patent_num
int64 3.93M
10.2M
| claim_num1
int64 1
519
| claim_num2
int64 2
520
| sentence1
stringlengths 40
15.9k
| sentence2
stringlengths 88
20k
| label
float64 0.5
1
|
|---|---|---|---|---|---|
9,031,845 | 1 | 4 | 1. A mobile system for processing natural language utterances, comprising: one or more physical processors at a vehicle that are programmed to execute one or more computer program instructions which, when executed, cause the one or more physical processors to: receive a natural language utterance associated with a user; perform speech recognition on the natural language utterance; parse and interpret the speech recognized natural language utterance; determine a domain and a context that are associated with the parsed and interpreted natural language utterance; formulate a command or query based on the domain and the context; determine whether the command or query is to be executed on-board or off-board the vehicle; execute the command or query at the vehicle in response to a determination that the command or query is to be executed on-board the vehicle; and invoke a device that communicates wirelessly over a wide area network to process the command or query such that the command or query is executed off-board the vehicle in response to a determination that the command or query is to be executed off-board the vehicle. | 1. A mobile system for processing natural language utterances, comprising: one or more physical processors at a vehicle that are programmed to execute one or more computer program instructions which, when executed, cause the one or more physical processors to: receive a natural language utterance associated with a user; perform speech recognition on the natural language utterance; parse and interpret the speech recognized natural language utterance; determine a domain and a context that are associated with the parsed and interpreted natural language utterance; formulate a command or query based on the domain and the context; determine whether the command or query is to be executed on-board or off-board the vehicle; execute the command or query at the vehicle in response to a determination that the command or query is to be executed on-board the vehicle; and invoke a device that communicates wirelessly over a wide area network to process the command or query such that the command or query is executed off-board the vehicle in response to a determination that the command or query is to be executed off-board the vehicle. 4. The mobile system of claim 1 , wherein the instructions cause the one or more physical processors to: determine whether executing the command or query will create a hazardous condition for the vehicle; provide interactive guidance to resolve the hazardous condition via an output device connected to the vehicle based on a determination that executing the command or query will create the hazardous condition; and receive an input that manually overrides the hazardous condition determination, wherein the command or query is executed based on the manual override. | 0.792763 |
8,843,493 | 1 | 8 | 1. A method for comparing documents, comprising: extracting, by a computer processor, a plurality of extracted elements from a first formatted document, wherein each of the plurality of extracted elements corresponds to a text element of the first formatted document, wherein the plurality of extracted elements comprises at least one selected from a group consisting of a plurality of words and a plurality of word lengths; extracting, by the computer processor, a first plurality of text fingerprints from a sequence of the plurality of extracted elements to form a first text feature of the first formatted document, wherein the first plurality of text fingerprints comprises at least one selected from a group consisting of a plurality of word n-grams and a plurality of word length n-grams, wherein the first text feature comprises at least one selected from a group consisting of a first text content feature based on the plurality of word n-grams and a first text geometric feature based on the plurality of word length n-grams; comparing, by the computer processor, the first text feature and a second text feature of a second formatted document to generate a comparison result, wherein the second text feature comprises at least one selected from a group consisting of a second text content feature and a second text geometric feature, wherein the comparison result comprises at least one selected from a group consisting of a text content match rate between the first and second text content features and a text geometric match rate between the first and second text geometric features; and determining, in response to the comparison result meeting a pre-determined criterion, that each of the first formatted document and the second formatted document contains common text content, wherein the comparison result meeting the pre-determined criterion is based on at least one selected from a group consisting of the text content match rate and the text geometric match rate exceeding a pre-determined threshold. | 1. A method for comparing documents, comprising: extracting, by a computer processor, a plurality of extracted elements from a first formatted document, wherein each of the plurality of extracted elements corresponds to a text element of the first formatted document, wherein the plurality of extracted elements comprises at least one selected from a group consisting of a plurality of words and a plurality of word lengths; extracting, by the computer processor, a first plurality of text fingerprints from a sequence of the plurality of extracted elements to form a first text feature of the first formatted document, wherein the first plurality of text fingerprints comprises at least one selected from a group consisting of a plurality of word n-grams and a plurality of word length n-grams, wherein the first text feature comprises at least one selected from a group consisting of a first text content feature based on the plurality of word n-grams and a first text geometric feature based on the plurality of word length n-grams; comparing, by the computer processor, the first text feature and a second text feature of a second formatted document to generate a comparison result, wherein the second text feature comprises at least one selected from a group consisting of a second text content feature and a second text geometric feature, wherein the comparison result comprises at least one selected from a group consisting of a text content match rate between the first and second text content features and a text geometric match rate between the first and second text geometric features; and determining, in response to the comparison result meeting a pre-determined criterion, that each of the first formatted document and the second formatted document contains common text content, wherein the comparison result meeting the pre-determined criterion is based on at least one selected from a group consisting of the text content match rate and the text geometric match rate exceeding a pre-determined threshold. 8. The method of claim 1 , wherein the plurality of extracted elements comprises a plurality of words, the method further comprising: extracting a segment of consecutive words from the plurality of words, wherein the first plurality of text fingerprints is based at least on the segment. | 0.827108 |
9,788,960 | 2 | 6 | 2. A tool for the spinal implant according to claim 1 , the tool comprising: a handle; a lever coupled to the handle, the lever comprising: an inner rotator, the inner rotator comprising a tooth coupled to an end of the inner rotator; and an outer rotator, the outer rotator comprising a tooth coupled to an end of the outer rotator, the inner rotator to be used independently from the outer rotator. | 2. A tool for the spinal implant according to claim 1 , the tool comprising: a handle; a lever coupled to the handle, the lever comprising: an inner rotator, the inner rotator comprising a tooth coupled to an end of the inner rotator; and an outer rotator, the outer rotator comprising a tooth coupled to an end of the outer rotator, the inner rotator to be used independently from the outer rotator. 6. The tool according to claim 2 , wherein the tooth of the inner rotator is to engage the first lever accommodation at substantially the same time the tooth of the outer rotator is to engage the second lever accommodation. | 0.940086 |
8,090,669 | 12 | 14 | 12. A computer-implemented method of analyzing effectiveness of a text correction tool, comprising: testing an error correction model of the text correction tool using a training corpus of original text and annotated text; receiving flagged text from the text correction tool based on the testing; applying simulated user actions to the flagged text based on a user model; employing an adaptive learning algorithm that learns based on implicit accepts and implicit ignores relative to the flagged text; generating and sending updates to the error correction model based on the simulated user actions; and computing quality data that represents effectiveness of the adaptive learning algorithm in learning the error correction model. | 12. A computer-implemented method of analyzing effectiveness of a text correction tool, comprising: testing an error correction model of the text correction tool using a training corpus of original text and annotated text; receiving flagged text from the text correction tool based on the testing; applying simulated user actions to the flagged text based on a user model; employing an adaptive learning algorithm that learns based on implicit accepts and implicit ignores relative to the flagged text; generating and sending updates to the error correction model based on the simulated user actions; and computing quality data that represents effectiveness of the adaptive learning algorithm in learning the error correction model. 14. The method of claim 12 , further comprising generating the training corpus to retain positions of the annotated text in a document and relative to surrounding context, and one or more occurrences of correctly-flagged text in the document. | 0.570922 |
9,679,047 | 1 | 2 | 1. A method comprising: under control of one or more computer systems configured with specific executable instructions, determining a genre of an electronic book based at least in part on a prior categorization of the electronic book, the prior categorization having previously classified the contents of the electronic book; receiving, on an electronic book reader device displaying the electronic book, a request for a definition of a word found within contents of the electronic book; selecting, based at least in part on the determined genre of the electronic book, a dictionary entry from multiple different dictionary entries each providing a definition of the word; locating the definition of the word from the selected dictionary entry; displaying the definition of the word from the selected dictionary entry on the electronic book reader device at least partly in response to the receiving of the request receiving feedback regarding the determined genre or the selected dictionary entry; and determining a different genre of the electronic book based at least in part on the received feedback. | 1. A method comprising: under control of one or more computer systems configured with specific executable instructions, determining a genre of an electronic book based at least in part on a prior categorization of the electronic book, the prior categorization having previously classified the contents of the electronic book; receiving, on an electronic book reader device displaying the electronic book, a request for a definition of a word found within contents of the electronic book; selecting, based at least in part on the determined genre of the electronic book, a dictionary entry from multiple different dictionary entries each providing a definition of the word; locating the definition of the word from the selected dictionary entry; displaying the definition of the word from the selected dictionary entry on the electronic book reader device at least partly in response to the receiving of the request receiving feedback regarding the determined genre or the selected dictionary entry; and determining a different genre of the electronic book based at least in part on the received feedback. 2. A method as recited in claim 1 , wherein the determined genre of the electronic book comprises a genre related to science, science fiction, medicine, business, law, or a foreign language. | 0.900938 |
8,285,196 | 14 | 15 | 14. The method of claim 9 , wherein the questionnaire comprises criteria tags inserted by the distribution server wherein the criteria tags determine the criteria for analysis by the distribution server, an age based analysis, a priority based analysis and a satisfaction level analysis. | 14. The method of claim 9 , wherein the questionnaire comprises criteria tags inserted by the distribution server wherein the criteria tags determine the criteria for analysis by the distribution server, an age based analysis, a priority based analysis and a satisfaction level analysis. 15. The method of claim 14 , wherein the questionnaire comprises at least one question soliciting selection by a user of an agreement level, in response to which the electronic device prompts the user to select at least one level of agreement from the set comprising ‘Strongly Agree’, ‘Somewhat Agree’, ‘Neutral’, ‘Somewhat Disagree’ and ‘Strongly Disagree. | 0.788507 |
7,496,547 | 1 | 2 | 1. A method implemented by a stylus-based personal computer for recognizing handwriting of a particular user, the method comprising: storing a set of handwriting samples of a particular user; receiving a handwritten inputs from the particular user for recognition; separately providing the handwritten input to first and second recognition engines, respectively, each of the first and second recognition engines applying a separate process for recognizing the handwritten input; producing by the recognition process of the first recognition engine a first list of alternative classifications of the handwritten input by matching features of the handwritten input to features of the stored handwriting samples of the particular user, each of the classifications of the first list comprising a potential character with an associated recognition probability; producing by the recognition process of the second recognition engine a second list of alternative classifications of the handwritten input without utilizing the stored handwriting samples, the process of the second recognition engine being designed to generically recognize handwriting for a plurality of users, each of the classifications of the second list comprising a potential character with an associated recognition probability; applying data of the handwritten input, the first list, and the second list to a comparative neural network for processing, the applied data including a context feature of the handwritten input, a descriptive feature of a potential character and an associated recognition probability from the first list, and a descriptive feature of a potential character and an associated probability from the second list; outputting a character as a recognition result of the handwritten input based on the processing of the neural network, the outputted character being one of the potential characters in the first and second lists; and adapting the stored set of handwriting samples by adding a previously received handwritten input from the particular user to the set before a subsequently received handwritten input from the particular user is provided to the first and second recognition engines, wherein the neural network is configured to merge the first and second lists by coalescing common classifications of the handwritten input in the first and second lists, wherein the neural network is based on a computational model comprising a group of interconnected processing units, and wherein the recognition process of the first recognition engine matches context features of the subsequently received handwritten input to the context features of the adapted set of handwriting samples to produce the first list for the subsequently received handwritten input. | 1. A method implemented by a stylus-based personal computer for recognizing handwriting of a particular user, the method comprising: storing a set of handwriting samples of a particular user; receiving a handwritten inputs from the particular user for recognition; separately providing the handwritten input to first and second recognition engines, respectively, each of the first and second recognition engines applying a separate process for recognizing the handwritten input; producing by the recognition process of the first recognition engine a first list of alternative classifications of the handwritten input by matching features of the handwritten input to features of the stored handwriting samples of the particular user, each of the classifications of the first list comprising a potential character with an associated recognition probability; producing by the recognition process of the second recognition engine a second list of alternative classifications of the handwritten input without utilizing the stored handwriting samples, the process of the second recognition engine being designed to generically recognize handwriting for a plurality of users, each of the classifications of the second list comprising a potential character with an associated recognition probability; applying data of the handwritten input, the first list, and the second list to a comparative neural network for processing, the applied data including a context feature of the handwritten input, a descriptive feature of a potential character and an associated recognition probability from the first list, and a descriptive feature of a potential character and an associated probability from the second list; outputting a character as a recognition result of the handwritten input based on the processing of the neural network, the outputted character being one of the potential characters in the first and second lists; and adapting the stored set of handwriting samples by adding a previously received handwritten input from the particular user to the set before a subsequently received handwritten input from the particular user is provided to the first and second recognition engines, wherein the neural network is configured to merge the first and second lists by coalescing common classifications of the handwritten input in the first and second lists, wherein the neural network is based on a computational model comprising a group of interconnected processing units, and wherein the recognition process of the first recognition engine matches context features of the subsequently received handwritten input to the context features of the adapted set of handwriting samples to produce the first list for the subsequently received handwritten input. 2. The method recited in claim 1 , wherein the first and second lists are generated by respective handwriting recognition engines. | 0.895833 |
8,249,855 | 3 | 4 | 3. The method of claim 1 and further comprising: prior to determining whether the candidate text includes a link, determining whether the candidate text includes a set of parallel, bi-lingual texts. | 3. The method of claim 1 and further comprising: prior to determining whether the candidate text includes a link, determining whether the candidate text includes a set of parallel, bi-lingual texts. 4. The method of claim 3 and further comprising: determining whether the candidate text includes words in the target language; if so, executing a target language query over the network to query the multiple data sources using the words in the target language; and determining whether texts returned in response to the target language query are parallel to the candidate text. | 0.926958 |
8,949,233 | 6 | 9 | 6. A computer-implemented method comprising: receiving, at one or more computers comprising at least one processor and at least one memory, a definition of a perspective into a dataset associated with N separate ontologies that each specify relationships among data elements in the dataset, wherein N is greater than two, the N separate ontologies correspond to an N dimensional information space, and the data elements are placed in the N dimensional information space according to semantic similarity among ontology elements, wherein the number N of dimensions in the information space matches up with the number N of the separate ontologies; reducing, at the one or more computers, the N dimensional information space to X dimensions based on the perspective definition, wherein X is greater than one and less than the perspective comprises a projection from the N-dimensional space to the X-dimensional space, and the perspective definition defines a mapping from original N axes to target X axes, the perspective definition being denotable as P N→3 =(F 1 (DS 1 ), F 2 (DS 2 ), F 3 (DS 3 )), where P N→3 represents a perspective that maps information from N-dimensional space to 3-D space, F i represents mapping functions from original N-dimensional axes to a target i-th axis, and DS i represents original axes that participate in a transformation; and presenting a visual representation of the dataset in the X dimensional space. | 6. A computer-implemented method comprising: receiving, at one or more computers comprising at least one processor and at least one memory, a definition of a perspective into a dataset associated with N separate ontologies that each specify relationships among data elements in the dataset, wherein N is greater than two, the N separate ontologies correspond to an N dimensional information space, and the data elements are placed in the N dimensional information space according to semantic similarity among ontology elements, wherein the number N of dimensions in the information space matches up with the number N of the separate ontologies; reducing, at the one or more computers, the N dimensional information space to X dimensions based on the perspective definition, wherein X is greater than one and less than the perspective comprises a projection from the N-dimensional space to the X-dimensional space, and the perspective definition defines a mapping from original N axes to target X axes, the perspective definition being denotable as P N→3 =(F 1 (DS 1 ), F 2 (DS 2 ), F 3 (DS 3 )), where P N→3 represents a perspective that maps information from N-dimensional space to 3-D space, F i represents mapping functions from original N-dimensional axes to a target i-th axis, and DS i represents original axes that participate in a transformation; and presenting a visual representation of the dataset in the X dimensional space. 9. The method of claim 6 , wherein the data elements are placed in the N dimensional information space by a process comprising determining distances among the data elements with respect to a given ontology based on a tree structure of the given ontology and estimates of co-relation between the ontology elements of the given ontology, wherein the estimates are based on a corpus including data elements associated with the ontology elements and documents retrieved from a computer network in accordance with terms retrieved from the data elements associated with the ontology elements. | 0.784559 |
9,721,563 | 12 | 17 | 12. The method as in claim 11 , wherein the method further comprises: obtaining changes in the contacts database and processing, using the plurality of pronunciation guessers, the changes to update the extended phonetic dictionary based on the changes, wherein the obtaining of the changes occurs in response to the changes being made. | 12. The method as in claim 11 , wherein the method further comprises: obtaining changes in the contacts database and processing, using the plurality of pronunciation guessers, the changes to update the extended phonetic dictionary based on the changes, wherein the obtaining of the changes occurs in response to the changes being made. 17. The method as in claim 12 wherein the method is performed by the user's device which includes the contacts database. | 0.940535 |
6,119,078 | 17 | 18 | 17. A computer program product for automatically translating a requested Web page from a first language to a second language, wherein the requested web page is stored within a server remotely located from a client requesting the Web page and wherein the Web page is configured to be displayed in a first language by the requesting client, comprising: a computer usable medium having computer readable program code means embodied in said medium for transmitting a request for the Web page from the client to the server via a communications network, wherein the Web page request comprises a universal resource locator that identifies a path to the Web page on the server, and wherein at least a portion of the universal resource locator is associated with a translating environment; computer readable program code means embodied in said medium for identifying a translating environment associated with the transmitted universal resource locator; computer readable program code means embodied in said medium for selecting the identified translating environment from a plurality of translating environments; and computer readable program code means embodied in said medium for translating the requested Web page from the first language to the second language using the selected translating environment prior to serving the requested Web page to the requesting client. | 17. A computer program product for automatically translating a requested Web page from a first language to a second language, wherein the requested web page is stored within a server remotely located from a client requesting the Web page and wherein the Web page is configured to be displayed in a first language by the requesting client, comprising: a computer usable medium having computer readable program code means embodied in said medium for transmitting a request for the Web page from the client to the server via a communications network, wherein the Web page request comprises a universal resource locator that identifies a path to the Web page on the server, and wherein at least a portion of the universal resource locator is associated with a translating environment; computer readable program code means embodied in said medium for identifying a translating environment associated with the transmitted universal resource locator; computer readable program code means embodied in said medium for selecting the identified translating environment from a plurality of translating environments; and computer readable program code means embodied in said medium for translating the requested Web page from the first language to the second language using the selected translating environment prior to serving the requested Web page to the requesting client. 18. A computer program product according to claim 17 wherein the at least one portion of the universal resource locator associated with the translating environment comprises at least one character string. | 0.725806 |
10,157,365 | 9 | 14 | 9. A system comprising: a memory; and a processing device, operatively coupled to the memory to: identify, via a user interface, a plurality of service oriented candidates in a service-oriented architecture (SOA) service model, wherein the plurality of service oriented comprise a first service candidate, a second service candidate, and a composition candidate, and wherein the composition candidate comprises at least the first service candidate and the second service candidate; replace a composition candidate inventory presented in a first portion of the user interface with a service candidate inventory comprising the first service candidate and the second service candidate in response to a selection of the composition candidate from the composition candidate inventory; add, via drag and drop operations, the first service candidate and the second service candidate to the composition candidate, wherein a first visualization of the first service candidate and a second visualization of the second service candidate are comprised in a layout of the composition candidate in a second portion of the user interface; receive, via the user interface, information to define a relationship between the first service candidate and the second service candidate; responsive to a determination that the relationship complies with a SOA principle: add the relationship to the SOA service model; update one or more relationship counters associated with the composition candidate, wherein the one or more relationship counters are updated to track the relationship between the first service candidate and the second service candidate; and provide, in view of an indicated selected function of a modeling tool provided via the user interface, the one or more relationship counters on the user interface; and reuse, via the user interface, the first service candidate, the second service candidate, and the composition candidate according to the relationship and the one or more relationship counters. | 9. A system comprising: a memory; and a processing device, operatively coupled to the memory to: identify, via a user interface, a plurality of service oriented candidates in a service-oriented architecture (SOA) service model, wherein the plurality of service oriented comprise a first service candidate, a second service candidate, and a composition candidate, and wherein the composition candidate comprises at least the first service candidate and the second service candidate; replace a composition candidate inventory presented in a first portion of the user interface with a service candidate inventory comprising the first service candidate and the second service candidate in response to a selection of the composition candidate from the composition candidate inventory; add, via drag and drop operations, the first service candidate and the second service candidate to the composition candidate, wherein a first visualization of the first service candidate and a second visualization of the second service candidate are comprised in a layout of the composition candidate in a second portion of the user interface; receive, via the user interface, information to define a relationship between the first service candidate and the second service candidate; responsive to a determination that the relationship complies with a SOA principle: add the relationship to the SOA service model; update one or more relationship counters associated with the composition candidate, wherein the one or more relationship counters are updated to track the relationship between the first service candidate and the second service candidate; and provide, in view of an indicated selected function of a modeling tool provided via the user interface, the one or more relationship counters on the user interface; and reuse, via the user interface, the first service candidate, the second service candidate, and the composition candidate according to the relationship and the one or more relationship counters. 14. The system of claim 9 , the processing device to update one or more different relationship counters associated with the first service candidate or the second service candidate, the one or more different relationship counters displayed in the user interface. | 0.650134 |
7,483,877 | 4 | 5 | 4. A method of determining the relative effectiveness of search engines comprising the steps of: selecting documents from a database; generating from the selected documents controlled relevant documents by manipulation of relevant terms in the selected documents based on a relevancy algorithm; wherein the relevancy algorithm relates to positions of the relevant terms in documents and the generation of the controlled relevant documents is done by placing search terms into various positions in the controlled relevant documents in accordance with the relevant algorithm; using the generated controlled relevant documents to create relevancy reference vectors; searching the database using each of the search engines and generating performance vectors with the search results for each engine; and comparing the performance vectors for each engine to the relevancy reference vectors to provide a relevancy rating for the search engines based on the relevancy algorithm using a relevancy vector chart made from the relevancy reference vectors to obtain a relative ranking of each of the search engines wherein at least 3 different controlled relevant documents are produced for each selected document using a given relevancy algorithm with search terms placed in 3 different positions in different documents with each document compared with the document relevant to the search area with an absence of search terms in the document to generate the relevancy reference vectors of the relevancy vector chart. | 4. A method of determining the relative effectiveness of search engines comprising the steps of: selecting documents from a database; generating from the selected documents controlled relevant documents by manipulation of relevant terms in the selected documents based on a relevancy algorithm; wherein the relevancy algorithm relates to positions of the relevant terms in documents and the generation of the controlled relevant documents is done by placing search terms into various positions in the controlled relevant documents in accordance with the relevant algorithm; using the generated controlled relevant documents to create relevancy reference vectors; searching the database using each of the search engines and generating performance vectors with the search results for each engine; and comparing the performance vectors for each engine to the relevancy reference vectors to provide a relevancy rating for the search engines based on the relevancy algorithm using a relevancy vector chart made from the relevancy reference vectors to obtain a relative ranking of each of the search engines wherein at least 3 different controlled relevant documents are produced for each selected document using a given relevancy algorithm with search terms placed in 3 different positions in different documents with each document compared with the document relevant to the search area with an absence of search terms in the document to generate the relevancy reference vectors of the relevancy vector chart. 5. The method of claim 4 , including removing relevant terms from the selected documents prior to placing the search terms into the various positions of the controlled relevant documents. | 0.76799 |
9,996,529 | 6 | 7 | 6. The method of claim 1 , wherein the first user interface further comprises a sorted list comprising the one or more analysis results such that an analysis result corresponding to the largest number of items is placed at a top of the sorted list, the analysis result comprising a numerical value identifying a number of items that pertain to a search term, the individual analysis result that is selected being visually differentiated from the one or more analysis results. | 6. The method of claim 1 , wherein the first user interface further comprises a sorted list comprising the one or more analysis results such that an analysis result corresponding to the largest number of items is placed at a top of the sorted list, the analysis result comprising a numerical value identifying a number of items that pertain to a search term, the individual analysis result that is selected being visually differentiated from the one or more analysis results. 7. The method of claim 6 , in which the user interface provides a listing of the two or more themes, along with content associated with a selected theme. | 0.9778 |
9,606,989 | 15 | 19 | 15. A system, the system comprising: a processor and memory configured to execute computer programs; a first application program having a first thread and a second thread; a second application program; a soft keyboard generator program configured to: receiving a selection of an input language for an application accepting input through a computer; based on the selection, determining the input language for the application program accepting input through the computer, wherein the input language is associated with both rendering a soft keyboard and designating a recognizer for the computer; determine whether the input language matches a language of the recognizer associated with the computer, wherein when the input language matches, the recognizer is designated for recognizing input based on the input language; designating the recognizer, for receiving input associated with the recognizer, based on determining that the input language matches the language of the recognizer associated with the computer, wherein rendering the soft keyboard and designating the recognizer is performed based on a thread of the first application program, wherein a user interface of the computer supports toggling between the soft keyboard and the recognizer, wherein the recognizer comprises one recognizer selected from the following: a handwriting recognizer; and a speech recognizer; and causing rendering of a soft keyboard on a display of the computer, wherein the soft keyboard is configured based, at least in part, on the input language for the first application program. | 15. A system, the system comprising: a processor and memory configured to execute computer programs; a first application program having a first thread and a second thread; a second application program; a soft keyboard generator program configured to: receiving a selection of an input language for an application accepting input through a computer; based on the selection, determining the input language for the application program accepting input through the computer, wherein the input language is associated with both rendering a soft keyboard and designating a recognizer for the computer; determine whether the input language matches a language of the recognizer associated with the computer, wherein when the input language matches, the recognizer is designated for recognizing input based on the input language; designating the recognizer, for receiving input associated with the recognizer, based on determining that the input language matches the language of the recognizer associated with the computer, wherein rendering the soft keyboard and designating the recognizer is performed based on a thread of the first application program, wherein a user interface of the computer supports toggling between the soft keyboard and the recognizer, wherein the recognizer comprises one recognizer selected from the following: a handwriting recognizer; and a speech recognizer; and causing rendering of a soft keyboard on a display of the computer, wherein the soft keyboard is configured based, at least in part, on the input language for the first application program. 19. The system of claim 15 , further comprising switching from a first recognizer as the designated recognizer to a second recognizer as the designated recognize when the second recognizer corresponds to a change in the input language. | 0.766865 |
9,959,607 | 3 | 4 | 3. The method of claim 1 , further comprising: creating an initial JSON file that causes the front end computer device to generate an initial front end graphic presentation of the data values of the baseline set of data of the back end data warehouse server that fails to meet the boundary condition requirement for displaying the data values; revising the initial JSON file into a revised JSON file in an iterative process in the front end computer device until the revised JSON file is used by the front end computer device to render graphic presentation results that meet the boundary condition requirement; and storing the revised JSON file as the stored baseline JSON file that is stored in the local file system for retrieval to the local reverse proxy server in response to the request from the front end computer device. | 3. The method of claim 1 , further comprising: creating an initial JSON file that causes the front end computer device to generate an initial front end graphic presentation of the data values of the baseline set of data of the back end data warehouse server that fails to meet the boundary condition requirement for displaying the data values; revising the initial JSON file into a revised JSON file in an iterative process in the front end computer device until the revised JSON file is used by the front end computer device to render graphic presentation results that meet the boundary condition requirement; and storing the revised JSON file as the stored baseline JSON file that is stored in the local file system for retrieval to the local reverse proxy server in response to the request from the front end computer device. 4. The method of claim 3 , wherein the values of the boundary condition requirement displayed in each of said graphic presentations comprise at least one of a chart element value, a graph element value and a report element value. | 0.960734 |
8,332,624 | 1 | 7 | 1. A method comprising: constructing a reduced ordered binary decision diagram from a resource description framework graph; computing a hash identifier corresponding to the decision diagram; and causing, at least in part, a storing of the hash identifier with the decision diagram. | 1. A method comprising: constructing a reduced ordered binary decision diagram from a resource description framework graph; computing a hash identifier corresponding to the decision diagram; and causing, at least in part, a storing of the hash identifier with the decision diagram. 7. A method of claim 1 , further comprising: receiving a keyed hash identifier of the decision diagram and an identifier of a key used to encrypt the hash identifier into the keyed hash identifier of the decision diagram; searching for the key with the received key identifier; and decrypting the keyed hash identifier with the key to generate the hash identifier. | 0.726727 |
8,812,315 | 9 | 15 | 9. A system comprising: a processor; and a computer-readable storage medium having instructions stored which, when executed by the processor, cause the processor to perform operations comprising: identifying an acoustic model, wherein the acoustic model is trained on native speech in a target dialect; transcribing collected speech from a speaker, to yield a lattice of plausible phonemes which depend on a property of the target dialect; and replacing each phoneme in the acoustic model with a modified phoneme, wherein the modified phoneme is a weighted sum of plausible phonemes in the lattice of plausible phonemes. | 9. A system comprising: a processor; and a computer-readable storage medium having instructions stored which, when executed by the processor, cause the processor to perform operations comprising: identifying an acoustic model, wherein the acoustic model is trained on native speech in a target dialect; transcribing collected speech from a speaker, to yield a lattice of plausible phonemes which depend on a property of the target dialect; and replacing each phoneme in the acoustic model with a modified phoneme, wherein the modified phoneme is a weighted sum of plausible phonemes in the lattice of plausible phonemes. 15. The system of claim 9 , wherein the replacing of each phoneme in the acoustic model is performed iteratively. | 0.610345 |
9,614,807 | 11 | 14 | 11. The method of claim 1 , wherein, the set of messages include messages with different destinations and different origins. | 11. The method of claim 1 , wherein, the set of messages include messages with different destinations and different origins. 14. The method of claim 11 , wherein an origin site includes one or more of, a social media network and a user. | 0.955812 |
8,326,091 | 2 | 4 | 2. The method of claim 1 , wherein the determining the probabilities of navigating between images in the plurality of images comprises: determining degrees of similarity between one or more pairs of images in the plurality of images; and wherein the probabilities of navigating between images in the plurality of images are determined based on the degrees of similarity. | 2. The method of claim 1 , wherein the determining the probabilities of navigating between images in the plurality of images comprises: determining degrees of similarity between one or more pairs of images in the plurality of images; and wherein the probabilities of navigating between images in the plurality of images are determined based on the degrees of similarity. 4. The method of claim 2 , wherein the probabilities of navigating between images in the plurality of images are further determined based on quality metrics of the images in the plurality of images. | 0.936782 |
7,533,034 | 1 | 4 | 1. A computer implemented method for providing through a computer network to business management a plan for implementing a user's suggestion for business improvement, the method comprising: in a first computer process, causing presentation to a user seeking to submit a suggestion for business improvement, a series of two or more templates for entering a structured response on a terminal device, wherein one of the templates presented to the user allows the user to characterize the type of suggestion as falling into at least one of a plurality of categories selected from a group of cost saving, revenue generation, quality improvement, safety improvement, customer service improvement, development of a new product, policy change and advertising or corporate slogan; receiving over a computer network the structured response, entered into the two or more templates from the user, wherein the structured response includes a characterization of the type of suggestion entered into one or more templates by the user and a server logically selects at least one of the templates presented to the user according to the type of suggestion characterized by the user; and in a second computer process, determining the network routing of data from the structured response to business management based upon entries of the response in one or more templates. | 1. A computer implemented method for providing through a computer network to business management a plan for implementing a user's suggestion for business improvement, the method comprising: in a first computer process, causing presentation to a user seeking to submit a suggestion for business improvement, a series of two or more templates for entering a structured response on a terminal device, wherein one of the templates presented to the user allows the user to characterize the type of suggestion as falling into at least one of a plurality of categories selected from a group of cost saving, revenue generation, quality improvement, safety improvement, customer service improvement, development of a new product, policy change and advertising or corporate slogan; receiving over a computer network the structured response, entered into the two or more templates from the user, wherein the structured response includes a characterization of the type of suggestion entered into one or more templates by the user and a server logically selects at least one of the templates presented to the user according to the type of suggestion characterized by the user; and in a second computer process, determining the network routing of data from the structured response to business management based upon entries of the response in one or more templates. 4. The method according to claim 1 , wherein at least one template provides for access to a database containing cost information. | 0.764599 |
8,578,323 | 8 | 10 | 8. The computer program product of claim 7 , where in causing the computer to retrieve the main program from the memory, the computer readable program code when executed on the computer causes the computer to: retrieve at least one layer file associated with the main program from the memory; display program code corresponding to the at least one layer file and the main program; and where the computer readable program code when executed on the computer further causes the computer to: determine whether to hide the program code corresponding to at least one of the at least one layer file in response to a detected user input from a user; and where in causing the computer to initiate the layer representing the portion of the main program for editing on the display, the computer readable program code when executed on the computer causes the computer to initiate the layer based upon the determination of whether to hide the program code corresponding to the at least one of the at least one layer file. | 8. The computer program product of claim 7 , where in causing the computer to retrieve the main program from the memory, the computer readable program code when executed on the computer causes the computer to: retrieve at least one layer file associated with the main program from the memory; display program code corresponding to the at least one layer file and the main program; and where the computer readable program code when executed on the computer further causes the computer to: determine whether to hide the program code corresponding to at least one of the at least one layer file in response to a detected user input from a user; and where in causing the computer to initiate the layer representing the portion of the main program for editing on the display, the computer readable program code when executed on the computer causes the computer to initiate the layer based upon the determination of whether to hide the program code corresponding to the at least one of the at least one layer file. 10. The computer program product of claim 8 , where in causing the computer to display the program code corresponding to the at least one layer file and the main program, the computer readable program code when executed on the computer causes the computer to: differentiate between the program code corresponding to the at least one layer file and the program code corresponding to the main program using a recognition marker, where the recognition marker comprises at least one of a background color, a text color, a frame line, a font, and a transparency. | 0.608848 |
9,977,510 | 1 | 5 | 1. A method comprising: receiving of gesture event data by a client application of a gesture-driven introduction system running on a user device of a first human actor, wherein the gesture event data comprises a gesture and at least one ancillary condition regarding performance of the gesture by a second human actor, wherein the gesture is representative of a discrete non-empty set of deliberate motions whose execution utilizes at least one visible and movable body part of the second human actor, wherein the first human actor and the second human actor are registered members of the gesture-driven introduction system; assessing the received gesture event data with respect to at least one introduction definition created by the first human actor, wherein an introduction definition defines triggering parameters for exchanging predetermined introduction data, wherein the triggering parameters comprise at least one gesture and at least one ancillary condition; and when the gesture event data is assessed as satisfying the triggering parameters expressed in an introduction definition, automatically transmitting the predetermined introduction data of the respective introduction definition to a user device of the second human actor, wherein said transmission occurs without direct physical or verbal interaction between the first and second human actors. | 1. A method comprising: receiving of gesture event data by a client application of a gesture-driven introduction system running on a user device of a first human actor, wherein the gesture event data comprises a gesture and at least one ancillary condition regarding performance of the gesture by a second human actor, wherein the gesture is representative of a discrete non-empty set of deliberate motions whose execution utilizes at least one visible and movable body part of the second human actor, wherein the first human actor and the second human actor are registered members of the gesture-driven introduction system; assessing the received gesture event data with respect to at least one introduction definition created by the first human actor, wherein an introduction definition defines triggering parameters for exchanging predetermined introduction data, wherein the triggering parameters comprise at least one gesture and at least one ancillary condition; and when the gesture event data is assessed as satisfying the triggering parameters expressed in an introduction definition, automatically transmitting the predetermined introduction data of the respective introduction definition to a user device of the second human actor, wherein said transmission occurs without direct physical or verbal interaction between the first and second human actors. 5. The method of claim 1 , wherein transmission of the predetermined introduction data utilizes one of a BLUETOOTH communications network, a near-field communications network, a wireless communications network, and a cellular communications network, wherein a selection of the communications network to utilize is based upon a proximity and capability of the first and second human actors' respective user devices. | 0.849564 |
8,332,220 | 35 | 37 | 35. The at least one computer readable recordable medium of claim 29 , wherein providing to a multiplicity of users a presentation comprises: providing a session document for the presentation, wherein the session document includes a session grammar and a session structured document; selecting from the session structured document a classified structural element in dependence upon user classifications of a user participant in the presentation; and presenting the selected structural element to the user participant. | 35. The at least one computer readable recordable medium of claim 29 , wherein providing to a multiplicity of users a presentation comprises: providing a session document for the presentation, wherein the session document includes a session grammar and a session structured document; selecting from the session structured document a classified structural element in dependence upon user classifications of a user participant in the presentation; and presenting the selected structural element to the user participant. 37. The at least one computer readable recordable medium of claim 35 , wherein the method further comprises creating a session document from a presentation document, including: identifying a presentation document for a presentation, the presentation document including a presentation grammar and a structured document having structural elements classified with classification identifiers; identifying a user participant for the presentation, the user participant having a user profile comprising user classifications; and filtering the structured document in dependence upon the user classifications and the classification identifiers. | 0.657497 |
7,797,180 | 2 | 3 | 2. A method as set forth in claim 1 , wherein the step of extracting includes profiling of the heterogeneous data to yield entities for the business location. | 2. A method as set forth in claim 1 , wherein the step of extracting includes profiling of the heterogeneous data to yield entities for the business location. 3. A method as set forth in claim 2 , wherein profiling of the heterogeneous data includes calculating entity attributes chosen from at least one of: Value Ratio, Focal Values, Impact, Revenue Difference, Support, and Baseline Value. | 0.779773 |
8,880,516 | 20 | 30 | 20. A system comprising: a member network server implemented by one or more computer processors, the member network server comprising: a member network database stored in machine-readable memory, the member network database storing profiles that represent members in a member network, the profiles comprising endorsements of electronic documents including web pages; and a member network engine programmed to allow users to interact with and participate in the member network, including by classifying particular electronic documents as user endorsed electronic documents by inputting a favorable rating on a control that is displayed simultaneously with an identifier for a corresponding electronic document; and a search engine server implemented by one or more computer processors, the search engine server comprising: an article index stored in machine-readable memory, the article index indexing electronic documents stored at other devices or systems; and a search engine programmed to respond to receipt of a local query signal that embodies a local search query for a particular geographic locality made by a query-submitting member of the member network, by performing operations comprising: performing a search of the article index to locate local information responsive to the local search query and for the particular geographic locality in the electronic documents indexed by the article index, and returning identifiers of the electronic documents in a first local search result set; communicating with the member network engine to identify particular members in the member network who have provided endorsements; accessing the member profiles of the particular members to identify the endorsements in the member profiles of the particular members and returning the identified endorsements in a second local search result set; merging the first local search result set and the second local search result set to form a final local search result set, wherein a ranking of the identifiers for the electronic documents in the final local search result set differs from a ranking of the identifiers for the electronic documents in the first local search result set and a ranking of the identifiers for the electronic documents in the second local search result set; and providing the final local search result set for presentation to the query-submitting member of the member network, wherein the presentation identifies, for particular ones of the final local search result set, the particular members in the member network identified as having provided endorsements for electronic documents that correspond to the particular ones of the final local search result set. | 20. A system comprising: a member network server implemented by one or more computer processors, the member network server comprising: a member network database stored in machine-readable memory, the member network database storing profiles that represent members in a member network, the profiles comprising endorsements of electronic documents including web pages; and a member network engine programmed to allow users to interact with and participate in the member network, including by classifying particular electronic documents as user endorsed electronic documents by inputting a favorable rating on a control that is displayed simultaneously with an identifier for a corresponding electronic document; and a search engine server implemented by one or more computer processors, the search engine server comprising: an article index stored in machine-readable memory, the article index indexing electronic documents stored at other devices or systems; and a search engine programmed to respond to receipt of a local query signal that embodies a local search query for a particular geographic locality made by a query-submitting member of the member network, by performing operations comprising: performing a search of the article index to locate local information responsive to the local search query and for the particular geographic locality in the electronic documents indexed by the article index, and returning identifiers of the electronic documents in a first local search result set; communicating with the member network engine to identify particular members in the member network who have provided endorsements; accessing the member profiles of the particular members to identify the endorsements in the member profiles of the particular members and returning the identified endorsements in a second local search result set; merging the first local search result set and the second local search result set to form a final local search result set, wherein a ranking of the identifiers for the electronic documents in the final local search result set differs from a ranking of the identifiers for the electronic documents in the first local search result set and a ranking of the identifiers for the electronic documents in the second local search result set; and providing the final local search result set for presentation to the query-submitting member of the member network, wherein the presentation identifies, for particular ones of the final local search result set, the particular members in the member network identified as having provided endorsements for electronic documents that correspond to the particular ones of the final local search result set. 30. The system of claim 20 , wherein the final local search result set comprises annotations indicative of the electronic document endorsements identified in the member profiles of the particular members. | 0.779221 |
9,411,972 | 12 | 13 | 12. A method for creating a single sign-on identity for a plurality of different groups, the method comprising: for each respective group of the plurality of different groups, receiving, via an interface, a selected group identification, a user id and a user passcode; generating, by a n-bit generator from the group identification, user id and user passcode, a n-bit result, wherein the n-bit result includes a shared secret for the respective group; and storing, in encrypted form, each shared secret for each respective group of the plurality of different groups in a secrets directory, the secrets directory further including one or more decoy files, each of the decoy files being of similar size as the encrypted shared secrets, wherein the storing in encrypted form each shared secret comprises selecting the encryption algorithm from among a plurality of encryption algorithms according to an encryption algorithm identifier according to information extracted from the n-bit result. | 12. A method for creating a single sign-on identity for a plurality of different groups, the method comprising: for each respective group of the plurality of different groups, receiving, via an interface, a selected group identification, a user id and a user passcode; generating, by a n-bit generator from the group identification, user id and user passcode, a n-bit result, wherein the n-bit result includes a shared secret for the respective group; and storing, in encrypted form, each shared secret for each respective group of the plurality of different groups in a secrets directory, the secrets directory further including one or more decoy files, each of the decoy files being of similar size as the encrypted shared secrets, wherein the storing in encrypted form each shared secret comprises selecting the encryption algorithm from among a plurality of encryption algorithms according to an encryption algorithm identifier according to information extracted from the n-bit result. 13. The method of claim 12 , wherein each shared secret is unique to each respective group of the plurality of different groups. | 0.813411 |
8,095,371 | 1 | 3 | 1. A method for providing voice responses to spoken input items received from a user during a session between the user and a voice response system, comprising: providing computer recognition of spoken input items; providing system responses to spoken input items; storing, in a dialog history log, a record of recognized spoken input items and system responses thereto, said record representing a dialog history; responsive to a determination that the system cannot provide a valid system response to spoken input items, using a dialog state determination model to determine the current state of the dialog with the user based on the dialog history log and a dialog state diagram definition file defining each expected dialog state for the session; forwarding the determined current dialog state to a visual information display remote from the user for use by a human operator other than the user; and forwarding a dialog state diagram including a representation of each dialog state defined by the dialog state diagram definition file, including at least one dialog state, other than a transition between dialog states, not yet entered during the session, to the visual information display for use by the human operator. | 1. A method for providing voice responses to spoken input items received from a user during a session between the user and a voice response system, comprising: providing computer recognition of spoken input items; providing system responses to spoken input items; storing, in a dialog history log, a record of recognized spoken input items and system responses thereto, said record representing a dialog history; responsive to a determination that the system cannot provide a valid system response to spoken input items, using a dialog state determination model to determine the current state of the dialog with the user based on the dialog history log and a dialog state diagram definition file defining each expected dialog state for the session; forwarding the determined current dialog state to a visual information display remote from the user for use by a human operator other than the user; and forwarding a dialog state diagram including a representation of each dialog state defined by the dialog state diagram definition file, including at least one dialog state, other than a transition between dialog states, not yet entered during the session, to the visual information display for use by the human operator. 3. The method according to claim 1 , wherein the dialog state diagram definition file defines each expected dialog state and the format in which each dialog state and associated input information is to be displayed to the human operator. | 0.776415 |
6,018,708 | 7 | 8 | 7. A speech recognition system as defined in claim 6, wherein said orthography insertion unit includes scoring means for scoring orthographies in said standard text lexicon on a basis of a potential match with the spoken utterance. | 7. A speech recognition system as defined in claim 6, wherein said orthography insertion unit includes scoring means for scoring orthographies in said standard text lexicon on a basis of a potential match with the spoken utterance. 8. A speech recognition system as defined in claim 7, wherein said first processing unit is operative to generate probability data indicative of a likelihood of an orthography to constitute a match to the spoken utterance, said scoring means utilizing said probability data for scoring orthographies in said standard text lexicon on a basis of a potential match with the spoken utterance. | 0.795574 |
9,501,585 | 1 | 8 | 1. A system, comprising: a processor; and a memory operatively coupled to the processor, the memory storing processor-readable instructions executable by the processor to: receive a data analytics request including a user desired data variable via a user interface; receive, via the user interface, user configured parameters identifying a plurality of user selected data sources and a plurality of user defined data fields for a new data set, a user defined data field from the plurality of user defined data fields representing a logic operation, each data source of the user selected data sources being a separate data source with a data structure schema different from a data structure schema of each of a remaining data source from the user selected data sources; generate an intermediate query based on the data analytics request; define an execution path for the intermediate query, the execution path including locations for a plurality of schema-independent distributed index files located on a plurality of distributed server node engines; transmit, substantially simultaneously, the intermediate query to each distributed service node engine of the plurality of distributed server node engines so as to instruct that distributed server node engine to run the intermediate query, using a schema-independent distributed index file from the plurality of schema-independent distributed index files that is stored at that distributed server node engine; receive intermediate query results from each distributed service node engine of the plurality of distributed server node engines based on the intermediate query; form the new data set based at least in part on the intermediate query results and on a relationship between the plurality of user selected data sources and the plurality of user defined data fields; query the new data set to obtain a first value relating to the user desired data variable; calculate an output value for the user desired data variable based on the first value and the logic operation; and send a signal to generate a user interactive graphical representation of the output value of user desired data variable. | 1. A system, comprising: a processor; and a memory operatively coupled to the processor, the memory storing processor-readable instructions executable by the processor to: receive a data analytics request including a user desired data variable via a user interface; receive, via the user interface, user configured parameters identifying a plurality of user selected data sources and a plurality of user defined data fields for a new data set, a user defined data field from the plurality of user defined data fields representing a logic operation, each data source of the user selected data sources being a separate data source with a data structure schema different from a data structure schema of each of a remaining data source from the user selected data sources; generate an intermediate query based on the data analytics request; define an execution path for the intermediate query, the execution path including locations for a plurality of schema-independent distributed index files located on a plurality of distributed server node engines; transmit, substantially simultaneously, the intermediate query to each distributed service node engine of the plurality of distributed server node engines so as to instruct that distributed server node engine to run the intermediate query, using a schema-independent distributed index file from the plurality of schema-independent distributed index files that is stored at that distributed server node engine; receive intermediate query results from each distributed service node engine of the plurality of distributed server node engines based on the intermediate query; form the new data set based at least in part on the intermediate query results and on a relationship between the plurality of user selected data sources and the plurality of user defined data fields; query the new data set to obtain a first value relating to the user desired data variable; calculate an output value for the user desired data variable based on the first value and the logic operation; and send a signal to generate a user interactive graphical representation of the output value of user desired data variable. 8. The method of claim 1 , wherein the user interactive graphical representation includes an engageable widget triggered to show an option of the user submitted query result parameter. | 0.768844 |
9,712,520 | 3 | 7 | 3. One or more non-transitory computer-readable media comprising instructions that, when executed with one or more processors, cause a system to at least: provide, to a computing system associated with a user account, a first network-based document of a network-based resource, the first network-based document comprising code and an identifier of a second network-based document of the network-based resource, the identifier comprising a network address of the second network-based document, the code configured at least to, upon execution: determine whether the network address and a cascading style sheets (CSS) attribute of the network address are present in a history stored at the computing system, and determine, based at least in part on presence of the network address and the CSS attribute in the history, that the second network-based document was accessed prior to providing the first network-based document to the computing system, the second network-based document accessed based at least in part on an identifier of the user account; determine an indication that the second network-based document was accessed, the indication determined based at least in part on a determination of the presence of the network address and the CSS attribute in the history upon an execution of the code at the computing system; and authenticate the user account based at least in part on the indication. | 3. One or more non-transitory computer-readable media comprising instructions that, when executed with one or more processors, cause a system to at least: provide, to a computing system associated with a user account, a first network-based document of a network-based resource, the first network-based document comprising code and an identifier of a second network-based document of the network-based resource, the identifier comprising a network address of the second network-based document, the code configured at least to, upon execution: determine whether the network address and a cascading style sheets (CSS) attribute of the network address are present in a history stored at the computing system, and determine, based at least in part on presence of the network address and the CSS attribute in the history, that the second network-based document was accessed prior to providing the first network-based document to the computing system, the second network-based document accessed based at least in part on an identifier of the user account; determine an indication that the second network-based document was accessed, the indication determined based at least in part on a determination of the presence of the network address and the CSS attribute in the history upon an execution of the code at the computing system; and authenticate the user account based at least in part on the indication. 7. The one or more non-transitory computer-readable media of claim 3 , wherein the identifier of the second network-based document is inserted in the first network-based document based at least in part on a selection of the second network-based document, wherein the selection is based at least in part on an identifier of the user account. | 0.756098 |
9,256,694 | 1 | 7 | 1. A computer-implemented method comprising: determining that, among a set of search results that are each identified as at least potentially relevant by a search engine in response to a search query submitted to the search engine, one or more of the search results are each classified by the search engine as very relevant to the search query; and in response to determining that, among the set of search results that are each identified as at least potentially relevant by the search engine in response to the search query submitted to the search engine, one or more of the search results are each classified by the search engine as very relevant to the search query: providing a search results page that (i) includes a subset of the search results, including the one or more search results that are each classified by the search engine as very relevant to the search query, and one or more search results that are identified as at least potentially relevant by the search engine but that are not each classified by the search engine as very relevant to the search query, (ii) includes a respective image in association with only those search results of the subset that are each classified by the search engine as very relevant to the search query, and (iii) does not include a respective image in association with those search results of the subset that are not each classified by the search engine as very relevant to the search query. | 1. A computer-implemented method comprising: determining that, among a set of search results that are each identified as at least potentially relevant by a search engine in response to a search query submitted to the search engine, one or more of the search results are each classified by the search engine as very relevant to the search query; and in response to determining that, among the set of search results that are each identified as at least potentially relevant by the search engine in response to the search query submitted to the search engine, one or more of the search results are each classified by the search engine as very relevant to the search query: providing a search results page that (i) includes a subset of the search results, including the one or more search results that are each classified by the search engine as very relevant to the search query, and one or more search results that are identified as at least potentially relevant by the search engine but that are not each classified by the search engine as very relevant to the search query, (ii) includes a respective image in association with only those search results of the subset that are each classified by the search engine as very relevant to the search query, and (iii) does not include a respective image in association with those search results of the subset that are not each classified by the search engine as very relevant to the search query. 7. The method of claim 1 , wherein the respective image comprises a logo associated with at least one of the search results that are each classified as very relevant to the search query. | 0.832734 |
7,552,055 | 13 | 14 | 13. The computer readable storage medium of claim 12 wherein said control is adapted to combine the processing of responses in the extra answer property with the processing of responses in the extra answer property of said another control identified in the imported answer property. | 13. The computer readable storage medium of claim 12 wherein said control is adapted to combine the processing of responses in the extra answer property with the processing of responses in the extra answer property of said another control identified in the imported answer property. 14. The computer readable storage medium of claim 13 wherein said control is adapted to combine the processing of responses in the extra answer property with the processing of responses m the extra answer property of said another control identified in the imported extra answer property. | 0.913917 |
9,898,390 | 1 | 13 | 1. A method comprising: instantiating a virtual service from a service model, wherein the virtual service is operable to receive requests intended for a particular one of a plurality of software components in a system and generate simulated responses of the particular software component based on a service model modeling responses of the particular software component, wherein the service model is based on monitored requests of the particular software component and monitored responses of the particular software component to the monitored requests; identifying a particular request from another software component intended for the particular software component, wherein the particular request is redirected to the virtual service; generating content of a simulated response to the particular request using the virtual service, wherein the content of the simulated response is in a first language based on the service model, the service model models responses of the particular software component in only a particular set of languages, and the particular set of languages comprises the first language; determining, based on the request, a second language to be applied to the simulated response, wherein the second language is outside the particular set of languages; determining, using a data processing apparatus, a translation of the content from the first language into the second language; and sending a modified version of the simulated response comprising the content in the second language to the other software component in response to the particular request. | 1. A method comprising: instantiating a virtual service from a service model, wherein the virtual service is operable to receive requests intended for a particular one of a plurality of software components in a system and generate simulated responses of the particular software component based on a service model modeling responses of the particular software component, wherein the service model is based on monitored requests of the particular software component and monitored responses of the particular software component to the monitored requests; identifying a particular request from another software component intended for the particular software component, wherein the particular request is redirected to the virtual service; generating content of a simulated response to the particular request using the virtual service, wherein the content of the simulated response is in a first language based on the service model, the service model models responses of the particular software component in only a particular set of languages, and the particular set of languages comprises the first language; determining, based on the request, a second language to be applied to the simulated response, wherein the second language is outside the particular set of languages; determining, using a data processing apparatus, a translation of the content from the first language into the second language; and sending a modified version of the simulated response comprising the content in the second language to the other software component in response to the particular request. 13. The method of claim 1 , wherein the second language is determined from content of the particular request. | 0.695531 |
9,733,821 | 1 | 9 | 1. A method, comprising: at an electronic device comprising a processor and memory storing instructions for execution by the processor: while the device is operating with a first setting in a first state, detecting, at a first time, a change in settings of the device to change the first setting from the first state to a second state that is different from the first state; while the device is operating with the first setting in the second state, receiving, at a second time that is after the first time, a user input that corresponds to a pattern of user behavior, wherein the user input is a user voice input; in response to receiving the user input: comparing the pattern of user behavior to a plurality of predefined conditions that, when met, indicate that the user is having difficulty with operating the device, wherein a predefined condition of the plurality of predefined conditions includes the user voice input containing one or more predetermined words associated with user difficulty; in accordance with a determination, based on the comparison of the pattern of user behavior to the plurality of predefined conditions, that the device changed the first setting from the first state to the second state within a predetermined time period prior to receiving the user input, restoring the first setting to the first state; and in accordance with a determination, based on the comparison of the pattern of user behavior to the plurality of predefined conditions, that the user is not having difficulty with operating the device, maintaining the first setting in the second state. | 1. A method, comprising: at an electronic device comprising a processor and memory storing instructions for execution by the processor: while the device is operating with a first setting in a first state, detecting, at a first time, a change in settings of the device to change the first setting from the first state to a second state that is different from the first state; while the device is operating with the first setting in the second state, receiving, at a second time that is after the first time, a user input that corresponds to a pattern of user behavior, wherein the user input is a user voice input; in response to receiving the user input: comparing the pattern of user behavior to a plurality of predefined conditions that, when met, indicate that the user is having difficulty with operating the device, wherein a predefined condition of the plurality of predefined conditions includes the user voice input containing one or more predetermined words associated with user difficulty; in accordance with a determination, based on the comparison of the pattern of user behavior to the plurality of predefined conditions, that the device changed the first setting from the first state to the second state within a predetermined time period prior to receiving the user input, restoring the first setting to the first state; and in accordance with a determination, based on the comparison of the pattern of user behavior to the plurality of predefined conditions, that the user is not having difficulty with operating the device, maintaining the first setting in the second state. 9. The method of claim 1 , further comprising: prior to restoring the first setting to the first state, prompting the user to confirm that the device operating with the first setting in the second state is causing the user difficulty with operating the device; and in response to receiving confirmation that the device operating with the first setting in the second state is causing the user difficulty with operating the device, restoring the first setting to the first state. | 0.620827 |
9,002,102 | 1 | 8 | 1. A method of generating training documents for training a classifying device comprising, with a processor: determining a number of sub-samples in a number of original documents; and creating a number of pseudo-documents from the sub-samples, the pseudo-documents comprising a portion of the number of sub-samples, in which each of the pseudo-documents are created by deleting a number of the sub-samples through a jackknife statistical method. | 1. A method of generating training documents for training a classifying device comprising, with a processor: determining a number of sub-samples in a number of original documents; and creating a number of pseudo-documents from the sub-samples, the pseudo-documents comprising a portion of the number of sub-samples, in which each of the pseudo-documents are created by deleting a number of the sub-samples through a jackknife statistical method. 8. The method of claim 1 , in which creating a number of pseudo-documents comprises creating at least 10 pseudo-documents per original document. | 0.84778 |
9,658,989 | 15 | 18 | 15. An apparatus for preparing a display document for analysis comprising a processor implementing: an extractor for extracting character data from said display document, wherein the character data comprises image data representing an image of a number of characters without including character codes; an order identifier for determining a first order associated with processing of said character data and a second order associated with a logical order of said character data, and for determining whether said first order is different from said second order, wherein determining the second order comprises identifying a punctuation character that is position dependent such that a space character will appear on only one side of the punctuation character, where the side of the punctuation character on which the space character appears depends on said second order; and a reverse component for reversing at least a portion of said character data, responsive to said order identifier determining that said first order is different from said second order. | 15. An apparatus for preparing a display document for analysis comprising a processor implementing: an extractor for extracting character data from said display document, wherein the character data comprises image data representing an image of a number of characters without including character codes; an order identifier for determining a first order associated with processing of said character data and a second order associated with a logical order of said character data, and for determining whether said first order is different from said second order, wherein determining the second order comprises identifying a punctuation character that is position dependent such that a space character will appear on only one side of the punctuation character, where the side of the punctuation character on which the space character appears depends on said second order; and a reverse component for reversing at least a portion of said character data, responsive to said order identifier determining that said first order is different from said second order. 18. The apparatus of claim 15 , wherein said order identifier is configured to compare said character data against a set of dictionaries in order to determine said second order. | 0.822645 |
7,970,764 | 3 | 6 | 3. The system of claim 1 , wherein the at least one selected search term is adapted to be selected by an input device. | 3. The system of claim 1 , wherein the at least one selected search term is adapted to be selected by an input device. 6. The system of claim 3 , wherein modifying the plurality of positions based on a new search term comprises decreasing the importance of the new search term in the neural network. | 0.90566 |
4,130,882 | 1 | 2 | 1. In an automatic word processing system including a keyboard, a printer and processor means for carrying out word processing functions indicated at the keyboard, each of which is connected to a common data bus and a common instruction word bus carrying instructions from said computer, improved apparatus for translating character information comprising: keyboard position information entered on said data bus at said keyboard, and language translation means for translating said keyboard position information as a function of a selected one of a plurality of language formats into media codes acceptable to said processor means, said language translation means being connected to said common data bus and said common instruction word bus and further including: a plurality of read-only memory storage means addressable for providing said media codes, means operatively connected to said common data bus and said plurality of read-only memory storage means for addressing said read-only memory storage means, along said common data bus, enabling means operatively connected to said common data bus and said common instruction word bus, for reading various read only memories for operation as a function of computer instructions present on said common instruction word bus and said data bus, output gating means for gating information read from said read only memories to said common data bus, said output gating means being operatively connected to said common data bus and said common instruction word bus and controlled by instructions on said common instruction bus, printer data memory for supplying printer codes for operation of said printer in one of a plurality of language formats, said printer data memory being operatively connected to said common data bus for receiving data from said gating means and said common instruction word bus, and further means within said language translation means for addressing certain read only memories for translating certain specific media codes. | 1. In an automatic word processing system including a keyboard, a printer and processor means for carrying out word processing functions indicated at the keyboard, each of which is connected to a common data bus and a common instruction word bus carrying instructions from said computer, improved apparatus for translating character information comprising: keyboard position information entered on said data bus at said keyboard, and language translation means for translating said keyboard position information as a function of a selected one of a plurality of language formats into media codes acceptable to said processor means, said language translation means being connected to said common data bus and said common instruction word bus and further including: a plurality of read-only memory storage means addressable for providing said media codes, means operatively connected to said common data bus and said plurality of read-only memory storage means for addressing said read-only memory storage means, along said common data bus, enabling means operatively connected to said common data bus and said common instruction word bus, for reading various read only memories for operation as a function of computer instructions present on said common instruction word bus and said data bus, output gating means for gating information read from said read only memories to said common data bus, said output gating means being operatively connected to said common data bus and said common instruction word bus and controlled by instructions on said common instruction bus, printer data memory for supplying printer codes for operation of said printer in one of a plurality of language formats, said printer data memory being operatively connected to said common data bus for receiving data from said gating means and said common instruction word bus, and further means within said language translation means for addressing certain read only memories for translating certain specific media codes. 2. The improvement according to claim 1 further including means within said language translator means for providing printer codes to said printer for those printer codes not provided in said printer data memory. | 0.502358 |
7,739,103 | 1 | 2 | 1. A computer-implemented method for identifying phrasal terms, the method comprising: receiving a text having a plurality of words using a processor; determining a plurality of contexts using the processor, wherein a context comprises one or more words proximate to another word in the text, the plurality of contexts including contexts with differing lengths, wherein some of the contexts have a length of a number of words and some other contexts have a different length of a different number of words; for each context, determining a first frequency using the processor based on a number of occurrences of the context within the text; assigning a first rank to at least one context using the processor based on the first frequency for the at least one context; determining multiple word-context pairs using the processor and, for each word-context pair, determining a second frequency using the processor based on a number of occurrences of the word associated with the word-context pair being used in the context; assigning a second rank to at least one word-context pair using the processor based on the second frequency for the at least one word-context pair; determining a rank ratio for each word-context pair equal to the first rank divided by the second rank using the processor; determining a mutual rank ratio using the processor based on multiple rank ratios, the multiple rank ratios including rank ratios associated with contexts of differing lengths; normalizing the mutual rank ratio to account for the contexts of differing lengths using the processor; and identifying a phrasal term using the mutual rank ratio using the processor, the phrasal term being a multiword unit of a vocabulary. | 1. A computer-implemented method for identifying phrasal terms, the method comprising: receiving a text having a plurality of words using a processor; determining a plurality of contexts using the processor, wherein a context comprises one or more words proximate to another word in the text, the plurality of contexts including contexts with differing lengths, wherein some of the contexts have a length of a number of words and some other contexts have a different length of a different number of words; for each context, determining a first frequency using the processor based on a number of occurrences of the context within the text; assigning a first rank to at least one context using the processor based on the first frequency for the at least one context; determining multiple word-context pairs using the processor and, for each word-context pair, determining a second frequency using the processor based on a number of occurrences of the word associated with the word-context pair being used in the context; assigning a second rank to at least one word-context pair using the processor based on the second frequency for the at least one word-context pair; determining a rank ratio for each word-context pair equal to the first rank divided by the second rank using the processor; determining a mutual rank ratio using the processor based on multiple rank ratios, the multiple rank ratios including rank ratios associated with contexts of differing lengths; normalizing the mutual rank ratio to account for the contexts of differing lengths using the processor; and identifying a phrasal term using the mutual rank ratio using the processor, the phrasal term being a multiword unit of a vocabulary. 2. The method of claim 1 wherein determining a mutual rank ratio comprises: selecting a first rank ratio for a first word-context pair, wherein the word in the first word-context pair comprises a first word, wherein the context in the first word-context pair comprises a second word following the word in the first word-context pair; selecting a second rank ratio for a second word-context pair, wherein the word in the second word-context pair comprises the second word, wherein the context in the second word-context pair comprises the first word preceding the word in the second word-context pair; and multiplying the first rank ratio by the second rank ratio to determine the mutual rank ratio. | 0.756455 |
10,073,883 | 6 | 7 | 6. One or more computer readable media comprising instructions that, when executed with one or more processors, cause a system to at least: receive a query of a user, the query associated with an item and comprising keywords; determine a context that indicates a specificity of the query, the context determined based at least in part on an abandonment rate associated with the keywords; identify, from a catalog, information about the item based at least in part on the query; identify additional information about at least an additional item based at least in part on a rule, the rule specifying an information type and a presentation location based at least in part on the specificity of the context, the additional information identified based at least in part on a determination that the additional information is of the information type and on an association of the additional information with the catalog; and provide a query result comprising the information for presentation in a first location of a space of a user interface and comprising the additional information for presentation in the presentation location of the space. | 6. One or more computer readable media comprising instructions that, when executed with one or more processors, cause a system to at least: receive a query of a user, the query associated with an item and comprising keywords; determine a context that indicates a specificity of the query, the context determined based at least in part on an abandonment rate associated with the keywords; identify, from a catalog, information about the item based at least in part on the query; identify additional information about at least an additional item based at least in part on a rule, the rule specifying an information type and a presentation location based at least in part on the specificity of the context, the additional information identified based at least in part on a determination that the additional information is of the information type and on an association of the additional information with the catalog; and provide a query result comprising the information for presentation in a first location of a space of a user interface and comprising the additional information for presentation in the presentation location of the space. 7. The one or more computer readable media of claim 6 , wherein the item and the additional item are offered at an electronic marketplace based at least in part on the catalog, wherein the catalog comprises a page containing the information about the item and a reference to the additional information, wherein the association of the additional information comprises the reference, and wherein the additional information is identified based at least in part on the reference. | 0.800084 |
7,752,417 | 1 | 7 | 1. A computer-implemented method, comprising, during execution of a first application: receiving, on behalf of said first application, a first memory request directed to a first virtual memory address; translating said first virtual memory address to a corresponding first physical address according to a first address translation technique; analyzing performance of said first application; dynamically selecting a second address translation technique for translating virtual memory addresses to corresponding physical memory addresses on behalf of said first application; and subsequent to said selecting a second address translation technique, receiving, on behalf of said first application, a second memory request directed to a second virtual memory address, and translating said second virtual memory address to a corresponding second physical address according to said second address translation technique; wherein said dynamically selecting a second address translation technique is dependent, at least in part, on a user policy and on results of said analyzing; and wherein said dynamically selecting and said translating according to said second address translation technique are performed transparently to said first application. | 1. A computer-implemented method, comprising, during execution of a first application: receiving, on behalf of said first application, a first memory request directed to a first virtual memory address; translating said first virtual memory address to a corresponding first physical address according to a first address translation technique; analyzing performance of said first application; dynamically selecting a second address translation technique for translating virtual memory addresses to corresponding physical memory addresses on behalf of said first application; and subsequent to said selecting a second address translation technique, receiving, on behalf of said first application, a second memory request directed to a second virtual memory address, and translating said second virtual memory address to a corresponding second physical address according to said second address translation technique; wherein said dynamically selecting a second address translation technique is dependent, at least in part, on a user policy and on results of said analyzing; and wherein said dynamically selecting and said translating according to said second address translation technique are performed transparently to said first application. 7. The method of claim 1 , further comprising, during said execution: selecting a third address translation technique for translating virtual addresses to corresponding physical addresses on behalf of a second application; subsequent to said selecting a third address translation technique, translating a third virtual memory address to a third physical memory address on behalf of said second application according to said third address translation technique; wherein said third address translation technique is different from one or more of said first address translation technique and said second address translation technique; and wherein said selecting said third address technique and said translating according to said third address translation technique are performed transparently to said first application. | 0.634736 |
7,933,871 | 1 | 5 | 1. A processor-based system to manage template updates by: receiving an update request based in part on an update time, wherein the update request includes a request for one or more links associated with one or more document libraries having one or more templates, wherein the one or more links are targeted to an associated user and point to targets that include the one or more document libraries and associated templates used in part to maintain locally stored templates for the associated user; generating markup data for the one or more templates associated with the one or more links, wherein the markup data includes template parameters, a description, and other information associated with the one or more templates of the one or more document libraries; setting a template synchronization flag to identify a document library to use as part of an update process including associating a first group of users with a first set of document libraries and a second group of users with a second set of document libraries; determining whether to replace a local template with an associated template targeted by a link including comparing a first template parameter of the local template with a second parameter of the associated template of the document library including comparing local template attribute values of the local template with attribute values of the associated template of the document library associated with the link; maintaining the locally stored templates to correspond with new and updated templates associated with the one or more document libraries including determining which parts of a locally stored template require updating based in part on updated aspects of the associated template, including automatically updating the local template based in part on the comparison of the first and second template parameters; and storing template schemas and associated metadata locally with a client as part of the updating. | 1. A processor-based system to manage template updates by: receiving an update request based in part on an update time, wherein the update request includes a request for one or more links associated with one or more document libraries having one or more templates, wherein the one or more links are targeted to an associated user and point to targets that include the one or more document libraries and associated templates used in part to maintain locally stored templates for the associated user; generating markup data for the one or more templates associated with the one or more links, wherein the markup data includes template parameters, a description, and other information associated with the one or more templates of the one or more document libraries; setting a template synchronization flag to identify a document library to use as part of an update process including associating a first group of users with a first set of document libraries and a second group of users with a second set of document libraries; determining whether to replace a local template with an associated template targeted by a link including comparing a first template parameter of the local template with a second parameter of the associated template of the document library including comparing local template attribute values of the local template with attribute values of the associated template of the document library associated with the link; maintaining the locally stored templates to correspond with new and updated templates associated with the one or more document libraries including determining which parts of a locally stored template require updating based in part on updated aspects of the associated template, including automatically updating the local template based in part on the comparison of the first and second template parameters; and storing template schemas and associated metadata locally with a client as part of the updating. 5. The system of claim 1 , further configured to manage template updates by receiving a client-initiated web service call that includes a request for one or more uniform resource locators (URLs) associated with the one or more document libraries having the one or more templates. | 0.561321 |
9,110,971 | 32 | 33 | 32. The computer-based system of claim 25 , wherein the re-ranking module configured based on a previously executed learning process involves automatically generated training data processed to establish a relevance weighting to be assigned to respective ones of the set of patent features. | 32. The computer-based system of claim 25 , wherein the re-ranking module configured based on a previously executed learning process involves automatically generated training data processed to establish a relevance weighting to be assigned to respective ones of the set of patent features. 33. The computer-based system of claim 32 , wherein the learning module collects training data and assigning a relevance weighting to the set of patent features based at least in part on the collected training data. | 0.969083 |
8,335,694 | 10 | 11 | 10. The method of claim 9 , further comprising: preparing and storing a report in a database of said computer system, and electronically forwarding said report to predetermined users, using said computer system. | 10. The method of claim 9 , further comprising: preparing and storing a report in a database of said computer system, and electronically forwarding said report to predetermined users, using said computer system. 11. The method of claim 10 , further comprising: performing an automated comparison of findings in said report with findings in said database, using said computer system. | 0.950924 |
6,155,485 | 16 | 18 | 16. A medicament-dispensing apparatus for filling a prescription for a medicament including a designated amount of the medicament, said apparatus comprising: a prescription database including prescription data corresponding to a prescription to be filled including the medicament thereof; a computer including means for accessing said prescription database for retrieving prescription data therefrom corresponding to the prescription to be filled; a printer coupled with said computer and operable to print a prescription label representative of the prescription; an indicia-reading device coupled with said computer and operable to read container indicia on a supply container of a medicament, said container data being representative of the medicament contained in the container, said device being operable to provide said container data to said computer, said computer including means for comparing said container data and said prescription data to determine a match therebetween and in response, prompting said printer to print the prescription label; and an attribute database including attribute data representative of at least one physical attribute of the medicament, said computer including means for accessing said attribute database and for retrieving attribute data therefrom corresponding to the prescription medicament and for activating said printer to print the prescription label with medicament indicia thereon representative of at least one physical attribute of the prescription medicament. | 16. A medicament-dispensing apparatus for filling a prescription for a medicament including a designated amount of the medicament, said apparatus comprising: a prescription database including prescription data corresponding to a prescription to be filled including the medicament thereof; a computer including means for accessing said prescription database for retrieving prescription data therefrom corresponding to the prescription to be filled; a printer coupled with said computer and operable to print a prescription label representative of the prescription; an indicia-reading device coupled with said computer and operable to read container indicia on a supply container of a medicament, said container data being representative of the medicament contained in the container, said device being operable to provide said container data to said computer, said computer including means for comparing said container data and said prescription data to determine a match therebetween and in response, prompting said printer to print the prescription label; and an attribute database including attribute data representative of at least one physical attribute of the medicament, said computer including means for accessing said attribute database and for retrieving attribute data therefrom corresponding to the prescription medicament and for activating said printer to print the prescription label with medicament indicia thereon representative of at least one physical attribute of the prescription medicament. 18. The apparatus of claim 16, said medicament indicia including at least one of the shape, color pattern, color, scoring and form of the medicament. | 0.838395 |
9,460,198 | 9 | 16 | 9. A non-transitory computer-readable medium having stored therein computer executable code that causes one or more processors to execute the steps of: receiving schema data, which describes the format and properties of an instance object to be transmitted or received; converting, using a class library, raw schema data into an intermediate hierarchical data structure, an upper level of the hierarchical data structure including the properties of the instance object, and each property including data representing attributes of that property; dynamically at runtime generating parser classes for deserialization and methods from the properties and attributes described in the intermediate hierarchical data structure based on the schema, wherein generating the parser classes comprises: iterating over each property defined in the schema and in any other schema referenced in the schema, and defining a new class for each non-scalar, non-array property defined by the schema; and storing the generated parser classes and methods in memory in order for a host programming language to transmit or receive instance data to or from an application programming interface. | 9. A non-transitory computer-readable medium having stored therein computer executable code that causes one or more processors to execute the steps of: receiving schema data, which describes the format and properties of an instance object to be transmitted or received; converting, using a class library, raw schema data into an intermediate hierarchical data structure, an upper level of the hierarchical data structure including the properties of the instance object, and each property including data representing attributes of that property; dynamically at runtime generating parser classes for deserialization and methods from the properties and attributes described in the intermediate hierarchical data structure based on the schema, wherein generating the parser classes comprises: iterating over each property defined in the schema and in any other schema referenced in the schema, and defining a new class for each non-scalar, non-array property defined by the schema; and storing the generated parser classes and methods in memory in order for a host programming language to transmit or receive instance data to or from an application programming interface. 16. The non-transitory computer-readable medium of claim 9 , further comprising: a property with a type attribute of union, which defines more than one type; matching the property to defined types in an order that the defined types are listed in the schema; and responsive to a match, using a matching defined type to create a class property. | 0.70364 |
9,053,500 | 18 | 19 | 18. The system of claim 16 , wherein the plurality of objects are related to a course. | 18. The system of claim 16 , wherein the plurality of objects are related to a course. 19. The system of claim 18 , wherein the pre-specified locale is set by an instructor or administrator of the course and is associated with the course. | 0.911385 |
8,504,507 | 1 | 6 | 1. A computer-implemented method for providing content based on an estimated actual age, the method comprising: identifying, by a computer, a set of related members for a first member, wherein the first member and each member in the set of related members are members of a social networking website, and wherein each member in the set of related members is connected to the first member in the social network website; examining, by the computer, age information associated with one or more members in the set of related members; when a threshold number of members in the set of related members have an estimated actual age within a certain age range, estimating, by the computer, an actual age of the first member based on the estimated actual age of the members in the set of related members; and providing, by the computer, content to the first member based on the first member's estimated actual age. | 1. A computer-implemented method for providing content based on an estimated actual age, the method comprising: identifying, by a computer, a set of related members for a first member, wherein the first member and each member in the set of related members are members of a social networking website, and wherein each member in the set of related members is connected to the first member in the social network website; examining, by the computer, age information associated with one or more members in the set of related members; when a threshold number of members in the set of related members have an estimated actual age within a certain age range, estimating, by the computer, an actual age of the first member based on the estimated actual age of the members in the set of related members; and providing, by the computer, content to the first member based on the first member's estimated actual age. 6. The method of claim 1 , wherein the threshold number includes one or more of: a minimum number of related members in the set of related members, and a minimum fraction of the related members in the set of related members. | 0.813644 |
8,489,523 | 3 | 4 | 3. The method of claim 1 , wherein generating the plurality of feature vectors comprises: selecting a first vocabulary term and a second vocabulary term of the plurality of vocabulary terms; identifying a term frequency of the first vocabulary term within a web page of the plurality of web pages; identifying a term frequency of the second vocabulary term within the web page of the plurality of web pages; identifying an inverse document frequency (IDF) of the first vocabulary term and an IDF of the second vocabulary term from the N-gram file; calculating a weight for the first vocabulary term based on the IDF of the first and second vocabulary term and the term frequency of the first and second vocabulary term; and calculating a weight for the second vocabulary term based on the IDF of the first and second vocabulary term and the term frequency of the first and second vocabulary term. | 3. The method of claim 1 , wherein generating the plurality of feature vectors comprises: selecting a first vocabulary term and a second vocabulary term of the plurality of vocabulary terms; identifying a term frequency of the first vocabulary term within a web page of the plurality of web pages; identifying a term frequency of the second vocabulary term within the web page of the plurality of web pages; identifying an inverse document frequency (IDF) of the first vocabulary term and an IDF of the second vocabulary term from the N-gram file; calculating a weight for the first vocabulary term based on the IDF of the first and second vocabulary term and the term frequency of the first and second vocabulary term; and calculating a weight for the second vocabulary term based on the IDF of the first and second vocabulary term and the term frequency of the first and second vocabulary term. 4. The method of claim 3 , wherein calculating the weight for the first vocabulary term comprises: calculating a product of the term frequency of the first vocabulary term by the IDF of the first vocabulary term; calculating a distance of the plurality of vocabulary terms; and dividing the product by the distance. | 0.897126 |
9,286,411 | 1 | 3 | 1. A method for retrieval of one or more relevant multi-attribute structured objects with respect to a query, wherein the method comprises: receiving a user query for retrieval of one or more multi-attribute structured objects from a database that includes multiple objects with interdependent and independent attributes; receiving user instructions specifying how the interdependent and independent attributes are to be grouped in carrying out the query; grouping the attributes of the objects in the database into one or more groups according to the user instructions by: associating each of the attributes with a list of one or more database objects that are ordered in an increasing value of dissimilarity from a query value for the respective attribute; combining multiple aggregation operators in accordance with user-provided specifications, wherein the multiple aggregation operators comprise: (i) an intersection aggregation operator, wherein the intersection aggregation operator deems a first object as having a lower value of dissimilarity than a second object if the most dissimilar attribute of the first object has a higher absolute value than the most dissimilar attribute of the second object, (ii) a union aggregation operator, wherein the union aggregation operator deems a first object as having a lower value of dissimilarity than a second object if the least dissimilar attribute of the first object has a higher absolute value than the least dissimilar attribute of the second object, (iii) a generalized mean aggregation operator, and (iv) a Euclidean distance aggregation operator, to compose the interdependent attributes into multiple interdependent attribute compositions; and using a skyline operator to combine the multiple interdependent attribute compositions and the independent attributes into the one or more groups according to the user instructions; and using the one or more attribute groups to produce an output of a sorted list of one or more relevant multi-attribute structured objects from the database in response to the query that express preference specification of the one or more attributes. | 1. A method for retrieval of one or more relevant multi-attribute structured objects with respect to a query, wherein the method comprises: receiving a user query for retrieval of one or more multi-attribute structured objects from a database that includes multiple objects with interdependent and independent attributes; receiving user instructions specifying how the interdependent and independent attributes are to be grouped in carrying out the query; grouping the attributes of the objects in the database into one or more groups according to the user instructions by: associating each of the attributes with a list of one or more database objects that are ordered in an increasing value of dissimilarity from a query value for the respective attribute; combining multiple aggregation operators in accordance with user-provided specifications, wherein the multiple aggregation operators comprise: (i) an intersection aggregation operator, wherein the intersection aggregation operator deems a first object as having a lower value of dissimilarity than a second object if the most dissimilar attribute of the first object has a higher absolute value than the most dissimilar attribute of the second object, (ii) a union aggregation operator, wherein the union aggregation operator deems a first object as having a lower value of dissimilarity than a second object if the least dissimilar attribute of the first object has a higher absolute value than the least dissimilar attribute of the second object, (iii) a generalized mean aggregation operator, and (iv) a Euclidean distance aggregation operator, to compose the interdependent attributes into multiple interdependent attribute compositions; and using a skyline operator to combine the multiple interdependent attribute compositions and the independent attributes into the one or more groups according to the user instructions; and using the one or more attribute groups to produce an output of a sorted list of one or more relevant multi-attribute structured objects from the database in response to the query that express preference specification of the one or more attributes. 3. The method of claim 1 , further comprising specifying how each of the one or more groups would be combined while evaluating similarity. | 0.890302 |
8,001,469 | 1 | 10 | 1. A method comprising: receiving a task flow that describes operations of a dialog system that provides synthesized speech responses to spoken user input by a caller; generating a script that is a formal description of the task flow; automatically generating a graphical user interface (GUI) from the script, the GUI consisting of templates for control of the dialog system, generation of context-dependent synthesized speech prompts, and real-time collection and annotating of dialog data during a live dialog between only the dialog system and the caller to the dialog system, the GUI comprising a first portion for input of caller provided information, a second portion comprising an output control panel for control of the synthesized speech prompts by a human operator, a third portion providing status of a current task within the task flow, and a fourth portion providing an graphical representation of the task flow; and detecting the presence of an abnormality in speech processing during the task flow and automatically switching control to the human operator to allow direct interaction with the caller to correct the abnormality. | 1. A method comprising: receiving a task flow that describes operations of a dialog system that provides synthesized speech responses to spoken user input by a caller; generating a script that is a formal description of the task flow; automatically generating a graphical user interface (GUI) from the script, the GUI consisting of templates for control of the dialog system, generation of context-dependent synthesized speech prompts, and real-time collection and annotating of dialog data during a live dialog between only the dialog system and the caller to the dialog system, the GUI comprising a first portion for input of caller provided information, a second portion comprising an output control panel for control of the synthesized speech prompts by a human operator, a third portion providing status of a current task within the task flow, and a fourth portion providing an graphical representation of the task flow; and detecting the presence of an abnormality in speech processing during the task flow and automatically switching control to the human operator to allow direct interaction with the caller to correct the abnormality. 10. The method of claim 1 , wherein the formal description includes memory allocations for maintaining state of the interactive system. | 0.911995 |
9,854,324 | 11 | 20 | 11. A system for automatically enabling subtitles based on a user profile when a language is spoken with an accent, the system comprising: control circuitry configured to: store, in a user profile associated with a user, a first data structure indicating a list of one or more languages that the user understands; determine, at a first point in time, that a language of the one or more languages in the list is being spoken with an accent by retrieving the first data structure, extracting the list, and comparing the language to the one or more languages; detect a first plurality of user interactions of the user while the given language is being spoken with the accent; store, in the user profile, a data log indicating the first point in time and the first plurality of user interactions; retrieve, from a remote source, an information table associating user interactions with values, wherein the values represent a general level of difficulty, the general level of difficulty being indicative of a measure of difficulty a plurality of users have in understanding accents in audio content; compare the first plurality of user interactions with the information table to determine a first plurality of values, wherein each value of the first plurality of values is associated with a respective one of the first plurality of user interactions; calculate a first value based on the first plurality of values; create a second data structure, wherein the second data structure associates the first value with a user specific level of difficulty, the user specific level of difficulty being indicative of a measure of difficulty the user encounters in understanding the given language when spoken with the accent; store the second data structure in the user profile; detect that the given language is being spoken with the accent at a second point in time later than the first point in time; retrieve, based on detecting that the given language is being spoken with the accent at the second point in time, from the user profile, the data log; monitor user interactions of the user while the given language is being spoken with the accent at the second point in time to determine whether the first plurality of user interactions are being performed again while the given language is being spoken with the accent; update, based on determining that the first plurality of user interactions are not being performed again, the second data structure, the second data structure associating a second value that is lower than the first value with the user specific level of difficulty; detect that a media asset includes the given language spoken with the accent; retrieve, from the user profile, the second data structure; extract, from the second data structure, the user specific level of difficulty; and automatically generate for display subtitles for the media asset based on the extracted user specific level of difficulty. | 11. A system for automatically enabling subtitles based on a user profile when a language is spoken with an accent, the system comprising: control circuitry configured to: store, in a user profile associated with a user, a first data structure indicating a list of one or more languages that the user understands; determine, at a first point in time, that a language of the one or more languages in the list is being spoken with an accent by retrieving the first data structure, extracting the list, and comparing the language to the one or more languages; detect a first plurality of user interactions of the user while the given language is being spoken with the accent; store, in the user profile, a data log indicating the first point in time and the first plurality of user interactions; retrieve, from a remote source, an information table associating user interactions with values, wherein the values represent a general level of difficulty, the general level of difficulty being indicative of a measure of difficulty a plurality of users have in understanding accents in audio content; compare the first plurality of user interactions with the information table to determine a first plurality of values, wherein each value of the first plurality of values is associated with a respective one of the first plurality of user interactions; calculate a first value based on the first plurality of values; create a second data structure, wherein the second data structure associates the first value with a user specific level of difficulty, the user specific level of difficulty being indicative of a measure of difficulty the user encounters in understanding the given language when spoken with the accent; store the second data structure in the user profile; detect that the given language is being spoken with the accent at a second point in time later than the first point in time; retrieve, based on detecting that the given language is being spoken with the accent at the second point in time, from the user profile, the data log; monitor user interactions of the user while the given language is being spoken with the accent at the second point in time to determine whether the first plurality of user interactions are being performed again while the given language is being spoken with the accent; update, based on determining that the first plurality of user interactions are not being performed again, the second data structure, the second data structure associating a second value that is lower than the first value with the user specific level of difficulty; detect that a media asset includes the given language spoken with the accent; retrieve, from the user profile, the second data structure; extract, from the second data structure, the user specific level of difficulty; and automatically generate for display subtitles for the media asset based on the extracted user specific level of difficulty. 20. The system of claim 11 , wherein the user is a first user, wherein the user specific level of difficulty is a first user specific level of difficulty, and wherein the control circuitry is further configured to: detect that the first user is watching the media asset; detect that a second user is watching the media asset; retrieve a third data structure from a user profile of the second user based on detecting that the second user is watching the media asset; and extract, from the third data structure, a second user specific level of difficulty for the second user; wherein the control circuitry is configured to retrieve the second data structure based on detecting that the first user is watching the media asset, and wherein the control circuitry is configured to automatically generate for display the subtitles for the media asset by: determining a threshold level of difficulty for generating for display the subtitles; determining that at least one of the first user specific level of difficulty and the second user specific level of difficulty exceeds the threshold level of difficulty; and automatically generating for display subtitles for the media asset based on determining that at least one of the first user specific level of difficulty and the second user specific level of difficulty exceeds the threshold level of difficulty. | 0.50037 |
9,292,798 | 8 | 12 | 8. The method of claim 7 , wherein the statistical model is obtained from a statistician. | 8. The method of claim 7 , wherein the statistical model is obtained from a statistician. 12. The method of claim 8 , further comprising the step of: providing the textual annotations to the statistician for use in retraining the statistical model. | 0.917879 |
9,880,570 | 8 | 10 | 8. A device for generating a vibration based on an adjective word, the device comprising: at least one processor configured to set for each of a plurality of adjective words, at least one fundamental frequency and a degree value of senses corresponding to an adjective word, the adjective words indicating senses provided to a user through the vibration of the device, and the degree value of senses indicating a degree of the senses provided to the user through the vibration of the device; control to display at least one adjective words and the degree value of senses corresponding to the adjective words; a user input unit configured to receive at least one user input for selecting an adjective word among the displayed adjective words; and a vibration generator configured to generate at least one vibration having the at least one fundamental frequency, the at least one fundamental frequency being based on the selected adjective word and the degree value of senses corresponding to the selected adjective word, according to the setting, wherein a certain adjective word comprises a first adjective word and a second adjective word, and wherein the at least one processor is further configured to: set at least one overlap ratio, acquire relationship information between a degree value of the first adjective word, a degree value of the second adjective word, and the fundamental frequency, and acquire relationship information between the degree value of the first adjective word, the degree value of the second adjective word, and the overlap ratio. | 8. A device for generating a vibration based on an adjective word, the device comprising: at least one processor configured to set for each of a plurality of adjective words, at least one fundamental frequency and a degree value of senses corresponding to an adjective word, the adjective words indicating senses provided to a user through the vibration of the device, and the degree value of senses indicating a degree of the senses provided to the user through the vibration of the device; control to display at least one adjective words and the degree value of senses corresponding to the adjective words; a user input unit configured to receive at least one user input for selecting an adjective word among the displayed adjective words; and a vibration generator configured to generate at least one vibration having the at least one fundamental frequency, the at least one fundamental frequency being based on the selected adjective word and the degree value of senses corresponding to the selected adjective word, according to the setting, wherein a certain adjective word comprises a first adjective word and a second adjective word, and wherein the at least one processor is further configured to: set at least one overlap ratio, acquire relationship information between a degree value of the first adjective word, a degree value of the second adjective word, and the fundamental frequency, and acquire relationship information between the degree value of the first adjective word, the degree value of the second adjective word, and the overlap ratio. 10. The device of claim 8 , wherein the user input unit is further configured to receive a first degree value of the first adjective word and a second degree value of the second adjective word, the first and second adjective words being input by the at least one user input, wherein the at least one processor is further configured to determine a fundamental frequency and an overlap ratio corresponding to the first degree value and the second degree value based on the acquired relationship information, and wherein the vibration generator is further configured to generate the at least one vibration based on the determined fundamental frequency and the determined overlap ratio. | 0.500732 |
8,914,276 | 1 | 12 | 1. A computer-implemented method to provide automated translation of video captions and playback to one or more clients, the method comprising: receiving an indication of a video that includes associated caption text; identifying a source language associated with the caption text without playing the video; selecting a target language to which to translate the associated caption text from the identified source language; automatically translating the caption text from the identified source language to the selected target language without playing the video; storing the translated captions in a caption file after automatically translating the caption text; repackaging the received video and translated captions so that the video can be played with the new captions; and playing the received video and displaying each translated caption at appropriate points during the video, wherein the preceding steps are performed by at least one processor. | 1. A computer-implemented method to provide automated translation of video captions and playback to one or more clients, the method comprising: receiving an indication of a video that includes associated caption text; identifying a source language associated with the caption text without playing the video; selecting a target language to which to translate the associated caption text from the identified source language; automatically translating the caption text from the identified source language to the selected target language without playing the video; storing the translated captions in a caption file after automatically translating the caption text; repackaging the received video and translated captions so that the video can be played with the new captions; and playing the received video and displaying each translated caption at appropriate points during the video, wherein the preceding steps are performed by at least one processor. 12. The method of claim 1 wherein repacking comprises forming a link with a specification of a path to the translated captions. | 0.892736 |
9,911,416 | 16 | 18 | 16. The electronic device of claim 9 , further comprising: an antenna; and a receiver coupled to the antenna and configured to receive a signal corresponding to a particular input sound. | 16. The electronic device of claim 9 , further comprising: an antenna; and a receiver coupled to the antenna and configured to receive a signal corresponding to a particular input sound. 18. The electronic device of claim 16 , wherein the speech detector, the frequency analyzer, the speech direction determiner, the circuitry, the receiver, and the antenna are integrated into a fixed location communication device. | 0.92665 |
8,380,726 | 1 | 6 | 1. A method of selecting and presenting a subset of content items to a user based on content item selections by other users having similar preferences as determined at least in part based on analyzing the weights of relative preferences and based on analyzing intervals of time occurring between user selection of similar content items, the method comprising: providing access to a set of content items, each content item having at least one associated descriptive term to describe the content item; receiving a plurality of incremental inputs, each incremental input being entered by a corresponding one of a plurality of users of an input device, wherein the incremental input includes at least one character in a series of characters; in response to each character of the incremental input, presenting a corresponding subset of content items; receiving selection actions of content items from the user who entered the incremental input for which the subset of content items was presented; determining a geographic location of the user at the time of at least one of the selection actions; analyzing the descriptive terms associated with the selected content items to identify sets of actions resulting in the selection of similar content items, wherein similarity is determined by comparing the descriptive terms associated with any one of the selected content items with any of the previously selected content items; analyzing the date, day, and time of at least three of the individual selection actions of the sets of actions to learn arbitrary periodicities corresponding to a particular set of actions for selecting similar content items, wherein the arbitrary periodicities each comprise repeated similar intervals of time between user actions resulting in the selections of similar content items; for each user of the plurality of users, learning the preferences of each user by associating a weight and arbitrary periodicity with each descriptive term associated with the selection actions of the user, said weight being indicative of the amount of use by the user of the selected content items associated with each of the descriptive terms and said arbitrary periodicity being the learned arbitrary periodicity of the descriptive terms associated with the set of similar content items, so that the user preferences are specified as a set of descriptive terms, each with associated weights and arbitrary periodicities, the learning the preferences of each user further including associating the geographic location with each descriptive term associated with the corresponding selection actions of the user; identifying users with similar preferences by comparing sets of learned user preferences to determine if the sets of preferences of the users match within a specified threshold; and presenting content items to at least one user of the plurality of users by identifying for presentation content items selected by users identified as having learned user preferences that are similar to the learned user preferences of said at least one user; wherein at least one of receiving a plurality of incremental inputs, presenting the corresponding subset of content items, receiving selection actions, learning the preferences of each user, identifying users with similar preferences, and presenting content items is performed on a server system remote from the user. | 1. A method of selecting and presenting a subset of content items to a user based on content item selections by other users having similar preferences as determined at least in part based on analyzing the weights of relative preferences and based on analyzing intervals of time occurring between user selection of similar content items, the method comprising: providing access to a set of content items, each content item having at least one associated descriptive term to describe the content item; receiving a plurality of incremental inputs, each incremental input being entered by a corresponding one of a plurality of users of an input device, wherein the incremental input includes at least one character in a series of characters; in response to each character of the incremental input, presenting a corresponding subset of content items; receiving selection actions of content items from the user who entered the incremental input for which the subset of content items was presented; determining a geographic location of the user at the time of at least one of the selection actions; analyzing the descriptive terms associated with the selected content items to identify sets of actions resulting in the selection of similar content items, wherein similarity is determined by comparing the descriptive terms associated with any one of the selected content items with any of the previously selected content items; analyzing the date, day, and time of at least three of the individual selection actions of the sets of actions to learn arbitrary periodicities corresponding to a particular set of actions for selecting similar content items, wherein the arbitrary periodicities each comprise repeated similar intervals of time between user actions resulting in the selections of similar content items; for each user of the plurality of users, learning the preferences of each user by associating a weight and arbitrary periodicity with each descriptive term associated with the selection actions of the user, said weight being indicative of the amount of use by the user of the selected content items associated with each of the descriptive terms and said arbitrary periodicity being the learned arbitrary periodicity of the descriptive terms associated with the set of similar content items, so that the user preferences are specified as a set of descriptive terms, each with associated weights and arbitrary periodicities, the learning the preferences of each user further including associating the geographic location with each descriptive term associated with the corresponding selection actions of the user; identifying users with similar preferences by comparing sets of learned user preferences to determine if the sets of preferences of the users match within a specified threshold; and presenting content items to at least one user of the plurality of users by identifying for presentation content items selected by users identified as having learned user preferences that are similar to the learned user preferences of said at least one user; wherein at least one of receiving a plurality of incremental inputs, presenting the corresponding subset of content items, receiving selection actions, learning the preferences of each user, identifying users with similar preferences, and presenting content items is performed on a server system remote from the user. 6. The method of claim 1 , wherein the incremental input is entered by the user on an input constrained device. | 0.831818 |
9,721,068 | 1 | 7 | 1. A method, comprising: conducting, by a device, a conversation with a patient; capturing, by the device, therapy interaction data during the conversation, the therapy interaction data including speech uttered by the patient; parsing, by the device, the captured therapy interaction data to identify one or more word occurrences; determining, by the device, one or more associations among the one or more word occurrences using a fuzzy association analysis and deep belief networks; determining, by the device and using fuzzy association propensity survival scoring, a propensity of the one or more associations based on a probability analysis that is based on patient data relating to a plurality of other patients, the patient data including control data that includes: data relating to one or more healthy patients, and data relating to one or more patients that have one or more diseases or health conditions; and determining, by the device and based on the propensity of the one or more associations, whether the patient has the one or more diseases or health conditions. | 1. A method, comprising: conducting, by a device, a conversation with a patient; capturing, by the device, therapy interaction data during the conversation, the therapy interaction data including speech uttered by the patient; parsing, by the device, the captured therapy interaction data to identify one or more word occurrences; determining, by the device, one or more associations among the one or more word occurrences using a fuzzy association analysis and deep belief networks; determining, by the device and using fuzzy association propensity survival scoring, a propensity of the one or more associations based on a probability analysis that is based on patient data relating to a plurality of other patients, the patient data including control data that includes: data relating to one or more healthy patients, and data relating to one or more patients that have one or more diseases or health conditions; and determining, by the device and based on the propensity of the one or more associations, whether the patient has the one or more diseases or health conditions. 7. The method of claim 1 , further comprising: changing a model for determining the one or more associations, determining the propensity of the one or more associations, or a combination thereof over time. | 0.865132 |
7,779,003 | 10 | 13 | 10. A system according to claim 1 , further comprising: at least one repository of term substitution information comprising mapping information associating a term with a corresponding term; and said search processor parses a search term in the one or more search terms and substitutes an associated corresponding term for said search term by applying said mapping information. | 10. A system according to claim 1 , further comprising: at least one repository of term substitution information comprising mapping information associating a term with a corresponding term; and said search processor parses a search term in the one or more search terms and substitutes an associated corresponding term for said search term by applying said mapping information. 13. A system according to claim 10 , wherein said search processor excludes short terms that potentially map to multiple irrelevant terms. | 0.976807 |
9,336,553 | 1 | 4 | 1. A method comprising: receiving a request from a viewing user of a social networking system for a newsfeed; determining a plurality of candidate stories for the viewing user, the plurality of candidate stories associated with a plurality of other users of the social networking system with which the viewing user has established a connection; extracting a plurality of attributes from each of the plurality of candidate stories, the extracted attributes comprising information about at least one selected from the group consisting of story content, story type, interaction type associated with the story, and user associated with the story; ranking the plurality of candidate stories to produce an initial ranking; selecting a candidate story and an additional candidate story from the plurality of candidate stories, the candidate story having a first position in the initial ranking and the additional candidate story having a second position in the initial ranking; comparing the extracted plurality of attributes of the candidate story and the extracted plurality of attributes of the additional candidate story to determine a level of similarity between the candidate story and the additional candidate story based on the extracted attribute comparison; responsive to the determined level of similarity meeting a threshold level of similarity, modifying the initial ranking to produce a modified ranking, the modifying comprising lowering the second position of the additional candidate story from the initial ranking to a lower position in the modified ranking relative to the candidate story; generating a newsfeed comprising a plurality of the candidate stories, the generated newsfeed based at least in part on the modified ranking; and sending the generated newsfeed for display to the viewing user. | 1. A method comprising: receiving a request from a viewing user of a social networking system for a newsfeed; determining a plurality of candidate stories for the viewing user, the plurality of candidate stories associated with a plurality of other users of the social networking system with which the viewing user has established a connection; extracting a plurality of attributes from each of the plurality of candidate stories, the extracted attributes comprising information about at least one selected from the group consisting of story content, story type, interaction type associated with the story, and user associated with the story; ranking the plurality of candidate stories to produce an initial ranking; selecting a candidate story and an additional candidate story from the plurality of candidate stories, the candidate story having a first position in the initial ranking and the additional candidate story having a second position in the initial ranking; comparing the extracted plurality of attributes of the candidate story and the extracted plurality of attributes of the additional candidate story to determine a level of similarity between the candidate story and the additional candidate story based on the extracted attribute comparison; responsive to the determined level of similarity meeting a threshold level of similarity, modifying the initial ranking to produce a modified ranking, the modifying comprising lowering the second position of the additional candidate story from the initial ranking to a lower position in the modified ranking relative to the candidate story; generating a newsfeed comprising a plurality of the candidate stories, the generated newsfeed based at least in part on the modified ranking; and sending the generated newsfeed for display to the viewing user. 4. The method of claim 1 , wherein an attribute of a candidate story comprises a story type. | 0.884712 |
8,635,340 | 3 | 4 | 3. The method of claim 1 , further comprising selecting a keyword registration provider from a plurality of keyword providers to process the keyword registration request. | 3. The method of claim 1 , further comprising selecting a keyword registration provider from a plurality of keyword providers to process the keyword registration request. 4. The method of claim 3 , wherein the keyword registration provider comprises at least one of a keyword registrar, keyword reseller, keyword advertiser, or keyword affiliate. | 0.940918 |
8,315,849 | 2 | 3 | 2. The system of claim 1 wherein the processor is configured to identify the set of candidate textual representations at least in part by performing a greedy match against a list of entries included in the taxonomy. | 2. The system of claim 1 wherein the processor is configured to identify the set of candidate textual representations at least in part by performing a greedy match against a list of entries included in the taxonomy. 3. The system of claim 2 wherein performing a greedy match includes detecting a preposition. | 0.964006 |
9,710,447 | 11 | 20 | 11. A system comprising: at least one computing device comprising one or more processors to execute and memory to store instructions to: train a machine-modeled kernel jointly modeling content, semantic information and social network information, the kernel for use with a digital content annotation and recommendation system, the training comprising building the kernel using a content kernel trained using a training set comprising content feature information, a semantic kernel trained using semantic feature information of the training data set and a social network kernel trained using social network feature information of the training data set, an implicit social network determined from a plurality of content items is used in determining the social network feature information used in training the kernel; identify one or more annotations for test content item other than the plurality of content items used to train the kernel, the identifying using the trained kernel and the test content item's content feature information to identify the one or more annotations; and serve, to a user computing device via an electronic communications network and to a client computing device of a user, the test content item based on the one or more identified annotations and an interest of the user, the serving of the test content item to the user computing device resulting in the test content item being output by the user computing device. | 11. A system comprising: at least one computing device comprising one or more processors to execute and memory to store instructions to: train a machine-modeled kernel jointly modeling content, semantic information and social network information, the kernel for use with a digital content annotation and recommendation system, the training comprising building the kernel using a content kernel trained using a training set comprising content feature information, a semantic kernel trained using semantic feature information of the training data set and a social network kernel trained using social network feature information of the training data set, an implicit social network determined from a plurality of content items is used in determining the social network feature information used in training the kernel; identify one or more annotations for test content item other than the plurality of content items used to train the kernel, the identifying using the trained kernel and the test content item's content feature information to identify the one or more annotations; and serve, to a user computing device via an electronic communications network and to a client computing device of a user, the test content item based on the one or more identified annotations and an interest of the user, the serving of the test content item to the user computing device resulting in the test content item being output by the user computing device. 20. The system of claim 11 , the instructions further comprising instructions to: identify at least one relationship between at least two individuals using the kernel jointly modeling content, semantic and social network information. | 0.824284 |
8,489,572 | 2 | 6 | 2. The method of claim 1 , further comprising: storing a plurality of contractual documents in a database; receive the predefined query from the integration component of the client access device at the server; executing the predefined query against the database to retrieve one or more contractual provisions from contractual documents; and returning the contractual provisions to the integration component of the client access device for presentation in the result folder. | 2. The method of claim 1 , further comprising: storing a plurality of contractual documents in a database; receive the predefined query from the integration component of the client access device at the server; executing the predefined query against the database to retrieve one or more contractual provisions from contractual documents; and returning the contractual provisions to the integration component of the client access device for presentation in the result folder. 6. The method of claim 2 , further comprising storing a predefined filter for contractual documents in association with an identifier that corresponds to the user. | 0.935111 |
7,945,469 | 9 | 11 | 9. The method of claim 1 wherein the providing of information about the at least some available tasks includes repeatedly providing information to one of the multiple human task performers about available tasks matching specified criteria. | 9. The method of claim 1 wherein the providing of information about the at least some available tasks includes repeatedly providing information to one of the multiple human task performers about available tasks matching specified criteria. 11. The method of claim 9 wherein the available tasks for which information is provided to the one human task performer are each part of a group of related tasks, and wherein the specified criteria includes a task being in that group of related tasks. | 0.956754 |
8,804,574 | 1 | 8 | 1. A method for transmitting a positioning-related message in a wireless network, said method comprising: obtaining, by a node in the wireless network, information associated with a language capability of at least one of a plurality of destinations; generating, by said node and based on said obtained language capability, positioning information for said positioning-related message, and transmitting, by said node, said positioning-related message including said positioning information toward said at least one of a plurality of destinations associated with said wireless network, the method further comprising: receiving, by said node, a request for location information of a target device, from a client; collecting, by said node, said positioning information associated with a geographical location of said target device; translating, by said node, said positioning information into a language according to said language capability; and generating, by said node, a reply to said request for location information as the positioning-related message including the translated positioning information wherein said step of generating said positioning information includes an information element in said positioning-related message which specifies a language associated with said positioning information contained in said positioning-related message. | 1. A method for transmitting a positioning-related message in a wireless network, said method comprising: obtaining, by a node in the wireless network, information associated with a language capability of at least one of a plurality of destinations; generating, by said node and based on said obtained language capability, positioning information for said positioning-related message, and transmitting, by said node, said positioning-related message including said positioning information toward said at least one of a plurality of destinations associated with said wireless network, the method further comprising: receiving, by said node, a request for location information of a target device, from a client; collecting, by said node, said positioning information associated with a geographical location of said target device; translating, by said node, said positioning information into a language according to said language capability; and generating, by said node, a reply to said request for location information as the positioning-related message including the translated positioning information wherein said step of generating said positioning information includes an information element in said positioning-related message which specifies a language associated with said positioning information contained in said positioning-related message. 8. The method of claim 1 , wherein said positioning information is translated to a language specified by a Public Safety Answer Point (PSAP). | 0.830935 |
8,381,299 | 74 | 76 | 74. A system for outputting a dataset based upon anomaly detection, the system comprising: a digital processing, device that: receives a first training dataset having a plurality of n-grams that includes a first plurality of distinct training n-grams, wherein each of the first plurality of distinct training n-grams is a first size; receives a second training dataset having a plurality of n-grams that includes a second plurality of distinct training n-grams, wherein each of the second plurality of distinct training n-grams is the first size; computes a first plurality of appearance frequencies, wherein each of the first plurality of appearance frequencies corresponds to one of the first plurality of distinct training n-grams; computes a first plurality of uniformities of distribution, wherein each of the first plurality of uniformities of distribution corresponds to one of the first plurality of distinct training n-grams; computes a second plurality of uniformities of distribution, wherein each of the second plurality of uniformities of distribution corresponds to one of the second plurality of distinct training n-grams; determines a first plurality of most-heavily weighted n-grams from the first plurality of distinct training n-grams using at least one of: the first-plurality of appearance frequencies; the first plurality of uniformities of distribution; and the second plurality of uniformities of distribution; selects a subset of the first plurality of most-heavily weighted n-grams, wherein the subset includes in n-grams and at least one of the n-grams in the subset is outside of the top m of the first plurality of most-heavily weighted n-grams; receives an input dataset including first input n-grams, wherein each of the plurality of first input n-grams is the first size; obtains a subset of a second plurality of most-heavily weighted n-grams from the first input n-grams that correspond to the subset of the first plurality of distinct training n-grams; classifies the input dataset as containing an anomaly using the subset of the first plurality of most-heavily weighted n-grams and the subset of the second plurality of most-heavily weighted n-grams; and outputs a dataset based upon the classifying of the input dataset. | 74. A system for outputting a dataset based upon anomaly detection, the system comprising: a digital processing, device that: receives a first training dataset having a plurality of n-grams that includes a first plurality of distinct training n-grams, wherein each of the first plurality of distinct training n-grams is a first size; receives a second training dataset having a plurality of n-grams that includes a second plurality of distinct training n-grams, wherein each of the second plurality of distinct training n-grams is the first size; computes a first plurality of appearance frequencies, wherein each of the first plurality of appearance frequencies corresponds to one of the first plurality of distinct training n-grams; computes a first plurality of uniformities of distribution, wherein each of the first plurality of uniformities of distribution corresponds to one of the first plurality of distinct training n-grams; computes a second plurality of uniformities of distribution, wherein each of the second plurality of uniformities of distribution corresponds to one of the second plurality of distinct training n-grams; determines a first plurality of most-heavily weighted n-grams from the first plurality of distinct training n-grams using at least one of: the first-plurality of appearance frequencies; the first plurality of uniformities of distribution; and the second plurality of uniformities of distribution; selects a subset of the first plurality of most-heavily weighted n-grams, wherein the subset includes in n-grams and at least one of the n-grams in the subset is outside of the top m of the first plurality of most-heavily weighted n-grams; receives an input dataset including first input n-grams, wherein each of the plurality of first input n-grams is the first size; obtains a subset of a second plurality of most-heavily weighted n-grams from the first input n-grams that correspond to the subset of the first plurality of distinct training n-grams; classifies the input dataset as containing an anomaly using the subset of the first plurality of most-heavily weighted n-grams and the subset of the second plurality of most-heavily weighted n-grams; and outputs a dataset based upon the classifying of the input dataset. 76. The system of claim 74 , wherein-the digital processing device also: receives a third training dataset having a plurality of n-grams that includes a third plurality of distinct training n-grams, wherein each of the third plurality of distinct training n-grams is the first size and contains malicious code; computes a third plurality of uniformities of distribution, wherein each of the third plurality of uniformities of distribution corresponds to one of the third plurality of distinct training n-grams; and determines a third plurality of most-heavily weighted n-grams from the third plurality of distinct training n-grams using at least one of: the first plurality of appearance frequencies; the first plurality of uniformities of distribution; and the third plurality of uniformities of distribution; and classifies the input dataset as containing an anomaly using a subset of the third plurality of most-heavily weighted n-grams and the subset of the second plurality of most-heavily weighted n-grams. | 0.717476 |
8,639,693 | 15 | 19 | 15. A computer-implemented method for providing personalized place recommendations, the method comprising: generating, using a processor, a plurality of collections of place listings, wherein the place listings in each collection includes a common trait, the common trait being based on a user's interaction with the place listings; identifying each place listing the user has interacted with as a seed listing; identifying a plurality of candidate listings, wherein at least one of the candidate listings and at least one of the seed listings are members of a particular collection; determining the collections having at least one of the candidate listings and at least one of the seed listings as members; calculating, using the processor, a weight value for each seed listing and each candidate listing in each collection, wherein the weight value indicates a strength of association between either the seed listing and the corresponding collection or the candidate listing and the corresponding collection; calculating, using the processor, a recommendation score for each candidate listing, wherein the recommendation score is calculated based on the weight values of the seed listings and the weight values of the candidate listings, the recommendation score indicating a likelihood that the user would be interested in the candidate listing; and in the event that any of the recommendation scores exceed a threshold: providing at least one candidate listing that corresponds to the recommendation score that exceeds the threshold for display on a computing device, and providing a justification for the at least one candidate listing for display on the computing device, wherein the justification is generated based on the seed listings. | 15. A computer-implemented method for providing personalized place recommendations, the method comprising: generating, using a processor, a plurality of collections of place listings, wherein the place listings in each collection includes a common trait, the common trait being based on a user's interaction with the place listings; identifying each place listing the user has interacted with as a seed listing; identifying a plurality of candidate listings, wherein at least one of the candidate listings and at least one of the seed listings are members of a particular collection; determining the collections having at least one of the candidate listings and at least one of the seed listings as members; calculating, using the processor, a weight value for each seed listing and each candidate listing in each collection, wherein the weight value indicates a strength of association between either the seed listing and the corresponding collection or the candidate listing and the corresponding collection; calculating, using the processor, a recommendation score for each candidate listing, wherein the recommendation score is calculated based on the weight values of the seed listings and the weight values of the candidate listings, the recommendation score indicating a likelihood that the user would be interested in the candidate listing; and in the event that any of the recommendation scores exceed a threshold: providing at least one candidate listing that corresponds to the recommendation score that exceeds the threshold for display on a computing device, and providing a justification for the at least one candidate listing for display on the computing device, wherein the justification is generated based on the seed listings. 19. The method of claim 15 , wherein the candidate listings are identified from results provided in response to a search. | 0.813846 |
8,098,976 | 15 | 16 | 15. A non-transitory computer-readable medium having sets of instructions stored thereon which, when executed by a computer, cause the computer to: receive a list of candidate tags for a video file; receive a transcript of audio associated with the video file; rank the list of candidate tags for the video file based on a plurality of ranking factors; filter candidate tags from the list of candidate tags which rank below a threshold value; present the filtered list of candidate tags in a user interface; receive a selection of one or more of the filtered list of candidate tags; receive one or more additional tags; based on the selected one or more of the filtered list of candidate tags and the evaluate the transcript and the one or more additional tags, evaluating the transcript and producing an updated list of candidate tags for the video file; establish a top concepts threshold value; determine that one or more of the rankings of the plurality of words exceeds the top concepts threshold; and associate information about the one or more of the plurality of words with rankings that exceeds the top concepts with the video file to designate the top concepts of the video file. | 15. A non-transitory computer-readable medium having sets of instructions stored thereon which, when executed by a computer, cause the computer to: receive a list of candidate tags for a video file; receive a transcript of audio associated with the video file; rank the list of candidate tags for the video file based on a plurality of ranking factors; filter candidate tags from the list of candidate tags which rank below a threshold value; present the filtered list of candidate tags in a user interface; receive a selection of one or more of the filtered list of candidate tags; receive one or more additional tags; based on the selected one or more of the filtered list of candidate tags and the evaluate the transcript and the one or more additional tags, evaluating the transcript and producing an updated list of candidate tags for the video file; establish a top concepts threshold value; determine that one or more of the rankings of the plurality of words exceeds the top concepts threshold; and associate information about the one or more of the plurality of words with rankings that exceeds the top concepts with the video file to designate the top concepts of the video file. 16. The non-transitory computer-readable medium of claim 15 , wherein the sets of instructions when further executed by the computer cause the computer to based on the updated list of candidate tags, provide suggested video files associated with the video file. | 0.859071 |
8,010,525 | 1 | 5 | 1. A computer-implemented method comprising: receiving a search query; generating first search results that identify resources that a search engine has identified as being responsive to the search query; identifying search modes based on the search query, the resources, or both the search query and the resources; providing a first user interface that presents for display at least a portion of the first search results and a respective search mode selector for each of one or more of the identified search modes; receiving user input selecting a first search mode by selecting one of the search mode selectors, wherein: the first search mode is associated with a first collection of records that share a first common attribute structure, a second of the search modes is associated with a second collection of records that share a second common attribute structure, and the first common attribute structure is different from the second common attribute structure; generating second search results that satisfy the search query and that refer to mode-specific records from the first collection of records that are associated with the first search mode, each of the search modes being associated with a particular collection of records from among multiple collections of records; formatting a plurality of the second search results using a mode-specific presentation template that is associated with the first search mode to generate formatted search results; and providing a second user interface that presents for display the formatted search results. | 1. A computer-implemented method comprising: receiving a search query; generating first search results that identify resources that a search engine has identified as being responsive to the search query; identifying search modes based on the search query, the resources, or both the search query and the resources; providing a first user interface that presents for display at least a portion of the first search results and a respective search mode selector for each of one or more of the identified search modes; receiving user input selecting a first search mode by selecting one of the search mode selectors, wherein: the first search mode is associated with a first collection of records that share a first common attribute structure, a second of the search modes is associated with a second collection of records that share a second common attribute structure, and the first common attribute structure is different from the second common attribute structure; generating second search results that satisfy the search query and that refer to mode-specific records from the first collection of records that are associated with the first search mode, each of the search modes being associated with a particular collection of records from among multiple collections of records; formatting a plurality of the second search results using a mode-specific presentation template that is associated with the first search mode to generate formatted search results; and providing a second user interface that presents for display the formatted search results. 5. The computer-implemented method of claim 1 , wherein identifying search modes comprises: determining that one or more of the resources include respective keywords that are associated with the search modes. | 0.895267 |
9,973,488 | 11 | 14 | 11. A computer-implemented method, comprising: receiving a first request to cause temporary password information to be added to a set of password information associated with a user, the first request being received in response to a login to a multi-tenant computing environment, and the set of password information associated with the user comprising a plurality of instances of password information; receiving a second request for authentication information to be provided to a target component, the second request based at least in part upon the temporary password information; adding the temporary password information to the set of password information, the set of password information including at least password information corresponding to a password known to the user, the temporary password information available for generating a ticket granting ticket (TGT); determining, based at least in part on the second request for authentication information, that the target component to receive the authentication information is not configured to accept the TGT; and generating a response to the second request for authentication information including at least a subset of the set of password information when the target component is determined as not being configured to accept the TGT. | 11. A computer-implemented method, comprising: receiving a first request to cause temporary password information to be added to a set of password information associated with a user, the first request being received in response to a login to a multi-tenant computing environment, and the set of password information associated with the user comprising a plurality of instances of password information; receiving a second request for authentication information to be provided to a target component, the second request based at least in part upon the temporary password information; adding the temporary password information to the set of password information, the set of password information including at least password information corresponding to a password known to the user, the temporary password information available for generating a ticket granting ticket (TGT); determining, based at least in part on the second request for authentication information, that the target component to receive the authentication information is not configured to accept the TGT; and generating a response to the second request for authentication information including at least a subset of the set of password information when the target component is determined as not being configured to accept the TGT. 14. The computer-implemented method of claim 11 , wherein the subset of the set of password information comprises the temporary password information. | 0.82304 |
7,546,382 | 1 | 25 | 1. A method of generating an application accessible by a user in accordance with a dialog system, the dialog system comprising one or more processors, the method comprising the steps of: declaratively representing by the one or more processors of the dialog system interactions that the user may have with the dialog system as a data model and one or more user interaction elements that populate an application state of the data model and that are bound thereto, the application comprising the data model and the one or more user interaction elements wherein the one or more user interaction elements comprise one or more elementary programming components that characterize a dialog, independent of modalities, devices, and browsers employable to access information associated with the application programmed in accordance therewith; wherein an intention of the user is determinable from an interpretation of the one or more user interaction elements and an extraction of a semantic meaning from a user input such that a dialog that the user has with the dialog system may be a mixed-initiative dialog whereby navigation through the application is performable in a non-sequential manner and at least partially user-driven; wherein at least a portion of the one or more user interaction elements can be transformed or associated to one or more modality-specific renderings of the application which are presentable to the user and are one of selected and generated by a dialog manager algorithm; and wherein the representation comprises attaching appropriate event handlers to each of a plurality of defined events comprising a parser event, a canonicalization event, a canonicalization response event, a backend submit event, a backend submit response event, a focus event, and a slot mutation event; wherein populating the application state of the data model comprises the steps of: scoring each of the one or more user interaction elements against one or more slots of each of a plurality of forms in accordance with a scoring algorithm; selecting at least one of the plurality of forms to represent the application state based at least in part on the scoring; and populating the one or more slots of the selected form by the one or more user interaction elements in accordance with the user's interaction with the dialog system; wherein the selected form specifies the scoring algorithm to be used for at least one subsequent scoring. | 1. A method of generating an application accessible by a user in accordance with a dialog system, the dialog system comprising one or more processors, the method comprising the steps of: declaratively representing by the one or more processors of the dialog system interactions that the user may have with the dialog system as a data model and one or more user interaction elements that populate an application state of the data model and that are bound thereto, the application comprising the data model and the one or more user interaction elements wherein the one or more user interaction elements comprise one or more elementary programming components that characterize a dialog, independent of modalities, devices, and browsers employable to access information associated with the application programmed in accordance therewith; wherein an intention of the user is determinable from an interpretation of the one or more user interaction elements and an extraction of a semantic meaning from a user input such that a dialog that the user has with the dialog system may be a mixed-initiative dialog whereby navigation through the application is performable in a non-sequential manner and at least partially user-driven; wherein at least a portion of the one or more user interaction elements can be transformed or associated to one or more modality-specific renderings of the application which are presentable to the user and are one of selected and generated by a dialog manager algorithm; and wherein the representation comprises attaching appropriate event handlers to each of a plurality of defined events comprising a parser event, a canonicalization event, a canonicalization response event, a backend submit event, a backend submit response event, a focus event, and a slot mutation event; wherein populating the application state of the data model comprises the steps of: scoring each of the one or more user interaction elements against one or more slots of each of a plurality of forms in accordance with a scoring algorithm; selecting at least one of the plurality of forms to represent the application state based at least in part on the scoring; and populating the one or more slots of the selected form by the one or more user interaction elements in accordance with the user's interaction with the dialog system; wherein the selected form specifies the scoring algorithm to be used for at least one subsequent scoring. 25. The method of claim 1 , wherein the representation permits continuous maintaining and updating of the application state. | 0.812121 |
8,271,481 | 11 | 14 | 11. A non-transitory computer-readable storage medium having instructions embodied thereon, the instructions being executable by a processor to perform a method for generating an automatic search query from an electronic mail application integrating with an electronic calendar system, the method comprising: receiving an input comprising a user-selected calendar entry from the electronic calendar system; in response to receiving the user-selected calendar entry, generating a search query from the user-selected calendar entry to search a local index of documents that the user has previously accessed for one or more documents related to the selected calendar entry; executing the search query by locating one or more documents in the local index that are related to the selected calendar entry; and providing search results to the user responsive to execution of the search query, wherein the search results include the one or more documents in the local index that were located during the execution of the search query. | 11. A non-transitory computer-readable storage medium having instructions embodied thereon, the instructions being executable by a processor to perform a method for generating an automatic search query from an electronic mail application integrating with an electronic calendar system, the method comprising: receiving an input comprising a user-selected calendar entry from the electronic calendar system; in response to receiving the user-selected calendar entry, generating a search query from the user-selected calendar entry to search a local index of documents that the user has previously accessed for one or more documents related to the selected calendar entry; executing the search query by locating one or more documents in the local index that are related to the selected calendar entry; and providing search results to the user responsive to execution of the search query, wherein the search results include the one or more documents in the local index that were located during the execution of the search query. 14. The to computer-readable storage medium of claim 11 , where the search results include only documents that the user has previously accessed. | 0.866171 |
8,818,910 | 1 | 3 | 1. A system for prioritizing a list of job candidates for a job opening with a firm, the system comprising: at least one computer system comprising at least one processor and at least one memory unit that is in communication with the at least one processor, wherein the at least one processor is programmed to: use a Random Forest Algorithm to generate a quantity T decision trees, where T is greater than or equal to 2, and the T decision trees are trained based on a training data set of historical candidates classified into hired or unhired classes, wherein each decision tree of the T decision trees is generated by selecting historical candidates in the training dataset randomly with replacement to train the decision tree; and for each of the job candidates, determine a classification of the job candidate for each of the T decision trees; compute a hiring probability for each job candidate based on a ratio of (i) a total of number of times the job candidate was classified as hired to (ii) T; and rank the job candidates by hiring probability to generate a prioritized list of the job candidates. | 1. A system for prioritizing a list of job candidates for a job opening with a firm, the system comprising: at least one computer system comprising at least one processor and at least one memory unit that is in communication with the at least one processor, wherein the at least one processor is programmed to: use a Random Forest Algorithm to generate a quantity T decision trees, where T is greater than or equal to 2, and the T decision trees are trained based on a training data set of historical candidates classified into hired or unhired classes, wherein each decision tree of the T decision trees is generated by selecting historical candidates in the training dataset randomly with replacement to train the decision tree; and for each of the job candidates, determine a classification of the job candidate for each of the T decision trees; compute a hiring probability for each job candidate based on a ratio of (i) a total of number of times the job candidate was classified as hired to (ii) T; and rank the job candidates by hiring probability to generate a prioritized list of the job candidates. 3. The system of claim 1 , wherein: there are N historical candidates in the training data set; and the at least one processor is programmed to select, for the training of each of the T decision trees, N historical candidates in the training dataset randomly with replacement. | 0.602305 |
7,877,255 | 1 | 19 | 1. A method for automatic speech recognition, the method comprising: determining for an input signal a plurality of scores representative of certainties that the input signal is associated with corresponding states of a speech recognition model; using the speech recognition model and the determined scores to compute an average signal; computing, via a processor device executing instructions, a difference value representative of a difference between the input signal and the average signal; and processing, via the processor device, the input signal in accordance with the difference value; wherein computing the average signal comprises: identifying a given score from the plurality of scores; selecting from the plurality of scores a set of scores whose corresponding values are within a predetermined threshold from a value of the given score; and performing an averaging operation on observation mean vectors of observation densities associated with the selected plurality of scores to obtain the average signal. | 1. A method for automatic speech recognition, the method comprising: determining for an input signal a plurality of scores representative of certainties that the input signal is associated with corresponding states of a speech recognition model; using the speech recognition model and the determined scores to compute an average signal; computing, via a processor device executing instructions, a difference value representative of a difference between the input signal and the average signal; and processing, via the processor device, the input signal in accordance with the difference value; wherein computing the average signal comprises: identifying a given score from the plurality of scores; selecting from the plurality of scores a set of scores whose corresponding values are within a predetermined threshold from a value of the given score; and performing an averaging operation on observation mean vectors of observation densities associated with the selected plurality of scores to obtain the average signal. 19. The method as in claim 1 further comprising: in response to determining that a segment of the input signal is inconsistent with signals normally received through a speech channel, biasing scores of noise states associated with the speech recognition model to increase a probability that the segment of the input signal is deemed to be sound received on a noise channel rather than sound received on the speech channel. | 0.616364 |
10,165,149 | 10 | 13 | 10. A method comprising, by a scanning device: receiving a physical document that is to be converted into an electronic document; performing optical character recognition on at least a portion of the physical document to identify one or more terms that are present in the physical document; storing the identified terms in the data store associated with the scanning device; receiving input from a user, wherein the input comprises one or more first characters and corresponds to a title of the electronic document; identifying one or more terms from the data store that correspond to the one or more first characters by querying the data store using the received input; and causing the identified terms to be displayed to the user via a display device of the scanning device as suggested document names for the electronic document. | 10. A method comprising, by a scanning device: receiving a physical document that is to be converted into an electronic document; performing optical character recognition on at least a portion of the physical document to identify one or more terms that are present in the physical document; storing the identified terms in the data store associated with the scanning device; receiving input from a user, wherein the input comprises one or more first characters and corresponds to a title of the electronic document; identifying one or more terms from the data store that correspond to the one or more first characters by querying the data store using the received input; and causing the identified terms to be displayed to the user via a display device of the scanning device as suggested document names for the electronic document. 13. The method of claim 10 , wherein receiving input from a user comprises determining that the input is being provided in a field associated with a name of the electronic document. | 0.901309 |
9,286,377 | 9 | 10 | 9. A method for identifying semantically relevant documents, comprising: maintaining an index comprising semantic index key terms from one or more documents; obtaining a query and identifying semantic key terms of the query, wherein each of the query key terms are associated with information comprising use of the word and a grammatical role of the word; and looking up the each of the query key terms and variants of the query key terms in the index based on the information; identifying one or more of the documents in the index as possible relevant candidates based on the look up; generating a potential match candidate set by filtering the possible relevant candidates; identifying at least one of the documents that match the query by comparing a semantic representation for each filtered potential match candidate in the set with a semantic representation for the query, wherein each of the semantic representation for the query and the semantic representation for each potential match candidate in the set comprises one or more semantic substructures, comprising: aligning the substructures for the query semantic representation and one or more of the semantic representations for the potential match candidates; and assigning a score to the one or more potential match candidates by identifying shared substructures with the query semantic representation. | 9. A method for identifying semantically relevant documents, comprising: maintaining an index comprising semantic index key terms from one or more documents; obtaining a query and identifying semantic key terms of the query, wherein each of the query key terms are associated with information comprising use of the word and a grammatical role of the word; and looking up the each of the query key terms and variants of the query key terms in the index based on the information; identifying one or more of the documents in the index as possible relevant candidates based on the look up; generating a potential match candidate set by filtering the possible relevant candidates; identifying at least one of the documents that match the query by comparing a semantic representation for each filtered potential match candidate in the set with a semantic representation for the query, wherein each of the semantic representation for the query and the semantic representation for each potential match candidate in the set comprises one or more semantic substructures, comprising: aligning the substructures for the query semantic representation and one or more of the semantic representations for the potential match candidates; and assigning a score to the one or more potential match candidates by identifying shared substructures with the query semantic representation. 10. A method according to claim 9 , further comprising: determining the possible relevant candidates, comprising: retrieving a result set for each of the query key terms identified in the index, wherein the result set comprises at least one of the documents; and performing set operations of the result sets for two or more of the query key terms and classifying the results of the set operations as the possible relevant candidates. | 0.646819 |
9,684,721 | 21 | 30 | 21. A system, comprising: one or more memory devices; and one or more processors coupled to the one or more memory devices; wherein the one or more memory devices store machine readable instructions that, when executed by the one or more processors, cause the one or more processors to: receive a user input in an imprecise syntax, wherein: the user input in the imprecise syntax includes at least (i) word, or a phrase, that corresponds to a formula having a plurality of mathematical or scientific parameters, and (ii) one or more words, and/or one or more phrases, that correspond to one or more parameter values corresponding to the formula, the user input in the imprecise syntax is expressed using natural language and/or informal terminology spoken by a user, and the user input in the imprecise syntax corresponds to a digital representation of an audio signal corresponding to speech spoken by the user, the digital representation of the audio signal corresponding to the speech spoken by the user having been generated by a voice recognition system; wherein the one or more memory devices store further machine readable instructions that, when executed by the one or more processors, cause the one or more processors to: analyze the user input in the imprecise syntax to determine the formula with the one or more parameter values integrated into the formula; calculate a numerical result using the determined formula with the one or more parameter values integrated into the determined formula; and generate an output, using the numerical result, to perform a physical machine action. | 21. A system, comprising: one or more memory devices; and one or more processors coupled to the one or more memory devices; wherein the one or more memory devices store machine readable instructions that, when executed by the one or more processors, cause the one or more processors to: receive a user input in an imprecise syntax, wherein: the user input in the imprecise syntax includes at least (i) word, or a phrase, that corresponds to a formula having a plurality of mathematical or scientific parameters, and (ii) one or more words, and/or one or more phrases, that correspond to one or more parameter values corresponding to the formula, the user input in the imprecise syntax is expressed using natural language and/or informal terminology spoken by a user, and the user input in the imprecise syntax corresponds to a digital representation of an audio signal corresponding to speech spoken by the user, the digital representation of the audio signal corresponding to the speech spoken by the user having been generated by a voice recognition system; wherein the one or more memory devices store further machine readable instructions that, when executed by the one or more processors, cause the one or more processors to: analyze the user input in the imprecise syntax to determine the formula with the one or more parameter values integrated into the formula; calculate a numerical result using the determined formula with the one or more parameter values integrated into the determined formula; and generate an output, using the numerical result, to perform a physical machine action. 30. The system of claim 21 , wherein the one or more memory devices store further machine readable instructions that, when executed by the one or more processors, cause the one or more processors to: electronically insert the numerical result into an electronic document. | 0.881556 |
8,990,200 | 1 | 2 | 1. A computer-implemented method for generating a context vector for a given topic in a set of topics, the method comprising: identifying a set of topics appearing in sentences in a corpus; for keywords appearing in the sentences in the corpus, determining a topic confidence value indicating a quality of a match between a keyword in a sentence and a topic in the set of topics by: identifying keywords within the sentence based at least in part on parts of speech contained in the sentence; matching the keywords with one or more stored topics to create a tuple for the sentence, the tuple describing topics that are included in the sentence; assigning a topic confidence value for each topic included in the tuple, the topic confidence value indicating a quality of the match between the topic and a keyword in the sentence; and storing the tuple including the topic confidence values for each topic included in the sentence; determining the context vector for the given topic, the context vector representing a frequency of the given topic co-occurring with a plurality of topics from the set of topics, the context vector comprising: a plurality of context confidence values each represent a relationship between the given topic and a topic from the plurality of topics in the set of topics that co-occur within a sentence from the corpus with the given topic; where each context confidence value of the plurality of context confidence values is based upon a combination of a topic confidence value of the given topic and a topic confidence value of the topic from the plurality of topics in the set of topics that co-occurs within the sentence from the corpus with the given topic; wherein determining the context vector for the given topic comprises: normalizing each topic confidence measure in the context vector; sorting the topic confidence measures in the context vector in descending order; and storing the context vector for the given topic in a memory. | 1. A computer-implemented method for generating a context vector for a given topic in a set of topics, the method comprising: identifying a set of topics appearing in sentences in a corpus; for keywords appearing in the sentences in the corpus, determining a topic confidence value indicating a quality of a match between a keyword in a sentence and a topic in the set of topics by: identifying keywords within the sentence based at least in part on parts of speech contained in the sentence; matching the keywords with one or more stored topics to create a tuple for the sentence, the tuple describing topics that are included in the sentence; assigning a topic confidence value for each topic included in the tuple, the topic confidence value indicating a quality of the match between the topic and a keyword in the sentence; and storing the tuple including the topic confidence values for each topic included in the sentence; determining the context vector for the given topic, the context vector representing a frequency of the given topic co-occurring with a plurality of topics from the set of topics, the context vector comprising: a plurality of context confidence values each represent a relationship between the given topic and a topic from the plurality of topics in the set of topics that co-occur within a sentence from the corpus with the given topic; where each context confidence value of the plurality of context confidence values is based upon a combination of a topic confidence value of the given topic and a topic confidence value of the topic from the plurality of topics in the set of topics that co-occurs within the sentence from the corpus with the given topic; wherein determining the context vector for the given topic comprises: normalizing each topic confidence measure in the context vector; sorting the topic confidence measures in the context vector in descending order; and storing the context vector for the given topic in a memory. 2. The computer-implemented method of claim 1 , wherein the topic confidence value is based upon: a string match between the keyword and a name of the topic; and a parts of speech match between the keyword and a part of speech of the topic. | 0.63964 |
10,127,305 | 17 | 18 | 17. A non-transitory machine-readable storage medium comprising instructions that, when executed by one or more processors of a machine, cause the machine to perform operations comprising: accessing a first profile of a first member of a social network, the first profile being accessed in response to an action that references at least part of the first profile; determining a similarity score that quantifies similarity between the first profile and a second profile of a second member of the social network; ranking the second profile of the second member based on the determined similarity score and based on an elapsed time since the action that references at least the part of the first profile; and presenting the second profile based on the ranking of the second profile. | 17. A non-transitory machine-readable storage medium comprising instructions that, when executed by one or more processors of a machine, cause the machine to perform operations comprising: accessing a first profile of a first member of a social network, the first profile being accessed in response to an action that references at least part of the first profile; determining a similarity score that quantifies similarity between the first profile and a second profile of a second member of the social network; ranking the second profile of the second member based on the determined similarity score and based on an elapsed time since the action that references at least the part of the first profile; and presenting the second profile based on the ranking of the second profile. 18. The non-transitory machine-readable storage medium of claim 17 , wherein: the presenting of the second profile of the second member includes presenting an indication of the elapsed time since the action that references at least the part of the first profile. | 0.669192 |
9,858,051 | 51 | 52 | 51. The security appliance of claim 50 wherein the processor is further configured to: if the first hash value is not present in the EC cache table, compute an epsilon closure of the set of NFA states received; and add a new entry into the EC cache table, the new entry mapping the first hash value of the set of NFA states received to the epsilon closure computed of the set of NFA states received. | 51. The security appliance of claim 50 wherein the processor is further configured to: if the first hash value is not present in the EC cache table, compute an epsilon closure of the set of NFA states received; and add a new entry into the EC cache table, the new entry mapping the first hash value of the set of NFA states received to the epsilon closure computed of the set of NFA states received. 52. The security appliance of claim 51 , wherein the processor is further configured to: determine whether there is sufficient memory to add the new entry; and if there is not sufficient memory, add the new entry according to a replacement policy. | 0.923292 |
9,852,192 | 15 | 18 | 15. A non-transitory computer-readable medium containing computer-executable instructions that, when executed by a processor, cause the processor to perform a method for recommending media content, the method comprising: determining that a session including presentation of at least a first media content item and a second media content item is likely to have ended, wherein the second media content item is presented within a given span of the presentation of the first media content item; in response to determining that the session is likely to have ended, determining a first plurality of topics associated with the first media content item and the second media content item; determining a second plurality of topics associated with the media content presentation session based on distance information for pairs of topics in the first plurality of topics, wherein each of the pairs of topics includes a first topic associated with the first media content item and a second topic associated with the second media content item; and transmitting an indication of a plurality of media content items that correspond to at least a portion of the second plurality of topics. | 15. A non-transitory computer-readable medium containing computer-executable instructions that, when executed by a processor, cause the processor to perform a method for recommending media content, the method comprising: determining that a session including presentation of at least a first media content item and a second media content item is likely to have ended, wherein the second media content item is presented within a given span of the presentation of the first media content item; in response to determining that the session is likely to have ended, determining a first plurality of topics associated with the first media content item and the second media content item; determining a second plurality of topics associated with the media content presentation session based on distance information for pairs of topics in the first plurality of topics, wherein each of the pairs of topics includes a first topic associated with the first media content item and a second topic associated with the second media content item; and transmitting an indication of a plurality of media content items that correspond to at least a portion of the second plurality of topics. 18. The non-transitory computer-readable medium of claim 15 , wherein the given span is two adjacent presentations. | 0.769076 |
9,971,967 | 4 | 5 | 4. The method of claim 2 further comprising: selecting a set of data sources included in the corpus of knowledge, wherein the selected set of data sources are related to a common domain of information; extracting a plurality of words from the set of data sources; calculating a domain-usage frequency for each of the plurality of words, wherein the domain-usage frequency is the frequency that each of the plurality of words occurs in the set of data sources; retrieving a general-usage frequency for each of the plurality of words, wherein the general-usage frequency is the frequency that each of the plurality of words occurs in general language usage; for each of the plurality of words, comparing the domain-usage frequency of the word with the general-usage frequency of the word; and identifying a set of the plurality of words from the plurality of words as the plurality of key words, the identifying based on the comparison revealing that the domain-usage frequency corresponding to each word in the set of the plurality of words is statistically significantly higher than the general-usage frequency corresponding to the respective word. | 4. The method of claim 2 further comprising: selecting a set of data sources included in the corpus of knowledge, wherein the selected set of data sources are related to a common domain of information; extracting a plurality of words from the set of data sources; calculating a domain-usage frequency for each of the plurality of words, wherein the domain-usage frequency is the frequency that each of the plurality of words occurs in the set of data sources; retrieving a general-usage frequency for each of the plurality of words, wherein the general-usage frequency is the frequency that each of the plurality of words occurs in general language usage; for each of the plurality of words, comparing the domain-usage frequency of the word with the general-usage frequency of the word; and identifying a set of the plurality of words from the plurality of words as the plurality of key words, the identifying based on the comparison revealing that the domain-usage frequency corresponding to each word in the set of the plurality of words is statistically significantly higher than the general-usage frequency corresponding to the respective word. 5. The method of claim 4 further comprising: searching a plurality of schemas corresponding to the structured database for the plurality of key words; finding a selected one of the key words in a selected one of the schemas, wherein the selected schema corresponds to a selected database table included in the structured database; and building the initial structured query language expression to search for the selected key word in the selected database table. | 0.839833 |
9,940,365 | 7 | 8 | 7. The computer system of claim 6 , further comprising the hardware processor executing the instructions stored in the system memory to access a set of query features for the search query; and wherein the hardware processor executing the instructions stored in the system memory to derive a set of ranking features for the candidate table comprises the hardware processor executing the instructions stored in the system memory to derive the set of ranking features from the set of static features, the one or more dynamic features, and the set of query features. | 7. The computer system of claim 6 , further comprising the hardware processor executing the instructions stored in the system memory to access a set of query features for the search query; and wherein the hardware processor executing the instructions stored in the system memory to derive a set of ranking features for the candidate table comprises the hardware processor executing the instructions stored in the system memory to derive the set of ranking features from the set of static features, the one or more dynamic features, and the set of query features. 8. The computer system of claim 7 , wherein the hardware processor executing the instructions stored in the system memory to access a set of query features for the search query comprises the hardware processor executing the instructions stored in the system memory to: for one or more keywords of the search query, access a translation model for the keyword; and access at least one other query feature selected from among: an indication if the keyword is a stop word, an indication if the keyword is numeric, and an indication if the keyword is alphanumeric. | 0.844376 |
7,516,070 | 11 | 12 | 11. The method according to claim 9 , further including transcribing audio into the other text. | 11. The method according to claim 9 , further including transcribing audio into the other text. 12. The method according to claim 11 , wherein the transcribing is done using a speech recognition software. | 0.957346 |
9,262,506 | 11 | 12 | 11. The system of claim 10 , wherein the taxonomy category is mapped by the processor to the corresponding category in the master taxonomy, and the processor is further configured with logic to: identify the outlier documents from the documents having insufficient classification score values indicating that the documents have classification score values that are insufficient for further evaluation for classification into the corresponding category in the master taxonomy. | 11. The system of claim 10 , wherein the taxonomy category is mapped by the processor to the corresponding category in the master taxonomy, and the processor is further configured with logic to: identify the outlier documents from the documents having insufficient classification score values indicating that the documents have classification score values that are insufficient for further evaluation for classification into the corresponding category in the master taxonomy. 12. The system of claim 11 , wherein the processor is further configured with logic to: create at least one new category in the master taxonomy for the outlier documents in response to a sufficient quantity of outlier documents having insufficient classification score values. | 0.89808 |
7,533,338 | 17 | 21 | 17. The system for asynchronous receipt and processing of electronic ink annotation of a document, comprising: an input for receiving electronic ink input data in the document, wherein The document is an electronic document; and a processor programmed and adapted to: generate a first analysis context object, the first analysis context object providing a translation layer for a document model of a current state of a relationship of elements in the document and comprising a tree data structure for storing document elements in a hierarchical relationship; start a first thread, wherein the first thread updates the first analysis context object based upon a user interaction with the document, the user interaction including electronic ink annotation; upon an event requiring analysis of new data in the document: suspend the execution of the first thread so as to prevent changes to the first analysis context object; start a second thread, wherein the second thread generates a second analysis context object corresponding to a portion of the first analysis context object, wherein the portion corresponds to a designated region of the document; upon completion of generation of the second analysis context object: suspend the execution of the second threat; restart the first threat; perform a first analysis of the second analysis context object to generate a third analysis context object from the second analysis context object, wherein the third analysis context object is generated by parsing the new data and modifying the second analysis context object based on the new data; upon completion of the first analysis: suspend execution of the first thread so as to prevent any changes to the first analysis context object; start a third thread, wherein the third thread reconciles the third analysis context object with the first analysis context object to generate first reconciled analysis results; upon completion of the reconciliation of the first analysis context object and the third analysis context object: update the first analysis context object with the first reconciled analysis results; and suspend the execution of the third thread; and restart the first thread. | 17. The system for asynchronous receipt and processing of electronic ink annotation of a document, comprising: an input for receiving electronic ink input data in the document, wherein The document is an electronic document; and a processor programmed and adapted to: generate a first analysis context object, the first analysis context object providing a translation layer for a document model of a current state of a relationship of elements in the document and comprising a tree data structure for storing document elements in a hierarchical relationship; start a first thread, wherein the first thread updates the first analysis context object based upon a user interaction with the document, the user interaction including electronic ink annotation; upon an event requiring analysis of new data in the document: suspend the execution of the first thread so as to prevent changes to the first analysis context object; start a second thread, wherein the second thread generates a second analysis context object corresponding to a portion of the first analysis context object, wherein the portion corresponds to a designated region of the document; upon completion of generation of the second analysis context object: suspend the execution of the second threat; restart the first threat; perform a first analysis of the second analysis context object to generate a third analysis context object from the second analysis context object, wherein the third analysis context object is generated by parsing the new data and modifying the second analysis context object based on the new data; upon completion of the first analysis: suspend execution of the first thread so as to prevent any changes to the first analysis context object; start a third thread, wherein the third thread reconciles the third analysis context object with the first analysis context object to generate first reconciled analysis results; upon completion of the reconciliation of the first analysis context object and the third analysis context object: update the first analysis context object with the first reconciled analysis results; and suspend the execution of the third thread; and restart the first thread. 21. The system according to claim 17 , wherein the portion includes at least one of electronic text, an image, a table, a list, a graph, a spreadsheet, a chart, or a drawing. | 0.812095 |
8,887,062 | 15 | 21 | 15. A computer readable storage medium has instructions stored for streamlined web site navigation thereon which, when executed by one or more computers, cause the one or more computers to perform operations including: providing a command line interface to a particular web site supplemental to a GUI interface, wherein the command line interface accepts entry of verbs and parameters from a web site-specific vocabulary, wherein the verbs and parameters have meaning local to a web server hosting the particular web site, wherein the web site-specific vocabulary allows a user to access functions of a GUI interface page of the web site by entering at least one verb and without navigating page links to reach the GUI interface page; receiving data entered at the command line interface, including the at least one verb; identifying a particular web page responsive to the verb; and sending the particular web page towards a client system. | 15. A computer readable storage medium has instructions stored for streamlined web site navigation thereon which, when executed by one or more computers, cause the one or more computers to perform operations including: providing a command line interface to a particular web site supplemental to a GUI interface, wherein the command line interface accepts entry of verbs and parameters from a web site-specific vocabulary, wherein the verbs and parameters have meaning local to a web server hosting the particular web site, wherein the web site-specific vocabulary allows a user to access functions of a GUI interface page of the web site by entering at least one verb and without navigating page links to reach the GUI interface page; receiving data entered at the command line interface, including the at least one verb; identifying a particular web page responsive to the verb; and sending the particular web page towards a client system. 21. The computer readable storage medium of claim 15 , wherein the operations further including: receiving with the data context information that was not entered at the command line interface; and identifying the particular web page, responsive to the verb combined with the context information. | 0.67511 |
8,793,253 | 1 | 3 | 1. A computer implemented method of converting at least some information of a composition of ontological subjects into at least one ordered array of data, said method comprises execution of a set of instructions, by one or more data processing or computing devices, configured to perform: partitioning, using one or more data processing or computing devices, the composition into one or more sets of partitions, wherein at least one of said one or more sets of partitions is assigned with a predefined ontological subject order l, wherein l is a variable and is represented by a string of one or more characters; identifying one or more sets of ontological subjects or partitions of the composition, wherein at least one set of said one or more sets of ontological subjects or partitions of the composition is assigned with a predefined ontological subject order k; wherein k is a variable and is represented by a string of one or more characters; constructing one or more data structure corresponding to at least one ordered array of data, wherein said at least one ordered array of data represents participation of some of said ontological subjects or partitions of the composition, assigned with the order k, into some of the partitions, assigned with the order l, by having a non-zero value in the corresponding entries of the at least one ordered array of data, wherein the ordered array of data represents a matrix, wherein each row of the matrix is representative of an ontological subjects or a partition of the composition, assigned with the order k, and each column of the matrix is representative of a partition from said set of partitions, assigned with order l, or vice versa; replacing one or more of ontological subjects or partitions of the composition, assigned with the order k, with an ontological subject, assigned with a predefined order, and updating respective entries of said one or more ontological subjects or partitions of the composition in the at least one ordered data array accordingly; and storing the one or more data structure corresponding to the at least one ordered array of data onto one or more non-transitory computer readable medium. | 1. A computer implemented method of converting at least some information of a composition of ontological subjects into at least one ordered array of data, said method comprises execution of a set of instructions, by one or more data processing or computing devices, configured to perform: partitioning, using one or more data processing or computing devices, the composition into one or more sets of partitions, wherein at least one of said one or more sets of partitions is assigned with a predefined ontological subject order l, wherein l is a variable and is represented by a string of one or more characters; identifying one or more sets of ontological subjects or partitions of the composition, wherein at least one set of said one or more sets of ontological subjects or partitions of the composition is assigned with a predefined ontological subject order k; wherein k is a variable and is represented by a string of one or more characters; constructing one or more data structure corresponding to at least one ordered array of data, wherein said at least one ordered array of data represents participation of some of said ontological subjects or partitions of the composition, assigned with the order k, into some of the partitions, assigned with the order l, by having a non-zero value in the corresponding entries of the at least one ordered array of data, wherein the ordered array of data represents a matrix, wherein each row of the matrix is representative of an ontological subjects or a partition of the composition, assigned with the order k, and each column of the matrix is representative of a partition from said set of partitions, assigned with order l, or vice versa; replacing one or more of ontological subjects or partitions of the composition, assigned with the order k, with an ontological subject, assigned with a predefined order, and updating respective entries of said one or more ontological subjects or partitions of the composition in the at least one ordered data array accordingly; and storing the one or more data structure corresponding to the at least one ordered array of data onto one or more non-transitory computer readable medium. 3. The method of claim 1 , further comprising calculating similarity coefficients, based on one or more similarity measures, between some of partitions, assigned with the order l, using said at least one ordered data array. | 0.902193 |
9,767,166 | 8 | 9 | 8. The method of claim 1 , further comprising: identifying at least one connection between at least two of the detected phrases, wherein the at least one term taxonomy is created further based on the identified at least one connection. | 8. The method of claim 1 , further comprising: identifying at least one connection between at least two of the detected phrases, wherein the at least one term taxonomy is created further based on the identified at least one connection. 9. The method of claim 8 , wherein each connection is any of: a direct connection, and a hidden connection. | 0.960662 |
8,806,401 | 5 | 6 | 5. The method of claim 1 , wherein the property is defined in an assertion specification language. | 5. The method of claim 1 , wherein the property is defined in an assertion specification language. 6. The method of claim 5 , wherein the assertion specification language is at least one of property specification language (PSL) and System Verilog® assertion (SVA). | 0.924173 |
9,740,692 | 17 | 18 | 17. A non-transitory computer-readable medium having instructions stored thereon to create a flexible structure description, the instructions comprising: instructions to receive an image of a document of a particular document type that contains a table; instructions to receive an entry describing an item in the table; instructions to search for title elements based upon the entry; instructions to detect data fields and anchor elements for the entry; instructions to generate a flexible structure description for the particular document type that includes a set of search elements for each data field in the image of the document and the title elements; instructions to match the flexible structure description against the image; and instructions to extract data from the image based upon the matching of the flexible structure description against the image. | 17. A non-transitory computer-readable medium having instructions stored thereon to create a flexible structure description, the instructions comprising: instructions to receive an image of a document of a particular document type that contains a table; instructions to receive an entry describing an item in the table; instructions to search for title elements based upon the entry; instructions to detect data fields and anchor elements for the entry; instructions to generate a flexible structure description for the particular document type that includes a set of search elements for each data field in the image of the document and the title elements; instructions to match the flexible structure description against the image; and instructions to extract data from the image based upon the matching of the flexible structure description against the image. 18. The non-transitory computer-readable medium of claim 17 , wherein the instructions further comprise instructions to adjust the flexible structure description based on user corrections of detected data fields, title elements, and/or anchor elements. | 0.501976 |
8,798,986 | 1 | 12 | 1. A method of providing a portable, real time voice translation, the method comprising: making a translation system available to a user for use on a single unit, portable device having a processor and a memory, the translation system having a computer program that is operable in executing the following functions: accessing a multilanguage database embodied in a non-transitory computer readable storage medium including a plurality of phrase templates associated with a respective plurality of phrases; selecting a source language from a plurality of source languages and a destination language from a plurality of destination languages; inputting a source phrase; transmitting the source phrase (i) to a speech recognition module embodied in a non-transitory computer readable storage medium for converting the spoken source phrase into a recognized source phrase; (ii) a translation engine embodied in a non-transitory computer readable storage medium for translating the recognized source phrase in the selected source language into a destination phrase in a destination language selected from multiple languages, wherein the plurality of phrases in the multilanguage database include the destination phrase; (iii) a template look-up engine embodied in a non-transitory computer readable storage medium for finding the phrase template associated with the destination phrase from among the multiple languages; and, outputting the spoken translation in the selected destination language; the translation system having a total time between the input of the source phrase and output of the destination phrase that is no slower than 0.010 seconds. | 1. A method of providing a portable, real time voice translation, the method comprising: making a translation system available to a user for use on a single unit, portable device having a processor and a memory, the translation system having a computer program that is operable in executing the following functions: accessing a multilanguage database embodied in a non-transitory computer readable storage medium including a plurality of phrase templates associated with a respective plurality of phrases; selecting a source language from a plurality of source languages and a destination language from a plurality of destination languages; inputting a source phrase; transmitting the source phrase (i) to a speech recognition module embodied in a non-transitory computer readable storage medium for converting the spoken source phrase into a recognized source phrase; (ii) a translation engine embodied in a non-transitory computer readable storage medium for translating the recognized source phrase in the selected source language into a destination phrase in a destination language selected from multiple languages, wherein the plurality of phrases in the multilanguage database include the destination phrase; (iii) a template look-up engine embodied in a non-transitory computer readable storage medium for finding the phrase template associated with the destination phrase from among the multiple languages; and, outputting the spoken translation in the selected destination language; the translation system having a total time between the input of the source phrase and output of the destination phrase that is no slower than 0.010 seconds. 12. The method of claim 1 , wherein the executing includes accessing a plurality of phrase templates that represent languages that include at least a combination of English, French, and Spanish; English, Japanese, and Mandarin; English, French, and Portuguese; English, Russian, and Mandarin; English, Hindustani, and Japanese; or, English, Arabic, and Russian. | 0.771808 |
7,734,622 | 1 | 6 | 1. A machine-implemented browsing method, comprising: performing a context search based on information associated with at least one media object, wherein the performing of the context search comprises searching a first database of indexed references to web pages and other documents based on search criteria derived from information extracted from the at least one media object, wherein the performing of the context search further comprises generating a context search query from information associated with the at least one media object, transmitting the context search query to a first search engine operable to query the first database in response to receipt of the context search query, and receiving a first search response from the first search engine; performing a context-sensitive search based on results of the context search, wherein the performing of the context-sensitive search comprises searching a second database of indexed references to web pages and other documents based on search criteria derived from the results of the context search, wherein the performing of the context-sensitive search further comprises generating a context-sensitive search query from the first search response, transmitting the context-sensitive search query to a second search engine operable to query the second database in response to receipt of the context-sensitive search query, and receiving a second search response from the second search engine; and presenting information derived from results of the context-sensitive search. | 1. A machine-implemented browsing method, comprising: performing a context search based on information associated with at least one media object, wherein the performing of the context search comprises searching a first database of indexed references to web pages and other documents based on search criteria derived from information extracted from the at least one media object, wherein the performing of the context search further comprises generating a context search query from information associated with the at least one media object, transmitting the context search query to a first search engine operable to query the first database in response to receipt of the context search query, and receiving a first search response from the first search engine; performing a context-sensitive search based on results of the context search, wherein the performing of the context-sensitive search comprises searching a second database of indexed references to web pages and other documents based on search criteria derived from the results of the context search, wherein the performing of the context-sensitive search further comprises generating a context-sensitive search query from the first search response, transmitting the context-sensitive search query to a second search engine operable to query the second database in response to receipt of the context-sensitive search query, and receiving a second search response from the second search engine; and presenting information derived from results of the context-sensitive search. 6. The method of claim 1 , wherein generating the context-sensitive search query comprises extracting one or more search criteria of the context-sensitive search query from the first search response. | 0.5025 |
8,819,000 | 1 | 4 | 1. A computer-implemented method, comprising: receiving an original query including a first limitation that constrains a search; modifying the original query to obtain a modified query in which the first limitation that constrains the search has been omitted; obtaining, from a search engine system, first search results responsive to the modified query, wherein the first search results have an associated ranking determined by the search engine system, and wherein each of the first search results refers to a respective resource; identifying one or more common characteristics shared by two or more resources, each of the two or more resources corresponding to a different highly-ranked result of the first search results; generating a second modified query comprising the original query and a second limitation representing the one or more common characteristics, the second limitation requiring results responsive to the second modified query to reference a resource having the one or more common characteristics; obtaining second search results responsive to the second modified query, wherein each of the second search results refers to a resource having the one or more common characteristics; and providing the second search results in a response to the original query. | 1. A computer-implemented method, comprising: receiving an original query including a first limitation that constrains a search; modifying the original query to obtain a modified query in which the first limitation that constrains the search has been omitted; obtaining, from a search engine system, first search results responsive to the modified query, wherein the first search results have an associated ranking determined by the search engine system, and wherein each of the first search results refers to a respective resource; identifying one or more common characteristics shared by two or more resources, each of the two or more resources corresponding to a different highly-ranked result of the first search results; generating a second modified query comprising the original query and a second limitation representing the one or more common characteristics, the second limitation requiring results responsive to the second modified query to reference a resource having the one or more common characteristics; obtaining second search results responsive to the second modified query, wherein each of the second search results refers to a resource having the one or more common characteristics; and providing the second search results in a response to the original query. 4. The computer-implemented method of claim 1 , wherein the first limitation constrains a time, a date, a document type, a media type, a language, an author, a publisher, a number of links or citations, or a geographical region of resources corresponding to results responsive to the original query. | 0.820743 |
7,584,093 | 9 | 11 | 9. A system comprising: a computer including a processor; a tangible computer-readable medium; program modules comprising instructions executable by the processor to suggest replacement words for input words of an input string, the modules comprising: a candidate generator including an output of one or more candidate replacement words and corresponding candidate scores for one of the input words that match a subject word of a candidate table, wherein each candidate score is indicative of a probability that the input word should be replaced with the corresponding candidate replacement word; a contextual spelling engine receives the output of one or more candidate replacement words and produces a candidate replacement string for each candidate replacement word, each candidate replacement string comprising the candidate replacement word and the input words of the input string less the input word corresponding to the candidate replacement word; and a language model having an output of probability scores for each of the candidate replacement strings, the probability scores based on statistical data; wherein the contextual spelling engine calculates a final score for each of the candidate replacement words based on the candidate score for the candidate replacement word and the probability score for the candidate replacement string containing the candidate replacement word, and outputs one of the candidate replacement words based on the final scores. | 9. A system comprising: a computer including a processor; a tangible computer-readable medium; program modules comprising instructions executable by the processor to suggest replacement words for input words of an input string, the modules comprising: a candidate generator including an output of one or more candidate replacement words and corresponding candidate scores for one of the input words that match a subject word of a candidate table, wherein each candidate score is indicative of a probability that the input word should be replaced with the corresponding candidate replacement word; a contextual spelling engine receives the output of one or more candidate replacement words and produces a candidate replacement string for each candidate replacement word, each candidate replacement string comprising the candidate replacement word and the input words of the input string less the input word corresponding to the candidate replacement word; and a language model having an output of probability scores for each of the candidate replacement strings, the probability scores based on statistical data; wherein the contextual spelling engine calculates a final score for each of the candidate replacement words based on the candidate score for the candidate replacement word and the probability score for the candidate replacement string containing the candidate replacement word, and outputs one of the candidate replacement words based on the final scores. 11. The system of claim 9 , wherein the probability scores are based on a likelihood of the words of the candidate replacement string appearing together. | 0.862162 |
9,971,774 | 23 | 55 | 23. A non-transitory computer readable storage medium storing one or more programs, the one or more programs comprising instructions, which when executed by one or more processors of an electronic device, cause the device to: provide a plurality of media items wherein at least some of the media items are each associated with a respective tag comprising at least one of a time tag, a date tag, or a geo-code tag; provide a natural language text string corresponding to a search query for one or more media items, wherein the search query includes one or more query terms; identify, based on the search query, a first media item of the plurality of media items, wherein the media item is associated with user-generated information and wherein the user-generated information matches a query term of the one or more query terms; compare the respective tags of the identified first media item to the respective tags of one or more other media items of the plurality of media items to identify a second media item, wherein the respective tags of the identified first media item are not generated based on the search query; and facilitate a presentation of the first media item and the second media item to a user. | 23. A non-transitory computer readable storage medium storing one or more programs, the one or more programs comprising instructions, which when executed by one or more processors of an electronic device, cause the device to: provide a plurality of media items wherein at least some of the media items are each associated with a respective tag comprising at least one of a time tag, a date tag, or a geo-code tag; provide a natural language text string corresponding to a search query for one or more media items, wherein the search query includes one or more query terms; identify, based on the search query, a first media item of the plurality of media items, wherein the media item is associated with user-generated information and wherein the user-generated information matches a query term of the one or more query terms; compare the respective tags of the identified first media item to the respective tags of one or more other media items of the plurality of media items to identify a second media item, wherein the respective tags of the identified first media item are not generated based on the search query; and facilitate a presentation of the first media item and the second media item to a user. 55. The non-transitory computer readable storage medium of claim 23 , wherein the tags are metadata stored with the plurality of media items. | 0.765781 |
8,253,580 | 10 | 11 | 10. The method of claim 6 , wherein the at least one criterion is a correlation between the term being entered and the past terms that have already been entered. | 10. The method of claim 6 , wherein the at least one criterion is a correlation between the term being entered and the past terms that have already been entered. 11. The method of claim 10 , wherein the at least one suggested term is a plurality of suggested terms, the method further comprising indicating a strength of the correlation by displaying each of the plurality of suggested terms in respective colors indicative of the respective correlation strengths. | 0.907871 |
9,326,116 | 17 | 19 | 17. An electronic book reading device comprising: a pause position manager configured to: receive identification of a current user reading position within an electronic text of an electronic book for a current reading session; and determine candidate pause positions within the electronic text of the electronic book based on the current user reading position and from among a portion of the electronic text extending from the current user reading position and another reading position following the current user reading position; select a suggested pause position from the determined candidate pause positions based on an available reading time and reading speed associated with a user profile of the current user for the current reading session; and a user interface configured to present the suggested pause position to indicate where to pause in reading the electronic text of the electronic book for the current reading session. | 17. An electronic book reading device comprising: a pause position manager configured to: receive identification of a current user reading position within an electronic text of an electronic book for a current reading session; and determine candidate pause positions within the electronic text of the electronic book based on the current user reading position and from among a portion of the electronic text extending from the current user reading position and another reading position following the current user reading position; select a suggested pause position from the determined candidate pause positions based on an available reading time and reading speed associated with a user profile of the current user for the current reading session; and a user interface configured to present the suggested pause position to indicate where to pause in reading the electronic text of the electronic book for the current reading session. 19. The electronic device of claim 17 , wherein the electronic text of the electronic book comprises metadata including the candidate pause positions, and wherein the pause position manager is configured to extract the candidate pause positions from the metadata of the electronic text of the electronic book. | 0.626812 |
Subsets and Splits