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1. A method of communication, messaging and searching in a network comprising the steps of: storing one or more user profiles, preferences, subscribers and subscriptions, dynamic relationships or connections among said users and privacy settings at a central unit; determining one or more target recipients by a sender; allowing the sender to perform one or more activities in one or more networks based on one or more applications, services, multimedia contents, user connections, communication, interactions, sharing and collaboration among users and/or to send one or more messages to the one or more target recipients via the central unit; receiving one or more messages from the sender at the central unit or auto-generating one or more messages and dynamically associating accessible metadata, fields, parameters and links with said auto generated messages based on monitoring, storing and managing of said one or more related activities, actions, events and transactions by the central unit; storing and processing said messages at the central unit; determining one or more target recipients by the central unit based on one or more preferences; sending to the one or more target recipients a representation of the one or more messages by the central unit; presenting one or more messages in chronological order and as per the target recipients' preferences and privacy settings by the central unit; and allowing the user to access one or more accessible metadata, fields, parameters and links associated with a message to view links and profile, communicate, collaborate, share and participate in the same activity as the sender, to subscribe to source of the message by searching or selecting said message(s) or message(s) associated one or more accessible metadata and links. | 1. A method of communication, messaging and searching in a network comprising the steps of: storing one or more user profiles, preferences, subscribers and subscriptions, dynamic relationships or connections among said users and privacy settings at a central unit; determining one or more target recipients by a sender; allowing the sender to perform one or more activities in one or more networks based on one or more applications, services, multimedia contents, user connections, communication, interactions, sharing and collaboration among users and/or to send one or more messages to the one or more target recipients via the central unit; receiving one or more messages from the sender at the central unit or auto-generating one or more messages and dynamically associating accessible metadata, fields, parameters and links with said auto generated messages based on monitoring, storing and managing of said one or more related activities, actions, events and transactions by the central unit; storing and processing said messages at the central unit; determining one or more target recipients by the central unit based on one or more preferences; sending to the one or more target recipients a representation of the one or more messages by the central unit; presenting one or more messages in chronological order and as per the target recipients' preferences and privacy settings by the central unit; and allowing the user to access one or more accessible metadata, fields, parameters and links associated with a message to view links and profile, communicate, collaborate, share and participate in the same activity as the sender, to subscribe to source of the message by searching or selecting said message(s) or message(s) associated one or more accessible metadata and links. 28. A client device communicatively coupled with the network device for sending and/or receiving one or more messages, searching, sharing, communication, participation with other users of network(s), said client device configured to perform the method as claimed in claim 1 . | 0.698249 |
1. A hardware computer storage device with computer executable instructions for accessing a database, comprising executable instructions to: present a user at a client computer with a set of business objects, wherein the business objects include familiar terms corresponding to information about the structure of the database; receive a plurality of selected business objects; generate a SQL query from the selected business objects, wherein the SQL query includes a SELECT clause and a FROM clause, wherein the selected business objects are associated with a selected context that includes a list of joins between tables that gives meaning to the selected business objects, wherein the selected context is chosen from several contexts applicable to the SQL query; receive a condition used to restrict the scope of values returned from the database; translate the condition into a WHERE clause in the SQL query; transmit the SQL query to the database; and receive a tabular result set. | 1. A hardware computer storage device with computer executable instructions for accessing a database, comprising executable instructions to: present a user at a client computer with a set of business objects, wherein the business objects include familiar terms corresponding to information about the structure of the database; receive a plurality of selected business objects; generate a SQL query from the selected business objects, wherein the SQL query includes a SELECT clause and a FROM clause, wherein the selected business objects are associated with a selected context that includes a list of joins between tables that gives meaning to the selected business objects, wherein the selected context is chosen from several contexts applicable to the SQL query; receive a condition used to restrict the scope of values returned from the database; translate the condition into a WHERE clause in the SQL query; transmit the SQL query to the database; and receive a tabular result set. 3. The hardware computer storage device of claim 1 further comprising executable instructions to: define a list of joins between tables in the database to characterize a set of linked tables, wherein a join is a relational synchronization between tables; add a union of the set of linked tables to the FROM clause if the set of linked tables is linked by one path; add a union of the set of linked tables along a particular path defined by the selected context to the FROM clause if the set of linked tables are linked by multiple paths, wherein the selected context includes a set of joins including all of the tables in the set of linked tables; and add a union of the set of linked tables arranged along all joins in the list of joins to the FROM clause if the set of linked tables is linked by multiple paths but no context exists. | 0.5 |
9. The searching device according to claim 5 , further comprising: a count unit counting the number of the same facility information as facility information stored in said storage unit by said history storing unit; and a weight storage unit storing a weight based on the number counted by the count unit, by associating the weight with facility information, wherein said extraction unit extracts facility information corresponding to the previous searching keyword and the facility information or attribute received by said reception unit, by referring to the previous searching keyword that is obtained after changing by said change unit, the facility information and the attribute that are stored in said storage unit, as well as said weight associated with the facility information stored by said weight storage unit. | 9. The searching device according to claim 5 , further comprising: a count unit counting the number of the same facility information as facility information stored in said storage unit by said history storing unit; and a weight storage unit storing a weight based on the number counted by the count unit, by associating the weight with facility information, wherein said extraction unit extracts facility information corresponding to the previous searching keyword and the facility information or attribute received by said reception unit, by referring to the previous searching keyword that is obtained after changing by said change unit, the facility information and the attribute that are stored in said storage unit, as well as said weight associated with the facility information stored by said weight storage unit. 11. The searching device according to claim 9 , further comprising an extraction number counting unit counting the number of extraction times facility information is extracted by said extraction unit, wherein said weight storage unit stores, in association with facility information, a weight based on the number counted by said count unit and the extraction number counted by said extraction number counting unit. | 0.811956 |
3. The method of claim 1 , wherein the computing a similarity measure comprises computing at least one factored word sequence kernel. | 3. The method of claim 1 , wherein the computing a similarity measure comprises computing at least one factored word sequence kernel. 5. The method of claim 3 , wherein the factored word sequence kernel has the general form: K n ( s , t ) = ∑ I , J λ l ( I ) + l ( J ) ∏ k = 1 n A ( s i k , t j k ) where: S and t represent the first and second sequences; n represents a length of the shared subsequences to be used in the computation; I and J represent two of the subsequences of size n of indices ranging on the positions of the symbols in s and t respectively; λ represents an optional decay factor which weights gaps in non-contiguous sequences; l (I) represents the length, as the number of symbols plus any gaps, spanned by the subsequence I in s ; l (J) represents the length, as the number of symbols plus any gaps, spanned by the subsequence J in t, respectively; and A(s i k ,t j k ) is a function of two symbols s i k ,t j k in the sequences s and t respectively, the function quantifying the similarity between the two symbols according to the set of factors. | 0.646711 |
13. A system comprising: a processor connected to Internet resources; and a computer readable storage medium having instructions stored which, when executed by the processor, cause the processor to perform operations comprising: identifying, via the processor communicating with Internet resources, common task independent web-sentences based on frequently occurring phrases across multiple websites from a web domain stored in a data store; selectively removing the common task independent web-sentences from the web domain data, to yield filtered web domain data comprising domain-specific data; identifying, via the processor, predicate/argument pairs from the filtered web domain data; replacing, via the processor, the predicate/argument pairs with predicate/argument tokens; generating, via the processor, conversational utterances by merging the predicate/argument tokens with manually written conversational templates while preserving a relative frequency of the manually written conversational templates, to yield generated conversational utterances; and generating, via the processor, a web data language model using the generated conversational utterances, and providing it as an initial language model for deployment of an automated speech recognition system. | 13. A system comprising: a processor connected to Internet resources; and a computer readable storage medium having instructions stored which, when executed by the processor, cause the processor to perform operations comprising: identifying, via the processor communicating with Internet resources, common task independent web-sentences based on frequently occurring phrases across multiple websites from a web domain stored in a data store; selectively removing the common task independent web-sentences from the web domain data, to yield filtered web domain data comprising domain-specific data; identifying, via the processor, predicate/argument pairs from the filtered web domain data; replacing, via the processor, the predicate/argument pairs with predicate/argument tokens; generating, via the processor, conversational utterances by merging the predicate/argument tokens with manually written conversational templates while preserving a relative frequency of the manually written conversational templates, to yield generated conversational utterances; and generating, via the processor, a web data language model using the generated conversational utterances, and providing it as an initial language model for deployment of an automated speech recognition system. 14. The system of claim 13 , wherein the parser identifies predicates/argument pairs by semantically parsing the filtered web domain data. | 0.635021 |
1. A method comprising: receiving a user utterance as part of a natural language dialog with a human user; applying a word n-gram classifier to the user utterance to obtain a first call type for the utterance; when a confidence associated with the first call type meets a threshold level, associating the user utterance with the first call type to yield a classified utterance; when the confidence associated with the first call type does not meet the threshold level, performing the steps of: (i) generating a semantic and syntactic graph associated with the user utterance; (ii) converting the semantic and syntactic graph into a first finite state transducer; (iii) composing the first finite state transducer with a second finite state transducer to form a third finite state transducer, wherein the second finite state transducer comprises all possible n-grams, and wherein the third finite state transducer comprises n-grams; (iv) extracting the n-grams as features from the third finite state transducer, to yield extracted n-grams; and (v) associating the user utterance with a second call type based on the extracted n-grams, to yield a classified utterance, wherein the second call type is determined based on semantic and syntactic features in the extracted n-grams; and responding to the human user in the natural language dialog based on the classified utterance. | 1. A method comprising: receiving a user utterance as part of a natural language dialog with a human user; applying a word n-gram classifier to the user utterance to obtain a first call type for the utterance; when a confidence associated with the first call type meets a threshold level, associating the user utterance with the first call type to yield a classified utterance; when the confidence associated with the first call type does not meet the threshold level, performing the steps of: (i) generating a semantic and syntactic graph associated with the user utterance; (ii) converting the semantic and syntactic graph into a first finite state transducer; (iii) composing the first finite state transducer with a second finite state transducer to form a third finite state transducer, wherein the second finite state transducer comprises all possible n-grams, and wherein the third finite state transducer comprises n-grams; (iv) extracting the n-grams as features from the third finite state transducer, to yield extracted n-grams; and (v) associating the user utterance with a second call type based on the extracted n-grams, to yield a classified utterance, wherein the second call type is determined based on semantic and syntactic features in the extracted n-grams; and responding to the human user in the natural language dialog based on the classified utterance. 9. The method of claim 1 , wherein classifying the user utterance further comprises classifying the user utterance using one of: the extracted n-grams, the semantic, and syntactic graph and writing rules. | 0.570472 |
1. A method for harvesting assets for packaged software application configuration, comprising: obtaining one or more documents defining deployment procedures associated with deploying a packaged software application; extracting content and style from the one or more documents, the content including one or more segmented elements of the one or more documents, the one or more segmented elements of the one or more documents include section, subsection, list or table, or combinations thereof, the style including one or more formats of the elements, the formats of the elements include font, color, texture, indentation, page layout, page number, footnote, header, image size, or spacing or combinations thereof; creating one or more document objects corresponding to respective one or more elements of the extracted content and style, and populating the one or more document objects with the respective one or more elements of the extracted content and the extracted style; storing the one or more document objects as assets in an asset repository; enhancing the content in the one or more documents; and cleansing the content and style according to one or more rules, wherein the cleansing further includes merging duplicate content if a duplicate in the content is discover, wherein the enhancing the content in the one or more documents includes adding information associated with identification of a process or user performing the cleansing, date, name of the process or the user, or project information, or combinations thereof, associated with the cleansing, and wherein the storing the one or more document objects as assets in an asset repository further includes: presenting to a user the one or more document objects with content, form, and metadata; enabling the user to select an output type format; generating the one or more document objects in the selected output type format; and storing the generated one or more document objects in the selected output type format. | 1. A method for harvesting assets for packaged software application configuration, comprising: obtaining one or more documents defining deployment procedures associated with deploying a packaged software application; extracting content and style from the one or more documents, the content including one or more segmented elements of the one or more documents, the one or more segmented elements of the one or more documents include section, subsection, list or table, or combinations thereof, the style including one or more formats of the elements, the formats of the elements include font, color, texture, indentation, page layout, page number, footnote, header, image size, or spacing or combinations thereof; creating one or more document objects corresponding to respective one or more elements of the extracted content and style, and populating the one or more document objects with the respective one or more elements of the extracted content and the extracted style; storing the one or more document objects as assets in an asset repository; enhancing the content in the one or more documents; and cleansing the content and style according to one or more rules, wherein the cleansing further includes merging duplicate content if a duplicate in the content is discover, wherein the enhancing the content in the one or more documents includes adding information associated with identification of a process or user performing the cleansing, date, name of the process or the user, or project information, or combinations thereof, associated with the cleansing, and wherein the storing the one or more document objects as assets in an asset repository further includes: presenting to a user the one or more document objects with content, form, and metadata; enabling the user to select an output type format; generating the one or more document objects in the selected output type format; and storing the generated one or more document objects in the selected output type format. 2. The method of claim 1 , wherein the cleansing includes deleting information associated with specific identification of projects. | 0.809798 |
1. A system to facilitate information sharing between databases, comprising: a plurality of independently functioning database systems each including at least one data processing apparatus with an associated digital memory and being coupled remotely to a data communication network, each of the database systems maintaining data fields that store values of variables having locally predetermined meanings, formatting attributes and relationships according to a database schema that is specific the respective said database system, and wherein the meanings and formatting attributes of the variable and the data fields, and labels applied thereto, differ arbitrarily among the plurality of database systems; wherein at least certain variables and data fields in at least two of the database systems maintain values of variables that have substantially equal conceptual meanings; a universal index server including at least one data processing apparatus with an associated digital memory, the universal index server being coupled remotely to the at least two database systems over the data communication network, wherein the universal index server is configured to maintain a lexicon of entries for diverse variables, definitions that contain meanings and formatting attributes of the variables being associated with the entries in the lexicon, and documented by information made universally available to at least a subset of the plurality of independently functioning database systems; wherein at least one of said universal index server and said at least two database systems supports a comparison process for comparing the locally predetermined meanings and formatting attributes of the variables of the at least two database systems, against the meanings and formatting attributes stored in the universal server, wherein the programmed comparison process produces for each of the database systems a cross-reference by which certain said variables of the at least two database systems are referenced separately for each of the at least two database systems, against entries in the lexicon maintained in the universal index server; wherein variables with locally predetermined meanings in the at least two database systems are referenced against corresponding definitions in the lexicon, and including translation parameters where required for converting between the locally determined formatting attributes and the formatting attributes for corresponding variables in the lexicon; wherein the at least two database systems are configured for at least one of transmitting and receiving variable values that are referenced to said entries in the lexicon with respect to said meanings and formatted to comply with the formatting attributes stored in the universal server; wherein the universal index server is configured to extend the lexicon upon demand by adding additional variables responsive to inputs received over the network, and wherein the additional variables comprise at least one of more general categorization variables encompassing variables that are broader in meaning than variables already in the lexicon, and more specific itemization variables that represent subcategories of variables already appearing in the lexicon. | 1. A system to facilitate information sharing between databases, comprising: a plurality of independently functioning database systems each including at least one data processing apparatus with an associated digital memory and being coupled remotely to a data communication network, each of the database systems maintaining data fields that store values of variables having locally predetermined meanings, formatting attributes and relationships according to a database schema that is specific the respective said database system, and wherein the meanings and formatting attributes of the variable and the data fields, and labels applied thereto, differ arbitrarily among the plurality of database systems; wherein at least certain variables and data fields in at least two of the database systems maintain values of variables that have substantially equal conceptual meanings; a universal index server including at least one data processing apparatus with an associated digital memory, the universal index server being coupled remotely to the at least two database systems over the data communication network, wherein the universal index server is configured to maintain a lexicon of entries for diverse variables, definitions that contain meanings and formatting attributes of the variables being associated with the entries in the lexicon, and documented by information made universally available to at least a subset of the plurality of independently functioning database systems; wherein at least one of said universal index server and said at least two database systems supports a comparison process for comparing the locally predetermined meanings and formatting attributes of the variables of the at least two database systems, against the meanings and formatting attributes stored in the universal server, wherein the programmed comparison process produces for each of the database systems a cross-reference by which certain said variables of the at least two database systems are referenced separately for each of the at least two database systems, against entries in the lexicon maintained in the universal index server; wherein variables with locally predetermined meanings in the at least two database systems are referenced against corresponding definitions in the lexicon, and including translation parameters where required for converting between the locally determined formatting attributes and the formatting attributes for corresponding variables in the lexicon; wherein the at least two database systems are configured for at least one of transmitting and receiving variable values that are referenced to said entries in the lexicon with respect to said meanings and formatted to comply with the formatting attributes stored in the universal server; wherein the universal index server is configured to extend the lexicon upon demand by adding additional variables responsive to inputs received over the network, and wherein the additional variables comprise at least one of more general categorization variables encompassing variables that are broader in meaning than variables already in the lexicon, and more specific itemization variables that represent subcategories of variables already appearing in the lexicon. 3. The system of claim 1 , wherein the programmed comparison process is configured to compare at least one of variable values and variable formatting attributes for data fields in the at least two databases against standards for commonly encountered variables, for producing a version of the cross-reference table limited to particular ones of the data fields. | 0.5 |
1. A computer program product comprising a non-transitory computer readable storage medium having program instructions embodied therewith, the program instructions executable by a processor to cause the processor to perform a method comprising: generating a time-marked word list of an automatic speech recognition system, wherein generating the time-marked word list comprises converting an indexing structure into an output, and wherein the time-marked word list comprises the output; generating an index from the time-marked word list, wherein generating the index comprises creating a word loop weighted finite state transducer for each utterance, i, of a plurality of utterances; receiving a plurality of keyword queries; and searching the index for a plurality of keyword hits; wherein the word loop weighted finite state transducer for each utterance, i, of the plurality of utterances, includes S i as a start node, E i as an end node, without a start node or an end node between S i and E i and a plurality of arcs connected between an S i to E i pair for each utterance, the plurality of arcs corresponding to each word label, start and end time, and posterior probability in the time-marked word list. | 1. A computer program product comprising a non-transitory computer readable storage medium having program instructions embodied therewith, the program instructions executable by a processor to cause the processor to perform a method comprising: generating a time-marked word list of an automatic speech recognition system, wherein generating the time-marked word list comprises converting an indexing structure into an output, and wherein the time-marked word list comprises the output; generating an index from the time-marked word list, wherein generating the index comprises creating a word loop weighted finite state transducer for each utterance, i, of a plurality of utterances; receiving a plurality of keyword queries; and searching the index for a plurality of keyword hits; wherein the word loop weighted finite state transducer for each utterance, i, of the plurality of utterances, includes S i as a start node, E i as an end node, without a start node or an end node between S i and E i and a plurality of arcs connected between an S i to E i pair for each utterance, the plurality of arcs corresponding to each word label, start and end time, and posterior probability in the time-marked word list. 19. The computer program product according to claim 1 , wherein the searching comprises an out-of-vocabulary (OOV) search, converting the index to a phone level by replacing all words with respective pronunciations, and performing a phone-based composition based on the conversion. | 0.534708 |
1. A method, executed by a computing system, for assigning publications to authors, the method comprising: for each of a plurality of publications, generating an author-name-mention data structure for each author name listed on the publication, the author-name-mention data structure comprising at least an identifier of the publication and the listed author name; associating, with each of the author-name-mention data structures, a feature set derived from the publication identified in the author-name-mention data structure; automatically clustering the author-name-mention data structures, at least in part based on comparison between the feature sets, to form a plurality of clusters each representing a disambiguated cluster author and containing one or more publications within the cluster; for a selected individual, searching one or more databases to identify social contacts of the selected individual; searching the one or more databases to automatically identify, among unassigned ones of the plurality of clusters and a plurality of author identities uniquely representing the selected individual's social contacts within the computing system, pairs of a cluster and an author identity name-compatible with the disambiguated cluster author of the cluster; and searching the one or more databases to detect, for at least one of the pairs of a cluster and a name-compatible author identity, at least one publication within the cluster that is at least one of co-authored by the selected individual or cited in a publication authored or co-authored by the selected individual, suggesting the at least one pair of a cluster and a name-compatible author identity representing one of the selected individual's social contacts as a candidate match to the selected individual with a request for confirmation that the social contact represented by the author identity is the disambiguated cluster author of the cluster, and, following receipt of the requested confirmation, assigning the cluster to the name-compatible author identity based at least in part on the confirmation. | 1. A method, executed by a computing system, for assigning publications to authors, the method comprising: for each of a plurality of publications, generating an author-name-mention data structure for each author name listed on the publication, the author-name-mention data structure comprising at least an identifier of the publication and the listed author name; associating, with each of the author-name-mention data structures, a feature set derived from the publication identified in the author-name-mention data structure; automatically clustering the author-name-mention data structures, at least in part based on comparison between the feature sets, to form a plurality of clusters each representing a disambiguated cluster author and containing one or more publications within the cluster; for a selected individual, searching one or more databases to identify social contacts of the selected individual; searching the one or more databases to automatically identify, among unassigned ones of the plurality of clusters and a plurality of author identities uniquely representing the selected individual's social contacts within the computing system, pairs of a cluster and an author identity name-compatible with the disambiguated cluster author of the cluster; and searching the one or more databases to detect, for at least one of the pairs of a cluster and a name-compatible author identity, at least one publication within the cluster that is at least one of co-authored by the selected individual or cited in a publication authored or co-authored by the selected individual, suggesting the at least one pair of a cluster and a name-compatible author identity representing one of the selected individual's social contacts as a candidate match to the selected individual with a request for confirmation that the social contact represented by the author identity is the disambiguated cluster author of the cluster, and, following receipt of the requested confirmation, assigning the cluster to the name-compatible author identity based at least in part on the confirmation. 3. The method of claim 1 , further comprising, following the detecting, comparing a feature set associated with the cluster to one or more features sets of one or more other clusters previously assigned to the name-compatible author identity to compute one or more respective feature-similarity scores, wherein the cluster is assigned to the name-compatible author identity further based at least in part on the one or more feature-similarity scores. | 0.643196 |
1. A method of processing a database query, comprising: receiving a query generated using a query builder application; identifying at least a first query condition included in the query having an associated database extension; identifying at least a second query condition included in the query having an associated parallel application extension; submitting the first query condition for execution against a database to produce a first query result, wherein the first query condition is executed according to the database extension associated with the first query condition; receiving a second query result produced by invoking an analysis routine on a parallel computer system, based on the second query condition, wherein the analysis routine is identified by the parallel application extension associated with the second query condition, the invoking comprising: transmitting, over a connection to a compute node of the parallel computing system, the second query condition and the first query result, wherein the compute node is configured to translate the second condition into a format compatible with the analysis routine, and wherein the compute node is further configured to invoke, on the parallel computing system, an execution of the analysis routine using the translated second condition and the first query result to obtain the second query result; merging the first query result and the second query result to produce merged results; and returning, as a response to the received query, the merged results. | 1. A method of processing a database query, comprising: receiving a query generated using a query builder application; identifying at least a first query condition included in the query having an associated database extension; identifying at least a second query condition included in the query having an associated parallel application extension; submitting the first query condition for execution against a database to produce a first query result, wherein the first query condition is executed according to the database extension associated with the first query condition; receiving a second query result produced by invoking an analysis routine on a parallel computer system, based on the second query condition, wherein the analysis routine is identified by the parallel application extension associated with the second query condition, the invoking comprising: transmitting, over a connection to a compute node of the parallel computing system, the second query condition and the first query result, wherein the compute node is configured to translate the second condition into a format compatible with the analysis routine, and wherein the compute node is further configured to invoke, on the parallel computing system, an execution of the analysis routine using the translated second condition and the first query result to obtain the second query result; merging the first query result and the second query result to produce merged results; and returning, as a response to the received query, the merged results. 8. The method of claim 1 , wherein a compute node of the parallel computing system is configured to translate the second query result into a format compatible with the query builder application. | 0.562937 |
1. A computer-implemented method to rank users in an online social network, comprising: determining, using a computer, a connectedness of a user on a social networking site based on a number of first-degree contacts of the user and a number of second-degree contacts of the user, wherein determining the connectedness comprises assigning a first weight to at least a portion of the first-degree contacts who have restricted respective connections with the user, and assigning a second weight to the first-degree contacts who have not restricted respective connections with the user; determining, using the computer, a number of first interactions directed from the user to at least one of the contacts by generating at least one of a matrix or a vector representative of an interaction between the user and at least one of the contacts; determining, using the computer, a number of second interactions associated with the first interaction and at least one of the contacts by generating or updating the at least one of the matrix or the vector representative of an interaction between the user and at least one of the contacts; and ranking, using the computer, the user with other users on the social networking site based on the connectedness, the first interactions, and the second interactions. | 1. A computer-implemented method to rank users in an online social network, comprising: determining, using a computer, a connectedness of a user on a social networking site based on a number of first-degree contacts of the user and a number of second-degree contacts of the user, wherein determining the connectedness comprises assigning a first weight to at least a portion of the first-degree contacts who have restricted respective connections with the user, and assigning a second weight to the first-degree contacts who have not restricted respective connections with the user; determining, using the computer, a number of first interactions directed from the user to at least one of the contacts by generating at least one of a matrix or a vector representative of an interaction between the user and at least one of the contacts; determining, using the computer, a number of second interactions associated with the first interaction and at least one of the contacts by generating or updating the at least one of the matrix or the vector representative of an interaction between the user and at least one of the contacts; and ranking, using the computer, the user with other users on the social networking site based on the connectedness, the first interactions, and the second interactions. 4. A method as defined in claim 1 , wherein ranking the user comprises determining a percentile rank of the user. | 0.676812 |
1. A system for maintaining conversational cadence, comprising: a processor; a social networking module operating on the processor, the social networking module comprising a conversational cadence module, the conversational cadence module being configured to cause the processor to perform a set of functions comprising: determining a conversational cadence associated with a user in a social network, wherein the conversational cadence is determined based on a plurality of messages previously transmitted by the user, wherein determining the conversational cadence associated with the user comprises determining an average number of messages transmitted by the user during a selected time duration and a standard deviation from the average number of messages; detecting a reduction in the conversational cadence of the user; and providing, in response to detecting the reduction in the conversational cadence of the user, a set of fill-in messages to a communications device of another user in the social network that creates an appearance to the other user in the social network of no reduction in the conversational cadence, wherein providing the set of fill-in messages comprises retroactively automatically distributing a portion of the set of fill-in messages to the other user over at least an earlier preset time period corresponding to when the reduction in the conversational cadence occurs, wherein the portion of the set of fill-in messages are retroactively automatically distributed over the earlier preset time period that corresponds to the reduction in conversational cadence of the user by automatically predating the set of fill-in messages by the processor to correlate with the conversational cadence associated with the user and each message of the portion of the set of fill-in messages indicating a time separation that correlates to the conversational cadence associated with the user. | 1. A system for maintaining conversational cadence, comprising: a processor; a social networking module operating on the processor, the social networking module comprising a conversational cadence module, the conversational cadence module being configured to cause the processor to perform a set of functions comprising: determining a conversational cadence associated with a user in a social network, wherein the conversational cadence is determined based on a plurality of messages previously transmitted by the user, wherein determining the conversational cadence associated with the user comprises determining an average number of messages transmitted by the user during a selected time duration and a standard deviation from the average number of messages; detecting a reduction in the conversational cadence of the user; and providing, in response to detecting the reduction in the conversational cadence of the user, a set of fill-in messages to a communications device of another user in the social network that creates an appearance to the other user in the social network of no reduction in the conversational cadence, wherein providing the set of fill-in messages comprises retroactively automatically distributing a portion of the set of fill-in messages to the other user over at least an earlier preset time period corresponding to when the reduction in the conversational cadence occurs, wherein the portion of the set of fill-in messages are retroactively automatically distributed over the earlier preset time period that corresponds to the reduction in conversational cadence of the user by automatically predating the set of fill-in messages by the processor to correlate with the conversational cadence associated with the user and each message of the portion of the set of fill-in messages indicating a time separation that correlates to the conversational cadence associated with the user. 10. The system of claim 1 , wherein determining the conversational cadence associated with the user comprises recording metrics related to a multiplicity of messages associated with the user. | 0.602438 |
1. A process for searching for relevant documents in a database comprising the steps of: (a) forming a database by storing for each of a plurality of documents at least one table of hash codes representing words in the document, the table(s) that represent the words in each different document being stored in a different digital data processor, each hash code comprising information at a plurality of bit locations; (b) forming a query having at least one word and a point value of relevance assigned to each word; (c) testing if the word in the query is in the database by: (1) determining the bit locations in the table at which the hash code corresponding to the queried word is stored; and (2) simultaneously testing in each of the processors the bit locations corresponding to the queried word; (d) adding at each digital data processor the point value associated with the queried word to a total point value for the document if the hash code is found at all the bit locations corresponding to the queried word that are tested in that processor; and (e) providing identification of those documents in the database with high total point values. | 1. A process for searching for relevant documents in a database comprising the steps of: (a) forming a database by storing for each of a plurality of documents at least one table of hash codes representing words in the document, the table(s) that represent the words in each different document being stored in a different digital data processor, each hash code comprising information at a plurality of bit locations; (b) forming a query having at least one word and a point value of relevance assigned to each word; (c) testing if the word in the query is in the database by: (1) determining the bit locations in the table at which the hash code corresponding to the queried word is stored; and (2) simultaneously testing in each of the processors the bit locations corresponding to the queried word; (d) adding at each digital data processor the point value associated with the queried word to a total point value for the document if the hash code is found at all the bit locations corresponding to the queried word that are tested in that processor; and (e) providing identification of those documents in the database with high total point values. 7. The process of claim 1 wherein the step of providing the identification of those documents with high total point values comprises identifying the documents in numeric order of total point value, said process comprising: (a) testing the most significant bit of the point values stored in memory in each processor; (b) setting a flag in the processor if the most significant bit is zero; (c) testing the next most significant bit of the point values stored in memory at each processor where a flag is not set; and (d) setting a second flag in the processor if the next most significant bit is zero. | 0.540541 |
9. The method of claim 8 further including automatically linking, by the computer system, the performance feedback information to the performance review document in response to designation of the selected text as feedback or in response to association of the performance feedback information with the performance review document. | 9. The method of claim 8 further including automatically linking, by the computer system, the performance feedback information to the performance review document in response to designation of the selected text as feedback or in response to association of the performance feedback information with the performance review document. 10. The method of claim 9 further including automatically embedding, by the computer system, the performance feedback information in the performance review document. | 0.850635 |
42. A method comprising: receiving, by a computer, a Web Service call that is associated with: (i) a part of a report and (ii) a Web Service, the report part associated with queries of a semantic layer, the report including a report part other than the report part associated with the Web Service call, the Web Service not associated with a Web Service call that is associated with the other report part; and determining, by a computer and based on the Web Service call that is associated with the part of the report and the Web Service, a query to return contents of the report part; wherein the Web Service includes a plurality of descriptions of Web Service calls that are to return contents of the report part and are stored in a repository. | 42. A method comprising: receiving, by a computer, a Web Service call that is associated with: (i) a part of a report and (ii) a Web Service, the report part associated with queries of a semantic layer, the report including a report part other than the report part associated with the Web Service call, the Web Service not associated with a Web Service call that is associated with the other report part; and determining, by a computer and based on the Web Service call that is associated with the part of the report and the Web Service, a query to return contents of the report part; wherein the Web Service includes a plurality of descriptions of Web Service calls that are to return contents of the report part and are stored in a repository. 47. A method according to claim 42 , wherein the Web Service call is associated with drilling parameters to specify a drilling direction, drilling steps and a drilling target, and wherein the method further comprises: determining, based on the Web Service call, a query to return drilled-down contents of the report part based on the drilling parameters. | 0.803296 |
1. A system for discriminatively pruning a language model, the system comprising: an electronic data store configured to store a corpus of training texts; and a computing device in communication with the electronic data store, the computing device configured to: obtain a confusion matrix of confusable phonemes; for a first text of the corpus of training texts, compute a first word lattice comprising the first text and an alternative hypothesis for the first text, wherein the first text comprises a first word; for a second text of the corpus of training texts, compute a second word lattice comprising the second text and an alternative hypothesis for the second text using the confusion matrix, wherein the second text comprises a second word, and wherein the alternative hypothesis for the second text comprises the second text with the first word substituted for the second word; obtain a language model comprising a plurality of trigrams; for a first trigram of the plurality of trigrams, wherein the first trigram comprises the first word in a context of two other words, determine a plurality of values using the language model without pruning the first trigram, the plurality of values comprising: a trigram probability for the first trigram; a backoff probability for the first trigram, wherein the backoff probability is computed using a backoff weight and a bigram probability, and wherein the backoff probability corresponds to a probability used in the absence of the trigram probability; a true path probability that a first true path of the first word lattice is correct, wherein the first true path comprises the first text; and an error path probability that a first error path of the second word lattice is correct, wherein the first error path the alternative hypothesis for the second text; compute a discriminative objective function value using the plurality of values, wherein the discriminative objective function value is based at least partly on a difference between (i) a first sum of values computed for individual true paths including the first true path, and (ii) a second sum of values computed for individual error paths including the first error path, wherein the value computed for the first true path is computed using the true path probability, the tri-gram probability and the backoff probability, and wherein the value computed for the first error path is computed using the error path probability, the tri-gram probability and the backoff probability; based at least in part on the discriminative objective function value, prune the first trigram from the language model to generate a pruned language model; receive, from a user computing device, an audio signal corresponding to speech of a user; and recognize the speech, via a speech recognition server, using the pruned language model. | 1. A system for discriminatively pruning a language model, the system comprising: an electronic data store configured to store a corpus of training texts; and a computing device in communication with the electronic data store, the computing device configured to: obtain a confusion matrix of confusable phonemes; for a first text of the corpus of training texts, compute a first word lattice comprising the first text and an alternative hypothesis for the first text, wherein the first text comprises a first word; for a second text of the corpus of training texts, compute a second word lattice comprising the second text and an alternative hypothesis for the second text using the confusion matrix, wherein the second text comprises a second word, and wherein the alternative hypothesis for the second text comprises the second text with the first word substituted for the second word; obtain a language model comprising a plurality of trigrams; for a first trigram of the plurality of trigrams, wherein the first trigram comprises the first word in a context of two other words, determine a plurality of values using the language model without pruning the first trigram, the plurality of values comprising: a trigram probability for the first trigram; a backoff probability for the first trigram, wherein the backoff probability is computed using a backoff weight and a bigram probability, and wherein the backoff probability corresponds to a probability used in the absence of the trigram probability; a true path probability that a first true path of the first word lattice is correct, wherein the first true path comprises the first text; and an error path probability that a first error path of the second word lattice is correct, wherein the first error path the alternative hypothesis for the second text; compute a discriminative objective function value using the plurality of values, wherein the discriminative objective function value is based at least partly on a difference between (i) a first sum of values computed for individual true paths including the first true path, and (ii) a second sum of values computed for individual error paths including the first error path, wherein the value computed for the first true path is computed using the true path probability, the tri-gram probability and the backoff probability, and wherein the value computed for the first error path is computed using the error path probability, the tri-gram probability and the backoff probability; based at least in part on the discriminative objective function value, prune the first trigram from the language model to generate a pruned language model; receive, from a user computing device, an audio signal corresponding to speech of a user; and recognize the speech, via a speech recognition server, using the pruned language model. 3. The system of claim 1 , wherein the confusion matrix comprises a plurality of confusion probabilities, and wherein individual confusion probabilities of the plurality of confusion probabilities comprise a probability that a phoneme of the language is recognized as a different phoneme of the language. | 0.56408 |
17. A document rating calculation method comprising: in a first information processing apparatus a document retrieval step of electronically retrieving a document fulfilling a given retrieval condition from a database storage medium for documents divided into items, and, for each condition item of the retrieval condition, specifying an item fulfilling the condition item in the retrieved document; a related item selection step, for each condition item of the retrieval condition, i) of specifying an item related to the item fulfilling the condition item for each item fulfilling the condition item and specified in the document retrieval step in the document retrieved by the document retrieval step, based on a mutual dependent relationship based on topics represented by each item among the items, which is stored in the item information database storing a mutual dependent relationship among items into which a document is divided and a rating for each of the items which is calculated based on a predetermined criterion, and ii) of selecting a set of related items including the item fulfilling the condition item and the item specified and related to the item fulfilling the condition item; a fulfilling-item set specifying step of performing a logical operation of the retrieval condition between sets of related items selected in the related item selection step to specify a set of items fulfilling the retrieval condition; and a score calculation step of calculating a document rating of the document fulfilling the retrieval condition based on the ratings of items stored in the item information database and included in the set of fulfilling items specified in the fulfilling-item set specifying step, wherein the score calculation step calculates a document rating of a document fulfilling the retrieval condition based on a rating calculated based on a predetermined degree of account for a number of elements included in an item of the document and a type of the elements, wherein the types of elements included in the items of the document include any combination of a sentence, a figure, a table, an equation, an emphasis expression, a citation and a key word, and wherein the score calculation step calculates the document rating of a document fulfilling the retrieval condition further based on a rating calculated based on a sum of product of a number of elements for each of the types of the elements included in the items of the document, a predetermined index for each of the types of the elements, and a predetermined weight set for the index. | 17. A document rating calculation method comprising: in a first information processing apparatus a document retrieval step of electronically retrieving a document fulfilling a given retrieval condition from a database storage medium for documents divided into items, and, for each condition item of the retrieval condition, specifying an item fulfilling the condition item in the retrieved document; a related item selection step, for each condition item of the retrieval condition, i) of specifying an item related to the item fulfilling the condition item for each item fulfilling the condition item and specified in the document retrieval step in the document retrieved by the document retrieval step, based on a mutual dependent relationship based on topics represented by each item among the items, which is stored in the item information database storing a mutual dependent relationship among items into which a document is divided and a rating for each of the items which is calculated based on a predetermined criterion, and ii) of selecting a set of related items including the item fulfilling the condition item and the item specified and related to the item fulfilling the condition item; a fulfilling-item set specifying step of performing a logical operation of the retrieval condition between sets of related items selected in the related item selection step to specify a set of items fulfilling the retrieval condition; and a score calculation step of calculating a document rating of the document fulfilling the retrieval condition based on the ratings of items stored in the item information database and included in the set of fulfilling items specified in the fulfilling-item set specifying step, wherein the score calculation step calculates a document rating of a document fulfilling the retrieval condition based on a rating calculated based on a predetermined degree of account for a number of elements included in an item of the document and a type of the elements, wherein the types of elements included in the items of the document include any combination of a sentence, a figure, a table, an equation, an emphasis expression, a citation and a key word, and wherein the score calculation step calculates the document rating of a document fulfilling the retrieval condition further based on a rating calculated based on a sum of product of a number of elements for each of the types of the elements included in the items of the document, a predetermined index for each of the types of the elements, and a predetermined weight set for the index. 26. The document rating calculation method according to claim 17 , further comprising a necessary item determining step of specifying a predetermined item in the document which does not influence the document rating of the document, and excluding the item from candidates whose document ratings are to be calculated. | 0.573773 |
64. In a data processing system, a method for archiving non-text objects in a document, comprising the steps of: loading an existing index into a data processing system; inputting a document architecture envelope including a non-text object and containing embedded text into said system; extracting said embedded text; automatically generating a first key word for said non-text object from said embedded text and adding said first key word to said index; storing said document architecture envelope in said system; storing said index including said first key word in said system; entering a search term into said data processing system; comparing said search term with candidate key words in said index; and retrieving said non-text object if said first key word is found in said comparing step. | 64. In a data processing system, a method for archiving non-text objects in a document, comprising the steps of: loading an existing index into a data processing system; inputting a document architecture envelope including a non-text object and containing embedded text into said system; extracting said embedded text; automatically generating a first key word for said non-text object from said embedded text and adding said first key word to said index; storing said document architecture envelope in said system; storing said index including said first key word in said system; entering a search term into said data processing system; comparing said search term with candidate key words in said index; and retrieving said non-text object if said first key word is found in said comparing step. 65. The method of claim 64, wherein non-text object is a graphics object. | 0.928112 |
1. A method for associating a document file with a record in a reference database, the method comprising: receiving the document file, the document file comprising unstructured data related to a record in the reference database; organizing data extracted from the unstructured data in the document file into an array of strings; obtaining a first set of strings by filtering at least a portion of the array of strings using at least one of: string position, position of a portion of a string, string value, value of a portion of a string, string format, format of a portion of a string, a property of one or more characters within a string, and string length; comparing the first set of strings from the array of strings against a comparison reference database comprising a plurality of records from the database, wherein a record comprises at least one data field element; dynamically generating a match pattern by selecting, from results of comparing the first set of strings from the array of strings against the comparison reference database, a set of matches to one or more data field elements within a record from the plurality of records in the comparison reference database to form the match pattern; determining a number of occurrences of the match pattern within records from the plurality of records in the comparison reference database; and responsive to the number of occurrences of the match pattern within records from the plurality of records in the comparison reference database being below a threshold number, associating the document file with the record corresponding with the set of matches from which the match pattern was formed. | 1. A method for associating a document file with a record in a reference database, the method comprising: receiving the document file, the document file comprising unstructured data related to a record in the reference database; organizing data extracted from the unstructured data in the document file into an array of strings; obtaining a first set of strings by filtering at least a portion of the array of strings using at least one of: string position, position of a portion of a string, string value, value of a portion of a string, string format, format of a portion of a string, a property of one or more characters within a string, and string length; comparing the first set of strings from the array of strings against a comparison reference database comprising a plurality of records from the database, wherein a record comprises at least one data field element; dynamically generating a match pattern by selecting, from results of comparing the first set of strings from the array of strings against the comparison reference database, a set of matches to one or more data field elements within a record from the plurality of records in the comparison reference database to form the match pattern; determining a number of occurrences of the match pattern within records from the plurality of records in the comparison reference database; and responsive to the number of occurrences of the match pattern within records from the plurality of records in the comparison reference database being below a threshold number, associating the document file with the record corresponding with the set of matches from which the match pattern was formed. 6. The method of claim 1 further comprising the step of: associating additional data with the document file that is matched to a record wherein the additional data associated with the document file is identified by information associated with the matched record. | 0.603644 |
9. A non-transitory computer-readable medium having stored contents that configure a computing device to perform a method, the method comprising: an itemMirror library providing support, in software applications that use the library, for: a. storing metadata in association with any grouping item; b. retrieving metadata previously stored in association with any grouping item; c. storing metadata in association with any reference in any grouping item to another information item; d. retrieving metadata previously stored in association with any reference in any grouping item to another information item; e. using drivers to store and retrieve information via an application programming interface (API) as supported by a separate application, database or cloud store service; f. controlling concurrency of access to ensure that the modifications in metadata made by one software application are sequenced to occur strictly before or after the modifications made by another software application. | 9. A non-transitory computer-readable medium having stored contents that configure a computing device to perform a method, the method comprising: an itemMirror library providing support, in software applications that use the library, for: a. storing metadata in association with any grouping item; b. retrieving metadata previously stored in association with any grouping item; c. storing metadata in association with any reference in any grouping item to another information item; d. retrieving metadata previously stored in association with any reference in any grouping item to another information item; e. using drivers to store and retrieve information via an application programming interface (API) as supported by a separate application, database or cloud store service; f. controlling concurrency of access to ensure that the modifications in metadata made by one software application are sequenced to occur strictly before or after the modifications made by another software application. 15. The computer-implemented method of claim 9 wherein some portion of the metadata stored, and later retrieved, can be used to represent differences in the state of the remaining metadata at two different points in time such that, for a given state of this remaining metadata and given a difference between this state t of metadata and a previous state t−1 of this metadata, the exact state of this metadata at state t−1 can be reconstructed for read-only viewing. | 0.763931 |
11. A computer-readable storage medium containing instructions for performing a method for schema mapping and data transformation, the method comprising: retrieving at least a portion of the first document; generating one or more labels representing schema information for the at least a portion of the first document based on a schema of the first document; displaying simultaneously to a user, with a graphical user interface (GUI), a representation of the schema of the first document comprising the at least a portion of the first document and the one or more labels representing schema information for the at least a portion of the first document and a representation of a schema of the second document within cells of a spreadsheet application, the first and second documents having different schemas; acquiring, from the user, at least one association usable to map at least a first element of the first document to at least a second element of the second document, wherein each of the first and second elements contain layout data; and storing the association. | 11. A computer-readable storage medium containing instructions for performing a method for schema mapping and data transformation, the method comprising: retrieving at least a portion of the first document; generating one or more labels representing schema information for the at least a portion of the first document based on a schema of the first document; displaying simultaneously to a user, with a graphical user interface (GUI), a representation of the schema of the first document comprising the at least a portion of the first document and the one or more labels representing schema information for the at least a portion of the first document and a representation of a schema of the second document within cells of a spreadsheet application, the first and second documents having different schemas; acquiring, from the user, at least one association usable to map at least a first element of the first document to at least a second element of the second document, wherein each of the first and second elements contain layout data; and storing the association. 12. The computer-readable storage medium of claim 11 , wherein the method further comprises: indicating to the user a second association between a third element of the first document and a fourth element of the second document based on the at least one association. | 0.549677 |
9. A method for contact centers to identify contact center agents based upon voice characteristics of the human agents comprising: a human agent logging onto a contact center and providing authentication information that includes a user name unique to that human agent and a corresponding password for the user name; the contact center authenticating the agent using the authentication information; the call center transferring a caller to the human agent to initiate a contact center communication session between the human agent and the caller; receiving speech content associated with the contact center communication session; extracting biometric characteristics contained within the speech content of the contact center communication session; comparing the extracted biometric characteristics against previously stored biometric characteristics associated with the human agent; determining an identity of a speaker of the content based upon results of the comparing step; comparing the identity of the speaker with an identity of a human associated with the user name, wherein the comparison is performed to verify that a human logged in as the human agent via the user name is in fact the speaker; a contact center performing at least one programmatic action based upon results of the determined identity, wherein the programmatic action is determining whether inappropriate phrases spoken during the communication session were attributable to the human agent or to the caller and taking corrective or punishment actions against the human agent when the human agent is determined to have spoken the inappropriate phrases. | 9. A method for contact centers to identify contact center agents based upon voice characteristics of the human agents comprising: a human agent logging onto a contact center and providing authentication information that includes a user name unique to that human agent and a corresponding password for the user name; the contact center authenticating the agent using the authentication information; the call center transferring a caller to the human agent to initiate a contact center communication session between the human agent and the caller; receiving speech content associated with the contact center communication session; extracting biometric characteristics contained within the speech content of the contact center communication session; comparing the extracted biometric characteristics against previously stored biometric characteristics associated with the human agent; determining an identity of a speaker of the content based upon results of the comparing step; comparing the identity of the speaker with an identity of a human associated with the user name, wherein the comparison is performed to verify that a human logged in as the human agent via the user name is in fact the speaker; a contact center performing at least one programmatic action based upon results of the determined identity, wherein the programmatic action is determining whether inappropriate phrases spoken during the communication session were attributable to the human agent or to the caller and taking corrective or punishment actions against the human agent when the human agent is determined to have spoken the inappropriate phrases. 10. The method of claim 9 , wherein said contact center communication session includes speech of the human agent and a contact center customer, and wherein said received speech content is a segment of speech provided by the human agent and the contact center customer, said determining step further comprising: determining utilizing a software program stored in a machine readable memory which one of the human agent and the contact center customer provided said speech content, wherein said determined identity is one of the human agent and the contact center customer. | 0.516422 |
1. A method of facilitating quick mobile website creation by mobile advertisers, the method executable by a computer having at least one processor and memory, the method comprising: providing to an advertiser, using the computer, access to a mobile marketing application that interfaces with an ad server and is executable by the at least one processor; authenticating the advertiser, using the at least one processor, for access to the application through an advertisement creation screen of the ad server with which the advertiser is already authenticated and from which the advertiser links to arrive at the application; receiving from the advertiser, through an interface of the application, a plurality of content items selected from a group consisting of a descriptive text, an image, a phone number, and a hyperlink; presenting the advertiser with a go live option through the interface; receiving a selection of the go live option through the interface; creating, using the at least one processor, the mobile website to include the received content items in response to selection of the go live option, wherein the application facilitates rapid creation by the advertiser of a mobile website having a plurality of web pages, and the mobile website is optimized for mobile delivery; subjecting, using the at least one processor, the created mobile website to a plurality of error checks; and publishing the mobile website, using the at least one processor, to a network through a mobile service provider system. | 1. A method of facilitating quick mobile website creation by mobile advertisers, the method executable by a computer having at least one processor and memory, the method comprising: providing to an advertiser, using the computer, access to a mobile marketing application that interfaces with an ad server and is executable by the at least one processor; authenticating the advertiser, using the at least one processor, for access to the application through an advertisement creation screen of the ad server with which the advertiser is already authenticated and from which the advertiser links to arrive at the application; receiving from the advertiser, through an interface of the application, a plurality of content items selected from a group consisting of a descriptive text, an image, a phone number, and a hyperlink; presenting the advertiser with a go live option through the interface; receiving a selection of the go live option through the interface; creating, using the at least one processor, the mobile website to include the received content items in response to selection of the go live option, wherein the application facilitates rapid creation by the advertiser of a mobile website having a plurality of web pages, and the mobile website is optimized for mobile delivery; subjecting, using the at least one processor, the created mobile website to a plurality of error checks; and publishing the mobile website, using the at least one processor, to a network through a mobile service provider system. 6. The method of claim 1 , wherein each page of the created mobile website comprises one or more of: a name provided to identify the page; a title to be used as a title tag in a markup generated when the page is created; a size limit; a capability to display an image and to make the image linkable; and a capability to display descriptive text and to make the text linkable. | 0.599517 |
15. A computer-implemented method comprising: determining a first set of one or more predicted characters based on one or more user inputted characters; presenting the first set of one or more predicted characters in an area that can be edited by a user; receiving new character user input that overwrites a predicted character of the first set of one or more predicted characters; removing a subset of characters of the first set of one or more predicted characters, the subset following the predicted character overwritten by the new character user input, the subset removed in response to receiving the new character user input; accepting one or more predicted characters between the overwritten character and an end of the one or more user inputted characters; and completing a word-based at least partially on the one or more user inputted characters, the accepted one or more predicted characters, and the new character user input. | 15. A computer-implemented method comprising: determining a first set of one or more predicted characters based on one or more user inputted characters; presenting the first set of one or more predicted characters in an area that can be edited by a user; receiving new character user input that overwrites a predicted character of the first set of one or more predicted characters; removing a subset of characters of the first set of one or more predicted characters, the subset following the predicted character overwritten by the new character user input, the subset removed in response to receiving the new character user input; accepting one or more predicted characters between the overwritten character and an end of the one or more user inputted characters; and completing a word-based at least partially on the one or more user inputted characters, the accepted one or more predicted characters, and the new character user input. 17. The computer-implemented method of claim 15 , comprising: presenting a revised set of predicted characters after the new character user input based on the one or more user inputted characters, the accepted one or more predicted characters, and the new character user input, the one or more user inputted characters, the accepted one or more predicted characters, the new character user input, and the revised set of predicted characters forming a word. | 0.588254 |
7. A method as recited in claim 1 , wherein the generating the first set of input candidates comprises: identifying a first input search engine from a pool of input candidate engines, the pool of input candidate engines including a plurality of input search engines, and utilizing the first input search engine to identify the first set of input candidates; and wherein the method further comprises: identifying a second input search engine from the pool of input candidate engines, and utilizing the second input search engine to identify the second set of input candidates. | 7. A method as recited in claim 1 , wherein the generating the first set of input candidates comprises: identifying a first input search engine from a pool of input candidate engines, the pool of input candidate engines including a plurality of input search engines, and utilizing the first input search engine to identify the first set of input candidates; and wherein the method further comprises: identifying a second input search engine from the pool of input candidate engines, and utilizing the second input search engine to identify the second set of input candidates. 8. A method as recited in claim 7 , wherein the first input search engine is configured to provide both text candidates and rich candidates. | 0.921744 |
9. A computer system comprising: a central processing unit (CPU); a memory coupled to said CPU; a computer-readable, tangible storage device coupled to said CPU, said storage device containing instructions that are carried out by said CPU via said memory to implement a method of querying multifaceted information, said method comprising: constructing an inverted index having a plurality of unique indexed tokens associated with a plurality of posting lists in a one-to-one correspondence, each posting list including one or more documents of a plurality of documents, wherein an indexed token of said plurality of unique indexed tokens is one of a facet token included as an annotation in a document of said plurality of documents and a path prefix of said facet token, wherein said annotation indicates a path within a tree structure representing a facet that includes said document, said tree structure including a plurality of nodes representing a category and one or more sub-categories that categorize said document; receiving a query that includes a plurality of constraints on said plurality of documents, said plurality of constraints being associated with multiple indexed tokens of said plurality of unique indexed tokens and multiple posting lists corresponding to said multiple indexed tokens; and executing said query by identifying said multiple posting lists via a utilization of said plurality of constraints and said inverted index, and intersecting said multiple posting lists to obtain a result of said query. | 9. A computer system comprising: a central processing unit (CPU); a memory coupled to said CPU; a computer-readable, tangible storage device coupled to said CPU, said storage device containing instructions that are carried out by said CPU via said memory to implement a method of querying multifaceted information, said method comprising: constructing an inverted index having a plurality of unique indexed tokens associated with a plurality of posting lists in a one-to-one correspondence, each posting list including one or more documents of a plurality of documents, wherein an indexed token of said plurality of unique indexed tokens is one of a facet token included as an annotation in a document of said plurality of documents and a path prefix of said facet token, wherein said annotation indicates a path within a tree structure representing a facet that includes said document, said tree structure including a plurality of nodes representing a category and one or more sub-categories that categorize said document; receiving a query that includes a plurality of constraints on said plurality of documents, said plurality of constraints being associated with multiple indexed tokens of said plurality of unique indexed tokens and multiple posting lists corresponding to said multiple indexed tokens; and executing said query by identifying said multiple posting lists via a utilization of said plurality of constraints and said inverted index, and intersecting said multiple posting lists to obtain a result of said query. 10. The system of claim 9 , wherein said plurality of constraints includes one or more facet constraints and one or more free-text constraints, and wherein said identifying said multiple posting lists comprises: identifying, via said inverted index, a first set of one or more indexed tokens associated with said one or more facet constraints in a one-to-one correspondence and a second set of one or more indexed tokens associated with said one or more free-text constraints in a one-to-one correspondence, said first set and said second set of one or more indexed tokens included in said plurality of unique indexed tokens; and identifying, via said inverted index, a first group of one or more posting lists and a second group of one or more posting lists, said one or more posting lists of said first group associated with said one or more indexed tokens of said first set in a one-to-one correspondence and said one or more posting lists of said second group associated with said one or more indexed tokens of said second set in a one-to-one correspondence. | 0.529039 |
1. A method of automatically finding one or more answers to a natural language question in a computer stored natural language text database, wherein said natural language text database has been analyzed with respect to syntactic functions of constituents, lexical meaning of word tokens, and initial clause boundaries, and wherein said natural language question comprises a question clause, comprising the steps of: analyzing, in an analyzing means of a computer system, a computer readable representation of said question clause with respect to syntactic functions of its constituents and the lexical meaning of its word tokens; defining, in a defining means of a computer system, in response to the analysis step, a set of conditions for an initial clause in said natural language text database to constitute an answer to said question clause, said conditions comprising a condition stipulating that, for an initial clause in said natural language text database to constitute an answer to said questions clause, at least one of the constituents of said question clause should have a corresponding constituent in said initial clause having the same syntactic function and an equivalent lexical meaning; identifying, in an answer finding means of a computer system, initial clauses in said natural language text database that satisfy said conditions; and returning, in an answer finding means of a computer system, answers to said question clause by means of the identified initial clauses that match said conditions. | 1. A method of automatically finding one or more answers to a natural language question in a computer stored natural language text database, wherein said natural language text database has been analyzed with respect to syntactic functions of constituents, lexical meaning of word tokens, and initial clause boundaries, and wherein said natural language question comprises a question clause, comprising the steps of: analyzing, in an analyzing means of a computer system, a computer readable representation of said question clause with respect to syntactic functions of its constituents and the lexical meaning of its word tokens; defining, in a defining means of a computer system, in response to the analysis step, a set of conditions for an initial clause in said natural language text database to constitute an answer to said question clause, said conditions comprising a condition stipulating that, for an initial clause in said natural language text database to constitute an answer to said questions clause, at least one of the constituents of said question clause should have a corresponding constituent in said initial clause having the same syntactic function and an equivalent lexical meaning; identifying, in an answer finding means of a computer system, initial clauses in said natural language text database that satisfy said conditions; and returning, in an answer finding means of a computer system, answers to said question clause by means of the identified initial clauses that match said conditions. 5. The method according to claim 1 , wherein said set of conditions in the defining step comprises: a manner adverb condition stipulating that a clause constitutes an answer to said question clause if a lexically headed constituent having the syntactic function of manner adverb of said question clause has a corresponding lexically headed constituent in said clause having the syntactic function of manner adverb and having an equivalent lexical meaning. | 0.5 |
19. A computer implemented method of automatically generating a playlist of snippets of multimedia content, the method comprising: receiving multimedia content on a user device; generating a first plurality of snippets from the received multimedia content according to a specified parameter; selecting a second plurality of snippets from the first plurality of snippets according to a predefined threshold; ordering the second plurality of snippets in a playlist according to a start time of each snippet in the ordered playlist; and processing snippets from the ordered playlist that are overlapping to automatically remove duplication of multimedia content from the ordered playlist and generate a final playlist with non-overlapping snippets. | 19. A computer implemented method of automatically generating a playlist of snippets of multimedia content, the method comprising: receiving multimedia content on a user device; generating a first plurality of snippets from the received multimedia content according to a specified parameter; selecting a second plurality of snippets from the first plurality of snippets according to a predefined threshold; ordering the second plurality of snippets in a playlist according to a start time of each snippet in the ordered playlist; and processing snippets from the ordered playlist that are overlapping to automatically remove duplication of multimedia content from the ordered playlist and generate a final playlist with non-overlapping snippets. 20. The computer implemented method of claim 19 further comprising: adding a new user selected snippet to the final playlist to create a modified playlist; reordering the modified playlist according to a start time of each snippet in the reordered modified playlist; and processing the snippets from the reordered modified playlist that are overlapping to remove duplication of multimedia content from the reordered modified playlist. | 0.640788 |
1. A method for employing a printer to print a document, comprising: providing a print request and the document to the printer in a native, non-page-description-language, file format that is editable by a document-processing application; employing the print request to determine one or more pages of the document to be printed, wherein the print request includes information identifying the one or more pages; determining a page representation for each of the identified one or more pages of the document from the native file format independent of a page description language, wherein each page representation includes a plurality of graphics primitives that are directly supported by the printer; determining an image representation for each page representation based on the plurality of graphics primitives included with each corresponding page representation; determining separate subsets of the plurality of graphics primitives that correspond to separate bands of the one or more pages; rendering at least a portion of the one or more pages based on the separate subsets of graphics primitives; decompressing, at the printer, at least a portion of the document that corresponds to the one or more pages prior to determining each page representation; and printing the one or more pages of the document based on the determined image representations. | 1. A method for employing a printer to print a document, comprising: providing a print request and the document to the printer in a native, non-page-description-language, file format that is editable by a document-processing application; employing the print request to determine one or more pages of the document to be printed, wherein the print request includes information identifying the one or more pages; determining a page representation for each of the identified one or more pages of the document from the native file format independent of a page description language, wherein each page representation includes a plurality of graphics primitives that are directly supported by the printer; determining an image representation for each page representation based on the plurality of graphics primitives included with each corresponding page representation; determining separate subsets of the plurality of graphics primitives that correspond to separate bands of the one or more pages; rendering at least a portion of the one or more pages based on the separate subsets of graphics primitives; decompressing, at the printer, at least a portion of the document that corresponds to the one or more pages prior to determining each page representation; and printing the one or more pages of the document based on the determined image representations. 5. The method of claim 1 , further comprising: receiving the one or more pages of the document from a remote computer as a data stream; determining the native file format from the data stream; and employing an interpreter engine that corresponds to the determined native file format to determine each page representation. | 0.745253 |
2. The method of claim 1 , wherein in each comparison, the elements of the set of elements of the first XML document and of the second XML document being compared match when their respective values for their merge attribute are equal. | 2. The method of claim 1 , wherein in each comparison, the elements of the set of elements of the first XML document and of the second XML document being compared match when their respective values for their merge attribute are equal. 5. The method of claim 2 , further comprising, comparison of the child elements of the matching elements of the first XML document and the second XML document. | 0.94481 |
30. A security appliance coupled to a network, the security appliance comprising: a processor coupled to a data store, the processor configured to monitor data received by the security appliance from the network and to convert a nondeterministic finite automata (NFA) graph for a given set of patterns to a deterministic finite automata (DFA) graph having a number of DFA states, wherein the processor employs the DFA graph in order to apply the given set of patterns to the data to monitor the data and wherein to convert the NFA graph to the DFA graph the processor is further configured to: map a DFA state of the number of DFA states to a corresponding set of one or more NFA states of the NFA graph; compute a first hash value of the one or more NFA states of the corresponding set; store the first hash value in an entry of a DFA states table in the data store, the DFA states table correlating the DFA state to the first hash value; and determine a transition DFA state from the DFA state for a character of an alphabet recognized by the NFA graph, based on whether a second hash value of transitions of the one or more NFA states for the character exists in an Epsilon Closure (EC) cache table, the EC cache table including hash value entries mapped to DFA states, and wherein, in an event the second hash value exists, setting the transition DFA state to be a given DFA state, the given DFA state mapped to the second hash value in the EC cache table. | 30. A security appliance coupled to a network, the security appliance comprising: a processor coupled to a data store, the processor configured to monitor data received by the security appliance from the network and to convert a nondeterministic finite automata (NFA) graph for a given set of patterns to a deterministic finite automata (DFA) graph having a number of DFA states, wherein the processor employs the DFA graph in order to apply the given set of patterns to the data to monitor the data and wherein to convert the NFA graph to the DFA graph the processor is further configured to: map a DFA state of the number of DFA states to a corresponding set of one or more NFA states of the NFA graph; compute a first hash value of the one or more NFA states of the corresponding set; store the first hash value in an entry of a DFA states table in the data store, the DFA states table correlating the DFA state to the first hash value; and determine a transition DFA state from the DFA state for a character of an alphabet recognized by the NFA graph, based on whether a second hash value of transitions of the one or more NFA states for the character exists in an Epsilon Closure (EC) cache table, the EC cache table including hash value entries mapped to DFA states, and wherein, in an event the second hash value exists, setting the transition DFA state to be a given DFA state, the given DFA state mapped to the second hash value in the EC cache table. 47. The security appliance of claim 30 wherein the processor is further configured to: in an event the second hash value does not exist in the EC cache table, compute an epsilon closure for the transitions of the one or more NFA states of the NFA graph; compute a third hash value of the epsilon closure; add a new entry into the EC cache table, the new entry mapping a new DFA state to the third hash value of the epsilon closure; and set the new DFA state as the transition DFA state for the character of the alphabet recognized by the NFA graph. | 0.5 |
9. A system for filtering a font character bitmap represented as a texture map, comprising: a texture read request unit configured to read a coarsely aligned region of the font character bitmap; a font alignment engine configured to align the coarsely aligned region of the texture map with a font filter footprint and produce a finely aligned region of the font character bitmap; a font sample unit configured to compute font samples for portions of the finely aligned region of the font character bitmap, wherein the font samples indicate a percentage of texels that are within a font character represented by the font character bitmap; a bilinear filter engine configured to bilinearly interpolate the font samples to produce a bilinearly filtered font sample value for the finely aligned region of the font character bitmap; and computing a font coverage value for the finely aligned region of the font character bitmap by scaling the bilinearly filtered font sample value by a normalization factor. | 9. A system for filtering a font character bitmap represented as a texture map, comprising: a texture read request unit configured to read a coarsely aligned region of the font character bitmap; a font alignment engine configured to align the coarsely aligned region of the texture map with a font filter footprint and produce a finely aligned region of the font character bitmap; a font sample unit configured to compute font samples for portions of the finely aligned region of the font character bitmap, wherein the font samples indicate a percentage of texels that are within a font character represented by the font character bitmap; a bilinear filter engine configured to bilinearly interpolate the font samples to produce a bilinearly filtered font sample value for the finely aligned region of the font character bitmap; and computing a font coverage value for the finely aligned region of the font character bitmap by scaling the bilinearly filtered font sample value by a normalization factor. 10. The system of claim 9 , wherein the normalization factor equals 2 n /(nu*nv), where n is a number of bits used to represent the font coverage value and nu and nv are size dimensions of the font filter footprint. | 0.719136 |
2. The method of claim 1 , further comprising: while facilitating a second real time conversation, receiving a request for activating a second email exchange based on the second real time conversation; determining recipients for the second email exchange based on at least one of the participants of the second real time conversation and a context of the second real time conversation; and preparing an email for the second email exchange, wherein the email is populated with information based on the context of the second real time conversation. | 2. The method of claim 1 , further comprising: while facilitating a second real time conversation, receiving a request for activating a second email exchange based on the second real time conversation; determining recipients for the second email exchange based on at least one of the participants of the second real time conversation and a context of the second real time conversation; and preparing an email for the second email exchange, wherein the email is populated with information based on the context of the second real time conversation. 3. The method of claim 2 , wherein the context of the first and second email exchanges and the context of the first and second real time conversations include an exchanged content, exchanged links, and exchanged documents. | 0.947403 |
8. A system, comprising: a computer system comprising a central processing unit coupled to a memory and resource management application; and a plurality of different automatic speech recognition (ASR) engines coupled to the computer system, wherein the resource management application assesses resources being used by each of the plurality of different ASR engines by monitoring port utilization and available processing power of each of the plurality of different ASR engines, and the computer system select a single ASR engine to analyze a speech utterance when the system is busy such that the port utilization and the available processing power are within a set of threshold values and selects multiple ASR engines to analyze the speech utterance when the system is not busy such that the port utilization and the available processing power are within another set of threshold values; wherein selecting a single ASR engine to analyze the speech utterance if available processing power is within a threshold value when the port utilization of the single ASR engine is lower than a port utilization of 80%. | 8. A system, comprising: a computer system comprising a central processing unit coupled to a memory and resource management application; and a plurality of different automatic speech recognition (ASR) engines coupled to the computer system, wherein the resource management application assesses resources being used by each of the plurality of different ASR engines by monitoring port utilization and available processing power of each of the plurality of different ASR engines, and the computer system select a single ASR engine to analyze a speech utterance when the system is busy such that the port utilization and the available processing power are within a set of threshold values and selects multiple ASR engines to analyze the speech utterance when the system is not busy such that the port utilization and the available processing power are within another set of threshold values; wherein selecting a single ASR engine to analyze the speech utterance if available processing power is within a threshold value when the port utilization of the single ASR engine is lower than a port utilization of 80%. 10. The system of claim 8 further comprising a telephone network comprising at least one switching service point coupled to the computer system. | 0.567473 |
1. A method for determining an emotional state of a user, comprising: extracting features including one or more acoustic features, visual features, linguistic features, physical feature s from signals obtained by one or more sensors with a processor; analyzing the features including the acoustic features, visual features, linguistic features, and physical features with one or more machine learning algorithms implemented on a processor; wherein analyzing the acoustic features, visual features, linguistic features, and physical features includes use of separate machine learning algorithms for the acoustic, visual, linguistic, and physical features; wherein a first machine learning algorithm provides feedback to a second machine learning algorithm in a serial fashion; and extracting an emotional state of the user from analysis of the features including analysis of the acoustic features, visual features, linguistic features, and physical features with the one or more machine learning algorithms. | 1. A method for determining an emotional state of a user, comprising: extracting features including one or more acoustic features, visual features, linguistic features, physical feature s from signals obtained by one or more sensors with a processor; analyzing the features including the acoustic features, visual features, linguistic features, and physical features with one or more machine learning algorithms implemented on a processor; wherein analyzing the acoustic features, visual features, linguistic features, and physical features includes use of separate machine learning algorithms for the acoustic, visual, linguistic, and physical features; wherein a first machine learning algorithm provides feedback to a second machine learning algorithm in a serial fashion; and extracting an emotional state of the user from analysis of the features including analysis of the acoustic features, visual features, linguistic features, and physical features with the one or more machine learning algorithms. 6. The method of claim 1 , further comprising changing a state of a computer system in response to the emotional state of the user extracted from analysis of the acoustic features, visual features, linguistic, and physical features. | 0.602706 |
10. A distributed big data database processing system comprising: a plurality of distributed processing apparatuses, each of the plurality of processing apparatuses connected to a computer network and configured to, sort data of a big data database stored on at least one non-transitory computer storage medium based on each column of the big data database and values of the data, generate a dictionary for each column of the big database based on the sorted data, classify the sorted data into a plurality of data blocks for each of the dictionaries, generate a columnar index for each of the dictionaries, the index including first data values of each of the data blocks of each of the dictionaries in an order of the data blocks in the dictionaries, the generating the columnar index including, generating a column ID block for each of the dictionaries, the column ID block storing a column ID as the row order of the big data, the column ID being a value for identifying a location or order of data of a corresponding dictionary, wherein each of the dictionaries includes a dictionary identifier, an index field, and a column ID field, the index field includes references to at least one index block, and the column ID field includes references to at least one column ID block, store the columnar index and the column ID block on the at least one non-transitory computer storage medium, receive a transmitted big data database operation request over the computer network, retrieve the data requested by the received big data database operation from the non-transitory computer storage medium using the columnar index, the retrieving including, determining data responsive to the received big data database operation, the determining including comparing data values of the at least one index block of the columnar index and determining a data block corresponding to the determined data value, and reading the determined data block from the corresponding non-transitory computer storage medium, and transmit the retrieved data to at least one client computer. | 10. A distributed big data database processing system comprising: a plurality of distributed processing apparatuses, each of the plurality of processing apparatuses connected to a computer network and configured to, sort data of a big data database stored on at least one non-transitory computer storage medium based on each column of the big data database and values of the data, generate a dictionary for each column of the big database based on the sorted data, classify the sorted data into a plurality of data blocks for each of the dictionaries, generate a columnar index for each of the dictionaries, the index including first data values of each of the data blocks of each of the dictionaries in an order of the data blocks in the dictionaries, the generating the columnar index including, generating a column ID block for each of the dictionaries, the column ID block storing a column ID as the row order of the big data, the column ID being a value for identifying a location or order of data of a corresponding dictionary, wherein each of the dictionaries includes a dictionary identifier, an index field, and a column ID field, the index field includes references to at least one index block, and the column ID field includes references to at least one column ID block, store the columnar index and the column ID block on the at least one non-transitory computer storage medium, receive a transmitted big data database operation request over the computer network, retrieve the data requested by the received big data database operation from the non-transitory computer storage medium using the columnar index, the retrieving including, determining data responsive to the received big data database operation, the determining including comparing data values of the at least one index block of the columnar index and determining a data block corresponding to the determined data value, and reading the determined data block from the corresponding non-transitory computer storage medium, and transmit the retrieved data to at least one client computer. 11. The distributed big data database processing system of claim 10 , wherein the corresponding non-transitory computer storage medium is accessed over the computer network. | 0.553327 |
12. The system of claim 11 , wherein the operations further comprise storing, in the age-restricted dictionary, a plurality of canonical pronunciations associated with the particular term, wherein the plurality of canonical pronunciations includes the restricted, canonical pronunciations for the particular term, and wherein two or more of the plurality of canonical pronunciations include an indication of age-appropriateness. | 12. The system of claim 11 , wherein the operations further comprise storing, in the age-restricted dictionary, a plurality of canonical pronunciations associated with the particular term, wherein the plurality of canonical pronunciations includes the restricted, canonical pronunciations for the particular term, and wherein two or more of the plurality of canonical pronunciations include an indication of age-appropriateness. 13. The system of claim 12 , wherein the operations further comprise determining that a pronunciation of the particular term by the user is not age-appropriate comprises determining that an indication of appropriateness of the term is greater than a minimum level. | 0.870452 |
1. A phonetic data-to-kanji characters converter for converting character string data including Kanji characters, comprising: input means for inputting phonetic data and sentence end data representing an end of a sentence; conversion processing means for sequentially converting the phonetic data input by said input means into character string data in a predetermined train of the phonetic data, selecting character string data having the highest priority according to a predetermined priority order in the predetermined train of the phonetic data if a plurality of conversion possibilities are present, and obtaining the character string data which corresponds to the phonetic data; storing means for storing, in accordance with said priority order, all of the character string data obtained by said conversion processing means; syntactic analyzing means for analyzing syntactic relations in the character string data from said conversion processing means in response to the sentence end data from said input means; priority order altering means for altering, based on the analyzed syntactic relations, the priority order of the plurality of conversion possibilities corresponding to homonymic data during the processing of said conversion processing means, and altering selection of the character string data according to an altered priority order; and output means for sequentially displaying the character string input from said conversion processing means. | 1. A phonetic data-to-kanji characters converter for converting character string data including Kanji characters, comprising: input means for inputting phonetic data and sentence end data representing an end of a sentence; conversion processing means for sequentially converting the phonetic data input by said input means into character string data in a predetermined train of the phonetic data, selecting character string data having the highest priority according to a predetermined priority order in the predetermined train of the phonetic data if a plurality of conversion possibilities are present, and obtaining the character string data which corresponds to the phonetic data; storing means for storing, in accordance with said priority order, all of the character string data obtained by said conversion processing means; syntactic analyzing means for analyzing syntactic relations in the character string data from said conversion processing means in response to the sentence end data from said input means; priority order altering means for altering, based on the analyzed syntactic relations, the priority order of the plurality of conversion possibilities corresponding to homonymic data during the processing of said conversion processing means, and altering selection of the character string data according to an altered priority order; and output means for sequentially displaying the character string input from said conversion processing means. 5. A system according to claim 1, wherein said input means comprises means for inputting a phonetic alphabetic character string as phonetic data. | 0.873921 |
10. A non-transitory computer-readable data storage medium comprising: non-volatile memory storing instructions for operatively instructing a digital processor to automatically adjust an arrangement of currently existing dimension annotations of a computer-aided design model representing a real-world object, the computer-aided design model being displayed on a computer screen and having one or more entities, the memory programmably causing said digital processor to: receive from a user input device input to adjust the arrangement, wherein the input specifies one of adding a certain dimension annotation to the arrangement and deleting one of the currently existing dimension annotations from the arrangement, and the input specifies user selection of an entity to annotate, said user selection being by user placement of a cursor at the entity as displayed in the computer-aided design model; create one or more sets of the currently existing dimension annotations, wherein currently existing dimension annotations of any one or combination of a similar proximity, a same dimension type, and a same orientation belong to a same set; sort the currently existing dimension annotations in the same set resulting in one or more probable locations able to be associated with the selected entity in the displayed computer-aided design model for placement of dimension annotations in the arrangement when adjusted either without the deleted one of the currently existing dimension annotations or with the certain dimension annotation added, and if the input specifies adding the certain dimension annotation to the arrangement and the certain dimension annotation has any one or combination of the similar proximity, the same dimension type, and the same orientation as the currently existing dimension annotations in the same set, then sort the certain dimension annotation along with the currently existing dimension annotations in the same set; automatically adjust the arrangement of the dimension annotations and render the adjusted arrangement on the computer screen by employing an ordering resulting from the sorting, wherein: the ordering including the certain dimension annotation in the adjusted arrangement if the input specifies adding the certain dimension annotation, wherein a location of the certain dimension annotation in the adjusted arrangement corresponds to the ordering resulting from the sort; and the ordering excluding the one of the currently existing dimension annotations from the adjusted arrangement if the input specifies deleting said one of the currently existing dimension annotations from the arrangement; and display a user-interface widget near the user placement of the cursor at the selected entity, the user-interface widget designating the probable locations for placement of the dimension annotations in the adjusted arrangement of the dimension annotations, and upon a user hovering the cursor over the widget, display a preview of the adjusted arrangement. | 10. A non-transitory computer-readable data storage medium comprising: non-volatile memory storing instructions for operatively instructing a digital processor to automatically adjust an arrangement of currently existing dimension annotations of a computer-aided design model representing a real-world object, the computer-aided design model being displayed on a computer screen and having one or more entities, the memory programmably causing said digital processor to: receive from a user input device input to adjust the arrangement, wherein the input specifies one of adding a certain dimension annotation to the arrangement and deleting one of the currently existing dimension annotations from the arrangement, and the input specifies user selection of an entity to annotate, said user selection being by user placement of a cursor at the entity as displayed in the computer-aided design model; create one or more sets of the currently existing dimension annotations, wherein currently existing dimension annotations of any one or combination of a similar proximity, a same dimension type, and a same orientation belong to a same set; sort the currently existing dimension annotations in the same set resulting in one or more probable locations able to be associated with the selected entity in the displayed computer-aided design model for placement of dimension annotations in the arrangement when adjusted either without the deleted one of the currently existing dimension annotations or with the certain dimension annotation added, and if the input specifies adding the certain dimension annotation to the arrangement and the certain dimension annotation has any one or combination of the similar proximity, the same dimension type, and the same orientation as the currently existing dimension annotations in the same set, then sort the certain dimension annotation along with the currently existing dimension annotations in the same set; automatically adjust the arrangement of the dimension annotations and render the adjusted arrangement on the computer screen by employing an ordering resulting from the sorting, wherein: the ordering including the certain dimension annotation in the adjusted arrangement if the input specifies adding the certain dimension annotation, wherein a location of the certain dimension annotation in the adjusted arrangement corresponds to the ordering resulting from the sort; and the ordering excluding the one of the currently existing dimension annotations from the adjusted arrangement if the input specifies deleting said one of the currently existing dimension annotations from the arrangement; and display a user-interface widget near the user placement of the cursor at the selected entity, the user-interface widget designating the probable locations for placement of the dimension annotations in the adjusted arrangement of the dimension annotations, and upon a user hovering the cursor over the widget, display a preview of the adjusted arrangement. 14. The non-transitory data storage medium as claimed in claim 10 wherein the input specifies adding the certain dimension annotation, and the steps of creating and sorting include determining optimal location for placement of the certain dimension annotation. | 0.501433 |
15. An article of manufacture being one or more machine-readable media that store instructions, which when executed by a machine, cause the machine to perform operations comprising: analyzing text from content in an active window without a user requesting the analysis; executing a query on the content in the active window without a user having to request the query; generating a list of links related to the content in the active window; and controlling how and where a first icon and the generated list of links is physically presented to the user on the display so as to be visually unobtrusive to the user in relation to the content in the active window by embedding in a title bar of an application operating in the active window a first icon associated with the list of links, displaying the list of links related to the content when a user activates the icon, calculating and assigning a relevance rating to the links from the list of links from a scale of how relevant a given link is in relation to the content, wherein a first link must have a relevance rating that is equal to or above a minimum threshold relevance rating in relation to the content before alerting the user by highlighting its corresponding first icon, and highlighting the first icon when one or more of the links related to the content is equal to or above the minimum threshold relevance level in relation to the content in the active window, wherein the minimum threshold relevance value is adjustable by a user. | 15. An article of manufacture being one or more machine-readable media that store instructions, which when executed by a machine, cause the machine to perform operations comprising: analyzing text from content in an active window without a user requesting the analysis; executing a query on the content in the active window without a user having to request the query; generating a list of links related to the content in the active window; and controlling how and where a first icon and the generated list of links is physically presented to the user on the display so as to be visually unobtrusive to the user in relation to the content in the active window by embedding in a title bar of an application operating in the active window a first icon associated with the list of links, displaying the list of links related to the content when a user activates the icon, calculating and assigning a relevance rating to the links from the list of links from a scale of how relevant a given link is in relation to the content, wherein a first link must have a relevance rating that is equal to or above a minimum threshold relevance rating in relation to the content before alerting the user by highlighting its corresponding first icon, and highlighting the first icon when one or more of the links related to the content is equal to or above the minimum threshold relevance level in relation to the content in the active window, wherein the minimum threshold relevance value is adjustable by a user. 19. The article of manufacture of claim 15 , storing instructions, which when executed by the machine, cause the machine to perform further operations, comprising: generating a set of most relevant terms from the text in the content through application of a Bayesian algorithm on the text; and executing the query on the set of most relevant terms from the text in the content. | 0.696528 |
2. A method for determining the pitch and voicing of human speech comprising the steps of: analyzing a speech signal input in accordance with an LPC (Linear Predictive Coding) model to provide LPC parameters and a residual signal organized into a sequence of speech data frames and the respective residual signals corresponding thereto; determining a plurality of pitch candidates for each of the speech data frames in said sequence; performing dynamic programming with respect both to said plurality of pitch candidates for each speech data frame and also to a voiced/unvoiced decision for each speech data frame by defining a transition error between each pitch candidate of the current frame and each pitch candidate of the preceding frame, defining a cumulative error for each pitch candidate of the current frame equal to the transition error between said pitch candidate of said current frame plus the cumulative error of an optimally identified pitch candidate in the preceding frame, and choosing said optimally identified pitch candidate in the preceding frame such that the cumulative error of said corresponding pitch candidate in said current frame is at a minimum; and determining both an optimal pitch and an optimal voicing decision for each speech data frame in the context of said sequence of speech data frames in response to the performance of said dynamic programming. | 2. A method for determining the pitch and voicing of human speech comprising the steps of: analyzing a speech signal input in accordance with an LPC (Linear Predictive Coding) model to provide LPC parameters and a residual signal organized into a sequence of speech data frames and the respective residual signals corresponding thereto; determining a plurality of pitch candidates for each of the speech data frames in said sequence; performing dynamic programming with respect both to said plurality of pitch candidates for each speech data frame and also to a voiced/unvoiced decision for each speech data frame by defining a transition error between each pitch candidate of the current frame and each pitch candidate of the preceding frame, defining a cumulative error for each pitch candidate of the current frame equal to the transition error between said pitch candidate of said current frame plus the cumulative error of an optimally identified pitch candidate in the preceding frame, and choosing said optimally identified pitch candidate in the preceding frame such that the cumulative error of said corresponding pitch candidate in said current frame is at a minimum; and determining both an optimal pitch and an optimal voicing decision for each speech data frame in the context of said sequence of speech data frames in response to the performance of said dynamic programming. 9. The method of claim 2, wherein said transition error is defined to include a voicing transition error component, said voicing transition error component being a small predetermined value when said current frame and said previous frame are both identically voiced or both identically unvoiced, and otherwise being a decreasing function of the spectral difference between said current frame and said previous frame. | 0.657006 |
1. A system, comprising: a processor; and a memory operatively coupled to the processor, the memory storing processor-readable instructions executable by the processor to: receive a data analytics request including a user desired data variable via a user interface; receive, via the user interface, user configured parameters identifying a plurality of user selected data sources and a plurality of user defined data fields for a new data set, a user defined data field from the plurality of user defined data fields representing a logic operation, each data source of the user selected data sources being a separate data source with a data structure schema different from a data structure schema of each of a remaining data source from the user selected data sources; generate an intermediate query based on the data analytics request; define an execution path for the intermediate query, the execution path including locations for a plurality of schema-independent distributed index files located on a plurality of distributed server node engines; transmit, substantially simultaneously, the intermediate query to each distributed service node engine of the plurality of distributed server node engines so as to instruct that distributed server node engine to run the intermediate query, using a schema-independent distributed index file from the plurality of schema-independent distributed index files that is stored at that distributed server node engine; receive intermediate query results from each distributed service node engine of the plurality of distributed server node engines based on the intermediate query; form the new data set based at least in part on the intermediate query results and on a relationship between the plurality of user selected data sources and the plurality of user defined data fields; query the new data set to obtain a first value relating to the user desired data variable; calculate an output value for the user desired data variable based on the first value and the logic operation; and send a signal to generate a user interactive graphical representation of the output value of user desired data variable. | 1. A system, comprising: a processor; and a memory operatively coupled to the processor, the memory storing processor-readable instructions executable by the processor to: receive a data analytics request including a user desired data variable via a user interface; receive, via the user interface, user configured parameters identifying a plurality of user selected data sources and a plurality of user defined data fields for a new data set, a user defined data field from the plurality of user defined data fields representing a logic operation, each data source of the user selected data sources being a separate data source with a data structure schema different from a data structure schema of each of a remaining data source from the user selected data sources; generate an intermediate query based on the data analytics request; define an execution path for the intermediate query, the execution path including locations for a plurality of schema-independent distributed index files located on a plurality of distributed server node engines; transmit, substantially simultaneously, the intermediate query to each distributed service node engine of the plurality of distributed server node engines so as to instruct that distributed server node engine to run the intermediate query, using a schema-independent distributed index file from the plurality of schema-independent distributed index files that is stored at that distributed server node engine; receive intermediate query results from each distributed service node engine of the plurality of distributed server node engines based on the intermediate query; form the new data set based at least in part on the intermediate query results and on a relationship between the plurality of user selected data sources and the plurality of user defined data fields; query the new data set to obtain a first value relating to the user desired data variable; calculate an output value for the user desired data variable based on the first value and the logic operation; and send a signal to generate a user interactive graphical representation of the output value of user desired data variable. 11. The system of claim 1 , wherein the output value for the user desired data variable is not previously stored in the plurality of user selected data sources prior to receipt of the data analytics request. | 0.539289 |
14. The method according to claim 13 , wherein the pixel dimensions are calculated based on: an available space in the display screen for the frameset, and parameters defined for the frame in the instructions. | 14. The method according to claim 13 , wherein the pixel dimensions are calculated based on: an available space in the display screen for the frameset, and parameters defined for the frame in the instructions. 16. An electronic terminal including a processing unit, which is configured to perform the method according to claim 14 . | 0.951444 |
17. The computing system of claim 16 , wherein the results of comparisons are based on a matching algorithm. | 17. The computing system of claim 16 , wherein the results of comparisons are based on a matching algorithm. 18. The computing system of claim 17 , wherein the matching algorithm is any of an area-based alignment algorithm or a feature-based alignment algorithm. | 0.97338 |
1. A method for natural-language processing based on DNA computing, the method comprising: a processor of a computer system translating a grammatical rule of a natural language into a listing of a first sequence of nucleotides, wherein the grammatical rule comprises an ordered set of slots, and wherein each slot of the ordered set of slots is configured to be filled with a compatible token, and wherein a token is a string of characters comprised by a vocabulary of the natural language; the processor further translating a first token of the vocabulary into a listing of a second sequence of nucleotides; the processor decoding information represented by a first bonded pair of nucleotide sequences, wherein the first bonded pair was formed by a chemical bonding of a first nucleotide chain to a second nucleotide chain, wherein nucleotides of the first nucleotide chain are ordered in the first sequence, wherein nucleotides of the second nucleotide chain are ordered in the second sequence, and wherein the decoded information represents a data structure formed by filling a first slot of the ordered set of slots with the first token; the processor determining that the first token comprises an adjacent pair of duplicate substrings; the processor identifying a second token that, other than omitting one occurrence of the duplicate substrings, is identical to the first token; the processor translating the second token into a listing of a third sequence of nucleotides; and the processor decoding information represented by a second bonded pair of nucleotide sequences, wherein the second bonded pair was formed by a chemical bonding of a third nucleotide chain to a fourth nucleotide chain, wherein nucleotides of the third nucleotide chain are ordered in the third sequence, wherein nucleotides of the fourth nucleotide chain are ordered in the first sequence, and wherein the decoded information represents a data structure formed by filling a first slot of the ordered set of slots with the second token. | 1. A method for natural-language processing based on DNA computing, the method comprising: a processor of a computer system translating a grammatical rule of a natural language into a listing of a first sequence of nucleotides, wherein the grammatical rule comprises an ordered set of slots, and wherein each slot of the ordered set of slots is configured to be filled with a compatible token, and wherein a token is a string of characters comprised by a vocabulary of the natural language; the processor further translating a first token of the vocabulary into a listing of a second sequence of nucleotides; the processor decoding information represented by a first bonded pair of nucleotide sequences, wherein the first bonded pair was formed by a chemical bonding of a first nucleotide chain to a second nucleotide chain, wherein nucleotides of the first nucleotide chain are ordered in the first sequence, wherein nucleotides of the second nucleotide chain are ordered in the second sequence, and wherein the decoded information represents a data structure formed by filling a first slot of the ordered set of slots with the first token; the processor determining that the first token comprises an adjacent pair of duplicate substrings; the processor identifying a second token that, other than omitting one occurrence of the duplicate substrings, is identical to the first token; the processor translating the second token into a listing of a third sequence of nucleotides; and the processor decoding information represented by a second bonded pair of nucleotide sequences, wherein the second bonded pair was formed by a chemical bonding of a third nucleotide chain to a fourth nucleotide chain, wherein nucleotides of the third nucleotide chain are ordered in the third sequence, wherein nucleotides of the fourth nucleotide chain are ordered in the first sequence, and wherein the decoded information represents a data structure formed by filling a first slot of the ordered set of slots with the second token. 5. The method of claim 1 , wherein the vocabulary comprises a dictionary of words comprised by the natural language. | 0.633998 |
1. A method comprising: a database server running on one or more computers; said database server receiving a first database statement; wherein the first database statement requires access to a view defined as combined results of a set of database statements; wherein the first database statement includes an expression that operates on an XML construct; and said database server generating a second database statement, based on the first database statement and the view, that includes a modified version of the set of database statements in the distributive form and rewritten to include the expression that operates on the XML construct. | 1. A method comprising: a database server running on one or more computers; said database server receiving a first database statement; wherein the first database statement requires access to a view defined as combined results of a set of database statements; wherein the first database statement includes an expression that operates on an XML construct; and said database server generating a second database statement, based on the first database statement and the view, that includes a modified version of the set of database statements in the distributive form and rewritten to include the expression that operates on the XML construct. 19. The method of claim 1 , wherein the expression is an XML component operation. | 0.792263 |
8. The method of claim 7 , further comprising separately sorting each subset of documents. | 8. The method of claim 7 , further comprising separately sorting each subset of documents. 9. The method of claim 8 , further comprising dynamically assigning a relevancy limit to the sorted subset and limiting return of query results based upon the assigned relevancy limit. | 0.957993 |
1. A computer-implemented method for determining effectiveness of social media pages hosted by one or more social media systems using content associated with the social media pages and user interaction with the social media pages, comprising the steps of: configuring a database table comprising: a first set of columns storing at least engagement information, wherein the engagement information comprises a number of users engaged with a social media page and one or more engagement parameters associated with user involvement with respect to the social media page, and a second set of columns storing values derived from the first set of columns, wherein the second set of columns are continuously updated based at least in part on adjustments of values of the first set of columns, and wherein the values derived from the first set of columns and stored in the second set of columns are at least evaluation measures; receiving a request for evaluation of a respective social media page maintained within a respective social media system, the respective social media page comprising one or more types of content for dissemination; querying the respective social media system for retrieval of engagement information corresponding to the respective social media page; receiving a response from the respective social media system comprising the engagement information associated with the respective social media page; storing, in the first set of columns in the database table, the engagement information from the respective social media system, wherein the first set of columns further comprises a timestamp column indicating a time an evaluation is performed and a URL corresponding to the respective social media page being evaluated; generating one or more evaluation measures corresponding to the respective social media page, wherein data from the first set of columns in the database table corresponding to the respective social media page are processed to generate values for the second set of columns, and wherein at least one evaluation measure of the one or more evaluation measures is processed based at least in part on: a number of users engaged with the respective social media page, an engagement multiplier indicating a level of engagement of the users relative to an amount of content posted on the social media page, the engagement multiplier is based at least in part upon the one or more engagement parameters retrieved from the first set of columns in the database table, the engagement parameters comprising a number of likes, a number of comments, a number of fans, and a number of posts on the respective social media page, and a selected earned media value representing an advertising cost of a social media interaction; storing, in the second set of columns in the database table, the one or more evaluation measures corresponding to the respective social media page; and generating a graphical user interface comprising the one or more evaluation measures from the first set of columns in the database table, the one or more engagement parameters from the second set of columns in the database table, and one or more user input controls to receive user input adjusting one or more engagement parameters from the first set of columns to re-compute the one or more evaluation measures of the second set of columns. | 1. A computer-implemented method for determining effectiveness of social media pages hosted by one or more social media systems using content associated with the social media pages and user interaction with the social media pages, comprising the steps of: configuring a database table comprising: a first set of columns storing at least engagement information, wherein the engagement information comprises a number of users engaged with a social media page and one or more engagement parameters associated with user involvement with respect to the social media page, and a second set of columns storing values derived from the first set of columns, wherein the second set of columns are continuously updated based at least in part on adjustments of values of the first set of columns, and wherein the values derived from the first set of columns and stored in the second set of columns are at least evaluation measures; receiving a request for evaluation of a respective social media page maintained within a respective social media system, the respective social media page comprising one or more types of content for dissemination; querying the respective social media system for retrieval of engagement information corresponding to the respective social media page; receiving a response from the respective social media system comprising the engagement information associated with the respective social media page; storing, in the first set of columns in the database table, the engagement information from the respective social media system, wherein the first set of columns further comprises a timestamp column indicating a time an evaluation is performed and a URL corresponding to the respective social media page being evaluated; generating one or more evaluation measures corresponding to the respective social media page, wherein data from the first set of columns in the database table corresponding to the respective social media page are processed to generate values for the second set of columns, and wherein at least one evaluation measure of the one or more evaluation measures is processed based at least in part on: a number of users engaged with the respective social media page, an engagement multiplier indicating a level of engagement of the users relative to an amount of content posted on the social media page, the engagement multiplier is based at least in part upon the one or more engagement parameters retrieved from the first set of columns in the database table, the engagement parameters comprising a number of likes, a number of comments, a number of fans, and a number of posts on the respective social media page, and a selected earned media value representing an advertising cost of a social media interaction; storing, in the second set of columns in the database table, the one or more evaluation measures corresponding to the respective social media page; and generating a graphical user interface comprising the one or more evaluation measures from the first set of columns in the database table, the one or more engagement parameters from the second set of columns in the database table, and one or more user input controls to receive user input adjusting one or more engagement parameters from the first set of columns to re-compute the one or more evaluation measures of the second set of columns. 3. The method of claim 1 , further comprising the step of, after the request for evaluation of the respective social media page has been received, determining whether an evaluation has been previously generated for the respective social media page. | 0.53251 |
10. A computing device comprising: a processor; a computer storage operationally coupled to the processor and configured to store a corpus of user utterances received by a conversational agent, configured to be processed computationally by the processor, through an interactive natural language dialog with a user; the conversational agent further configured to perform computationally a linguistics analysis of the corpus of user utterances to identify semantic graphs that match respective user utterances in the corpus; the executing conversational agent still further configured to: cluster computationally the semantic graphs of the utterances in the first corpus based on user intent to form one or more semantic clusters; and attach additional semantic graphs of user utterances to the one or more semantic clusters based on the user intent. | 10. A computing device comprising: a processor; a computer storage operationally coupled to the processor and configured to store a corpus of user utterances received by a conversational agent, configured to be processed computationally by the processor, through an interactive natural language dialog with a user; the conversational agent further configured to perform computationally a linguistics analysis of the corpus of user utterances to identify semantic graphs that match respective user utterances in the corpus; the executing conversational agent still further configured to: cluster computationally the semantic graphs of the utterances in the first corpus based on user intent to form one or more semantic clusters; and attach additional semantic graphs of user utterances to the one or more semantic clusters based on the user intent. 18. The computing device as claimed in claim 10 wherein the executing conversation agent is further configured to leverage the one or more semantic clusters in order to respond to interaction with the user. | 0.608581 |
28. A computer-readable memory device that includes programming instructions to control at least one processor, the computer-readable memory device comprising: instructions for calculating a first value representing a coherence of terms in a sequence of terms; instructions for calculating a second value representing variation of context in which the sequence occurs, where the variation of context in which the sequence occurs is calculated as a measure of entropy of the context of the sequence; instructions for identifying that the sequence is a semantic unit based on the first and second values; and instructions for outputting an indication that the sequence is a semantic unit. | 28. A computer-readable memory device that includes programming instructions to control at least one processor, the computer-readable memory device comprising: instructions for calculating a first value representing a coherence of terms in a sequence of terms; instructions for calculating a second value representing variation of context in which the sequence occurs, where the variation of context in which the sequence occurs is calculated as a measure of entropy of the context of the sequence; instructions for identifying that the sequence is a semantic unit based on the first and second values; and instructions for outputting an indication that the sequence is a semantic unit. 29. The computer-readable memory device of claim 28 , where the coherence of the terms in the sequence is calculated relative to a collection of documents. | 0.752941 |
1. A computer-implemented method for responding to a search request for non-avatar virtual objects present in an immersive virtual environment, comprising: receiving, from a user, a search query for non-avatar virtual objects of the virtual environment, wherein the search query includes one or more attribute conditions identifying characteristics of at least one non-avatar virtual object of the virtual environment, and wherein the search query includes at least one interaction condition describing the user's past interaction with non-avatar virtual objects of the virtual environment; determining a collection of non-avatar virtual objects present in the virtual environment satisfying the one or more attribute conditions of the search query; filtering the collection of non-avatar virtual objects, based on the one or more interaction conditions, to produce a set of search results responsive to the search query; and returning the set of search results to the user. | 1. A computer-implemented method for responding to a search request for non-avatar virtual objects present in an immersive virtual environment, comprising: receiving, from a user, a search query for non-avatar virtual objects of the virtual environment, wherein the search query includes one or more attribute conditions identifying characteristics of at least one non-avatar virtual object of the virtual environment, and wherein the search query includes at least one interaction condition describing the user's past interaction with non-avatar virtual objects of the virtual environment; determining a collection of non-avatar virtual objects present in the virtual environment satisfying the one or more attribute conditions of the search query; filtering the collection of non-avatar virtual objects, based on the one or more interaction conditions, to produce a set of search results responsive to the search query; and returning the set of search results to the user. 6. The method of claim 1 , wherein the interaction condition specifies an action a user avatar performed with a given virtual object present in the virtual environment. | 0.623843 |
9. A computer-implemented method comprising: under direction of one or more hardware processors configured with specific software instructions, receiving, from a user interacting with a textual record including one or more nodes and one or more subnodes, a first input including a command and a node identifier; in response to receiving the command and the node identifier: identifying, based on the node identifier, a node of the textual record associated with the node identifier; determining a first portion of the textual record related to the identified node; and selecting the first portion of the textual record; receiving, from the user interacting with the textual record, a second input including the command and a subnode identifier; and in response to receiving the command and the subnode identifier: identifying, based on the subnode identifier, a subnode of the textual record associated with the subnode identifier; determining a second portion of the textual record related to the identified subnode; and selecting the second portion of the textual record. | 9. A computer-implemented method comprising: under direction of one or more hardware processors configured with specific software instructions, receiving, from a user interacting with a textual record including one or more nodes and one or more subnodes, a first input including a command and a node identifier; in response to receiving the command and the node identifier: identifying, based on the node identifier, a node of the textual record associated with the node identifier; determining a first portion of the textual record related to the identified node; and selecting the first portion of the textual record; receiving, from the user interacting with the textual record, a second input including the command and a subnode identifier; and in response to receiving the command and the subnode identifier: identifying, based on the subnode identifier, a subnode of the textual record associated with the subnode identifier; determining a second portion of the textual record related to the identified subnode; and selecting the second portion of the textual record. 16. The computer-implemented method of claim 9 , wherein the first input comprises a key press input and an audio input. | 0.73303 |
7. A method according to claim 6 , further comprising: digitizing the audio stream to obtain a digitized audio stream; and dividing the digitized audio stream into digitized blocks; wherein the step of dividing is performed prior to the step of segmenting and the step of segmenting comprises a step of segmenting the digitized blocks. | 7. A method according to claim 6 , further comprising: digitizing the audio stream to obtain a digitized audio stream; and dividing the digitized audio stream into digitized blocks; wherein the step of dividing is performed prior to the step of segmenting and the step of segmenting comprises a step of segmenting the digitized blocks. 8. A method according to claim 7 , wherein the windows are overlapping and the step of segmenting the digitized blocks comprises segmenting the digitized blocks into the overlapping windows. | 0.903175 |
1. A computer-readable memory containing therein instructions that, when executed, generate on a display device a graphical user interface (GUI) for creating or revising a rule that contains multiple conditions and an action to be taken when the conditions are satisfied, the GUI comprising: first and second user-selectable elements; a rule-editing area that is configured to: (i) display, upon user selection of the first element, a condition input field set for accepting a first user specification of: (a) an attribute name for each of the conditions, (b) an attribute value for each of the conditions, and (c) a choice between an “and” logical operator and an “or” logical operator for logically connecting two or more of the conditions, wherein the condition input field set accepts user selection of the attribute name for each of the conditions from a list of options for the attribute name for each of the conditions and further accepts user input of text for the attribute value for each of the conditions, wherein, after the first user specification, the rule-editing area displays a user-specified attribute name and attribute value for each of the conditions while the condition input field set is displayed, and (ii) display, upon user selection of the second element, an action input field set for accepting a second user specification of: (d) an action name identifying the action, and (e) an action value for the action, wherein the action input field accepts user selection of the action name from a list of options for the action name and further accepts user input of text for the action value, wherein, after the second user specification, the rule-editing area displays a user-specified action name and action value while the action input field set is displayed, and wherein the condition input field set and the action input field set are not displayed concurrently with each other; and a rule preview area configured to provide, after the first and second user specifications, a display of a user-understandable representation of the rule comprising both the conditions and the action, the rule preview area being displayed both while the condition input field set is displayed and while the action input field set is displayed, the user-understandable representation including at least the user-specified attribute name and attribute value for each of the conditions after the first user specification, and including at least the user-specified action name and action value for the action after the second user specification. | 1. A computer-readable memory containing therein instructions that, when executed, generate on a display device a graphical user interface (GUI) for creating or revising a rule that contains multiple conditions and an action to be taken when the conditions are satisfied, the GUI comprising: first and second user-selectable elements; a rule-editing area that is configured to: (i) display, upon user selection of the first element, a condition input field set for accepting a first user specification of: (a) an attribute name for each of the conditions, (b) an attribute value for each of the conditions, and (c) a choice between an “and” logical operator and an “or” logical operator for logically connecting two or more of the conditions, wherein the condition input field set accepts user selection of the attribute name for each of the conditions from a list of options for the attribute name for each of the conditions and further accepts user input of text for the attribute value for each of the conditions, wherein, after the first user specification, the rule-editing area displays a user-specified attribute name and attribute value for each of the conditions while the condition input field set is displayed, and (ii) display, upon user selection of the second element, an action input field set for accepting a second user specification of: (d) an action name identifying the action, and (e) an action value for the action, wherein the action input field accepts user selection of the action name from a list of options for the action name and further accepts user input of text for the action value, wherein, after the second user specification, the rule-editing area displays a user-specified action name and action value while the action input field set is displayed, and wherein the condition input field set and the action input field set are not displayed concurrently with each other; and a rule preview area configured to provide, after the first and second user specifications, a display of a user-understandable representation of the rule comprising both the conditions and the action, the rule preview area being displayed both while the condition input field set is displayed and while the action input field set is displayed, the user-understandable representation including at least the user-specified attribute name and attribute value for each of the conditions after the first user specification, and including at least the user-specified action name and action value for the action after the second user specification. 7. The computer-readable memory of claim 1 , wherein the first user-selectable element is adjacent to the second user-selectable element. | 0.558632 |
19. A non-transitory computer-readable data storage medium having instructions stored thereon that when executed cause a video coding device to code three-dimensional (3D) video data, the instructions causing the video coding device to: generate a current list of merging candidates for coding a video block of the 3D video data, wherein a maximum number of merging candidates in the current list of merging candidates is equal to 6, there are 20 possible combinations of list 0 and list 1 motion vectors of different bi-predictive merging candidates in lists of merging candidates having 5 bi-predictive merging candidates, and as part of generating the current list of merging candidates, the one or more processors: determine that a number of merging candidates initially in the current list of merging candidates is less than 5, wherein each respective value of a combination index from 0 to 11 corresponds to a respective pre-defined combination of values from 0 to 3; and in response to determining that the number of merging candidates in the current list of merging candidates is less than 5, performing the following for each respective value of the combination index from 0 to 11 until at least one of the following conditions is true: the respective value of the combination index is equal to the number of merging candidates initially in the current list of merging candidates multiplied by one less than the number of merging candidates initially in the current list of merging candidates, and the current list of merging candidates has 6 merging candidates: determine whether a first merging candidate in the current list of merging candidates has a list 0 motion vector and whether a second merging candidate in the current list of merging candidates has a list 1 motion vector, wherein the first merging candidate and the second merging candidate are at positions in the current list of merging candidates indicated by the pre-defined combination of values corresponding to the respective value of the combination index; responsive to determining the first merging candidate has a list 0 motion vector and the second merging candidate has a list 1 motion vector, derive a respective combined bi-predictive merging candidate, wherein the respective combined bi-predictive merging candidate is a combination of the list 0 motion vector of the first merging candidate and the list 1 motion vector of the second merging candidate, wherein the motion vector of the first merging candidate and the motion vector of the second merging candidate refer to pictures in different reference picture lists; and include the respective combined bi-predictive merging candidate in the current list of merging candidates. | 19. A non-transitory computer-readable data storage medium having instructions stored thereon that when executed cause a video coding device to code three-dimensional (3D) video data, the instructions causing the video coding device to: generate a current list of merging candidates for coding a video block of the 3D video data, wherein a maximum number of merging candidates in the current list of merging candidates is equal to 6, there are 20 possible combinations of list 0 and list 1 motion vectors of different bi-predictive merging candidates in lists of merging candidates having 5 bi-predictive merging candidates, and as part of generating the current list of merging candidates, the one or more processors: determine that a number of merging candidates initially in the current list of merging candidates is less than 5, wherein each respective value of a combination index from 0 to 11 corresponds to a respective pre-defined combination of values from 0 to 3; and in response to determining that the number of merging candidates in the current list of merging candidates is less than 5, performing the following for each respective value of the combination index from 0 to 11 until at least one of the following conditions is true: the respective value of the combination index is equal to the number of merging candidates initially in the current list of merging candidates multiplied by one less than the number of merging candidates initially in the current list of merging candidates, and the current list of merging candidates has 6 merging candidates: determine whether a first merging candidate in the current list of merging candidates has a list 0 motion vector and whether a second merging candidate in the current list of merging candidates has a list 1 motion vector, wherein the first merging candidate and the second merging candidate are at positions in the current list of merging candidates indicated by the pre-defined combination of values corresponding to the respective value of the combination index; responsive to determining the first merging candidate has a list 0 motion vector and the second merging candidate has a list 1 motion vector, derive a respective combined bi-predictive merging candidate, wherein the respective combined bi-predictive merging candidate is a combination of the list 0 motion vector of the first merging candidate and the list 1 motion vector of the second merging candidate, wherein the motion vector of the first merging candidate and the motion vector of the second merging candidate refer to pictures in different reference picture lists; and include the respective combined bi-predictive merging candidate in the current list of merging candidates. 21. The non-transitory computer-readable data storage medium of claim 19 , wherein the instructions cause the video coding device to generate the current list of merging candidates without checking any backward warping view synthesis (BVSP) flags. | 0.789055 |
10. A handheld electronic device, comprising: a number of keys, including one or more keys each having at least one non-diacritical version of a linguistic element assigned thereto and at least one diacritical version of the linguistic element assigned thereto; a display; a processor apparatus comprising a processor and a memory in electronic communication with one another, said processor apparatus having stored therein a linguistic source and a number of routines which, when executed on said processor, cause said handheld electronic device to perform operations comprising: detecting selection of one of the keys; based at least in part on the detection of the key selection, determining whether to output (i) a non-diacritical version of a linguistic element assigned to the selected key or (ii) a diacritical version of the linguistic element assigned to the selected key in response to the selection, the determination comprising: determining whether the selection corresponds to a first alphanumeric input for the enabled input, based upon a determination that the selection corresponds to the first alphanumeric input for the enabled input, determining to output the non-diacritical version of the linguistic element assigned to the selected key, and based upon a determination that there have been previous alphanumeric inputs for the enabled input, determining whether to output the non-diacritical version or the diacritical version of the linguistic element based on whether the previous alphanumeric inputs satisfy a predetermined condition; and outputting the determined output using the output apparatus. | 10. A handheld electronic device, comprising: a number of keys, including one or more keys each having at least one non-diacritical version of a linguistic element assigned thereto and at least one diacritical version of the linguistic element assigned thereto; a display; a processor apparatus comprising a processor and a memory in electronic communication with one another, said processor apparatus having stored therein a linguistic source and a number of routines which, when executed on said processor, cause said handheld electronic device to perform operations comprising: detecting selection of one of the keys; based at least in part on the detection of the key selection, determining whether to output (i) a non-diacritical version of a linguistic element assigned to the selected key or (ii) a diacritical version of the linguistic element assigned to the selected key in response to the selection, the determination comprising: determining whether the selection corresponds to a first alphanumeric input for the enabled input, based upon a determination that the selection corresponds to the first alphanumeric input for the enabled input, determining to output the non-diacritical version of the linguistic element assigned to the selected key, and based upon a determination that there have been previous alphanumeric inputs for the enabled input, determining whether to output the non-diacritical version or the diacritical version of the linguistic element based on whether the previous alphanumeric inputs satisfy a predetermined condition; and outputting the determined output using the output apparatus. 17. The handheld electronic device according to claim 10 , wherein the number of routines cause the handheld electronic device to perform operations further comprising outputting another output as an alternative to the determined output selectable by a user. | 0.534239 |
30. A computer-implemented system, comprising: one or more processors; one or more non-transitory computer readable storage media; computer readable instructions stored on the one or more non-transitory computer readable storage media which, when executed by the one or more processors, implement a first cluster configured to perform operations comprising: receiving, at a first cluster, a search query, the first cluster being a first data intake and query system; transmitting, through a firewall of either the first cluster or a cloud-based cluster, a request for information identifying a plurality of indexers of the cloud-based cluster, the cloud-based cluster being a second data intake and query system; in response to the request, obtaining, from the cloud-based cluster, the information identifying the plurality of indexers, wherein the first cluster and the cloud-based cluster each include at least one master node that is knowledgeable about active indexers within its respective cluster, and the information identifies the plurality of indexers based on the at least one master node of the cloud-based cluster identifying the active indexers; distributing the search query to the plurality of indexers of the cloud-based cluster and one or more indexers of the first cluster, said distributing using the obtained information identifying the plurality of indexers and being through the firewall; and receiving, at the first cluster, a response to the distributed search query from at least one of the plurality of indexers of the cloud-based cluster wherein each response from a respective indexer is produced by the respective indexer based on an evaluation, by the respective indexer, of the distributed search query. | 30. A computer-implemented system, comprising: one or more processors; one or more non-transitory computer readable storage media; computer readable instructions stored on the one or more non-transitory computer readable storage media which, when executed by the one or more processors, implement a first cluster configured to perform operations comprising: receiving, at a first cluster, a search query, the first cluster being a first data intake and query system; transmitting, through a firewall of either the first cluster or a cloud-based cluster, a request for information identifying a plurality of indexers of the cloud-based cluster, the cloud-based cluster being a second data intake and query system; in response to the request, obtaining, from the cloud-based cluster, the information identifying the plurality of indexers, wherein the first cluster and the cloud-based cluster each include at least one master node that is knowledgeable about active indexers within its respective cluster, and the information identifies the plurality of indexers based on the at least one master node of the cloud-based cluster identifying the active indexers; distributing the search query to the plurality of indexers of the cloud-based cluster and one or more indexers of the first cluster, said distributing using the obtained information identifying the plurality of indexers and being through the firewall; and receiving, at the first cluster, a response to the distributed search query from at least one of the plurality of indexers of the cloud-based cluster wherein each response from a respective indexer is produced by the respective indexer based on an evaluation, by the respective indexer, of the distributed search query. 38. The system as described in claim 30 , wherein said first cluster is an on-premises cluster. | 0.585304 |
7. A machine-implemented, non-abstract and automated process that provides for adaptive social networking between plural users of a machine system, where the machine system is used in implementing the process and where the process comprises: empowering a first user and/or one or more data processing devices proximate to the first user to cause one or more other data processors of the machine system, which other data processors are operatively coupled to the one or more proximate devices, to home in on one or more of at least one plurality of points, nodes or subregions in a maintained one of plural Communal Cognitions-representing Spaces maintained by the machine system, where the homed-in on points, nodes or subregions are ones determined by the machine system to more likely than others cross-correlate to apparent individualized current cognitions of the first user, wherein the Communal Cognitions-representing Spaces include a Context Space whose points, nodes or subregions include ones representing different user-adoptable roles; wherein said empowering includes machine-implemented identification of the first user; wherein said system-maintained plural Communal Cognitions-representing Spaces each includes stored data-objects representing hierarchically and/or spatially organized at least one plurality of points, nodes or subregions and wherein the hierarchical and/or spatial organizations in the respective Communal Cognitions-representing Space of at least one plurality of the points, nodes or subregions thereof are determined and are modifiable, at least in part, by over-a-network reported actions of a corresponding community formed by at least a subset of the plural users of the machine system; and wherein the empowering of the first user includes: automatically repeatedly carrying out one or more automated informational resource lookup operations on behalf of the first user without need for diverting focusing of attention by the first user for aiding the one or more automated informational resource lookup operations, at least one of the automated informational resource lookup operations being based on an identifying by the machine system of a likely context of the first user among plural contexts represented by the points, nodes or subregions of the Context Space; and providing the first user with an opportunity to access one or more informational resources identified by the machine system based on the one or more automated informational resource lookup operations. | 7. A machine-implemented, non-abstract and automated process that provides for adaptive social networking between plural users of a machine system, where the machine system is used in implementing the process and where the process comprises: empowering a first user and/or one or more data processing devices proximate to the first user to cause one or more other data processors of the machine system, which other data processors are operatively coupled to the one or more proximate devices, to home in on one or more of at least one plurality of points, nodes or subregions in a maintained one of plural Communal Cognitions-representing Spaces maintained by the machine system, where the homed-in on points, nodes or subregions are ones determined by the machine system to more likely than others cross-correlate to apparent individualized current cognitions of the first user, wherein the Communal Cognitions-representing Spaces include a Context Space whose points, nodes or subregions include ones representing different user-adoptable roles; wherein said empowering includes machine-implemented identification of the first user; wherein said system-maintained plural Communal Cognitions-representing Spaces each includes stored data-objects representing hierarchically and/or spatially organized at least one plurality of points, nodes or subregions and wherein the hierarchical and/or spatial organizations in the respective Communal Cognitions-representing Space of at least one plurality of the points, nodes or subregions thereof are determined and are modifiable, at least in part, by over-a-network reported actions of a corresponding community formed by at least a subset of the plural users of the machine system; and wherein the empowering of the first user includes: automatically repeatedly carrying out one or more automated informational resource lookup operations on behalf of the first user without need for diverting focusing of attention by the first user for aiding the one or more automated informational resource lookup operations, at least one of the automated informational resource lookup operations being based on an identifying by the machine system of a likely context of the first user among plural contexts represented by the points, nodes or subregions of the Context Space; and providing the first user with an opportunity to access one or more informational resources identified by the machine system based on the one or more automated informational resource lookup operations. 9. The automated process of claim 7 and further wherein: the stored data-objects of one or more of the plural Communal Cognitions-representing Spaces include hierarchically and/or spatially clustered together ones of points, nodes or subregions of the respective one or more Communal Cognitions-representing Spaces; and the automated process uses a calculated hierarchical and/or spatial distance between the hierarchically and/or spatially clustered together ones of points, nodes or subregions of a respective Communal Cognitions-representing Space to automatically determine how substantially same or similar the one or more points, nodes or subregions in an underlying cognitive sense are to one another. | 0.81675 |
1. A method of matching pattern-based data, comprising: extracting first distinct values from a first input dataset and second distinct values from a second input dataset; generating a first pattern based on symbols appearing in the first distinct values and a second pattern based on symbols appearing in the second distinct values, the first and second patterns comprising nodes and one or more delimiters; calculating support levels for the nodes; removing one or more delimiters from the first and second patterns using the support levels; wherein removing one or more delimiters from the first pattern further comprises calculating the support level at a node by summing support values of incoming transitions to that node; initializing an expansion factor; expanding a language of the first and second patterns at the expansion factor, the expanding of the language diminishing a size of the first and second patterns and decreasing a precision of the first and second patterns, wherein a number of distinct symbols allowed by the expanded language of the first pattern divided by a number of distinct symbols allowed by the non-expanded language of the first pattern equals the expansion factor and a number of distinct symbols allowed by the expanded language of the second pattern divided by a number of distinct symbols allowed by the non-expanded language of the second pattern equals the expansion factor; incrementing the expansion factor and repeating the expanding of the language when the expansion factor is less than a predetermined value; computing a similarity of the first pattern and the second pattern using the expanded language of the first and second patterns; and matching the first input dataset with the second input dataset based on the similarity computation. | 1. A method of matching pattern-based data, comprising: extracting first distinct values from a first input dataset and second distinct values from a second input dataset; generating a first pattern based on symbols appearing in the first distinct values and a second pattern based on symbols appearing in the second distinct values, the first and second patterns comprising nodes and one or more delimiters; calculating support levels for the nodes; removing one or more delimiters from the first and second patterns using the support levels; wherein removing one or more delimiters from the first pattern further comprises calculating the support level at a node by summing support values of incoming transitions to that node; initializing an expansion factor; expanding a language of the first and second patterns at the expansion factor, the expanding of the language diminishing a size of the first and second patterns and decreasing a precision of the first and second patterns, wherein a number of distinct symbols allowed by the expanded language of the first pattern divided by a number of distinct symbols allowed by the non-expanded language of the first pattern equals the expansion factor and a number of distinct symbols allowed by the expanded language of the second pattern divided by a number of distinct symbols allowed by the non-expanded language of the second pattern equals the expansion factor; incrementing the expansion factor and repeating the expanding of the language when the expansion factor is less than a predetermined value; computing a similarity of the first pattern and the second pattern using the expanded language of the first and second patterns; and matching the first input dataset with the second input dataset based on the similarity computation. 12. The method of claim 1 , wherein matching comprises comparing the similarity of the first pattern and the second pattern to a threshold; and determining that the first input dataset matches the second input dataset if the similarity exceeds a predetermined threshold. | 0.5 |
17. A tangible computer-readable medium storing a computer program having instructions which, when executed by a computing device, cause the computing device to perform steps comprising: obtaining a priority of each of at least one task objective based upon a structure of a hierarchy of task objectives; associating the at least one task objective from the hierarchy of task objectives with a first input received from a user, wherein each task objective is assigned corresponding priority; determining an order of implementation of the at least one task objective based on the corresponding priority assigned to each of the task objectives associated with the first input; associating the at least one task objective from the hierarchy of task objectives with a second input received from a user; revising the order of implementation of the at least one task objective based on the corresponding priority assigned to each of the task objectives associated with the first input and the second input, to yield a revised order of implementation; and implementing the task objectives based on the revised order of implementation. | 17. A tangible computer-readable medium storing a computer program having instructions which, when executed by a computing device, cause the computing device to perform steps comprising: obtaining a priority of each of at least one task objective based upon a structure of a hierarchy of task objectives; associating the at least one task objective from the hierarchy of task objectives with a first input received from a user, wherein each task objective is assigned corresponding priority; determining an order of implementation of the at least one task objective based on the corresponding priority assigned to each of the task objectives associated with the first input; associating the at least one task objective from the hierarchy of task objectives with a second input received from a user; revising the order of implementation of the at least one task objective based on the corresponding priority assigned to each of the task objectives associated with the first input and the second input, to yield a revised order of implementation; and implementing the task objectives based on the revised order of implementation. 18. The tangible computer-readable medium of claim 17 , the instructions further comprising applying a threshold to task objectives associated with the first input, wherein task objectives below the threshold are not implemented. | 0.5 |
1. An image forming apparatus comprising: an image reading portion capable of reading image data of a document sheet placed on a document sheet placement surface; two document sheet detection portions configured to detect reflected light when light is emitted on a document sheet through the document sheet placement surface, and disposed at positions that are mutually separated in a main scanning direction on the document sheet placement surface and that are both separated from a predetermined placement reference position on the document sheet placement surface by a predetermined distance in a sub scanning direction; a document sheet cover including a document holding surface that faces the document sheet placement surface and on which first and second areas that are both shaped to be long in the main scanning direction, that are mutually separated in the sub scanning direction, and that have different reflection characteristics, and third and fourth areas that are formed at positions corresponding to irradiation positions of light from the two document sheet detection portions and that have different reflection characteristics, are formed; a first reading control portion configured to cause the image reading portion to read image data of each of the first and second areas, when the document sheet cover is closed with respect to the document sheet placement surface; a first document sheet width detection portion configured to detect, as a width of the document sheet in the main scanning direction, a width that is larger between a width, specified based on the image data read from the first area by the first reading control portion, of the document sheet in the main scanning direction, and a width, specified based on the image data read from the second area by the first reading control portion, of the document sheet in the main scanning direction; and a first size detection portion capable of detecting a size of the document sheet placed on the document sheet placement surface based on detection results from the first document sheet width detection portion and the two document sheet detection portions. | 1. An image forming apparatus comprising: an image reading portion capable of reading image data of a document sheet placed on a document sheet placement surface; two document sheet detection portions configured to detect reflected light when light is emitted on a document sheet through the document sheet placement surface, and disposed at positions that are mutually separated in a main scanning direction on the document sheet placement surface and that are both separated from a predetermined placement reference position on the document sheet placement surface by a predetermined distance in a sub scanning direction; a document sheet cover including a document holding surface that faces the document sheet placement surface and on which first and second areas that are both shaped to be long in the main scanning direction, that are mutually separated in the sub scanning direction, and that have different reflection characteristics, and third and fourth areas that are formed at positions corresponding to irradiation positions of light from the two document sheet detection portions and that have different reflection characteristics, are formed; a first reading control portion configured to cause the image reading portion to read image data of each of the first and second areas, when the document sheet cover is closed with respect to the document sheet placement surface; a first document sheet width detection portion configured to detect, as a width of the document sheet in the main scanning direction, a width that is larger between a width, specified based on the image data read from the first area by the first reading control portion, of the document sheet in the main scanning direction, and a width, specified based on the image data read from the second area by the first reading control portion, of the document sheet in the main scanning direction; and a first size detection portion capable of detecting a size of the document sheet placed on the document sheet placement surface based on detection results from the first document sheet width detection portion and the two document sheet detection portions. 4. The image forming apparatus according to claim 1 , wherein the third area is white and the fourth area is black. | 0.774091 |
1. A method for processing a query, the method comprising: receiving, by a processor, the query from a user; processing, by the processor, the query to locate a plurality of document in accordance with a search engine having a discriminative classifier, wherein the discriminative classifier is trained with a plurality of artificial multi-label query examples, wherein the artificial multi-label query examples comprise simulated queries automatically generated from terms in the plurality of documents, wherein each of the artificial multi-label query examples further comprises a name and metadata information associated with the name, wherein one of the simulated queries comprises a plurality of the terms selected from the plurality of documents; retraining, by the processor, the discriminative classifier based on an update to at least one the plurality of documents and based on an example derived from a log of previous searches; and presenting, by the processor, a result of the processing to the user. | 1. A method for processing a query, the method comprising: receiving, by a processor, the query from a user; processing, by the processor, the query to locate a plurality of document in accordance with a search engine having a discriminative classifier, wherein the discriminative classifier is trained with a plurality of artificial multi-label query examples, wherein the artificial multi-label query examples comprise simulated queries automatically generated from terms in the plurality of documents, wherein each of the artificial multi-label query examples further comprises a name and metadata information associated with the name, wherein one of the simulated queries comprises a plurality of the terms selected from the plurality of documents; retraining, by the processor, the discriminative classifier based on an update to at least one the plurality of documents and based on an example derived from a log of previous searches; and presenting, by the processor, a result of the processing to the user. 3. The method of claim 1 , wherein the discriminative classifier comprises a support vector machine classifier. | 0.81877 |
20. A method comprising: communicating with a first user computer and a second user computer via a network; receiving, a computing device, a unique key value from the first user computer; converting, via the computing device, the unique key value into a word or phrase using a server conversion table, the server conversion table comprising a unique key value for each of a plurality of unique words or phrases, a language key for a plurality of languages, and a plurality of text phrases each corresponding to a language key and a unique key value, and transmitting, over the network, the word or phrase to the second user computer for display. | 20. A method comprising: communicating with a first user computer and a second user computer via a network; receiving, a computing device, a unique key value from the first user computer; converting, via the computing device, the unique key value into a word or phrase using a server conversion table, the server conversion table comprising a unique key value for each of a plurality of unique words or phrases, a language key for a plurality of languages, and a plurality of text phrases each corresponding to a language key and a unique key value, and transmitting, over the network, the word or phrase to the second user computer for display. 21. The method of claim 20 , wherein said converting corresponds to a language key of the second user computer using the server conversion table. | 0.687556 |
1. A system that facilitates access of at least one memory, comprising: the at least one memory that is configured to include a plurality of memory locations; and a memory controller component that is configured to generate and execute a configuration sequence, comprising at least two configuration sequence portions, in a specified order to facilitate performance of a logical block address to physical block address translation associated with the at least one memory based at least in part on the configuration sequence, wherein the configuration sequence is configured to comprise at least a first configuration sequence portion to facilitate performance of a first translation function of a plurality of available translation functions and a second configuration sequence portion to facilitate performance of a second translation function of the plurality of available translation functions, wherein the available translation functions comprise at least two of a calculation function, a table look-up function, or a search function, and wherein one of the calculation function, the table look-up function, or the search function is selected as the first translation function based at least in part on its higher efficiency in determination of a first translation attribute, which relates to the logical block address to physical block address translation, relative to efficiency of other of the available translation functions not selected as the first translation function. | 1. A system that facilitates access of at least one memory, comprising: the at least one memory that is configured to include a plurality of memory locations; and a memory controller component that is configured to generate and execute a configuration sequence, comprising at least two configuration sequence portions, in a specified order to facilitate performance of a logical block address to physical block address translation associated with the at least one memory based at least in part on the configuration sequence, wherein the configuration sequence is configured to comprise at least a first configuration sequence portion to facilitate performance of a first translation function of a plurality of available translation functions and a second configuration sequence portion to facilitate performance of a second translation function of the plurality of available translation functions, wherein the available translation functions comprise at least two of a calculation function, a table look-up function, or a search function, and wherein one of the calculation function, the table look-up function, or the search function is selected as the first translation function based at least in part on its higher efficiency in determination of a first translation attribute, which relates to the logical block address to physical block address translation, relative to efficiency of other of the available translation functions not selected as the first translation function. 2. The system of claim 1 , the logical block address to physical block address translations translation comprises identification of at least one of a memory component, an erase block, a page, or a data block, wherein a physical block address is located based at least in part on information associated with the logical block address. | 0.647165 |
1. A method, comprising: filtering information contained in a plurality of tags stored in a database, the filtering based on one or more specified elements of a tag, wherein the information relates to objects discovered through a capture system, and wherein each object is associated with one of the tags, wherein each of the one or more specified elements includes one of a communication parameter, a content type, a concept, a word, and a signature; generating an Online Analytical Processing (OLAP) element to represent the filtered information; receiving as input one or more parameters based, at least in part, on the OLAP element, wherein each of the one or more parameters includes one of a communication parameter, a content type, a concept, a word, and a signature; and generating a rule from the one or more parameters, wherein the rule includes an action to be performed on one or more objects identified by the one or more parameters, the one or more objects sought to be propagated through e-mail in a network environment. | 1. A method, comprising: filtering information contained in a plurality of tags stored in a database, the filtering based on one or more specified elements of a tag, wherein the information relates to objects discovered through a capture system, and wherein each object is associated with one of the tags, wherein each of the one or more specified elements includes one of a communication parameter, a content type, a concept, a word, and a signature; generating an Online Analytical Processing (OLAP) element to represent the filtered information; receiving as input one or more parameters based, at least in part, on the OLAP element, wherein each of the one or more parameters includes one of a communication parameter, a content type, a concept, a word, and a signature; and generating a rule from the one or more parameters, wherein the rule includes an action to be performed on one or more objects identified by the one or more parameters, the one or more objects sought to be propagated through e-mail in a network environment. 7. The method of claim 1 , further comprising: updating one or more parameters for a rule or a policy; and storing the updates in a database to be accessed by the capture system. | 0.589723 |
29. The method of claim 28 , wherein the one or more time trend statistics include a quality of result difference between two of the quality of result statistics. | 29. The method of claim 28 , wherein the one or more time trend statistics include a quality of result difference between two of the quality of result statistics. 30. The method of claim 29 , further comprising verifying that the quality of result difference satisfies a statistically significant threshold before generating the first modified quality of result statistic. | 0.93962 |
9. 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 an expression in a database query language, the expression having a programming language construct representing an algebraic data type, wherein the expression specifies two or more alternative subtypes, and wherein a particular alternative subtype of the two or more alternative subtypes is a recursively defined subtype; generating respective domain relations using definitions of each of the alternative subtypes within the expression, wherein each domain relation for each alternative subtype has domain tuples belonging to the alternative subtype, including generating a recursively defined domain relation for the recursively defined alternative subtype and performing one or more iterations of recursive evaluation for the recursively defined domain relation to generate one or more new domain tuples belonging to the recursively defined domain relation; generating respective domain id relations for each of the domain relations, wherein each domain id relation for each domain relation of each alternative subtype defines uniquely identified tuples that each assign a unique domain identifier to each of the domain tuples belonging to the respective domain relation of each alternative subtype, including performing, for each domain tuple of one or more new domain tuples generated for the recursively defined domain relation, operations comprising: determining that the elements of the new domain tuple are not represented in a cache of keys; and in response, generating a new domain identifier for the new domain tuple and adding a new domain id tuple to the domain id relation, the new domain id tuple having all elements of the new domain tuple and the new domain identifier; generating a union relation for the algebraic data type, wherein the union relation assigns a respective branch identifier to each of the two or more alternative subtypes and defines union tuples that each have a domain identifier of a domain tuple and a branch identifier of a subtype to which the domain tuple belongs; assigning unique union identifiers for union tuples belonging to the union relation; and generating respective injector relations for each of the alternative subtypes, wherein each injector relation for each alternative subtype defines, for a particular domain tuple of an alternative subtype, an injector tuple having elements from the particular domain tuple and a union identifier corresponding to the particular domain tuple. | 9. 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 an expression in a database query language, the expression having a programming language construct representing an algebraic data type, wherein the expression specifies two or more alternative subtypes, and wherein a particular alternative subtype of the two or more alternative subtypes is a recursively defined subtype; generating respective domain relations using definitions of each of the alternative subtypes within the expression, wherein each domain relation for each alternative subtype has domain tuples belonging to the alternative subtype, including generating a recursively defined domain relation for the recursively defined alternative subtype and performing one or more iterations of recursive evaluation for the recursively defined domain relation to generate one or more new domain tuples belonging to the recursively defined domain relation; generating respective domain id relations for each of the domain relations, wherein each domain id relation for each domain relation of each alternative subtype defines uniquely identified tuples that each assign a unique domain identifier to each of the domain tuples belonging to the respective domain relation of each alternative subtype, including performing, for each domain tuple of one or more new domain tuples generated for the recursively defined domain relation, operations comprising: determining that the elements of the new domain tuple are not represented in a cache of keys; and in response, generating a new domain identifier for the new domain tuple and adding a new domain id tuple to the domain id relation, the new domain id tuple having all elements of the new domain tuple and the new domain identifier; generating a union relation for the algebraic data type, wherein the union relation assigns a respective branch identifier to each of the two or more alternative subtypes and defines union tuples that each have a domain identifier of a domain tuple and a branch identifier of a subtype to which the domain tuple belongs; assigning unique union identifiers for union tuples belonging to the union relation; and generating respective injector relations for each of the alternative subtypes, wherein each injector relation for each alternative subtype defines, for a particular domain tuple of an alternative subtype, an injector tuple having elements from the particular domain tuple and a union identifier corresponding to the particular domain tuple. 12. The system of claim 9 , wherein the operations further comprise: receiving a query that references a variable having the algebraic data type; and computing one or more tuples that satisfy the query, wherein each of the one or more tuples that satisfies the query is an injector tuple defined by a respective injector relation of one of the alternative subtypes for the algebraic data type. | 0.5 |
8. The method of claim 1 further comprising displaying information regarding the text item in a visualization using the analysis of the first and second representations. | 8. The method of claim 1 further comprising displaying information regarding the text item in a visualization using the analysis of the first and second representations. 9. The method of claim 8 further comprising accessing user input, generating a third representation of the text item responsive to the user input, and displaying information regarding the text item in another visualization using the third representation. | 0.897755 |
1. A method for distributed control of a process, comprising: accessing a multi-Boolean function block configured to receive a plurality of inputs, to perform multiple Boolean logical operations based on the inputs, and to output any one of a plurality of logical outputs based upon the Boolean logical operations, wherein the plurality of inputs are accessible from the multi-Boolean function block as both a single bundle of the plurality of inputs and as the plurality of individual inputs, and the plurality of logical outputs are accessible from the multi-Boolean function block as both a single bundle of the plurality of logical outputs and as the plurality of individual logical outputs; configuring the multi-Boolean function block for a particular automation process; and downloading the configured multi-Boolean function block into a low-level distributed automation device. | 1. A method for distributed control of a process, comprising: accessing a multi-Boolean function block configured to receive a plurality of inputs, to perform multiple Boolean logical operations based on the inputs, and to output any one of a plurality of logical outputs based upon the Boolean logical operations, wherein the plurality of inputs are accessible from the multi-Boolean function block as both a single bundle of the plurality of inputs and as the plurality of individual inputs, and the plurality of logical outputs are accessible from the multi-Boolean function block as both a single bundle of the plurality of logical outputs and as the plurality of individual logical outputs; configuring the multi-Boolean function block for a particular automation process; and downloading the configured multi-Boolean function block into a low-level distributed automation device. 17. The method of claim 1 , comprising uploading the multi-Boolean function block from the low-level distributed automation device to a configuration station. | 0.786134 |
8. A method for optimizing a query, comprising: building a data structure for a query, the data structure including a plurality of components, wherein each of the plurality of components corresponds to at least one graph pattern; determining a plurality of flows of query variables between the plurality of components; generating one or more constraints to dynamically eliminate invalid flows from the plurality of flows of query variables, wherein a flow is determined to be invalid if the flow would violate semantics of one or more control statements in the query; wherein the one or more constraints are expressed as a function of decision variables and comprise one or more of at least one component constraint enforcing semantics of an external view of the plurality of components, at least one graph constraint enforcing semantics of the plurality of flows of query variables, and at least one predecessor constraint enforcing semantics of one or more potential predecessors; formulating a cost function associated with the plurality of flows; and outputting a query plan based on the cost function, wherein outputting the query plan comprises determining a combination of the plurality of flows that results in a minimum cost under the one or more constraints. | 8. A method for optimizing a query, comprising: building a data structure for a query, the data structure including a plurality of components, wherein each of the plurality of components corresponds to at least one graph pattern; determining a plurality of flows of query variables between the plurality of components; generating one or more constraints to dynamically eliminate invalid flows from the plurality of flows of query variables, wherein a flow is determined to be invalid if the flow would violate semantics of one or more control statements in the query; wherein the one or more constraints are expressed as a function of decision variables and comprise one or more of at least one component constraint enforcing semantics of an external view of the plurality of components, at least one graph constraint enforcing semantics of the plurality of flows of query variables, and at least one predecessor constraint enforcing semantics of one or more potential predecessors; formulating a cost function associated with the plurality of flows; and outputting a query plan based on the cost function, wherein outputting the query plan comprises determining a combination of the plurality of flows that results in a minimum cost under the one or more constraints. 17. The method of claim 8 , wherein the one or more constraints further comprise at least one output pin constraint controlling an activation of output pins of the plurality of components. | 0.631224 |
14. The mobile device of claim 13 , wherein the mobile device comprises a smart phone. | 14. The mobile device of claim 13 , wherein the mobile device comprises a smart phone. 16. The mobile device of claim 14 further comprising: a speaker, and wherein the biosensor data indicator comprises an audio signal propagated by the speaker of the smart phone. | 0.934703 |
1. A modem for use at a terminal, the modem comprising: first interface apparatus comprising a first wireless transceiver arranged to connect to a wireless cellular network; second interface apparatus arranged to connect to the terminal; and processing apparatus configured to perform operations of a wireless cellular modem so as to enable the terminal to access a further, packet-based network via the second interface apparatus, the first interface apparatus and a plurality of access points of the wireless cellular network, each of the plurality of access points of the wireless cellular network having a respective name; wherein each of said plurality of access points is configured according to a different version of a packet communication protocol, said plurality of access points comprising at least a first access point configured according to a first version of the packet communication protocol and a second access point configured according to a second version of the packet communication protocol; wherein the processing apparatus is configured to receive a modem command from the terminal via the second interface apparatus, the modem command comprising a field for specifying the name of one of said plurality of access points in the form of a text string; wherein said field comprises a plurality of names, wherein in each name corresponds to one of said plurality of access points of the wireless cellular network and one or more separator characters between each of the names in the field; and wherein the processing apparatus is configured to extract each of the names of said plurality of access points from said field based on the one or more separator characters, and to establish a first channel with the first access point based on a first of the names extracted from said field, and establish a second channel with the second access point based on a second of the names extracted from said field. | 1. A modem for use at a terminal, the modem comprising: first interface apparatus comprising a first wireless transceiver arranged to connect to a wireless cellular network; second interface apparatus arranged to connect to the terminal; and processing apparatus configured to perform operations of a wireless cellular modem so as to enable the terminal to access a further, packet-based network via the second interface apparatus, the first interface apparatus and a plurality of access points of the wireless cellular network, each of the plurality of access points of the wireless cellular network having a respective name; wherein each of said plurality of access points is configured according to a different version of a packet communication protocol, said plurality of access points comprising at least a first access point configured according to a first version of the packet communication protocol and a second access point configured according to a second version of the packet communication protocol; wherein the processing apparatus is configured to receive a modem command from the terminal via the second interface apparatus, the modem command comprising a field for specifying the name of one of said plurality of access points in the form of a text string; wherein said field comprises a plurality of names, wherein in each name corresponds to one of said plurality of access points of the wireless cellular network and one or more separator characters between each of the names in the field; and wherein the processing apparatus is configured to extract each of the names of said plurality of access points from said field based on the one or more separator characters, and to establish a first channel with the first access point based on a first of the names extracted from said field, and establish a second channel with the second access point based on a second of the names extracted from said field. 16. The modem of claim 1 , wherein the modem comprises an external unit for use at the terminal. | 0.549836 |
10. A computer program product for matching a Uniform Resource Locator (URL) to a resource or rule, the computer program product comprising: a computer readable storage medium comprising computer readable instructions, the computer readable instructions comprising: first instructions for progressively hashing a clause of the URL, character by character individually, to generate a hash code associated with the clause; second instructions for determining if a delimiting character is encountered; third instructions for using the hash code associated with the clause to traverse a tree data structure representing clauses of URLs and corresponding resources or rules, wherein each node of the tree data structure has an associated multidimensional hash table, wherein using the hash code includes calculating a target value based on the hash code and dimensions of a multidimensional hash table associated with a current node in the tree data structure; and fourth instructions for matching the URL to resources or rules based on the traversing of the tree data structure. | 10. A computer program product for matching a Uniform Resource Locator (URL) to a resource or rule, the computer program product comprising: a computer readable storage medium comprising computer readable instructions, the computer readable instructions comprising: first instructions for progressively hashing a clause of the URL, character by character individually, to generate a hash code associated with the clause; second instructions for determining if a delimiting character is encountered; third instructions for using the hash code associated with the clause to traverse a tree data structure representing clauses of URLs and corresponding resources or rules, wherein each node of the tree data structure has an associated multidimensional hash table, wherein using the hash code includes calculating a target value based on the hash code and dimensions of a multidimensional hash table associated with a current node in the tree data structure; and fourth instructions for matching the URL to resources or rules based on the traversing of the tree data structure. 11. The computer program product of claim 10 , wherein the third instructions for using the hash code further include instructions for using the target value to identify an entry in the multidimensional hash table corresponding to a subtree associated with the clause. | 0.548436 |
1. An apparatus for document identification, having: a capture device for capturing a document feature of a document; a processor designed to perform document identification locally using the document feature if a processing criterion for the local performance of document identification by the apparatus for document identification is satisfied; and a transmitter designed to send a data record that is dependent on the document feature via a communication network to a communication network address if the processing criterion for the local performance of document identification by the apparatus for document identification is not satisfied; wherein the processing criterion is satisfied if the available processing resources of the apparatus are sufficient for performing document identification, or if the size of the document feature is below a prescribed threshold value, or if a data transmission speed of the communication network is below a threshold value, and wherein the processing criterion is not satisfied, if the available processing resources of the apparatus are not sufficient for performing document identification, or if the size of the document feature exceeds a prescribed threshold value, or if a connection speed via the communication network is below a threshold value. | 1. An apparatus for document identification, having: a capture device for capturing a document feature of a document; a processor designed to perform document identification locally using the document feature if a processing criterion for the local performance of document identification by the apparatus for document identification is satisfied; and a transmitter designed to send a data record that is dependent on the document feature via a communication network to a communication network address if the processing criterion for the local performance of document identification by the apparatus for document identification is not satisfied; wherein the processing criterion is satisfied if the available processing resources of the apparatus are sufficient for performing document identification, or if the size of the document feature is below a prescribed threshold value, or if a data transmission speed of the communication network is below a threshold value, and wherein the processing criterion is not satisfied, if the available processing resources of the apparatus are not sufficient for performing document identification, or if the size of the document feature exceeds a prescribed threshold value, or if a connection speed via the communication network is below a threshold value. 14. The apparatus as claimed in claim 1 , which is a mobile telecommunication device. | 0.641118 |
2. The method of claim 1 , further comprising: receiving a selection of the one or more pages; providing, for display, a menu including information regarding one or more categories associated with the plurality of topics; receiving a selection, using the menu, of the one of the one or more categories; and providing, for display, information associated with the selected one of the one or more categories. | 2. The method of claim 1 , further comprising: receiving a selection of the one or more pages; providing, for display, a menu including information regarding one or more categories associated with the plurality of topics; receiving a selection, using the menu, of the one of the one or more categories; and providing, for display, information associated with the selected one of the one or more categories. 3. The method of claim 2 , where the information associated with the selected one of the one or more categories includes the at least one link to a topic, of the respective plurality of topics, the method further comprising: receiving a selection of a link, of the at least one link; and providing, for display, a document including content associated with the selected link. | 0.8314 |
1. A method for processing data in one or more data storage systems, the method including: receiving mapping information that specifies one or more attributes of one or more destination entities in terms of one or more attributes of one or more source entities, at least some of the one or more source entities corresponding to respective sets of records in the one or more data storage systems; and processing the mapping information to generate a procedural specification for computing values corresponding to at least some of the one or more attributes of one or more destination entities, the processing including generating a plurality of collections of nodes, each collection including a first node representing a first relational expression associated with an attribute specified by the mapping information, and at least some collections forming a directed acyclic graph that includes links to one or more other nodes representing respective relational expressions associated with at least one attribute of at least one source entity referenced by a relational expression of a node in the directed acyclic graph, and merging at least two of the collections with each other to form a third collection based on comparing relational expressions of nodes being merged. | 1. A method for processing data in one or more data storage systems, the method including: receiving mapping information that specifies one or more attributes of one or more destination entities in terms of one or more attributes of one or more source entities, at least some of the one or more source entities corresponding to respective sets of records in the one or more data storage systems; and processing the mapping information to generate a procedural specification for computing values corresponding to at least some of the one or more attributes of one or more destination entities, the processing including generating a plurality of collections of nodes, each collection including a first node representing a first relational expression associated with an attribute specified by the mapping information, and at least some collections forming a directed acyclic graph that includes links to one or more other nodes representing respective relational expressions associated with at least one attribute of at least one source entity referenced by a relational expression of a node in the directed acyclic graph, and merging at least two of the collections with each other to form a third collection based on comparing relational expressions of nodes being merged. 2. The method of claim 1 , wherein the mapping information includes a first mapping rule that defines a value of an attribute of a destination entity in terms of a value of an attribute of a first source entity and a value of an attribute of a second source entity. | 0.585125 |
14. The method of claim 13 , further comprising: automatically generating data classification rules based at least in part on a subset of the first set of selected codes, a subset of second set of selected codes, the set of data items in the training data set, the first trust score, and the second trust score; automatically applying the data classification rules to the first data set; and generating a set of selected classification codes for the first data set. | 14. The method of claim 13 , further comprising: automatically generating data classification rules based at least in part on a subset of the first set of selected codes, a subset of second set of selected codes, the set of data items in the training data set, the first trust score, and the second trust score; automatically applying the data classification rules to the first data set; and generating a set of selected classification codes for the first data set. 15. The method of claim 14 , wherein the first set of selected codes are given more weight than a second set of selected codes because of the first trust score being higher than the second trust score. | 0.966164 |
29. A device for presenting web content comprising: a hardware network interface configured to receive encoded content, the encoded content includes text-based content extracted from web content, and the encoded content is encoded by an encoding device in a format suitable for presenting the text-based content as spoken audio using a template automatically selected by an encoding device processor of the encoding device based on one or more of a type of the text-based content and a content provider for the text-based content, the template including placeholders to be replaced with respective portions of the text-based content, a configuration of the template and the placeholders in the template being selected based on the type of the text-based content and selectively employed to generate the encoded content; a display configured to display a user interface for requesting, presenting, and selecting web text items; an audio output device configured to output speech audio; a processor; and a computer-readable storage medium storing instructions executable by the processor to: decode the encoded content with a decoding module to access the text-based content, the text-based content being accessed, via the hardware network interface, from a content database including one or more web text tables for storing each item of the text-based content in respective rows of the web text tables, the content database including a category table for storing available categories of text-based content in respective rows of the category table, where each web text table of the one or more web text tables is associated with a different type of web text stored in that web text table, and each web text table includes different fields from other web text tables based on the type of web text stored in that web text table; display the user interface including a plurality of panels, the plurality of panels including an item list panel for displaying one or more web text items of the text-based content, and a content panel for displaying at least a portion of a selected web text item of the text-based content; generate a speech audio signal based on the text-based content with a text-to-speech module responsive to receiving input to the user interface requesting a first web text item to be output as spoken audio; and output the speech audio signal via the audio output device to present the first web text item as spoken audio. | 29. A device for presenting web content comprising: a hardware network interface configured to receive encoded content, the encoded content includes text-based content extracted from web content, and the encoded content is encoded by an encoding device in a format suitable for presenting the text-based content as spoken audio using a template automatically selected by an encoding device processor of the encoding device based on one or more of a type of the text-based content and a content provider for the text-based content, the template including placeholders to be replaced with respective portions of the text-based content, a configuration of the template and the placeholders in the template being selected based on the type of the text-based content and selectively employed to generate the encoded content; a display configured to display a user interface for requesting, presenting, and selecting web text items; an audio output device configured to output speech audio; a processor; and a computer-readable storage medium storing instructions executable by the processor to: decode the encoded content with a decoding module to access the text-based content, the text-based content being accessed, via the hardware network interface, from a content database including one or more web text tables for storing each item of the text-based content in respective rows of the web text tables, the content database including a category table for storing available categories of text-based content in respective rows of the category table, where each web text table of the one or more web text tables is associated with a different type of web text stored in that web text table, and each web text table includes different fields from other web text tables based on the type of web text stored in that web text table; display the user interface including a plurality of panels, the plurality of panels including an item list panel for displaying one or more web text items of the text-based content, and a content panel for displaying at least a portion of a selected web text item of the text-based content; generate a speech audio signal based on the text-based content with a text-to-speech module responsive to receiving input to the user interface requesting a first web text item to be output as spoken audio; and output the speech audio signal via the audio output device to present the first web text item as spoken audio. 39. The device of claim 29 where the speech audio signal is a pulse code modulated signal. | 0.58026 |
1. A computer implemented method for inferring a probability of a first inference relating to a drug, the computer implemented method comprising: importing additional data into the plurality of data, wherein the additional data initially is not associated with metadata and the additional data does not conform to the dimensions of the database; conforming the additional data to the dimensions of the database; associating metadata and a key with each datum of the additional data; receiving a query at a database regarding a fact related to the drug, wherein the first inference is absent from the database, wherein the database comprises a plurality of divergent data, wherein the plurality of divergent data includes a plurality of cohort data, wherein each datum of the database is conformed to the dimensions of the database, wherein each datum of the plurality of data has associated metadata and an associated key, wherein the associated metadata comprises data regarding cohorts associated with the corresponding datum, data regarding hierarchies associated with the corresponding datum, data regarding a corresponding source of the datum, and data regarding probabilities associated with integrity, reliability, and importance of each associated datum; establishing the fact as a frame of reference for the query; determining an I th set of rules using a J th set of rules, wherein the J th set of rules, wherein J=1 is the first iteration of a recursion process and I-1 is the J th iteration of the recursion process, wherein the I th set of rules is a first set of rules, and wherein the J th set of rules is a second set of rules; applying the first set of rules to the query, wherein the first set of rules are determined for the query according to the second set of rules, wherein the frame of reference serves as an anchor for generating associations among the plurality of cohort data and is used to determine rules for limiting the plurality of divergent data that is searched, wherein the first set of rules determine how the plurality of divergent data are to be compared to the fact, and wherein the first set of rules determine a search space for the query; executing the query to create the first inference and the probability of the first inference, wherein the probability of the first inference is determined from comparing the plurality of data according to the first set of rules, wherein the probability of the first inference is based on factors selected from the group consisting of: a timing of the plurality of data according to the first set of rules, a source of the plurality of data according to the first set of rules, a trustworthiness of the plurality of data according to the first set of rules, a relevance of the plurality of data according to the first set of rules the plurality of data according to the first set of rules, a reliability of the plurality of data according to the first set of rules, an importance of the plurality of data according to the first set of rules, a data integrity of the plurality of data according to the first set of rules, and cohort information of the plurality of data according to the first set of rules, wherein a combination of the factors has a synergistic effect on the probability of the first inference; and storing the probability of the first inference, wherein subsequently viewing the first inference is accessible to individuals having one of a set of different security access clearances based on the probability of the first inference having a higher or lower threshold of certainty probabilities of inferences when the inference implicates medical privacy laws, wherein first ones the individuals having a first one of the set of different security access clearances are permitted to viewing the first inference, and, wherein second ones the individuals having a second one of the set of different security access clearances are not permitted to viewing the first inference. | 1. A computer implemented method for inferring a probability of a first inference relating to a drug, the computer implemented method comprising: importing additional data into the plurality of data, wherein the additional data initially is not associated with metadata and the additional data does not conform to the dimensions of the database; conforming the additional data to the dimensions of the database; associating metadata and a key with each datum of the additional data; receiving a query at a database regarding a fact related to the drug, wherein the first inference is absent from the database, wherein the database comprises a plurality of divergent data, wherein the plurality of divergent data includes a plurality of cohort data, wherein each datum of the database is conformed to the dimensions of the database, wherein each datum of the plurality of data has associated metadata and an associated key, wherein the associated metadata comprises data regarding cohorts associated with the corresponding datum, data regarding hierarchies associated with the corresponding datum, data regarding a corresponding source of the datum, and data regarding probabilities associated with integrity, reliability, and importance of each associated datum; establishing the fact as a frame of reference for the query; determining an I th set of rules using a J th set of rules, wherein the J th set of rules, wherein J=1 is the first iteration of a recursion process and I-1 is the J th iteration of the recursion process, wherein the I th set of rules is a first set of rules, and wherein the J th set of rules is a second set of rules; applying the first set of rules to the query, wherein the first set of rules are determined for the query according to the second set of rules, wherein the frame of reference serves as an anchor for generating associations among the plurality of cohort data and is used to determine rules for limiting the plurality of divergent data that is searched, wherein the first set of rules determine how the plurality of divergent data are to be compared to the fact, and wherein the first set of rules determine a search space for the query; executing the query to create the first inference and the probability of the first inference, wherein the probability of the first inference is determined from comparing the plurality of data according to the first set of rules, wherein the probability of the first inference is based on factors selected from the group consisting of: a timing of the plurality of data according to the first set of rules, a source of the plurality of data according to the first set of rules, a trustworthiness of the plurality of data according to the first set of rules, a relevance of the plurality of data according to the first set of rules the plurality of data according to the first set of rules, a reliability of the plurality of data according to the first set of rules, an importance of the plurality of data according to the first set of rules, a data integrity of the plurality of data according to the first set of rules, and cohort information of the plurality of data according to the first set of rules, wherein a combination of the factors has a synergistic effect on the probability of the first inference; and storing the probability of the first inference, wherein subsequently viewing the first inference is accessible to individuals having one of a set of different security access clearances based on the probability of the first inference having a higher or lower threshold of certainty probabilities of inferences when the inference implicates medical privacy laws, wherein first ones the individuals having a first one of the set of different security access clearances are permitted to viewing the first inference, and, wherein second ones the individuals having a second one of the set of different security access clearances are not permitted to viewing the first inference. 12. The computer implemented method of claim 1 further comprising: responsive to receiving an additional datum in the database, establishing a second query; applying a third set of rules to the query, wherein the third set of rules are determined for the second query according to a fourth set of rules, and wherein the third set of rules determine how the plurality of data are to be compared to the fact; and executing the second query to create a second probability of a second inference relating to the drug, wherein the second probability of the second inference is determined from comparing the plurality of data according to the third set of rules. | 0.518476 |
1. A method for creating a presentation, comprising the steps of: (a) receiving information indicative of a goal; (b) integrating information that motivates accomplishment of the goal for use in the presentation; (c) managing information flow utilizing a linked list; and (d) evaluating progress toward the goal and providing feedback that further motivates accomplishment of the goal. | 1. A method for creating a presentation, comprising the steps of: (a) receiving information indicative of a goal; (b) integrating information that motivates accomplishment of the goal for use in the presentation; (c) managing information flow utilizing a linked list; and (d) evaluating progress toward the goal and providing feedback that further motivates accomplishment of the goal. 5. A method for creating a presentation as recited in claim 1, including the step of allowing controlling the presentation based on the progress of a student. | 0.799748 |
39. The computer readable storage medium of claim 38 wherein the question control activates the answer control. | 39. The computer readable storage medium of claim 38 wherein the question control activates the answer control. 43. The computer readable storage medium of claim 39 wherein the second set of controls comprise: a command control for generating markup related to a grammar for one of navigation in the markup, help with a task, and repeating an audible prompt. | 0.960572 |
25. A method of receiving a response generated by machine learning in the selection of a ranked response to a structured data input having a natural language processing output schema received from a requesting device, the method comprising: in an electronic, machine learning processing system: receiving the response generated by: receiving the structured data input, wherein the structured data input includes filtering parameters for conversion into response template filtering criteria; converting the filtering parameters into the response template filtering criteria; querying a library of response templates to identify candidate response templates that meet the response template filtering criteria to filter the response templates; receiving a selection of the candidate response templates that meet the response template filtering criteria and respond to the structured input data, wherein the candidate response templates include static data; operating a ranking engine to rank the selection of candidate response templates in accordance with ranking criteria; selecting a highest ranked candidate response template to provide a response to a device; and deriving the response to the structured data input from the selected, highest ranked, candidate response template. | 25. A method of receiving a response generated by machine learning in the selection of a ranked response to a structured data input having a natural language processing output schema received from a requesting device, the method comprising: in an electronic, machine learning processing system: receiving the response generated by: receiving the structured data input, wherein the structured data input includes filtering parameters for conversion into response template filtering criteria; converting the filtering parameters into the response template filtering criteria; querying a library of response templates to identify candidate response templates that meet the response template filtering criteria to filter the response templates; receiving a selection of the candidate response templates that meet the response template filtering criteria and respond to the structured input data, wherein the candidate response templates include static data; operating a ranking engine to rank the selection of candidate response templates in accordance with ranking criteria; selecting a highest ranked candidate response template to provide a response to a device; and deriving the response to the structured data input from the selected, highest ranked, candidate response template. 28. The method of claim 25 wherein at least a proper subset of the response templates include one or more dynamic fields, the method further comprising: populating the one or more dynamic data fields of at least one of the candidate response templates with data obtained from the structured data input. | 0.584525 |
10. The computer-readable storage medium of claim 8 wherein the computer-executable instructions provide for the further step of requesting a segment of an audio signal, the segment containing less than the entire time span of the audio signal, based on an indication that a user has selected a marker. | 10. The computer-readable storage medium of claim 8 wherein the computer-executable instructions provide for the further step of requesting a segment of an audio signal, the segment containing less than the entire time span of the audio signal, based on an indication that a user has selected a marker. 11. The computer-readable storage medium of claim 10 wherein the computer-executable instructions provide for the further step of displaying a selectable item to allow a user to request a listing of the query terms represented by markers on the timeline. | 0.906303 |
3. The system of claim 1 , wherein positioning of a cursor over one of the search terms rearranges the search terms on the map to correspond to an increased relevance of that search term, while the cursor is over that search term. | 3. The system of claim 1 , wherein positioning of a cursor over one of the search terms rearranges the search terms on the map to correspond to an increased relevance of that search term, while the cursor is over that search term. 5. The system of claim 3 , wherein clicking on that search term rearranges the map to increase importance of the selected search term in the search query. | 0.937701 |
1. A method of generating a virtual suffix tree (ViST) structure for searching XML documents, comprising: receiving one or more XML documents; converting the one or more XML documents into respective structure-encoded sequences; generating the ViST structure comprising: generating a D-Ancestor index of node pairs in the respective structure-encoded sequences; generating an S-Ancestor index of labels in one or more suffix trees corresponding to respective ones of the structure-encoded sequences; and generating a doc-ID index encoding the D-Ancestor index and the S-Ancestor index for each node of the structure-encoded sequences, wherein the encoding of the doc-ID index contains an answer to a query matching a non-contiguous subsequence in the doc-ID index; and updating the ViST structure, the updating comprising: receiving a new XML document; transforming the new XML document into a respecitve structure-encoded sequence; inserting each element of the sequence into the D-Ancestor index to update relationships among nodes of the D-Ancestor index wherein the insertion of at least one of the elements results in the creation of a new node; assigning a new label to the new node based on an estimated number of different elements following the element corresponding to the new node and an occurrence probability of each of the elements following the element corresponding to the new node; and inserting the new label into the S-Ancestor index. | 1. A method of generating a virtual suffix tree (ViST) structure for searching XML documents, comprising: receiving one or more XML documents; converting the one or more XML documents into respective structure-encoded sequences; generating the ViST structure comprising: generating a D-Ancestor index of node pairs in the respective structure-encoded sequences; generating an S-Ancestor index of labels in one or more suffix trees corresponding to respective ones of the structure-encoded sequences; and generating a doc-ID index encoding the D-Ancestor index and the S-Ancestor index for each node of the structure-encoded sequences, wherein the encoding of the doc-ID index contains an answer to a query matching a non-contiguous subsequence in the doc-ID index; and updating the ViST structure, the updating comprising: receiving a new XML document; transforming the new XML document into a respecitve structure-encoded sequence; inserting each element of the sequence into the D-Ancestor index to update relationships among nodes of the D-Ancestor index wherein the insertion of at least one of the elements results in the creation of a new node; assigning a new label to the new node based on an estimated number of different elements following the element corresponding to the new node and an occurrence probability of each of the elements following the element corresponding to the new node; and inserting the new label into the S-Ancestor index. 2. The method of claim 1 , wherein generating the D-Ancestor index comprises generating a D-Ancestor B+Tree, wherein the D-Ancestor B+Tree indexes one or more (key, data) pairs and wherein the key element is a unique (symbol,path) pair in the one or more structure-encoded sequences, and the data element is a pointer to an S-Ancestor B+Tree. | 0.53753 |
1. A computer implemented method for creating a call routing system, the computer implemented method comprising: receiving a set of initial target classes and a corresponding set of topic descriptions; identifying non-overlapping semantic tokens from the set of topic descriptions; identifying a set of clear target classes from the non-overlapping semantic tokens and the set of initial target classes; identifying overlapping semantic tokens from the set of topic descriptions; identifying a set of vague classes from the overlapping semantic tokens and the initial target classes; generating a set of disambiguation dialogues and a set of grammar prompts according to the non-overlapping semantic tokens; and creating the call routing system based on the set of clear target classes, the set of vague target classes, and the set of disambiguation dialogues. | 1. A computer implemented method for creating a call routing system, the computer implemented method comprising: receiving a set of initial target classes and a corresponding set of topic descriptions; identifying non-overlapping semantic tokens from the set of topic descriptions; identifying a set of clear target classes from the non-overlapping semantic tokens and the set of initial target classes; identifying overlapping semantic tokens from the set of topic descriptions; identifying a set of vague classes from the overlapping semantic tokens and the initial target classes; generating a set of disambiguation dialogues and a set of grammar prompts according to the non-overlapping semantic tokens; and creating the call routing system based on the set of clear target classes, the set of vague target classes, and the set of disambiguation dialogues. 3. The computer implemented method of claim 1 , the computer implemented method further comprising: identifying the overlapping semantic tokens from the set of topic descriptions, wherein the overlapping semantic tokens are maximum length semantic tokens. | 0.852056 |
1. A computer-implemented method for information seeking in a multimedia collection of objects comprising: through a graphical user interface, receiving at least one of an input text query and an input image query; providing for a user to select a subset of objects from a multimedia collection, at least some of the objects in the collection comprising first and second modalities, wherein the first and second modalities comprise a text modality and an image modality; displaying representations of objects in the subset on a local map; at each of a plurality of iterations: providing for the user to annotate the text and image modalities of an object represented in the local map with a relevance label, wherein an object's text modality and image modality are labeled independently; automatically assigning a default forgetting factor for at least one of the first and second modalities, or providing for the user to select the forgetting factor for the at least one of the first and second modalities; automatically assigning a default locality factor for at least one annotated object, or providing for the user to select a locality factor for the at least one annotated object; with a computer processor, computing relevance scores for unlabeled objects in the collection, each relevance score taking into account labels applied to other objects, computed similarity measures between one of the unlabeled objects and the other objects in the collection, the locality factor selected by the user or the default locality factor, and the forgetting factor selected by the user or the default forgetting factor, the forgetting factor placing a greater weight on objects labeled in a more recent iteration; modifying the local map based on the computed relevance scores; and displaying the modified local map on a visual display. | 1. A computer-implemented method for information seeking in a multimedia collection of objects comprising: through a graphical user interface, receiving at least one of an input text query and an input image query; providing for a user to select a subset of objects from a multimedia collection, at least some of the objects in the collection comprising first and second modalities, wherein the first and second modalities comprise a text modality and an image modality; displaying representations of objects in the subset on a local map; at each of a plurality of iterations: providing for the user to annotate the text and image modalities of an object represented in the local map with a relevance label, wherein an object's text modality and image modality are labeled independently; automatically assigning a default forgetting factor for at least one of the first and second modalities, or providing for the user to select the forgetting factor for the at least one of the first and second modalities; automatically assigning a default locality factor for at least one annotated object, or providing for the user to select a locality factor for the at least one annotated object; with a computer processor, computing relevance scores for unlabeled objects in the collection, each relevance score taking into account labels applied to other objects, computed similarity measures between one of the unlabeled objects and the other objects in the collection, the locality factor selected by the user or the default locality factor, and the forgetting factor selected by the user or the default forgetting factor, the forgetting factor placing a greater weight on objects labeled in a more recent iteration; modifying the local map based on the computed relevance scores; and displaying the modified local map on a visual display. 15. The method of claim 1 , wherein the relevance scores for unlabeled objects in the collection are computed with an equation which includes: a first term which takes into account relevance feedback and pseudo-relevance feedback of positively labeled text portions of other objects; a second term which takes into account relevance feedback and pseudo-relevance feedback of negatively labeled text portions of other objects; a third term which takes into account relevance feedback and pseudo-relevance feedback of positively labeled image portions of other objects; and a fourth term which takes into account relevance feedback and pseudo-relevance feedback of negatively labeled image portions of other objects. | 0.600549 |
1. A computer-implemented method comprising: determining, by an automatic speech recognition unit, spoken sound from a first speaker in a first language; creating a plurality of partial hypotheses of the spoken sound of the first speaker; merging, by a resegmentation unit that is in communication with the automatic speech recognition unit, at least two of the partial hypotheses received from the automatic speech recognition unit; receiving an end-of-sentence cue from one or more listeners, the end-of-sentence cue being commonly associated with an end of a sentence; determining a segment boundary for a translatable segment based on the received end-of-sentence cue; resegmenting, by the resegmentation unit, the merged partial hypotheses into the translatable segment in the first language based on the determined segment boundary; and receiving, by a machine translation unit that is in communication with the resegmentation unit, the translatable segment in the first language from the resegmentation unit outputting, by the machine translation unit, a translation of the spoken sound from the first speaker into a second language based on the received translatable segment. | 1. A computer-implemented method comprising: determining, by an automatic speech recognition unit, spoken sound from a first speaker in a first language; creating a plurality of partial hypotheses of the spoken sound of the first speaker; merging, by a resegmentation unit that is in communication with the automatic speech recognition unit, at least two of the partial hypotheses received from the automatic speech recognition unit; receiving an end-of-sentence cue from one or more listeners, the end-of-sentence cue being commonly associated with an end of a sentence; determining a segment boundary for a translatable segment based on the received end-of-sentence cue; resegmenting, by the resegmentation unit, the merged partial hypotheses into the translatable segment in the first language based on the determined segment boundary; and receiving, by a machine translation unit that is in communication with the resegmentation unit, the translatable segment in the first language from the resegmentation unit outputting, by the machine translation unit, a translation of the spoken sound from the first speaker into a second language based on the received translatable segment. 5. The computer-implemented method of claim 1 , wherein the end-of-sentence cue is phraseology. | 0.602318 |
1. A computer implemented method for constructing a strong classifier, comprising a computer processor for performing steps of the method, comprising the steps of: selecting a plurality of weak classifiers; representing an output of each weak classifier by a posterior probability; associating each weak classifier with a confidence matrix; combining the weak classifiers to form a set of combinations of the weak classifiers, in which the combining is an approximate Bayesian combination, and in which an output λ of each weak classifier is a random variable {tilde over (ω)} taking integer values from 1 to K, the number of classes, and a probability distribution over values of a true class label ω is P λ (ω|{tilde over (ω)}), and the approximate Bayesian combination is P a ( ω i | x ) = ∑ k = 1 K w k ∑ j = 1 J P k ( ω i | ω ~ j ) P k ( ω ~ j | x ) ︸ P k ( ω i | x ) , where P k ({tilde over (ω)}|x) is a prediction probability of the weak classifier, and w k is a weight of the classifier; boosting each combination of the weak classifiers to determine a weighted score for each combination of the weak classifiers; and selecting combinations of the weak classifiers having a weighted score greater than a predetermined threshold to form the strong classifier. | 1. A computer implemented method for constructing a strong classifier, comprising a computer processor for performing steps of the method, comprising the steps of: selecting a plurality of weak classifiers; representing an output of each weak classifier by a posterior probability; associating each weak classifier with a confidence matrix; combining the weak classifiers to form a set of combinations of the weak classifiers, in which the combining is an approximate Bayesian combination, and in which an output λ of each weak classifier is a random variable {tilde over (ω)} taking integer values from 1 to K, the number of classes, and a probability distribution over values of a true class label ω is P λ (ω|{tilde over (ω)}), and the approximate Bayesian combination is P a ( ω i | x ) = ∑ k = 1 K w k ∑ j = 1 J P k ( ω i | ω ~ j ) P k ( ω ~ j | x ) ︸ P k ( ω i | x ) , where P k ({tilde over (ω)}|x) is a prediction probability of the weak classifier, and w k is a weight of the classifier; boosting each combination of the weak classifiers to determine a weighted score for each combination of the weak classifiers; and selecting combinations of the weak classifiers having a weighted score greater than a predetermined threshold to form the strong classifier. 5. The method of claim 1 , in which the set of combinations is formed according to P n β ( ω i | x ) = exp ( β ∑ j ∈ S n P j ( ω i | x ) ) ∑ c = 1 C exp [ ( β ∑ k ∈ S n P k ( ω c | x ) ) ] , where P k (ω j |x) is a weighted weak classifier according to a non-linear weight β, and S n is an n th classifier combination. | 0.5 |
1. A tangible computer-readable medium, storing instructions executed by a computer system to implement a method for indexing data, the instructions comprising: instructions for receiving input from a user defining a classification; instructions for receiving input from the user defining an analytic for the classification; instructions for determining a definition of relevance parameters that characterize the classification; instructions for populating a cortex of data in a tangible computer readable database, the cortex of data being populated based on the classification of the data to be indexed; instructions for determining, using a processor based machine learning engine, relevant data from the cortex of data based on the definition of relevance parameters, the relevant data being data which is determined to be relevant to the classification defined by the user; instructions for analyzing the relevant data from the cortex of data based on the relevance parameters to determine attributes in the relevant data; instructions for generating an index of the attributes from the relevant data based on the analyzing of the relevant data; instructions for storing the index in the cortex; and instructions for receiving a query from an analytics tool, the query specifying the classification and an analytics measure, wherein the index is used by the analytics tool to provide results for the query using the analytics measure as applied to the data in the relevant data indexed in the classification. | 1. A tangible computer-readable medium, storing instructions executed by a computer system to implement a method for indexing data, the instructions comprising: instructions for receiving input from a user defining a classification; instructions for receiving input from the user defining an analytic for the classification; instructions for determining a definition of relevance parameters that characterize the classification; instructions for populating a cortex of data in a tangible computer readable database, the cortex of data being populated based on the classification of the data to be indexed; instructions for determining, using a processor based machine learning engine, relevant data from the cortex of data based on the definition of relevance parameters, the relevant data being data which is determined to be relevant to the classification defined by the user; instructions for analyzing the relevant data from the cortex of data based on the relevance parameters to determine attributes in the relevant data; instructions for generating an index of the attributes from the relevant data based on the analyzing of the relevant data; instructions for storing the index in the cortex; and instructions for receiving a query from an analytics tool, the query specifying the classification and an analytics measure, wherein the index is used by the analytics tool to provide results for the query using the analytics measure as applied to the data in the relevant data indexed in the classification. 3. The tangible computer-readable medium of claim 1 , wherein the relevance parameters comprise attributes that are determined to be relevant to defining the classification. | 0.57849 |
13. A method, using an image processor capable of processing data representing image data, for generating a sequence of stylized output images from a sequence of input animation images, the method comprising: receiving an input animation sequence comprising a plurality of time-sequenced frames; receiving a style image package, the style image package comprising data including at least an input style image and an output style image, wherein differences between the input style image and the output style image define a style for drawings and other visual elements; generating an image orientation field for each time-sequenced frame from image data within the respective time-sequenced frame; calculating a velocity field from the time-sequenced frames; generating an output animation sequence comprising output images that has temporal coherence and that takes on the style defined by the style image pair by using the image orientation fields, the style orientation field, and the velocity fields; and outputting the output animation sequence. | 13. A method, using an image processor capable of processing data representing image data, for generating a sequence of stylized output images from a sequence of input animation images, the method comprising: receiving an input animation sequence comprising a plurality of time-sequenced frames; receiving a style image package, the style image package comprising data including at least an input style image and an output style image, wherein differences between the input style image and the output style image define a style for drawings and other visual elements; generating an image orientation field for each time-sequenced frame from image data within the respective time-sequenced frame; calculating a velocity field from the time-sequenced frames; generating an output animation sequence comprising output images that has temporal coherence and that takes on the style defined by the style image pair by using the image orientation fields, the style orientation field, and the velocity fields; and outputting the output animation sequence. 16. The method of claim 13 , further comprising evaluating a goal function to map points of each output image to points of the output style image. | 0.640614 |
1. A method of examining policies for a domain of an enterprise system, the method comprising: in response to user input, representing the policies as a plurality of policy rules for use in a target system of the domain, each of the policy rules including a condition in which one or more expressions are included, each expression referring to one or more policy attributes; for a pair of expressions included in at least one of the conditions: obtaining one or more sets of sample values sufficient to represent all values assumable by the one or more policy attributes referred to in the pair of expressions; combining the sample values in a mixed-radix enumeration in which each attribute is represented in a corresponding position of each sample value combination and of the mixed-radix enumeration; and using the mixed-radix enumeration, evaluating each expression of the pair of expressions relative to each of the sample value combinations to obtain a truth table; based on the truth table, detecting a relationship between the pair of expressions; and based on the detecting, notifying the user as to an anomaly in the rules for the target system; the method performed by one or more computers of the enterprise system. | 1. A method of examining policies for a domain of an enterprise system, the method comprising: in response to user input, representing the policies as a plurality of policy rules for use in a target system of the domain, each of the policy rules including a condition in which one or more expressions are included, each expression referring to one or more policy attributes; for a pair of expressions included in at least one of the conditions: obtaining one or more sets of sample values sufficient to represent all values assumable by the one or more policy attributes referred to in the pair of expressions; combining the sample values in a mixed-radix enumeration in which each attribute is represented in a corresponding position of each sample value combination and of the mixed-radix enumeration; and using the mixed-radix enumeration, evaluating each expression of the pair of expressions relative to each of the sample value combinations to obtain a truth table; based on the truth table, detecting a relationship between the pair of expressions; and based on the detecting, notifying the user as to an anomaly in the rules for the target system; the method performed by one or more computers of the enterprise system. 7. The method of claim 1 , wherein at least one of the sets of sample values includes non-numeric values. | 0.894 |
1. A computer-readable storage medium storing instructions executable to perform an operation to govern information assets managed by an enterprise, the operation comprising: identifying, by an enterprise information asset management application executing on a computing system having at least a processor and a memory, a set of search results responsive to a query requesting a subset of information assets within the enterprise; providing the set of search results; receiving a selection of a first information asset presented in the set of search results; identifying at least a second information asset presented in the set of search results, wherein the first information asset and the second information asset are related to one another by an edge in a semantic graph that represents relationships between the plurality of information assets, wherein the semantic graph associates the plurality of information assets with nodes of the semantic graph, wherein the relationships between nodes in the semantic graph are generated and updated by monitoring user behavior in accessing the plurality of information assets with the set of search results and without requiring user input explicitly specifying to update the relationships, wherein the semantic graph is updated based on a domain ontology; parsing the semantic graph in order to identify at least one information asset selected from: (i) an informal information asset whose relationships satisfy an overuse criterion and (ii) an underused information asset whose relationships satisfy an underuse criterion; and designating the at least one information asset as being overused or underused, whereafter the at least one information asset is formally commissioned or decommissioned. | 1. A computer-readable storage medium storing instructions executable to perform an operation to govern information assets managed by an enterprise, the operation comprising: identifying, by an enterprise information asset management application executing on a computing system having at least a processor and a memory, a set of search results responsive to a query requesting a subset of information assets within the enterprise; providing the set of search results; receiving a selection of a first information asset presented in the set of search results; identifying at least a second information asset presented in the set of search results, wherein the first information asset and the second information asset are related to one another by an edge in a semantic graph that represents relationships between the plurality of information assets, wherein the semantic graph associates the plurality of information assets with nodes of the semantic graph, wherein the relationships between nodes in the semantic graph are generated and updated by monitoring user behavior in accessing the plurality of information assets with the set of search results and without requiring user input explicitly specifying to update the relationships, wherein the semantic graph is updated based on a domain ontology; parsing the semantic graph in order to identify at least one information asset selected from: (i) an informal information asset whose relationships satisfy an overuse criterion and (ii) an underused information asset whose relationships satisfy an underuse criterion; and designating the at least one information asset as being overused or underused, whereafter the at least one information asset is formally commissioned or decommissioned. 3. The computer-readable storage medium of claim 1 , wherein the plurality of information assets include at least one of a database system, a web service, and a server application. | 0.618504 |
1. A method comprising: receiving, by a computing device, a spreadsheet model; receiving, by the computing device, a model template wherein the model template further comprises instructions for spreadsheet evaluation, template management, and web representation; and template management instructions on how to manage evaluations; and deploying, by the computing device, an instance of the model template into a model relationship structure relating one or more model template instances wherein the deploying of an instance of the model template occurs in a model relationship structure selected from a tree, a directed acyclic graph (DAG), and a matrix; wherein the template management instructions includes instructions on how evaluations using the model template interrelate with evaluations from the one or more other model template instances. | 1. A method comprising: receiving, by a computing device, a spreadsheet model; receiving, by the computing device, a model template wherein the model template further comprises instructions for spreadsheet evaluation, template management, and web representation; and template management instructions on how to manage evaluations; and deploying, by the computing device, an instance of the model template into a model relationship structure relating one or more model template instances wherein the deploying of an instance of the model template occurs in a model relationship structure selected from a tree, a directed acyclic graph (DAG), and a matrix; wherein the template management instructions includes instructions on how evaluations using the model template interrelate with evaluations from the one or more other model template instances. 6. The method of claim 1 , further comprising separating, by the computing device, inputs and outputs of the model template. | 0.920886 |
1. A system for assessing information in natural language contents, comprising: a user interface configured to receive an object name as a query term and a value for a customized ranking parameter from a user; a computer storage configured to store an object-specific data set related to the object name, wherein the object-specific data set includes a plurality of property names and association-strength values, each property name being associated with an association-strength value, wherein the association strength values of the plurality of property names are above a predetermined threshold value, wherein the plurality of property names includes a first property name and a second property name, wherein the computer storage configured to store a plurality of documents containing text in a natural language; and a computer processing system in communication with the computer storage and the user interface, the computer processing system being configured to count a first frequency of the first property name in one of the plurality of documents, to count a second frequency of the second property name in the document, to calculate a relevance score as a function of the first frequency and the second frequency, to rank the plurality of documents using their respective relevance scores, and to return one or more documents to the user based on the ranking of the plurality of documents, wherein the function is in part defined by the customized ranking parameter. | 1. A system for assessing information in natural language contents, comprising: a user interface configured to receive an object name as a query term and a value for a customized ranking parameter from a user; a computer storage configured to store an object-specific data set related to the object name, wherein the object-specific data set includes a plurality of property names and association-strength values, each property name being associated with an association-strength value, wherein the association strength values of the plurality of property names are above a predetermined threshold value, wherein the plurality of property names includes a first property name and a second property name, wherein the computer storage configured to store a plurality of documents containing text in a natural language; and a computer processing system in communication with the computer storage and the user interface, the computer processing system being configured to count a first frequency of the first property name in one of the plurality of documents, to count a second frequency of the second property name in the document, to calculate a relevance score as a function of the first frequency and the second frequency, to rank the plurality of documents using their respective relevance scores, and to return one or more documents to the user based on the ranking of the plurality of documents, wherein the function is in part defined by the customized ranking parameter. 4. The system of claim 1 , wherein the function depends on the sum of a first multiplication of the first frequency and its corresponding association-strength value and a second multiplication of the second frequency and its corresponding association-strength value. | 0.643961 |
12. The method of claim 11 wherein the step of adjusting the belief network includes adding an arc that introduces a cycle into the belief network to create a cyclic directed graph. | 12. The method of claim 11 wherein the step of adjusting the belief network includes adding an arc that introduces a cycle into the belief network to create a cyclic directed graph. 13. The method of claim 12, further including the step of performing probabilistic inference using the cyclic directed graph. | 0.978029 |
12. A method for rendering virtual reality (VR) views into VR scenes for presentation to a head mounted display (HMD), comprising, sensing one or more geometric surfaces of a nose of the user by one or more proximity sensors disposed in or around a nose insert region of a display housing of the HMD; generating a model of the nose of the user using the sensed one more geometric surfaces; detecting eye gaze of the user using one or more eye gaze sensors disposed in the display housing of the HMD; and rendering images to a screen of the HMD to present the VR scenes, the images being augmented to include nose image data from the model of the nose; wherein the augmenting of the images is adjusted to include more of the nose image data when it is determined that the eye gaze is directed down and toward the nose of the user. | 12. A method for rendering virtual reality (VR) views into VR scenes for presentation to a head mounted display (HMD), comprising, sensing one or more geometric surfaces of a nose of the user by one or more proximity sensors disposed in or around a nose insert region of a display housing of the HMD; generating a model of the nose of the user using the sensed one more geometric surfaces; detecting eye gaze of the user using one or more eye gaze sensors disposed in the display housing of the HMD; and rendering images to a screen of the HMD to present the VR scenes, the images being augmented to include nose image data from the model of the nose; wherein the augmenting of the images is adjusted to include more of the nose image data when it is determined that the eye gaze is directed down and toward the nose of the user. 13. The method of claim 12 , wherein the screen of the HMD is defined by a left screen for a left eye of the user and a right screen for a right eye of the user, the nose image data being rendered near a bottom right region of the left screen and a bottom left region of the right screen, the left and right screens being disposed in the display housing having a left optic in front of the left screen and a right optic in front of the right screen. | 0.544395 |
1. A computer implemented method of enabling an ontology system to provide enhanced search capability, wherein said ontology system maintains information in the form of a plurality of ontologies, wherein each of said plurality of ontologies contains a corresponding plurality of nodes and a corresponding plurality of edges, some of said plurality of edges being of a corresponding one of a plurality of relationship types between a corresponding pair of said plurality of nodes, wherein the relationship type of an edge identifies the specific relation represented by the edge, said method comprising: receiving a search request specifying a set of nodes and a set of edges of interest, said search request further specifying a corresponding one of a set of relationship types for each of said set of edges of interest, wherein said received search request contains express data which explicitly identifies each of said set of nodes, said set of edges of interest and said set of relationship types, wherein said set of relationship types is contained in said plurality of relationship types; determining a set of ontologies matching said search request based on said set of nodes and said set of edges of interest, wherein said set of ontologies is contained in said plurality of ontologies, wherein said set of ontologies contains a first ontology and a second ontology, said first ontology and said second ontology respectively containing a first edge and a second edge, wherein both of said first edge and said second edge are between a same pair of nodes of said first ontology and said second ontology, wherein both of said same pair of nodes are contained in said set of nodes received in said search request, wherein said first edge in said first ontology is of a first relationship type matching the corresponding relationship type explicitly identified for a first edge of interest in said search request, wherein said first edge of interest is also between said same pair of nodes in said search request, wherein said second edge in said second ontology is not of said first relationship type; computing a match score for each of said set of ontologies, wherein a first match score and a second match score are respectively computed for said first ontology and said second ontology, wherein said first edge contributes more to said first match score than said second edge contributes to said second match score in view of said first edge being of said first relationship type in said first ontology, and said second edge not being of said first relationship type in said second ontology, ranking said set of ontologies according to the computed match scores; and sending a data indicating said set of ontologies and corresponding ranks as a result of said search request. | 1. A computer implemented method of enabling an ontology system to provide enhanced search capability, wherein said ontology system maintains information in the form of a plurality of ontologies, wherein each of said plurality of ontologies contains a corresponding plurality of nodes and a corresponding plurality of edges, some of said plurality of edges being of a corresponding one of a plurality of relationship types between a corresponding pair of said plurality of nodes, wherein the relationship type of an edge identifies the specific relation represented by the edge, said method comprising: receiving a search request specifying a set of nodes and a set of edges of interest, said search request further specifying a corresponding one of a set of relationship types for each of said set of edges of interest, wherein said received search request contains express data which explicitly identifies each of said set of nodes, said set of edges of interest and said set of relationship types, wherein said set of relationship types is contained in said plurality of relationship types; determining a set of ontologies matching said search request based on said set of nodes and said set of edges of interest, wherein said set of ontologies is contained in said plurality of ontologies, wherein said set of ontologies contains a first ontology and a second ontology, said first ontology and said second ontology respectively containing a first edge and a second edge, wherein both of said first edge and said second edge are between a same pair of nodes of said first ontology and said second ontology, wherein both of said same pair of nodes are contained in said set of nodes received in said search request, wherein said first edge in said first ontology is of a first relationship type matching the corresponding relationship type explicitly identified for a first edge of interest in said search request, wherein said first edge of interest is also between said same pair of nodes in said search request, wherein said second edge in said second ontology is not of said first relationship type; computing a match score for each of said set of ontologies, wherein a first match score and a second match score are respectively computed for said first ontology and said second ontology, wherein said first edge contributes more to said first match score than said second edge contributes to said second match score in view of said first edge being of said first relationship type in said first ontology, and said second edge not being of said first relationship type in said second ontology, ranking said set of ontologies according to the computed match scores; and sending a data indicating said set of ontologies and corresponding ranks as a result of said search request. 2. The method of claim 1 , wherein a node in said plurality of nodes represents a concept or an instance or a property or a event in said plurality of ontologies, and an edge in said plurality of edges indicates a relation or link existing between two nodes. | 0.587122 |
1. A method of query optimization, comprising: comparing a complexity measure of a client query received from a client application to a predetermined threshold, the client query received before the client query reaches a server application on a server, wherein the predetermined threshold is determined based on query execution data collected from at least one previous query; generating an optimized query by modifying the client query to reduce the complexity measure of the client query if the complexity measure of the client query exceeds the predetermined threshold, wherein an expected result set size of the optimized query is greater than an expected result set size of the client query; submitting the optimized query to the server application on the server; selecting a post-processing routine to be applied to a result set of the optimized query to have a filtered result set; and returning the filtered set to the client application. | 1. A method of query optimization, comprising: comparing a complexity measure of a client query received from a client application to a predetermined threshold, the client query received before the client query reaches a server application on a server, wherein the predetermined threshold is determined based on query execution data collected from at least one previous query; generating an optimized query by modifying the client query to reduce the complexity measure of the client query if the complexity measure of the client query exceeds the predetermined threshold, wherein an expected result set size of the optimized query is greater than an expected result set size of the client query; submitting the optimized query to the server application on the server; selecting a post-processing routine to be applied to a result set of the optimized query to have a filtered result set; and returning the filtered set to the client application. 3. The method of claim 1 , wherein the predetermined threshold is determined further based on system data comprising at least one of: static system data including at least one of server performance characteristics, server capacity characteristics, a server content distribution, a predetermined maximum client load, a predetermined maximum server load, and predetermined maximum network load; and dynamic system data including at least one of a measure of the server load at the time a query is submitted, a measure of the client load at the time the query is submitted, and a measure of the network load at the time the query is submitted. | 0.709165 |
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