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9,710,449 | 1 | 8 | 1. One or more computer storage media storing computer-useable instructions that, when used by one or more computing devices, cause the one or more computing devices to perform operations to automatically generate a promotional message for a company in response to a post by a user on a competitor's webpage, the operations comprising: employing sentiment analysis to determine a user sentiment in the post and to identify a feature of a product or service of the competitor discussed in the post as a subject of the user sentiment; automatically generating the promotional message promoting the product or service of the company by: retrieving, from a promotional content data store, information tagged with metadata corresponding with the feature of the product or service identified as the subject of the user sentiment, the information describing a feature of a product or service of the company corresponding to the feature of the product or service of the competitor, and assembling content of the promotional message from the information retrieved from the promotional content data store; and electronically communicating the promotional message for presentation to the user on a user device in response to the post. | 1. One or more computer storage media storing computer-useable instructions that, when used by one or more computing devices, cause the one or more computing devices to perform operations to automatically generate a promotional message for a company in response to a post by a user on a competitor's webpage, the operations comprising: employing sentiment analysis to determine a user sentiment in the post and to identify a feature of a product or service of the competitor discussed in the post as a subject of the user sentiment; automatically generating the promotional message promoting the product or service of the company by: retrieving, from a promotional content data store, information tagged with metadata corresponding with the feature of the product or service identified as the subject of the user sentiment, the information describing a feature of a product or service of the company corresponding to the feature of the product or service of the competitor, and assembling content of the promotional message from the information retrieved from the promotional content data store; and electronically communicating the promotional message for presentation to the user on a user device in response to the post. 8. The one or more computer storage media of claim 1 , wherein automatically generating the promotional message promoting the product or service of the company by assembling the content of the promotional message from the information retrieved from the promotional content data store comprises employing natural language processing and/or spoken language understanding to generate the promotional message from the information. | 0.522422 |
8,073,741 | 1 | 3 | 1. A method of locating a relevant product via a computer network, the method comprising: receiving at a client computer a search topic from a user; receiving at the client computer one or more attributes associated with the topic; assigning a rating to at least one of the attributes with the client computer; with a server, locating at one or more information locations at least two separate instances of the topic; locating, with the server, at least two information fields, each field related to one of the instances of the topic; and with at least one of the client computer and the server: associating content in at least two of the information fields with at least one of the attributes; comparing the content in each of the at least two information fields associated with an attribute against each other; assigning a score to the content of each compared instance of content based on the comparing; prioritizing the attributes; and ranking the located instances of the topic based on the prioritizing and the score of content associated with the topic. | 1. A method of locating a relevant product via a computer network, the method comprising: receiving at a client computer a search topic from a user; receiving at the client computer one or more attributes associated with the topic; assigning a rating to at least one of the attributes with the client computer; with a server, locating at one or more information locations at least two separate instances of the topic; locating, with the server, at least two information fields, each field related to one of the instances of the topic; and with at least one of the client computer and the server: associating content in at least two of the information fields with at least one of the attributes; comparing the content in each of the at least two information fields associated with an attribute against each other; assigning a score to the content of each compared instance of content based on the comparing; prioritizing the attributes; and ranking the located instances of the topic based on the prioritizing and the score of content associated with the topic. 3. The method according to claim 1 , wherein at least one of the attributes comprises a geographical location. | 0.928385 |
6,082,775 | 29 | 35 | 29. A method of verifying a counterfeit-resistant document, the method comprising the steps: applying a molecular code to said document; and spectrographically analyzing said molecular code to detect said molecular code. | 29. A method of verifying a counterfeit-resistant document, the method comprising the steps: applying a molecular code to said document; and spectrographically analyzing said molecular code to detect said molecular code. 35. The method of claim 29, wherein said molecular code is specific to an identifying aspect of said document. | 0.882479 |
5,515,474 | 12 | 13 | 12. The system as recited in claim 11 further comprising: means responsive to an absence of a corresponding audio voice for calculating a weighted average of the data in the first I/O instruction and selecting an audio voice as a closest match having a value closest to the weighted average; and, means for transmitting audio data corresponding to the audio voice which is the closest match to the second type of audio card coupled to the computer system and an expected I/O instruction to the audio application. | 12. The system as recited in claim 11 further comprising: means responsive to an absence of a corresponding audio voice for calculating a weighted average of the data in the first I/O instruction and selecting an audio voice as a closest match having a value closest to the weighted average; and, means for transmitting audio data corresponding to the audio voice which is the closest match to the second type of audio card coupled to the computer system and an expected I/O instruction to the audio application. 13. The system as recited in claim 12 further comprising: means for determining whether a value of a first audio parameter in each selected set corresponding to each audio voice matches a value of the first audio parameter in the first I/O instruction where there is a single value for the first audio parameter for each audio voice; and, means for discarding any audio voice as a contender for the closest match whose first audio parameter value does not match the first audio parameter value of the first plurality of audio parameters I/O instruction. | 0.767256 |
8,380,121 | 17 | 18 | 17. The method of claim 16 , wherein generating said report further comprises providing at least one of said plurality of performance indicators, electronic learning outcome indicator, an identification of at least one of said instructors, an identification of at least one of said groups of students, an identification of said learning content item, an indemnification of said assessment content item, an indication of a score awarded to said student relative to said assessment content item, and an indication of an amount of time spent by said student relative to said learning outcome. | 17. The method of claim 16 , wherein generating said report further comprises providing at least one of said plurality of performance indicators, electronic learning outcome indicator, an identification of at least one of said instructors, an identification of at least one of said groups of students, an identification of said learning content item, an indemnification of said assessment content item, an indication of a score awarded to said student relative to said assessment content item, and an indication of an amount of time spent by said student relative to said learning outcome. 18. The method of claim 17 , wherein said generating said report further comprises aggregating said performance indicator for plurality of students relative to said learning outcome to facilitate identification of deficient course content items associated with said learning outcome. | 0.953864 |
8,655,918 | 1 | 7 | 1. A process of transforming data residing in databases into forms suitable as input to data analysis tools, the process including the steps of defining a business process problem to be solved and identifying data requirements, the improvement of computer implemented method for automatically transforming data for use in data analysis tools used to build predictive models comprising the steps of: specifying by a database administrator database metadata information of data to be transformed, said specification encapsulating said database metadata information; creating by an analyst from said database metadata specification a mining transformation profile comprising a specification of key fields and desired data transformations, said specification being relative to said database metadata information and suitable for use by said data analysis tools to build predictive models; generating executable data transformation code automatically from the encapsulated database metadata information and the mining transformation profile, execution of said data transformation code producing at least one of said desired transformations aggregated relative to at least one of said key fields for input to one of said data analysis tools; and iteratively executing the data transformation code by said analyst to build a predictive model according to said data analysis tool, the model generating an output that provides a solution to the business process problem, the iterative execution by a computer of said data transformation code replacing repeated interactions between the database administrator and the analyst. | 1. A process of transforming data residing in databases into forms suitable as input to data analysis tools, the process including the steps of defining a business process problem to be solved and identifying data requirements, the improvement of computer implemented method for automatically transforming data for use in data analysis tools used to build predictive models comprising the steps of: specifying by a database administrator database metadata information of data to be transformed, said specification encapsulating said database metadata information; creating by an analyst from said database metadata specification a mining transformation profile comprising a specification of key fields and desired data transformations, said specification being relative to said database metadata information and suitable for use by said data analysis tools to build predictive models; generating executable data transformation code automatically from the encapsulated database metadata information and the mining transformation profile, execution of said data transformation code producing at least one of said desired transformations aggregated relative to at least one of said key fields for input to one of said data analysis tools; and iteratively executing the data transformation code by said analyst to build a predictive model according to said data analysis tool, the model generating an output that provides a solution to the business process problem, the iterative execution by a computer of said data transformation code replacing repeated interactions between the database administrator and the analyst. 7. The process of claim 1 wherein said business process problem is to predict a customer's likelihood of making purchases in the future. | 0.884941 |
9,892,725 | 1 | 2 | 1. A method of assigning a confidence level to at least one axiom extracted from a text, comprising: determining a number of accurate words in text data based on a spell check function, wherein the text data are extracted from different sources; dividing a number of accurate words from the text data by a total number of words in the text data; assigning a greater weight to at least one word exceeding a predetermined number of characters as compared to at least one other word below the predetermined number of characters; automatically extracting, using natural language processing, from a knowledge base stored in a computer infrastructure, the at least one axiom, wherein the at least one axiom is associated with at least one word from the text data, and wherein the axiom comprises a computer-parsable definition of a relationship of data to at least one of the words in the text data; assigning a confidence level to the at least one axiom based on a result of the dividing and the assigning, wherein the confidence level is assigned based on an output of a Gaussian function applied to the result of the dividing and the assigning; receiving a query from a user device, wherein the query includes at least one word; matching the at least one word with the at least one axiom using the knowledge base; and providing the at least one axiom from the knowledge base to the user device based on the matching and the assigned confidence level. | 1. A method of assigning a confidence level to at least one axiom extracted from a text, comprising: determining a number of accurate words in text data based on a spell check function, wherein the text data are extracted from different sources; dividing a number of accurate words from the text data by a total number of words in the text data; assigning a greater weight to at least one word exceeding a predetermined number of characters as compared to at least one other word below the predetermined number of characters; automatically extracting, using natural language processing, from a knowledge base stored in a computer infrastructure, the at least one axiom, wherein the at least one axiom is associated with at least one word from the text data, and wherein the axiom comprises a computer-parsable definition of a relationship of data to at least one of the words in the text data; assigning a confidence level to the at least one axiom based on a result of the dividing and the assigning, wherein the confidence level is assigned based on an output of a Gaussian function applied to the result of the dividing and the assigning; receiving a query from a user device, wherein the query includes at least one word; matching the at least one word with the at least one axiom using the knowledge base; and providing the at least one axiom from the knowledge base to the user device based on the matching and the assigned confidence level. 2. The method of claim 1 , further comprising: comparing the text data to the data structure, wherein the data structure comprises a dictionary. | 0.861538 |
8,467,530 | 2 | 3 | 2. The method for secure document transmission of claim 1 , further comprising: associating the encrypted portion with an encryption key; and selectively communicating the encryption key to the selected destination to enable decryption of the hybrid electronic document. | 2. The method for secure document transmission of claim 1 , further comprising: associating the encrypted portion with an encryption key; and selectively communicating the encryption key to the selected destination to enable decryption of the hybrid electronic document. 3. The method for secure document transmission of claim 2 , wherein the step of communicating the hybrid electronic document to a selected destination further comprises: rendering the hybrid electronic document so as to output the hybrid electronic document as a hardcopy document; scanning the hardcopy document to generate facsimile data representative of the hybrid electronic document; and transmitting the facsimile data to the selected destination. | 0.824575 |
9,201,760 | 11 | 12 | 11. The method of claim 1 , the host system having a plurality of servers on which the objects run. | 11. The method of claim 1 , the host system having a plurality of servers on which the objects run. 12. The method of claim 11 , the host system being a multitenant relational database, and the plurality of sever run copies of a database server for the multitenant relational database. | 0.928406 |
8,417,649 | 1 | 2 | 1. A method, performed on a computing device, for providing a seamless conversation service between interacting environments, comprising: using the computing device to perform actions including: facilitating commencement of a conversation between two or more parties over a communication path in a first interacting environment; monitoring a user context associated with the conversation between the two or more parties, wherein the monitoring of user context between the two or more parties comprises extracting user context data describing attributes that are relevant to behavioral needs of the two or more parties; and enabling the two or more parties to seamlessly continue the conversation in a second interacting environment while maintaining a transparency of functionality of the communication path, wherein the enabling of the two or more parties to seamlessly continue the conversation comprises using a plurality of predetermined communication rules and the user context being monitored to decide whether to enable the conversation to continue, wherein the plurality of predetermined communication rules comprise customer specified communication rules and provider specified communication rules. | 1. A method, performed on a computing device, for providing a seamless conversation service between interacting environments, comprising: using the computing device to perform actions including: facilitating commencement of a conversation between two or more parties over a communication path in a first interacting environment; monitoring a user context associated with the conversation between the two or more parties, wherein the monitoring of user context between the two or more parties comprises extracting user context data describing attributes that are relevant to behavioral needs of the two or more parties; and enabling the two or more parties to seamlessly continue the conversation in a second interacting environment while maintaining a transparency of functionality of the communication path, wherein the enabling of the two or more parties to seamlessly continue the conversation comprises using a plurality of predetermined communication rules and the user context being monitored to decide whether to enable the conversation to continue, wherein the plurality of predetermined communication rules comprise customer specified communication rules and provider specified communication rules. 2. The method according to claim 1 , wherein the first and second interacting environments comprise an environment selected from the group consisting of a virtual universe, social network and real world. | 0.878734 |
9,600,825 | 1 | 7 | 1. A method of estimating a probability of re-sharing information, comprising: extracting keywords from a set of documents addressed to a user, said documents being published on social media; weighting the keywords from the set of documents according a metric for the user's interest in the keywords' respective source documents to create an interest model; receiving a new document having one or more keywords; determining a likelihood that the user will re-share the new document on social media using a processor, said likelihood being based on the interest model and the one or more keywords present in the new document, wherein the likelihood comprises a probability defined as: P ( u , m ) = a ( t m ) ( 1 - ∏ j ( 1 - q j ( u ) f j ( m ) ) ) where f j (m) is 1 if the keyword j appeared in a post m and is 0 otherwise, where q j (u) is a weighted value for the keyword j for the user u, and where α(t m ) is an activity function at time t m ; and automatically performing one of addressing a complaint in the new document, issuing a press release, or initiating an advertising campaign, using a processor, responsive to the new document based on the determined likelihood. | 1. A method of estimating a probability of re-sharing information, comprising: extracting keywords from a set of documents addressed to a user, said documents being published on social media; weighting the keywords from the set of documents according a metric for the user's interest in the keywords' respective source documents to create an interest model; receiving a new document having one or more keywords; determining a likelihood that the user will re-share the new document on social media using a processor, said likelihood being based on the interest model and the one or more keywords present in the new document, wherein the likelihood comprises a probability defined as: P ( u , m ) = a ( t m ) ( 1 - ∏ j ( 1 - q j ( u ) f j ( m ) ) ) where f j (m) is 1 if the keyword j appeared in a post m and is 0 otherwise, where q j (u) is a weighted value for the keyword j for the user u, and where α(t m ) is an activity function at time t m ; and automatically performing one of addressing a complaint in the new document, issuing a press release, or initiating an advertising campaign, using a processor, responsive to the new document based on the determined likelihood. 7. The method of claim 1 , embodied as a computer readable program on a non-transitory computer readable storage medium. | 0.905808 |
8,117,024 | 1 | 6 | 1. A method of processing candidate resumes and job specifications to match candidates with job specifications, comprising providing a database of elements, each element expressed in natural language and at least some of which are associated with a corresponding set of synonymous words or phrases, the elements and the synonymous words or phrases each having a corresponding usage counter; a server receiving candidate resumes and job specifications in electronic form and expressed in natural language, such that candidates skills and experiences are expressed in words and phrases; a server analyzing the natural language expression of the candidate resumes and job specifications to extract elements expressed in candidate resumes and job specifications; a server comparing the extracted elements to the database and updating the usage counters corresponding to the extracted elements such that the relative frequency of the words or phrases expressing skills and experiences is tracked; a server for each extracted element, determining which of the extracted element or the corresponding set of synonymous words or phrases has the highest usage and using the word, phrase or element with the highest usage as a common form for the extracted element and; a server matching a set of candidate resumes with a corresponding job specification by comparing the set of elements expressed in common form for the candidate resumes with the set of elements expressed in common form for the job specification. | 1. A method of processing candidate resumes and job specifications to match candidates with job specifications, comprising providing a database of elements, each element expressed in natural language and at least some of which are associated with a corresponding set of synonymous words or phrases, the elements and the synonymous words or phrases each having a corresponding usage counter; a server receiving candidate resumes and job specifications in electronic form and expressed in natural language, such that candidates skills and experiences are expressed in words and phrases; a server analyzing the natural language expression of the candidate resumes and job specifications to extract elements expressed in candidate resumes and job specifications; a server comparing the extracted elements to the database and updating the usage counters corresponding to the extracted elements such that the relative frequency of the words or phrases expressing skills and experiences is tracked; a server for each extracted element, determining which of the extracted element or the corresponding set of synonymous words or phrases has the highest usage and using the word, phrase or element with the highest usage as a common form for the extracted element and; a server matching a set of candidate resumes with a corresponding job specification by comparing the set of elements expressed in common form for the candidate resumes with the set of elements expressed in common form for the job specification. 6. The method of claim 1 wherein the elements include products used, tools used, industries, education level attained, role or job title, willingness to travel, or security clearance. | 0.725225 |
7,496,834 | 9 | 13 | 9. A method implemented by an apparatus for updating a previously supplied electronic document related to a schedule of broadcasting a plurality of television broadcast programs in a program broadcasting system, wherein the previously supplied electronic document is stored in a client of the program broadcasting system and has a hierarchical structure based on a prescribed syntax, the hierarchical structure including an upper fragment and a plurality of lower fragments located below the upper fragment in the hierarchical structure to describe, for each of the television broadcast programs, a program identifier, a title, broadcast information and corresponding program content information, the method comprising: requesting by the client an updated version for said previously supplied electronic document from a provider in the program broadcasting system; in response to the request, receiving from the provider at the client an update document for updating the previously supplied electronic document, the update document having a structure based on the prescribed syntax and including the upper fragment and an invalid element which indicates an invalid fragment as one of the lower fragments of the previously supplied electronic document, wherein said invalid fragment is related to one of the television broadcast programs scheduled for broadcast in the program broadcasting system; and deleting said invalid fragment from the previously supplied electronic document at said client as indicated by the invalid element in the update document supplied from said provider. | 9. A method implemented by an apparatus for updating a previously supplied electronic document related to a schedule of broadcasting a plurality of television broadcast programs in a program broadcasting system, wherein the previously supplied electronic document is stored in a client of the program broadcasting system and has a hierarchical structure based on a prescribed syntax, the hierarchical structure including an upper fragment and a plurality of lower fragments located below the upper fragment in the hierarchical structure to describe, for each of the television broadcast programs, a program identifier, a title, broadcast information and corresponding program content information, the method comprising: requesting by the client an updated version for said previously supplied electronic document from a provider in the program broadcasting system; in response to the request, receiving from the provider at the client an update document for updating the previously supplied electronic document, the update document having a structure based on the prescribed syntax and including the upper fragment and an invalid element which indicates an invalid fragment as one of the lower fragments of the previously supplied electronic document, wherein said invalid fragment is related to one of the television broadcast programs scheduled for broadcast in the program broadcasting system; and deleting said invalid fragment from the previously supplied electronic document at said client as indicated by the invalid element in the update document supplied from said provider. 13. The method of claim 9 , wherein said invalid fragment is indicated to be invalid by an invalid attribute. | 0.800366 |
8,792,714 | 1 | 4 | 1. A method, comprising: automatically identifying, by a processor, a region of a digital image containing first pixels, each situated on a positive horizontal gradient, and second pixels in proximity to the first pixels, each situated on a negative horizontal gradient; calculating a distribution of intensities of a color channel for the pixels in the region; analyzing the distribution in order to detect whether the region contains anti-aliased text; wherein analyzing the distribution comprises creating a histogram presenting a distribution of intensities of the color channel for pixels in the region, identifying a number of bins in the histogram, identifying a number of intensities in each bin, and identifying an intensity associated with a bin containing a highest number of pixels; and wherein the region contains anti-aliased text upon detecting that the identified number of bins and the identified number of intensities in each bin are within specified ranges, and the bin containing the highest number of pixels comprises the bin having either highest or lowest intensity. | 1. A method, comprising: automatically identifying, by a processor, a region of a digital image containing first pixels, each situated on a positive horizontal gradient, and second pixels in proximity to the first pixels, each situated on a negative horizontal gradient; calculating a distribution of intensities of a color channel for the pixels in the region; analyzing the distribution in order to detect whether the region contains anti-aliased text; wherein analyzing the distribution comprises creating a histogram presenting a distribution of intensities of the color channel for pixels in the region, identifying a number of bins in the histogram, identifying a number of intensities in each bin, and identifying an intensity associated with a bin containing a highest number of pixels; and wherein the region contains anti-aliased text upon detecting that the identified number of bins and the identified number of intensities in each bin are within specified ranges, and the bin containing the highest number of pixels comprises the bin having either highest or lowest intensity. 4. The method according to claim 1 , wherein the color channel is selected from a list consisting of a red channel, a blue channel and a green channel. | 0.88438 |
7,627,551 | 1 | 7 | 1. A computer implemented method for using case-based reasoning (CBR) information retrieval processes, the method comprising: accessing a data model including symptom attributes and solution attributes; receiving a query from a requestor specifying one or more values for one or more of the symptom attributes; executing the query including searching a database of archive records that are not structurted to facilitate CBR for the specified symptom attribute values and receiving a subset of the archive records that include the specified values; determining values associated with one or more of the solution attributes for each of the records in the subset; and creating a temporary case record for each of the records in the subset, each of the temporary case records comprising a pointer to the corresponding record in the subset and a heading section including the symptom attributes, the specified symptom attribute values, the solution attributes, and the solution attribute values associated with the corresponding record in the subset, creating a temporary case base from archive records in real time in response to the values specified in the query. | 1. A computer implemented method for using case-based reasoning (CBR) information retrieval processes, the method comprising: accessing a data model including symptom attributes and solution attributes; receiving a query from a requestor specifying one or more values for one or more of the symptom attributes; executing the query including searching a database of archive records that are not structurted to facilitate CBR for the specified symptom attribute values and receiving a subset of the archive records that include the specified values; determining values associated with one or more of the solution attributes for each of the records in the subset; and creating a temporary case record for each of the records in the subset, each of the temporary case records comprising a pointer to the corresponding record in the subset and a heading section including the symptom attributes, the specified symptom attribute values, the solution attributes, and the solution attribute values associated with the corresponding record in the subset, creating a temporary case base from archive records in real time in response to the values specified in the query. 7. The method of claim 1 wherein the searching the database of archive records includes searching free form text for the specified symptom attribute values. | 0.793103 |
9,411,803 | 9 | 10 | 9. A method comprising: determining, using at least one processor, keywords that are likely to appear in natural language queries, the determining of the keywords based on source code text of program modules executable to obtain data from a data structure in response to the natural language queries; associating, using the at least one processor, each determined keyword with a program module of the program modules; changing, using the at least one processor, an association between a determined keyword and a program module, in response to determining that changing the association is more likely to trigger an accurate response to a natural language query of the natural language queries; determining, using the at least one processor, whether at least one determined keyword of the determined keywords appears in a received natural language query; generating, using the at least one processor, a response to the received natural language query with data produced by each respective program module, of the program modules, that is associated with the at least one determined keyword appearing in the received natural language query; and ranking, using the at least one processor, the data returned by each respective program module associated with the at least one determined keyword based on a probability that the data returned is a correct response to the received natural language query. | 9. A method comprising: determining, using at least one processor, keywords that are likely to appear in natural language queries, the determining of the keywords based on source code text of program modules executable to obtain data from a data structure in response to the natural language queries; associating, using the at least one processor, each determined keyword with a program module of the program modules; changing, using the at least one processor, an association between a determined keyword and a program module, in response to determining that changing the association is more likely to trigger an accurate response to a natural language query of the natural language queries; determining, using the at least one processor, whether at least one determined keyword of the determined keywords appears in a received natural language query; generating, using the at least one processor, a response to the received natural language query with data produced by each respective program module, of the program modules, that is associated with the at least one determined keyword appearing in the received natural language query; and ranking, using the at least one processor, the data returned by each respective program module associated with the at least one determined keyword based on a probability that the data returned is a correct response to the received natural language query. 10. The method of claim 9 , wherein the probability is at least partially based on a number of associations between each respective program module associated with the at least one determined keyword and determined keywords appearing in the received natural language query. | 0.638298 |
8,346,759 | 1 | 4 | 1. A system in communication, comprising: a processor; and a computer readable storage medium including code executed by the processor to perform operations, the operations comprising: accessing document identifiers for documents, wherein the documents include at least one value that is a member of a set of values; generating a number of posting lists, wherein each posting list is associated with a range of consecutive values within the set of values and includes document identifiers for documents including at least one value within the range of consecutive values associated with the posting list, and wherein each document identifier is associated with one value in the set of values included in the document identified by the document identifier; storing the generated posting lists, wherein the posting lists are used to process a query on a range of values within the set of values; receiving a query on a query range of values within the set of values; determining a minimum number of posting lists associated with consecutive values that together include the query range of values; merging the determined posting lists to form a merged posting list including document identifiers of documents including values within the query range; and returning the document identifiers in the merged posting list. | 1. A system in communication, comprising: a processor; and a computer readable storage medium including code executed by the processor to perform operations, the operations comprising: accessing document identifiers for documents, wherein the documents include at least one value that is a member of a set of values; generating a number of posting lists, wherein each posting list is associated with a range of consecutive values within the set of values and includes document identifiers for documents including at least one value within the range of consecutive values associated with the posting list, and wherein each document identifier is associated with one value in the set of values included in the document identified by the document identifier; storing the generated posting lists, wherein the posting lists are used to process a query on a range of values within the set of values; receiving a query on a query range of values within the set of values; determining a minimum number of posting lists associated with consecutive values that together include the query range of values; merging the determined posting lists to form a merged posting list including document identifiers of documents including values within the query range; and returning the document identifiers in the merged posting list. 4. The system of claim 1 , wherein determining the minimum number of posting lists comprises determining a minimum number of posting lists including values outside of the query range of values that are filtered before merging the posting lists. | 0.894555 |
9,875,297 | 4 | 6 | 4. The method of claim 1 , further comprising determining the at least one task associated with the task suggestion. | 4. The method of claim 1 , further comprising determining the at least one task associated with the task suggestion. 6. The method of claim 4 , wherein determining the at least one task comprises determining the at least one task based on user data associated with the user. | 0.955245 |
9,646,081 | 1 | 8 | 1. A computer implemented method for providing information related to a task in a case management system configured to process a plurality of cases, the computer implemented method comprising: identifying among the plurality of cases, by a server, a plurality of case clusters, wherein each of the plurality of case clusters is associated with a case similarity factor shared by at least two cases of the plurality of cases, and the case similarity factor is related to at least one of geographical case specific parameters and contextual case specific parameters; for a case cluster of the plurality of case clusters, identifying, by the server, a plurality of task clusters, wherein each of the plurality of task clusters is associated with a task similarity factor shared by at least two tasks of the task cluster, and tasks of the plurality of task clusters are performed on cases of the case cluster, and wherein for the case cluster of the plurality of case clusters, the task similarity factor is related to the case similarity factor and task specific parameters and the identifying the plurality of task clusters comprises: based on the task similarity factor, using task metadata, case metadata, and semantic entities to categorize the tasks into the plurality of task clusters, wherein the semantic entities are extracted from case documents used in performing the tasks; analyzing, by the server, reports and documents used to perform the at least two tasks of the task cluster sharing the task similarity factor; and when performing a task sharing the task similarity factor with the at least two tasks, providing, by the server, at least one report based on the reports and at least one summary based on the documents. | 1. A computer implemented method for providing information related to a task in a case management system configured to process a plurality of cases, the computer implemented method comprising: identifying among the plurality of cases, by a server, a plurality of case clusters, wherein each of the plurality of case clusters is associated with a case similarity factor shared by at least two cases of the plurality of cases, and the case similarity factor is related to at least one of geographical case specific parameters and contextual case specific parameters; for a case cluster of the plurality of case clusters, identifying, by the server, a plurality of task clusters, wherein each of the plurality of task clusters is associated with a task similarity factor shared by at least two tasks of the task cluster, and tasks of the plurality of task clusters are performed on cases of the case cluster, and wherein for the case cluster of the plurality of case clusters, the task similarity factor is related to the case similarity factor and task specific parameters and the identifying the plurality of task clusters comprises: based on the task similarity factor, using task metadata, case metadata, and semantic entities to categorize the tasks into the plurality of task clusters, wherein the semantic entities are extracted from case documents used in performing the tasks; analyzing, by the server, reports and documents used to perform the at least two tasks of the task cluster sharing the task similarity factor; and when performing a task sharing the task similarity factor with the at least two tasks, providing, by the server, at least one report based on the reports and at least one summary based on the documents. 8. The method of claim 1 , wherein the at least one summary is generated by applying a document summarization algorithm to searches conducted inside the documents, a tracking of document review, and semantic entities extracted from the documents. | 0.85461 |
9,397,972 | 1 | 3 | 1. A machine implemented method of communicating, comprising: (i) composing an electronic message, via a first device having a processing unit and program code stored on a storage device of said first device; (ii) selecting a well-known animation character, via the first device; (iii) transmitting the electronic message, via the first device; (iv) transmitting the well-known animation character, via the first device; (v) receiving the electronic message, via a server having a processing unit and program code stored on a storage device of said server; (vi) receiving the well-known animation character, via the server; (vii) converting the electronic message into speech using one of synthesized voice of the well-known animation character and actual voice of the well-known animation character, via the server; (viii) generating moving images of the well-known animation character, via the server; (ix) transmitting the speech, via the server; (x) transmitting the moving images, via the server; (xi) receiving the speech, via a second device having a processing unit and program code stored on a storage device of said second device; (xii) receiving the moving images, via the second device; (xiii) outputting the speech, via the second device; and (xiv) displaying the moving images, via the second device. | 1. A machine implemented method of communicating, comprising: (i) composing an electronic message, via a first device having a processing unit and program code stored on a storage device of said first device; (ii) selecting a well-known animation character, via the first device; (iii) transmitting the electronic message, via the first device; (iv) transmitting the well-known animation character, via the first device; (v) receiving the electronic message, via a server having a processing unit and program code stored on a storage device of said server; (vi) receiving the well-known animation character, via the server; (vii) converting the electronic message into speech using one of synthesized voice of the well-known animation character and actual voice of the well-known animation character, via the server; (viii) generating moving images of the well-known animation character, via the server; (ix) transmitting the speech, via the server; (x) transmitting the moving images, via the server; (xi) receiving the speech, via a second device having a processing unit and program code stored on a storage device of said second device; (xii) receiving the moving images, via the second device; (xiii) outputting the speech, via the second device; and (xiv) displaying the moving images, via the second device. 3. The method of claim 1 , further comprising: (xv) selecting a type of animation, via the first device; and wherein the step of generating moving images of the well-known animation character comprises generating moving images of the well-known animation character according to the type of animation. | 0.501661 |
8,886,676 | 13 | 21 | 13. A non-transitory machine readable medium storing a program which when executed by at least one processing unit analyzes a document comprising a plurality of primitive elements, the program comprising sets of instructions for: identifying different sets of lists for different columns of the document, each column ordered within the document based on a reading order; identifying a first list in a first column of the document that has an open end state; identifying a second list, in a second column of the document subsequent to the first column in the reading order, that has an open start state; determining that the first list in the first column continues as the second list in the second column of the document; and storing the first list and the second list as a single list structure associated with the document. | 13. A non-transitory machine readable medium storing a program which when executed by at least one processing unit analyzes a document comprising a plurality of primitive elements, the program comprising sets of instructions for: identifying different sets of lists for different columns of the document, each column ordered within the document based on a reading order; identifying a first list in a first column of the document that has an open end state; identifying a second list, in a second column of the document subsequent to the first column in the reading order, that has an open start state; determining that the first list in the first column continues as the second list in the second column of the document; and storing the first list and the second list as a single list structure associated with the document. 21. The non-transitory machine readable medium of claim 13 , wherein the program further comprises a set of instructions for determining that a plurality of lists in the first column continue as a second plurality of lists in the second column with each list in the second plurality matched to a different list in the first plurality such that a set of all matched list levels in the second plurality are a monotonically increasing function of list levels to which they are matched in the first plurality. | 0.6682 |
9,973,523 | 7 | 12 | 7. A non-transitory computer-readable storage medium storing computer-executable instructions, which, when executed on a processor, performs an operation for processing streams of data of one or more networked computer systems, the computer-executable instruction comprising instructions to: receive at least one ordered stream of normalized vectors corresponding to information security data obtained from one or more sensors monitoring a computer network; process, via a neuro-linguistic model, the at least one ordered stream of normalized vectors, the neuro-linguistic model including a plurality of letters, a dictionary of words, and a plurality of phrases; generate, via the neuro-linguistic model, an ordered sequence of letters based on the at least one ordered stream of normalized vectors, an ordered stream of words based on the ordered sequence of letters, and at least one phrase based on the ordered stream of words; dynamically update the plurality of letters, the dictionary of words, and the plurality of phrases based on the generated ordered sequence of letters, the ordered stream of words, and the at least one phrase; evaluate at least one of the updated plurality of letters, dictionary of words, and plurality of phrases to determine an unusualness score; and publish an alert based on the unusualness score, the alert indicative of malicious activity. | 7. A non-transitory computer-readable storage medium storing computer-executable instructions, which, when executed on a processor, performs an operation for processing streams of data of one or more networked computer systems, the computer-executable instruction comprising instructions to: receive at least one ordered stream of normalized vectors corresponding to information security data obtained from one or more sensors monitoring a computer network; process, via a neuro-linguistic model, the at least one ordered stream of normalized vectors, the neuro-linguistic model including a plurality of letters, a dictionary of words, and a plurality of phrases; generate, via the neuro-linguistic model, an ordered sequence of letters based on the at least one ordered stream of normalized vectors, an ordered stream of words based on the ordered sequence of letters, and at least one phrase based on the ordered stream of words; dynamically update the plurality of letters, the dictionary of words, and the plurality of phrases based on the generated ordered sequence of letters, the ordered stream of words, and the at least one phrase; evaluate at least one of the updated plurality of letters, dictionary of words, and plurality of phrases to determine an unusualness score; and publish an alert based on the unusualness score, the alert indicative of malicious activity. 12. The non-transitory computer-readable storage medium of claim 7 , wherein building the dictionary comprises building a dictionary of words up to a maximum length of letters. | 0.811159 |
9,710,730 | 17 | 19 | 17. A method of automatic medical image registration comprising: receiving a first medical image and a second medical image, the first medical image and the second medical image being of objects and with at least part of one object being common to the first medical image and the second medical image; for each of the first and second medical images, computing a probability map comprising, for each image element, a probability that the image element is of a specified object; wherein computing the probability map comprises, for at least one specified object, computing a posterior distribution of the location of the specified object in each of the first and second medical images by using a regression forest comprising a plurality of regression trees each having been trained to predict a location of the specified object; finding a mapping to register the first and second medical images by optimizing an energy function which is a function of the intensities of the first and second medical images and also of the probability maps, the energy function comprising: a summation of a term related to a Kullback-Leibler divergence; and a summation of a term related to a marginal entropy of the first medical image and a term related to a marginal entropy of the second medical image, less a term related to a joint entropy of the first and second medical images. | 17. A method of automatic medical image registration comprising: receiving a first medical image and a second medical image, the first medical image and the second medical image being of objects and with at least part of one object being common to the first medical image and the second medical image; for each of the first and second medical images, computing a probability map comprising, for each image element, a probability that the image element is of a specified object; wherein computing the probability map comprises, for at least one specified object, computing a posterior distribution of the location of the specified object in each of the first and second medical images by using a regression forest comprising a plurality of regression trees each having been trained to predict a location of the specified object; finding a mapping to register the first and second medical images by optimizing an energy function which is a function of the intensities of the first and second medical images and also of the probability maps, the energy function comprising: a summation of a term related to a Kullback-Leibler divergence; and a summation of a term related to a marginal entropy of the first medical image and a term related to a marginal entropy of the second medical image, less a term related to a joint entropy of the first and second medical images. 19. The method as claimed in claim 17 , wherein the first medical image and the second medical image are of different modalities. | 0.877143 |
9,262,403 | 13 | 20 | 13. A system for managing translation of content, the system comprising: a memory; a dictionary generation module stored in the memory and executable by a processor to extract auto-suggest dictionary data comprising source sentence sub-segments and corresponding target sentence sub-segments from stored translation data including source sentence segments and corresponding translated target sentence segments; a translation module to display a plurality of predictive translations to a human translator, each predictive translation received as a target sentence sub-segment from the auto-suggest dictionary data based on correspondence between data input by the human translator and at least a portion of the received target sentence sub-segment; a ranking module to rank the plurality of displayed predictive translations; an input/output module to receive a selection from the human translator of a predictive translation from the plurality of ranked predictive translations; and a package management module stored in the memory and executable by the processor to: generate a package including content to be translated, the extracted auto-suggest dictionary data which corresponds to the source language and target language for the translation job to be performed, parameters for translation in the form of metadata, and placeable identification and conversion data, provide the generated package to the translation module, and update the auto-suggest dictionary data in the package based on the received selection. | 13. A system for managing translation of content, the system comprising: a memory; a dictionary generation module stored in the memory and executable by a processor to extract auto-suggest dictionary data comprising source sentence sub-segments and corresponding target sentence sub-segments from stored translation data including source sentence segments and corresponding translated target sentence segments; a translation module to display a plurality of predictive translations to a human translator, each predictive translation received as a target sentence sub-segment from the auto-suggest dictionary data based on correspondence between data input by the human translator and at least a portion of the received target sentence sub-segment; a ranking module to rank the plurality of displayed predictive translations; an input/output module to receive a selection from the human translator of a predictive translation from the plurality of ranked predictive translations; and a package management module stored in the memory and executable by the processor to: generate a package including content to be translated, the extracted auto-suggest dictionary data which corresponds to the source language and target language for the translation job to be performed, parameters for translation in the form of metadata, and placeable identification and conversion data, provide the generated package to the translation module, and update the auto-suggest dictionary data in the package based on the received selection. 20. The system of claim 13 , wherein the plurality of predictive translations are ranked based on ranking factors, the ranking factors comprising: a likelihood of selection by the human translator; an amount of words in the source sub-segments to which words in the respective predictive translations correspond; and a length of one of the predictive translations. | 0.776687 |
7,720,857 | 12 | 18 | 12. A computer for providing a visualization graph, the computer comprising: a storage medium having recorded therein processor readable code processable to provide a visualization graph; a database for storing data corresponding to a plurality of entities having a particular type, wherein a semantic net includes the entities and wherein the entities are linked to each other by a plurality of relations; a query interface adapted, so that in response to a query with respect to an entity selected from the plurality of entities, a visualization graph is provided representing the results of the query, wherein the code comprises an allocator code processable to: allocate a first of the entities, representing results of the query, displayed because it is a focus entity defined by the user or the query; allocate a second of the entities, representing the results of the query, displayed because it is directly related to the focus entity, wherein a third of the entities, representing the results of the query, is not displayed because it is indirectly related to the focus entity; allocate a fourth of the entities, representing the results of the query, that is indirectly related to the focus entity, wherein context information is used to determine that the fourth entity be displayed; allocate a first set of the entities to a predetermined sector of the graph depending on an entity type, the predetermined sectors being subdivisions of a screen area with boundaries; allocate a second set of the entities to a predetermined sub-sector being a subdivision inside the boundaries of the predetermined sector depending on an entity sub-type, the sub-sectors also having boundaries, wherein a size of the predetermined sub-sector depends on a number of the second set of entities allocated to the predetermined sub-sector, wherein the predetermined sector has a size that depends on a number of the first set of the entities allocated to the predetermined sector and the number of the second set of the entities allocated to the predetermined sub-sector; and provide an invisible attractor in the predetermined sector, which attracts a subset of the entities to the predetermined sector depending on the entity type of the subset of entities, wherein the invisible attractor remains invisible during user interaction with the visualization graph. | 12. A computer for providing a visualization graph, the computer comprising: a storage medium having recorded therein processor readable code processable to provide a visualization graph; a database for storing data corresponding to a plurality of entities having a particular type, wherein a semantic net includes the entities and wherein the entities are linked to each other by a plurality of relations; a query interface adapted, so that in response to a query with respect to an entity selected from the plurality of entities, a visualization graph is provided representing the results of the query, wherein the code comprises an allocator code processable to: allocate a first of the entities, representing results of the query, displayed because it is a focus entity defined by the user or the query; allocate a second of the entities, representing the results of the query, displayed because it is directly related to the focus entity, wherein a third of the entities, representing the results of the query, is not displayed because it is indirectly related to the focus entity; allocate a fourth of the entities, representing the results of the query, that is indirectly related to the focus entity, wherein context information is used to determine that the fourth entity be displayed; allocate a first set of the entities to a predetermined sector of the graph depending on an entity type, the predetermined sectors being subdivisions of a screen area with boundaries; allocate a second set of the entities to a predetermined sub-sector being a subdivision inside the boundaries of the predetermined sector depending on an entity sub-type, the sub-sectors also having boundaries, wherein a size of the predetermined sub-sector depends on a number of the second set of entities allocated to the predetermined sub-sector, wherein the predetermined sector has a size that depends on a number of the first set of the entities allocated to the predetermined sector and the number of the second set of the entities allocated to the predetermined sub-sector; and provide an invisible attractor in the predetermined sector, which attracts a subset of the entities to the predetermined sector depending on the entity type of the subset of entities, wherein the invisible attractor remains invisible during user interaction with the visualization graph. 18. The computer according to claim 12 , wherein the code further comprises representation code processable to represent a plurality of entities having a common relation as a node on the visualization graph, and in response to a predetermined stimulus causes the entities comprised at the node to be displayed, and in response to a further predetermined stimulus causes the graph to restructure so that the entities displayed are replaced by the node. | 0.501106 |
9,483,240 | 16 | 20 | 16. A non-transitory computer-readable storage medium comprising instructions that, when executed, cause one or more processors of a computing device to: identify, based at least in part on parsing source code of a layout the that defines a graphical user interface, a plurality of data binding expressions, wherein each of the plurality of data binding expressions defines a respective data binding between a user interface element of the graphical user interface and a model object; determine, based at least in part on the plurality of data binding expressions, one or more dependencies between each of the plurality of data binding expressions; generate, based at least in part on the one or more dependencies, additional source code for updating at least one respective data binding defined by the plurality of data binding expressions in response to a change to at least one property of the model object; and generate, an application comprising machine-executable code that is based at least in part on the source code of the layout file, the model object, and the additional source code. | 16. A non-transitory computer-readable storage medium comprising instructions that, when executed, cause one or more processors of a computing device to: identify, based at least in part on parsing source code of a layout the that defines a graphical user interface, a plurality of data binding expressions, wherein each of the plurality of data binding expressions defines a respective data binding between a user interface element of the graphical user interface and a model object; determine, based at least in part on the plurality of data binding expressions, one or more dependencies between each of the plurality of data binding expressions; generate, based at least in part on the one or more dependencies, additional source code for updating at least one respective data binding defined by the plurality of data binding expressions in response to a change to at least one property of the model object; and generate, an application comprising machine-executable code that is based at least in part on the source code of the layout file, the model object, and the additional source code. 20. The computer-readable storage medium of claim 16 , comprising additional instructions that, when executed, cause the one or more processors of the computing device to further generate the additional source code for evaluating, based on the flag, each of the one or more dependencies between each of the plurality of data biding expressions by at least masking, with the flag, a respective bitmap associated with a particular binding expression from the plurality of binding expressions to determine whether to evaluate the particular binding expression, the respective bitmap defining which of the one or more dependencies is associated with that particular binding expression. | 0.598467 |
8,694,960 | 1 | 8 | 1. A computer-implemented method for displaying a user interface component according to an implementation language independent description of the user interface component, the method comprising: selecting, based on a characteristic of the implementation language independent description, a description parser; receiving the implementation language independent description; determining an implementation language for displaying the user interface component; parsing, by the description parser, the implementation language independent description by: identifying an implementation language independent type, and determining an implementation language dependent type of the user interface component based on the implementation language independent type and the implementation language; identifying a presentation rule corresponding to the implementation language dependent type; selecting, according to the implementation language, a set of instructions for processing the parsed description; processing the parsed description according to the set of instructions in order to create an implementation language dependent specification of the user interface component, wherein the processing comprises including an association of the implementation language dependent type with the presentation rule in the implementation language dependent specification; and displaying the user interface component according to the implementation language dependent specification. | 1. A computer-implemented method for displaying a user interface component according to an implementation language independent description of the user interface component, the method comprising: selecting, based on a characteristic of the implementation language independent description, a description parser; receiving the implementation language independent description; determining an implementation language for displaying the user interface component; parsing, by the description parser, the implementation language independent description by: identifying an implementation language independent type, and determining an implementation language dependent type of the user interface component based on the implementation language independent type and the implementation language; identifying a presentation rule corresponding to the implementation language dependent type; selecting, according to the implementation language, a set of instructions for processing the parsed description; processing the parsed description according to the set of instructions in order to create an implementation language dependent specification of the user interface component, wherein the processing comprises including an association of the implementation language dependent type with the presentation rule in the implementation language dependent specification; and displaying the user interface component according to the implementation language dependent specification. 8. The method of claim 1 , wherein the implementation language independent description includes a user specified presentation attribute of the user interface component, wherein parsing the implementation language independent description further comprises identifying the user specified presentation attribute, and wherein processing the parsed description further comprises including the user specified presentation attribute in the implementation language dependent specification. | 0.662693 |
9,817,819 | 11 | 13 | 11. The method of claim 10 , wherein the priority value is determined based on an impact-metric of the first text string, wherein the impact-metric measures an importance of the first text string. | 11. The method of claim 10 , wherein the priority value is determined based on an impact-metric of the first text string, wherein the impact-metric measures an importance of the first text string. 13. The method of claim 11 , wherein the impact-metric of the first text string is based on an estimate of the number of distinct users for whom a translation of the first text string is to be published, the estimate being based on a sample of a plurality of text strings or their associated translations that have been published to a subset of users. | 0.864059 |
9,275,139 | 18 | 25 | 18. A method to search audio data, comprising: receiving audio data representing speech; receiving a search query related to the audio data; compiling, by use of a processor, the search query into a hierarchy of scored speech recognition sub-searches; searching, by use of an audio search engine operating in an audio domain, the audio data for speech identified by one or more of the sub-searches to produce hits; and combining, by use of a processor, the hits by use of at least one combination function to provide a composite search score of the audio data, wherein at least one of the combination functions comprises an at-least-M-of-N function, wherein the at-least-M-of-N function produces a high score when at least M members found within a set having membership size of N exceed a predetermined threshold value, wherein N is greater than or equal to M, wherein the composite search score may be determined in accordance with the following relationship: L ab ( x ) = 1 1 + ⅇ a ( x - b ) , wherein: x comprises a vector of scores associated with the hits; a and b comprise sensitivity vectors; and L ab (x) comprises the composite search score. | 18. A method to search audio data, comprising: receiving audio data representing speech; receiving a search query related to the audio data; compiling, by use of a processor, the search query into a hierarchy of scored speech recognition sub-searches; searching, by use of an audio search engine operating in an audio domain, the audio data for speech identified by one or more of the sub-searches to produce hits; and combining, by use of a processor, the hits by use of at least one combination function to provide a composite search score of the audio data, wherein at least one of the combination functions comprises an at-least-M-of-N function, wherein the at-least-M-of-N function produces a high score when at least M members found within a set having membership size of N exceed a predetermined threshold value, wherein N is greater than or equal to M, wherein the composite search score may be determined in accordance with the following relationship: L ab ( x ) = 1 1 + ⅇ a ( x - b ) , wherein: x comprises a vector of scores associated with the hits; a and b comprise sensitivity vectors; and L ab (x) comprises the composite search score. 25. The method of claim 18 , wherein the composite search score comprises an attribute with an associated score and or more associated time intervals. | 0.594595 |
10,033,671 | 4 | 6 | 4. The computer program product of claim 1 , wherein the code is further executable by the processor to examine the message for delivery controls. | 4. The computer program product of claim 1 , wherein the code is further executable by the processor to examine the message for delivery controls. 6. The computer program product of claim 4 , wherein to examine the message for delivery controls further comprises to determine whether the broker has permission to publish the message. | 0.943874 |
9,508,354 | 1 | 5 | 1. A method of synchronising a device with an audio signal having encoded pairs of code words embedded separately therein, each pair of code words including an ID code word and a synchronisation code word, the method comprising: receiving the audio signal with the encoded pairs of code words; synchronising the device with the audio signal by detecting: i) an ID code word and a synchronisation code word from one pair of code words; or ii) an ID code word from one pair of code words and a synchronisation code word from another pair of code words; and using a detected ID code word to retrieve timing information relating to an expected time for detected synchronisation code words and determining a difference in time between an expected time for a detected synchronisation code word and an actual time of the detected synchronisation code word and using the determined difference to synchronise the device to the audio signal. | 1. A method of synchronising a device with an audio signal having encoded pairs of code words embedded separately therein, each pair of code words including an ID code word and a synchronisation code word, the method comprising: receiving the audio signal with the encoded pairs of code words; synchronising the device with the audio signal by detecting: i) an ID code word and a synchronisation code word from one pair of code words; or ii) an ID code word from one pair of code words and a synchronisation code word from another pair of code words; and using a detected ID code word to retrieve timing information relating to an expected time for detected synchronisation code words and determining a difference in time between an expected time for a detected synchronisation code word and an actual time of the detected synchronisation code word and using the determined difference to synchronise the device to the audio signal. 5. A method according to claim 1 , comprising using a first decoding technique to decode the encoded code words in the received audio signal before synchronisation and using a second decoding technique to decode the encoded code words after synchronisation. | 0.753831 |
8,892,186 | 1 | 3 | 1. A method for detecting and tracking coronary sinus (CS) catheter electrodes in a fluoroscopic image sequence comprising: initializing a catheter electrode model in a first frame of a fluoroscopic image sequence based on input locations of a plurality of CS catheter electrodes in the first frame, wherein the catheter electrode model in the first frame comprises a plurality of template points corresponding to locations of the CS catheter electrodes in the first frame; and tracking the catheter electrode model in a second frame of the fluoroscopic image sequence by: detecting electrode position candidates in a second frame of the fluoroscopic image sequence using at least one trained electrode detector; generating catheter electrode model candidates in the second frame based on the detected electrode position candidates and the catheter electrode model initialized in the first frame by translating each of the plurality of template points of the catheter electrode model initialized in the first frame to each of the detected electrode position candidates in the second frame; calculating a probability score for each of the catheter electrode model candidates in the second frame; and selecting one of the catheter electrode model candidates in the second frame based on the probability score, wherein the selected catheter electrode model candidate provides locations of the plurality of CS catheter electrodes in the second frame. | 1. A method for detecting and tracking coronary sinus (CS) catheter electrodes in a fluoroscopic image sequence comprising: initializing a catheter electrode model in a first frame of a fluoroscopic image sequence based on input locations of a plurality of CS catheter electrodes in the first frame, wherein the catheter electrode model in the first frame comprises a plurality of template points corresponding to locations of the CS catheter electrodes in the first frame; and tracking the catheter electrode model in a second frame of the fluoroscopic image sequence by: detecting electrode position candidates in a second frame of the fluoroscopic image sequence using at least one trained electrode detector; generating catheter electrode model candidates in the second frame based on the detected electrode position candidates and the catheter electrode model initialized in the first frame by translating each of the plurality of template points of the catheter electrode model initialized in the first frame to each of the detected electrode position candidates in the second frame; calculating a probability score for each of the catheter electrode model candidates in the second frame; and selecting one of the catheter electrode model candidates in the second frame based on the probability score, wherein the selected catheter electrode model candidate provides locations of the plurality of CS catheter electrodes in the second frame. 3. The method of claim 1 , wherein the step of initializing a catheter electrode model in a first frame of a fluoroscopic image sequence based on input locations of a plurality of CS catheter electrodes in the first frame comprises: determining a number of CS catheter electrodes in the first frame; and if the number of CS catheter electrodes in the first frame is greater than a threshold, decomposing the plurality of CS catheter electrodes into multiple parts, and initializing separate catheter electrode models in the first frame for the multiple parts, wherein the catheter electrode model initialized in the first frame comprises the separate catheter electrode models initialized for the multiple parts. | 0.709861 |
9,607,303 | 13 | 20 | 13. One or more non-transitory computer readable media having instructions stored thereon that, when executed by an apparatus, cause the apparatus to: receive a first transmission comprising data from a first content provider and a second transmission comprising data from a second content provider; determine a first context for a first message to be transmitted from the apparatus to a consumer computing device, wherein the first context defines a meaning of first payload data included in the first message; generate a first message, wherein the first message is structured according to: a transport layer defining one or more interaction paradigms for categorizing interactions and defining a plurality of message types, wherein each message type of the plurality of message types includes a set of attributes that comprises at least a message attribute and a transport attribute; a data layer defining one or more data formats, wherein the plurality of message types include first payload data formatted according to at least one of the one or more data formats; and a first domain message layer that defines a first set of the plurality of message types used to generate messages between the consumer computing device and the apparatus for the first context; send the first message to the consumer computing device; determine a second context different from the first context for a second message to be transmitted from the apparatus to the consumer computing device, wherein the second context defines a meaning of second payload data included in the second message; generate a second message, wherein the second message is structured according to the transport layer, the data layer, and a second domain message layer that defines, for the second context, a second set of the plurality of message types different from the first set of the plurality of message types; and send the second message to the consumer computing device, wherein the first domain message layer includes the item type model and a content definition model, wherein the content definition model defines at least one of a field meaning or a field relationship for a field used by the item type model. | 13. One or more non-transitory computer readable media having instructions stored thereon that, when executed by an apparatus, cause the apparatus to: receive a first transmission comprising data from a first content provider and a second transmission comprising data from a second content provider; determine a first context for a first message to be transmitted from the apparatus to a consumer computing device, wherein the first context defines a meaning of first payload data included in the first message; generate a first message, wherein the first message is structured according to: a transport layer defining one or more interaction paradigms for categorizing interactions and defining a plurality of message types, wherein each message type of the plurality of message types includes a set of attributes that comprises at least a message attribute and a transport attribute; a data layer defining one or more data formats, wherein the plurality of message types include first payload data formatted according to at least one of the one or more data formats; and a first domain message layer that defines a first set of the plurality of message types used to generate messages between the consumer computing device and the apparatus for the first context; send the first message to the consumer computing device; determine a second context different from the first context for a second message to be transmitted from the apparatus to the consumer computing device, wherein the second context defines a meaning of second payload data included in the second message; generate a second message, wherein the second message is structured according to the transport layer, the data layer, and a second domain message layer that defines, for the second context, a second set of the plurality of message types different from the first set of the plurality of message types; and send the second message to the consumer computing device, wherein the first domain message layer includes the item type model and a content definition model, wherein the content definition model defines at least one of a field meaning or a field relationship for a field used by the item type model. 20. The non-transitory computer readable media of claim 13 , wherein the apparatus has compressed the payload data by removing an element common to each record of a plurality of records in the payload data. | 0.811009 |
9,684,641 | 6 | 7 | 6. A method comprising: under control of one or more processors configured with executable instructions, receiving a first location associated with a portion of a first version of a content item, the portion of the first version being in a first language; determining a second location associated with a portion of a second version of the content item, the portion of the second version being in a second language, wherein: the second language is different from the first language, and content of the portion of the second version corresponds, at least in part, to content of the portion of the first version; returning the second location; presenting a first amount of the content of the portion of the first version in a first area; presenting a first amount of the content of the portion of the second version in a second area; determining a second amount of the content of the portion of the first version to present within the first area; determining a second amount of the content of the portion of the second version to present based at least in part on associating the second amount of the content of the portion of the second version with the second amount of the content of the portion of the first version; and adjusting a size of the second area based at least in part on the second amount of the content of the portion of the second version. | 6. A method comprising: under control of one or more processors configured with executable instructions, receiving a first location associated with a portion of a first version of a content item, the portion of the first version being in a first language; determining a second location associated with a portion of a second version of the content item, the portion of the second version being in a second language, wherein: the second language is different from the first language, and content of the portion of the second version corresponds, at least in part, to content of the portion of the first version; returning the second location; presenting a first amount of the content of the portion of the first version in a first area; presenting a first amount of the content of the portion of the second version in a second area; determining a second amount of the content of the portion of the first version to present within the first area; determining a second amount of the content of the portion of the second version to present based at least in part on associating the second amount of the content of the portion of the second version with the second amount of the content of the portion of the first version; and adjusting a size of the second area based at least in part on the second amount of the content of the portion of the second version. 7. The method as recited in claim 6 , the determining the second location further comprising accessing mapping information that maps the first location to the second location. | 0.940678 |
8,560,531 | 11 | 12 | 11. The method of claim 1 , wherein the proximity score utilizes a scale having a lower bound and an upper bound denoting a distant match and an exact match 0, respectively, to the user-entered geospatial and temporal search parameters. | 11. The method of claim 1 , wherein the proximity score utilizes a scale having a lower bound and an upper bound denoting a distant match and an exact match 0, respectively, to the user-entered geospatial and temporal search parameters. 12. The method of claim 11 , further comprising: arranging the at least one identified metadata record in descending order by the calculated proximity score, wherein said arranged metadata records create a listing of proximate dataset results, wherein said arranging of the at least one identified metadata record further comprises: and comparing the calculated proximity score of the at least one identified metadata record to the lower bound of the scale. | 0.909791 |
9,367,583 | 10 | 13 | 10. A system for evaluating a performance of a content group via a computer network, comprising: a processor executing on a server and communicatively coupled to a memory element, the processor configured to: receive a request to display performance of a content group of a content provider; access a data structure storing, in the memory element, a plurality of keywords, a quality metric for each keyword, and a number of impressions for each keyword; identify one or more keywords of the plurality of keywords of the data structure corresponding to the content group of the content provider; obtain, for each of the one or more keywords, via the data structure, the quality metric and the number of impressions associated with the content group of the content provider; determine, for the content group, a performance score based on a weighted average of the quality metric and number of impressions of each of the one or more keywords of the plurality of keywords by performing a summation of products of the quality metric and impression count of each of the one or more keywords of the plurality of keywords and dividing the summation by a sum of the impression count of each of the one or more keywords of the plurality of keywords; and transmit, for display on a user device, the performance score. | 10. A system for evaluating a performance of a content group via a computer network, comprising: a processor executing on a server and communicatively coupled to a memory element, the processor configured to: receive a request to display performance of a content group of a content provider; access a data structure storing, in the memory element, a plurality of keywords, a quality metric for each keyword, and a number of impressions for each keyword; identify one or more keywords of the plurality of keywords of the data structure corresponding to the content group of the content provider; obtain, for each of the one or more keywords, via the data structure, the quality metric and the number of impressions associated with the content group of the content provider; determine, for the content group, a performance score based on a weighted average of the quality metric and number of impressions of each of the one or more keywords of the plurality of keywords by performing a summation of products of the quality metric and impression count of each of the one or more keywords of the plurality of keywords and dividing the summation by a sum of the impression count of each of the one or more keywords of the plurality of keywords; and transmit, for display on a user device, the performance score. 13. The system of claim 10 , wherein the processor is further configured to: update, responsive to a time interval, the quality metrics of at least one keyword of the data structure. | 0.820513 |
9,491,207 | 1 | 4 | 1. A method comprising: maintaining a profile for the user at a social networking system including a processor, the profile including one or more information items associated with data describing characteristics of the user and a set of unknown information items not associated with data; obtaining a plurality of questions associated with one or more unknown information items from the set of unknown information items at the social networking system; determining, for each of the plurality of questions associated with the one or more unknown information items, a response probability based at least in part on one or a combination of a format and content of the question, the response probability indicating a likelihood of the social networking system receiving a response to the question when presented; determining a data acquisition value for each of the one or more unknown information items in the set of unknown information items, the data acquisition value of an unknown information item based at least in part on a value to the social networking system of associating data with the unknown information item and the determined response probability; selecting an unknown information item from the one or more unknown information items by the social networking system based at least in part on the data acquisition values; and selecting, by the social networking system, a question associated with the selected unknown information item for presentation to the user based at least in part on the response probabilities of one or more questions associated with the selected unknown information item. | 1. A method comprising: maintaining a profile for the user at a social networking system including a processor, the profile including one or more information items associated with data describing characteristics of the user and a set of unknown information items not associated with data; obtaining a plurality of questions associated with one or more unknown information items from the set of unknown information items at the social networking system; determining, for each of the plurality of questions associated with the one or more unknown information items, a response probability based at least in part on one or a combination of a format and content of the question, the response probability indicating a likelihood of the social networking system receiving a response to the question when presented; determining a data acquisition value for each of the one or more unknown information items in the set of unknown information items, the data acquisition value of an unknown information item based at least in part on a value to the social networking system of associating data with the unknown information item and the determined response probability; selecting an unknown information item from the one or more unknown information items by the social networking system based at least in part on the data acquisition values; and selecting, by the social networking system, a question associated with the selected unknown information item for presentation to the user based at least in part on the response probabilities of one or more questions associated with the selected unknown information item. 4. The method of claim 1 , wherein the format of the question comprises a request for confirmation. | 0.946254 |
9,361,406 | 2 | 14 | 2. A system comprising: one or more computers and one or more storage devices storing instructions that are operable, when executed by the one or more computers, to cause the one or more computers to perform operations comprising: receiving a query prefix from a user; obtaining a reference parameter for the user; identifying one or more likely queries that are likely to co-occur with the reference parameter in user activity sessions; obtaining initial ranking scores for the one or more likely queries; computing, for each likely query of the one or more likely queries, a respective new ranking score including multiplying the initial ranking score for the likely query by a ranking factor associated with the likely query, wherein the ranking factor R is given by: R = P ( x | q ) P ( x ) , wherein P(x|q) is a measure of a likelihood of the likely query x occurring in a user activity session given that the reference parameter q also occurred in a same user activity session, and wherein P(x) is a measure of the likelihood of the likely query x appearing in a user activity session; determining a ranking of the one or more likely queries according to the new ranking scores; and providing the ranking of the one or more likely queries in response to receiving the query prefix. | 2. A system comprising: one or more computers and one or more storage devices storing instructions that are operable, when executed by the one or more computers, to cause the one or more computers to perform operations comprising: receiving a query prefix from a user; obtaining a reference parameter for the user; identifying one or more likely queries that are likely to co-occur with the reference parameter in user activity sessions; obtaining initial ranking scores for the one or more likely queries; computing, for each likely query of the one or more likely queries, a respective new ranking score including multiplying the initial ranking score for the likely query by a ranking factor associated with the likely query, wherein the ranking factor R is given by: R = P ( x | q ) P ( x ) , wherein P(x|q) is a measure of a likelihood of the likely query x occurring in a user activity session given that the reference parameter q also occurred in a same user activity session, and wherein P(x) is a measure of the likelihood of the likely query x appearing in a user activity session; determining a ranking of the one or more likely queries according to the new ranking scores; and providing the ranking of the one or more likely queries in response to receiving the query prefix. 14. The system of claim 2 , wherein obtaining the initial ranking scores of the one or more likely queries comprises obtaining scores in a baseline collection of query completions for the query prefix. | 0.818592 |
9,092,792 | 1 | 7 | 1. A method executing on a server computer comprising: receiving a connection request from a seller application that is customizable by configuration information that includes a hierarchal product category structure for generating a listing for a product for sale, the seller application executing on a client machine; determining that the seller application has not been customized by a current version of the configuration information; transmitting the current version of the configuration information to the seller application, receiving, from the seller application, a product listing request and a configuration confirmation, the configuration confirmation indicating the seller application on the client machine has been configured using the current version of the configuration information to include the hierarchal product category structure; and generating a product listing using the product listing request. | 1. A method executing on a server computer comprising: receiving a connection request from a seller application that is customizable by configuration information that includes a hierarchal product category structure for generating a listing for a product for sale, the seller application executing on a client machine; determining that the seller application has not been customized by a current version of the configuration information; transmitting the current version of the configuration information to the seller application, receiving, from the seller application, a product listing request and a configuration confirmation, the configuration confirmation indicating the seller application on the client machine has been configured using the current version of the configuration information to include the hierarchal product category structure; and generating a product listing using the product listing request. 7. The method of claim 1 , wherein: the transmitting of the configuration information includes transmitting a software module upgrade of the seller application from a network-based facility to the seller application. | 0.796992 |
8,332,225 | 6 | 7 | 6. The method of claim 5 , wherein hosting a TTS web service comprises: receiving a request including text from a remote client to convert text to speech using the custom voice font data; converting the text to speech using the custom voice font data; and providing the speech to the remote client. | 6. The method of claim 5 , wherein hosting a TTS web service comprises: receiving a request including text from a remote client to convert text to speech using the custom voice font data; converting the text to speech using the custom voice font data; and providing the speech to the remote client. 7. The method of claim 6 , further comprising: receiving ratings on the custom voice font data from operators of remote clients; and at least one of: awarding, tracking or collecting resources to and from the operators according to a participation activity. | 0.881129 |
7,516,442 | 1 | 15 | 1. A method for creating language-neutral and corresponding language-specific resource files for a component, the method comprising: obtaining a resource manifest file; retrieving a resource file by accessing the resource manifest file; creating a language-neutral file and a language-specific resource file for the retrieved resource file, the language-specific resource file having a plurality of language-specific resources, the language neutral file and the language-specific resource file being created by reading localizable resource information contained in the resource manifest file, the localizable resource information specifying locations of specific resources to be retrieved during runtime from the language-specific resource file, the locations of the specific resources being mapped to resource identifiers used by applications to identify the specific resources within the language-specific resource file, in the resource manifest file, the resource manifest file further specifying a type of resource to be retrieved, and indicating whether the resource is localizable; creating a checksum data; updating a field in the resource manifest file with the checksum data; and the language-neutral file and language-specific resource file being created by splitting localizable resources identified by the localizable resource information into neutral and localized files, and by creating a language-neutral image and a language-specific image of the retrieved resource file. | 1. A method for creating language-neutral and corresponding language-specific resource files for a component, the method comprising: obtaining a resource manifest file; retrieving a resource file by accessing the resource manifest file; creating a language-neutral file and a language-specific resource file for the retrieved resource file, the language-specific resource file having a plurality of language-specific resources, the language neutral file and the language-specific resource file being created by reading localizable resource information contained in the resource manifest file, the localizable resource information specifying locations of specific resources to be retrieved during runtime from the language-specific resource file, the locations of the specific resources being mapped to resource identifiers used by applications to identify the specific resources within the language-specific resource file, in the resource manifest file, the resource manifest file further specifying a type of resource to be retrieved, and indicating whether the resource is localizable; creating a checksum data; updating a field in the resource manifest file with the checksum data; and the language-neutral file and language-specific resource file being created by splitting localizable resources identified by the localizable resource information into neutral and localized files, and by creating a language-neutral image and a language-specific image of the retrieved resource file. 15. The method of claim 1 , wherein reading the plurality of fields further comprises reading: a fourteenth data field containing data representing a name of the element associated with the user interface resource type of the fourth data field; a fifteenth data field containing data representing an identifier of the element associated with the user interface resource type of the fourth data field; a sixteenth data field containing data representing a name of a resource item; and a seventeenth data field containing data representing an identifier of the resource item. | 0.561927 |
8,509,826 | 4 | 5 | 4. In a mobile device having a graphical user interface (GUI) comprising a display and a selection device, a method comprising: rendering a user-generated text-message component on a GUI, wherein the text-message component is drafted with a text-messaging application of the mobile device by a user of a mobile device, and wherein the text-message component comprises a term in the memory of the mobile device that is used to automatically correlate the text-message component with a biosensor-data type; automatically rendering a biosensor-data icon on the GUI; automatically determining the biosensor-data type relationally linked with the user-generated text-message component, wherein the use of the biosensor-data type is automatically determined by the text-message component; retrieving a biosensor-data measurement associated with the text-message component, wherein the biosensor-data measurement is comprised of the biosensor-data type relationally linked with the user-generated text-message component, wherein the biosensor-data provides information of an attribute of an environment of a mobile device, and wherein the biosensor-data measurement is retrieved from the memory of the mobile device; and transforming the biosensor-data icon according to the biosensor data measurement. | 4. In a mobile device having a graphical user interface (GUI) comprising a display and a selection device, a method comprising: rendering a user-generated text-message component on a GUI, wherein the text-message component is drafted with a text-messaging application of the mobile device by a user of a mobile device, and wherein the text-message component comprises a term in the memory of the mobile device that is used to automatically correlate the text-message component with a biosensor-data type; automatically rendering a biosensor-data icon on the GUI; automatically determining the biosensor-data type relationally linked with the user-generated text-message component, wherein the use of the biosensor-data type is automatically determined by the text-message component; retrieving a biosensor-data measurement associated with the text-message component, wherein the biosensor-data measurement is comprised of the biosensor-data type relationally linked with the user-generated text-message component, wherein the biosensor-data provides information of an attribute of an environment of a mobile device, and wherein the biosensor-data measurement is retrieved from the memory of the mobile device; and transforming the biosensor-data icon according to the biosensor data measurement. 5. The method of claim 4 , wherein the sensor comprises a near field communication (NFC) device. | 0.688312 |
10,001,977 | 5 | 6 | 5. The method of claim 1 wherein a group of operations from the plurality of operations is identified where the input data satisfies the one or more constraints on the one or more input arguments of each operation in the group of operations, and at least one operation from the group of operations is presented on the display in a popup window. | 5. The method of claim 1 wherein a group of operations from the plurality of operations is identified where the input data satisfies the one or more constraints on the one or more input arguments of each operation in the group of operations, and at least one operation from the group of operations is presented on the display in a popup window. 6. The method of claim 5 further comprising: presenting a result window on the display, the result window containing a result of the executing the first operation; and maintaining, on the display, the popup window together with the result window. | 0.91661 |
8,290,895 | 11 | 12 | 11. The electronic device of claim 10 , wherein generating the dictionary comprises storing, as language objects of the dictionary, words found in messages associated with the message thread. | 11. The electronic device of claim 10 , wherein generating the dictionary comprises storing, as language objects of the dictionary, words found in messages associated with the message thread. 12. The electronic device of claim 11 , wherein the language objects are associated with frequency objects containing frequency values for the language objects. | 0.858907 |
8,587,613 | 10 | 11 | 10. A computer program product for facilitating accurate review of a document, the computer program product being encoded on one or more machine-readable storage media and comprising: instruction for manipulating by a computer a scanned image of the document, instruction for indicating to a reader portions of the document which have been already reviewed in a previous or master document, wherein the document comprises two or more documents, instruction for indicating to the reader the similarities and/or differences between the two or more documents, and instruction for re-ordering of the two or more documents by moving documents which have a large set of same or similar changes together so as to facilitate their review consecutively allowing more text, diagrams, and photos to be marked as the same. | 10. A computer program product for facilitating accurate review of a document, the computer program product being encoded on one or more machine-readable storage media and comprising: instruction for manipulating by a computer a scanned image of the document, instruction for indicating to a reader portions of the document which have been already reviewed in a previous or master document, wherein the document comprises two or more documents, instruction for indicating to the reader the similarities and/or differences between the two or more documents, and instruction for re-ordering of the two or more documents by moving documents which have a large set of same or similar changes together so as to facilitate their review consecutively allowing more text, diagrams, and photos to be marked as the same. 11. The computer program product of claim 10 , wherein said instruction for manipulating the image includes instruction for highlighting or de-emphasizing portions of the image. | 0.502809 |
8,311,800 | 4 | 5 | 4. The method of claim 1 , further comprising determining whether the translation of the key term in the second language matches one or more terms included in the translation of the computing string in the second language. | 4. The method of claim 1 , further comprising determining whether the translation of the key term in the second language matches one or more terms included in the translation of the computing string in the second language. 5. The method of claim 4 , further comprising comparing a part of speech tag of the key term in the first language with a part of speech tag of one or more terms included in the translation of the computing string in the second language if the translation of the key term in the second language does not match one or more terms included in the translation of the computing string in the second language. | 0.823401 |
7,689,407 | 13 | 15 | 13. The computer product as claimed in claim 12 , wherein the plurality of input words are placed below or above the plurality of pictures, and the plurality of output words are placed below or above the plurality of pictures. | 13. The computer product as claimed in claim 12 , wherein the plurality of input words are placed below or above the plurality of pictures, and the plurality of output words are placed below or above the plurality of pictures. 15. The computer product as claimed in claim 13 , wherein said computer readable medium further comprising a seventh code: providing a picture option interface capable of displaying plurality of picture formats from which users can choose a specific picture format. | 0.878885 |
10,037,563 | 1 | 5 | 1. A system for determining order details based on phrase matching, the system comprising: a non-transitory memory; and one or more hardware processors coupled to the non-transitory memory and configured to read instructions from the non-transitory memory to cause the system to perform operations comprising: receiving, from a user device via a network, a first phrase and a user device identifier that identifies a user account at the system; accessing, based on the user device identifier, the user account from a plurality of user accounts, the accessing for obtaining information comprising a plurality of phrases associated with the user account; determining whether the first phrase matches a second phrase of the plurality of phrases that are stored at the system for the plurality of user accounts, the second phrase identifying a first order from a first merchant and a second order from a second merchant; in response to a determination that the first phrase matches the second phrase, determining, based on the first phrase, first details of the first order and second details of the second order; communicating a first request, based on the first details, via the network to the first merchant for a first list of items; communicating a second request, based on the second details, via the network to the second merchant for a second list of items; and processing a first payment for the first request and a second payment for the second request. | 1. A system for determining order details based on phrase matching, the system comprising: a non-transitory memory; and one or more hardware processors coupled to the non-transitory memory and configured to read instructions from the non-transitory memory to cause the system to perform operations comprising: receiving, from a user device via a network, a first phrase and a user device identifier that identifies a user account at the system; accessing, based on the user device identifier, the user account from a plurality of user accounts, the accessing for obtaining information comprising a plurality of phrases associated with the user account; determining whether the first phrase matches a second phrase of the plurality of phrases that are stored at the system for the plurality of user accounts, the second phrase identifying a first order from a first merchant and a second order from a second merchant; in response to a determination that the first phrase matches the second phrase, determining, based on the first phrase, first details of the first order and second details of the second order; communicating a first request, based on the first details, via the network to the first merchant for a first list of items; communicating a second request, based on the second details, via the network to the second merchant for a second list of items; and processing a first payment for the first request and a second payment for the second request. 5. The system of claim 1 , wherein the first phrase is received from the user device via an email message. | 0.504673 |
8,335,754 | 21 | 22 | 21. The method of claim 17 wherein presenting at said client computer at least one of a concept map, facts listing, a text summary, a tag cloud, an index and an annotated text comprises determining link counts of said tree elements, producing keyword weights associated with words of said at least one sentence in accordance with said link counts, selecting among said words one or more keywords in accordance with said keyword weights and presenting said keywords. | 21. The method of claim 17 wherein presenting at said client computer at least one of a concept map, facts listing, a text summary, a tag cloud, an index and an annotated text comprises determining link counts of said tree elements, producing keyword weights associated with words of said at least one sentence in accordance with said link counts, selecting among said words one or more keywords in accordance with said keyword weights and presenting said keywords. 22. The method of claim 21 wherein presenting at said client computer at least one of a concept map, facts listing, a text summary, a tag cloud, an index and an annotated text comprises presenting an alphabetical listing of said keywords, said keywords being hyperlinked to occurrences of said keywords within at least one of said facts listing and said resource. | 0.89569 |
6,101,537 | 38 | 39 | 38. The method of claim 37 further comprising the step of storing in a cache memory in said local server, at least one resource alias and its associated resource alias record. | 38. The method of claim 37 further comprising the step of storing in a cache memory in said local server, at least one resource alias and its associated resource alias record. 39. The method of claim 38 further comprising the step of retrieving from said local server said data from said cache memory of said local server, if available, which is responsive to said received request from said client computer. | 0.918596 |
8,639,509 | 19 | 27 | 19. The method of claim 5 , wherein the at least one feature includes at least one of a set of features, including: a parse-tree-word-level confidence score calculated based on respective word-level confidence scores of a plurality of words of the respective sub-tree and/or its surrounding sub-trees; a POS-tag confidence score based on respective POS-tag scores computed for the POS tag assignments of the plurality of words of the respective sub-tree and/or its surrounding sub-trees; a linking score representing a conditional probability of a link of a highest level of the respective sub-tree, the link including a dependency relation and a directionality; a linking score representing a conditional probability of a link of a highest level of the surrounding sub-trees, the link including a dependency relation and a directionality; a history score which includes, for each of at least one child sub-tree of the surrounding sub-trees, the surrounding child sub-trees' previously computed confidence score; each of a plurality of words of the respective sub-tree's corresponding section of the interpreted text; each of a plurality of words of the surrounding sub-trees' corresponding section of the interpreted text; each of the plurality of POS tags corresponding to the plurality of words of the respective sub-tree's corresponding section of the interpreted text; each of the plurality of POS tags corresponding to the plurality of words of the surrounding sub-trees' corresponding section of the interpreted text; each of a plurality of multi-level hierarchical POS tags corresponding to the plurality of words of the respective sub-tree's corresponding section of the interpreted text; each of a plurality of multi-level hierarchical POS tags corresponding to the plurality of words of the surrounding sub-trees' corresponding section of the interpreted text; a dependency relation characteristic; a single level joint head and dependency relation (SL-JHD) characteristic; a single level joint mod and dependency relation (SL-JMD) characteristic; a single level joint head, mod, and dependency relation (SL-JHMD) characteristic; a joint dependency relation (JDR) characteristic; a multi-level joint head and dependency relation (ML-JHD) characteristic; a multi-level joint mod and dependency relation (ML-JMD) characteristic; a multi-level joint head, mod, and dependency relation (ML-JHMD) characteristic; a head, dependency, and left and right neighbors (HDLRN) characteristic; a sub-tree size characteristic; and a semantic slot feature. | 19. The method of claim 5 , wherein the at least one feature includes at least one of a set of features, including: a parse-tree-word-level confidence score calculated based on respective word-level confidence scores of a plurality of words of the respective sub-tree and/or its surrounding sub-trees; a POS-tag confidence score based on respective POS-tag scores computed for the POS tag assignments of the plurality of words of the respective sub-tree and/or its surrounding sub-trees; a linking score representing a conditional probability of a link of a highest level of the respective sub-tree, the link including a dependency relation and a directionality; a linking score representing a conditional probability of a link of a highest level of the surrounding sub-trees, the link including a dependency relation and a directionality; a history score which includes, for each of at least one child sub-tree of the surrounding sub-trees, the surrounding child sub-trees' previously computed confidence score; each of a plurality of words of the respective sub-tree's corresponding section of the interpreted text; each of a plurality of words of the surrounding sub-trees' corresponding section of the interpreted text; each of the plurality of POS tags corresponding to the plurality of words of the respective sub-tree's corresponding section of the interpreted text; each of the plurality of POS tags corresponding to the plurality of words of the surrounding sub-trees' corresponding section of the interpreted text; each of a plurality of multi-level hierarchical POS tags corresponding to the plurality of words of the respective sub-tree's corresponding section of the interpreted text; each of a plurality of multi-level hierarchical POS tags corresponding to the plurality of words of the surrounding sub-trees' corresponding section of the interpreted text; a dependency relation characteristic; a single level joint head and dependency relation (SL-JHD) characteristic; a single level joint mod and dependency relation (SL-JMD) characteristic; a single level joint head, mod, and dependency relation (SL-JHMD) characteristic; a joint dependency relation (JDR) characteristic; a multi-level joint head and dependency relation (ML-JHD) characteristic; a multi-level joint mod and dependency relation (ML-JMD) characteristic; a multi-level joint head, mod, and dependency relation (ML-JHMD) characteristic; a head, dependency, and left and right neighbors (HDLRN) characteristic; a sub-tree size characteristic; and a semantic slot feature. 27. The method of claim 19 , wherein the at least one feature includes three ML-JMD features, including one for each of the highest level of the surrounding sub-trees and left and right child sub-trees corresponding to a level immediately below the highest level of the surrounding sub-trees. | 0.757072 |
9,904,676 | 1 | 5 | 1. A computer implemented method comprising: identifying, using a processor, a time period to be described linguistically in an output text; identifying, using the processor, a communicative context for the output text; determining, using the processor, one or more temporal reference frames that are applicable to the time period and a domain defined by the communicative context; and generating, using the processor, a phrase specification that linguistically describes the time period based on a descriptor that is defined by a temporal reference frame of the one or more temporal reference frames, wherein the descriptor specifies a time window that is inclusive of at least a portion of the time period to be described linguistically. | 1. A computer implemented method comprising: identifying, using a processor, a time period to be described linguistically in an output text; identifying, using the processor, a communicative context for the output text; determining, using the processor, one or more temporal reference frames that are applicable to the time period and a domain defined by the communicative context; and generating, using the processor, a phrase specification that linguistically describes the time period based on a descriptor that is defined by a temporal reference frame of the one or more temporal reference frames, wherein the descriptor specifies a time window that is inclusive of at least a portion of the time period to be described linguistically. 5. A method according to claim 1 , further comprising: identifying, using the processor, another time period to be described linguistically; and determining, using the processor, a descriptor that is defined by another temporal reference frame of the one or more temporal reference frames. | 0.786243 |
9,176,958 | 5 | 6 | 5. The method according to claim 4 , wherein said generating the fault-tolerant tempo word comprises: selecting one or more tempo scales contained in a corresponding tempo word; and replacing the selected tempo scales in said corresponding tempo word with corresponding fault-tolerant tempo scales to generate the fault-tolerant tempo word. | 5. The method according to claim 4 , wherein said generating the fault-tolerant tempo word comprises: selecting one or more tempo scales contained in a corresponding tempo word; and replacing the selected tempo scales in said corresponding tempo word with corresponding fault-tolerant tempo scales to generate the fault-tolerant tempo word. 6. The method according to claim 5 , wherein said generating a fault-tolerant tempo word further comprises: ranking the selected tempo scales; and selecting, for each tempo scale contained in said corresponding tempo word, a predetermined number of tempo scales that are anteriorly or posteriorly ranked, as fault-tolerant tempo scales for the tempo scale. | 0.88805 |
4,815,029 | 1 | 2 | 1. A method for the intelligent, in-line, dynamic editing of documents containing mixed object types on a computer work station comprising the steps of: (a) displaying a document and a command bar on the computer work station, said command bar containing at least generic actions which may be chosen by a user in the editing of the document; (b) determining if an object on the document has been selected by the user for editing; (c) determining the type of object selected by the user for editing; and (d) displaying in said command bar editing actions which are specific to the type of object selected by the user for editing. | 1. A method for the intelligent, in-line, dynamic editing of documents containing mixed object types on a computer work station comprising the steps of: (a) displaying a document and a command bar on the computer work station, said command bar containing at least generic actions which may be chosen by a user in the editing of the document; (b) determining if an object on the document has been selected by the user for editing; (c) determining the type of object selected by the user for editing; and (d) displaying in said command bar editing actions which are specific to the type of object selected by the user for editing. 2. The method recited in claim 1 further comprising the steps of: (e) determining if an edit action has been selected by the user for editing a selected object; (f) processing the edit action selected by the user for the selected object and automatically reformatting the document as required; and (g) redisplaying the document as edited and reformatted. | 0.740469 |
7,603,300 | 14 | 16 | 14. The system of claim 9 wherein the statistical data stored in the data warehouse comprises spending data extracted from the identified documents. | 14. The system of claim 9 wherein the statistical data stored in the data warehouse comprises spending data extracted from the identified documents. 16. The system of claim 14 wherein the predetermined statistical categories are defined by at least one parameter selected from the group consisting of a trading partner, a contract identifier, a material group identifier, a document type and a time period. | 0.938605 |
7,921,106 | 1 | 5 | 1. A computer-implemented apparatus that enhances search result listings, comprising: a processor operatively coupled to a computer readable medium having stored thereon the following computer executable components: an attribute value ranking component comprising a search engine search result list sorted by search results rank, and further sorted by attribute value as a primary sort and rank as a secondary sort, wherein an attribute value rank is calculated for each of the attribute values; grouped search results comprising the search result list resorted by the calculated attribute value ranks, and further resorted by the attribute values, and still further resorted by the search results rank; a search result display component that provides search result groupings based on the group-by ranking for interaction with a user; and computer-readable storage medium comprising data structures and code for causing a computer to execute the attribute value ranking and search result display components, wherein the object oriented search result list references a plurality of information pages each comprising an object block representing an object classified as an object type having attributes for which the object block contains elements identified as attribute values, wherein the attribute pertains to a source of a respective information page. | 1. A computer-implemented apparatus that enhances search result listings, comprising: a processor operatively coupled to a computer readable medium having stored thereon the following computer executable components: an attribute value ranking component comprising a search engine search result list sorted by search results rank, and further sorted by attribute value as a primary sort and rank as a secondary sort, wherein an attribute value rank is calculated for each of the attribute values; grouped search results comprising the search result list resorted by the calculated attribute value ranks, and further resorted by the attribute values, and still further resorted by the search results rank; a search result display component that provides search result groupings based on the group-by ranking for interaction with a user; and computer-readable storage medium comprising data structures and code for causing a computer to execute the attribute value ranking and search result display components, wherein the object oriented search result list references a plurality of information pages each comprising an object block representing an object classified as an object type having attributes for which the object block contains elements identified as attribute values, wherein the attribute pertains to a source of a respective information page. 5. The computer-implemented apparatus of claim 1 , wherein the attribute value ranking component employs an object oriented ranking process in providing the group-by ranking. | 0.693662 |
8,131,647 | 23 | 26 | 23. A non-transitory computer-readable medium having stored thereon computer-executable instructions that, in response to execution by a computing system, cause the computing system to: receive from a client system an annotation of a digital work by a first user; store the annotation in a memory in association with the digital work; require a second user desiring to access the annotation of the first user to perform a specified action before providing an authorization credential to the second user, wherein the specified action is contributing an annotation of a digital work; and upon receipt of the authorization credential from the second user desiring to access the annotation, provide the annotation to a client system for output to the second user, wherein the annotation is provided in context with regard to the digital work. | 23. A non-transitory computer-readable medium having stored thereon computer-executable instructions that, in response to execution by a computing system, cause the computing system to: receive from a client system an annotation of a digital work by a first user; store the annotation in a memory in association with the digital work; require a second user desiring to access the annotation of the first user to perform a specified action before providing an authorization credential to the second user, wherein the specified action is contributing an annotation of a digital work; and upon receipt of the authorization credential from the second user desiring to access the annotation, provide the annotation to a client system for output to the second user, wherein the annotation is provided in context with regard to the digital work. 26. The computer-readable medium of claim 23 , further having stored thereon computer-executable instructions that direct the computing system to store the annotation in association with particular content in the digital work. | 0.606272 |
8,971,630 | 4 | 8 | 4. The method of claim 1 , wherein isolating the plurality of glyph-based character representations includes: detecting character gaps in the line of glyph-based character representations; creating a histogram of distances for the detected character gaps; constructing a graph according to the detected character gaps; assigning a penalty to arcs of the graph wherein the penalty is based in part on the histogram of distances; and selecting a path in the graph associated with the character cells based on said penalty and arcs of the graph. | 4. The method of claim 1 , wherein isolating the plurality of glyph-based character representations includes: detecting character gaps in the line of glyph-based character representations; creating a histogram of distances for the detected character gaps; constructing a graph according to the detected character gaps; assigning a penalty to arcs of the graph wherein the penalty is based in part on the histogram of distances; and selecting a path in the graph associated with the character cells based on said penalty and arcs of the graph. 8. The method of claim 4 , wherein the method further comprises: determining whether the line of glyph-based character representations includes non-CJK characters by detecting whether any of the arcs associated with the desired path have been assigned a second type penalty. | 0.883701 |
7,958,136 | 1 | 8 | 1. A computer-implemented method for identifying similar documents, comprising: (a) receiving document text for a current document that includes at least two words; (b) calculating: a prominence score for each word, wherein the prominence score for each word is based on a term weight and a non-compound likelihood for each word, a prominence score for each pair of consecutive words, wherein the prominence score for each pair of consecutive words is based on a term weight and a compound probability for each pair of consecutive words, a descriptiveness score for each word wherein the descriptiveness score for each word is based on a corpus, and a descriptiveness score for each pair of consecutive words, wherein the descriptiveness score for each pair of consecutive words is based on the corpus; (c) calculating a comparison metric for the current document, wherein the comparison metric is based on the combination of each prominence score and each descriptiveness score; (d) finding, using a query processor, at least one potential document, wherein document text for each potential document includes at least one word from the current document; and (e) analyzing each found potential document to identify at least one similar document as a function of a comparison metric for the respective potential document and the comparison metric for the current document. | 1. A computer-implemented method for identifying similar documents, comprising: (a) receiving document text for a current document that includes at least two words; (b) calculating: a prominence score for each word, wherein the prominence score for each word is based on a term weight and a non-compound likelihood for each word, a prominence score for each pair of consecutive words, wherein the prominence score for each pair of consecutive words is based on a term weight and a compound probability for each pair of consecutive words, a descriptiveness score for each word wherein the descriptiveness score for each word is based on a corpus, and a descriptiveness score for each pair of consecutive words, wherein the descriptiveness score for each pair of consecutive words is based on the corpus; (c) calculating a comparison metric for the current document, wherein the comparison metric is based on the combination of each prominence score and each descriptiveness score; (d) finding, using a query processor, at least one potential document, wherein document text for each potential document includes at least one word from the current document; and (e) analyzing each found potential document to identify at least one similar document as a function of a comparison metric for the respective potential document and the comparison metric for the current document. 8. The method of claim 1 , wherein calculating the descriptiveness score comprises: calculating a frequency of each word or pair of consecutive words in a purpose-relevant corpus and a frequency of each word or pair of consecutive words in a background corpus. | 0.877934 |
7,665,141 | 1 | 5 | 1. A method of separately authenticating the origin and custody of substantially each substantive page reproduced from a plurality of stored digitized electronic records created by a plurality of different originators, said method comprising: creating and storing said plurality of digitized electronic records; applying a custodian mark to each of said digitized electronic records when said digitized electronic records are placed in storage; applying an originator mark to each of said digitized electronic records after it has been created, wherein the same originator mark is applied to each of said digitized electronic records that is created by the same originator; reproducing at least one said substantive page from at least one of said stored digitized electronic records, the resulting reproduced substantive page being in digitized form; and wherein both said custodian and originator marks appear on said reproduced substantive page only if such reproduced substantive page has not been changed since said custodian and originator marks were applied to said digitized electronic record, said reproduced substantive page being alterable to produce an altered page from which said custodian and originator marks have been automatically and unavoidably removed by the alteration of said reproduced substantive page. | 1. A method of separately authenticating the origin and custody of substantially each substantive page reproduced from a plurality of stored digitized electronic records created by a plurality of different originators, said method comprising: creating and storing said plurality of digitized electronic records; applying a custodian mark to each of said digitized electronic records when said digitized electronic records are placed in storage; applying an originator mark to each of said digitized electronic records after it has been created, wherein the same originator mark is applied to each of said digitized electronic records that is created by the same originator; reproducing at least one said substantive page from at least one of said stored digitized electronic records, the resulting reproduced substantive page being in digitized form; and wherein both said custodian and originator marks appear on said reproduced substantive page only if such reproduced substantive page has not been changed since said custodian and originator marks were applied to said digitized electronic record, said reproduced substantive page being alterable to produce an altered page from which said custodian and originator marks have been automatically and unavoidably removed by the alteration of said reproduced substantive page. 5. A method of claim 1 wherein said at least one originator determines whether said originator mark is to be applied to a particular said stored digitized electronic record, and instructs said custodian as to what access controls to apply to said particular stored digitized electronic record, said access controls including at least who shall have access to read or change said particular stored digitized electronic record. | 0.501174 |
8,600,100 | 13 | 15 | 13. The method of claim 1 , wherein the stimulus comprises one or more of questions, statements, or scenarios. | 13. The method of claim 1 , wherein the stimulus comprises one or more of questions, statements, or scenarios. 15. The method of claim 13 , wherein the objective the individual is being assessed for is to determine potential romantic partners. | 0.965856 |
9,159,318 | 8 | 9 | 8. 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: performing automatic speech recognition using a bootstrap model on utterance data not having a corresponding manual transcription, to produce automatically transcribed utterances, wherein the bootstrap model is based on text data mined from a website relevant to a specific domain; selecting a predetermined number of utterances not having a corresponding manual transcription based on a geometrically computed n-tuple confidence score; receiving transcriptions of the predetermined number of utterances, wherein the transcriptions are made by a human being; and generating a language model based on the automatically transcribed utterances, the predetermined number of utterances, and the transcriptions. | 8. 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: performing automatic speech recognition using a bootstrap model on utterance data not having a corresponding manual transcription, to produce automatically transcribed utterances, wherein the bootstrap model is based on text data mined from a website relevant to a specific domain; selecting a predetermined number of utterances not having a corresponding manual transcription based on a geometrically computed n-tuple confidence score; receiving transcriptions of the predetermined number of utterances, wherein the transcriptions are made by a human being; and generating a language model based on the automatically transcribed utterances, the predetermined number of utterances, and the transcriptions. 9. The system of claim 8 , the computer-readable storage medium having additional instructions stored which, when executed by the processor, result in operations comprising: performing automatic speech recognition using the language model. | 0.502083 |
10,129,373 | 12 | 13 | 12. The method of claim 11 , wherein the reconstructing the entire existing network infrastructure further comprises matching of the capabilities and the configuration data of each of the plurality of replacement devices with the capabilities and the configuration data of each of the plurality of target devices to determine functionally equivalent replacement devices. | 12. The method of claim 11 , wherein the reconstructing the entire existing network infrastructure further comprises matching of the capabilities and the configuration data of each of the plurality of replacement devices with the capabilities and the configuration data of each of the plurality of target devices to determine functionally equivalent replacement devices. 13. The method of claim 12 , wherein the reconstructing the entire existing network infrastructure further comprises creating inputs for provisioning tools based on the generalized descriptive language for the captured data and the ecology information of the existing network infrastructure and the generalized descriptive language for the determined functionally equivalent replacement devices. | 0.710411 |
9,946,770 | 16 | 17 | 16. The non-transitory storage medium of claim 15 , wherein the first set of directly associated words of the key word comprise word groups in the keyword database having at least one word matching the key word and wherein the second set of indirectly associated words of the key word comprise words from the keyword database that are associated with but are not direct match of the key word. | 16. The non-transitory storage medium of claim 15 , wherein the first set of directly associated words of the key word comprise word groups in the keyword database having at least one word matching the key word and wherein the second set of indirectly associated words of the key word comprise words from the keyword database that are associated with but are not direct match of the key word. 17. The non-transitory storage medium of claim 16 , wherein the search results queried using the first set of directly associated words are obtained by searches performed by a server using the first set of directed associated words as search queries. | 0.911723 |
8,744,861 | 1 | 6 | 1. A computer-implemented method for invoking a tapered prompt comprising a plurality of prompt elements, each prompt element comprising a voice component and a non-voice component, the method comprising acts of: selecting a first voice style for the voice component of a first prompt element in the plurality of prompt elements of the tapered prompt, wherein the voice component of the first prompt element solicits requested information from a user; selecting, in conjunction with selecting the first voice style, a first non-voice style for the non-voice component of the first prompt element, wherein the non-voice component of the first prompt element solicits the same requested information as the voice component of the first prompt element; receiving voice input provided by the user in response to the first prompt element; using at least one processor to process the voice input to determine whether the user provided the requested information; and in response to determining that at least some of the requested information was not provided by the user, selecting a second voice style for the voice component of a second prompt element of the tapered prompt, and selecting, in conjunction with selecting the second voice style, a second non-voice style for the non-voice component of the second prompt element, wherein: both the voice component and non-voice component of the second prompt element further solicit the at least some of the requested information from the user, the second voice style is different from the first voice style, and the second non-voice style is different from the first non-voice style. | 1. A computer-implemented method for invoking a tapered prompt comprising a plurality of prompt elements, each prompt element comprising a voice component and a non-voice component, the method comprising acts of: selecting a first voice style for the voice component of a first prompt element in the plurality of prompt elements of the tapered prompt, wherein the voice component of the first prompt element solicits requested information from a user; selecting, in conjunction with selecting the first voice style, a first non-voice style for the non-voice component of the first prompt element, wherein the non-voice component of the first prompt element solicits the same requested information as the voice component of the first prompt element; receiving voice input provided by the user in response to the first prompt element; using at least one processor to process the voice input to determine whether the user provided the requested information; and in response to determining that at least some of the requested information was not provided by the user, selecting a second voice style for the voice component of a second prompt element of the tapered prompt, and selecting, in conjunction with selecting the second voice style, a second non-voice style for the non-voice component of the second prompt element, wherein: both the voice component and non-voice component of the second prompt element further solicit the at least some of the requested information from the user, the second voice style is different from the first voice style, and the second non-voice style is different from the first non-voice style. 6. The computer-implemented method of claim 1 , further comprising an act of: audibly rendering the voice component of the first prompt element in the first voice style. | 0.771622 |
8,949,340 | 8 | 9 | 8. The computer program product of claim 1 , further comprising: computer code for causing delivery of event-related information utilizing the short message service in the form of an event-related short message service message including a first selection option indicating a first event short form command associated with a first event and a second selection option indicating a second event short form command associated with a second event; computer code for allowing receipt of the first event short form command associated with the first event, in response to the event-related short message service message; computer code for allowing receipt of the second event short form command associated with the second event, in response to the event-related short message service message; computer code for, in response to the receipt of the first event short form command associated with the first event, causing delivery of first event information associated with the first event; and computer code for, in response to the receipt of the second event short form command associated with the second event, causing delivery of second event information associated with the second event. | 8. The computer program product of claim 1 , further comprising: computer code for causing delivery of event-related information utilizing the short message service in the form of an event-related short message service message including a first selection option indicating a first event short form command associated with a first event and a second selection option indicating a second event short form command associated with a second event; computer code for allowing receipt of the first event short form command associated with the first event, in response to the event-related short message service message; computer code for allowing receipt of the second event short form command associated with the second event, in response to the event-related short message service message; computer code for, in response to the receipt of the first event short form command associated with the first event, causing delivery of first event information associated with the first event; and computer code for, in response to the receipt of the second event short form command associated with the second event, causing delivery of second event information associated with the second event. 9. The computer program product of claim 8 , wherein the computer program is operable such that the first event information describes the first event. | 0.974645 |
8,122,104 | 1 | 5 | 1. A method for providing a feed control, comprising: loading a template defining a format of one of a plurality of entries in a data feed to be displayed to a local user; loading the data feed onto a local device from a remote data server, wherein said loading includes retrieving data bindings from said template and using said data bindings retrieved from said template to request data specified by said data bindings from said remote data server; receiving said requested data from said remote server system at said local device; applying said template to said plurality of entries; and displaying said plurality of entries to said local user. | 1. A method for providing a feed control, comprising: loading a template defining a format of one of a plurality of entries in a data feed to be displayed to a local user; loading the data feed onto a local device from a remote data server, wherein said loading includes retrieving data bindings from said template and using said data bindings retrieved from said template to request data specified by said data bindings from said remote data server; receiving said requested data from said remote server system at said local device; applying said template to said plurality of entries; and displaying said plurality of entries to said local user. 5. The method of claim 1 , further comprising: determining an identifier of said template based on an automatically determined type of said data feed. | 0.750831 |
8,055,608 | 30 | 33 | 30. A method, performed by computing hardware and programmable memory, for determining whether a concept is referenced by a first unit of natural language discourse, comprising: parsing the first unit of natural language discourse into a first parse structure that represents each sub-unit, of the first unit of natural language discourse, by a node; adding at least one concept-value pair, each of which indicates a reference to a same first concept, to at least one node of the first parse structure, wherein each reference is determined by identifying an occurrence of a first linguistic feature from a first set of linguistic features and the first set of linguistic features contains many linguistic features; adding at least one concept-value pair, each of which indicates a reference to a same modifier concept that can modify a reference level assigned to the first concept, to at least one node of the first parse structure, wherein each reference to the modifier concept is determined by identifying an occurrence of a second linguistic feature from a second set of linguistic features and the second set of linguistic features contains many linguistic features; propagating the at least one concept-value pair for the modifier concept; identifying a first node of the first parse structure that has at least one concept-value pair for the first concept and at least one concept-value pair for the modifier concept; determining a first value to be scaled from the least one concept-value pair for the first concept; determining a first scaling value from the least one concept-value pair for the modifier concept; scaling the first value to be scaled with the first scaling value to produce a first scaled value; and propagating the at least one concept-value pair for the first concept. | 30. A method, performed by computing hardware and programmable memory, for determining whether a concept is referenced by a first unit of natural language discourse, comprising: parsing the first unit of natural language discourse into a first parse structure that represents each sub-unit, of the first unit of natural language discourse, by a node; adding at least one concept-value pair, each of which indicates a reference to a same first concept, to at least one node of the first parse structure, wherein each reference is determined by identifying an occurrence of a first linguistic feature from a first set of linguistic features and the first set of linguistic features contains many linguistic features; adding at least one concept-value pair, each of which indicates a reference to a same modifier concept that can modify a reference level assigned to the first concept, to at least one node of the first parse structure, wherein each reference to the modifier concept is determined by identifying an occurrence of a second linguistic feature from a second set of linguistic features and the second set of linguistic features contains many linguistic features; propagating the at least one concept-value pair for the modifier concept; identifying a first node of the first parse structure that has at least one concept-value pair for the first concept and at least one concept-value pair for the modifier concept; determining a first value to be scaled from the least one concept-value pair for the first concept; determining a first scaling value from the least one concept-value pair for the modifier concept; scaling the first value to be scaled with the first scaling value to produce a first scaled value; and propagating the at least one concept-value pair for the first concept. 33. The method of claim 30 , wherein the first set of linguistic features is approximately complete with respect to the first concept and the second set of linguistic features is approximately complete with respect to the modifier concept. | 0.816154 |
8,911,478 | 18 | 19 | 18. The improvement of claim 1 wherein the closure further comprises an inner threaded bore and a set screw having an outer thread for mating with the closure at the inner threaded bore. | 18. The improvement of claim 1 wherein the closure further comprises an inner threaded bore and a set screw having an outer thread for mating with the closure at the inner threaded bore. 19. The improvement of claim 18 wherein the closure has a bottom surface sized and shaped for engagement with a compression insert located within a cavity of the receiver that communicates with the channel and the set screw has a bottom surface sized and shaped for engagement with the longitudinal connecting member. | 0.93614 |
8,533,195 | 1 | 9 | 1. A topic modeling system, comprising: at least one calculating unit; and at least one computer readable medium in communication with the at least one calculating unit and having instructions and a first equation stored therein, the first equation having terms including a term-document matrix D, a term-topic matrix U, a topic-document matrix V, a regularization of vectors of the term-topic matrix U and a regularization of vectors of the topic-document matrix V, the term-document matrix D having N columns, N>1, each column of the term-document matrix D representing a respective document and having M (M>1) members in which each member represents a respective term of the respective document, the term-topic matrix U and the topic-document matrix V are related such that the term-document matrix D is approximated by a matrix multiplication of the term-topic matrix U and the topic-document matrix V, when executed by the at least one calculating unit, cause the at least one calculating unit to perform acts comprising: for a number of iterations, minimizing the first equation while holding the topic-document matrix V fixed; updating the term-topic matrix U based at least on values of the topic-document matrix V calculated in a most recent minimization of the first equation; minimizing the first equation while holding the term-topic matrix U fixed; and updating the topic-document matrix V based at least on values of the term-topic matrix U calculated in a most recent minimization of the first equation. | 1. A topic modeling system, comprising: at least one calculating unit; and at least one computer readable medium in communication with the at least one calculating unit and having instructions and a first equation stored therein, the first equation having terms including a term-document matrix D, a term-topic matrix U, a topic-document matrix V, a regularization of vectors of the term-topic matrix U and a regularization of vectors of the topic-document matrix V, the term-document matrix D having N columns, N>1, each column of the term-document matrix D representing a respective document and having M (M>1) members in which each member represents a respective term of the respective document, the term-topic matrix U and the topic-document matrix V are related such that the term-document matrix D is approximated by a matrix multiplication of the term-topic matrix U and the topic-document matrix V, when executed by the at least one calculating unit, cause the at least one calculating unit to perform acts comprising: for a number of iterations, minimizing the first equation while holding the topic-document matrix V fixed; updating the term-topic matrix U based at least on values of the topic-document matrix V calculated in a most recent minimization of the first equation; minimizing the first equation while holding the term-topic matrix U fixed; and updating the topic-document matrix V based at least on values of the term-topic matrix U calculated in a most recent minimization of the first equation. 9. The topic modeling system as recited in claim 1 , the acts further comprising: retrieving a number (N) of electronic documents; generating the term-document matrix D based at least on the retrieved documents; and initializing the topic-document matrix V based at least on random values assigned to members of the topic-document matrix V. | 0.803241 |
9,317,569 | 14 | 18 | 14. A system comprising: one or more processors; memory, in communication with the one or more processors; a module, defined in the memory, executable by the one or more processors, and configured to: obtain web documents based at least in part on a search term; extract a plurality of entities and entity relationships from the web documents, each of the plurality of entities related to, but distinct from, the search term; cause display of representations indicating each of the plurality of entities; cause display of edges to define pairs of the displayed representations, the edges indicated by the entity relationships; cause display of a representation of the search term and edges from the representation of the search term to each of the representations of the plurality of entities; receive user input indicating an edge between representations of two particular entities; and cause display of a description of a relationship between the two particular entities in response to the received user input. | 14. A system comprising: one or more processors; memory, in communication with the one or more processors; a module, defined in the memory, executable by the one or more processors, and configured to: obtain web documents based at least in part on a search term; extract a plurality of entities and entity relationships from the web documents, each of the plurality of entities related to, but distinct from, the search term; cause display of representations indicating each of the plurality of entities; cause display of edges to define pairs of the displayed representations, the edges indicated by the entity relationships; cause display of a representation of the search term and edges from the representation of the search term to each of the representations of the plurality of entities; receive user input indicating an edge between representations of two particular entities; and cause display of a description of a relationship between the two particular entities in response to the received user input. 18. The system as recited in claim 14 , wherein each representation of an entity is displayed as a circle having a diameter size based at least in part on a number of relationships of that entity with other entities and wherein each representation of an entity is connected to the representation of the search term and to at least one other representation of an entity. | 0.676883 |
8,024,327 | 30 | 42 | 30. A system for information processing, the system comprising: at least one processor operatively connected to a memory adapted to execute system components, and wherein the system further comprises: an access component adapted to access a set of documents obtained from an information retrieval system, wherein the access component is further configured to establish, automatically, at least one identifying characteristic within the set of documents; an analysis component adapted to obtain a statistical distribution based on values associated with the set of documents, the set of documents having a given size; a measurement component adapted to compute value of a function that measures distinctiveness of the obtained statistical distribution relative to a baseline statistical distribution of values associated with a baseline set of documents; a normalization component adapted to normalize the value relative to a distribution of values of the function that measures distinctiveness over a space of document sets, wherein a respective value of the function that measures distinctiveness corresponds to a respective document set within the space of document sets, wherein each document set in the space has a size that is comparable to the given size, wherein the normalization component is further adapted to perform a computation on the value that accounts for the given size of the set of documents; and an output component adapted to generate a response derived from the normalized value. | 30. A system for information processing, the system comprising: at least one processor operatively connected to a memory adapted to execute system components, and wherein the system further comprises: an access component adapted to access a set of documents obtained from an information retrieval system, wherein the access component is further configured to establish, automatically, at least one identifying characteristic within the set of documents; an analysis component adapted to obtain a statistical distribution based on values associated with the set of documents, the set of documents having a given size; a measurement component adapted to compute value of a function that measures distinctiveness of the obtained statistical distribution relative to a baseline statistical distribution of values associated with a baseline set of documents; a normalization component adapted to normalize the value relative to a distribution of values of the function that measures distinctiveness over a space of document sets, wherein a respective value of the function that measures distinctiveness corresponds to a respective document set within the space of document sets, wherein each document set in the space has a size that is comparable to the given size, wherein the normalization component is further adapted to perform a computation on the value that accounts for the given size of the set of documents; and an output component adapted to generate a response derived from the normalized value. 42. The system according to claim 30 , further comprising an approximation component adapted to generate a representation of the set, wherein the representation of the set is adapted to statistical manipulation. | 0.763453 |
9,922,138 | 1 | 10 | 1. A method, comprising: maintaining an online grammar model used by an online voice-based query processor to parse online voice-based queries, the online grammar model mapping a plurality of queries to actions, wherein the actions include non-search actions performable by a computer system, wherein each of the actions is mapped in the grammar model to one or more corresponding queries of the plurality of queries, and wherein each of a plurality of the actions includes one or more corresponding parameters for constraining performance of the action; analyzing query usage data for at least a subset of the plurality of queries to identify a subset of popular queries from among the plurality of queries mapped by the online grammar model, wherein the query usage data includes query usage data collected for queries issued by a plurality of users; and building an offline grammar model that maps the subset of popular queries to actions among the actions for use by a resource-constrained offline device, wherein the offline grammar model has reduced resource requirements relative to the online grammar model and omits mappings for one or more queries among the plurality of queries. | 1. A method, comprising: maintaining an online grammar model used by an online voice-based query processor to parse online voice-based queries, the online grammar model mapping a plurality of queries to actions, wherein the actions include non-search actions performable by a computer system, wherein each of the actions is mapped in the grammar model to one or more corresponding queries of the plurality of queries, and wherein each of a plurality of the actions includes one or more corresponding parameters for constraining performance of the action; analyzing query usage data for at least a subset of the plurality of queries to identify a subset of popular queries from among the plurality of queries mapped by the online grammar model, wherein the query usage data includes query usage data collected for queries issued by a plurality of users; and building an offline grammar model that maps the subset of popular queries to actions among the actions for use by a resource-constrained offline device, wherein the offline grammar model has reduced resource requirements relative to the online grammar model and omits mappings for one or more queries among the plurality of queries. 10. The method of claim 1 , wherein building the offline grammar model includes building a personalized offline grammar model for a user of the resource-constrained offline device based at least in part on query usage data collected from the resource-constrained offline device. | 0.764805 |
9,811,566 | 1 | 2 | 1. A system comprising: a client system implemented on one or more computers for use by a plurality of users; wherein the client system comprises: result selection logs stored on memory devices of the client system; and a tracking component that is operable to store in the result selection logs information about search result selections made by users of the client system; wherein the client system is programmed with instructions that are operable, when executed on the client system, to cause the client system to perform operations to: submit a search query to a search engine that receives search queries from the client system and from other sources of queries; receive search results responsive to the search query, the search results including either an initial ranking of the search results from the search engine or actual information retrieval scores for the search results from the search engine; compute, for each of the search results, a respective measure of relevance based on the information stored by the tracking component of the client system about search result selections made by multiple users of the client system and not by other users of the search engine; and re-rank the search results returned by the search engine based on the respective measures of relevance and provide the re-ranked search results in a response to the search query. | 1. A system comprising: a client system implemented on one or more computers for use by a plurality of users; wherein the client system comprises: result selection logs stored on memory devices of the client system; and a tracking component that is operable to store in the result selection logs information about search result selections made by users of the client system; wherein the client system is programmed with instructions that are operable, when executed on the client system, to cause the client system to perform operations to: submit a search query to a search engine that receives search queries from the client system and from other sources of queries; receive search results responsive to the search query, the search results including either an initial ranking of the search results from the search engine or actual information retrieval scores for the search results from the search engine; compute, for each of the search results, a respective measure of relevance based on the information stored by the tracking component of the client system about search result selections made by multiple users of the client system and not by other users of the search engine; and re-rank the search results returned by the search engine based on the respective measures of relevance and provide the re-ranked search results in a response to the search query. 2. The system of claim 1 , wherein the client system is made up of computers of an enterprise and a data communication network of the enterprise. | 0.843413 |
8,813,047 | 7 | 24 | 7. The non-transitory computer-readable medium of claim 6 , wherein the YATL statement is selected from the group consisting of: a foreach-match statement, a match-once statement, a match statement, a foreach-element statement, a debug statement, a native statement, a print statement, a log statement, an express “on” statement, an isolated statement, a continue statement, a die statement, an “on” statement, a statement insertion statement, a layout insertion statement, an if statement, a while statement, a do while statement, a for statement, a delete statement, a transform decl statement, a transform use statement, a replace with statement, a return statement, a try catch statement, an either or statement, a fail statement, an on file statement, and a pointer declare statement. | 7. The non-transitory computer-readable medium of claim 6 , wherein the YATL statement is selected from the group consisting of: a foreach-match statement, a match-once statement, a match statement, a foreach-element statement, a debug statement, a native statement, a print statement, a log statement, an express “on” statement, an isolated statement, a continue statement, a die statement, an “on” statement, a statement insertion statement, a layout insertion statement, an if statement, a while statement, a do while statement, a for statement, a delete statement, a transform decl statement, a transform use statement, a replace with statement, a return statement, a try catch statement, an either or statement, a fail statement, an on file statement, and a pointer declare statement. 24. The non-transitory computer-readable medium of claim 7 , wherein the YATL program includes an isolate statement having “isolate” followed by the compound statement. | 0.916914 |
8,245,281 | 19 | 20 | 19. A system to grant network access to a client in a communication network, the system comprising: client protocol terminator means adapted for coupling to a remote client; an enforcer; access attribute translation means for translating attributes from a first framework representation into a canonical representation; protocol storage means for storing protocol attributes relating to a plurality of frameworks; service protocol terminator means adapted for coupling to one or more backend service devices; service attribute translation means for translating attributes from a second framework representation into the canonical representation; and policy determination means coupled to the enforcer, the access attribute translation means and the protocol storage means, for determining a policy result based upon an attempt by the client to connect to the communication network, wherein the enforcer blocks the client from accessing the communication network prior to the policy result being determined and the enforcer grants the client access to the communication network based on the policy result. | 19. A system to grant network access to a client in a communication network, the system comprising: client protocol terminator means adapted for coupling to a remote client; an enforcer; access attribute translation means for translating attributes from a first framework representation into a canonical representation; protocol storage means for storing protocol attributes relating to a plurality of frameworks; service protocol terminator means adapted for coupling to one or more backend service devices; service attribute translation means for translating attributes from a second framework representation into the canonical representation; and policy determination means coupled to the enforcer, the access attribute translation means and the protocol storage means, for determining a policy result based upon an attempt by the client to connect to the communication network, wherein the enforcer blocks the client from accessing the communication network prior to the policy result being determined and the enforcer grants the client access to the communication network based on the policy result. 20. The system of claim 19 wherein the policy determination means includes a policy subsystem coupled to the access attribute translation means and the protocol storage means, the policy subsystem having a plurality of rules engine pipeline stages. | 0.714286 |
7,686,682 | 21 | 23 | 21. A method for generating tags for digital images, comprising: for each game round performing the following steps: a. selecting m images of the digital images and displaying the m images on m display areas, wherein m is equal to the numbers of users playing the game round; b. selecting n number of letters of the alphabet, and displaying each of the n letters as a letter tile in a display area defined as a letter tray; c. enabling users to select letter tiles and, when a user selects a letter tile, displaying the letter tile in a user's display area defined as word tray; d. when sufficient letter tiles have been displayed in a word tray to form a word, enabling the user to select one of the m image; e. creating a tag associating the word with the selected image and storing the tag in a storage area so as to enable searching and browsing of the digital images using the tag; and f. counting time periods T 1 and at each end of time period T 1 exchanging the display area for displaying the m images. | 21. A method for generating tags for digital images, comprising: for each game round performing the following steps: a. selecting m images of the digital images and displaying the m images on m display areas, wherein m is equal to the numbers of users playing the game round; b. selecting n number of letters of the alphabet, and displaying each of the n letters as a letter tile in a display area defined as a letter tray; c. enabling users to select letter tiles and, when a user selects a letter tile, displaying the letter tile in a user's display area defined as word tray; d. when sufficient letter tiles have been displayed in a word tray to form a word, enabling the user to select one of the m image; e. creating a tag associating the word with the selected image and storing the tag in a storage area so as to enable searching and browsing of the digital images using the tag; and f. counting time periods T 1 and at each end of time period T 1 exchanging the display area for displaying the m images. 23. The method of claim 21 , wherein selecting n number of letters at step b comprises including duplicate letters but not including all of the alphabet letters. | 0.781843 |
8,027,867 | 1 | 5 | 1. A system for providing reader-supplied evaluation of a sample of an authored literary work for potential publication of the work comprising: a host computer comprising a processor and a storage device; a first interface module operably connected to the Internet, for receiving only a portion of the literary work from an author to be reviewed via the Internet; the storage device stores portion of the literary work along with other portions of other literary works for review; a second interface module that receives a request from a reader to review the portion of the literary work; a work presenter that presents the portion of literary work to the reader based on the reader's request; a security mechanism that limits the ability of users to misappropriate credit for the portion of literary work when the literary work were to be resubmitted by another author including a timestamp associated with a time of first receipt of the portion of the literary work from the author for resolving disputes regarding original authorship; a review receiving module that receives evaluation of the portion of the literary work from the reader and placing the review in the storage device associated with portion of the literary work; a criteria determination module, executed by the processor, having multiple levels of review of the authored literary work, further comprising: a reader-satisfaction module, executed by the processor, for determining whether a predetermined reader-satisfaction criteria is met during a first level review, the first level review being one of multiple levels of review; and a demographic module for determining whether the literary work has been reviewed by a predetermined number of reviewers from a plurality of reviewer demographics; and a publishing determination module that decides to publish the literary work when the predetermined reader-satisfaction criteria is met and when the literary work has been reviewed by a predetermined number of reviewers from a plurality of reviewer demographics. | 1. A system for providing reader-supplied evaluation of a sample of an authored literary work for potential publication of the work comprising: a host computer comprising a processor and a storage device; a first interface module operably connected to the Internet, for receiving only a portion of the literary work from an author to be reviewed via the Internet; the storage device stores portion of the literary work along with other portions of other literary works for review; a second interface module that receives a request from a reader to review the portion of the literary work; a work presenter that presents the portion of literary work to the reader based on the reader's request; a security mechanism that limits the ability of users to misappropriate credit for the portion of literary work when the literary work were to be resubmitted by another author including a timestamp associated with a time of first receipt of the portion of the literary work from the author for resolving disputes regarding original authorship; a review receiving module that receives evaluation of the portion of the literary work from the reader and placing the review in the storage device associated with portion of the literary work; a criteria determination module, executed by the processor, having multiple levels of review of the authored literary work, further comprising: a reader-satisfaction module, executed by the processor, for determining whether a predetermined reader-satisfaction criteria is met during a first level review, the first level review being one of multiple levels of review; and a demographic module for determining whether the literary work has been reviewed by a predetermined number of reviewers from a plurality of reviewer demographics; and a publishing determination module that decides to publish the literary work when the predetermined reader-satisfaction criteria is met and when the literary work has been reviewed by a predetermined number of reviewers from a plurality of reviewer demographics. 5. The system of claim 1 wherein the criteria determination module determines whether a predetermined number of reviews have been made during the first level review prior to evaluating whether the reader-satisfaction criteria have been met. | 0.581882 |
9,767,158 | 15 | 18 | 15. A server computer system comprising: a processing device; a memory coupled to the processing device; and a user bucketing module, executable by the processing device from the memory, to: identify, in a content sharing platform, a bucket comprising a plurality of content items associated with a group of users of the content sharing platform that have similar interests; associate a bucketing token pertaining to the bucket with each of the plurality of content items the bucketing token comprising a unique identifier that identifies the plurality of content items as being associated with the group of users of the content sharing platform that have similar interests; receive a request for the bucketing token from a ranking service; and provide the bucketing token to the ranking service, the ranking service to use the bucketing token to determine, with respect to a first user of a social network platform, a ranking score for a content item of the plurality of associated content items in view of one or more interests of the first user of the social network platform that is separate from the content sharing platform. | 15. A server computer system comprising: a processing device; a memory coupled to the processing device; and a user bucketing module, executable by the processing device from the memory, to: identify, in a content sharing platform, a bucket comprising a plurality of content items associated with a group of users of the content sharing platform that have similar interests; associate a bucketing token pertaining to the bucket with each of the plurality of content items the bucketing token comprising a unique identifier that identifies the plurality of content items as being associated with the group of users of the content sharing platform that have similar interests; receive a request for the bucketing token from a ranking service; and provide the bucketing token to the ranking service, the ranking service to use the bucketing token to determine, with respect to a first user of a social network platform, a ranking score for a content item of the plurality of associated content items in view of one or more interests of the first user of the social network platform that is separate from the content sharing platform. 18. The server computer system of claim 15 , wherein to associate the bucketing token with each of the plurality of associated content items, the user bucketing module to embed the bucketing token in a metadata of each of the plurality of associated content items. | 0.813031 |
10,088,981 | 3 | 4 | 3. The method of claim 1 further comprising: receiving user select input to select and insert a user interface data object from one of the multiple applications into a selected collection from the multiple collection in the collection user interface; and in response to receiving the user select input, copying, inserting and saving the selected user interface data object into the selected collection in the collection user interface. | 3. The method of claim 1 further comprising: receiving user select input to select and insert a user interface data object from one of the multiple applications into a selected collection from the multiple collection in the collection user interface; and in response to receiving the user select input, copying, inserting and saving the selected user interface data object into the selected collection in the collection user interface. 4. The method of claim 3 further comprising displaying the saved user interface data object both in the selected collection in the collection user interface and in the application from which the user interface data object was selected in the single window. | 0.945969 |
9,946,712 | 13 | 14 | 13. The computer-implemented method 6 , wherein identifying the sub-period of audio data, performing speech recognition on the identified audio data sub-period, transmitting the first text to the translation server, and receiving the first translated text from the translation server are each performed during outputting of the media stream. | 13. The computer-implemented method 6 , wherein identifying the sub-period of audio data, performing speech recognition on the identified audio data sub-period, transmitting the first text to the translation server, and receiving the first translated text from the translation server are each performed during outputting of the media stream. 14. The computer-implemented method of claim 13 , wherein the first input is received without interrupting the outputting of the media stream. | 0.963849 |
9,703,769 | 1 | 4 | 1. A method comprising: inserting, via a discriminative classification approach, boundary tags into speech utterance text, the boundary tags identifying boundaries selected from a group comprising phrase boundaries, sentence boundaries, and paragraph boundaries, wherein the discriminative classification approach utilizes syntactic features before and after each word being tagged, to yield boundary marked speech utterance text and unedited text; identifying, via a processor, a coordinating conjunction within the unedited text based on a conjunction tag, wherein the conjunction tag comprises conjunction span information indicating how many words to the left of the conjunction tag a corresponding conjunction includes; and identifying clauses in the speech utterance text based on the boundary marked speech utterance text and the coordinating conjunction. | 1. A method comprising: inserting, via a discriminative classification approach, boundary tags into speech utterance text, the boundary tags identifying boundaries selected from a group comprising phrase boundaries, sentence boundaries, and paragraph boundaries, wherein the discriminative classification approach utilizes syntactic features before and after each word being tagged, to yield boundary marked speech utterance text and unedited text; identifying, via a processor, a coordinating conjunction within the unedited text based on a conjunction tag, wherein the conjunction tag comprises conjunction span information indicating how many words to the left of the conjunction tag a corresponding conjunction includes; and identifying clauses in the speech utterance text based on the boundary marked speech utterance text and the coordinating conjunction. 4. The method of claim 1 , wherein a different classifier performs each step of the method. | 0.905797 |
7,752,534 | 9 | 10 | 9. The apparatus of claim 7 wherein the plurality of tag attributes comprise: popularity of an item, last update of an item, frequency of updates to an item, age of an item, size of an item, most recently accessed, and whether there have been comments or replies related to an item. | 9. The apparatus of claim 7 wherein the plurality of tag attributes comprise: popularity of an item, last update of an item, frequency of updates to an item, age of an item, size of an item, most recently accessed, and whether there have been comments or replies related to an item. 10. The apparatus of claim 9 where the plurality of tag attributes further comprise: a custom tag attribute. | 0.952 |
10,025,779 | 1 | 7 | 1. A method for predicting an optimal machine translation system for a user comprising: for each of a set of users, providing a respective user profile which includes rankings for at least some machine translation systems from a set of machine translation systems, the set of users including a first user and a plurality of other users, wherein the rankings are pairwise rankings for pairs of machine translation systems; updating the user profile of the first user based on the user profiles of at least a subset of the other users, the updating including generating at least one missing ranking, the updating including: for each of a subset of the other users whose user profiles include a pairwise ranking for a selected pair of the machine translation systems, computing a similarity between the first user's user profile and the respective other user's user profile; identifying, based on the computed similarities, a set of the other users as nearest neighbors to the first user, the identifying comprising applying at least one criterion for inclusion of the other users in the nearest neighbors; and computing a pairwise ranking for the pair of the machine translation systems as a function of the pairwise rankings of the nearest neighbors for the selected pair of machine translation systems, wherein when a number of the nearest neighbors does not meet a threshold number of nearest neighbors, the pairwise ranking for the pair of the machine translation systems is computed as a function of the pairwise rankings of at least one other of the users in addition to the nearest neighbors; predicting an optimal machine translation system for the first user from the set of machine translation systems based on the pairwise rankings for the pairs of machine translation systems in the updated user profile computed for the first user for translation of source text in a source language to target text in a target language; outputting a machine translation of source text in the target language for the first user, based on the prediction; and wherein at least one of the updating and the predicting of the optimal translation system is performed with a processor. | 1. A method for predicting an optimal machine translation system for a user comprising: for each of a set of users, providing a respective user profile which includes rankings for at least some machine translation systems from a set of machine translation systems, the set of users including a first user and a plurality of other users, wherein the rankings are pairwise rankings for pairs of machine translation systems; updating the user profile of the first user based on the user profiles of at least a subset of the other users, the updating including generating at least one missing ranking, the updating including: for each of a subset of the other users whose user profiles include a pairwise ranking for a selected pair of the machine translation systems, computing a similarity between the first user's user profile and the respective other user's user profile; identifying, based on the computed similarities, a set of the other users as nearest neighbors to the first user, the identifying comprising applying at least one criterion for inclusion of the other users in the nearest neighbors; and computing a pairwise ranking for the pair of the machine translation systems as a function of the pairwise rankings of the nearest neighbors for the selected pair of machine translation systems, wherein when a number of the nearest neighbors does not meet a threshold number of nearest neighbors, the pairwise ranking for the pair of the machine translation systems is computed as a function of the pairwise rankings of at least one other of the users in addition to the nearest neighbors; predicting an optimal machine translation system for the first user from the set of machine translation systems based on the pairwise rankings for the pairs of machine translation systems in the updated user profile computed for the first user for translation of source text in a source language to target text in a target language; outputting a machine translation of source text in the target language for the first user, based on the prediction; and wherein at least one of the updating and the predicting of the optimal translation system is performed with a processor. 7. The method of claim 1 , wherein each machine translation system in the set of machine translation systems is configured for translating source text from a same source language into target text in a same target language as the other machine translation systems in the set of machine translation systems. | 0.636038 |
9,032,374 | 21 | 22 | 21. A computer program product, comprising: one or more non-transitory computer useable storage media; program logic stored on said computer useable media for programming a data processing platform to perform software debugging using annotation metadata, as by: maintaining a set of metadata comprising metadata topics that describes operational features of said source code components of a software program by storing the metadata in a metadata container stored separately from the source code; maintaining data/metadata relationships by storing one or more context discriminants in the metadata container that describes said data/metadata relationships between individual metadata topics and individual units of said source code; displaying one or more metadata topics for user selection; setting one or more software debugging points in said software program that is associated with one or more metadata topics, said setting comprising using said one or more context discriminants associated with the selected one or more units of said metadata to identify one or more locations in said source code where said one or more debugging points should be set, wherein said metadata selected by way of a first user input in said user interface, said one or more debugging points not being present in said software program prior to said setting; and performing a debugging action when execution of said software program reaches said debugging points in response to a second user input in said user interface. | 21. A computer program product, comprising: one or more non-transitory computer useable storage media; program logic stored on said computer useable media for programming a data processing platform to perform software debugging using annotation metadata, as by: maintaining a set of metadata comprising metadata topics that describes operational features of said source code components of a software program by storing the metadata in a metadata container stored separately from the source code; maintaining data/metadata relationships by storing one or more context discriminants in the metadata container that describes said data/metadata relationships between individual metadata topics and individual units of said source code; displaying one or more metadata topics for user selection; setting one or more software debugging points in said software program that is associated with one or more metadata topics, said setting comprising using said one or more context discriminants associated with the selected one or more units of said metadata to identify one or more locations in said source code where said one or more debugging points should be set, wherein said metadata selected by way of a first user input in said user interface, said one or more debugging points not being present in said software program prior to said setting; and performing a debugging action when execution of said software program reaches said debugging points in response to a second user input in said user interface. 22. A computer program product in accordance with claim 21 wherein said second user input comprises a selection of one or more metadata topics and said debugging action comprises executing all source code associated with said one or more metadata topics selected by said second user input. | 0.667816 |
8,041,746 | 1 | 6 | 1. A computer-implemented method for mapping a first schema to a second schema, the method comprising: identifying a first schema that includes a plurality of first data element definitions, each of the first data element definitions defining a semantic of a data portion in first electronic documents that are generated according to a format of the first schema, wherein each of the first data element definitions in the first schema is uniquely identified by a respective first name; receiving an indication that the first schema is to be mapped to a second schema, the first and second schemas being different from each other such that a computer system configured according to the second schema is unable to semantically interpret the first electronic documents, wherein a naming rule specifies a process to generate a name for a data element from a human-understandable description for the data element by performing linguistic analysis on the human-understandable description for the data element, wherein each of multiple second data element definitions in the second schema is uniquely identified by a respective second name generated using the naming rule, wherein the first names that identify the first data element definitions in the first schema are not generated using the naming rule; generating a new name for each of the first data element definitions from the human-understandable description for each of the first data element definitions by applying the process that is specified by the naming rule to the human-understandable description for each of the first data element definitions, wherein the second names and the new names are defined by Core Components Technical Specification (CCTS) standard, and wherein the first names are not defined by the CCTS standard; and mapping at least one of the first data element definitions in the first schema to a corresponding one of the second data element definitions in the second schema based on the new name for the one of the first data element definitions in the first schema matching the second name of the one of the second data element definition in the second schema. | 1. A computer-implemented method for mapping a first schema to a second schema, the method comprising: identifying a first schema that includes a plurality of first data element definitions, each of the first data element definitions defining a semantic of a data portion in first electronic documents that are generated according to a format of the first schema, wherein each of the first data element definitions in the first schema is uniquely identified by a respective first name; receiving an indication that the first schema is to be mapped to a second schema, the first and second schemas being different from each other such that a computer system configured according to the second schema is unable to semantically interpret the first electronic documents, wherein a naming rule specifies a process to generate a name for a data element from a human-understandable description for the data element by performing linguistic analysis on the human-understandable description for the data element, wherein each of multiple second data element definitions in the second schema is uniquely identified by a respective second name generated using the naming rule, wherein the first names that identify the first data element definitions in the first schema are not generated using the naming rule; generating a new name for each of the first data element definitions from the human-understandable description for each of the first data element definitions by applying the process that is specified by the naming rule to the human-understandable description for each of the first data element definitions, wherein the second names and the new names are defined by Core Components Technical Specification (CCTS) standard, and wherein the first names are not defined by the CCTS standard; and mapping at least one of the first data element definitions in the first schema to a corresponding one of the second data element definitions in the second schema based on the new name for the one of the first data element definitions in the first schema matching the second name of the one of the second data element definition in the second schema. 6. The method of claim 1 , wherein generating the new name for each first data element definition comprises transforming the first schema into a transformed schema, wherein the transformed schema includes, for each first data element definition in the first schema, a corresponding transformed data element definition that is uniquely identified by the new name for the corresponding first data element definition, and wherein each transformed data element definition identifies a first name of the corresponding first data element definition. | 0.642763 |
9,444,934 | 1 | 9 | 1. A method comprising: receiving, at a processor of a computing device, an audio voice signal of a first call participant during a first call, wherein the first call is a communication across a communication network; determining, by the processor of the computing device, an identity of the first call participant; determining, by the processor of the computing device, a speech to text profile associated with the identity of the first call participant, wherein the speech to text profile comprises a plurality of rules, and further wherein each of the plurality of rules is a rule for transcribing a word in the audio voice signal into text; and wherein the speech to text profile is adequately trained when a number of the plurality of rules reaches a predetermined threshold; and generating, by the processor of the computing device, a text output, wherein the text output is a transcribed version of a plurality of words identified in the audio voice signal of the first call participant, and further wherein at least one of the plurality of words identified is identified using at least one rule of the plurality of rules; and wherein the speech to text profile is used to generate a text output after the speech to text profile has been adequately trained. | 1. A method comprising: receiving, at a processor of a computing device, an audio voice signal of a first call participant during a first call, wherein the first call is a communication across a communication network; determining, by the processor of the computing device, an identity of the first call participant; determining, by the processor of the computing device, a speech to text profile associated with the identity of the first call participant, wherein the speech to text profile comprises a plurality of rules, and further wherein each of the plurality of rules is a rule for transcribing a word in the audio voice signal into text; and wherein the speech to text profile is adequately trained when a number of the plurality of rules reaches a predetermined threshold; and generating, by the processor of the computing device, a text output, wherein the text output is a transcribed version of a plurality of words identified in the audio voice signal of the first call participant, and further wherein at least one of the plurality of words identified is identified using at least one rule of the plurality of rules; and wherein the speech to text profile is used to generate a text output after the speech to text profile has been adequately trained. 9. The method of claim 1 , wherein the speech to text profile is adequately trained when a number of calls involving the first call participant reaches a predetermined threshold. | 0.770619 |
7,529,852 | 24 | 25 | 24. A computer program product as recited in claim 23 , wherein the operation of generating the IPv4 reply comprises: when a valid IPv6 reply is received from the IPv6 DNS Server in response to either the second IPv6 query having the IP6.ARPA string or the first IPv6 query having the IP6.INT string, translating the valid IPv6 reply into a valid IPv4 reply and dropping any other replies received in response to either the second IPv6 query having the IP6.ARPA string or the first IPv6 query having the IP6.INT string; and when a valid IPv6 reply is not received from the IPv6 DNS Server in response to either the second IPv6 query having the IP6.ARPA string or the first IPv6 query having the IP6.INT string but at least one “no answer” IPv6 reply is received from the IPv6 DNS Server in response to either the second IPv6 query having the IP6.ARPA string or the first IPv6 query having the IP6.INT string, translating one of the received “no answer” IPv6 replies into a “no answer” IPv4 reply. | 24. A computer program product as recited in claim 23 , wherein the operation of generating the IPv4 reply comprises: when a valid IPv6 reply is received from the IPv6 DNS Server in response to either the second IPv6 query having the IP6.ARPA string or the first IPv6 query having the IP6.INT string, translating the valid IPv6 reply into a valid IPv4 reply and dropping any other replies received in response to either the second IPv6 query having the IP6.ARPA string or the first IPv6 query having the IP6.INT string; and when a valid IPv6 reply is not received from the IPv6 DNS Server in response to either the second IPv6 query having the IP6.ARPA string or the first IPv6 query having the IP6.INT string but at least one “no answer” IPv6 reply is received from the IPv6 DNS Server in response to either the second IPv6 query having the IP6.ARPA string or the first IPv6 query having the IP6.INT string, translating one of the received “no answer” IPv6 replies into a “no answer” IPv4 reply. 25. A computer program product as recited in claim 24 , the computer program instructions stored within the at least one computer readable product being further configured for: setting a timer to a predefined value after the IPv4 query has been received, wherein the operations of translating the valid IPv6 reply or a one of the “no answer”replies are only performed if the timer has not expired. | 0.860897 |
8,775,447 | 12 | 13 | 12. The method of claim 1 , wherein the one or more transformations are applied by at least one dataflow graph that includes nodes representing data processing components connected by links representing flows of records between data processing components, with each dataset to which the transformations are being applied providing an input flow of records to the dataflow graph. | 12. The method of claim 1 , wherein the one or more transformations are applied by at least one dataflow graph that includes nodes representing data processing components connected by links representing flows of records between data processing components, with each dataset to which the transformations are being applied providing an input flow of records to the dataflow graph. 13. The method of claim 12 , wherein the dataflow graph is executed successively in multiple iterations using a respective one of the multiple datasets to provide an input flow of records, in the determined processing order for the multiple datasets. | 0.948197 |
8,255,572 | 4 | 5 | 4. The computing system implemented process for identifying 419 messages in a live message stream of claim 1 , further comprising: if, as a result of the analysis of the message by the dynamic feedback-based heuristic filter stage, the message is determined to be a potential 419 message, in addition to removing the message from further processing by the computing system implemented process for identifying 419 messages in a live message stream, data indicating a status of the message is transformed to data indicating a status of potential 419 message and the message is subjected to one or more protective actions. | 4. The computing system implemented process for identifying 419 messages in a live message stream of claim 1 , further comprising: if, as a result of the analysis of the message by the dynamic feedback-based heuristic filter stage, the message is determined to be a potential 419 message, in addition to removing the message from further processing by the computing system implemented process for identifying 419 messages in a live message stream, data indicating a status of the message is transformed to data indicating a status of potential 419 message and the message is subjected to one or more protective actions. 5. The computing system implemented process for identifying 419 messages in a live message stream of claim 4 , wherein: at least one of the one or more protective actions is selected from the group of protective actions consisting of: blocking the message from the user computing system; quarantining the message; performing further analysis of the message; labeling or tagging the message as spam/scam or potential spam/scam; redirection of the message to a specific address or location for further processing; and buffering the message. | 0.942948 |
7,567,895 | 14 | 15 | 14. The method of claim 13 wherein a feature representation includes a keyword feature, a lexical feature, and a pattern feature. | 14. The method of claim 13 wherein a feature representation includes a keyword feature, a lexical feature, and a pattern feature. 15. The method of claim 14 wherein the pattern feature is based on similarity of a sentence to be a generalized sentence pattern of sentences within training data. | 0.92072 |
8,019,783 | 10 | 11 | 10. The system of claim 9 , wherein each of said plurality of entity types is defined to include a corresponding set of attributes, wherein said enabling comprises: identifying the attributes associated with said first entity type and said at least one of said second set of entity types; displaying the identified attributes on said display unit; and receiving from said user respective data values associated with corresponding ones of a desired set of attributes. | 10. The system of claim 9 , wherein each of said plurality of entity types is defined to include a corresponding set of attributes, wherein said enabling comprises: identifying the attributes associated with said first entity type and said at least one of said second set of entity types; displaying the identified attributes on said display unit; and receiving from said user respective data values associated with corresponding ones of a desired set of attributes. 11. The system of claim 10 , wherein said identifying comprises examining data representing a schema defining said plurality of entity types in said database system, wherein said schema further defines attributes of each entity type and specifies the primary entity and the secondary entity for each of said plurality of relationships. | 0.900534 |
7,827,100 | 36 | 39 | 36. The computer-readable medium of claim 35 , wherein the method further comprises: obtaining a second credit score for another debtor; selecting another score band from the second credit score; and applying another scoring expression assigned to the other score band to another raw credit data and another tax form data to determine another collections score for the other debtor. | 36. The computer-readable medium of claim 35 , wherein the method further comprises: obtaining a second credit score for another debtor; selecting another score band from the second credit score; and applying another scoring expression assigned to the other score band to another raw credit data and another tax form data to determine another collections score for the other debtor. 39. The computer-readable medium of claim 36 , wherein the first scoring expression utilizes a same variable as the other scoring expression with a different weight. | 0.893273 |
10,055,470 | 11 | 12 | 11. The system of claim 7 , wherein the output module is further configured to: generate pivot data based on the calculated values. | 11. The system of claim 7 , wherein the output module is further configured to: generate pivot data based on the calculated values. 12. The system of claim 11 , wherein the output module is further configured to format the pivot data to generate output data, wherein the data presentation is generated based on the output data. | 0.947665 |
8,010,979 | 17 | 24 | 17. A non-transitory computer readable medium having computer readable program codes embodied therein for performing interactive television program guide operations, the non-transitory computer readable medium program codes performing functions comprising: allowing an operator to update a functionality characteristic of an interactive television program guide implemented on a user television equipment; allowing the operator to remotely supply a markup language document to the interactive television program guide implemented on the user television equipment; updating the functionality characteristic of the interactive television program guide based on the markup language document using the interactive television program guide; and generating a program guide display screen on the user television equipment having the functionality characteristic of the interactive television program guide as updated based on the markup language document. | 17. A non-transitory computer readable medium having computer readable program codes embodied therein for performing interactive television program guide operations, the non-transitory computer readable medium program codes performing functions comprising: allowing an operator to update a functionality characteristic of an interactive television program guide implemented on a user television equipment; allowing the operator to remotely supply a markup language document to the interactive television program guide implemented on the user television equipment; updating the functionality characteristic of the interactive television program guide based on the markup language document using the interactive television program guide; and generating a program guide display screen on the user television equipment having the functionality characteristic of the interactive television program guide as updated based on the markup language document. 24. The non-transitory computer readable medium defined in claim 17 wherein the markup language document is a Hyper Text Markup Language document, a Dynamic Hyper Text Markup Language document, or an Extensible Markup Language document. | 0.572464 |
9,070,036 | 1 | 16 | 1. A method of collecting content of notes, comprising: capturing, by a sensor of a computing device, an image, comprising a visual representation of a scene having a plurality of physical notes, each of the physical notes comprising a separate physical object having a predefined boundary and recognizable content thereon; processing, by a processing unit of the computing device, image data associated with the image to identify a predefined boundary of one of the plurality of physical notes from the visual representation; extracting, by the processing unit and based at least in part on identifying the predefined boundary, from the image data the recognizable content from within the predefined boundary of the one of the plurality of physical notes and based at least in part on a contrast between the recognizable content and a background of the one of the plurality of physical notes from the visual representation; and associating the recognizable content with a digital representative of the one of the plurality of physical notes. | 1. A method of collecting content of notes, comprising: capturing, by a sensor of a computing device, an image, comprising a visual representation of a scene having a plurality of physical notes, each of the physical notes comprising a separate physical object having a predefined boundary and recognizable content thereon; processing, by a processing unit of the computing device, image data associated with the image to identify a predefined boundary of one of the plurality of physical notes from the visual representation; extracting, by the processing unit and based at least in part on identifying the predefined boundary, from the image data the recognizable content from within the predefined boundary of the one of the plurality of physical notes and based at least in part on a contrast between the recognizable content and a background of the one of the plurality of physical notes from the visual representation; and associating the recognizable content with a digital representative of the one of the plurality of physical notes. 16. The method of claim 1 , wherein the computing device comprises a mobile computing device. | 0.794248 |
4,695,975 | 13 | 17 | 13. The visual communications device as claimed in claim 1, wherein at least some of said natural language words each have a plurality of image addresses associated therewith and stored in said image dictionary memory means, and said control means includes selector means for choosing for display a particular one of the plurality of images when a plurality of such image addresses are obtained by the addressing of said image dictionary memory means. | 13. The visual communications device as claimed in claim 1, wherein at least some of said natural language words each have a plurality of image addresses associated therewith and stored in said image dictionary memory means, and said control means includes selector means for choosing for display a particular one of the plurality of images when a plurality of such image addresses are obtained by the addressing of said image dictionary memory means. 17. The visual communications system as claimed in claim 13, further comprising text buffer means for storing a plurality of said natural language words occurring in time sequence over a duration including the natural language word currently addressing said image dictionary memory means, wherein said image dictionary memory means has stored along with the image addresses of at least some of said plurality of images a context description, and wherein the choosing by said selection means is responsive to a comparison between the context description and the contents of said text buffer means. | 0.819394 |
9,996,566 | 25 | 26 | 25. The system according to claim 1 and also comprising an experiment system. | 25. The system according to claim 1 and also comprising an experiment system. 26. The system according to claim 25 and wherein said experiment system comprises: an experiment creator to receive said alternate visual data structures and to present them to a user as part of a controlled experiment; and an experiment analyzer to analyze results of said selection of a visual data structure by said user to provide statistical information on preferred visual data structures for said visual design system. | 0.878986 |
6,151,021 | 1 | 11 | 1. A method comprising the steps, performed by a data processing system, of: executing program code in the data processing system to display a note, wherein the note has contents and a location; and, executing program code in the data processing system to add a representation of the contents of the note and the location of the note to an index, wherein the location of the note added to the index is with respect to an object within a window. | 1. A method comprising the steps, performed by a data processing system, of: executing program code in the data processing system to display a note, wherein the note has contents and a location; and, executing program code in the data processing system to add a representation of the contents of the note and the location of the note to an index, wherein the location of the note added to the index is with respect to an object within a window. 11. The method of claim 1 wherein the object is a sound. | 0.923077 |
7,620,607 | 1 | 8 | 1. A system for generating annotations of a document, comprising: a processor; a memory coupled to the processor; computer code loaded into the memory for implementing the following functionality: a plurality of neurons organized as a bidirectional neural network, the neurons being associated with words (word-neurons), and sentences (sentence-neurons), and the sentences being extracted from documents, wherein the word-neurons are organized into a first layer and the sentence-neurons are organized into a second layer, the first layer being a layer into which the input query is inputted, wherein at least some of the word-neurons of the first layer have connections between each other, and wherein the word-neurons include additional words, different from the search query, generated by the neural network from the sentences; (a) an activity regulator that regulates a sum of all activity of all active neurons of the neural network that are excited at any given time; and (b) in response to a user interactively changing a context of an input query, means for displaying sentences corresponding to the sentence-neurons to a user and identifying the sentence-neurons that correspond to sentences taken from the documents having the highest relevance to document meaning based on a predetermined percentage of document meaning, (c) wherein the predetermined percentage of document meaning is a function of percentage of meaning of the sentences; (d) wherein the percentage of meaning of each sentence, describing the degree of relevance of the sentence to the document, is calculated by the bidirectional neural network, and (e) wherein the taken sentences represent the annotations of a selected document. | 1. A system for generating annotations of a document, comprising: a processor; a memory coupled to the processor; computer code loaded into the memory for implementing the following functionality: a plurality of neurons organized as a bidirectional neural network, the neurons being associated with words (word-neurons), and sentences (sentence-neurons), and the sentences being extracted from documents, wherein the word-neurons are organized into a first layer and the sentence-neurons are organized into a second layer, the first layer being a layer into which the input query is inputted, wherein at least some of the word-neurons of the first layer have connections between each other, and wherein the word-neurons include additional words, different from the search query, generated by the neural network from the sentences; (a) an activity regulator that regulates a sum of all activity of all active neurons of the neural network that are excited at any given time; and (b) in response to a user interactively changing a context of an input query, means for displaying sentences corresponding to the sentence-neurons to a user and identifying the sentence-neurons that correspond to sentences taken from the documents having the highest relevance to document meaning based on a predetermined percentage of document meaning, (c) wherein the predetermined percentage of document meaning is a function of percentage of meaning of the sentences; (d) wherein the percentage of meaning of each sentence, describing the degree of relevance of the sentence to the document, is calculated by the bidirectional neural network, and (e) wherein the taken sentences represent the annotations of a selected document. 8. The system of claim 1 , wherein the user can inhibit neurons of the neural network by indicating irrelevance of a sentence neuron. | 0.81108 |
Subsets and Splits