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1. A computer-implemented method for identifying automated-agents, comprising: providing, in connection with navigation of a website by an entity, a collection of security checks to the entity, the collection of security checks including a challenge-response problem based at least in part on evolutionary psychology, cognitive psychology, psycholinguistics, or color psychology; receiving a collection of responses comprising at least a first response to a first security check of the collection of security checks and a second response to a second security check of the collection of security checks; calculating, based at least in part on the collection of responses, an aggregate performance score for the entity; determining a reference performance score for the collection of security checks; determining, based at least in part on the aggregate performance score and the reference performance score, information indicative of whether the entity is an automated-agent or a human-user, wherein the information indicates that the entity is human by including one or more incorrect responses of the collection of responses and indicates that the entity is automated by including one or more correct responses of the collection of responses; and performing one or more operations as a result of the information. | 1. A computer-implemented method for identifying automated-agents, comprising: providing, in connection with navigation of a website by an entity, a collection of security checks to the entity, the collection of security checks including a challenge-response problem based at least in part on evolutionary psychology, cognitive psychology, psycholinguistics, or color psychology; receiving a collection of responses comprising at least a first response to a first security check of the collection of security checks and a second response to a second security check of the collection of security checks; calculating, based at least in part on the collection of responses, an aggregate performance score for the entity; determining a reference performance score for the collection of security checks; determining, based at least in part on the aggregate performance score and the reference performance score, information indicative of whether the entity is an automated-agent or a human-user, wherein the information indicates that the entity is human by including one or more incorrect responses of the collection of responses and indicates that the entity is automated by including one or more correct responses of the collection of responses; and performing one or more operations as a result of the information. 2. The computer-implemented method of claim 1 , wherein providing the collection of security checks to the entity includes providing one or more security checks over multiple requests for webpages of the website. | 0.615453 |
1. A method comprising: receiving one or more documents that contain a first flow diagram in one or more diagram formats supported by the documents; automatically extracting from the first flow diagram one or more flow graphs comprising extracted nodes and edges; automatically extracting from the first flow diagram relational, geometric and textual features for the extracted nodes and edges; automatically learning rules to recognize process semantics based on the extracted nodes and edges, and the relational, geometric and textual features of the extracted nodes and edges, the rules configured as a decision tree; and automatically generating, based on the learned rules, process modeling recognition code to recognize and decide process semantics in a second flow diagram. | 1. A method comprising: receiving one or more documents that contain a first flow diagram in one or more diagram formats supported by the documents; automatically extracting from the first flow diagram one or more flow graphs comprising extracted nodes and edges; automatically extracting from the first flow diagram relational, geometric and textual features for the extracted nodes and edges; automatically learning rules to recognize process semantics based on the extracted nodes and edges, and the relational, geometric and textual features of the extracted nodes and edges, the rules configured as a decision tree; and automatically generating, based on the learned rules, process modeling recognition code to recognize and decide process semantics in a second flow diagram. 25. The method of claim 1 , wherein automatically generating the process modeling recognition code based on the learned rules includes forming learned rules based on a number of incoming and outgoing edges, and a number of vertical and horizontal lines of the extracted nodes and edges. | 0.645764 |
1. A method to perform relation extraction in text, comprising: applying a convolution strategy to determine a kernel between sentences; deriving an unweighted undirected graph G D (S) for a sentence S from a set of dependency relations supplemented by a linear-order structure, where the set is denoted by D(S) and V(S) is the set of vertices, with each v i εV(S) representing a certain word
G D ( S )=( V ( S ), E ( S )); determining a single path p from a dependency graph G D (S) composed from a sequence of words and their associated dependencies
p =( w i ,d i,j ,w j , . . . ,w p ,d p,q ,w q ) where word w i and w j are connected by the dependency edge d i,j ; determining a convolution kernel K G as a sum of kernels on paths (K p ): K G ( G D ( S ) , G D ( S ′ ) ) = ∑ p ∈ P n ( G D ( S ) ) ∑ p ′ ∈ P ″ ( G D ( S ′ ) ) K p ( p , p ′ ) Pr ( p G D ( S ) ) Pr ( p ′ G D ( S ′ ) ) where Pr(p|G D (S)) is a probability that single path p happens in the graph G D (S) and calculated as a ratio of path count over sum of path counts; applying one or more semi-supervised strategies to the kernel to encode syntactic and semantic information to recover a relational pattern of interest; and applying a classifier to the kernel to identify the relational pattern of interest in the text in response to a query. | 1. A method to perform relation extraction in text, comprising: applying a convolution strategy to determine a kernel between sentences; deriving an unweighted undirected graph G D (S) for a sentence S from a set of dependency relations supplemented by a linear-order structure, where the set is denoted by D(S) and V(S) is the set of vertices, with each v i εV(S) representing a certain word
G D ( S )=( V ( S ), E ( S )); determining a single path p from a dependency graph G D (S) composed from a sequence of words and their associated dependencies
p =( w i ,d i,j ,w j , . . . ,w p ,d p,q ,w q ) where word w i and w j are connected by the dependency edge d i,j ; determining a convolution kernel K G as a sum of kernels on paths (K p ): K G ( G D ( S ) , G D ( S ′ ) ) = ∑ p ∈ P n ( G D ( S ) ) ∑ p ′ ∈ P ″ ( G D ( S ′ ) ) K p ( p , p ′ ) Pr ( p G D ( S ) ) Pr ( p ′ G D ( S ′ ) ) where Pr(p|G D (S)) is a probability that single path p happens in the graph G D (S) and calculated as a ratio of path count over sum of path counts; applying one or more semi-supervised strategies to the kernel to encode syntactic and semantic information to recover a relational pattern of interest; and applying a classifier to the kernel to identify the relational pattern of interest in the text in response to a query. 5. The method of claim 1 , wherein one of the semi-supervised strategies is added on a graph kernel or a string kernel to consider semantics of natural English words using word embedding representations. | 0.536524 |
1. An apparatus for synthesizing speech from text, comprising: a language processing section determining an accent environment of each mora of each phrase of the text, said accent environment including a height of an accent of each mora; a basic accent pattern table in which a basic accent pattern has been classified according to an accent environment of the mora, the basic accent pattern including pitch data which has been edited from real voice data according to the accent environment; a basic accent pattern processing section selecting the basic accent pattern of each mora from said basic accent pattern table according to the accent environment and processing the basic accent pattern in a pitch according to the accent environment; a correcting section receiving the basic access pattern in the pitch in said basic accent pattern processing section and correcting the pitch according to the number of moras in each phrase and the position of the moras in the phrase so as to correct the data in the corrected accent component; a phrase pattern processing section determining a phrase component according to the number of moras in each phrase of the accent environment; and a speech synthesizing section synthesizing speech according to an accent control pattern of the text which is obtained by adding the basic accent pattern and the basic phrase pattern. | 1. An apparatus for synthesizing speech from text, comprising: a language processing section determining an accent environment of each mora of each phrase of the text, said accent environment including a height of an accent of each mora; a basic accent pattern table in which a basic accent pattern has been classified according to an accent environment of the mora, the basic accent pattern including pitch data which has been edited from real voice data according to the accent environment; a basic accent pattern processing section selecting the basic accent pattern of each mora from said basic accent pattern table according to the accent environment and processing the basic accent pattern in a pitch according to the accent environment; a correcting section receiving the basic access pattern in the pitch in said basic accent pattern processing section and correcting the pitch according to the number of moras in each phrase and the position of the moras in the phrase so as to correct the data in the corrected accent component; a phrase pattern processing section determining a phrase component according to the number of moras in each phrase of the accent environment; and a speech synthesizing section synthesizing speech according to an accent control pattern of the text which is obtained by adding the basic accent pattern and the basic phrase pattern. 5. An apparatus for synthesizing speech from text as claimed in claim 1, wherein said basic accent pattern table is classified in accordance with the accent environment of each mora and the type of each mora. | 0.501091 |
1. A system to detect garbled closed captioning data, comprising: a receiver to receive an encoded video data stream containing closed captioning data; a decoder to decode the encoded video data stream, and to reorder frames in the encoded video stream into display order; a closed captioning data detector to detect closed captioning data in the decoded, reordered video data stream; a data extractor to extract individual data elements from the detected closed captioning data; a data counter to count a total number of data elements in the closed captioning data as a total data element count, and to count a total number of data elements in the closed captioning data having a particular characteristic as a total data element characteristic count; a memory in which to store the total data element count and the data element characteristic count in the memory; a garbled closed captioning data detector to determine a metric as a function of the total data element count and the total data element characteristic count; and an alert generator that generates an alert in accordance with the determined metric. | 1. A system to detect garbled closed captioning data, comprising: a receiver to receive an encoded video data stream containing closed captioning data; a decoder to decode the encoded video data stream, and to reorder frames in the encoded video stream into display order; a closed captioning data detector to detect closed captioning data in the decoded, reordered video data stream; a data extractor to extract individual data elements from the detected closed captioning data; a data counter to count a total number of data elements in the closed captioning data as a total data element count, and to count a total number of data elements in the closed captioning data having a particular characteristic as a total data element characteristic count; a memory in which to store the total data element count and the data element characteristic count in the memory; a garbled closed captioning data detector to determine a metric as a function of the total data element count and the total data element characteristic count; and an alert generator that generates an alert in accordance with the determined metric. 5. The system recited in claim 1 , wherein the data counter uses a data delimiter to identify unique data elements within the closed captioning data for determining total data element count and total data element characteristic count. | 0.613787 |
14. A computer-implemented method for graphically representing one or more referents associated with a plurality of stories, the computer-implemented method comprising: as implemented by one or more computing devices configured with specific executable instructions, determining, for each of the plurality of stories, a score for the story based at least in part on a number of times that one or more referents of interest are referenced in at least a portion of content of the story; and generating for display a graphical representation of a subset of the plurality of stories, the graphical representation comprising a plurality of indicia, wherein each indicium of the plurality of indicia is associated with a different story of the subset of the plurality of stories, wherein the indicium for each story of the subset graphically indicates a strength of association between the story and the one or more referents of interest, and wherein the strength of association is determined based at least in part on the score for the story. | 14. A computer-implemented method for graphically representing one or more referents associated with a plurality of stories, the computer-implemented method comprising: as implemented by one or more computing devices configured with specific executable instructions, determining, for each of the plurality of stories, a score for the story based at least in part on a number of times that one or more referents of interest are referenced in at least a portion of content of the story; and generating for display a graphical representation of a subset of the plurality of stories, the graphical representation comprising a plurality of indicia, wherein each indicium of the plurality of indicia is associated with a different story of the subset of the plurality of stories, wherein the indicium for each story of the subset graphically indicates a strength of association between the story and the one or more referents of interest, and wherein the strength of association is determined based at least in part on the score for the story. 15. The computer-implemented method of claim 14 , wherein each indicium comprises a color. | 0.791224 |
1. A computer network implementable method for synthesizing relevant messaging from one or more domains of information, underpinned by non-promoted content, using a consumer-generated context, the method comprising: obtaining non-promoted content and linking the non-promoted content to at least one promoter; receiving advertising material from the at least one promoter; receiving a consumer-generated context; and semantically analyzing and synthesizing, or facilitating the semantic analysis and synthesis of, by one or more computer processors, relevant messaging based on the non-promoted content and the consumer-generated context, wherein the relevant messaging is traceable to the at least one promoter, the synthesizing comprising: deconstructing the advertising material received from the at least one promoter into a plurality of messaging leads; and selecting at least some of the plurality of messaging leads and assembling the selected messaging leads into a message based on the consumer-generated context, the message having relevant non-promoted content interspersed between the selected messaging leads from the received advertising material. | 1. A computer network implementable method for synthesizing relevant messaging from one or more domains of information, underpinned by non-promoted content, using a consumer-generated context, the method comprising: obtaining non-promoted content and linking the non-promoted content to at least one promoter; receiving advertising material from the at least one promoter; receiving a consumer-generated context; and semantically analyzing and synthesizing, or facilitating the semantic analysis and synthesis of, by one or more computer processors, relevant messaging based on the non-promoted content and the consumer-generated context, wherein the relevant messaging is traceable to the at least one promoter, the synthesizing comprising: deconstructing the advertising material received from the at least one promoter into a plurality of messaging leads; and selecting at least some of the plurality of messaging leads and assembling the selected messaging leads into a message based on the consumer-generated context, the message having relevant non-promoted content interspersed between the selected messaging leads from the received advertising material. 3. The method of claim 1 , wherein the non-promoted content is selected from the one or more domains based on the consumer-generated context. | 0.656712 |
4. A document processing method for importing a first specified document file into a second document file to be edited, comprising: a determination step of determining whether or not security information is added to the first document file; an import control step of importing the first document file with the security information into the second document file in order to generate a third document file, if the determination step determines that the security information is added to the first document file; a receiving step of receiving an instruction for editing the third document file in a unit of a page included in the third document file; an edition control step of, if edit prohibition security information is added to the first document file, permitting editing of the third document file by movement of all pages which are imported from the first document file into the third document file, and prohibiting editing the third document file by editing of each page among the pages imported from the first document file; an adding step of adding additional information to a page based on the first document file; a control step of causing printing based on the additional information added by the adding step; and an export control step of exporting the first document file including the security information from the third document file, wherein the export control step exports the first document file excluding the additional information, wherein the edition control relocates pages of the third document without changing the location of pages in the first document file. | 4. A document processing method for importing a first specified document file into a second document file to be edited, comprising: a determination step of determining whether or not security information is added to the first document file; an import control step of importing the first document file with the security information into the second document file in order to generate a third document file, if the determination step determines that the security information is added to the first document file; a receiving step of receiving an instruction for editing the third document file in a unit of a page included in the third document file; an edition control step of, if edit prohibition security information is added to the first document file, permitting editing of the third document file by movement of all pages which are imported from the first document file into the third document file, and prohibiting editing the third document file by editing of each page among the pages imported from the first document file; an adding step of adding additional information to a page based on the first document file; a control step of causing printing based on the additional information added by the adding step; and an export control step of exporting the first document file including the security information from the third document file, wherein the export control step exports the first document file excluding the additional information, wherein the edition control relocates pages of the third document without changing the location of pages in the first document file. 6. The document processing method according to claim 4 , wherein if a document file to which the determination step determines the security information is not added is imported into the second document file, the edition control step changes the order of any of the pages in the third document file. | 0.529346 |
1. A computer-implemented method comprising: (a) generating, using a data federation computer system, electronic configuration triple data structures for each of a plurality of data sources by performing the following steps for each of the plurality of data sources: i. identifying, using a data federation computer system, the respective data source; ii. identifying, using the data federation computer system, respective access data used to access the respective data source; iii. converting, by the data federation computer system, the respective access data to corresponding electronic configuration triple data structures based at least in part upon a common configuration ontology; and iv. storing in non-transitory computer-readable memory comprising at least one triplestore database, by the data federation computer system, the electronic configuration triple data structures; (b) generating, using the data federation computer system, a generated metadata ontology for each of the plurality of data sources by performing the following steps for each of the plurality of data sources: i. accessing, by the data federation computer system, the respective data source using the respective access data identified by the respective electronic configuration triple data structures; ii. extracting, by the data federation computer system, respective metadata from the respective data source, wherein the respective metadata identifies respective data specified in respective data structures; iii. converting, by the data federation computer system, the extracted respective metadata to corresponding respective electronic metadata triple data structures based at least in part upon a common metadata ontology; and iv. storing in the non-transitory computer-readable memory, by the data federation computer system, the respective electronic metadata triple data structures to form a respective generated metadata ontology for each respective data source; (c) generating, using the data federation computer system, a domain ontology corresponding to a first target data environment, wherein the first target data environment comprises a respective lexicon for specifying queries of the plurality of data sources; (d) storing, using the data federation computer system, the domain ontology; (e) for each of the plurality of data sources, generating, using the data federation computer system, a bridge ontology comprising an electronic mapping between the generated metadata ontology for the respective data source and the domain ontology; (f) determining, by the data federation computer system, a subset of the plurality of data sources that cannot be queried in place; (g) generating, by the data federation computer system, a re-hosted data ontology for each of the subset of the plurality of data sources by performing the following steps for each of the subset of the plurality of data sources: i. extracting, by the data federation computer system, respective data from the respective data source; ii. converting, by the data federation computer system, the respective extracted data to corresponding electronic data triple data structures based upon the respective bridge ontology; and iii. storing in the non-transitory computer-readable memory, by the data federation computer system, the electronic data triple data structures to form a re-hosted data ontology; and (h) correlating, by the data federation computer system, a query expressed in the domain ontology to the data from the plurality of data sources using the re-hosted data ontologies for each of the subset of the plurality of data sources and using the bridge ontologies for the remaining data sources. | 1. A computer-implemented method comprising: (a) generating, using a data federation computer system, electronic configuration triple data structures for each of a plurality of data sources by performing the following steps for each of the plurality of data sources: i. identifying, using a data federation computer system, the respective data source; ii. identifying, using the data federation computer system, respective access data used to access the respective data source; iii. converting, by the data federation computer system, the respective access data to corresponding electronic configuration triple data structures based at least in part upon a common configuration ontology; and iv. storing in non-transitory computer-readable memory comprising at least one triplestore database, by the data federation computer system, the electronic configuration triple data structures; (b) generating, using the data federation computer system, a generated metadata ontology for each of the plurality of data sources by performing the following steps for each of the plurality of data sources: i. accessing, by the data federation computer system, the respective data source using the respective access data identified by the respective electronic configuration triple data structures; ii. extracting, by the data federation computer system, respective metadata from the respective data source, wherein the respective metadata identifies respective data specified in respective data structures; iii. converting, by the data federation computer system, the extracted respective metadata to corresponding respective electronic metadata triple data structures based at least in part upon a common metadata ontology; and iv. storing in the non-transitory computer-readable memory, by the data federation computer system, the respective electronic metadata triple data structures to form a respective generated metadata ontology for each respective data source; (c) generating, using the data federation computer system, a domain ontology corresponding to a first target data environment, wherein the first target data environment comprises a respective lexicon for specifying queries of the plurality of data sources; (d) storing, using the data federation computer system, the domain ontology; (e) for each of the plurality of data sources, generating, using the data federation computer system, a bridge ontology comprising an electronic mapping between the generated metadata ontology for the respective data source and the domain ontology; (f) determining, by the data federation computer system, a subset of the plurality of data sources that cannot be queried in place; (g) generating, by the data federation computer system, a re-hosted data ontology for each of the subset of the plurality of data sources by performing the following steps for each of the subset of the plurality of data sources: i. extracting, by the data federation computer system, respective data from the respective data source; ii. converting, by the data federation computer system, the respective extracted data to corresponding electronic data triple data structures based upon the respective bridge ontology; and iii. storing in the non-transitory computer-readable memory, by the data federation computer system, the electronic data triple data structures to form a re-hosted data ontology; and (h) correlating, by the data federation computer system, a query expressed in the domain ontology to the data from the plurality of data sources using the re-hosted data ontologies for each of the subset of the plurality of data sources and using the bridge ontologies for the remaining data sources. 17. The computer-implemented method of claim 1 , further comprising the steps of: (i) generating, using the data federation computer system, a second bridge ontology comprising an electronic mapping between the domain ontology and a first sub-domain ontology wherein the first sub-domain ontology corresponds to a respective lexicon for specifying queries of the plurality of data sources. | 0.502519 |
1. A computer-implemented method for ranking web pages in a result set, comprising: under control of one or more computer systems configured with executable instructions, establishing, in response to receiving a query containing one or more query terms, a plurality of rating scores, a first subset of the plurality of rating scores reflecting a first determined level of relevance of one of a plurality of web pages generated in response to the query to one of a plurality of query terms, a second subset of the plurality of rating scores reflecting a second determined level of relevance of the one of the plurality of web pages generated in response to the query to one of a plurality of terms not included in the query terms and associated with the one of the plurality of web pages; observing interaction of a plurality of users with a selected web page of the plurality of web pages during a rating period to detect any of a type of content interaction, each of the type of content interaction being performed with respect to the selected web page, the type of content interaction comprising printing the content and copying the content; in response to detecting any of the type of content interaction performed by any of the plurality of users, adjusting at least one of the established first subset of the plurality of rating scores for at least one combination of the selected web page and a query term among the one or more query terms, the rating score being adjusted by an amount based at least in part upon the detected content interaction, the adjustment to the rating score being configured to be positive based at least in part on the detected content interaction, each adjustment to the rating score corresponding to an inferred relevance of the web page to one of the query terms; and adjusting at least one of the established second subset of the plurality of rating scores for at least one combination of the selected web page and one of the plurality of terms not included in the query terms and associated with the one of the plurality of web pages, the rating score being adjusted by an amount based at least in part upon the detected content interaction, the adjustment to the rating score being configured to be positive based at least in part on the detected content interaction, each adjustment to the rating score corresponding to an inferred relevance of the selected web page to the one of the plurality of terms; and for each of a plurality of web pages included generated in response to the query: selecting established and adjusted rating scores for each combination of the web page and a query term and for each combination of the web page and a term not included in the query terms, and determining a ranking score for the web page by combining the selected rating scores. | 1. A computer-implemented method for ranking web pages in a result set, comprising: under control of one or more computer systems configured with executable instructions, establishing, in response to receiving a query containing one or more query terms, a plurality of rating scores, a first subset of the plurality of rating scores reflecting a first determined level of relevance of one of a plurality of web pages generated in response to the query to one of a plurality of query terms, a second subset of the plurality of rating scores reflecting a second determined level of relevance of the one of the plurality of web pages generated in response to the query to one of a plurality of terms not included in the query terms and associated with the one of the plurality of web pages; observing interaction of a plurality of users with a selected web page of the plurality of web pages during a rating period to detect any of a type of content interaction, each of the type of content interaction being performed with respect to the selected web page, the type of content interaction comprising printing the content and copying the content; in response to detecting any of the type of content interaction performed by any of the plurality of users, adjusting at least one of the established first subset of the plurality of rating scores for at least one combination of the selected web page and a query term among the one or more query terms, the rating score being adjusted by an amount based at least in part upon the detected content interaction, the adjustment to the rating score being configured to be positive based at least in part on the detected content interaction, each adjustment to the rating score corresponding to an inferred relevance of the web page to one of the query terms; and adjusting at least one of the established second subset of the plurality of rating scores for at least one combination of the selected web page and one of the plurality of terms not included in the query terms and associated with the one of the plurality of web pages, the rating score being adjusted by an amount based at least in part upon the detected content interaction, the adjustment to the rating score being configured to be positive based at least in part on the detected content interaction, each adjustment to the rating score corresponding to an inferred relevance of the selected web page to the one of the plurality of terms; and for each of a plurality of web pages included generated in response to the query: selecting established and adjusted rating scores for each combination of the web page and a query term and for each combination of the web page and a term not included in the query terms, and determining a ranking score for the web page by combining the selected rating scores. 10. The computer-implemented method of claim 1 wherein at least one rating score for a distinguished web page is adjusted in a positive direction in response to a content interaction in which a user searches within the distinguished web page. | 0.873173 |
2. A machine process for identifying a human language used in a computer coded document from text in the document as defined in claim 1, further comprising the steps of finding the largest FO value of all words in each WFT, normalizing the FO value for each WFT by dividing each FO value by the largest FO value found in the WFT to generate a normalized frequency of occurrence (NFO) for the word, and replacing each FO value with the NFO value determined by the normalizing step. | 2. A machine process for identifying a human language used in a computer coded document from text in the document as defined in claim 1, further comprising the steps of finding the largest FO value of all words in each WFT, normalizing the FO value for each WFT by dividing each FO value by the largest FO value found in the WFT to generate a normalized frequency of occurrence (NFO) for the word, and replacing each FO value with the NFO value determined by the normalizing step. 5. A machine process for identifying a human language used in a computer coded document from text in the document as defined in claim 2, further comprising the steps of generating a word frequency table (WFT) by reading a plurality of sampled documents known to be in a language of interest for which the WFT is to be generated, counting number of occurrances for each word read in the sampled documents by the generating step to establish a FO value associated with each word in the WFT, and retaining in the WFT language the words having associated FO values exceeding a threshold, and the WFTs each having approximately the same total value for all FOs in each WFT. | 0.742928 |
9. A speech recognition system comprising: a memory configured to store: a corpus including a plurality of complex proper names; and a model for a speech recognizer; and a processor operatively connected to the memory, the processor being configured to: perform natural language processing to generate syntactic structure corresponding to a plurality of words in one of the plurality of complex proper names in the corpus; generate a plurality of candidate partial names corresponding to the one complex proper name using a machine learning process with reference to the syntactic structure corresponding to the one complex proper name and the plurality of words in the one complex proper name, wherein the one complex proper name is divided into categories of syntactic units and each of the plurality of candidate partial names comprises a subset of words from the plurality of words contained within the one complex proper name and the subset of words classified into a specific syntactic category; select only a portion of the plurality of candidate partial names based on at least one syntactic structural identifier of at least one phrase in each candidate partial name to provide a modified list of candidate partial names; incorporate the modified list of candidate partial names based on the phonetic transcription into the model for the speech recognizer to recognize partial names in a speech recognition process; store the model for the speech recognizer in the memory; receive speech input from a user comprising a candidate partial name from the modified candidate partial names; perform speech recognition, using the model, on the received speech; and identify the one complex proper name based on the recognized speech and performing an action on a user device based on the identified one complex proper name. | 9. A speech recognition system comprising: a memory configured to store: a corpus including a plurality of complex proper names; and a model for a speech recognizer; and a processor operatively connected to the memory, the processor being configured to: perform natural language processing to generate syntactic structure corresponding to a plurality of words in one of the plurality of complex proper names in the corpus; generate a plurality of candidate partial names corresponding to the one complex proper name using a machine learning process with reference to the syntactic structure corresponding to the one complex proper name and the plurality of words in the one complex proper name, wherein the one complex proper name is divided into categories of syntactic units and each of the plurality of candidate partial names comprises a subset of words from the plurality of words contained within the one complex proper name and the subset of words classified into a specific syntactic category; select only a portion of the plurality of candidate partial names based on at least one syntactic structural identifier of at least one phrase in each candidate partial name to provide a modified list of candidate partial names; incorporate the modified list of candidate partial names based on the phonetic transcription into the model for the speech recognizer to recognize partial names in a speech recognition process; store the model for the speech recognizer in the memory; receive speech input from a user comprising a candidate partial name from the modified candidate partial names; perform speech recognition, using the model, on the received speech; and identify the one complex proper name based on the recognized speech and performing an action on a user device based on the identified one complex proper name. 16. The system of claim 9 , the processor being further configured to: generate the plurality of partial proper name candidates using a neural network. | 0.815085 |
18. The method of claim 17 , wherein the infrastructure is an electrical grid. | 18. The method of claim 17 , wherein the infrastructure is an electrical grid. 19. The method of claim 18 , wherein the predicted effectiveness of the improvement to the infrastructure is obtained based at least in part from machine learning. | 0.965872 |
1. A method of developing and deploying a network application in a distributed computing system including at least a server and at least a client machine, wherein said client machine is adapted to connect to said server via a network, said method comprising: developing a server-side application comprising at least one markup document and at least one business logic component, wherein said markup document is written using any declarative Extensible Markup Language (XML) and said business logic component is written using any programming language; compiling said business logic component into a specific executable code using a compiler, wherein said compiler is adapted to receive a business logic component written in any programming language and to compile said business logic component into a specific executable code that can be executed by a specific execution engine in said client machine; converting said markup document into a specific markup language document using a markup language converter, wherein said markup language converter is adapted to receive a markup document written in any XML language and to convert said markup document into a specific markup language document that is compatible with a specific client runtime environment (CRE) of said client machine; and deploying said specific markup document and said specific executable code to said client machine via said network. | 1. A method of developing and deploying a network application in a distributed computing system including at least a server and at least a client machine, wherein said client machine is adapted to connect to said server via a network, said method comprising: developing a server-side application comprising at least one markup document and at least one business logic component, wherein said markup document is written using any declarative Extensible Markup Language (XML) and said business logic component is written using any programming language; compiling said business logic component into a specific executable code using a compiler, wherein said compiler is adapted to receive a business logic component written in any programming language and to compile said business logic component into a specific executable code that can be executed by a specific execution engine in said client machine; converting said markup document into a specific markup language document using a markup language converter, wherein said markup language converter is adapted to receive a markup document written in any XML language and to convert said markup document into a specific markup language document that is compatible with a specific client runtime environment (CRE) of said client machine; and deploying said specific markup document and said specific executable code to said client machine via said network. 16. The method of claim 1 wherein said network is selected from a group consisting of the World Wide Web (www), the Internet, a wide area network (WAN), a local area network (LAN), a personal area network (PAN), a telecommunication network, a virtual private network (VPN) and a wireless network. | 0.516933 |
24. The engine of claim 1 , wherein the environment comprises a global environment. | 24. The engine of claim 1 , wherein the environment comprises a global environment. 25. The engine of claim 24 , wherein the first and the second aspects are associated with different local environments. | 0.957163 |
1. A method comprising: receiving a term of a search request; identifying the term as a meta-keyword, the meta-keyword having a relationship with one or more different words, the relationship being an “is-a” relationship between the one or more different words and the meta-keyword; obtaining a plurality of linguistically transformed keywords associated with the meta-keyword; performing a search using the plurality of the linguistically transformed keywords to obtain a result; and providing the result to a client machine for presentation, the result being provided in a plurality of tabbed pages, a first tabbed page of the plurality of tabbed pages including a first linguistically transformed keyword of the plurality of linguistically transformed keywords and a first portion of the result corresponding to the first linguistically transformed keyword, a second tabbed page of the plurality of tabbed pages including a second linguistically transformed keyword of the plurality of linguistically transformed keywords and second portion of the results corresponding to the second linguistically transformed keyword, wherein the plurality of the linguistically transformed keywords comprises at least one of a hyponym keyword, a hypernym keyword, a meronym keyword, a holonym keyword, a derived keyword, a sounds-like keyword, or combinations thereof. | 1. A method comprising: receiving a term of a search request; identifying the term as a meta-keyword, the meta-keyword having a relationship with one or more different words, the relationship being an “is-a” relationship between the one or more different words and the meta-keyword; obtaining a plurality of linguistically transformed keywords associated with the meta-keyword; performing a search using the plurality of the linguistically transformed keywords to obtain a result; and providing the result to a client machine for presentation, the result being provided in a plurality of tabbed pages, a first tabbed page of the plurality of tabbed pages including a first linguistically transformed keyword of the plurality of linguistically transformed keywords and a first portion of the result corresponding to the first linguistically transformed keyword, a second tabbed page of the plurality of tabbed pages including a second linguistically transformed keyword of the plurality of linguistically transformed keywords and second portion of the results corresponding to the second linguistically transformed keyword, wherein the plurality of the linguistically transformed keywords comprises at least one of a hyponym keyword, a hypernym keyword, a meronym keyword, a holonym keyword, a derived keyword, a sounds-like keyword, or combinations thereof. 3. The method of claim 1 , wherein the obtaining comprises: accessing a plurality of prior user search patterns; analyzing the plurality of prior user search patterns to identify the plurality of the linguistically transformed keywords. | 0.601567 |
36. The method of claim 1 , wherein providing, for display in a drop-down menu and to the user device, a first drop down entry that indicates a first instance of the auto-completion and that includes an icon representing the first corpus adjacent to the first instance of the auto-completion, and a second drop down entry that indicates a second instance of the auto-completion that corresponds to the universal search corpus and that excludes the icon representing the first corpus comprises: providing, for display in the drop down menu and to the user device, a user interface element representing the universal search corpus adjacent to the second instance of the auto-completion. | 36. The method of claim 1 , wherein providing, for display in a drop-down menu and to the user device, a first drop down entry that indicates a first instance of the auto-completion and that includes an icon representing the first corpus adjacent to the first instance of the auto-completion, and a second drop down entry that indicates a second instance of the auto-completion that corresponds to the universal search corpus and that excludes the icon representing the first corpus comprises: providing, for display in the drop down menu and to the user device, a user interface element representing the universal search corpus adjacent to the second instance of the auto-completion. 37. The method of claim 36 , wherein the user interface element representing the universal search corpus is located after the second instance of the auto-completion. | 0.850048 |
1. A method of optimising Rate Distortion Optimisation candidate assessment in hardware apparatus, comprising: determining which Rate Distortion Optimisation candidates out of a plurality of candidates are separately processable, wherein the candidates are partitions of a picture; determining a processing delay of critical portions of candidate assessment hardware, wherein the critical portions of candidate processing hardware include a Rate Distortion Optimization Best Candidate Decision Block; a Motion Vector Predictor Calculation Block; and a Sum and Langrangian Multiplication Block; determining a rule set governing how the separately processable candidates may be ordered for processing, wherein the rule set for ordering the separately processable candidates depends on the input video resolution; determining an optimised processing order for processing the separately processable candidate assessments, dependent on the processing delay of critical portions of the candidate assessment hardware and the determined rule set; spending enough clock cycles processing other candidates in between partitions of the same size, such that the best candidate for a given partition can be set in time to calculate a motion vector difference (MVD) bit cost (RMV) for the next partition; and processing the candidates according to the determined processing order. | 1. A method of optimising Rate Distortion Optimisation candidate assessment in hardware apparatus, comprising: determining which Rate Distortion Optimisation candidates out of a plurality of candidates are separately processable, wherein the candidates are partitions of a picture; determining a processing delay of critical portions of candidate assessment hardware, wherein the critical portions of candidate processing hardware include a Rate Distortion Optimization Best Candidate Decision Block; a Motion Vector Predictor Calculation Block; and a Sum and Langrangian Multiplication Block; determining a rule set governing how the separately processable candidates may be ordered for processing, wherein the rule set for ordering the separately processable candidates depends on the input video resolution; determining an optimised processing order for processing the separately processable candidate assessments, dependent on the processing delay of critical portions of the candidate assessment hardware and the determined rule set; spending enough clock cycles processing other candidates in between partitions of the same size, such that the best candidate for a given partition can be set in time to calculate a motion vector difference (MVD) bit cost (RMV) for the next partition; and processing the candidates according to the determined processing order. 2. The method of claim 1 , wherein the rule set is dependent on the number of candidates being processed during Rate Distortion Optimisation. | 0.671108 |
9. A method comprising: accessing a plurality of logged actions related to a viewing user of a social networking system, the plurality of logged actions comprising logged actions of the viewing user or one or more other users connected to the viewing user in the social networking system; selecting one or more of the logged actions from the plurality of logged actions based at least in part on a relevance of each of the logged actions to the viewing user; generating a plurality of candidate stories from the logged actions based on a view requested by the viewing user, each of the plurality of candidate stories being associated with a story type of plurality of story types, two or more stories of the plurality of candidate stories associated with a same logged action; selecting one or more of the generated candidate stories based on the viewing user; identifying the two or more candidate stories associated with the same logged action; responsive to the identifying, removing a subset of the two or more candidate stories from the plurality of candidate stories; and sending displayable representations of the candidate stories to a client device for display to the viewing user. | 9. A method comprising: accessing a plurality of logged actions related to a viewing user of a social networking system, the plurality of logged actions comprising logged actions of the viewing user or one or more other users connected to the viewing user in the social networking system; selecting one or more of the logged actions from the plurality of logged actions based at least in part on a relevance of each of the logged actions to the viewing user; generating a plurality of candidate stories from the logged actions based on a view requested by the viewing user, each of the plurality of candidate stories being associated with a story type of plurality of story types, two or more stories of the plurality of candidate stories associated with a same logged action; selecting one or more of the generated candidate stories based on the viewing user; identifying the two or more candidate stories associated with the same logged action; responsive to the identifying, removing a subset of the two or more candidate stories from the plurality of candidate stories; and sending displayable representations of the candidate stories to a client device for display to the viewing user. 10. The method of claim 9 , wherein selecting logged actions from the plurality of logged actions based at least in part on the relevance of each of the logged actions to the viewing user comprises: determining a type of logged action associated with the requested view; identifying logged actions having the type of logged action associated with the requested view; and selecting the logged actions from the identified logged actions based at least in part on the relevance of the identified logged actions to the viewing user. | 0.747132 |
1. A computer implemented method for implementing multi-power domain digital or mixed-signal verification and low power simulation of an electronic circuit design, comprising: using a computer system to perform a process, the process comprising: identifying one or more schematics of the electronic circuit design; generating one or more net or terminal sets or one or more overriding net or terminal sets for the one or more schematics of the electronic circuit design by at least referencing a power data file for the electronic circuit design, wherein the power data file for the electronic circuit design includes a specification of one or more power-saving techniques and data or information for power intent for at least a portion of the electronic circuit design to provide portability of the power intent across multiple electronic circuit design tools; and performing verification or simulation of the electronic circuit design by using at least the one or more net or terminal sets or the one or more overriding net or terminal sets. | 1. A computer implemented method for implementing multi-power domain digital or mixed-signal verification and low power simulation of an electronic circuit design, comprising: using a computer system to perform a process, the process comprising: identifying one or more schematics of the electronic circuit design; generating one or more net or terminal sets or one or more overriding net or terminal sets for the one or more schematics of the electronic circuit design by at least referencing a power data file for the electronic circuit design, wherein the power data file for the electronic circuit design includes a specification of one or more power-saving techniques and data or information for power intent for at least a portion of the electronic circuit design to provide portability of the power intent across multiple electronic circuit design tools; and performing verification or simulation of the electronic circuit design by using at least the one or more net or terminal sets or the one or more overriding net or terminal sets. 14. The computer implemented method of claim 1 , further comprising: specifying or causing to specify a net or terminal expression. | 0.675171 |
27. A digital conversation generating processor-implemented method, comprising: instantiating a processor-implemented dialogue agent; identifying an individual target for conversation; initiating a conversational dialogue between the individual target and the dialogue agent; recording a first dialogue segment from the individual target as part of the conversational dialogue, wherein the first dialogue segment is a subportion of the conversational dialogue; responding to the first dialogue segment from the individual target with an at least one subsequent response dialogue segment, wherein the at least one subsequent response dialogue segment is a subportion of the conversational dialogue; recording a subsequent dialogue segment from the individual target, wherein the subsequent dialogue segment is a subportion of the conversational dialogue; retrieving the recorded interactive dialogue between the individual target and the dialogue agent; allocating a value point to each interactive dialogue segment of the interactive dialogue; creating a digital conversation asset comprising at least the retrieved interactive dialogue associated with the allocated value point to each subsequent interactive dialogue segment of the interactive dialogue; determining a value for the digital conversation asset at least based on the allocated value point to each subsequent interactive dialogue segment of the interactive dialogue; and providing the created digital conversation asset associated with the determined value for exchange. | 27. A digital conversation generating processor-implemented method, comprising: instantiating a processor-implemented dialogue agent; identifying an individual target for conversation; initiating a conversational dialogue between the individual target and the dialogue agent; recording a first dialogue segment from the individual target as part of the conversational dialogue, wherein the first dialogue segment is a subportion of the conversational dialogue; responding to the first dialogue segment from the individual target with an at least one subsequent response dialogue segment, wherein the at least one subsequent response dialogue segment is a subportion of the conversational dialogue; recording a subsequent dialogue segment from the individual target, wherein the subsequent dialogue segment is a subportion of the conversational dialogue; retrieving the recorded interactive dialogue between the individual target and the dialogue agent; allocating a value point to each interactive dialogue segment of the interactive dialogue; creating a digital conversation asset comprising at least the retrieved interactive dialogue associated with the allocated value point to each subsequent interactive dialogue segment of the interactive dialogue; determining a value for the digital conversation asset at least based on the allocated value point to each subsequent interactive dialogue segment of the interactive dialogue; and providing the created digital conversation asset associated with the determined value for exchange. 34. The method of claim 27 , further comprising: registering the conversation on a financial trading platform. | 0.619432 |
27. An information handling system comprising: one or more processors; a memory accessible by the processors; a storage device accessible by the processors; and a dataflow computing system for simulating dataflow, the dataflow computing system being effective to: include a plurality of operators in a dataflow diagram, wherein each of the operators includes at least one input port or at least one output port; include a plurality of arcs in the dataflow diagram, wherein each of the arcs connects one of the output ports of one of the plurality operators to one of the input ports of a different one of the plurality of operators; include a plurality of data items that flow in streams along the plurality of arcs between the plurality of operators; group the plurality of data items into a particle at a first operator included in the plurality of operators to form a particle grouping, wherein the first operator includes meta ports, wherein the meta ports include an arc-level meta port and a particle-level meta port, wherein the arc-level meta-port provides an arc-level meta-state that holds the state execution from a process initialization point to a process termination point, and wherein the particle-level meta-port provides a particle-level meta-state that provides an execution state of an input particle at any given point of time; perform, at the first operator, computations on the particle grouping, resulting in a computed plurality of data items; transmit, from the first operator, the computed plurality of data items over one of the plurality of arcs to a second operator included in the plurality of operators; produce control data items at one of the meta ports included on the first operator based upon meta-state transitions that are in response to the computations performed by the first operator on the particle grouping; and transmit the control data items from the first operator to one of the plurality of operators, wherein the control data items control the flow of the computed plurality of data items. | 27. An information handling system comprising: one or more processors; a memory accessible by the processors; a storage device accessible by the processors; and a dataflow computing system for simulating dataflow, the dataflow computing system being effective to: include a plurality of operators in a dataflow diagram, wherein each of the operators includes at least one input port or at least one output port; include a plurality of arcs in the dataflow diagram, wherein each of the arcs connects one of the output ports of one of the plurality operators to one of the input ports of a different one of the plurality of operators; include a plurality of data items that flow in streams along the plurality of arcs between the plurality of operators; group the plurality of data items into a particle at a first operator included in the plurality of operators to form a particle grouping, wherein the first operator includes meta ports, wherein the meta ports include an arc-level meta port and a particle-level meta port, wherein the arc-level meta-port provides an arc-level meta-state that holds the state execution from a process initialization point to a process termination point, and wherein the particle-level meta-port provides a particle-level meta-state that provides an execution state of an input particle at any given point of time; perform, at the first operator, computations on the particle grouping, resulting in a computed plurality of data items; transmit, from the first operator, the computed plurality of data items over one of the plurality of arcs to a second operator included in the plurality of operators; produce control data items at one of the meta ports included on the first operator based upon meta-state transitions that are in response to the computations performed by the first operator on the particle grouping; and transmit the control data items from the first operator to one of the plurality of operators, wherein the control data items control the flow of the computed plurality of data items. 29. The information handling system of claim 27 wherein the dataflow computing system is further effective to: transmit the control data items to the second operator, the control data items instructing the second operator a time at which to process the computed plurality of data items. | 0.665136 |
8. A computer-implemented method for accessing documents, the method comprising: from a device, receiving a request for creating an analytical file corresponding to a document stored on a server; retrieving, from the device, a business intelligence archive resource (BIAR) file related to the document, wherein the BIAR file includes metadata related to the document and connection details of the server; connecting to the server to retrieve the document and at least one of: values corresponding to the metadata, one or more annotations, and one or more operations related to the document from the server; integrating the retrieved document, the retrieved BIAR file,and the retrieved at least one of the values of the corresponding metadata, the one or more annotations, and the one or more operations to create the analytical file corresponding to the document; and storing the created analytical file locally on the device to enable accessing the document and the at least one of the values of the corresponding metadata, the one or more annotations, and the one or more operations related to the document, without being connected to the server. | 8. A computer-implemented method for accessing documents, the method comprising: from a device, receiving a request for creating an analytical file corresponding to a document stored on a server; retrieving, from the device, a business intelligence archive resource (BIAR) file related to the document, wherein the BIAR file includes metadata related to the document and connection details of the server; connecting to the server to retrieve the document and at least one of: values corresponding to the metadata, one or more annotations, and one or more operations related to the document from the server; integrating the retrieved document, the retrieved BIAR file,and the retrieved at least one of the values of the corresponding metadata, the one or more annotations, and the one or more operations to create the analytical file corresponding to the document; and storing the created analytical file locally on the device to enable accessing the document and the at least one of the values of the corresponding metadata, the one or more annotations, and the one or more operations related to the document, without being connected to the server. 9. The computer-implemented method of claim 8 further comprising: from the device, receiving a request to connect to the server to retrieve information comprising at least one of the document, the values of the corresponding metadata related to the document, the one or more annotations, and the one or more operations related to the document; based upon the request, determining whether the device is a registered device; upon determining that the device is the registered device, providing an access to the server to retrieve the information; and upon determining that the device is not the registered device, restricting the access to the server and displaying an error message. | 0.558885 |
1. A method, comprising: opening a first electronic document; creating a second electronic document superimposed over the first electronic document to receive annotations in reference to the first electronic document; creating, in response to creating the second electronic document to receive annotations, an association between the first electronic document and the second electronic document; saving the second document as a separate document independent of the first document; in response to a second opening of the first electronic document, and based upon the association between the first electronic document and the second electronic document that was annotated during a previous viewing of the first electronic document, automatically opening the second electronic document without user intervention; superimposing the second electronic document with the annotations over the first electronic document; and receiving additional annotations in reference to the first electronic document within the second electronic document concurrently while viewing the first electronic document beneath the second electronic document. | 1. A method, comprising: opening a first electronic document; creating a second electronic document superimposed over the first electronic document to receive annotations in reference to the first electronic document; creating, in response to creating the second electronic document to receive annotations, an association between the first electronic document and the second electronic document; saving the second document as a separate document independent of the first document; in response to a second opening of the first electronic document, and based upon the association between the first electronic document and the second electronic document that was annotated during a previous viewing of the first electronic document, automatically opening the second electronic document without user intervention; superimposing the second electronic document with the annotations over the first electronic document; and receiving additional annotations in reference to the first electronic document within the second electronic document concurrently while viewing the first electronic document beneath the second electronic document. 7. The method of claim 1 , wherein the first electronic document is a spreadsheet file. | 0.641042 |
1. A system for generating a language-independent representation of a software project's structure from its source code comprises: one or more language analyzers, each comprising a language structurer system and a language inferencer system for a selected language, wherein said language structurer system generates a language-specific representation of code structure from the software project, and said language inferencer system augments the language-specific representation with additional, inferred information; one or more language translators in communication with said one or more language analyzers for mapping from language-specific components to language-independent components, wherein said language-independent components represent a source-to-source translation that maintains a semantic structure of the software project's source code such that each language-independent component corresponds to at least one of a function, a method, a package, a class, a type, a field, a variable declaration, a comment, an interface, a reference to the function, a reference to the method, a reference to the package, a reference to the class, a reference to the type, a reference to the field, and a reference to the variable declaration; and a database for storage of the language-independent components. | 1. A system for generating a language-independent representation of a software project's structure from its source code comprises: one or more language analyzers, each comprising a language structurer system and a language inferencer system for a selected language, wherein said language structurer system generates a language-specific representation of code structure from the software project, and said language inferencer system augments the language-specific representation with additional, inferred information; one or more language translators in communication with said one or more language analyzers for mapping from language-specific components to language-independent components, wherein said language-independent components represent a source-to-source translation that maintains a semantic structure of the software project's source code such that each language-independent component corresponds to at least one of a function, a method, a package, a class, a type, a field, a variable declaration, a comment, an interface, a reference to the function, a reference to the method, a reference to the package, a reference to the class, a reference to the type, a reference to the field, and a reference to the variable declaration; and a database for storage of the language-independent components. 7. The system of claim 1 , wherein the additional, inferred information is obtained from at least one of constraint-based type inference and global probabilistic models. | 0.548364 |
1. A computer-implemented method for text processing, the method being executable at a computing device, the method comprising: at a training phase: acquiring one or more source phrases, each of the source phrase comprising a first set of sequential words, each word of the first set of sequential words being a source word; acquiring one or more target phrases, each of the target phrase being in a same language as the source phrases, each of the target phrase comprising a second set of sequential words being at least partially different from the first set of sequential words of a respective source phrase, each word of the second set of sequential words being a target word; associating, for a given source phrase, a respective source word feature set with each one of the source words, the respective source word feature set for a given source word comprising: one or more grammatical features of the given source word; and a meaning of the given source word; associating, for a respective target phrase, a respective target word feature set with each one of the target words, the respective target word feature set for a given target word comprising: one or more grammatical features of the given target word; and a meaning of the given target word; analyzing the respective source word feature set of each source words of the given source phrase and the respective target word feature set of each target words of the respective target phrase; mapping the given source word of the given source phrase to a corresponding target word of the respective target phrase based on a similarity of the source word feature set of the given source word to the target word feature set of the corresponding target word; based on the mapping, generating one or more phrase transformation rules applicable to the given source phrase to transform the first set of sequential words into the second set of sequential words of the respective target phrase; storing the one or more source phrases and the associated one or more generated phrase transformation rules in a memory of the computing device; at an in-use phase: acquiring a text phrase, the text phrase comprising a third set of sequential words being at least partially different from the first set of sequential words; and retrieving the one or more source phrases from the memory; performing at least one of a grammatical analysis and a semantic analysis of the text phrase and the one or more stored source phrases, to determine similarity of the text phrase to the one or more stored source phrases; upon determining that the text phrase has the similarity to the given stored source phrase greater than a threshold, applying the associated one or more phrase transformation rules to the text phrase to generate a transformed text phrase, the transformed text phrase comprising a fourth set of sequential words being at least partially similar to the second set of sequential words of the respective target phrase. | 1. A computer-implemented method for text processing, the method being executable at a computing device, the method comprising: at a training phase: acquiring one or more source phrases, each of the source phrase comprising a first set of sequential words, each word of the first set of sequential words being a source word; acquiring one or more target phrases, each of the target phrase being in a same language as the source phrases, each of the target phrase comprising a second set of sequential words being at least partially different from the first set of sequential words of a respective source phrase, each word of the second set of sequential words being a target word; associating, for a given source phrase, a respective source word feature set with each one of the source words, the respective source word feature set for a given source word comprising: one or more grammatical features of the given source word; and a meaning of the given source word; associating, for a respective target phrase, a respective target word feature set with each one of the target words, the respective target word feature set for a given target word comprising: one or more grammatical features of the given target word; and a meaning of the given target word; analyzing the respective source word feature set of each source words of the given source phrase and the respective target word feature set of each target words of the respective target phrase; mapping the given source word of the given source phrase to a corresponding target word of the respective target phrase based on a similarity of the source word feature set of the given source word to the target word feature set of the corresponding target word; based on the mapping, generating one or more phrase transformation rules applicable to the given source phrase to transform the first set of sequential words into the second set of sequential words of the respective target phrase; storing the one or more source phrases and the associated one or more generated phrase transformation rules in a memory of the computing device; at an in-use phase: acquiring a text phrase, the text phrase comprising a third set of sequential words being at least partially different from the first set of sequential words; and retrieving the one or more source phrases from the memory; performing at least one of a grammatical analysis and a semantic analysis of the text phrase and the one or more stored source phrases, to determine similarity of the text phrase to the one or more stored source phrases; upon determining that the text phrase has the similarity to the given stored source phrase greater than a threshold, applying the associated one or more phrase transformation rules to the text phrase to generate a transformed text phrase, the transformed text phrase comprising a fourth set of sequential words being at least partially similar to the second set of sequential words of the respective target phrase. 2. The method of claim 1 , wherein: determining the similarity of each one of the source word feature sets to each one of the target word feature sets comprises comparing the respective grammatical features of each one of the source words to the respective grammatical features of each one of the target words; determining the similarity of each one of the source word feature sets to each one of the target word feature sets comprises determining a similarity of the respective meaning of each one of the source words to the respective meaning of each one of the target words. | 0.533566 |
1. A learning apparatus for a pattern detector, which includes a plurality of weak classifiers and detects a specific pattern from input data by classifications of the plurality of weak classifiers, comprising: an acquisition unit configured to acquire a plurality of data for learning in each of which whether or not the specific pattern is included is given; a learning unit configured to make the plurality of weak classifiers learn by making the plurality of weak classifiers detect the specific pattern from the data for learning acquired by the acquisition unit; a selection unit configured to select a plurality of weak classifiers to be composited from the weak classifiers which have learned by the learning unit; a composition unit configured to composite the plurality of weak classifiers selected by the selection unit into one composite weak classifier based on comparison between a performance of the composite weak classifier and performances of the plurality of weak classifiers; and an initialization unit configured to initialize a filter structure of the composite weak classifier after composition by superimposing filter structures of the selected plurality of weak classifiers. | 1. A learning apparatus for a pattern detector, which includes a plurality of weak classifiers and detects a specific pattern from input data by classifications of the plurality of weak classifiers, comprising: an acquisition unit configured to acquire a plurality of data for learning in each of which whether or not the specific pattern is included is given; a learning unit configured to make the plurality of weak classifiers learn by making the plurality of weak classifiers detect the specific pattern from the data for learning acquired by the acquisition unit; a selection unit configured to select a plurality of weak classifiers to be composited from the weak classifiers which have learned by the learning unit; a composition unit configured to composite the plurality of weak classifiers selected by the selection unit into one composite weak classifier based on comparison between a performance of the composite weak classifier and performances of the plurality of weak classifiers; and an initialization unit configured to initialize a filter structure of the composite weak classifier after composition by superimposing filter structures of the selected plurality of weak classifiers. 17. The apparatus according to claim 1 , wherein a characteristic evaluation value of the weak classifier is based on at least one of a detection ratio of the specific pattern, a detection speed of the specific pattern, and an abortion ratio when the learning unit makes the weak classifier learn using data for learning. | 0.561872 |
12. The method of claim 1 , wherein determining the composite impairment correlation term based on the subset of modeled impairment correlation terms comprises: scaling the modeled impairment correlation terms included in the subset by respective model fitting parameters; and combining the scaled modeled impairment correlation terms to form the composite impairment correlation term. | 12. The method of claim 1 , wherein determining the composite impairment correlation term based on the subset of modeled impairment correlation terms comprises: scaling the modeled impairment correlation terms included in the subset by respective model fitting parameters; and combining the scaled modeled impairment correlation terms to form the composite impairment correlation term. 13. The method of claim 12 , wherein the model fitting parameters are calculated based on the set of modeled impairment correlation terms. | 0.810378 |
1. A method of identifying a name and boundary of a neighborhood based on web documents, the method comprising: extracting, via one or more processors, n-grams appearing in a plurality of web documents and being of less than a threshold word count: obtaining a plurality of web documents, each web document being associated with a respective geographic location, the web documents including user reviews of local businesses associated with the respective geographic locations in the geographic information system, extracting n-grams from each of the web documents; associating, via the one or more processors, the n-grams with geographic locations associated with the web documents from which the n-grams were extracted, including associating each of the n-grams with a respective latitude and longitude coordinate of the web document from which the n-grams were extracted; identifying, via the one or more processors, a neighborhood by identifying a cluster of geographic locations associated with the n-grams, including: filtering from the n-grams stop-words, filtering from the n-grams phrases occurring in the web documents less than a threshold amount, filtering from the n-grams at least some n-grams that do not correspond with a cluster, filtering from the n-grams at least some n-grams that correspond to more than a threshold amount of clusters, filtering from the n-grams at least some n-grams that correspond to more than a threshold amount of geographic locations outside of a cluster; determining, via the one or more processors, a boundary for the neighborhood from the distribution of geographical locations in the cluster, including determining a convex hull of the cluster by identifying geographic locations of vertices of a polygon that contains at least a substantial portion of the cluster; determining, via the one or more processors, a name for the neighborhood from the n-gram, including: designating the n-gram as a candidate name for the geographic area defined by the polygon, identifying one or more candidate names for geographic areas at least partially overlapping the polygon, ranking the candidate names based on an amount of times the name appears in the web documents and the size of the geographic areas at least partially overlapping the polygon, and selecting the highest ranking candidate name as the name; and adding, via the one or more processors, the name and boundary of the neighborhood to a geographic information system, including storing the name in memory in a record that associates the name with the geographic area defined by the boundary. | 1. A method of identifying a name and boundary of a neighborhood based on web documents, the method comprising: extracting, via one or more processors, n-grams appearing in a plurality of web documents and being of less than a threshold word count: obtaining a plurality of web documents, each web document being associated with a respective geographic location, the web documents including user reviews of local businesses associated with the respective geographic locations in the geographic information system, extracting n-grams from each of the web documents; associating, via the one or more processors, the n-grams with geographic locations associated with the web documents from which the n-grams were extracted, including associating each of the n-grams with a respective latitude and longitude coordinate of the web document from which the n-grams were extracted; identifying, via the one or more processors, a neighborhood by identifying a cluster of geographic locations associated with the n-grams, including: filtering from the n-grams stop-words, filtering from the n-grams phrases occurring in the web documents less than a threshold amount, filtering from the n-grams at least some n-grams that do not correspond with a cluster, filtering from the n-grams at least some n-grams that correspond to more than a threshold amount of clusters, filtering from the n-grams at least some n-grams that correspond to more than a threshold amount of geographic locations outside of a cluster; determining, via the one or more processors, a boundary for the neighborhood from the distribution of geographical locations in the cluster, including determining a convex hull of the cluster by identifying geographic locations of vertices of a polygon that contains at least a substantial portion of the cluster; determining, via the one or more processors, a name for the neighborhood from the n-gram, including: designating the n-gram as a candidate name for the geographic area defined by the polygon, identifying one or more candidate names for geographic areas at least partially overlapping the polygon, ranking the candidate names based on an amount of times the name appears in the web documents and the size of the geographic areas at least partially overlapping the polygon, and selecting the highest ranking candidate name as the name; and adding, via the one or more processors, the name and boundary of the neighborhood to a geographic information system, including storing the name in memory in a record that associates the name with the geographic area defined by the boundary. 9. The method of claim 1 , wherein extracting the n-gram appearing in the plurality of web documents comprises: extracting n-grams of a plurality of different lengths and less than a threshold length from the web documents. | 0.529527 |
18. A computer-readable medium storing thereon computer-readable instructions, comprising: instructions for ascertaining an intent of a query; instructions for determining a relevance of each one of a plurality of lines of text of a document based upon the intent of the query, content of the query, and content of each of the plurality of lines of text, wherein the document is a single search result returned in response to the query; instructions for ranking the plurality of lines of text according to the determined relevance of each of the plurality of lines of text; and instructions for generating a summary of the single search result using a subset of the plurality of lines of text based upon the ranking of the plurality of lines of text. | 18. A computer-readable medium storing thereon computer-readable instructions, comprising: instructions for ascertaining an intent of a query; instructions for determining a relevance of each one of a plurality of lines of text of a document based upon the intent of the query, content of the query, and content of each of the plurality of lines of text, wherein the document is a single search result returned in response to the query; instructions for ranking the plurality of lines of text according to the determined relevance of each of the plurality of lines of text; and instructions for generating a summary of the single search result using a subset of the plurality of lines of text based upon the ranking of the plurality of lines of text. 20. The computer-readable medium as recited in claim 18 , wherein the instructions for determining a relevance of each one of a plurality of lines of text of a document based upon the intent of the query, content of the query, and content of each of the plurality of lines of text comprises: instructions for determining a query-independent relevance of each of the plurality of lines of text in the document; instructions for determining a query-dependent relevance of each of the plurality of lines of text in the document; and instructions for calculating the relevance of each one of the plurality of lines of text based upon the intent of the query, the query independent relevance of the one of the plurality of lines of text in the document and the query dependent relevance of the one of the plurality of lines of text in the document. | 0.505459 |
10. An apparatus for determining an economic impact of business policies, comprising: a computer system; a business process definition module executable in the computer system for providing player definitions defining a plurality of players and an associated set of rules defining a decision space, a decision-making process tree, an information set, an outcome function, and a payoff function for each player; a script translator module executable in the computer system for translating the player definitions into codified scripts, wherein the codified scripts define at least one simulation stage; and a simulation module executable in the computer system for executing the codified scripts, wherein a result of the outcome and payoff functions at the end of execution of the at least one simulation stage determines the economic impact of the business policies. | 10. An apparatus for determining an economic impact of business policies, comprising: a computer system; a business process definition module executable in the computer system for providing player definitions defining a plurality of players and an associated set of rules defining a decision space, a decision-making process tree, an information set, an outcome function, and a payoff function for each player; a script translator module executable in the computer system for translating the player definitions into codified scripts, wherein the codified scripts define at least one simulation stage; and a simulation module executable in the computer system for executing the codified scripts, wherein a result of the outcome and payoff functions at the end of execution of the at least one simulation stage determines the economic impact of the business policies. 21. The apparatus of claim 10 , wherein in response to modification of the set of rules for one or more players, the script translator re-translates the player definitions into modified scripts, and the simulation module is for executing the modified scripts. | 0.531339 |
1. A method of naming resources stored in a resource set of a device having a processor, a name hierarchy, and a name hierarchy navigation logic, the method comprising: executing on the processor instructions configured to: upon receiving a resource, store the resource in the resource set; upon receiving a public name of a resource: using the name hierarchy navigation logic, compute, from the public name, an identifier associated with a location in the name hierarchy, and store, at the location in the name hierarchy associated with the identifier, a reference to the resource in the resource set; and upon receiving a request for a resource associated with a public name: using the name hierarchy navigation logic, compute, from the public name, the identifier associated with the location in the name hierarchy; retrieve, from the location in the name hierarchy associated with the identifier, the reference to a resource in the resource set; using the reference, retrieve the resource from the resource set; and present the resource in response to the request. | 1. A method of naming resources stored in a resource set of a device having a processor, a name hierarchy, and a name hierarchy navigation logic, the method comprising: executing on the processor instructions configured to: upon receiving a resource, store the resource in the resource set; upon receiving a public name of a resource: using the name hierarchy navigation logic, compute, from the public name, an identifier associated with a location in the name hierarchy, and store, at the location in the name hierarchy associated with the identifier, a reference to the resource in the resource set; and upon receiving a request for a resource associated with a public name: using the name hierarchy navigation logic, compute, from the public name, the identifier associated with the location in the name hierarchy; retrieve, from the location in the name hierarchy associated with the identifier, the reference to a resource in the resource set; using the reference, retrieve the resource from the resource set; and present the resource in response to the request. 4. The method of claim 1 , the device having a hierarchical data store comprising the resource set and the name hierarchy. | 0.726728 |
1. A method for interpreting natural language utterances using out-of-vocabulary and noise toleration capabilities, comprising: recognizing, on an electronic device, a phoneme stream contained in an utterance received at the electronic device; mapping, on the electronic device, the recognized phoneme stream to a syllable series that includes one or more syllables that an acoustic grammar phonemically represents in accordance with an acoustic speech model; and generating, on the electronic device, an interpretation of the utterance that includes the one or more syllables in the syllable series mapped to the recognized phoneme stream. | 1. A method for interpreting natural language utterances using out-of-vocabulary and noise toleration capabilities, comprising: recognizing, on an electronic device, a phoneme stream contained in an utterance received at the electronic device; mapping, on the electronic device, the recognized phoneme stream to a syllable series that includes one or more syllables that an acoustic grammar phonemically represents in accordance with an acoustic speech model; and generating, on the electronic device, an interpretation of the utterance that includes the one or more syllables in the syllable series mapped to the recognized phoneme stream. 3. The method of claim 1 , wherein the acoustic speech model includes an unstressed central vowel that links sequential phonemic elements in the acoustic speech model. | 0.56701 |
8. One or more non-transitory computer readable media comprising instructions that, when executed by a processor, cause the processor to perform steps comprising: receiving, by a computing device, audiovisual input comprising audio input and video input associated with a subject; extracting, by the computing device, visual features from the video input; applying, by the computing device, a scattering operation to the extracted visual features to generate a vector of scattering coefficients in a first dimensional space; providing the vector of scattering coefficients as input to a first neural network for visual processing; providing the audio input to a second neural network for audio processing; comparing, by the computing device, a first output of the first neural network with a second output of the second neural network to determine a synchrony state of the audio input and the video input, wherein the synchrony state indicates whether the audio input is in-sync with the video input; and storing the synchrony state of the audio input and the video input. | 8. One or more non-transitory computer readable media comprising instructions that, when executed by a processor, cause the processor to perform steps comprising: receiving, by a computing device, audiovisual input comprising audio input and video input associated with a subject; extracting, by the computing device, visual features from the video input; applying, by the computing device, a scattering operation to the extracted visual features to generate a vector of scattering coefficients in a first dimensional space; providing the vector of scattering coefficients as input to a first neural network for visual processing; providing the audio input to a second neural network for audio processing; comparing, by the computing device, a first output of the first neural network with a second output of the second neural network to determine a synchrony state of the audio input and the video input, wherein the synchrony state indicates whether the audio input is in-sync with the video input; and storing the synchrony state of the audio input and the video input. 12. The computer readable media of claim 8 , wherein applying the scattering operation to the extracted visual features to generate a vector of visual scattering features in a first dimensional space comprises: applying the scattering operation to the extracted visual features to generate a second scattering vector in a second dimensional space; and projecting the second scattering vector into the first dimensional space to generate the vector of visual scattering features in the first dimensional space, wherein the second dimensional space is of a higher dimensionality than the first dimensional space. | 0.616206 |
1. A system comprising: a first computer-readable storage media having stored thereon a reference dictionary file data structure, the reference dictionary file data structure including terms parsed from a plurality of documents stored in a document repository, and terms parsed from a new document received by the system but not stored in the document repository, the plurality of documents and the new document parsed without regard to any user profile, a user profile updated based at least in part on terms from the new document included in the reference dictionary file data structure and feedback from a user regarding relevance of a document received by the user before the system determines whether the new document is relevant to any user, the user profile specifying one or more areas of interest of the user; the first computer-readable storage media having stored thereon a parsed term data structure, the parsed term data structure including a one or more parsed terms and a term selection value associated with each of the one or more parsed terms, each of the parsed terms either: present in the reference dictionary file data structure indicating at least one document indicated as relevant to the user contains the term, or present in an original user profile, at least one of the parsed terms present in an original user profile and not present in the reference dictionary file data, the term selection value used for determining whether the associated term is to be included in the undated user profile; and a second computer-readable storage media having stored thereon a document dictionary index data structure and the document repository, the document dictionary index data structure including only terms located in the plurality of documents stored in the document repository. | 1. A system comprising: a first computer-readable storage media having stored thereon a reference dictionary file data structure, the reference dictionary file data structure including terms parsed from a plurality of documents stored in a document repository, and terms parsed from a new document received by the system but not stored in the document repository, the plurality of documents and the new document parsed without regard to any user profile, a user profile updated based at least in part on terms from the new document included in the reference dictionary file data structure and feedback from a user regarding relevance of a document received by the user before the system determines whether the new document is relevant to any user, the user profile specifying one or more areas of interest of the user; the first computer-readable storage media having stored thereon a parsed term data structure, the parsed term data structure including a one or more parsed terms and a term selection value associated with each of the one or more parsed terms, each of the parsed terms either: present in the reference dictionary file data structure indicating at least one document indicated as relevant to the user contains the term, or present in an original user profile, at least one of the parsed terms present in an original user profile and not present in the reference dictionary file data, the term selection value used for determining whether the associated term is to be included in the undated user profile; and a second computer-readable storage media having stored thereon a document dictionary index data structure and the document repository, the document dictionary index data structure including only terms located in the plurality of documents stored in the document repository. 10. A system as defined in claim 1 , further comprising a profile repository stored on the first computer-readable storage media. | 0.779966 |
1. A method for analyzing an electronic communication between a customer and a contact center, wherein the electronic communication is a telephonic communication, the method comprising: receiving a single telephonic communication between a first communicant to the telephonic communication and a second communicant to the telephonic communication; separating the telephonic communication into at least first and second constituent voice data, the first constituent voice data being generated by the first communicant and the second constituent voice data being generated by the second communicant; analyzing one of the separated first and second constituent voice data by mining the separated one of the first and second constituent voice data and applying a predetermined linguistic-based psychological behavioral model to the one of the separated first and second constituent voice data; and, generating behavioral assessment data including a personality type corresponding to the analyzed one of the separated first and second constituent voice data based on the step of analyzing one of the first and second constituent voice data. | 1. A method for analyzing an electronic communication between a customer and a contact center, wherein the electronic communication is a telephonic communication, the method comprising: receiving a single telephonic communication between a first communicant to the telephonic communication and a second communicant to the telephonic communication; separating the telephonic communication into at least first and second constituent voice data, the first constituent voice data being generated by the first communicant and the second constituent voice data being generated by the second communicant; analyzing one of the separated first and second constituent voice data by mining the separated one of the first and second constituent voice data and applying a predetermined linguistic-based psychological behavioral model to the one of the separated first and second constituent voice data; and, generating behavioral assessment data including a personality type corresponding to the analyzed one of the separated first and second constituent voice data based on the step of analyzing one of the first and second constituent voice data. 4. The method of claim 1 , wherein the predetermined linguistic-based psychological behavioral model is adapted to assess distress levels in a communication, the method further comprising the step of generating distress assessment data corresponding to the analyzed one of the first and second voice data. | 0.693696 |
11. The computer-implemented method of claim 10 , wherein the layout of the text content is modified by a display tool having a plurality of components including an orientation detection component, a language detection component, and a rotation component. | 11. The computer-implemented method of claim 10 , wherein the layout of the text content is modified by a display tool having a plurality of components including an orientation detection component, a language detection component, and a rotation component. 12. The computer-implemented method of claim 11 , wherein each of the characters is encoded in a universal character encoding scheme, wherein each of the first and second languages is determined by identifying the respective language from a content language field of a respective HyperText Transfer Protocol (HTTP) header. | 0.854465 |
1. A method of providing information associated with a focused-on item in an electronic document, comprising: receiving a first user-initiated selection comprising a focus on an item contained in an electronic document; evaluating a current mode of the electronic document selected from a first mode in which a plurality of editing functions of the electronic document are disabled, and a second mode in which the plurality of editing functions of the electronic document are enabled; automatically initiating a search for information on the focused-on item when the current mode is evaluated as the first mode; receiving a second user-initiated selection for initiating the search for information on the focused-on item when the current mode is evaluated as the second mode, wherein the second user selection is selected from a group comprising: a simultaneous keyboard and mouse selection; and a control selection accessed in one of a control toolbar and a drop-down menu; passing data representing the focused-on item to an information source following initiating the search for information on the focused-on item; receiving the information associated with the focused-on item from the information source; automatically displaying the returned information associated with the focused-on item in a user interface in the electronic document in proximity to the focused-on item; and when the information associated with the focused-on item will not fit in an available display space provided in the user interface: truncating a portion of the information such that only a portion of the information that will fit in the available display space provided in the user interface is displayed; and disposing a selectable control tab on a first side the user interface which, when selected, causes a display of the truncated portion of the information, the selectable control tab including: a first selectable tab which, when selected, causes to be displayed a first portion of the truncated portion of the information; and a second selectable tab which, when selected, causes to be displayed a second portion of the truncated portion of the information; the first and second selectable tabs extending from the user interface, with the first selectable tab being positioned above the second selectable tab. | 1. A method of providing information associated with a focused-on item in an electronic document, comprising: receiving a first user-initiated selection comprising a focus on an item contained in an electronic document; evaluating a current mode of the electronic document selected from a first mode in which a plurality of editing functions of the electronic document are disabled, and a second mode in which the plurality of editing functions of the electronic document are enabled; automatically initiating a search for information on the focused-on item when the current mode is evaluated as the first mode; receiving a second user-initiated selection for initiating the search for information on the focused-on item when the current mode is evaluated as the second mode, wherein the second user selection is selected from a group comprising: a simultaneous keyboard and mouse selection; and a control selection accessed in one of a control toolbar and a drop-down menu; passing data representing the focused-on item to an information source following initiating the search for information on the focused-on item; receiving the information associated with the focused-on item from the information source; automatically displaying the returned information associated with the focused-on item in a user interface in the electronic document in proximity to the focused-on item; and when the information associated with the focused-on item will not fit in an available display space provided in the user interface: truncating a portion of the information such that only a portion of the information that will fit in the available display space provided in the user interface is displayed; and disposing a selectable control tab on a first side the user interface which, when selected, causes a display of the truncated portion of the information, the selectable control tab including: a first selectable tab which, when selected, causes to be displayed a first portion of the truncated portion of the information; and a second selectable tab which, when selected, causes to be displayed a second portion of the truncated portion of the information; the first and second selectable tabs extending from the user interface, with the first selectable tab being positioned above the second selectable tab. 2. The method of claim 1 , wherein receiving the information associated with the focused-on item includes receiving the information associated with the focused-on item in a format associated with each of a plurality of media types, and further comprising providing access to the information associated with the focused-on item in the format associated with each of the plurality of media types via the displayed user interface. | 0.563192 |
3. The method of claim 1 further comprising: constructing the animatronics unit in response the specification for construction of the animatronics unit; and animating the animatronics unit in response to the plurality of driving signals. | 3. The method of claim 1 further comprising: constructing the animatronics unit in response the specification for construction of the animatronics unit; and animating the animatronics unit in response to the plurality of driving signals. 4. The method of claim 3 further comprising receiving modified animation data for animating the kinematics-based software model, wherein the modified animation data comprises artistically determined modified motions for the kinematics-based software model by a user, in response to animation of the animatronics unit; determining a plurality of modified driving signals in response to the modified animation data; and animating the animatronics unit in response to the plurality of modified driving signals. | 0.867846 |
1. A method comprising using a computing device having a processing unit to perform the following: obtaining a list of searchable web sites, the list of searchable web sites including a first searchable web site to which users have submitted first queries and a second searchable web site to which the users have submitted second queries; inputting another query received from an individual user; computing probabilities of the searchable web sites given the another query, the probabilities including a first probability for the first searchable web site and a second probability for the second searchable web site; ranking the searchable web sites based on the probabilities; and creating a ranked list of searchable web sites based on the ranking, wherein, in at least one instance, the ranked list of searchable web sites includes the first searchable web site to which the users have submitted the first queries and the second searchable web site to which the users have submitted the second queries. | 1. A method comprising using a computing device having a processing unit to perform the following: obtaining a list of searchable web sites, the list of searchable web sites including a first searchable web site to which users have submitted first queries and a second searchable web site to which the users have submitted second queries; inputting another query received from an individual user; computing probabilities of the searchable web sites given the another query, the probabilities including a first probability for the first searchable web site and a second probability for the second searchable web site; ranking the searchable web sites based on the probabilities; and creating a ranked list of searchable web sites based on the ranking, wherein, in at least one instance, the ranked list of searchable web sites includes the first searchable web site to which the users have submitted the first queries and the second searchable web site to which the users have submitted the second queries. 7. The method of claim 1 , wherein the probabilities are computed using a probabilistic model having multiple components. | 0.713227 |
10. A computer system, comprising: one or more computing nodes having a memory and a processor; and a computer readable storage medium of the one or more computing nodes having program instructions embodied therewith, the program instructions executable by the processor to cause the computer system to: receive an inquiry, wherein the inquiry is directed to at least one content topic; identify the at least one content topic; determine that a cognitive component of the computer system managed by a content provider has access to a content repository addressing the at least one content topic, wherein the content provider restricts access to the content repository according to an agreement; determine, in response to the at least one topic and the agreement, that the cognitive component can address the inquiry; distribute, in response to determining that the cognitive component can address the inquiry, the inquiry to the cognitive component; receive a response from the cognitive component; process the response to generate an answer to the inquiry; determine that a first confidence score associated with the response from the cognitive component is below a threshold value; determine that one or more cognitive components, not associated with the computer system, has access to a content repository addressing the at least one content topic and can provide a response having a second confidence score, the second confidence score being larger than the first confidence score; and associate the one or more cognitive components with the computer system. | 10. A computer system, comprising: one or more computing nodes having a memory and a processor; and a computer readable storage medium of the one or more computing nodes having program instructions embodied therewith, the program instructions executable by the processor to cause the computer system to: receive an inquiry, wherein the inquiry is directed to at least one content topic; identify the at least one content topic; determine that a cognitive component of the computer system managed by a content provider has access to a content repository addressing the at least one content topic, wherein the content provider restricts access to the content repository according to an agreement; determine, in response to the at least one topic and the agreement, that the cognitive component can address the inquiry; distribute, in response to determining that the cognitive component can address the inquiry, the inquiry to the cognitive component; receive a response from the cognitive component; process the response to generate an answer to the inquiry; determine that a first confidence score associated with the response from the cognitive component is below a threshold value; determine that one or more cognitive components, not associated with the computer system, has access to a content repository addressing the at least one content topic and can provide a response having a second confidence score, the second confidence score being larger than the first confidence score; and associate the one or more cognitive components with the computer system. 12. The computer system of claim 10 , wherein the program instructions executable by the processor further cause the computer system to: segment the inquiry into a set of sub-inquiries; and identify, for a sub-inquiry in the set of sub-inquiries, a set of topics addressed by the inquiry. | 0.599407 |
13. A computer storage device storing instructions that upon execution by a data processing apparatus cause the data processing apparatus to perform operations comprising: receiving selection criteria for a campaign, the selection criteria including a plurality of keywords that control distribution of content items associated with the campaign; assigning each of the selection criteria to one or more sets of topic clusters, wherein at least some of the selection criteria are assigned to multiple topic clusters; determining, for pairs of selection criteria in one of the topic clusters, a measure of similarity between the topic clusters to which each selection criteria in the pair was assigned; identifying, as related pairs of selection criteria, the pairs of selection criteria for which the measure of similarity meets a threshold; creating a new keyword cluster based on the related pairs, the new keyword cluster including fewer than all of the keywords in the received selection criteria, the creating comprising: identifying a first selection keyword and a second selection keyword that are included in one of the related pairs; and including each of the first selection keyword and the second selection keyword in the new keyword cluster; and creating a new group for the campaign, the new group specifying at least one content item that is selected for distribution using keywords in the new keyword cluster. | 13. A computer storage device storing instructions that upon execution by a data processing apparatus cause the data processing apparatus to perform operations comprising: receiving selection criteria for a campaign, the selection criteria including a plurality of keywords that control distribution of content items associated with the campaign; assigning each of the selection criteria to one or more sets of topic clusters, wherein at least some of the selection criteria are assigned to multiple topic clusters; determining, for pairs of selection criteria in one of the topic clusters, a measure of similarity between the topic clusters to which each selection criteria in the pair was assigned; identifying, as related pairs of selection criteria, the pairs of selection criteria for which the measure of similarity meets a threshold; creating a new keyword cluster based on the related pairs, the new keyword cluster including fewer than all of the keywords in the received selection criteria, the creating comprising: identifying a first selection keyword and a second selection keyword that are included in one of the related pairs; and including each of the first selection keyword and the second selection keyword in the new keyword cluster; and creating a new group for the campaign, the new group specifying at least one content item that is selected for distribution using keywords in the new keyword cluster. 14. The computer storage device of claim 13 , wherein assigning each of the selection criteria to one or more sets of topic clusters comprises assigning each selection keyword in a set of selection keywords to one or more topic clusters corresponding to predetermined classifications. | 0.795482 |
15. A method performed in at least one computer, to convert a first web page into a second web page, the method comprising: receiving the first web page, wherein the first web page comprises a source-descriptive version of a text string, the source-descriptive version being expressed in accordance with a predetermined syntax, the source-descriptive version comprising each item in a group consisting of (the text string, a name of a source of the text string, and a unique identifier of the text string); wherein the unique identifier uniquely identifies the text string, from among a plurality of text strings in said source; automatically parsing the first web page to identify at least one item in the group; and automatically preparing the second web page, by adding to the first web page at least one of (a tag and an attribute), to hide from display in a browser the name of the source and the unique identifier of the text string; wherein the second web page comprises said text string, said name of the source, and said unique identifier of the text string. | 15. A method performed in at least one computer, to convert a first web page into a second web page, the method comprising: receiving the first web page, wherein the first web page comprises a source-descriptive version of a text string, the source-descriptive version being expressed in accordance with a predetermined syntax, the source-descriptive version comprising each item in a group consisting of (the text string, a name of a source of the text string, and a unique identifier of the text string); wherein the unique identifier uniquely identifies the text string, from among a plurality of text strings in said source; automatically parsing the first web page to identify at least one item in the group; and automatically preparing the second web page, by adding to the first web page at least one of (a tag and an attribute), to hide from display in a browser the name of the source and the unique identifier of the text string; wherein the second web page comprises said text string, said name of the source, and said unique identifier of the text string. 16. The method of claim 15 wherein: the source of the text string is a file; and within at least one of said first web page and said second web page, the name of the file is concatenated to the text string by use of at least one predetermined character. | 0.529863 |
1. A method for an abstract syntax tree (AST) builder, the method comprising: (a) utilizing an input string based on a document being analyzed; (b) launching a recognizer process configured to process the input string and to identify lexemes in the input string so as to accept or to reject grammatical structure of the input string; (c) generating a plurality of Left Recursive Earley (LRE) states and transitions between the LRE states by the recognizer process based on the lexemes, and entering the LRE states and the transitions into a state set table; (d) once the LRE states and the state set table are generated, parsing complete elements from a latest LRE state, wherein an order of elements within the state is preserved; (e) discarding an accepting element, when the extracted elements contain the accepting element, and when there are more lexemes left in the input string; (f) computing a parent-sibling relationship between a next element and an element currently located at a top of a stack; (g) pushing the next element onto the stack, when the stack is empty; (h) pushing the next element onto the stack, when the next element is a right sibling of the element currently located at a top of a stack; (i) repeating steps (d)-(h) until there are no lexemes left in the input string; and (j) generating the AST from the state set table that corresponds to the document. | 1. A method for an abstract syntax tree (AST) builder, the method comprising: (a) utilizing an input string based on a document being analyzed; (b) launching a recognizer process configured to process the input string and to identify lexemes in the input string so as to accept or to reject grammatical structure of the input string; (c) generating a plurality of Left Recursive Earley (LRE) states and transitions between the LRE states by the recognizer process based on the lexemes, and entering the LRE states and the transitions into a state set table; (d) once the LRE states and the state set table are generated, parsing complete elements from a latest LRE state, wherein an order of elements within the state is preserved; (e) discarding an accepting element, when the extracted elements contain the accepting element, and when there are more lexemes left in the input string; (f) computing a parent-sibling relationship between a next element and an element currently located at a top of a stack; (g) pushing the next element onto the stack, when the stack is empty; (h) pushing the next element onto the stack, when the next element is a right sibling of the element currently located at a top of a stack; (i) repeating steps (d)-(h) until there are no lexemes left in the input string; and (j) generating the AST from the state set table that corresponds to the document. 5. The method of claim 1 , wherein the AST is built in parallel with the recognition process. | 0.58775 |
1. A system in communication, comprising: a processor; and a computer readable storage medium including code executed by the processor to perform operations, the operations comprising: accessing document identifiers for documents, wherein the documents include at least one value that is a member of a set of values; generating a number of posting lists, wherein each posting list is associated with a range of consecutive values within the set of values and includes document identifiers for documents including at least one value within the range of consecutive values associated with the posting list, and wherein each document identifier is associated with one value in the set of values included in the document identified by the document identifier; storing the generated posting lists, wherein the posting lists are used to process a query on a range of values within the set of values; receiving a query on a query range of values within the set of values; determining a minimum number of posting lists associated with consecutive values that together include the query range of values; merging the determined posting lists to form a merged posting list including document identifiers of documents including values within the query range; and returning the document identifiers in the merged posting list. | 1. A system in communication, comprising: a processor; and a computer readable storage medium including code executed by the processor to perform operations, the operations comprising: accessing document identifiers for documents, wherein the documents include at least one value that is a member of a set of values; generating a number of posting lists, wherein each posting list is associated with a range of consecutive values within the set of values and includes document identifiers for documents including at least one value within the range of consecutive values associated with the posting list, and wherein each document identifier is associated with one value in the set of values included in the document identified by the document identifier; storing the generated posting lists, wherein the posting lists are used to process a query on a range of values within the set of values; receiving a query on a query range of values within the set of values; determining a minimum number of posting lists associated with consecutive values that together include the query range of values; merging the determined posting lists to form a merged posting list including document identifiers of documents including values within the query range; and returning the document identifiers in the merged posting list. 7. The system of claim 1 , wherein the set of values comprises at least one of an integer and a real number. | 0.728522 |
9. The computer-readable hardware device of claim 8 , wherein the physical sports player includes a car driver and the physical sports event includes a car driving route. | 9. The computer-readable hardware device of claim 8 , wherein the physical sports player includes a car driver and the physical sports event includes a car driving route. 10. The computer-readable hardware device of claim 9 , wherein the one or more parameters include at least one parameter that identifies a driving style of the car driver. | 0.949251 |
2. An automated system, comprising: a command processing system that processes input commands; and a command execution system that executes an input command based on command processing results provided by the command processing system, wherein the command processing system evaluates consequences of executing input commands and take preventative actions for execution of input commands that could result in undesirable consequences, and wherein the command processing system, comprises: an automatic recognition system for recognizing input patterns associated with the input command; a command interpretation system to interpret input commands based on recognition results generated by the automatic recognition system; a consequence evaluation system to determine a potential consequence of executing input commands based on interpretation results generated by the command interpretation system and determine a likelihood that the potential consequences can occur; and a feedback system to perform preventative actions for executing input commands when consequence evaluation results of an input command indicate at the likelihood of the potential consequence is greater than a threshold, wherein the potential consequence is an undesirable consequence of executing the input command. | 2. An automated system, comprising: a command processing system that processes input commands; and a command execution system that executes an input command based on command processing results provided by the command processing system, wherein the command processing system evaluates consequences of executing input commands and take preventative actions for execution of input commands that could result in undesirable consequences, and wherein the command processing system, comprises: an automatic recognition system for recognizing input patterns associated with the input command; a command interpretation system to interpret input commands based on recognition results generated by the automatic recognition system; a consequence evaluation system to determine a potential consequence of executing input commands based on interpretation results generated by the command interpretation system and determine a likelihood that the potential consequences can occur; and a feedback system to perform preventative actions for executing input commands when consequence evaluation results of an input command indicate at the likelihood of the potential consequence is greater than a threshold, wherein the potential consequence is an undesirable consequence of executing the input command. 11. The system of claim 2 , wherein the automatic recognition system comprises a user state recognition system. | 0.541514 |
18. The non-transitory computer readable storage medium of claim 17 , wherein the method further comprises determining a context score based on the retrieved information; and wherein the combined prospect score is based at least partly on the context score in addition to the likelihood that the insurance offer will be made and the likelihood that the prospect will accept the insurance offer. | 18. The non-transitory computer readable storage medium of claim 17 , wherein the method further comprises determining a context score based on the retrieved information; and wherein the combined prospect score is based at least partly on the context score in addition to the likelihood that the insurance offer will be made and the likelihood that the prospect will accept the insurance offer. 19. The non-transitory computer readable storage medium of claim 18 , wherein the context score is based on retrieved information representative of a timeliness of the insurance offer and retrieved information representative of whether a prospect attitude is appropriate for making the insurance offer to the prospect. | 0.832197 |
1. In a computer system including a display screen comprising a result display area of a graphical user interface, a computer-implemented method of receiving user input for changing the amount of data displayed in the result display area of the graphical user interface, the method comprising: retrieving data from a data source, the data comprising a plurality of text elements; displaying, in the result display area, a plurality of text display blocks each comprising at least a portion of the text of each of the plurality of text elements, each text display block having a size individually determined based on the amount of data to be displayed in the block; displaying in a control area of the graphical user interface distinguished from the result display area, a single control for adjusting the sizes of the displayed plurality of text display blocks; and in response to user input moving the control in the control area: adjusting the size of each of the displayed plurality of text display blocks, wherein at least two of the text display blocks have different amounts of data and are displayed having different sizes, and wherein the adjusting is dynamic, visible and concurrent with moving the control. | 1. In a computer system including a display screen comprising a result display area of a graphical user interface, a computer-implemented method of receiving user input for changing the amount of data displayed in the result display area of the graphical user interface, the method comprising: retrieving data from a data source, the data comprising a plurality of text elements; displaying, in the result display area, a plurality of text display blocks each comprising at least a portion of the text of each of the plurality of text elements, each text display block having a size individually determined based on the amount of data to be displayed in the block; displaying in a control area of the graphical user interface distinguished from the result display area, a single control for adjusting the sizes of the displayed plurality of text display blocks; and in response to user input moving the control in the control area: adjusting the size of each of the displayed plurality of text display blocks, wherein at least two of the text display blocks have different amounts of data and are displayed having different sizes, and wherein the adjusting is dynamic, visible and concurrent with moving the control. 3. The method of claim 1 , wherein the step of adjusting the size of each of the displayed plurality of text display blocks comprising the portions of the text displayed is a sentence by sentence adjustment. | 0.707018 |
1. A method for performing speech to text conversion, the method comprising: receiving, via a processor, an audio data and a video data of a user while the user is speaking; generating, via the processor, a first raw text based on the audio data using a language model and an acoustic model in conjunction with a Hidden Markov Model; generating, via the processor, a second raw text based on the video data using Karhunen-Loeve Transform (KLT) in conjunction with the Hidden Markov Model; determining, via the processor, a plurality of errors by comparing the first raw text and the second raw text, wherein determining the one or more errors comprises comparing a sequence of phonemes in the first raw text with a corresponding sequence of visemes in the second raw text for one or more mismatches; correcting, via the processor, the plurality of errors by applying one or more rules, wherein the one or more rules employ at least one of a domain specific word database, a context of conversation, and a prior communication history; generating a correction to an error of the plurality of errors; automatically generating a rule based on the error, the correction and training; and applying the one or more rules to another error of the plurality of errors to obtain a final text. | 1. A method for performing speech to text conversion, the method comprising: receiving, via a processor, an audio data and a video data of a user while the user is speaking; generating, via the processor, a first raw text based on the audio data using a language model and an acoustic model in conjunction with a Hidden Markov Model; generating, via the processor, a second raw text based on the video data using Karhunen-Loeve Transform (KLT) in conjunction with the Hidden Markov Model; determining, via the processor, a plurality of errors by comparing the first raw text and the second raw text, wherein determining the one or more errors comprises comparing a sequence of phonemes in the first raw text with a corresponding sequence of visemes in the second raw text for one or more mismatches; correcting, via the processor, the plurality of errors by applying one or more rules, wherein the one or more rules employ at least one of a domain specific word database, a context of conversation, and a prior communication history; generating a correction to an error of the plurality of errors; automatically generating a rule based on the error, the correction and training; and applying the one or more rules to another error of the plurality of errors to obtain a final text. 8. The method of claim 1 , further comprising generating a final text based on the first raw text or the second raw text, and the correction. | 0.594073 |
17. A computer implemented method for processing database content, the method comprising the steps of: receiving one or more data objects associated with a database at one or more remote computers; parsing one or more source documents to identify at least one term based on one or more predetermined rules; identifying content for the at least one term, wherein at least a portion of the identified content is stored in the database; linking the content with the at least one term; and wherein the one or more data objects associated with the database provide a representation of at least a portion of the database at the one or more remote computers; and wherein the linked content is displayed on a user interface based upon a user interaction with at least a portion of the one or more source documents. | 17. A computer implemented method for processing database content, the method comprising the steps of: receiving one or more data objects associated with a database at one or more remote computers; parsing one or more source documents to identify at least one term based on one or more predetermined rules; identifying content for the at least one term, wherein at least a portion of the identified content is stored in the database; linking the content with the at least one term; and wherein the one or more data objects associated with the database provide a representation of at least a portion of the database at the one or more remote computers; and wherein the linked content is displayed on a user interface based upon a user interaction with at least a portion of the one or more source documents. 22. The method of claim 17 , wherein one or more of the predetermined rules are based on frequency of a term within a source document. | 0.51626 |
1. A method of merging search results, comprising: identifying a query from a user; splitting the query into sub-queries; for each of the sub-queries, determining a user importance value for said each sub-query to quantify how important said each sub-query is to the user relative to how important the others of the sub-queries are to the user, executing said each sub-query to obtain a search result for said each sub-query, and using the user importance value determined for said each sub-query to assign a user relevance score to the search result obtained for said each sub-query; and combining the search results for the sub-queries based on the user relevance scores assigned to the search results to obtain merged search results; and wherein: the execution of each of the sub-queries includes identifying a multitude of search results for at least one of the sub-queries; the combining includes grouping said multitude of search results into a plurality of clusters, and computing a relevance score for each of said clusters, wherein each cluster represents a high level entity; the determining a user importance value for said each sub-query includes identifying one of the sub-queries as a primary focus, and identifying another of the sub-queries as providing context, computing a probability p(Q) of each of the sub-queries, and computing information content of each of the sub-queries as log p(Q); and the combining the search results further includes, once the information content of the sub-queries are computed, merging the search results. | 1. A method of merging search results, comprising: identifying a query from a user; splitting the query into sub-queries; for each of the sub-queries, determining a user importance value for said each sub-query to quantify how important said each sub-query is to the user relative to how important the others of the sub-queries are to the user, executing said each sub-query to obtain a search result for said each sub-query, and using the user importance value determined for said each sub-query to assign a user relevance score to the search result obtained for said each sub-query; and combining the search results for the sub-queries based on the user relevance scores assigned to the search results to obtain merged search results; and wherein: the execution of each of the sub-queries includes identifying a multitude of search results for at least one of the sub-queries; the combining includes grouping said multitude of search results into a plurality of clusters, and computing a relevance score for each of said clusters, wherein each cluster represents a high level entity; the determining a user importance value for said each sub-query includes identifying one of the sub-queries as a primary focus, and identifying another of the sub-queries as providing context, computing a probability p(Q) of each of the sub-queries, and computing information content of each of the sub-queries as log p(Q); and the combining the search results further includes, once the information content of the sub-queries are computed, merging the search results. 6. The method according to claim 1 , wherein: said sub-queries include a first sub-query and a second sub-query; the execution of each of the sub-queries includes executing the first sub-query to identify a plurality of first class entities, and executing the second sub-query to identify multitude of second class entities, each of the second class entities being associated, according to a defined criteria, with one of the first class entities; and the combining includes clustering the second class entities into the plurality of clusters based on the first class entity to which each of the second class entities belongs. | 0.613343 |
8. A system for culture mapping and intelligence, comprising a computer having a microprocessor in communication with a selected data source for receiving data including unstructured words and phrases collected from a plurality of user account profiles associated with at least one networked computer, generating a list of monitored user accounts based on a user query relative to a topic of interest, and processing the unstructured words and phrases data collected from the monitored user accounts using semiotic analysis to associate a behavior archetype based on the user account profiles; and a display in communication with the computer that maps the user account on a cultural segmentation map relative to first and second behavior continuums based on a relationship of user to self and a relationship of user to society. | 8. A system for culture mapping and intelligence, comprising a computer having a microprocessor in communication with a selected data source for receiving data including unstructured words and phrases collected from a plurality of user account profiles associated with at least one networked computer, generating a list of monitored user accounts based on a user query relative to a topic of interest, and processing the unstructured words and phrases data collected from the monitored user accounts using semiotic analysis to associate a behavior archetype based on the user account profiles; and a display in communication with the computer that maps the user account on a cultural segmentation map relative to first and second behavior continuums based on a relationship of user to self and a relationship of user to society. 11. The system of claim 8 wherein the computer comprises a hand-held mobile device. | 0.690217 |
1. A computer-implemented method, comprising: receiving a database request having a projection operation for all of a plurality of columns in one or more tables, wherein the projection operation comprises a SELECT statement having a column list that includes having (i) a shorthand that specifies all of the plurality of columns and (ii) a substitute clause that specifies a column from the plurality of columns and an expression, wherein the shorthand comprises a wildcard that expands to specify all of the plurality of columns, the shorthand being less than a plurality of column references to the plurality of columns; responsive to the request, retrieving one or more data records having the plurality of columns including the specified column; evaluating the specified expression to generate an expression result corresponding to a respective data record of the one or more data records; and generating, by operation of one or more computer processors, a result set comprised of the one of more data records having the plurality of columns, such that, for the respective data record, a value for the specified column is replaced with the corresponding expression result, wherein a number of columns in the result set is the same as the number of the plurality of columns in the one or more tables and specified by the shorthand. | 1. A computer-implemented method, comprising: receiving a database request having a projection operation for all of a plurality of columns in one or more tables, wherein the projection operation comprises a SELECT statement having a column list that includes having (i) a shorthand that specifies all of the plurality of columns and (ii) a substitute clause that specifies a column from the plurality of columns and an expression, wherein the shorthand comprises a wildcard that expands to specify all of the plurality of columns, the shorthand being less than a plurality of column references to the plurality of columns; responsive to the request, retrieving one or more data records having the plurality of columns including the specified column; evaluating the specified expression to generate an expression result corresponding to a respective data record of the one or more data records; and generating, by operation of one or more computer processors, a result set comprised of the one of more data records having the plurality of columns, such that, for the respective data record, a value for the specified column is replaced with the corresponding expression result, wherein a number of columns in the result set is the same as the number of the plurality of columns in the one or more tables and specified by the shorthand. 4. The computer-implemented method of claim 1 , wherein the expression comprises a function having a scalar value and based on at least one column reference. | 0.842315 |
1. A method in a computing device for determining importance of documents with links between documents, the method comprising: generating transition probabilities of transitioning between pairs of source and target documents based on a determination of information available through each target document of a source document, each source document having one or more links to target documents of that source document, the transition probability for transitioning from a source document to a target document is based on the number of links on that target document and the total number of links on the target documents of that source document; storing the generated transition probabilities in a transition probability matrix; calculating importance of documents based on a stationary distribution of the generated transition probabilities stored in the transition probability matrix, the stationary distribution including stationary probabilities of visiting documents; and storing the calculated importance of the documents. | 1. A method in a computing device for determining importance of documents with links between documents, the method comprising: generating transition probabilities of transitioning between pairs of source and target documents based on a determination of information available through each target document of a source document, each source document having one or more links to target documents of that source document, the transition probability for transitioning from a source document to a target document is based on the number of links on that target document and the total number of links on the target documents of that source document; storing the generated transition probabilities in a transition probability matrix; calculating importance of documents based on a stationary distribution of the generated transition probabilities stored in the transition probability matrix, the stationary distribution including stationary probabilities of visiting documents; and storing the calculated importance of the documents. 12. The method of claim 1 wherein a transition probability of transitioning between a source document and a target document is based on number of links on documents that are a look-ahead distance from the source document, the look-ahead distance being based on number of links needed to transition from a source document to a target document. | 0.567871 |
13. The method of claim 12 wherein the impact that additional reviews on the one or more external review websites would have for the first entity is modeled at least in part by using target distributions, wherein the target distributions indicate, for at least the first external review website and the second external review website, a respective first and second number of reviews the first entity should have on the respective first and second external review websites. | 13. The method of claim 12 wherein the impact that additional reviews on the one or more external review websites would have for the first entity is modeled at least in part by using target distributions, wherein the target distributions indicate, for at least the first external review website and the second external review website, a respective first and second number of reviews the first entity should have on the respective first and second external review websites. 14. The method of claim 13 wherein the first and second number of reviews are expressed as percentages of a total volume of reviews. | 0.962064 |
1. A method of controlling a group chat, the method comprising: controlling, by a controller, a display unit to display a group chatting window for the group chat, if a request of a user of a portable device for the group chat is detected through an input unit; detecting, by the controller, a request for an extraction of a dialog for at least one certain conversation partner of conversation partners in the group chat; if the request for the extraction of the dialog is detected, extracting, by the controller, the dialog of the at least one certain conversation partner from one or more dialogs in the group chat; and controlling, by the controller, the display unit to display the extracted dialog on a sub-chatting window, wherein the controller extracts automatically the dialog of the at least one certain conversation partner during the group chatting, and controls the display unit to display the dialog on the sub-chatting window. | 1. A method of controlling a group chat, the method comprising: controlling, by a controller, a display unit to display a group chatting window for the group chat, if a request of a user of a portable device for the group chat is detected through an input unit; detecting, by the controller, a request for an extraction of a dialog for at least one certain conversation partner of conversation partners in the group chat; if the request for the extraction of the dialog is detected, extracting, by the controller, the dialog of the at least one certain conversation partner from one or more dialogs in the group chat; and controlling, by the controller, the display unit to display the extracted dialog on a sub-chatting window, wherein the controller extracts automatically the dialog of the at least one certain conversation partner during the group chatting, and controls the display unit to display the dialog on the sub-chatting window. 3. The method of claim 1 , wherein the sub-chatting window is displayed according to at least one effect of a pop-up, a screen division, and an overlay. | 0.639866 |
1. A computer-implemented method, comprising: at a portable electronic device with a keyboard: receiving a sequence of input characters from the keyboard, wherein the keyboard has a predefined layout with a plurality of keys, each respective key in the plurality of keys corresponding to a single respective character, each respective key in the predefined layout having one or more neighbor keys; generating a set of strings from at least a subset of the sequence of input characters, the set of strings comprising permutations of respective input characters in the subset of the sequence and characters corresponding to neighbor keys of the keys corresponding to the respective input characters on the layout of the keyboard, wherein for each permutation: a respective character at a respective position in the permutation is either a corresponding input character at a corresponding position in the sequence of input characters or a character corresponding to an adjacent, neighbor key of the key corresponding to the corresponding input character in the predefined layout; and, after generating the set of strings: identifying in a dictionary one or more candidate words, each candidate word having a string in the set of strings as a prefix; scoring the candidate words; selecting a subset of the candidate words based on predefined criteria; and presenting the subset of the candidate words. | 1. A computer-implemented method, comprising: at a portable electronic device with a keyboard: receiving a sequence of input characters from the keyboard, wherein the keyboard has a predefined layout with a plurality of keys, each respective key in the plurality of keys corresponding to a single respective character, each respective key in the predefined layout having one or more neighbor keys; generating a set of strings from at least a subset of the sequence of input characters, the set of strings comprising permutations of respective input characters in the subset of the sequence and characters corresponding to neighbor keys of the keys corresponding to the respective input characters on the layout of the keyboard, wherein for each permutation: a respective character at a respective position in the permutation is either a corresponding input character at a corresponding position in the sequence of input characters or a character corresponding to an adjacent, neighbor key of the key corresponding to the corresponding input character in the predefined layout; and, after generating the set of strings: identifying in a dictionary one or more candidate words, each candidate word having a string in the set of strings as a prefix; scoring the candidate words; selecting a subset of the candidate words based on predefined criteria; and presenting the subset of the candidate words. 5. The method of claim 1 , wherein the keyboard comprises a virtual keyboard. | 0.580556 |
6. The method of claim 1 , wherein the determination of the third likelihood score is based on a third model, wherein the third model comprises a garbage state. | 6. The method of claim 1 , wherein the determination of the third likelihood score is based on a third model, wherein the third model comprises a garbage state. 7. The method of claim 6 , further comprising determining, by the one or more processors, a second score based on the third likelihood score. | 0.956254 |
1. A computer-implemented method for implementing regular expression matching using ternary content-addressable memory devices, comprising: receiving a set of regular expressions that specify characters to be extracted from data packets; constructing a deterministic finite automaton from the set of regular expressions; building a state transition table for each node of the deterministic finite automaton, the table having an input field having a fixed number of bits for encoding characters to be extracted from data packets, by constructing a space reduction graph from the deterministic finite automaton, where vertices of the graph represent a distinct state of the automaton and weight assigned to each edge of the graph is a number of common transitions between two connected states; trimming away edges in the graph having a weight below a predefined threshold; computing a deferment forest by finding a maximum weight spanning forest for the space reduction graph; and assigning identifiers of source states and destination states for states of the deferment forest; combining the state transition tables into a single lookup table; instantiating the lookup table in a ternary content-addressable memory device, wherein assigning identifiers further comprises constructing an assignment tree by adding a virtual root node whose children are root nodes of all deferment trees comprising the deferment forest; assigning nonzero binary identifiers to each node in the assignment tree such that all siblings have the same identifier; setting source state identifiers for each node in the assignment tree such that a source state identifier of a given node is set to a concatenation of the binary identifiers assigned to the given node and its parent nodes; identifying longest source state identifier from amongst the nodes in the assignment tree and padding remaining source state identifiers with trailing wildcard bits; and setting destination state identifiers for each node in the assignment tree such that a destination state identifier of a given node is set to corresponding source state identifier for the given node with trailing wildcard bits replaced by zeros. | 1. A computer-implemented method for implementing regular expression matching using ternary content-addressable memory devices, comprising: receiving a set of regular expressions that specify characters to be extracted from data packets; constructing a deterministic finite automaton from the set of regular expressions; building a state transition table for each node of the deterministic finite automaton, the table having an input field having a fixed number of bits for encoding characters to be extracted from data packets, by constructing a space reduction graph from the deterministic finite automaton, where vertices of the graph represent a distinct state of the automaton and weight assigned to each edge of the graph is a number of common transitions between two connected states; trimming away edges in the graph having a weight below a predefined threshold; computing a deferment forest by finding a maximum weight spanning forest for the space reduction graph; and assigning identifiers of source states and destination states for states of the deferment forest; combining the state transition tables into a single lookup table; instantiating the lookup table in a ternary content-addressable memory device, wherein assigning identifiers further comprises constructing an assignment tree by adding a virtual root node whose children are root nodes of all deferment trees comprising the deferment forest; assigning nonzero binary identifiers to each node in the assignment tree such that all siblings have the same identifier; setting source state identifiers for each node in the assignment tree such that a source state identifier of a given node is set to a concatenation of the binary identifiers assigned to the given node and its parent nodes; identifying longest source state identifier from amongst the nodes in the assignment tree and padding remaining source state identifiers with trailing wildcard bits; and setting destination state identifiers for each node in the assignment tree such that a destination state identifier of a given node is set to corresponding source state identifier for the given node with trailing wildcard bits replaced by zeros. 8. The method of claim 1 further comprises modifying the lookup table so that the input field is enlarged to accommodate multiple sub-fields, where each sub-field having the fixed number of bits, and the decision includes an identifier for a decision state and a stride length indicating a number of characters consumed in a table lookup. | 0.50043 |
1. A computerized method for optimizing name search results for a computer user comprising: (a) creating at a computer for a name database indices comprising: (i) a phonetic index with terms generated from application of at least one phonetic algorithm to first names and to last names in said database; (ii) a nickname index with terms generated from application of at least one nickname algorithm to first names in said database; (b) creating at said computer for said name database a misspelling index with keys for finding names in said database by applying a misspelling algorithm to first names and to last names wherein the algorithm: (i) alphanumerically sorts the letters in said first names and last names; (ii) generates a first key for each of said first names and said last names comprising letters for said first name or last name in alphanumeric sorted order; and (iii) removes each letter of said first name or last name in alphanumeric sorted order to generate additional keys comprising said first key with said letters removed from said first key; (c) receiving at said computer a search request comprising a first name and a last name; (d) receiving at said computer a candidate number of names from said database; (e) creating at said computer a search results set by adding names to said search results set for said first name and said last name up to said candidate number of names according to the following steps: (i) searching said name database for an exact match of said first name and said last name; (ii) searching said name database for names that have all words from said last name and said first name but not in said search results set; (iii) searching said name database for names that have all words from said last name and a fuzzy version of said first name using said phonetic, nickname, and misspelling indices but not in said search results set; (iv) searching said name database for names that have all words from said first name and a fuzzy version of said last name using said phonetic and misspelling indices but not in said search results set; (v) searching said name database for names that have fuzzy versions of said first name and said last name using said phonetic, misspelling, and nickname indices but not in said search results set; (vi) ranking intermediate results at each step (i)-(v) and eliminating a plurality of names from said search results set according to said rankings for said names; and (f) presenting to said computer user on a computer display names from said search results set up to said candidate number of names. | 1. A computerized method for optimizing name search results for a computer user comprising: (a) creating at a computer for a name database indices comprising: (i) a phonetic index with terms generated from application of at least one phonetic algorithm to first names and to last names in said database; (ii) a nickname index with terms generated from application of at least one nickname algorithm to first names in said database; (b) creating at said computer for said name database a misspelling index with keys for finding names in said database by applying a misspelling algorithm to first names and to last names wherein the algorithm: (i) alphanumerically sorts the letters in said first names and last names; (ii) generates a first key for each of said first names and said last names comprising letters for said first name or last name in alphanumeric sorted order; and (iii) removes each letter of said first name or last name in alphanumeric sorted order to generate additional keys comprising said first key with said letters removed from said first key; (c) receiving at said computer a search request comprising a first name and a last name; (d) receiving at said computer a candidate number of names from said database; (e) creating at said computer a search results set by adding names to said search results set for said first name and said last name up to said candidate number of names according to the following steps: (i) searching said name database for an exact match of said first name and said last name; (ii) searching said name database for names that have all words from said last name and said first name but not in said search results set; (iii) searching said name database for names that have all words from said last name and a fuzzy version of said first name using said phonetic, nickname, and misspelling indices but not in said search results set; (iv) searching said name database for names that have all words from said first name and a fuzzy version of said last name using said phonetic and misspelling indices but not in said search results set; (v) searching said name database for names that have fuzzy versions of said first name and said last name using said phonetic, misspelling, and nickname indices but not in said search results set; (vi) ranking intermediate results at each step (i)-(v) and eliminating a plurality of names from said search results set according to said rankings for said names; and (f) presenting to said computer user on a computer display names from said search results set up to said candidate number of names. 4. The method of claim 1 wherein said nicknames algorithm comprises the following steps: (a) preparing a text file of formal names and nicknames; (b) inverting said file such that nicknames map to formal names and to nicknames for said formal names; and (c) generating multiple keys for first names for all possible nicknames and formal names related to said first names. | 0.50225 |
1. A method comprising: receiving first recognized text corresponding to first speech input from a user; displaying a first tab of a user interface, the first tab corresponding to a first application, wherein the first tab comprises the first recognized text with an icon associated with the first application; receiving second recognized text corresponding to second speech input from the user; displaying, responsive to the first speech input and the second speech input, a second tab of the user interface, the second tab corresponding to a second application, wherein the second application is selected based on the second speech input; receiving third recognized text corresponding to third speech input from the user; and displaying the first tab of the user interface, wherein the first tab further comprises the second recognized text with an icon associated with the second application and the third recognized text with the icon associated with the first application. | 1. A method comprising: receiving first recognized text corresponding to first speech input from a user; displaying a first tab of a user interface, the first tab corresponding to a first application, wherein the first tab comprises the first recognized text with an icon associated with the first application; receiving second recognized text corresponding to second speech input from the user; displaying, responsive to the first speech input and the second speech input, a second tab of the user interface, the second tab corresponding to a second application, wherein the second application is selected based on the second speech input; receiving third recognized text corresponding to third speech input from the user; and displaying the first tab of the user interface, wherein the first tab further comprises the second recognized text with an icon associated with the second application and the third recognized text with the icon associated with the first application. 2. The method of claim 1 , wherein the first application comprises a text messaging application and the second application comprises an email application, a social media application, a weather application, or a map application. | 0.650771 |
6. The method as claimed in claim 4 , wherein the comparing step comprises the sub-steps of: segmenting the handwritten annotations in the at least one database into segmented strokes and mapping the segmented strokes into a first sequence of feature representations; segmenting the handwritten search query into segmented strokes and mapping the segmented strokes into a second sequence of feature representations; performing an edit distance calculation between the first sequence of feature representations and the second sequence of feature representations; and, determining matches between the handwritten annotations in the at least one database and the handwritten search query by locating the smallest values from the edit distance calculation. | 6. The method as claimed in claim 4 , wherein the comparing step comprises the sub-steps of: segmenting the handwritten annotations in the at least one database into segmented strokes and mapping the segmented strokes into a first sequence of feature representations; segmenting the handwritten search query into segmented strokes and mapping the segmented strokes into a second sequence of feature representations; performing an edit distance calculation between the first sequence of feature representations and the second sequence of feature representations; and, determining matches between the handwritten annotations in the at least one database and the handwritten search query by locating the smallest values from the edit distance calculation. 10. The method as claimed in claim 6 , wherein a weighting factor is applied to the vertical-axis (Y) coordinates of the feature representations. | 0.578866 |
21. A computer-implemented query processing method in which the query is interpreted based on a set of formally represented knowledge items stored in a knowledge base, wherein each formally represented knowledge item further comprises an item that has been edited or analyzed, the formally represented knowledge further comprising one or more synsets wherein each synset contains a group of terms that have a same meaning, one or more taxonomies wherein each taxonomy contains one or more synsets in a subject matter area that are organized from a synset having a general meaning to a synset having a specific meaning, one or more ontologies wherein each ontology contains one or more synsets associated with an area of interest and one or more facets wherein each facet is associated with a particular ontology and wherein a piece of content is associated with the facet when the piece of content contains the one or more synsets associated with the facet, the method comprising: receiving a query containing one or more query terms; determining a language of the query; identifying one or more items in the knowledge base based on the language of the query that match the one or more terms in the query; performing a raw search of the one or more terms of the query against a corpus of pieces of content to retrieve a raw search results set containing one or more pieces of content with a term that matches a term of the query; selecting an interpretation of a concept based on the query and the retrieved pieces of content; modifying the query to generate an expanded query that includes the identified knowledge base items if the raw search results set match one or more of the identified knowledge base items; selecting one or more facets that match the interpretation of the expanded query based on the corpus of pieces of content; and performing a concept search that compares the one or more query terms against the expanded query and the selected one or more facets against a corpus of documents to display one or more facets whose synsets are matched by the query terms. | 21. A computer-implemented query processing method in which the query is interpreted based on a set of formally represented knowledge items stored in a knowledge base, wherein each formally represented knowledge item further comprises an item that has been edited or analyzed, the formally represented knowledge further comprising one or more synsets wherein each synset contains a group of terms that have a same meaning, one or more taxonomies wherein each taxonomy contains one or more synsets in a subject matter area that are organized from a synset having a general meaning to a synset having a specific meaning, one or more ontologies wherein each ontology contains one or more synsets associated with an area of interest and one or more facets wherein each facet is associated with a particular ontology and wherein a piece of content is associated with the facet when the piece of content contains the one or more synsets associated with the facet, the method comprising: receiving a query containing one or more query terms; determining a language of the query; identifying one or more items in the knowledge base based on the language of the query that match the one or more terms in the query; performing a raw search of the one or more terms of the query against a corpus of pieces of content to retrieve a raw search results set containing one or more pieces of content with a term that matches a term of the query; selecting an interpretation of a concept based on the query and the retrieved pieces of content; modifying the query to generate an expanded query that includes the identified knowledge base items if the raw search results set match one or more of the identified knowledge base items; selecting one or more facets that match the interpretation of the expanded query based on the corpus of pieces of content; and performing a concept search that compares the one or more query terms against the expanded query and the selected one or more facets against a corpus of documents to display one or more facets whose synsets are matched by the query terms. 23. The method of claim 21 , wherein determining the language of the query further comprises one of determining the language of the query based on an explicit user preference, and determining the language of the query based on comparing the languages of pieces of content that contain the query terms. | 0.5 |
1. A computer-implemented method of processing messages, comprising: at a client computer: receiving a plurality of messages directed to a user, each message having a unique message identifier; associating each of the plurality of messages with a respective conversation, each conversation having a respective conversation identifier, wherein each conversation comprises a set of one or more messages sharing a common set of characteristics that meet first predefined criteria and the respective conversation identifier is distinct from a subject reference of the one or more messages in the respective conversation; associating with each conversation a set of senders of messages included in the conversation; and displaying a list of conversations in an order determined in accordance with second predefined criteria, each conversation being represented as a single item in the list, wherein a plurality of conversations in the list of conversations each include a plurality of messages that share a common set of characteristics that meet the first predefined criteria; wherein the list of conversations comprises a set of rows, each row corresponding to one of the listed conversations and including at least a sender list, a conversation topic and a date/time value, wherein the sender list of a row in the list of conversations includes identifiers of one or more senders of at least one message in the corresponding conversation, including identifiers of a plurality of the senders in the set of senders, but less than all of the senders in the set of senders, when the set of senders exceeds a predefined limit. | 1. A computer-implemented method of processing messages, comprising: at a client computer: receiving a plurality of messages directed to a user, each message having a unique message identifier; associating each of the plurality of messages with a respective conversation, each conversation having a respective conversation identifier, wherein each conversation comprises a set of one or more messages sharing a common set of characteristics that meet first predefined criteria and the respective conversation identifier is distinct from a subject reference of the one or more messages in the respective conversation; associating with each conversation a set of senders of messages included in the conversation; and displaying a list of conversations in an order determined in accordance with second predefined criteria, each conversation being represented as a single item in the list, wherein a plurality of conversations in the list of conversations each include a plurality of messages that share a common set of characteristics that meet the first predefined criteria; wherein the list of conversations comprises a set of rows, each row corresponding to one of the listed conversations and including at least a sender list, a conversation topic and a date/time value, wherein the sender list of a row in the list of conversations includes identifiers of one or more senders of at least one message in the corresponding conversation, including identifiers of a plurality of the senders in the set of senders, but less than all of the senders in the set of senders, when the set of senders exceeds a predefined limit. 9. The method of claim 1 , wherein, when the conversation corresponding to the row includes a message sent by a first sender and one or more messages sent by a second sender, the displaying includes displaying in a first distinct format an identifier of the first sender in the sender list when the message sent by the first sender has not been viewed or marked as read by the user, and displaying in second distinct format an identifier of the second sender in the sender list when all the messages sent by the second sender have been viewed or marked as read by the user. | 0.5939 |
1. A computer-implemented system comprising: a digital processing device comprising: at least one processor, an operating system configured to perform executable instructions, a memory, and a computer program including instructions executable by the digital processing device to create a social query response application comprising: a) a software module monitoring queries from users, each query submitted to a vendor via an interactive chat feature of an external electronic communication platform, monitoring human responses to the queries, and monitoring subsequent communications conducted via the electronic communication platform until each query is resolved; b) a software module applying a first machine learning algorithm to the monitored communications to identify one or more queries susceptible to response automation; and c) a software module applying a second machine learning algorithm to the queries susceptible to response automation to identify one or more responses likely to resolve the query. | 1. A computer-implemented system comprising: a digital processing device comprising: at least one processor, an operating system configured to perform executable instructions, a memory, and a computer program including instructions executable by the digital processing device to create a social query response application comprising: a) a software module monitoring queries from users, each query submitted to a vendor via an interactive chat feature of an external electronic communication platform, monitoring human responses to the queries, and monitoring subsequent communications conducted via the electronic communication platform until each query is resolved; b) a software module applying a first machine learning algorithm to the monitored communications to identify one or more queries susceptible to response automation; and c) a software module applying a second machine learning algorithm to the queries susceptible to response automation to identify one or more responses likely to resolve the query. 3. The system of claim 1 , wherein the application further comprises: a) a software module receiving a query from a user, the query submitted to the vendor via an interactive chat feature of an external electronic communication platform; b) a software module automatically responding to the query with the identified one or more responses likely to resolve the query; c) a software module determining when the query is resolved; and d) a software module transmitting the outcome of the resolution to an enterprise software system. | 0.536136 |
6. A computer program product for implementing a method for generating a partitioned representation of a sequence of query operators in a parallel query engine, the computer program product comprising one or more hardware computer-readable storage devices having stored thereon computer-executable instructions that, when executed by one or more processors of a computing system, cause the computing system to perform the method, the method comprising: an act of accessing a sequence of operators configured to process a portion of partitioned input data in a parallel query system, the sequence of operators comprising one or more built-in operators that are part of a parallel query engine and at least one user-defined custom operator, the at least one user-defined custom operator being provided to the parallel query engine by a user and being configured for processing along with the one or more built-in operators by being configured to: poll a predecessor operator of the at least one user-defined custom operator in the sequence of operators to determine the predecessor operator's output information, the output information including (i) a number of partitions of the input data that are requestable by the at least one user-defined custom operator and (ii) one or more ordering guarantees that apply to output of the at least one user-defined custom operator; repartition the input data by adding or reducing the number of partitions of the input data during processing of the input data; and determine whether changes have occurred that affect the one or more ordering guarantees and, when changes have occurred that affect the one or more ordering guarantees, modify at least a portion of the one or more ordering guarantees that apply to the output of the at least one user-defined custom operator; an act of generating a list of partitions into which the input data has been partitioned; an act of determining a number of partitions that will be made during a re-partitioning operation at an indicated built-in operator in the sequence of operators; and an act of generating a partitioned representation of the sequence of operators, wherein the partitioned representation of the sequence of operators provides internal information regarding the processing of the input data by the indicated built-in operator, the internal information enabling processing of the input data by one of the at least one user-defined custom operator. | 6. A computer program product for implementing a method for generating a partitioned representation of a sequence of query operators in a parallel query engine, the computer program product comprising one or more hardware computer-readable storage devices having stored thereon computer-executable instructions that, when executed by one or more processors of a computing system, cause the computing system to perform the method, the method comprising: an act of accessing a sequence of operators configured to process a portion of partitioned input data in a parallel query system, the sequence of operators comprising one or more built-in operators that are part of a parallel query engine and at least one user-defined custom operator, the at least one user-defined custom operator being provided to the parallel query engine by a user and being configured for processing along with the one or more built-in operators by being configured to: poll a predecessor operator of the at least one user-defined custom operator in the sequence of operators to determine the predecessor operator's output information, the output information including (i) a number of partitions of the input data that are requestable by the at least one user-defined custom operator and (ii) one or more ordering guarantees that apply to output of the at least one user-defined custom operator; repartition the input data by adding or reducing the number of partitions of the input data during processing of the input data; and determine whether changes have occurred that affect the one or more ordering guarantees and, when changes have occurred that affect the one or more ordering guarantees, modify at least a portion of the one or more ordering guarantees that apply to the output of the at least one user-defined custom operator; an act of generating a list of partitions into which the input data has been partitioned; an act of determining a number of partitions that will be made during a re-partitioning operation at an indicated built-in operator in the sequence of operators; and an act of generating a partitioned representation of the sequence of operators, wherein the partitioned representation of the sequence of operators provides internal information regarding the processing of the input data by the indicated built-in operator, the internal information enabling processing of the input data by one of the at least one user-defined custom operator. 10. The computer program product of claim 6 , wherein the partitioned representation provides an indication of those characteristics that are necessary for operators to be efficiently executed. | 0.520825 |
10. The method of claim 9 further comprising: performing the voice matching operation between the probe and the prototypes to obtain probe-prototype match scores; selecting first templates from the biometric corpus; performing the voice matching operation between the first templates and the prototypes to obtain template-prototype match scores; and selecting as the speaker-identity candidates one or more second templates corresponding to template-prototype match scores that are nearest to the probe-prototype match scores based on a nearness measurement. | 10. The method of claim 9 further comprising: performing the voice matching operation between the probe and the prototypes to obtain probe-prototype match scores; selecting first templates from the biometric corpus; performing the voice matching operation between the first templates and the prototypes to obtain template-prototype match scores; and selecting as the speaker-identity candidates one or more second templates corresponding to template-prototype match scores that are nearest to the probe-prototype match scores based on a nearness measurement. 11. The method of claim 10 furthering comprising: clustering the probe match scores until probe match scores in each of K clusters have a deviation less than about ten times a deviation in the probe match scores; and selecting templates that belong to clusters that have probe match scores greater than M as the first templates. | 0.847229 |
7. A message server configured to route a speech message to at least one recipient in a communication network, the message server comprising a processing circuit and a memory circuit containing computer program instructions for execution by the processing circuit, the computer program instructions comprising instructions for: receiving the speech message sent from a user equipment in audio form when a sending user has spoken the speech message into the user equipment; obtaining a text version created by speech recognition of the received speech message; obtaining contextual information comprising at least one contextual factor regarding the sending user; identifying the at least one recipient based on the obtained text version; routing the speech message to the identified at least one recipient; and processing the received speech message based on the contextual information regarding the sending user; wherein the memory circuit further comprises programming instructions for processing the received speech message by modifying the received speech message by adding information deduced by analysis of the obtained text version and the contextual information. | 7. A message server configured to route a speech message to at least one recipient in a communication network, the message server comprising a processing circuit and a memory circuit containing computer program instructions for execution by the processing circuit, the computer program instructions comprising instructions for: receiving the speech message sent from a user equipment in audio form when a sending user has spoken the speech message into the user equipment; obtaining a text version created by speech recognition of the received speech message; obtaining contextual information comprising at least one contextual factor regarding the sending user; identifying the at least one recipient based on the obtained text version; routing the speech message to the identified at least one recipient; and processing the received speech message based on the contextual information regarding the sending user; wherein the memory circuit further comprises programming instructions for processing the received speech message by modifying the received speech message by adding information deduced by analysis of the obtained text version and the contextual information. 10. The message server of claim 7 , wherein the memory circuit comprises programming instructions for obtaining the contextual information from any of: meta data received with the speech message, user information that has been pre-configured in the message server, and user information maintained by another node or service in the communication network. | 0.5 |
10. A system for performing multi-objective asset optimization and decision-making using predictive modeling, comprising: a processor; an asset in communication with the processor, the asset comprising a physical machine; and a process manager application implemented by the processor, the process manager application performing: building at least two predictive models for the asset, comprising: categorizing operational historical data of the asset that is retrieved from a storage device, the operation historical data categorized by at least one of: controllable variables; uncontrollable variables; output objectives; and constraints; selecting at least two output objectives or constraints; and identifying at least one controllable or uncontrollable variable suitable for achieving the at least two output objectives or constraints; inputting the at least one controllable or uncontrollable variable to each of the at least two predictive models; validating each predictive model; if results of the validating indicate a confidence level above a specified threshold, applying a live data stream of inputs from the asset to the predictive models; if results of the validating indicate a confidence level at or below a specified threshold, selecting at least one alternative controllable or uncontrollable variable for input to the predictive models; performing multi-objective optimization using the predictive models, comprising: specifying search constraints, comprising: upper and lower bounds for each input variable; and tolerance levels representing a range of values for achieving optimal output objectives, and constraints; applying a multi-objective optimization algorithm; and generating a Pareto Frontier, the Pareto Frontier including optimal input-output vectors; using results of the multi-objective asset optimization, selecting, from the Pareto Frontier, a Pareto optimal input-output vector for deployment to the asset, the Pareto optimal input-output vector specifying an optimal operational state for the asset; and re-configuring the asset using the Pareto optimal input-output vector to realize the optimal operational state. | 10. A system for performing multi-objective asset optimization and decision-making using predictive modeling, comprising: a processor; an asset in communication with the processor, the asset comprising a physical machine; and a process manager application implemented by the processor, the process manager application performing: building at least two predictive models for the asset, comprising: categorizing operational historical data of the asset that is retrieved from a storage device, the operation historical data categorized by at least one of: controllable variables; uncontrollable variables; output objectives; and constraints; selecting at least two output objectives or constraints; and identifying at least one controllable or uncontrollable variable suitable for achieving the at least two output objectives or constraints; inputting the at least one controllable or uncontrollable variable to each of the at least two predictive models; validating each predictive model; if results of the validating indicate a confidence level above a specified threshold, applying a live data stream of inputs from the asset to the predictive models; if results of the validating indicate a confidence level at or below a specified threshold, selecting at least one alternative controllable or uncontrollable variable for input to the predictive models; performing multi-objective optimization using the predictive models, comprising: specifying search constraints, comprising: upper and lower bounds for each input variable; and tolerance levels representing a range of values for achieving optimal output objectives, and constraints; applying a multi-objective optimization algorithm; and generating a Pareto Frontier, the Pareto Frontier including optimal input-output vectors; using results of the multi-objective asset optimization, selecting, from the Pareto Frontier, a Pareto optimal input-output vector for deployment to the asset, the Pareto optimal input-output vector specifying an optimal operational state for the asset; and re-configuring the asset using the Pareto optimal input-output vector to realize the optimal operational state. 16. The system of claim 10 , wherein the multi-objective optimization algorithm is at least one of: an evolutionary algorithm; a gradient-based algorithm; a hybrid algorithm; and Pareto Frontier generator. | 0.822414 |
11. A method for the voice-controlled selection of a media file stored on a data storage unit, the data storage unit including a plurality of media files, the media files including respective file identification data, the method comprising: receiving voice data indicative of selection of the media file from among the media files, and supplying the voice data to a speech recognition unit; extracting, by a processor, a first language identification tag included in the respective file identification data of each of the media files, the first language identification tag indicating a first language associated with a first data field of the respective file identification data, where the respective file identification data is in a header section of each of the respective media files; extracting, by the processor, a second language identification tag included in the respective file identification data of each of the media file, the second language identification tag indicating a second language associated with a second data field of the respective file identification data in the header section of each of the respective media files; generating, by the processor, phonetic data corresponding to the file identification data for each of the media files, the generated phonetic data comprising phonetic representations of the first data field and the second data field that are generated based on the first language identification tag and the second language identification tag, respectively; comparing, by the processor, the generated phonetic data to the received voice data by the speech recognition unit and generating a corresponding speech control command; and selecting, by the processor, the media file from the data storage unit in accordance with the generated speech control command. | 11. A method for the voice-controlled selection of a media file stored on a data storage unit, the data storage unit including a plurality of media files, the media files including respective file identification data, the method comprising: receiving voice data indicative of selection of the media file from among the media files, and supplying the voice data to a speech recognition unit; extracting, by a processor, a first language identification tag included in the respective file identification data of each of the media files, the first language identification tag indicating a first language associated with a first data field of the respective file identification data, where the respective file identification data is in a header section of each of the respective media files; extracting, by the processor, a second language identification tag included in the respective file identification data of each of the media file, the second language identification tag indicating a second language associated with a second data field of the respective file identification data in the header section of each of the respective media files; generating, by the processor, phonetic data corresponding to the file identification data for each of the media files, the generated phonetic data comprising phonetic representations of the first data field and the second data field that are generated based on the first language identification tag and the second language identification tag, respectively; comparing, by the processor, the generated phonetic data to the received voice data by the speech recognition unit and generating a corresponding speech control command; and selecting, by the processor, the media file from the data storage unit in accordance with the generated speech control command. 17. The method of claim 11 , where generating the phonetic representation of the first data field includes applying phonetic rules of the first language identified by the first language identification tag on natural language text stored in the file identification data. | 0.516915 |
6. A method comprising: receiving data identifying an entity; parsing the data to extract the entity; generating in a computer system a group of candidate aspects for the entity, the computer system comprising one or more computers; for each of one or more pairs of candidate aspects, calculating a similarity score based on identifying respective sets of search results corresponding to respective queries of candidate aspects in the pair of candidate aspects and comparing search results in the sets of search results; modifying in the computer system the group of candidate aspects to generate a group of modified candidate aspects based on the similarity score for the candidate aspects, modifying comprising combining similar candidate aspects and grouping candidate aspects using one or more aspect classes each associated with one or more candidate aspects; ranking in the computer system one or more modified candidate aspects in the group of modified candidate aspects based on a diversity score and a popularity score, the popularity score for each of the modified candidate aspects based on a frequency of appearance of the modified candidate aspect and the diversity score for each of the modified candidate aspects based on similarity of the modified candidate aspect to other of the modified candidate aspects; and storing an association of one or more of the highest ranked modified candidate aspects with the entity in a data storage device of the computer system for presentation of each of the modified candidate aspects in combination with one or more search results that are specific to the modified candidate aspect. | 6. A method comprising: receiving data identifying an entity; parsing the data to extract the entity; generating in a computer system a group of candidate aspects for the entity, the computer system comprising one or more computers; for each of one or more pairs of candidate aspects, calculating a similarity score based on identifying respective sets of search results corresponding to respective queries of candidate aspects in the pair of candidate aspects and comparing search results in the sets of search results; modifying in the computer system the group of candidate aspects to generate a group of modified candidate aspects based on the similarity score for the candidate aspects, modifying comprising combining similar candidate aspects and grouping candidate aspects using one or more aspect classes each associated with one or more candidate aspects; ranking in the computer system one or more modified candidate aspects in the group of modified candidate aspects based on a diversity score and a popularity score, the popularity score for each of the modified candidate aspects based on a frequency of appearance of the modified candidate aspect and the diversity score for each of the modified candidate aspects based on similarity of the modified candidate aspect to other of the modified candidate aspects; and storing an association of one or more of the highest ranked modified candidate aspects with the entity in a data storage device of the computer system for presentation of each of the modified candidate aspects in combination with one or more search results that are specific to the modified candidate aspect. 9. The method of claim 6 , further comprising receiving data identifying one or more entity properties, where: generating the group of candidate aspects includes using the one or more entity properties; and the one or more highest ranked candidates aspects are associated with both the entity and the entity properties. | 0.570229 |
1. A method for user interface optimization, including: A. on a digital data processing system that comprises one or more digital data processors, identifying one or more rules for execution by a rules engine in order to generate any of a markup language page providing a user interface and a markup language stream providing the user interface, B. on the digital data processing system, executing a step of determining whether one or more aspects of the user interface generated as a result of execution of one or more of the rules is in conformity with one or more requirements, C. responding to a negative such determination by executing on the digital data processing system any of the steps of: i. generating a notification that identifies modifications to one or more of the rules which would result in generation of any of said markup language page and markup language stream providing a conforming user interface, wherein the conforming user interface includes a field having a modified display characteristic vis-à-vis a non-conforming user interface otherwise resulting from execution of one or more of the rules, and wherein the display characteristic is modified based on one or more of the requirements relating to a correlation between transactional data associated with the field having the modified display characteristic and transactional data associated with another field, ii. modifying one or more of the rules to generate any of said markup language page and markup language stream providing the conforming user interface, iii. modifying any of said markup language page and markup language stream to provide the conforming user interface, and D. any of storing to and generating as an output from said digital data processing system a result of one or more steps executed in step C. | 1. A method for user interface optimization, including: A. on a digital data processing system that comprises one or more digital data processors, identifying one or more rules for execution by a rules engine in order to generate any of a markup language page providing a user interface and a markup language stream providing the user interface, B. on the digital data processing system, executing a step of determining whether one or more aspects of the user interface generated as a result of execution of one or more of the rules is in conformity with one or more requirements, C. responding to a negative such determination by executing on the digital data processing system any of the steps of: i. generating a notification that identifies modifications to one or more of the rules which would result in generation of any of said markup language page and markup language stream providing a conforming user interface, wherein the conforming user interface includes a field having a modified display characteristic vis-à-vis a non-conforming user interface otherwise resulting from execution of one or more of the rules, and wherein the display characteristic is modified based on one or more of the requirements relating to a correlation between transactional data associated with the field having the modified display characteristic and transactional data associated with another field, ii. modifying one or more of the rules to generate any of said markup language page and markup language stream providing the conforming user interface, iii. modifying any of said markup language page and markup language stream to provide the conforming user interface, and D. any of storing to and generating as an output from said digital data processing system a result of one or more steps executed in step C. 35. The method of claim 1 , wherein a said conforming user interface includes a field that has a modified display characteristic vis-a-vis the non-conforming user interface which would result from a said rule. | 0.551634 |
16. The system of claim 15, wherein each of the terminals generates at least one of at least one first accessibility node corresponding to all pairs of ones of the input nodes of the respective separated portion and ones of the groups of matching patterns, and at least one second accessibility node corresponding to all pairs of ones of the output nodes of the separated portion and one of the groups of matching patterns, generate at least one of at least one third accessibility node corresponding to all input nodes of the separated portion and at least one fourth accessibility node corresponding to all output nodes of the separated portion, and connected the first and third accessibility nodes to the second and the fourth accessibility nodes with at least one directed graph edge based on the match results. | 16. The system of claim 15, wherein each of the terminals generates at least one of at least one first accessibility node corresponding to all pairs of ones of the input nodes of the respective separated portion and ones of the groups of matching patterns, and at least one second accessibility node corresponding to all pairs of ones of the output nodes of the separated portion and one of the groups of matching patterns, generate at least one of at least one third accessibility node corresponding to all input nodes of the separated portion and at least one fourth accessibility node corresponding to all output nodes of the separated portion, and connected the first and third accessibility nodes to the second and the fourth accessibility nodes with at least one directed graph edge based on the match results. 17. The system of claim 16, wherein the client terminal connects first, second, third, and fourth accessibility nodes of each of the accessibility graphs to first, second, third and fourth accessibility nodes of accessibility graphs of other separated portions based on the cross links of corresponding input nodes and corresponding output nodes to form the single graph. | 0.760571 |
9. A non-transitory machine-readable medium having instructions stored therein, which when executed by a machine, cause the machine to perform a method, the method comprising: in response to a first request received from a first remote metadata store (MDS) peer instance of a first remote peer for accessing metadata stored in a local MDS of a local peer, creating and initiating by a peer manager a first local MDS peer instance to establish a first communications channel with the first remote MDS peer instance to allow the first remote peer accessing the metadata stored in the local MDS of the local peer, wherein the first local MDS peer instance operates as a first proxy for a first peer MDS process specifically for handling the first request for accessing the metadata stored in the local MDS over the first communications channel; in response to a second request received from a local client of the local peer for accessing metadata stored in a second remote peer, creating and initiating by the peer manager a second local MDS peer instance to establish a second communications channel with a second remote MDS peer instance of the second remote peer to allow the local client accessing the metadata stored in the second remote peer, wherein the second local MDS peer instance operates as a second proxy for a second peer MDS process specifically for handling the second request for accessing the metadata stored in the second remote peer over second communications channel; and managing by the peer manager the first and second communications channels via the first and second MDS peer instances, respectively. | 9. A non-transitory machine-readable medium having instructions stored therein, which when executed by a machine, cause the machine to perform a method, the method comprising: in response to a first request received from a first remote metadata store (MDS) peer instance of a first remote peer for accessing metadata stored in a local MDS of a local peer, creating and initiating by a peer manager a first local MDS peer instance to establish a first communications channel with the first remote MDS peer instance to allow the first remote peer accessing the metadata stored in the local MDS of the local peer, wherein the first local MDS peer instance operates as a first proxy for a first peer MDS process specifically for handling the first request for accessing the metadata stored in the local MDS over the first communications channel; in response to a second request received from a local client of the local peer for accessing metadata stored in a second remote peer, creating and initiating by the peer manager a second local MDS peer instance to establish a second communications channel with a second remote MDS peer instance of the second remote peer to allow the local client accessing the metadata stored in the second remote peer, wherein the second local MDS peer instance operates as a second proxy for a second peer MDS process specifically for handling the second request for accessing the metadata stored in the second remote peer over second communications channel; and managing by the peer manager the first and second communications channels via the first and second MDS peer instances, respectively. 16. The non-transitory machine-readable medium of claim 9 , wherein creating and initiating the second local MDS peer instance comprises: transmitting a second user credential of a second user of the local client to the second remote peer to allow the second remote peer to authenticate the second user; receiving from the second remote peer a second MDS channel token representing an access permission to a second storage volume associated with the second remote peer; and providing the second user access of the second storage volume of the second remote peer based on the second MDS channel token. | 0.5 |
25. A personalized text and pictorial printed presentation produced by the process of: storing a plurality of segments of the facial features of various types; storing a plurality of hair styles; storing a plurality of clothing styles; introducing personal data of a person to be characterized into a storage means, said personal data including age, category, sex and race; introducing personal data of a person including name into a storage means; selecting facial features, hair style and clothing as a function of the personal data introduced into said storage means; plotting a combination of facial features, hair style and clothing as selected to produce a pictorial printed presentation of the person; and printing personal data such as the person's name along with the pictorial printed presentation. | 25. A personalized text and pictorial printed presentation produced by the process of: storing a plurality of segments of the facial features of various types; storing a plurality of hair styles; storing a plurality of clothing styles; introducing personal data of a person to be characterized into a storage means, said personal data including age, category, sex and race; introducing personal data of a person including name into a storage means; selecting facial features, hair style and clothing as a function of the personal data introduced into said storage means; plotting a combination of facial features, hair style and clothing as selected to produce a pictorial printed presentation of the person; and printing personal data such as the person's name along with the pictorial printed presentation. 26. A personalized text and pictorial printed presentation in accordance with claim 25 wherein said personalized text and pictorial printed presentation is printed on a preprinted background including standardized text whereby said standardized text and personal data such as the person's name constitute meaningful personalized text. | 0.58692 |
11. The system of claim 10 , wherein the processor is further operable to generate a user profile, and wherein the processor is further operable to filter the one or more related documents using the user profile. | 11. The system of claim 10 , wherein the processor is further operable to generate a user profile, and wherein the processor is further operable to filter the one or more related documents using the user profile. 12. The system of claim 11 , further comprising an interface operable to receive, from the user, a selection of at least one of the one or more filtered related documents, and wherein the processor is further operable to update the user profile to reflect the user's selection of at least one of the one or more filtered related documents. | 0.754246 |
18. The machine of claim 16 , wherein at least one property in the hierarchy is a transitive property. | 18. The machine of claim 16 , wherein at least one property in the hierarchy is a transitive property. 19. The machine of claim 18 , wherein the original ontology is a SHOQ ontology. | 0.976876 |
8. The method as recited in claim 6 , wherein the act of computing comprises: computing the dependencies based on the messages that are detected by the act of monitoring and responsive to a predefined dependency interval. | 8. The method as recited in claim 6 , wherein the act of computing comprises: computing the dependencies based on the messages that are detected by the act of monitoring and responsive to a predefined dependency interval. 9. The method as recited in claim 8 , wherein the act of computing further comprises: rejecting a potential dependency on a given service as a false positive based on an average interval of a repeated message exchange to a given endhost that corresponds to the given service and responsive to a length of the predefined dependency interval. | 0.867212 |
39. A computer-readable medium holding computer-executable instructions for debugging a graphical model, the instructions comprising: one or more instructions for providing a model view of a graphical model being executed, the model view showing a plurality of entities from a plurality of different types of modeling domains and transitioning between views of at least two of a time-based block diagram, a statechart, a data flow diagram, a discrete event model and compiled code; and, one or more instructions for providing a plurality of debuggable objects (DBOs) associated with the plurality of entities found in the graphical model and a solver for the graphical model, the graphical model including entities from a plurality of modeling domains, the modeling domains being of different types; one or more instructions for generating an execution list view displaying information from the execution of the entities in the graphical model; and one or more instructions for integrating the model view, a plurality of DBOs that are associated with entities from different types of modeling domains, and the execution list view into a common diagnostic environment, the common diagnostic environment including a unified debugger for the plurality of modeling domain. | 39. A computer-readable medium holding computer-executable instructions for debugging a graphical model, the instructions comprising: one or more instructions for providing a model view of a graphical model being executed, the model view showing a plurality of entities from a plurality of different types of modeling domains and transitioning between views of at least two of a time-based block diagram, a statechart, a data flow diagram, a discrete event model and compiled code; and, one or more instructions for providing a plurality of debuggable objects (DBOs) associated with the plurality of entities found in the graphical model and a solver for the graphical model, the graphical model including entities from a plurality of modeling domains, the modeling domains being of different types; one or more instructions for generating an execution list view displaying information from the execution of the entities in the graphical model; and one or more instructions for integrating the model view, a plurality of DBOs that are associated with entities from different types of modeling domains, and the execution list view into a common diagnostic environment, the common diagnostic environment including a unified debugger for the plurality of modeling domain. 47. The medium of claim 39 , wherein the common diagnostic environment displays profiling information to a user. | 0.686553 |
12. A system comprising: at least one server computer configured to: provide content management access to a plurality of content providers to access a data store resident on a web site and use a same data store template comprising one set of metadata elements to transfer media files' associated metadata to the web site's data store; receive from each of the plurality of content providers at least one media file via the content provider's content management access, each received media file comprising content; for each media file received from a content provider of the plurality, receive, from the content provider via the content provider's content management access, a transfer of the media file's associated metadata from the content provider to the web site's data store using the template, the metadata received from the content provider is organized according to the template, the template identifying metadata elements of the set and a correspondence between the metadata and the metadata elements; map a number of the metadata elements to a plurality of metadata display areas of a content presentation user interface, the metadata display area for each mapped metadata element is consistent across the plurality of content providers such that a mapped metadata element's metadata display area displays the metadata element's corresponding metadata regardless of the content provider that provided the metadata, the content presentation user interface further comprising at least one content presentation area for presentation of the content received from the plurality of content providers; and make the content presentation user interface available, the content presentation user interface providing a consistent interface for presentation of the content and metadata received from the plurality of content providers. | 12. A system comprising: at least one server computer configured to: provide content management access to a plurality of content providers to access a data store resident on a web site and use a same data store template comprising one set of metadata elements to transfer media files' associated metadata to the web site's data store; receive from each of the plurality of content providers at least one media file via the content provider's content management access, each received media file comprising content; for each media file received from a content provider of the plurality, receive, from the content provider via the content provider's content management access, a transfer of the media file's associated metadata from the content provider to the web site's data store using the template, the metadata received from the content provider is organized according to the template, the template identifying metadata elements of the set and a correspondence between the metadata and the metadata elements; map a number of the metadata elements to a plurality of metadata display areas of a content presentation user interface, the metadata display area for each mapped metadata element is consistent across the plurality of content providers such that a mapped metadata element's metadata display area displays the metadata element's corresponding metadata regardless of the content provider that provided the metadata, the content presentation user interface further comprising at least one content presentation area for presentation of the content received from the plurality of content providers; and make the content presentation user interface available, the content presentation user interface providing a consistent interface for presentation of the content and metadata received from the plurality of content providers. 17. The system of claim 12 , the content presentation user interface comprising a channel description area comprising a plurality of user-selectable channels, a show description area comprising a description of a plurality of user-selectable shows, and an episode description area comprising a description of a plurality of user-selectable episodes. | 0.534764 |
8. A computer-implemented process for translating knowledge implicit in a continuous-state feedforward neural network stored in a computer into an explicit set of if-then rules supporting possible conclusions, said computer comprising a CPU and an output device coupled to the CPU, said neural network being stored in said CPU, said CPU comprising an explanation module, said process comprising directing the explanation module to perform the steps of: determining output states of the neural network based upon a set of input variables, some of whose values are known and others of whose values are unknown; determining, using the process of claim 10, a minimal subset of possible values of input variables which, if true, would result in reaching a final conclusion condition for the network, where said minimal subset of input values then constitutes a rule for said conclusion condition; searching input values for a set of all possible rules which support said conclusion condition; and displaying said rules on said output device. | 8. A computer-implemented process for translating knowledge implicit in a continuous-state feedforward neural network stored in a computer into an explicit set of if-then rules supporting possible conclusions, said computer comprising a CPU and an output device coupled to the CPU, said neural network being stored in said CPU, said CPU comprising an explanation module, said process comprising directing the explanation module to perform the steps of: determining output states of the neural network based upon a set of input variables, some of whose values are known and others of whose values are unknown; determining, using the process of claim 10, a minimal subset of possible values of input variables which, if true, would result in reaching a final conclusion condition for the network, where said minimal subset of input values then constitutes a rule for said conclusion condition; searching input values for a set of all possible rules which support said conclusion condition; and displaying said rules on said output device. 9. The process of claim 8 wherein, for any continuous-valued input variable, specific input values are chosen to be representative of upper, lower, and middle statistical regions of said variable's value range, and those values are examined for possible inclusion in a rule. | 0.921563 |
13. The system of claim 1 wherein, upon selection by the user of an integrated ad displayed at the user terminal, the processor is programmed to transfer the user from the displayed publisher page to a corresponding display of an advertiser site. | 13. The system of claim 1 wherein, upon selection by the user of an integrated ad displayed at the user terminal, the processor is programmed to transfer the user from the displayed publisher page to a corresponding display of an advertiser site. 15. The system of claim 13 , wherein the determination of at least one ad associated with the displayed advertiser site is at least partially influenced by one or more tracked actions at the displayed advertiser site. | 0.959293 |
1. A device comprising: one or more processors; and one or more computer readable storage media, coupled to the one or more processors, embodying computer readable instructions executable by the one or more processors to implement a method comprising: receiving a user selection of a site mode, the site mode being associated with a web application installed on an associated client device; responsive to receiving the site mode selection, requesting a start URL, wherein the start URL is ascertained from a web application file that was created from information received from a website associated with the web application; receiving web resources associated with the start URL; rendering the web resources in a web application window; receiving a user interaction with respect to the resources rendered in the web application window; responsive to the user interaction being within boundaries, associated with a website domain or subdomain and defined by the web application file, rendering user interface customization within the boundaries in the web application window; and responsive to the user interaction not being within boundaries associated with a website domain or subdomain and defined by the web application file, rendering content associated with the user interaction in a default browser different from the web application window. | 1. A device comprising: one or more processors; and one or more computer readable storage media, coupled to the one or more processors, embodying computer readable instructions executable by the one or more processors to implement a method comprising: receiving a user selection of a site mode, the site mode being associated with a web application installed on an associated client device; responsive to receiving the site mode selection, requesting a start URL, wherein the start URL is ascertained from a web application file that was created from information received from a website associated with the web application; receiving web resources associated with the start URL; rendering the web resources in a web application window; receiving a user interaction with respect to the resources rendered in the web application window; responsive to the user interaction being within boundaries, associated with a website domain or subdomain and defined by the web application file, rendering user interface customization within the boundaries in the web application window; and responsive to the user interaction not being within boundaries associated with a website domain or subdomain and defined by the web application file, rendering content associated with the user interaction in a default browser different from the web application window. 7. The device of claim 1 , wherein the web application file includes one or more navigation domains that can be navigated within the web application window. | 0.615222 |
17. The system according to claim 11 , wherein the segmenting includes segmenting one of the connected components into a plurality of fragments. | 17. The system according to claim 11 , wherein the segmenting includes segmenting one of the connected components into a plurality of fragments. 18. The system according to claim 17 , wherein the plurality of the fragments correspond to a plurality of different types of markings. | 0.962101 |
9. A computer-implemented method for converting content of a target for use with a text-to-speech engine, said method comprising: at a computer comprising a computer program to implement processing operations: receiving data that defines content of a Website; processing the data to, identify a context identifier from among the content; separate the content into relevant content and miscellaneous content; locate a target term in the relevant content; use the context identifier to identify a substitution unit for the target term; and generate a spoken content input that can be utilized by a text-to-speech generator to generate spoken content, the spoken content input comprising a replacement unit corresponding to the substitution unit, wherein the substitution unit is selected from a repository with entries that are arranged in tables in accordance with a prioritized scheme, wherein the prioritized scheme defines a position amongst the tables for the substitution unit, wherein the position in the tables is assigned based on a specificity characteristic that describes a relative inclusivity of the substitution unit as compared to other substitution units, and wherein the position defines a level of priority for the identified token. | 9. A computer-implemented method for converting content of a target for use with a text-to-speech engine, said method comprising: at a computer comprising a computer program to implement processing operations: receiving data that defines content of a Website; processing the data to, identify a context identifier from among the content; separate the content into relevant content and miscellaneous content; locate a target term in the relevant content; use the context identifier to identify a substitution unit for the target term; and generate a spoken content input that can be utilized by a text-to-speech generator to generate spoken content, the spoken content input comprising a replacement unit corresponding to the substitution unit, wherein the substitution unit is selected from a repository with entries that are arranged in tables in accordance with a prioritized scheme, wherein the prioritized scheme defines a position amongst the tables for the substitution unit, wherein the position in the tables is assigned based on a specificity characteristic that describes a relative inclusivity of the substitution unit as compared to other substitution units, and wherein the position defines a level of priority for the identified token. 18. A computer-implemented method according to claim 9 , wherein the tables comprise at least one regular expression associated with at least one of the terms. | 0.614346 |
13. A document and template creation system comprising: a document and template creation device including a processor and a memory, the processor configured to execute computer-readable instructions to, auto-complete a first text string based on at least one domain ontology concept and a context of a portion of the first text string in a clinical document for a clinical indication; analyze the clinical document to identify at least one first candidate for structural content, the clinical document including documentation of at least clinical observations by a physician, the at least one first candidate for structural content including a free form second text-string entry input into the clinical document by a user, identify a parent node corresponding to the at least one first candidate in a domain ontology database, obtain at least one domain specific structural element from the domain ontology database based on the identified parent node, the at least one domain specific structural element including the at least one first candidate and a plurality of second candidates, the plurality of second candidates being additional concepts identified as siblings of the at least one first candidate, and create a template for the clinical document by inserting, into the clinical document for the clinical indication, structural content including the at least one domain specific structural element, the at least one domain specific structural element including the at least one first candidate and the plurality of second candidates, wherein the structural content forms a structured part of the template for creating subsequent clinical documents for subsequent clinical indications, the plurality of second candidates are in the form of one or more third text-strings, and the at least one first candidate and the plurality of second candidates are displayed and selectable by the user for insertion into the subsequent clinical documents when creating the subsequent clinical documents from the created template. | 13. A document and template creation system comprising: a document and template creation device including a processor and a memory, the processor configured to execute computer-readable instructions to, auto-complete a first text string based on at least one domain ontology concept and a context of a portion of the first text string in a clinical document for a clinical indication; analyze the clinical document to identify at least one first candidate for structural content, the clinical document including documentation of at least clinical observations by a physician, the at least one first candidate for structural content including a free form second text-string entry input into the clinical document by a user, identify a parent node corresponding to the at least one first candidate in a domain ontology database, obtain at least one domain specific structural element from the domain ontology database based on the identified parent node, the at least one domain specific structural element including the at least one first candidate and a plurality of second candidates, the plurality of second candidates being additional concepts identified as siblings of the at least one first candidate, and create a template for the clinical document by inserting, into the clinical document for the clinical indication, structural content including the at least one domain specific structural element, the at least one domain specific structural element including the at least one first candidate and the plurality of second candidates, wherein the structural content forms a structured part of the template for creating subsequent clinical documents for subsequent clinical indications, the plurality of second candidates are in the form of one or more third text-strings, and the at least one first candidate and the plurality of second candidates are displayed and selectable by the user for insertion into the subsequent clinical documents when creating the subsequent clinical documents from the created template. 14. The system of claim 13 , wherein the structured part of the template includes a pick list including children of the identified parent node as an option, the children including the at least one first candidate and the plurality of second candidates. | 0.898194 |
1. A method employing a portable user device having at least one microphone that captures audio, and at least one image sensor for capturing imagery, the method comprising the acts: (a) capturing imagery with the image sensor, the captured image depicting one or more physical subjects within an environment of said user, and capturing user speech with the microphone; (b) sending, to a speech recognition module, audio data corresponding to the user speech, and receiving recognized user speech data corresponding thereto; (c) applying a computer-implemented cognition process to the imagery, said cognition process also employing information from the recognized user speech data as a clue to help identify a physical subject within the captured imagery that is of interest to said user; and (d) presenting a set of plural response options to the user, for user selection therebetween; wherein the set of plural response options presented to the user varies based on said identified physical subject. | 1. A method employing a portable user device having at least one microphone that captures audio, and at least one image sensor for capturing imagery, the method comprising the acts: (a) capturing imagery with the image sensor, the captured image depicting one or more physical subjects within an environment of said user, and capturing user speech with the microphone; (b) sending, to a speech recognition module, audio data corresponding to the user speech, and receiving recognized user speech data corresponding thereto; (c) applying a computer-implemented cognition process to the imagery, said cognition process also employing information from the recognized user speech data as a clue to help identify a physical subject within the captured imagery that is of interest to said user; and (d) presenting a set of plural response options to the user, for user selection therebetween; wherein the set of plural response options presented to the user varies based on said identified physical subject. 4. The method of claim 1 in which the captured imagery depicts a parking meter. | 0.671415 |
10. A system for populating a predictive text dictionary according to claim 8 , wherein said subset of said words from said word database is selected by said query module has not been previously communicated to said handheld electronic device. | 10. A system for populating a predictive text dictionary according to claim 8 , wherein said subset of said words from said word database is selected by said query module has not been previously communicated to said handheld electronic device. 11. A system for populating a predictive text dictionary according to claim 10 , wherein said user database is also operable to store historical user preferences. | 0.872817 |
1. An input auxiliary apparatus comprising: a voice input section for inputting a voice; an embellishment information retaining section for retaining embellishment information on a plurality of posture patterns in a storing section in advance such that each piece of the embellishment information links each posture pattern; a posture detecting section for detecting posture; and a control section for being operable as: by a speech recognition instruction by a user, recognizing, for each speech unit, voice inputted from the voice input section, as a character string, determining, for the each speech unit, a posture pattern instructed by the user, based the posture detected by the posture detecting section during the speech recognition, reading out an embellishment information linked with the posture pattern determined for the each speech unit from the storing section; and applying the embellishment information read out for each speech unit to the character string recognized for the each speech unit, wherein the embellishment information is character color of the character string, character size of the character string, and an emoticon or a pictograph added following the character string, wherein the embellishment information retaining section also retains emotion information or season information such that each piece of the emotion information or season information is linked with the each posture pattern, wherein, during the speech recognition, the control section sequentially changes a display mode of a display section based on a piece of the emotion information or season information linked with a posture pattern including displacement of the posture being detected by the posture detecting section, and wherein the display mode is an avatar, or a mark or a diagram which represents an emotion. | 1. An input auxiliary apparatus comprising: a voice input section for inputting a voice; an embellishment information retaining section for retaining embellishment information on a plurality of posture patterns in a storing section in advance such that each piece of the embellishment information links each posture pattern; a posture detecting section for detecting posture; and a control section for being operable as: by a speech recognition instruction by a user, recognizing, for each speech unit, voice inputted from the voice input section, as a character string, determining, for the each speech unit, a posture pattern instructed by the user, based the posture detected by the posture detecting section during the speech recognition, reading out an embellishment information linked with the posture pattern determined for the each speech unit from the storing section; and applying the embellishment information read out for each speech unit to the character string recognized for the each speech unit, wherein the embellishment information is character color of the character string, character size of the character string, and an emoticon or a pictograph added following the character string, wherein the embellishment information retaining section also retains emotion information or season information such that each piece of the emotion information or season information is linked with the each posture pattern, wherein, during the speech recognition, the control section sequentially changes a display mode of a display section based on a piece of the emotion information or season information linked with a posture pattern including displacement of the posture being detected by the posture detecting section, and wherein the display mode is an avatar, or a mark or a diagram which represents an emotion. 3. The input auxiliary apparatus according to claim 1 , wherein, in the emotion information or season information, different emotions or seasons are retained for different directions included in the plurality of posture patterns, and different levels of an emotion or a season corresponding to an arbitrary direction are retained for different angles of the arbitrary direction. | 0.5 |
1. A computer-implemented method, comprising: receiving input files comprising markup language text for a graphical user interface; obtaining an application framework code; receiving web application business logic objects; organizing the application framework code and the web application business logic objects into web application source code; and binding the web application source code with the input files, the binding including compiling the input files; wherein the application framework code is configured to, at runtime, detect any change to web application screens and to re-compile the input files in response to detecting the any change. | 1. A computer-implemented method, comprising: receiving input files comprising markup language text for a graphical user interface; obtaining an application framework code; receiving web application business logic objects; organizing the application framework code and the web application business logic objects into web application source code; and binding the web application source code with the input files, the binding including compiling the input files; wherein the application framework code is configured to, at runtime, detect any change to web application screens and to re-compile the input files in response to detecting the any change. 21. The computer-implemented method of claim 1 , wherein the application framework code is configured to control an operating system of a web application server by sending instructions to the operating system. | 0.681667 |
13. 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: obtaining, for a sequence of strokes that represent a handwritten input, cut point data indicating one or more particular candidate cut points that are identified within the sequence of strokes; obtaining, for the one or more of the particular candidate cut points, feature data indicating one or more features of the particular candidate cut point; for each of the one or more particular candidate cut points, providing the feature data to a classifier that is trained to predict, based on one or more features of a candidate cut point, a likelihood of the candidate cut point being a correct cut point; for each of the one or more particular candidate cut points, receiving, from the classifier, data indicating the likelihood that the particular candidate cut point is a correct cut point; selecting a set of one or more of the particular candidate cut points whose respective likelihoods satisfy a threshold; and using the set of candidate cut points to segment the sequence of strokes. | 13. 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: obtaining, for a sequence of strokes that represent a handwritten input, cut point data indicating one or more particular candidate cut points that are identified within the sequence of strokes; obtaining, for the one or more of the particular candidate cut points, feature data indicating one or more features of the particular candidate cut point; for each of the one or more particular candidate cut points, providing the feature data to a classifier that is trained to predict, based on one or more features of a candidate cut point, a likelihood of the candidate cut point being a correct cut point; for each of the one or more particular candidate cut points, receiving, from the classifier, data indicating the likelihood that the particular candidate cut point is a correct cut point; selecting a set of one or more of the particular candidate cut points whose respective likelihoods satisfy a threshold; and using the set of candidate cut points to segment the sequence of strokes. 18. The system of claim 13 , wherein the operations further comprise: determining, for each segment of the handwritten between two adjacent candidate cut points of the set of the candidate cut points, a character that corresponds to the segment. | 0.533973 |
10. A computer storage medium having computer executable instructions that are not a signal stored thereon which, when executed by a computer, cause the computer to: identify a given word W to be entered into an index; determine a plurality of word senses S n associated with the word W; determine a plurality of hypernyms H n associated with the plurality of word senses S n , the plurality of hypernyms H n comprising a tree-like inheritance hierarchy of hypernyms associated with each of the plurality of word senses S n ; establish a word hypernym weight WHW(H n ,W) for each of the plurality of hypernyms H n based on
WHW ( H n W )=Σ p ( S n |W )f( H n ,S n ) where the word hypernym weight WHW(H n ,W) being equal to a sum, over the plurality of word senses S n , of the product of the probability p of the sense of given word S n |W and a function f(H n ,S n ) defined as having a value of one when a given hypernym H is an inherited hypernym of the plurality of word senses Sn, and having a value of zero otherwise; and store information associated with the hypernym H into the index based on the word hypernym weight WHW(H n W). | 10. A computer storage medium having computer executable instructions that are not a signal stored thereon which, when executed by a computer, cause the computer to: identify a given word W to be entered into an index; determine a plurality of word senses S n associated with the word W; determine a plurality of hypernyms H n associated with the plurality of word senses S n , the plurality of hypernyms H n comprising a tree-like inheritance hierarchy of hypernyms associated with each of the plurality of word senses S n ; establish a word hypernym weight WHW(H n ,W) for each of the plurality of hypernyms H n based on
WHW ( H n W )=Σ p ( S n |W )f( H n ,S n ) where the word hypernym weight WHW(H n ,W) being equal to a sum, over the plurality of word senses S n , of the product of the probability p of the sense of given word S n |W and a function f(H n ,S n ) defined as having a value of one when a given hypernym H is an inherited hypernym of the plurality of word senses Sn, and having a value of zero otherwise; and store information associated with the hypernym H into the index based on the word hypernym weight WHW(H n W). 15. The computer storage medium of claim 10 , further causing the computer to query the index. | 0.526578 |
12. The apparatus of claim 10 , wherein the continual range queries define respective geographic regions of interest, the geographic regions of interest remaining stationary over multiple evaluations of the continual range queries. | 12. The apparatus of claim 10 , wherein the continual range queries define respective geographic regions of interest, the geographic regions of interest remaining stationary over multiple evaluations of the continual range queries. 14. The apparatus of claim 12 , wherein the one or more moving objects comprise cellular phones. | 0.946667 |
1. A method for collaborative editing of a document by an author of the document and a plurality of reviewers, said method being performed by program code executing on a computer, said method comprising: receiving, by the program code from the author, an identification of a plurality of selected portions of the document; receiving, by the program code from the author, a plurality of comments created by the author and an identification of at least one reviewer of the plurality of reviewers to which each received comment is directed, wherein the selected portions and the comments are associated with each other on a one-to-one basis, and wherein each comment pertains to content of the selected portion that each comment is associated with; parsing the received comments, and utilizing the received identification of the at least one reviewer to which each comment is directed, to generate a list of comments comprising the plurality of comments, wherein the list of comments specifies for each comment the at least one reviewer to which each comment is directed, and wherein said parsing and said utilizing are performed by the program code; and making available, by the program code to each reviewer, the comments on the list of comments directed to each reviewer, wherein the method further comprises for each selected portion of the document: providing, by the program code to the author, a corresponding displayed form; wherein each displayed form includes the selected portion and space for the author to specify both the comment associated with the selected portion and the identification of at the least one reviewer to which the associated comment is directed; and wherein said receiving the plurality of comments comprises receiving the comments in the displayed forms corresponding to the selected portions of the document. | 1. A method for collaborative editing of a document by an author of the document and a plurality of reviewers, said method being performed by program code executing on a computer, said method comprising: receiving, by the program code from the author, an identification of a plurality of selected portions of the document; receiving, by the program code from the author, a plurality of comments created by the author and an identification of at least one reviewer of the plurality of reviewers to which each received comment is directed, wherein the selected portions and the comments are associated with each other on a one-to-one basis, and wherein each comment pertains to content of the selected portion that each comment is associated with; parsing the received comments, and utilizing the received identification of the at least one reviewer to which each comment is directed, to generate a list of comments comprising the plurality of comments, wherein the list of comments specifies for each comment the at least one reviewer to which each comment is directed, and wherein said parsing and said utilizing are performed by the program code; and making available, by the program code to each reviewer, the comments on the list of comments directed to each reviewer, wherein the method further comprises for each selected portion of the document: providing, by the program code to the author, a corresponding displayed form; wherein each displayed form includes the selected portion and space for the author to specify both the comment associated with the selected portion and the identification of at the least one reviewer to which the associated comment is directed; and wherein said receiving the plurality of comments comprises receiving the comments in the displayed forms corresponding to the selected portions of the document. 15. The method of claim 1 , wherein a first comment of the plurality of comments is directed to at least two reviewers of the plurality of reviewers. | 0.662846 |
9. The system of claim 8 , wherein the images are silhouette images obtained from a plurality of viewpoints surrounding the 3D model. | 9. The system of claim 8 , wherein the images are silhouette images obtained from a plurality of viewpoints surrounding the 3D model. 11. The system of claim 9 , wherein the viewpoints are selected by the model processing engine in a manner that captures a maximum amount of non-overlapping information with a given number of silhouette images. | 0.9491 |
9. The speech dialogue system of claim 8, wherein the speech segment detection means obtains the power level of the synthetic speech response by calculating a convolution of the synthetic speech response and an estimate for the filter coefficients. | 9. The speech dialogue system of claim 8, wherein the speech segment detection means obtains the power level of the synthetic speech response by calculating a convolution of the synthetic speech response and an estimate for the filter coefficients. 11. The speech dialogue system of claim 9, wherein the estimate for the filter coefficients is obtained by a spectral pre-whitening of a frequency spectrum of the synthetic speech response. | 0.951207 |
1. A system for detecting a presence of a third party participating in a monitored telephone conversation, the system comprising: a speech recognition module configured to detect a first characteristic of the monitored telephone conversation and a second characteristic of the monitored telephone conversation; a speech analysis module configured to calculate a three-way calling score for the monitored telephone conversation, the calculating including: assigning a first score of the first characteristic based on a predefined importance of the first characteristic; assigning a second score of the second characteristic based on a predefined importance of the second characteristic; and calculating the three-way calling score by summing the first score and the second score; and a three-way call detection module configured to detect the presence of the third party based on a comparison of the three-way calling score to a predetermined threshold. | 1. A system for detecting a presence of a third party participating in a monitored telephone conversation, the system comprising: a speech recognition module configured to detect a first characteristic of the monitored telephone conversation and a second characteristic of the monitored telephone conversation; a speech analysis module configured to calculate a three-way calling score for the monitored telephone conversation, the calculating including: assigning a first score of the first characteristic based on a predefined importance of the first characteristic; assigning a second score of the second characteristic based on a predefined importance of the second characteristic; and calculating the three-way calling score by summing the first score and the second score; and a three-way call detection module configured to detect the presence of the third party based on a comparison of the three-way calling score to a predetermined threshold. 2. The system of claim 1 , further comprising a database that stores the first score and the second score. | 0.606009 |
1. A method for recognizing a character in a portable device, the method comprising: obtaining, in accordance with a character recognition request, an image using a camera of the portable device in a preview mode in which a plurality of images are being sequentially displayed in real time on a display of the portable device; performing an auto focus function of the camera to obtain an image having a certain level of clarity for character recognition using the camera; character-recognition-processing the image having the certain level of clarity so as to generate recognition result data; and displaying a recognized character row on the display based on the recognition result data. | 1. A method for recognizing a character in a portable device, the method comprising: obtaining, in accordance with a character recognition request, an image using a camera of the portable device in a preview mode in which a plurality of images are being sequentially displayed in real time on a display of the portable device; performing an auto focus function of the camera to obtain an image having a certain level of clarity for character recognition using the camera; character-recognition-processing the image having the certain level of clarity so as to generate recognition result data; and displaying a recognized character row on the display based on the recognition result data. 7. The method as claimed in claim 1 , further comprising: combining one or more characters identified through the character-recognition-processing of the image obtained in the preview mode and having a predetermined maximum number of characters as a first word; searching a dictionary database that stores dictionary information on various languages using the first word; and outputting a word corresponding to the first word in at least one of the various languages according to a result of the search of the dictionary database using the first word. | 0.5 |
9. A tangible computer readable storage medium comprising computer readable instructions which, when executed, cause a processor to at least: access a query based on a topic term; determine topic specific posts by applying the query to a first plurality of posts to a web site; compare the topic specific posts to a list of web sites to determine a topic volume per site; determine a plurality of inbound links to the first plurality of posts; determine a number of inbound links to the posts that are relevant to the topic term by comparing the topic volume per site and the inbound links; and generate a rank of the web site based on the number of inbound links to the posts that are relevant to the topic term and times between the inbound links. | 9. A tangible computer readable storage medium comprising computer readable instructions which, when executed, cause a processor to at least: access a query based on a topic term; determine topic specific posts by applying the query to a first plurality of posts to a web site; compare the topic specific posts to a list of web sites to determine a topic volume per site; determine a plurality of inbound links to the first plurality of posts; determine a number of inbound links to the posts that are relevant to the topic term by comparing the topic volume per site and the inbound links; and generate a rank of the web site based on the number of inbound links to the posts that are relevant to the topic term and times between the inbound links. 10. A tangible computer readable medium as defined in claim 9 , wherein the instructions are further to cause the processor to calculate elapsed times between postings of adjacent ones of the inbound links by: determining posting times of posts that are relevant to the topic term; comparing the posting times to the inbound links to determine a first list of inbound links and posting times of the inbound links; and comparing the posting times of the inbound links to the topic specific posts to generate a second list of (1) inbound links, (2) posting times, and (3) posts associated with the inbound links and the posting times. | 0.5 |
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