing said characteristics. | 23. A method according to claim 22 , wherein the annotating step comprises: achieving information about network characteristics to be observed comprising said semantic information; and annotating the first formal model using the formal ontologies of the second formal model to provide an annotated formal model describing said characteristics. 24. A method according to claim 23 , comprising the step of: storing said first formal model, said second formal model and said annotated formal model in ontology holding means. | 0.832924 |
9. The method of claim 4 , wherein said agents include smart integration workers for operationally connecting to the data sources. | 9. The method of claim 4 , wherein said agents include smart integration workers for operationally connecting to the data sources. 10. The method of claim 9 , wherein said workers include adapters for facilitating an operational connection to the data sources. | 0.950994 |
19. A non-transitory computer-readable medium storing software comprising instructions executable by one or more computers which, upon such execution, cause the one or more computers to perform operations comprising: identifying two or more consecutive terms in a search query; determining a first quantity of search results that (i) are responsive to the search query, and (ii) have been selected by a user; determining a second quantity of search results that (i) are responsive to the search query, (ii) have been selected by the user, and (iii) have summaries that include the two or more consecutive terms; determining a value using the first quantity and the second quantity; and determining a likelihood that the two or more consecutive terms represent a compound based on the value. | 19. A non-transitory computer-readable medium storing software comprising instructions executable by one or more computers which, upon such execution, cause the one or more computers to perform operations comprising: identifying two or more consecutive terms in a search query; determining a first quantity of search results that (i) are responsive to the search query, and (ii) have been selected by a user; determining a second quantity of search results that (i) are responsive to the search query, (ii) have been selected by the user, and (iii) have summaries that include the two or more consecutive terms; determining a value using the first quantity and the second quantity; and determining a likelihood that the two or more consecutive terms represent a compound based on the value. 20. The medium of claim 19 , wherein determining a second quantity of search results comprises determining a second quantity of search results that (i) are responsive to the search query, (ii) have been selected by the user, and (iii) have summaries that include the two or more terms, and in which two or more of the terms appear non-consecutively. | 0.527174 |
12. A system for digitally signing an electronic document with a user-entered image of a signature, the system comprising: a computing apparatus, including a display screen and an input device, operative to: render the document; examine properties of each of a plurality of signing certificates available to the user; in response to examining the properties, filter out signing certificates that are used for network authentication and for code signing from among the plurality of signing certificates to determine signing certificates that match a selection criterion; select a signing certificate from among the signing certificates that match the selection criterion; render a sign dialog associated with the document; receive a signature from a user, wherein the signature comprises a written signature from the user; create a digital signature that includes an image of the written signature from the user; create a single unique value, the single unique value representative of both the image of the written signature from the user and of the document; and save the unique value in association with the document thereby digitally signing the document, wherein the unique value is associated with the signing certificate automatically selected. | 12. A system for digitally signing an electronic document with a user-entered image of a signature, the system comprising: a computing apparatus, including a display screen and an input device, operative to: render the document; examine properties of each of a plurality of signing certificates available to the user; in response to examining the properties, filter out signing certificates that are used for network authentication and for code signing from among the plurality of signing certificates to determine signing certificates that match a selection criterion; select a signing certificate from among the signing certificates that match the selection criterion; render a sign dialog associated with the document; receive a signature from a user, wherein the signature comprises a written signature from the user; create a digital signature that includes an image of the written signature from the user; create a single unique value, the single unique value representative of both the image of the written signature from the user and of the document; and save the unique value in association with the document thereby digitally signing the document, wherein the unique value is associated with the signing certificate automatically selected. 13. The system of claim 12 , wherein the computing apparatus is further operative to: insert a signature line in the document wherein the document rendered includes the signature line; and receive a selection to sign the document at the signature line. | 0.722659 |
11. A computer system comprising a processor, a memory coupled to the processor, and a computer readable storage device coupled to the processor, said storage device containing program code configured to be executed by the processor via the memory to implement a method for advanced searching of a service registry for a service description that most closely matches a service name provided by a user, said method comprising: said processor receiving the service name wherein the SOA service registry system comprises the service registry, a name parser, a dictionary, and a name composer, and wherein the service registry comprises at least one service description searchable by a respectively associated service name; said processor determining that the service name does not have the service description that is an exact match to the received service name in the service registry; said processor generating a ranked alternative service name list by use of the name parser, the dictionary, and the name composer, wherein the ranked alternative service name list comprises at least one alternative service name and a respective rank of each alternative service name of said at least one alternative service name, wherein the respective rank indicates how closely the alternative service name associated with the respective rank resembles the service name provided by the user; said processor ascertaining that the service description matches the highest ranked alternative service name in the alternative service name list by searching the service registry with said at least one alternative service name in a descending order of the respective ranks of said at least one alternative service name; and said processor communicating the service description matching the highest ranked alternative service name to the user. | 11. A computer system comprising a processor, a memory coupled to the processor, and a computer readable storage device coupled to the processor, said storage device containing program code configured to be executed by the processor via the memory to implement a method for advanced searching of a service registry for a service description that most closely matches a service name provided by a user, said method comprising: said processor receiving the service name wherein the SOA service registry system comprises the service registry, a name parser, a dictionary, and a name composer, and wherein the service registry comprises at least one service description searchable by a respectively associated service name; said processor determining that the service name does not have the service description that is an exact match to the received service name in the service registry; said processor generating a ranked alternative service name list by use of the name parser, the dictionary, and the name composer, wherein the ranked alternative service name list comprises at least one alternative service name and a respective rank of each alternative service name of said at least one alternative service name, wherein the respective rank indicates how closely the alternative service name associated with the respective rank resembles the service name provided by the user; said processor ascertaining that the service description matches the highest ranked alternative service name in the alternative service name list by searching the service registry with said at least one alternative service name in a descending order of the respective ranks of said at least one alternative service name; and said processor communicating the service description matching the highest ranked alternative service name to the user. 12. The computer system of claim 11 , said generating comprising: creating a constituent word list comprising at least one constituent word that is a respective dictionary word appearing in the service name as a result of parsing the service name into a set of dictionary words by the name parser; associating a respective weight to each constituent word of said at least one constituent word, wherein said respective weight associated with said each constituent word is predefined by the SOA service registry system; producing a respective synonym list for said each constituent word as a result of running the dictionary, the respective synonym list comprising at least one synonym of said each constituent word as located in the dictionary; associating a respective weight to each synonym in the respective synonym list for said each constituent word, wherein said respective weight associated with said each synonym is predefined by the SOA service registry system; composing at least one alternative service name by combining said at least one constituent word from the constituent word list and said at least one synonym from the respective synonym list pursuant to a sequence in the service name by use of the name composer; calculating a respective rank for said at least one alternative service name by adding the respective weights of all words employed in each alternative service name from said composing; rendering the ranked alternative service name list by associating the respective rank with said each alternative service name. | 0.522905 |
4. The method of claim 1 , wherein said managing comprises specifying an access control list against each of the one or more sites in the search list. | 4. The method of claim 1 , wherein said managing comprises specifying an access control list against each of the one or more sites in the search list. 6. The method of claim 4 , wherein said access control list comprises an identification of a user of a given search engine having read and/or write privileges associated with said search list. | 0.912658 |
1. A method for document management comprising: automatically acquiring image logs for all input documents being processed by image output devices within an organization, each image log comprising image data and an associated record for an input document being processed by one of at least one image output device within the organization, whereby image data is automatically acquired for all documents being processed by the organization's image output devices, without provision for a user to select whether a document image should be logged; automatically sending all of the image logs from the image output devices to an image log management system and storing the image logs in memory until a search for similar documents is performed; for each of the acquired and stored image logs, performing the search for similar documents and automatically retrieving similar documents, including identifying keywords extracted from the acquired image data, and based on the keywords, performing a search among previously acquired documents archived in a computer readable storage medium and accessible electronic documents stored in at least one other document repository to retrieve similar documents; and where a similar document is retrieved, computing a measure of similarity between the retrieved similar document and the input document; and based on the computed similarity, determining whether the retrieved document is a matching document and, if so, storing a location of the retrieved matching document whereby for the input document, a location of each retrieved matching document is stored; and providing a procedure for ensuring that a single version of the input document is archived in the computer-readable storage medium, the version being selected from the captured image data and any identified matching documents, except optionally where the job log indicates that at least one of the retrieved matching document locations is a public document source; the method further comprising: where the retrieved document has access controls, including a reference to the access controls of the retrieved document in the stored job log and further including at least one of: a) storing user information from the record of the image log in the stored job log, whereby a leak of an access controlled document is attributable to the user which caused the input document to be processed by the image output device; and b) blocking processing of the input document by the image output device where the access controls of the retrieved matching document indicate that such processing should be blocked. | 1. A method for document management comprising: automatically acquiring image logs for all input documents being processed by image output devices within an organization, each image log comprising image data and an associated record for an input document being processed by one of at least one image output device within the organization, whereby image data is automatically acquired for all documents being processed by the organization's image output devices, without provision for a user to select whether a document image should be logged; automatically sending all of the image logs from the image output devices to an image log management system and storing the image logs in memory until a search for similar documents is performed; for each of the acquired and stored image logs, performing the search for similar documents and automatically retrieving similar documents, including identifying keywords extracted from the acquired image data, and based on the keywords, performing a search among previously acquired documents archived in a computer readable storage medium and accessible electronic documents stored in at least one other document repository to retrieve similar documents; and where a similar document is retrieved, computing a measure of similarity between the retrieved similar document and the input document; and based on the computed similarity, determining whether the retrieved document is a matching document and, if so, storing a location of the retrieved matching document whereby for the input document, a location of each retrieved matching document is stored; and providing a procedure for ensuring that a single version of the input document is archived in the computer-readable storage medium, the version being selected from the captured image data and any identified matching documents, except optionally where the job log indicates that at least one of the retrieved matching document locations is a public document source; the method further comprising: where the retrieved document has access controls, including a reference to the access controls of the retrieved document in the stored job log and further including at least one of: a) storing user information from the record of the image log in the stored job log, whereby a leak of an access controlled document is attributable to the user which caused the input document to be processed by the image output device; and b) blocking processing of the input document by the image output device where the access controls of the retrieved matching document indicate that such processing should be blocked. 13. A computer implemented system for performing the method of claim 1 comprising software instructions stored in memory for performing the method and at least one processor, in communication with the memory, for executing the instructions. | 0.632402 |
7. In a language model defining a probability for sequences of words, the language model invoked by a production application responsive to an end user for performing statistical language recognition services, a method of assigning words to classes comprising: defining a language model for predicting a likelihood of sequences of words received from the production application, the language model having a classing function, the classing function for assigning words to classes, the word classes grouping words for receiving similar treatment as other words in the class; identifying a clustering, the clustering defining the number of words in sequence to which a prediction applies, in which an n-gram cluster defines a probability that, for an n−1 sequence of words, the successive nth word will be found; identifying a language context corresponding to the usage of the language as received by the production application; defining the classing function, the classing function for scanning a learning set and identifying the word classes by: employing a word based classing approach; backing off, if the word based approach indicates a null probability; and employing a class based approach; further comprising: determining seen and unseen clusters, the unseen clusters having a previously unoccurring sequence of words; employing the word based classification if the cluster has a previous occurrence, identifying a discount parameter, the discount parameter reducing a count of word occurrences of a particular cluster in favor of a class count of words of the cluster; and backing off using the discount parameter and employing a class based approach if the cluster is unseen, unseen clusters based on occurrence of any of the words in the cluster, the unseen words has occurred the discount parameter reducing a count of word occurrences of a particular cluster in favor of a class count of words of the cluster; the discount parameter defining an absolute discounting model, further comprising: identifying a discount parameter indicative; of a reduction of a word count of words in a cluster; determining if the cluster is to be pruned or retained in the corpus; count of the observed word based count of the cluster to compute a count of the observed word based count of the cluster to compute a discounted count; or defining the discount count of the cluster as zero if the cluster is pruned; applying the classing function to the learning set to generate the word classes, the word classes indicative of words statistically likely to be employed based on predetermined sequences of words in the learning set; and optimizing the classing function by selecting the word classes based on an objective of the production application, optimizing further including: analyzing word counts and class counts of the learning set; and analyzing word frequency within an assigned class; the objective of the production application defined by the identified language context. | 7. In a language model defining a probability for sequences of words, the language model invoked by a production application responsive to an end user for performing statistical language recognition services, a method of assigning words to classes comprising: defining a language model for predicting a likelihood of sequences of words received from the production application, the language model having a classing function, the classing function for assigning words to classes, the word classes grouping words for receiving similar treatment as other words in the class; identifying a clustering, the clustering defining the number of words in sequence to which a prediction applies, in which an n-gram cluster defines a probability that, for an n−1 sequence of words, the successive nth word will be found; identifying a language context corresponding to the usage of the language as received by the production application; defining the classing function, the classing function for scanning a learning set and identifying the word classes by: employing a word based classing approach; backing off, if the word based approach indicates a null probability; and employing a class based approach; further comprising: determining seen and unseen clusters, the unseen clusters having a previously unoccurring sequence of words; employing the word based classification if the cluster has a previous occurrence, identifying a discount parameter, the discount parameter reducing a count of word occurrences of a particular cluster in favor of a class count of words of the cluster; and backing off using the discount parameter and employing a class based approach if the cluster is unseen, unseen clusters based on occurrence of any of the words in the cluster, the unseen words has occurred the discount parameter reducing a count of word occurrences of a particular cluster in favor of a class count of words of the cluster; the discount parameter defining an absolute discounting model, further comprising: identifying a discount parameter indicative; of a reduction of a word count of words in a cluster; determining if the cluster is to be pruned or retained in the corpus; count of the observed word based count of the cluster to compute a count of the observed word based count of the cluster to compute a discounted count; or defining the discount count of the cluster as zero if the cluster is pruned; applying the classing function to the learning set to generate the word classes, the word classes indicative of words statistically likely to be employed based on predetermined sequences of words in the learning set; and optimizing the classing function by selecting the word classes based on an objective of the production application, optimizing further including: analyzing word counts and class counts of the learning set; and analyzing word frequency within an assigned class; the objective of the production application defined by the identified language context. 19. The method of claim 7 further comprising classing words according to a hard classing approach such that each word appears in only one class. | 0.583546 |
32. The system of claim 23 , wherein relevance scores are determined using a statistical classification or rank regression algorithm, a clustering analysis algorithm, or a morphological analysis algorithm. | 32. The system of claim 23 , wherein relevance scores are determined using a statistical classification or rank regression algorithm, a clustering analysis algorithm, or a morphological analysis algorithm. 33. The system of claim 32 , wherein the statistical classification or rank regression algorithm comprises any one of logistic regression, support vector machines, classification or regression tree, and boosted tree ensembles. | 0.927352 |
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