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11. The method of claim 10 wherein the size parameter is reduced by use of semi join operations on the base relations or temporary relations. | 11. The method of claim 10 wherein the size parameter is reduced by use of semi join operations on the base relations or temporary relations. 12. The method of claim 11 wherein the reduction of the size parameter by use of the semi join operations is estimated by use of selectivity parameters. | 0.971438 |
1. A computer-implemented method, comprising: receiving a first profile in a system comprising one or more computers, wherein the first profile is for a first author, wherein the first profile links to one or more first documents, wherein the first author is an author of each of the one or more first documents; identifying by operation of the system, one or more second authors, wherein each of the one or more second authors is a co-author of one or more of the first documents; calculating by operation of the system and for each of the one or more second authors, a respective co-author score for the second author that is a measure of how connected the second author and the first author are as co-authors; ranking by operation of the system, the one or more second authors based on their respective co-author scores; associating by operation of the system, the one or more second authors with the first profile; receiving a request from a user to access a profile for the first author; and providing the first profile for presentation to the user, wherein, when presented to the user, the first profile includes a result list of retrieved and ranked resources associated with the first author and a listing of the one or more second authors in an order according to the ranking of the one or more second authors. | 1. A computer-implemented method, comprising: receiving a first profile in a system comprising one or more computers, wherein the first profile is for a first author, wherein the first profile links to one or more first documents, wherein the first author is an author of each of the one or more first documents; identifying by operation of the system, one or more second authors, wherein each of the one or more second authors is a co-author of one or more of the first documents; calculating by operation of the system and for each of the one or more second authors, a respective co-author score for the second author that is a measure of how connected the second author and the first author are as co-authors; ranking by operation of the system, the one or more second authors based on their respective co-author scores; associating by operation of the system, the one or more second authors with the first profile; receiving a request from a user to access a profile for the first author; and providing the first profile for presentation to the user, wherein, when presented to the user, the first profile includes a result list of retrieved and ranked resources associated with the first author and a listing of the one or more second authors in an order according to the ranking of the one or more second authors. 4. The method of claim 1 , wherein associating the one or more second authors with the first profile comprises: adding data identifying one or more second authors that each have a respective co-author score that satisfies a threshold, the one or more second authors being ranked in a descending order of the co-authorship score. | 0.735662 |
13. A method comprising: receiving multisensory input from a plurality of input devices, the plurality of devices consisting of a hand-held keypad controller and a microphone; responsive to the receiving of multisensory input, filtering environment background noise from the multisensory input, yielding filtered multisensory input; responsive to the filtering environment background noise from the multisensory input, extracting a patient-lifting-device command from the filtered multisensory input; responsive to the extracting of the patient-lifting-device command from the filtered multisensory input, generating at least one electrical signal from the patient-lifting-device command; and responsive to the generating of the at least one the electrical signal, performing motion of a patient-lifting-device in accordance with the at least one electrical signal. | 13. A method comprising: receiving multisensory input from a plurality of input devices, the plurality of devices consisting of a hand-held keypad controller and a microphone; responsive to the receiving of multisensory input, filtering environment background noise from the multisensory input, yielding filtered multisensory input; responsive to the filtering environment background noise from the multisensory input, extracting a patient-lifting-device command from the filtered multisensory input; responsive to the extracting of the patient-lifting-device command from the filtered multisensory input, generating at least one electrical signal from the patient-lifting-device command; and responsive to the generating of the at least one the electrical signal, performing motion of a patient-lifting-device in accordance with the at least one electrical signal. 17. The method of claim 13 wherein extracting the patient-lifting-device command from the filtered multisensory input further comprises: voice recognition on input from the microphone. | 0.857425 |
1. A computer-implemented method for program code library selection in a networked computing environment, comprising: receiving a search results file in a library selection integrated development environment (IDE) from a library searching IDE, the search results file comprising at least one method and at least one class from a first program code file in the library searching IDE, and the search results file having a set of attributes; determining whether to perform a micro-benchmarking on the at least one method and the at least one class of the search results file, the determining being based on at least one of: a configuration of a second program code file in the library selection IDE, or a detected code pattern of the second program code file; performing, responsive to the determining, the micro-benchmarking on the at least one method and the at least one class, and storing an associated micro-benchmark time and an invocation timestamp in a computer storage device; calculating a set of code style similarity scores that indicate a similarity between the at least one method and the at least one class with the methods and classes of the second program code file based on code syntax similarity; and providing an ordered list of the methods and classes of the second program code file based on the set of code style similarity scores, the micro-benchmarking, and the set of attributes. | 1. A computer-implemented method for program code library selection in a networked computing environment, comprising: receiving a search results file in a library selection integrated development environment (IDE) from a library searching IDE, the search results file comprising at least one method and at least one class from a first program code file in the library searching IDE, and the search results file having a set of attributes; determining whether to perform a micro-benchmarking on the at least one method and the at least one class of the search results file, the determining being based on at least one of: a configuration of a second program code file in the library selection IDE, or a detected code pattern of the second program code file; performing, responsive to the determining, the micro-benchmarking on the at least one method and the at least one class, and storing an associated micro-benchmark time and an invocation timestamp in a computer storage device; calculating a set of code style similarity scores that indicate a similarity between the at least one method and the at least one class with the methods and classes of the second program code file based on code syntax similarity; and providing an ordered list of the methods and classes of the second program code file based on the set of code style similarity scores, the micro-benchmarking, and the set of attributes. 2. The computer-implemented method of claim 1 , further comprising selecting a program code library based on the ordered list. | 0.870672 |
12. A system for detecting malware, the system comprising: an identification module, stored in memory, that identifies a behavioral trace of a program, the behavioral trace comprising a sequence of runtime behaviors exhibited by the program; a division module, stored in memory, that divides the behavioral trace to identify a plurality of n-grams within the behavioral trace, each runtime behavior within the sequence of runtime behaviors corresponding to an n-gram token; an analysis module, stored in memory, that analyzes the plurality of n-grams to generate a feature vector of the behavioral trace comprising: applying, for each given n-gram in the plurality of n-grams, a feature function to the behavioral trace that describes an occurrence characteristic of the given n-gram within the behavioral trace; and including a result of the feature function in the feature vector; wherein: the feature vector comprises a plurality of dimensions, each n-gram within the plurality of n-grams corresponding to a dimension within the plurality of dimensions; the plurality of n-grams map to the plurality of dimensions according to a non-injective surjection; and including the result of the feature function in the feature vector comprises aggregating a subset of outputs of the feature function derived from a subset of the plurality of n-grams into a value and assigning the value to a dimension within the plurality of dimensions according to the non-injective surjection; a classification module, stored in memory, that classifies the program based at least in part on the feature vector of the behavioral trace to determine whether the program is malicious; and at least one physical processor configured to execute the identification module, the division module, the analysis module, and the classification module. | 12. A system for detecting malware, the system comprising: an identification module, stored in memory, that identifies a behavioral trace of a program, the behavioral trace comprising a sequence of runtime behaviors exhibited by the program; a division module, stored in memory, that divides the behavioral trace to identify a plurality of n-grams within the behavioral trace, each runtime behavior within the sequence of runtime behaviors corresponding to an n-gram token; an analysis module, stored in memory, that analyzes the plurality of n-grams to generate a feature vector of the behavioral trace comprising: applying, for each given n-gram in the plurality of n-grams, a feature function to the behavioral trace that describes an occurrence characteristic of the given n-gram within the behavioral trace; and including a result of the feature function in the feature vector; wherein: the feature vector comprises a plurality of dimensions, each n-gram within the plurality of n-grams corresponding to a dimension within the plurality of dimensions; the plurality of n-grams map to the plurality of dimensions according to a non-injective surjection; and including the result of the feature function in the feature vector comprises aggregating a subset of outputs of the feature function derived from a subset of the plurality of n-grams into a value and assigning the value to a dimension within the plurality of dimensions according to the non-injective surjection; a classification module, stored in memory, that classifies the program based at least in part on the feature vector of the behavioral trace to determine whether the program is malicious; and at least one physical processor configured to execute the identification module, the division module, the analysis module, and the classification module. 13. The system of claim 12 , wherein the feature function comprises a boolean function that outputs a predetermined boolean output for the given n-gram when the given n-gram was observed within the behavioral trace. | 0.559263 |
7. An apparatus for performing bilingual word alignment on source and target text in bilingual documents, comprising: a link gain computation module for computing a probability gain of adding a link between any source and target words in the source and target text, and selecting all links having positive gains; a word alignment search module for using a greedy algorithm to iteratively search for a plurality of word alignments that satisfy an inversion transduction grammar constraint, the word alignment search module further including: a pending list initializing unit for initializing a pending list; a local list generation unit for expanding word alignments in the pending list, and generating a local list; and a branch selecting unit for determining whether to return to the local list generation unit; and a word alignment result output module for outputting a best word alignment measured by quality among the plurality. | 7. An apparatus for performing bilingual word alignment on source and target text in bilingual documents, comprising: a link gain computation module for computing a probability gain of adding a link between any source and target words in the source and target text, and selecting all links having positive gains; a word alignment search module for using a greedy algorithm to iteratively search for a plurality of word alignments that satisfy an inversion transduction grammar constraint, the word alignment search module further including: a pending list initializing unit for initializing a pending list; a local list generation unit for expanding word alignments in the pending list, and generating a local list; and a branch selecting unit for determining whether to return to the local list generation unit; and a word alignment result output module for outputting a best word alignment measured by quality among the plurality. 12. The apparatus according to claim 7 , wherein the quality of a word alignment is measured as a product of all probability values Π(j,i) p(f j , e i ) that are members of set a, and for any pair of f j and e i that have a link between them, and all probability values Π(i) p(ε, e i ) that are not members of set a, and for any source word that is not aligned to any word, and all probability values Π(j) p(f j , ε) that are not members of set a, for any target word that is not aligned to any word, where p(f j , e i ) is a probability of e i that is aligned to f j ; p(ε, e i ) is a probability of e i that is not aligned to any word; and p(f j , ε) is a probability of f j that is not aligned to any word. | 0.556611 |
1. A method, comprising: accessing, by one or more processing devices, a set of events, wherein each event in the set of events is associated with a time stamp and includes a portion of machine data indicative of performance or operation of an information technology environment; accessing an object-scoring rule that (i) includes a search query that determines when events meet a triggering condition; (ii) identifies an object representing a component of the information technology environment, an application running in the information technology environment, or a person using a component in the information technology environment, and (iii) specifies a numerical contribution to a score for the object, the numerical contribution to be applied to the score based at least on part on a determination that the triggering condition is met; executing the search query of the object-scoring rule against the set of events to determine if the triggering condition of the object-scoring rule is met; based on determining that the triggering condition is met, generating a record of the numerical contribution specified in the object-scoring rule, the record associating the numerical contribution with a time indicator and indicating the object whose score should be affected by the contribution; identifying, using one or more records of numerical contributions, a set of numerical contributions having associated time indicators falling within a defined time period; and calculating the score for the object based on the set of numerical contributions, wherein the score indicates at least one of: an indication of a security risk posed by the component or person that the object represents, an indication of performance of the component of the information technology environment that the object represents, or an indication of performance of the application that the object represents. | 1. A method, comprising: accessing, by one or more processing devices, a set of events, wherein each event in the set of events is associated with a time stamp and includes a portion of machine data indicative of performance or operation of an information technology environment; accessing an object-scoring rule that (i) includes a search query that determines when events meet a triggering condition; (ii) identifies an object representing a component of the information technology environment, an application running in the information technology environment, or a person using a component in the information technology environment, and (iii) specifies a numerical contribution to a score for the object, the numerical contribution to be applied to the score based at least on part on a determination that the triggering condition is met; executing the search query of the object-scoring rule against the set of events to determine if the triggering condition of the object-scoring rule is met; based on determining that the triggering condition is met, generating a record of the numerical contribution specified in the object-scoring rule, the record associating the numerical contribution with a time indicator and indicating the object whose score should be affected by the contribution; identifying, using one or more records of numerical contributions, a set of numerical contributions having associated time indicators falling within a defined time period; and calculating the score for the object based on the set of numerical contributions, wherein the score indicates at least one of: an indication of a security risk posed by the component or person that the object represents, an indication of performance of the component of the information technology environment that the object represents, or an indication of performance of the application that the object represents. 24. The method of claim 1 , further comprising: sending a message comprising the score for the object. | 0.920525 |
3. A computer-implemented method for training a human searcher for use with a computer, comprising: consulting a searcher database to monitor a busy status of a searcher; determining whether the searcher is a pro searcher when the searcher status indicates that the searcher is idle; determining whether an apprentice searcher is logged-in; receiving a training request from a master searcher; alerting said apprentice searcher, a pro searcher, or a master searcher to which training is to be provided with a message to participate in query training said alerting emulating processing of a user request; obtaining a training query from a query database at a searcher ranking and matching keywords to which said apprentice searcher, said pro searcher, or said master searcher is assigned; receiving from said apprentice searcher, said pro searcher, or said master searcher, an acceptance of the training query as the user request; determining whether the training query has been previously provided to said apprentice searcher, said pro searcher, or said master searcher; transmitting the training query to emulate a request from a user to said apprentice searcher, said pro searcher, or said master searcher when the searcher is selected to participate in query training when determining that the training query has not been previously provided to said apprentice searcher, said pro searcher, or said master searcher; comparing search results produced by said apprentice searcher, said pro searcher, or said master searcher to previously provided search results; assigning a grade to said apprentice searcher, said pro searcher, or said master searcher; sending feedback to said apprentice searcher, said pro searcher, or said master searcher regarding performance when determining that a user provides feedback for the user request; marking the training query as completed for said apprentice searcher, said pro searcher, or said master searcher; determining whether ranking of said apprentice searcher, said pro searcher, or said master searcher requires adjustment; and adjusting rank of said apprentice searcher, said pro searcher, or said master searcher based on said determining. | 3. A computer-implemented method for training a human searcher for use with a computer, comprising: consulting a searcher database to monitor a busy status of a searcher; determining whether the searcher is a pro searcher when the searcher status indicates that the searcher is idle; determining whether an apprentice searcher is logged-in; receiving a training request from a master searcher; alerting said apprentice searcher, a pro searcher, or a master searcher to which training is to be provided with a message to participate in query training said alerting emulating processing of a user request; obtaining a training query from a query database at a searcher ranking and matching keywords to which said apprentice searcher, said pro searcher, or said master searcher is assigned; receiving from said apprentice searcher, said pro searcher, or said master searcher, an acceptance of the training query as the user request; determining whether the training query has been previously provided to said apprentice searcher, said pro searcher, or said master searcher; transmitting the training query to emulate a request from a user to said apprentice searcher, said pro searcher, or said master searcher when the searcher is selected to participate in query training when determining that the training query has not been previously provided to said apprentice searcher, said pro searcher, or said master searcher; comparing search results produced by said apprentice searcher, said pro searcher, or said master searcher to previously provided search results; assigning a grade to said apprentice searcher, said pro searcher, or said master searcher; sending feedback to said apprentice searcher, said pro searcher, or said master searcher regarding performance when determining that a user provides feedback for the user request; marking the training query as completed for said apprentice searcher, said pro searcher, or said master searcher; determining whether ranking of said apprentice searcher, said pro searcher, or said master searcher requires adjustment; and adjusting rank of said apprentice searcher, said pro searcher, or said master searcher based on said determining. 12. The computer-implemented method of claim 3 , further comprising, prior to said consulting, accepting an election by said searcher to respond to user queries associated with a keyword of a generated query. | 0.506321 |
1. At a computer system including a processor and system memory, a method for generating a Web based user-interface for interacting with a database, the method comprising: an act of accessing a schema that defines a plurality tables in the database, the schema also defining relationships between fields in the plurality of tables of the database, definition of field relationships by the schema including defining a foreign key relationship from a first table to a second table of the database indicative of a key field in the first table identifying records in the second table; an act of converting the schema, including the foreign key relationship, into source code, the source code including classes and subclasses that represent relationships between the plurality of tables and fields defined in accordance with the schema; annotating the source code with a metadata annotation representing the foreign key relationship from the first table to the second table, the metadata annotation indicating the basis for creation of any classes or subclasses based on the foreign key relationship indicative of a key field in the first table identifying records in the second table; an act of generating executable code from the source code, including: compiling classes and subclasses of the source code into executable code of a dynamic link library, the executable code obscuring any indication of the relationships between the plurality of tables and fields in the database in the source code; and retaining the metadata annotations from the source code in the executable code of the dynamic link library, including a metadata annotation representing the foreign key relationship indicative of a key field in the first table identifying records in the second table; an act of identifying the metadata annotations from within the executable code of the dynamic link library, including the metadata annotation representing the foreign key relationship indicative of a key field in the first table identifying records in the second table, for use in creating a database mapping for the database; an act of the processor creating a database mapping for the database from the metadata annotations, the database mapping describing the configuration of the database such that the database mapping is based on the schema and retains an indication of the foreign key relationship indicative of a key field in the first table identifying records in the second table in a format processable by a Web site generator; an act of the Web site generator inferring, from the existence of the foreign key relationship from the first table to the second table, that a relationship from the second table back to the first table is also relevant to navigating Web based forms that present data from the database, even though a relationship from the second table to the first table is not expressly described in the schema, the inferred relationship for use in generating additional functionality in a Web site for the database permitting traversal of a navigable link from the second table back to the first table; and an act of the Web site generator generating a Web site for the database in accordance with the database mapping, the Web site including at least one navigable link from the second table back to the first table based on the inferred relationship, the at least one navigable link implementing the inferred relationship from the second table back to the first table, the Web site configured to provide a plurality of navigable linked Web based forms for interacting with the tables and fields of the database, including a first Web based form for interacting with data from the second table, the first Web based form configured with a navigable link that can be selected to automatically formulate a dynamic query for querying database records from the first table in the context of a row from the second table. | 1. At a computer system including a processor and system memory, a method for generating a Web based user-interface for interacting with a database, the method comprising: an act of accessing a schema that defines a plurality tables in the database, the schema also defining relationships between fields in the plurality of tables of the database, definition of field relationships by the schema including defining a foreign key relationship from a first table to a second table of the database indicative of a key field in the first table identifying records in the second table; an act of converting the schema, including the foreign key relationship, into source code, the source code including classes and subclasses that represent relationships between the plurality of tables and fields defined in accordance with the schema; annotating the source code with a metadata annotation representing the foreign key relationship from the first table to the second table, the metadata annotation indicating the basis for creation of any classes or subclasses based on the foreign key relationship indicative of a key field in the first table identifying records in the second table; an act of generating executable code from the source code, including: compiling classes and subclasses of the source code into executable code of a dynamic link library, the executable code obscuring any indication of the relationships between the plurality of tables and fields in the database in the source code; and retaining the metadata annotations from the source code in the executable code of the dynamic link library, including a metadata annotation representing the foreign key relationship indicative of a key field in the first table identifying records in the second table; an act of identifying the metadata annotations from within the executable code of the dynamic link library, including the metadata annotation representing the foreign key relationship indicative of a key field in the first table identifying records in the second table, for use in creating a database mapping for the database; an act of the processor creating a database mapping for the database from the metadata annotations, the database mapping describing the configuration of the database such that the database mapping is based on the schema and retains an indication of the foreign key relationship indicative of a key field in the first table identifying records in the second table in a format processable by a Web site generator; an act of the Web site generator inferring, from the existence of the foreign key relationship from the first table to the second table, that a relationship from the second table back to the first table is also relevant to navigating Web based forms that present data from the database, even though a relationship from the second table to the first table is not expressly described in the schema, the inferred relationship for use in generating additional functionality in a Web site for the database permitting traversal of a navigable link from the second table back to the first table; and an act of the Web site generator generating a Web site for the database in accordance with the database mapping, the Web site including at least one navigable link from the second table back to the first table based on the inferred relationship, the at least one navigable link implementing the inferred relationship from the second table back to the first table, the Web site configured to provide a plurality of navigable linked Web based forms for interacting with the tables and fields of the database, including a first Web based form for interacting with data from the second table, the first Web based form configured with a navigable link that can be selected to automatically formulate a dynamic query for querying database records from the first table in the context of a row from the second table. 3. The method as recited in claim 1 , wherein the act of inferring, from the existence of the foreign key relationship, that a relationship from the second table back to the first second table is also relevant comprising an act of inferring that values for a field in the second table represented by the foreign key in the first table can be included in a plurality of rows in the first table. | 0.5 |
7. An apparatus for authenticating a user within a data processing system to enable the user to access a controlled resource, the apparatus comprising: a processor; a computer memory holding computer program instructions which when executed by the processor perform a method comprising: generating an authentication assertion for the user at a first trust proxy within a first domain; at a system in a second domain, receiving a request from a client to access a controlled resource within the second domain; sending the authentication assertion from the first domain to a second trust proxy in the second domain by the second trust proxy pulling the authentication assertion from the first trust proxy after receipt at the system in the second domain of the request for the controlled resource; validating the authentication assertion at the second trust proxy in the second domain; upon validating the authentication assertion, building a session for the user so that the user appears to the system in the second domain as an authenticated user; and providing access to the controlled resource using the session. | 7. An apparatus for authenticating a user within a data processing system to enable the user to access a controlled resource, the apparatus comprising: a processor; a computer memory holding computer program instructions which when executed by the processor perform a method comprising: generating an authentication assertion for the user at a first trust proxy within a first domain; at a system in a second domain, receiving a request from a client to access a controlled resource within the second domain; sending the authentication assertion from the first domain to a second trust proxy in the second domain by the second trust proxy pulling the authentication assertion from the first trust proxy after receipt at the system in the second domain of the request for the controlled resource; validating the authentication assertion at the second trust proxy in the second domain; upon validating the authentication assertion, building a session for the user so that the user appears to the system in the second domain as an authenticated user; and providing access to the controlled resource using the session. 10. The apparatus of claim 7 wherein the method further comprises: maintaining an indirect relationship between the first trust proxy and the second trust proxy through a trust broker. | 0.66219 |
17. A system for analyzing messages in a computer system to allow workflows constituted by the messages to be identified, the system comprising: at least one processor; and a memory coupled to the at least one processor and configured to store computer instructions that, when executed, cause the processor to perform a method of analyzing messages in a computer system to allow workflows constituted by the messages to be identified, the method comprising: analyzing a sequence of messages in a computer system to classify each of the messages and produce a corresponding sequence of classifications of the messages; and applying sequence induction to the sequence of classifications of the messages and determining a temporal proximity of classifications in the sequence of classifications to produce a set of sub-sequences of the classifications of the messages and a sequence grammar for the sub-sequences, from which a workflow constituted by the sequence of messages is identified in order to create a control policy stored in the computer system; receiving a new sequence of messages; comparing the new sequence of messages with the workflow in the control policy; and in response to the new sequence of messages being acceptable by the control policy, sending an output message sequence to a destination computer resource, and wherein in response to the new sequence of messages requiring further action in accordance with the control policy, sending an alternative output message sequence to the destination computer resource. | 17. A system for analyzing messages in a computer system to allow workflows constituted by the messages to be identified, the system comprising: at least one processor; and a memory coupled to the at least one processor and configured to store computer instructions that, when executed, cause the processor to perform a method of analyzing messages in a computer system to allow workflows constituted by the messages to be identified, the method comprising: analyzing a sequence of messages in a computer system to classify each of the messages and produce a corresponding sequence of classifications of the messages; and applying sequence induction to the sequence of classifications of the messages and determining a temporal proximity of classifications in the sequence of classifications to produce a set of sub-sequences of the classifications of the messages and a sequence grammar for the sub-sequences, from which a workflow constituted by the sequence of messages is identified in order to create a control policy stored in the computer system; receiving a new sequence of messages; comparing the new sequence of messages with the workflow in the control policy; and in response to the new sequence of messages being acceptable by the control policy, sending an output message sequence to a destination computer resource, and wherein in response to the new sequence of messages requiring further action in accordance with the control policy, sending an alternative output message sequence to the destination computer resource. 18. The system of claim 17 wherein the sequence of messages is analyzed and the messages are classified by clustering the messages according to the semantic intent of the messages. | 0.5 |
1. A computer-implemented method for automatically ranking product reviews relating to a product of interest stored in a computer-readable memory according to the estimated helpfulness of the product reviews, said method comprising: identifying dominant lexical terms in the product reviews; using the dominant lexical terms to define a feature vector representation; converting the product reviews to said feature vector representation; and ranking the product reviews according to the distance of the product reviews from a ‘locally optimal’ review vector; wherein: lexical terms are assigned a dominance score based on statistical occurrence of words in the product reviews and general literature that is not specific to the subject matter of the product reviews; the dominance score of lexical terms that appear in the product reviews and are also commonly found in the general literature are assigned different values compared to lexical terms that appear in the product reviews but are not commonly found in the general literature; and the dominance score Di(t) of a lexical item t in a layer i is given by: Di ( t ) = fRi ( t ) · c · 1 log B ( t ) where fRi(t) is the frequency of t in Ri, B(t) is the average number of times t appears per one million words in the balanced corpus, and c is a factor used to control the level of dominance; so as to capture key concepts that are dominant in the collection Ri, balancing bias induced by frequent words, capturing words of different semantic types and capturing words that are dominant but infrequent. | 1. A computer-implemented method for automatically ranking product reviews relating to a product of interest stored in a computer-readable memory according to the estimated helpfulness of the product reviews, said method comprising: identifying dominant lexical terms in the product reviews; using the dominant lexical terms to define a feature vector representation; converting the product reviews to said feature vector representation; and ranking the product reviews according to the distance of the product reviews from a ‘locally optimal’ review vector; wherein: lexical terms are assigned a dominance score based on statistical occurrence of words in the product reviews and general literature that is not specific to the subject matter of the product reviews; the dominance score of lexical terms that appear in the product reviews and are also commonly found in the general literature are assigned different values compared to lexical terms that appear in the product reviews but are not commonly found in the general literature; and the dominance score Di(t) of a lexical item t in a layer i is given by: Di ( t ) = fRi ( t ) · c · 1 log B ( t ) where fRi(t) is the frequency of t in Ri, B(t) is the average number of times t appears per one million words in the balanced corpus, and c is a factor used to control the level of dominance; so as to capture key concepts that are dominant in the collection Ri, balancing bias induced by frequent words, capturing words of different semantic types and capturing words that are dominant but infrequent. 5. The method according to claim 1 , wherein the first lexicon is computed as:
L i =( L i I ∩ L i+1 I )/( L i+l I # L i−1 I ) where L i I is an initial lexicon for layer i and L i is a final, ‘clean’ lexicon for layer i. | 0.547662 |
12. A system for automatically identifying and filling in source code snippets based upon a context of a user in a development environment, the system comprising: one or more processors configured to provide: a code editor that accepts user input comprising source code; a code modification command set that: identifies an existing code snippet associated with the user's current context within the development environment; duplicates and inserts the code snippet into the code editor and automatically customizes the code snippet based upon the code modification command set used by replacing one or more characters in the snippet with user indicated characters; electronic memory that stores textual information including existing code snippets and transformed code snippets; and an electronic display that displays textual information including existing code snippets and transformed code snippets, the electronic display comprising a plurality of light emitting circuits; wherein said code modification command set transforms a portion of said plurality of light emitting circuits to display customized code snippets. | 12. A system for automatically identifying and filling in source code snippets based upon a context of a user in a development environment, the system comprising: one or more processors configured to provide: a code editor that accepts user input comprising source code; a code modification command set that: identifies an existing code snippet associated with the user's current context within the development environment; duplicates and inserts the code snippet into the code editor and automatically customizes the code snippet based upon the code modification command set used by replacing one or more characters in the snippet with user indicated characters; electronic memory that stores textual information including existing code snippets and transformed code snippets; and an electronic display that displays textual information including existing code snippets and transformed code snippets, the electronic display comprising a plurality of light emitting circuits; wherein said code modification command set transforms a portion of said plurality of light emitting circuits to display customized code snippets. 14. The system of claim 12 , wherein the customization of the code snippet includes complex operations based on conditions as specified in the command set, the complex operations being performed by a logic processor in electronic communication with an electronic memory. | 0.678346 |
21. An apparatus that recognizes voice input, comprising: a receiving mechanism configured to receive a document that includes a specification of a datatype for which there exists a predefined grammar, wherein the document that includes the specification of the datatype is a Multi-channel extensible Markup Language (MXML) document; a generation mechanism configured to generate a Voice eXtensible Markup Language (VoiceXML) document from the MXML document; wherein the receiving mechanism is additionally configured to obtain a locale attribute for the datatype, wherein the locale attribute identifies a version of a language that is spoken in a locale; a lookup mechanism configured to use the locale attribute to lookup a locale-specific grammar for the datatype; and a communication mechanism configured to communicate the locale-specific grammar to a speech recognition engine, wherein the locale-specific grammar comprises a gateway-specific transformer that is produced by a gateway driver, wherein the gateway driver is incorporated into a transformation framework, thereby allowing the speech recognition engine to use the locale-specific grammar in recognizing a voice input for the datatype; wherein communicating the locale-specific grammar fully specifies the set of phrases that can be recognized for the datatype. | 21. An apparatus that recognizes voice input, comprising: a receiving mechanism configured to receive a document that includes a specification of a datatype for which there exists a predefined grammar, wherein the document that includes the specification of the datatype is a Multi-channel extensible Markup Language (MXML) document; a generation mechanism configured to generate a Voice eXtensible Markup Language (VoiceXML) document from the MXML document; wherein the receiving mechanism is additionally configured to obtain a locale attribute for the datatype, wherein the locale attribute identifies a version of a language that is spoken in a locale; a lookup mechanism configured to use the locale attribute to lookup a locale-specific grammar for the datatype; and a communication mechanism configured to communicate the locale-specific grammar to a speech recognition engine, wherein the locale-specific grammar comprises a gateway-specific transformer that is produced by a gateway driver, wherein the gateway driver is incorporated into a transformation framework, thereby allowing the speech recognition engine to use the locale-specific grammar in recognizing a voice input for the datatype; wherein communicating the locale-specific grammar fully specifies the set of phrases that can be recognized for the datatype. 26. The apparatus of claim 21 , wherein the locale-specific grammar identifies a standard set of phrases to be recognized by the speech recognition engine while receiving voice input for the datatype. | 0.606445 |
1. A method performed on at least one computing device that includes at least one processor and memory, the method comprising: substantially simultaneously providing, by the at least one computing device in response to receiving one or more characters that form at least a portion of a query string that does not include an explicit submission of the portion of the query string, both query results and query refinement options, where the one or more received characters match at least one pattern that indicates one or more characters followed by a space character. | 1. A method performed on at least one computing device that includes at least one processor and memory, the method comprising: substantially simultaneously providing, by the at least one computing device in response to receiving one or more characters that form at least a portion of a query string that does not include an explicit submission of the portion of the query string, both query results and query refinement options, where the one or more received characters match at least one pattern that indicates one or more characters followed by a space character. 5. The method of claim 1 where the providing the query refinement options is in response to the receiving but prior to detecting the match. | 0.786585 |
16. A system comprising: memory storing instructions that are executable, and one or more processing devices to execute the instructions to implement elements comprising: an indexing engine to generate a search index; and a data engine to use the search index to identify a topic relating to text, the data engine comprising instructions that are executable to perform operations comprising: receiving the text into a first display field; performing a search of the search index to identify a topic relating to the text, the topic being among plural topics being discussed on a social networking service; identifying discussions on the social network service, the discussions relating to the topic; retrieving, from the search index, the tags for discussions that relate to the topic; ranking the tags for the discussions that relate to the topic based, at least in part, on popularity of the discussions on the social networking service, a popularity of a discussion is based, at least in part, on an amount of participation in the discussion; suggesting, to a user in an interface, in an order and based on the ranking, ranked tags for the first display field that promote posting to the discussions identified by the tags, with a first tag among the ranked tags relating to a first discussion topic having a first amount of participation, a second tag among the ranked tags relating to a second discussion topic having a second amount of participation, the first tag ranked higher, relative to a ranking of the second tag, based on the first amount exceeding the second amount, wherein suggesting comprises: selecting the first, higher ranked tag from among the ranked tags in the interface; and automatically incorporating the first, higher ranked tag into the first display field; and enabling, through the interface, the user to accept or reject the first, higher ranked tag that was automatically incorporated into the first display field, wherein, if the user rejects the first, higher ranked tag, the first, higher ranked tag is removed from the first display field. | 16. A system comprising: memory storing instructions that are executable, and one or more processing devices to execute the instructions to implement elements comprising: an indexing engine to generate a search index; and a data engine to use the search index to identify a topic relating to text, the data engine comprising instructions that are executable to perform operations comprising: receiving the text into a first display field; performing a search of the search index to identify a topic relating to the text, the topic being among plural topics being discussed on a social networking service; identifying discussions on the social network service, the discussions relating to the topic; retrieving, from the search index, the tags for discussions that relate to the topic; ranking the tags for the discussions that relate to the topic based, at least in part, on popularity of the discussions on the social networking service, a popularity of a discussion is based, at least in part, on an amount of participation in the discussion; suggesting, to a user in an interface, in an order and based on the ranking, ranked tags for the first display field that promote posting to the discussions identified by the tags, with a first tag among the ranked tags relating to a first discussion topic having a first amount of participation, a second tag among the ranked tags relating to a second discussion topic having a second amount of participation, the first tag ranked higher, relative to a ranking of the second tag, based on the first amount exceeding the second amount, wherein suggesting comprises: selecting the first, higher ranked tag from among the ranked tags in the interface; and automatically incorporating the first, higher ranked tag into the first display field; and enabling, through the interface, the user to accept or reject the first, higher ranked tag that was automatically incorporated into the first display field, wherein, if the user rejects the first, higher ranked tag, the first, higher ranked tag is removed from the first display field. 17. The system of claim 16 , wherein the plural topics have different levels of popularity on the social networking service; and wherein ranking comprises ranking tags of discussion topics that have more than a number of members as being more relevant than tags of discussion topics that have more than the number of members. | 0.5 |
1. A method for approximate named-entity extraction from a dictionary comprising a plurality of entries, each of the entries including one or more words, the method comprising: reading a plurality of the words from the entries of the dictionary; searching network resources to determine a frequency of occurrence of the words on the network resources; in view of the frequency of occurrence of the words located on the network resources, determining domain relevancy of the words in the entries of the dictionary; creating a domain repository using top-ranked words as determined by the domain relevancy of the words; in view of the domain repository, computing signatures for both the entries of the dictionary and strings of an input document as representative strings that capture domain-related information based on a domain knowledge base; filtering the strings of the input document by comparing the signatures of the strings against the signatures of the entries to identify approximate-match entity names, the filtering further comprising: storing the signatures for the entries in a signature Bloom filter, wherein comparing the signatures of the strings is performed against the signatures of the entries in the signature Bloom filter; creating a length-based inverted index as a list of unique tokens from the dictionary indicating the entries where the tokens occur, the signatures of the entries, and a number of tokens per entry; and narrowing a search range when filtering the strings using the length-based inverted index to identify approximate matches having matching signatures and a similar length in view of the number of tokens per entry compared to a number of tokens per string of the input document as bounded by a parameter that establishes the search range relative to the number of tokens per string of the input document; and generating a list of the approximate-match entity names as identified based on the filtering. | 1. A method for approximate named-entity extraction from a dictionary comprising a plurality of entries, each of the entries including one or more words, the method comprising: reading a plurality of the words from the entries of the dictionary; searching network resources to determine a frequency of occurrence of the words on the network resources; in view of the frequency of occurrence of the words located on the network resources, determining domain relevancy of the words in the entries of the dictionary; creating a domain repository using top-ranked words as determined by the domain relevancy of the words; in view of the domain repository, computing signatures for both the entries of the dictionary and strings of an input document as representative strings that capture domain-related information based on a domain knowledge base; filtering the strings of the input document by comparing the signatures of the strings against the signatures of the entries to identify approximate-match entity names, the filtering further comprising: storing the signatures for the entries in a signature Bloom filter, wherein comparing the signatures of the strings is performed against the signatures of the entries in the signature Bloom filter; creating a length-based inverted index as a list of unique tokens from the dictionary indicating the entries where the tokens occur, the signatures of the entries, and a number of tokens per entry; and narrowing a search range when filtering the strings using the length-based inverted index to identify approximate matches having matching signatures and a similar length in view of the number of tokens per entry compared to a number of tokens per string of the input document as bounded by a parameter that establishes the search range relative to the number of tokens per string of the input document; and generating a list of the approximate-match entity names as identified based on the filtering. 5. The method of claim 1 , comprising: determining a longest entry length of the entries in the dictionary; and ignoring the strings of the input document that are longer than the longest entry length. | 0.529397 |
1. A collaborative first order logic system with dynamic ontology comprising: a server computer; a database coupled with said server and configured to store information related to documents; subjects associated with said documents; associations between said subjects; assertions associated with said subjects; opinions regarding said assertions; theorems associated with said assertions; a website coupled with said server computer wherein said website is configured to display said documents; display said subjects associated with said documents; display said associations between said subjects; display said assertions associated with said subjects; display said opinions regarding said assertions; accept input from a plurality of users including a first user and a second user to alter said associations between said subjects; command said server computer to alter said associations between said subjects in said database; accept an opinion from said first user related to said assertion associated with one or more subjects wherein said assertion is made by said second user; and, wherein said server computer is configured to analyze said assertions and display any logical contradictions with said theorems. | 1. A collaborative first order logic system with dynamic ontology comprising: a server computer; a database coupled with said server and configured to store information related to documents; subjects associated with said documents; associations between said subjects; assertions associated with said subjects; opinions regarding said assertions; theorems associated with said assertions; a website coupled with said server computer wherein said website is configured to display said documents; display said subjects associated with said documents; display said associations between said subjects; display said assertions associated with said subjects; display said opinions regarding said assertions; accept input from a plurality of users including a first user and a second user to alter said associations between said subjects; command said server computer to alter said associations between said subjects in said database; accept an opinion from said first user related to said assertion associated with one or more subjects wherein said assertion is made by said second user; and, wherein said server computer is configured to analyze said assertions and display any logical contradictions with said theorems. 4. The collaborative first order logic system with dynamic ontology of claim 1 wherein said website is configured to display said assertions associated with one or more subject with respect to locations of said plurality of users over a defined time period to display how said assertions have changed over time. | 0.782822 |
1. A process for monitoring, scoring and providing feedback on written text, the process comprising: receiving a student development language selection and a feedback prompt mode selection from a user; providing a writing assignment to said user in a student development language corresponding to said student development language selection; monitoring written text input by said user for the writing assignment in said student development language; scoring, by a processor, said monitored written text to produce at least one score; providing feedback prompts, via said processor, that include writing improvement instructions for improving said monitored written text input by said user, wherein said feedback prompts are selected as a function of said student development language selection, student proficiency level, said feedback prompt mode selection, and said at least one score for said monitored written text. | 1. A process for monitoring, scoring and providing feedback on written text, the process comprising: receiving a student development language selection and a feedback prompt mode selection from a user; providing a writing assignment to said user in a student development language corresponding to said student development language selection; monitoring written text input by said user for the writing assignment in said student development language; scoring, by a processor, said monitored written text to produce at least one score; providing feedback prompts, via said processor, that include writing improvement instructions for improving said monitored written text input by said user, wherein said feedback prompts are selected as a function of said student development language selection, student proficiency level, said feedback prompt mode selection, and said at least one score for said monitored written text. 18. The process of claim 1 , wherein the at least one score includes at least one domain score and at least one editing score. | 0.683322 |
3. The method of claim 1 , wherein the automated response includes an option to speak with a live agent. | 3. The method of claim 1 , wherein the automated response includes an option to speak with a live agent. 4. The method of claim 3 , wherein if the user elects to speak with a live agent, the user is given a high priority for a live agent. | 0.959517 |
1. A method of processing an incoming voice message, the method comprising: at a recipient system, receiving an incoming voice message from a message communicator; using a processor to automatically analyze message content of the incoming voice message to identity at least one keyword included in the message content, the message content analysis being performed while a caller is connected with the message communicator; identifying a predefined action associated with the at least one keyword, the predefined action including associating a priority with the incoming voice message; and performing the predefined action when the at least one keyword is identified in the message content, the predefined action including a search action wherein the message content includes a spoken search term used to obtain an equivalent textual search term which is used to search a database of stored incoming voice messages for the textual equivalent search term to identify any stored incoming voice messages including the spoken search term. | 1. A method of processing an incoming voice message, the method comprising: at a recipient system, receiving an incoming voice message from a message communicator; using a processor to automatically analyze message content of the incoming voice message to identity at least one keyword included in the message content, the message content analysis being performed while a caller is connected with the message communicator; identifying a predefined action associated with the at least one keyword, the predefined action including associating a priority with the incoming voice message; and performing the predefined action when the at least one keyword is identified in the message content, the predefined action including a search action wherein the message content includes a spoken search term used to obtain an equivalent textual search term which is used to search a database of stored incoming voice messages for the textual equivalent search term to identify any stored incoming voice messages including the spoken search term. 2. The method of claim 1 , wherein the predefined action is selected from the group consisting of alerting an intended recipient of the incoming voice message, routing the incoming voice message to the intended recipient, paging the intended recipient, entailing the incoming voice message to the intended recipient, and sending an SMS message to the intended recipient. | 0.505192 |
45. The method of claim 44 , wherein gathering switching data from previous queries comprises: identifying possible query phrases from the previous queries; and generating probabilities of switching between query phrases based on patterns observed in the previous queries; wherein the switching probabilities are used to determine whether a switched query phrase will be considered as a candidate synonym for a query phrase. | 45. The method of claim 44 , wherein gathering switching data from previous queries comprises: identifying possible query phrases from the previous queries; and generating probabilities of switching between query phrases based on patterns observed in the previous queries; wherein the switching probabilities are used to determine whether a switched query phrase will be considered as a candidate synonym for a query phrase. 46. The method of claim 45 , wherein gathering switching data comprises gathering context data for other terms located in proximity to query terms or query phrases in previous queries; and wherein generating the probabilities of switching between query phrases comprises using the context data to consider conditional probabilities. | 0.755704 |
14. A processor-based database system, comprising: a memory configured to store modules comprising: a first module configured to identify a set of rows that satisfy local conditions to a table prior to an execution of a query; a second module configured to generate a data structure based on an actual effect of the local conditions on the table comprising one or more bits, each bit representing a row in the set of identified rows, a value of each bit indicating whether its respective row satisfies the local conditions to the table; a third module configured to modify the query based on the generated data structure, wherein the third module is further configured to identify a quantity of rows that satisfy the local conditions by: a module operable to identify whether there are no rows that satisfy the local conditions in the data structure; a module operable to identify whether there is exactly one row that satisfies the local conditions for contents of cell values in the exactly one row in the data structure; and a module operable to identify whether there are a moderate number of rows that satisfy the local conditions for contents of cell values in the moderate number of rows in the data structure and wherein the third module is further configured to modify the query based on the identifying the quantity of rows; and a fourth module configured to process the modified query to generate an execution plan for the query, wherein the first module, the second module, the third module and the fourth module are implemented on one or more processors of the system. | 14. A processor-based database system, comprising: a memory configured to store modules comprising: a first module configured to identify a set of rows that satisfy local conditions to a table prior to an execution of a query; a second module configured to generate a data structure based on an actual effect of the local conditions on the table comprising one or more bits, each bit representing a row in the set of identified rows, a value of each bit indicating whether its respective row satisfies the local conditions to the table; a third module configured to modify the query based on the generated data structure, wherein the third module is further configured to identify a quantity of rows that satisfy the local conditions by: a module operable to identify whether there are no rows that satisfy the local conditions in the data structure; a module operable to identify whether there is exactly one row that satisfies the local conditions for contents of cell values in the exactly one row in the data structure; and a module operable to identify whether there are a moderate number of rows that satisfy the local conditions for contents of cell values in the moderate number of rows in the data structure and wherein the third module is further configured to modify the query based on the identifying the quantity of rows; and a fourth module configured to process the modified query to generate an execution plan for the query, wherein the first module, the second module, the third module and the fourth module are implemented on one or more processors of the system. 19. The processor-based database system of claim 14 , wherein the identifying the moderate number of rows module comprises: a module operable to infer an IN condition when a column from the table is used with a join condition. | 0.624845 |
18. The method of claim 17 , further comprising: creating a partition for each variable in the expression tree; identifying equivalent variables in the expression tree; and merging partitions containing equivalent variables. | 18. The method of claim 17 , further comprising: creating a partition for each variable in the expression tree; identifying equivalent variables in the expression tree; and merging partitions containing equivalent variables. 19. The method of claim 18 , further comprising determining if any remaining partitions contain non-null unique keys. | 0.935413 |
1. A method for determining social media influencers in a specific topic, the method comprising: receiving, by a processor, a dataset of information associated with a website, the information including a first list of users of the website and a list of content that each user posts on the website, wherein each user is associated with one or more other users from the first list of users; determining, by a processor, initial values representing variables of the dataset of information on the website, wherein the variables include one or more topics for the list of content that each user from the first list of users posts on the website; performing, by a processor, one or more iterations of Gibbs Sampling utilizing the initial values, wherein performing each of the one or more iterations assigns new values representing variables of the dataset; determining, by a processor, that the one or more new values representing variables of the dataset represent a distribution of the one or more topics for the list of content that each user from the first list of users posts; executing, by a processor, a topic specific search in a topic search engine based on the distribution of the one or more topics for the list of content that each user from the first list of users posts, the topic search providing a subset list of the first list of users representing influencers in a specific topic; identifying, by a processor, one or more topics in the list of content that each user of the first list of users posts on the website; determining, by a processor, the one or more topics do not exist in the topic search engine; creating, by a processor, the one or more topics in the topic search engine; identifying, by a processors, a list of keywords in the list of content that each user from the first list of users posts on the website; and consolidating, by a processor, the list of keywords. | 1. A method for determining social media influencers in a specific topic, the method comprising: receiving, by a processor, a dataset of information associated with a website, the information including a first list of users of the website and a list of content that each user posts on the website, wherein each user is associated with one or more other users from the first list of users; determining, by a processor, initial values representing variables of the dataset of information on the website, wherein the variables include one or more topics for the list of content that each user from the first list of users posts on the website; performing, by a processor, one or more iterations of Gibbs Sampling utilizing the initial values, wherein performing each of the one or more iterations assigns new values representing variables of the dataset; determining, by a processor, that the one or more new values representing variables of the dataset represent a distribution of the one or more topics for the list of content that each user from the first list of users posts; executing, by a processor, a topic specific search in a topic search engine based on the distribution of the one or more topics for the list of content that each user from the first list of users posts, the topic search providing a subset list of the first list of users representing influencers in a specific topic; identifying, by a processor, one or more topics in the list of content that each user of the first list of users posts on the website; determining, by a processor, the one or more topics do not exist in the topic search engine; creating, by a processor, the one or more topics in the topic search engine; identifying, by a processors, a list of keywords in the list of content that each user from the first list of users posts on the website; and consolidating, by a processor, the list of keywords. 2. The method of claim 1 , wherein the one or more new values statistically represent one or more topics for which each user associates with the one or more other users. | 0.636049 |
15. A computer-readable medium for testing compliance of a computing system, the computer-readable medium being non-transitory and storing a set of computer instructions executable by a computerized device to cause the computerized device to at least: receive a collection of rules in a first set of markup-language statements, the collection of rules representing a configuration benchmark against which a computing system is to be tested for compliance, the computing system having interconnected components including different types of hardware components; parse the collection of rules to obtain test references to tests and comparison values used therein, the tests being defined in a second set of markup-language statements, with references to at least some of the interconnected components and their attributes as represented in a database organized as an object model of the computing system, the object model expressing physical and functional relationships among the interconnected components including the different types of hardware components; and invoke an interpreter with the test references and comparison values to perform the tests defined in the second set of markup-language statements using the comparison values, performance of the tests including the computerized device being caused to: access the database using the references to the at least some of the interconnected components and their attributes to obtain actual values of their attributes; and perform the tests to generate results based on comparisons of the actual values and corresponding ones of the comparison values, the results indicating whether the computing system is compliant with the configuration benchmark. | 15. A computer-readable medium for testing compliance of a computing system, the computer-readable medium being non-transitory and storing a set of computer instructions executable by a computerized device to cause the computerized device to at least: receive a collection of rules in a first set of markup-language statements, the collection of rules representing a configuration benchmark against which a computing system is to be tested for compliance, the computing system having interconnected components including different types of hardware components; parse the collection of rules to obtain test references to tests and comparison values used therein, the tests being defined in a second set of markup-language statements, with references to at least some of the interconnected components and their attributes as represented in a database organized as an object model of the computing system, the object model expressing physical and functional relationships among the interconnected components including the different types of hardware components; and invoke an interpreter with the test references and comparison values to perform the tests defined in the second set of markup-language statements using the comparison values, performance of the tests including the computerized device being caused to: access the database using the references to the at least some of the interconnected components and their attributes to obtain actual values of their attributes; and perform the tests to generate results based on comparisons of the actual values and corresponding ones of the comparison values, the results indicating whether the computing system is compliant with the configuration benchmark. 20. The computer-readable medium of claim 15 , wherein the interconnected components further include different types of software components, and the object model expresses physical and functional relationships among the interconnected components including the different types of hardware components and the different types of software components, and wherein a rule of the collection of rules specifies a relationship between a hardware component and software component of respectively the different types of hardware components and the different types of software components, and a test of the tests is for compliance with the rule. | 0.5 |
1. A method for editing a test script for testing software comprising: a processor in communication with a database, the processor configured for: providing an application state stack that includes a plurality of consecutive states, each application state includes at least one test object; providing a test script that lists actions that the software under test is to execute, the test script including test methods, the test methods being associated with state transitions; receiving a request to modify the test script; creating a modified application state stack portion based on the modified test script; checking the integrity of the modified test script by ensuring that the modified application state stack portion can be integrated with at least a portion of the application state stack subsequent to the modified portion by analyzing the state transitions associated with test methods; and if the modified test script maintains integrity, allowing the modified test script to replace the test script and updating the application state stack with the application state stack integrated with the modified portion of the application state stack. | 1. A method for editing a test script for testing software comprising: a processor in communication with a database, the processor configured for: providing an application state stack that includes a plurality of consecutive states, each application state includes at least one test object; providing a test script that lists actions that the software under test is to execute, the test script including test methods, the test methods being associated with state transitions; receiving a request to modify the test script; creating a modified application state stack portion based on the modified test script; checking the integrity of the modified test script by ensuring that the modified application state stack portion can be integrated with at least a portion of the application state stack subsequent to the modified portion by analyzing the state transitions associated with test methods; and if the modified test script maintains integrity, allowing the modified test script to replace the test script and updating the application state stack with the application state stack integrated with the modified portion of the application state stack. 2. The method of claim 1 , wherein the test script is modified by appending an action to the end of the test script. | 0.506548 |
6. A method comprising: when a portable electronic device having a touch-sensitive display is disposed in a holster: monitoring, by the portable electronic device, an area of the touch-sensitive display for a query gesture that requests information; when the query gesture is detected on the touch-sensitive display and is associated with the area, communicating the information via tactile feedback provided by the portable electronic device. | 6. A method comprising: when a portable electronic device having a touch-sensitive display is disposed in a holster: monitoring, by the portable electronic device, an area of the touch-sensitive display for a query gesture that requests information; when the query gesture is detected on the touch-sensitive display and is associated with the area, communicating the information via tactile feedback provided by the portable electronic device. 20. The method of claim 6 , further comprising, by the portable electronic device, identifying an identifier associated with the holster and identifying the area based on the identifier. | 0.719219 |
8. A system for applying an update to a communication protocol in a software application, the system comprising: a memory for storing a first protocol definition corresponding to a communication protocol and a first machine-executable object parser configured to parse received data objects based on the communication protocol, wherein the first machine-executable object parser is associated with a first timestamp, and wherein the first machine-executable object parser is based on the first protocol definition, wherein the first protocol definition indicates positions of data elements within data objects corresponding to the communication protocol; a communications unit configured to receive a second protocol definition corresponding to the communication protocol, wherein the second protocol definition indicates positions of data elements within data objects corresponding to the communication protocol, and wherein the second protocol definition includes a second timestamp; and a processor unit coupled to the memory and the communication interface, the processor programmed to: execute the software application including the first machine-executable object parser, wherein the first machine-executable object parser is loaded in active memory of the system and is in communication with the software application; determine that the second protocol definition differs from the first protocol definition; determine that the second timestamp is newer than the first timestamp; upon determining that the second timestamp is newer than the first timestamp, automatically create a second machine-executable object parser based on the second protocol definition without pausing execution of the software application; replace the first machine-executable object parser in active memory with the second machine-executable object parser; receive by the software application a data object corresponding to the communication protocol; and execute the second machine-executable object parser to parse at least a portion of the data elements in the data object received by the software application and communicate the parsed data elements to the software application. | 8. A system for applying an update to a communication protocol in a software application, the system comprising: a memory for storing a first protocol definition corresponding to a communication protocol and a first machine-executable object parser configured to parse received data objects based on the communication protocol, wherein the first machine-executable object parser is associated with a first timestamp, and wherein the first machine-executable object parser is based on the first protocol definition, wherein the first protocol definition indicates positions of data elements within data objects corresponding to the communication protocol; a communications unit configured to receive a second protocol definition corresponding to the communication protocol, wherein the second protocol definition indicates positions of data elements within data objects corresponding to the communication protocol, and wherein the second protocol definition includes a second timestamp; and a processor unit coupled to the memory and the communication interface, the processor programmed to: execute the software application including the first machine-executable object parser, wherein the first machine-executable object parser is loaded in active memory of the system and is in communication with the software application; determine that the second protocol definition differs from the first protocol definition; determine that the second timestamp is newer than the first timestamp; upon determining that the second timestamp is newer than the first timestamp, automatically create a second machine-executable object parser based on the second protocol definition without pausing execution of the software application; replace the first machine-executable object parser in active memory with the second machine-executable object parser; receive by the software application a data object corresponding to the communication protocol; and execute the second machine-executable object parser to parse at least a portion of the data elements in the data object received by the software application and communicate the parsed data elements to the software application. 11. The system in accordance with claim 8 , wherein the processor is further programmed to: store in the memory the second machine-executable object parser; and execute the second machine-executable object parser to parse data elements in data objects received by the software application until a third protocol definition corresponding to the communication protocol and differing from the second protocol definition is received. | 0.503695 |
14. A computing device, comprising: a processor; a display screen; and memory including instructions that, when executed by the processor, cause the computing device to: obtain an image captured with an imaging element of the computing device; identify, within the image, a first region and a second region, the first region and the second region each containing text; determine that the first region has a first text quality associated with poor text recognition, and that the second region has a second text quality associated with acceptable text recognition; apply at least one image quality enhancement to the first region to improve text recognition within the first region, wherein the first text quality is improved to be associated with the acceptable text recognition; and causing the first region to be processed using a visual recognition technique. | 14. A computing device, comprising: a processor; a display screen; and memory including instructions that, when executed by the processor, cause the computing device to: obtain an image captured with an imaging element of the computing device; identify, within the image, a first region and a second region, the first region and the second region each containing text; determine that the first region has a first text quality associated with poor text recognition, and that the second region has a second text quality associated with acceptable text recognition; apply at least one image quality enhancement to the first region to improve text recognition within the first region, wherein the first text quality is improved to be associated with the acceptable text recognition; and causing the first region to be processed using a visual recognition technique. 19. The computing device of claim 14 , wherein the at least one image quality enhancement includes image denoising, contrast stretching, histogram normalization, image sharpening, image upscaling, image deconvolution, or image super-resolution. | 0.621224 |
9. The system of claim 8 , wherein the personal information is received by collecting personal data elements in response to events, the personal information including personally-identifying information, comprising at least one of: name; address; and account data. | 9. The system of claim 8 , wherein the personal information is received by collecting personal data elements in response to events, the personal information including personally-identifying information, comprising at least one of: name; address; and account data. 10. The system of claim 9 , wherein the events include at least one of: online activities; electronic calendar activities; global positioning system location; and in-store activities. | 0.911477 |
14. The method of claim 13 , wherein: the selecting a first eye comprises: prioritizing the eye candidates according to contrast into a first list of eye candidates; extracting a number of eye candidates from the first list of eye candidates into a second list of eye candidates; and selecting a first eye from the second list of eye candidates; and the selecting a second eye comprises selecting a second eye from the second list of eye candidates. | 14. The method of claim 13 , wherein: the selecting a first eye comprises: prioritizing the eye candidates according to contrast into a first list of eye candidates; extracting a number of eye candidates from the first list of eye candidates into a second list of eye candidates; and selecting a first eye from the second list of eye candidates; and the selecting a second eye comprises selecting a second eye from the second list of eye candidates. 15. The method of claim 14 , wherein: the validating a profile of first eye comprises: measuring profile metrics of the first eye; and determining whether the profile metrics of the first eye are valid; and the validating a profile of second eye comprises: measuring profile metrics of the second eye; and determining whether the profile metrics of the second eye are valid. | 0.865563 |
1. A method, performed by a computing device, for mining translation pairs for training in-domain machine translation engines, comprising: obtaining one or more sources of potential translation pairs comprising one or more content items, wherein the one or more sources of potential translation pairs are in an identified domain for which a machine translation engine is to be trained; generating one or more potential translation pairs from the obtained one or more sources of potential translation pairs by applying one or more automated filtering techniques to the obtained one or more sources of potential translation pairs, wherein one of the one or more automated filtering techniques applied to a selected obtained source of potential translation pairs is configured based on a type of the selected obtained source of potential translation pairs, and wherein each of the one or more potential translation pairs comprises at least two language snippets; selecting at least one actual translation pair from the generated one or more potential translation pairs, said selecting comprising: extracting characteristics from each of the two language snippets of at least one of the one or more potential translation pairs; determining that the two language snippets of the at least one of the one or more potential translation pairs are translations of each other by comparing the extracted characteristics; and training the machine translation engine using the selected at least one actual translation pair. | 1. A method, performed by a computing device, for mining translation pairs for training in-domain machine translation engines, comprising: obtaining one or more sources of potential translation pairs comprising one or more content items, wherein the one or more sources of potential translation pairs are in an identified domain for which a machine translation engine is to be trained; generating one or more potential translation pairs from the obtained one or more sources of potential translation pairs by applying one or more automated filtering techniques to the obtained one or more sources of potential translation pairs, wherein one of the one or more automated filtering techniques applied to a selected obtained source of potential translation pairs is configured based on a type of the selected obtained source of potential translation pairs, and wherein each of the one or more potential translation pairs comprises at least two language snippets; selecting at least one actual translation pair from the generated one or more potential translation pairs, said selecting comprising: extracting characteristics from each of the two language snippets of at least one of the one or more potential translation pairs; determining that the two language snippets of the at least one of the one or more potential translation pairs are translations of each other by comparing the extracted characteristics; and training the machine translation engine using the selected at least one actual translation pair. 4. The method of claim 1 : wherein each of the obtained one or more sources of potential translation pairs comprise multiple content items in different languages; wherein the multiple content items in different languages of each individual obtained one or more sources of potential translation pairs are related to the same target; wherein the at least two language snippets for each potential translation pair are: from different ones of the multiple content items of one of the obtained one or more sources of potential translation pairs and are in different languages; and wherein the identified domain for which the machine translation engine is to be trained is a social media domain. | 0.647851 |
16. The system of claim 9 wherein the parser rules and analyzer rules include actions to be performed when rules are matched. | 16. The system of claim 9 wherein the parser rules and analyzer rules include actions to be performed when rules are matched. 17. The system of claim 16 further comprising a scripting engine stored on the medium and executed by the computer, operatively coupled to said parser and said analyzer, for implementing the actions to be performed. | 0.945264 |
10. A tangible computer readable medium having encoded thereon computer-executable instructions which, when executed by a computer, cause the computer to perform the method of claim 1 . | 10. A tangible computer readable medium having encoded thereon computer-executable instructions which, when executed by a computer, cause the computer to perform the method of claim 1 . 16. The method of claim 10 , wherein the second language communication includes text based communication. | 0.94212 |
1. A sign language translation system, comprising: input means for inputting motion of hands as electric signals; sign language word generating means for recognizing words in accordance with said input electric signals and generating sign language words; storage means for storing conjugations or translations of said generated sign language words and postpositions or auxiliary verbs to be supplemented between said generated sign language words; dependence analyzing means for analyzing a dependence relationship between successive ones of said recognized words in accordance with said stored translations of said recognized words and outputting analyzed results; spoken language generating means for generating, in accordance with said analyzed results, an audibly communicated sentence by supplementing said stored postpositions or auxiliary verbs and providing said stored conjugations of conjugative words; and output means for outputting said generated spoken language. | 1. A sign language translation system, comprising: input means for inputting motion of hands as electric signals; sign language word generating means for recognizing words in accordance with said input electric signals and generating sign language words; storage means for storing conjugations or translations of said generated sign language words and postpositions or auxiliary verbs to be supplemented between said generated sign language words; dependence analyzing means for analyzing a dependence relationship between successive ones of said recognized words in accordance with said stored translations of said recognized words and outputting analyzed results; spoken language generating means for generating, in accordance with said analyzed results, an audibly communicated sentence by supplementing said stored postpositions or auxiliary verbs and providing said stored conjugations of conjugative words; and output means for outputting said generated spoken language. 12. A sign language translation system according to claim 1, wherein each said omitted word to be supplemented is at least one of an auxiliary verb, postposition, pseudo pronoun, and conjunction, respectively representing a semantic and time sequential relationships between words. | 0.646539 |
10. The method of claim 9 , wherein gathering additional product type information further defining the visualized product comprises gathering additional product type information provided via a graphical user interface. | 10. The method of claim 9 , wherein gathering additional product type information further defining the visualized product comprises gathering additional product type information provided via a graphical user interface. 15. The method of claim 10 , further comprising generating a custom product type visualization using a product visualizer; and exporting said generated custom product type visualization as a product description. | 0.904933 |
1. An apparatus for providing information related to a broadcast program, the apparatus comprising: an object detector that detects at least one object from scenes displayed on a display; a keyword generator that generates a keyword including a name and information related to a meaning of the object; a section setting unit that sets a scene section comprising a group of the scenes that deal with a same subject between the scenes displayed on the display using the generated keyword based on an amount of preserved keywords that are generated based on the at least one object from the scenes; a related information searching unit that requests a searching of related information associated with the object by using the keyword, and receives the searched related information; and a related information provider that synchronizes the received related information along with the scene section comprising the group of the scenes that deal with the same subject between the scenes displayed on the display and provides the related information synchronized with the scene section to display, wherein the object detector, the keyword generator, the section setting unit, the related information searching unit, the related information provider comprise at least one processor; wherein the section setting unit sets as the scene section a group of scenes between which an amount of preserved keywords is equal to or greater than a threshold value, the preserved keywords being defined by a number of keywords that exist in common between keywords generated from a first scene and keywords generated from a second scene, and wherein the keyword generator determines an object name which corresponds to the object and a category to which the object name belongs by using an object name dictionary in which a plurality of object names are individually mapped to categories, thereby generating the keyword including the object name and the category. | 1. An apparatus for providing information related to a broadcast program, the apparatus comprising: an object detector that detects at least one object from scenes displayed on a display; a keyword generator that generates a keyword including a name and information related to a meaning of the object; a section setting unit that sets a scene section comprising a group of the scenes that deal with a same subject between the scenes displayed on the display using the generated keyword based on an amount of preserved keywords that are generated based on the at least one object from the scenes; a related information searching unit that requests a searching of related information associated with the object by using the keyword, and receives the searched related information; and a related information provider that synchronizes the received related information along with the scene section comprising the group of the scenes that deal with the same subject between the scenes displayed on the display and provides the related information synchronized with the scene section to display, wherein the object detector, the keyword generator, the section setting unit, the related information searching unit, the related information provider comprise at least one processor; wherein the section setting unit sets as the scene section a group of scenes between which an amount of preserved keywords is equal to or greater than a threshold value, the preserved keywords being defined by a number of keywords that exist in common between keywords generated from a first scene and keywords generated from a second scene, and wherein the keyword generator determines an object name which corresponds to the object and a category to which the object name belongs by using an object name dictionary in which a plurality of object names are individually mapped to categories, thereby generating the keyword including the object name and the category. 3. The apparatus of claim 1 , wherein the keyword generator determines the category by acquiring genre information relating to the scene. | 0.533238 |
1. A system for providing recommendations for hiring agents within a call center environment, comprising: a list of candidates for hire as agents within a call center; a voice assessor to analyze a voice recording from each of the candidates by measuring voice characteristics within the voice recording and calculating a score for the voice recording based on the measured voice characteristics; a comparison module to compare the voice recording to a voice model; a modifier to increase the voice recording score when the recording substantially resembles the voice model; a threshold module to apply a threshold to the increased voice recording score; and a recommendation module to retain one or more of the candidates on the list of candidates for hire when the voice recording score for that candidate satisfies the threshold and to remove one or more of the candidates from the list when the voice recording score for that candidate fails to satisfy the threshold. | 1. A system for providing recommendations for hiring agents within a call center environment, comprising: a list of candidates for hire as agents within a call center; a voice assessor to analyze a voice recording from each of the candidates by measuring voice characteristics within the voice recording and calculating a score for the voice recording based on the measured voice characteristics; a comparison module to compare the voice recording to a voice model; a modifier to increase the voice recording score when the recording substantially resembles the voice model; a threshold module to apply a threshold to the increased voice recording score; and a recommendation module to retain one or more of the candidates on the list of candidates for hire when the voice recording score for that candidate satisfies the threshold and to remove one or more of the candidates from the list when the voice recording score for that candidate fails to satisfy the threshold. 9. A system according to claim 1 , further comprising: a hiring module to automatically make hiring decisions for the call center based on the voice recording score. | 0.843396 |
21. The method of claim 20, including the step of streaming a first model and each of a plurality of embedded models contained within the first model. | 21. The method of claim 20, including the step of streaming a first model and each of a plurality of embedded models contained within the first model. 23. The method of claim 21, including the step of filing a first model, wherein in response to the first model being filed, the step of filing a first model includes the steps of: filing a plurality of embedded models contained within the first model; and filing each of the plurality of embedded models independently from the first model in which the plurality of embedded models are contained. | 0.871311 |
12. 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: detecting an occurrence of a pre-search trigger, the pre-search trigger corresponding to a user action to gain access to a search interface at a particular time; identifying a user associated with the pre-search trigger; identifying a topic classified as a likely topic of interest for the identified user based on a browsing history of the identified user or a search query history of the identified user; in response to detecting the occurrence of the pre-search trigger, determining a confidence score associated with the topic based on the particular time of the user action, the confidence score indicating a likelihood that the topic is of interest to the identified user at the particular time; determining that the confidence score associated with the topic satisfies a predetermined threshold value; instructing a search engine to execute a search using a search query associated with the particular topic in response to determining that the confidence score associated with the particular topic satisfies the predetermined threshold value; and providing a representation of a resource identified in results received in response to the search. | 12. 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: detecting an occurrence of a pre-search trigger, the pre-search trigger corresponding to a user action to gain access to a search interface at a particular time; identifying a user associated with the pre-search trigger; identifying a topic classified as a likely topic of interest for the identified user based on a browsing history of the identified user or a search query history of the identified user; in response to detecting the occurrence of the pre-search trigger, determining a confidence score associated with the topic based on the particular time of the user action, the confidence score indicating a likelihood that the topic is of interest to the identified user at the particular time; determining that the confidence score associated with the topic satisfies a predetermined threshold value; instructing a search engine to execute a search using a search query associated with the particular topic in response to determining that the confidence score associated with the particular topic satisfies the predetermined threshold value; and providing a representation of a resource identified in results received in response to the search. 16. The system of claim 12 , wherein providing a representation of the resource comprises providing a resource that, when rendered, causes content of the resource to be displayed on a portion of a user interface. | 0.628279 |
1. A method comprising: receiving an initial query term set; performing phrase recognition on the initial query term set to determine recognized phrases; determining a synonym for one of the recognized phrases, the synonym comprising a plurality of words merged together as a phrase; and determining, using one or more processors, results that match the initial query term set and the synonym, the synonym being matched based on selection of a search option from one or more search options selected from a group of search options consisting of: a first search option operable to cause the synonym to be matched whenever the plurality of words of the synonym are matched without regard to order, a second search option operable to cause the synonym to be matched whenever at least one of the plurality of words of the synonym is matched, and a third search option operable to cause the synonym to be matched whenever the plurality of words of the synonym are matched in order. | 1. A method comprising: receiving an initial query term set; performing phrase recognition on the initial query term set to determine recognized phrases; determining a synonym for one of the recognized phrases, the synonym comprising a plurality of words merged together as a phrase; and determining, using one or more processors, results that match the initial query term set and the synonym, the synonym being matched based on selection of a search option from one or more search options selected from a group of search options consisting of: a first search option operable to cause the synonym to be matched whenever the plurality of words of the synonym are matched without regard to order, a second search option operable to cause the synonym to be matched whenever at least one of the plurality of words of the synonym is matched, and a third search option operable to cause the synonym to be matched whenever the plurality of words of the synonym are matched in order. 5. The method of claim 1 , further comprising: determining a synonym for a second one of the recognized phrases, the synonym comprising a plurality of words; determining additional results that match the synonym for the second one of the recognized phrases, the additional results being matches whenever the plurality of words of the synonym are matched in order; and adding the additional results to the results that match the initial query term set and the synonym. | 0.806291 |
17. A computer program product, encoded on one or more non-transitory computer storage media, comprising instructions that when executed by one or more computers cause the one or more computers to perform operations comprising: receiving a query; identifying an original term occurring in the query; determining a plurality of substitution contexts for the original term occurring in the query, wherein a substitution context specifies a context in which the original term in the query is replaced by a substitute term, and wherein a substitution context includes one or more context terms and an indication of a position in the query of the original term relative to the one or more context terms; generating a context hierarchy of the plurality of substitution contexts, wherein any conditions of a parent context in the context hierarchy also apply to each of one or more child contexts of the parent context in the context hierarchy, and wherein each child context in the context hierarchy includes all of the terms of a parent context of the child context as well as an additional term that does not occur in the parent context of the child context; determining a score for each substitution context of the plurality of substitution contexts including comparing a particular substitution context to its parent context in the context hierarchy; ranking the plurality of substitution contexts based on the score of each substitution context; and determining one or more substitute terms for the original term occurring in the query in a context specified by a highest-ranking substitution context of the plurality of substitution contexts. | 17. A computer program product, encoded on one or more non-transitory computer storage media, comprising instructions that when executed by one or more computers cause the one or more computers to perform operations comprising: receiving a query; identifying an original term occurring in the query; determining a plurality of substitution contexts for the original term occurring in the query, wherein a substitution context specifies a context in which the original term in the query is replaced by a substitute term, and wherein a substitution context includes one or more context terms and an indication of a position in the query of the original term relative to the one or more context terms; generating a context hierarchy of the plurality of substitution contexts, wherein any conditions of a parent context in the context hierarchy also apply to each of one or more child contexts of the parent context in the context hierarchy, and wherein each child context in the context hierarchy includes all of the terms of a parent context of the child context as well as an additional term that does not occur in the parent context of the child context; determining a score for each substitution context of the plurality of substitution contexts including comparing a particular substitution context to its parent context in the context hierarchy; ranking the plurality of substitution contexts based on the score of each substitution context; and determining one or more substitute terms for the original term occurring in the query in a context specified by a highest-ranking substitution context of the plurality of substitution contexts. 22. The computer program product of claim 17 , wherein the operations comprise: computing a score between two of the plurality of substitution contexts, wherein the score represents how closely the substitution contexts agree; determining, based on the score, that the substitution contexts do not agree; and in response to determining that the substitution contexts do not agree, decreasing a weight given to substitute terms for the original term generated using the substitution contexts that do not agree. | 0.5 |
35. The computer program product of claim 26 , wherein the program instructions for performing receiving the knowledge tip in the tips repository comprises: a. a program instructions for creating a new category in the tips repository if a required category is not existing among a the plurality of predefined categories in the tips repository; and b. program instructions for storing the knowledge tip to the new category. | 35. The computer program product of claim 26 , wherein the program instructions for performing receiving the knowledge tip in the tips repository comprises: a. a program instructions for creating a new category in the tips repository if a required category is not existing among a the plurality of predefined categories in the tips repository; and b. program instructions for storing the knowledge tip to the new category. 40. The computer program product of claim 35 further comprising program instructions for deleting an existing knowledge tip in the tips repository, wherein an author of the knowledge tip or an administrator are allowed to delete the knowledge tip if the knowledge tip is not scheduled to be shared. | 0.893643 |
9. An apparatus, comprising a detector device including a detector configured to accept multiple types of input, the multiple types of input comprising a video input, the detector configured to evaluate a person detection classifier to detect a person, the person detection classifier created by: identifying a pool of features from the multiple types of input, the pool of features comprising a first video feature from the video input, the first video feature comprising a parent rectangle within a feature rectangle in an image of the video input; calculating a numeric value associated with the first video feature by summing values of pixels in the parent rectangle; and generating the classifier for speaker detection using a learning algorithm wherein nodes of the classifier are selected using the pool of features, based on the numeric value associated with the first video feature. | 9. An apparatus, comprising a detector device including a detector configured to accept multiple types of input, the multiple types of input comprising a video input, the detector configured to evaluate a person detection classifier to detect a person, the person detection classifier created by: identifying a pool of features from the multiple types of input, the pool of features comprising a first video feature from the video input, the first video feature comprising a parent rectangle within a feature rectangle in an image of the video input; calculating a numeric value associated with the first video feature by summing values of pixels in the parent rectangle; and generating the classifier for speaker detection using a learning algorithm wherein nodes of the classifier are selected using the pool of features, based on the numeric value associated with the first video feature. 14. The apparatus of claim 9 , creation of the person detection classifier comprising defining a second video feature using bilateral symmetry to mirror the first video feature. | 0.528311 |
1. A composite application modeling system comprising at least one memory storing a composite application modeling tool and at least one processor executing the application modeling tool to perform operations, the operations comprising: processing at least one input defining a user-centric modeling component, the user-centric modeling component modeling an interactive software system and including a plurality of process steps, the plurality of process steps defining a business scenario; processing at least one input identifying for each process step in the plurality of process steps one or more service requirements, where a service requirement represents functionality necessary to accomplish a step; processing at least one input identifying for each service requirement a process component capable of providing the service requirement, the process component modeling software implementing at least one process and defining a service operation for providing the service requirement and for interacting with other process components, each process component belonging to exactly one deployment unit and comprising a pair-wise interaction with another process component in another deployment unit, each deployment unit characterizing independently operable software deployable on a separate computer hardware platform; and generating at least one process component interaction model with a plurality of identified process components. | 1. A composite application modeling system comprising at least one memory storing a composite application modeling tool and at least one processor executing the application modeling tool to perform operations, the operations comprising: processing at least one input defining a user-centric modeling component, the user-centric modeling component modeling an interactive software system and including a plurality of process steps, the plurality of process steps defining a business scenario; processing at least one input identifying for each process step in the plurality of process steps one or more service requirements, where a service requirement represents functionality necessary to accomplish a step; processing at least one input identifying for each service requirement a process component capable of providing the service requirement, the process component modeling software implementing at least one process and defining a service operation for providing the service requirement and for interacting with other process components, each process component belonging to exactly one deployment unit and comprising a pair-wise interaction with another process component in another deployment unit, each deployment unit characterizing independently operable software deployable on a separate computer hardware platform; and generating at least one process component interaction model with a plurality of identified process components. 4. The system of claim 1 , where: the plurality of services are defined by a service pattern. | 0.557496 |
156. The computer program product of claim 70 , wherein the computer program product is operable such that first preloaded information derived from the first message is preloaded and initially hidden, and later displayed in response to a first user interaction. | 156. The computer program product of claim 70 , wherein the computer program product is operable such that first preloaded information derived from the first message is preloaded and initially hidden, and later displayed in response to a first user interaction. 164. The computer program product of claim 156 , wherein the computer program product is operable such that the first preloaded information is displayed without accessing a server. | 0.927345 |
8. A communication device for communicating a food order while a customer is driving a vehicle, the communication device comprising: a computer processor; a memory, comprising instructions, which when executed by the computer processor, causes the computer processor to perform operations comprising: creating a graphical user interface (GUI) that is output to a display of the communications device; receiving a manual input from an input device, the input relating to one or more GUI elements of the GUI, the input indicating partial information about a food order; monitoring a speed of the communication device calculated based upon received data from one of an accelerometer or a global positioning system receiver of the communication device; responsive to a determination that the speed of the communications device is above a specified speed threshold: disabling input from the input device and entering a voice input mode; initiating, using communications circuitry of the communications device, a wireless data connection, over a computer network, between the communications device and a remote communications device at a remote order facilitation system; transmitting, using the wireless data connection, data generated based upon the input received before the input from the input device was disabled, the data conveying a portion of the food order to the remote communications device; receiving, at a microphone of the communications device, voice input corresponding to a second portion of the food order to be fulfilled by a restaurant; converting the voice input into one or more data packets; transmitting, via the wireless data connection, the data packets to the remote communications device at the remote order facilitation system to send the second portion of the food order; upon completion of the food order, receiving, from the remote communications device via the wireless data connection, an indication that the food order was successfully received by the remote communications device; and generating an indication that the food order is being processed to be fulfilled at the restaurant. | 8. A communication device for communicating a food order while a customer is driving a vehicle, the communication device comprising: a computer processor; a memory, comprising instructions, which when executed by the computer processor, causes the computer processor to perform operations comprising: creating a graphical user interface (GUI) that is output to a display of the communications device; receiving a manual input from an input device, the input relating to one or more GUI elements of the GUI, the input indicating partial information about a food order; monitoring a speed of the communication device calculated based upon received data from one of an accelerometer or a global positioning system receiver of the communication device; responsive to a determination that the speed of the communications device is above a specified speed threshold: disabling input from the input device and entering a voice input mode; initiating, using communications circuitry of the communications device, a wireless data connection, over a computer network, between the communications device and a remote communications device at a remote order facilitation system; transmitting, using the wireless data connection, data generated based upon the input received before the input from the input device was disabled, the data conveying a portion of the food order to the remote communications device; receiving, at a microphone of the communications device, voice input corresponding to a second portion of the food order to be fulfilled by a restaurant; converting the voice input into one or more data packets; transmitting, via the wireless data connection, the data packets to the remote communications device at the remote order facilitation system to send the second portion of the food order; upon completion of the food order, receiving, from the remote communications device via the wireless data connection, an indication that the food order was successfully received by the remote communications device; and generating an indication that the food order is being processed to be fulfilled at the restaurant. 9. The device of claim 8 , wherein the restaurant is a restaurant chosen by a user from the GUI. | 0.551801 |
5. A method comprising: receiving, at an ecommerce service, text from a first user, the text in a first language and pertaining to a first listing on the ecommerce service; retrieving contextual information about the first listing; translating the text to a second language; locating, in a database, a plurality of text objects, in the second language, similar to the translated text, each text object comprising textual information pertaining to at least one listing; ranking the plurality of text objects similar to the translated text based on a comparison of the contextual information about the first listing and contextual information stored in the database for the listings corresponding to the plurality of text objects similar to the translated text; translating at least one of the ranked plurality of text objects to the first language; presenting a subset of the ranked plurality of text objects to the first user; receiving feedback from the first user; selecting one of the subset of the ranked plurality of text objects based on the feedback; and using the selected text object in the ecommerce service. | 5. A method comprising: receiving, at an ecommerce service, text from a first user, the text in a first language and pertaining to a first listing on the ecommerce service; retrieving contextual information about the first listing; translating the text to a second language; locating, in a database, a plurality of text objects, in the second language, similar to the translated text, each text object comprising textual information pertaining to at least one listing; ranking the plurality of text objects similar to the translated text based on a comparison of the contextual information about the first listing and contextual information stored in the database for the listings corresponding to the plurality of text objects similar to the translated text; translating at least one of the ranked plurality of text objects to the first language; presenting a subset of the ranked plurality of text objects to the first user; receiving feedback from the first user; selecting one of the subset of the ranked plurality of text objects based on the feedback; and using the selected text object in the ecommerce service. 7. The method of claim 5 , wherein the text from the first user is a portion of an item description of the first listing and the using includes utilizing the selected text object as the portion of the item description of the first listing. | 0.567096 |
1. A computer-implemented method, comprising: invoking a contextual scope function executed on a processor-based computing device, wherein the contextual scope function establishes a contextual neighborhood within a computer-implemented fuzzy network-based structure; receiving a recommendation, wherein the recommendation is generated by a computer-implemented discovery function that generates the recommendation in accordance with the contextual neighborhood and an inference from a plurality of usage behaviors; and receiving the recommendation, wherein the recommendation is generated in accordance with the contextual neighborhood, wherein the contextual neighborhood is based on a selected object. | 1. A computer-implemented method, comprising: invoking a contextual scope function executed on a processor-based computing device, wherein the contextual scope function establishes a contextual neighborhood within a computer-implemented fuzzy network-based structure; receiving a recommendation, wherein the recommendation is generated by a computer-implemented discovery function that generates the recommendation in accordance with the contextual neighborhood and an inference from a plurality of usage behaviors; and receiving the recommendation, wherein the recommendation is generated in accordance with the contextual neighborhood, wherein the contextual neighborhood is based on a selected object. 6. The method of claim 1 , further comprising: receiving the recommendation, wherein the recommendation is generated by the computer-implemented discovery function that generates the recommendation in accordance with the inference, wherein the inference is of a level of expertise. | 0.693211 |
7. The method according to claim 1 wherein said classifying comprises: determining the length and direction of each of said primitives; and comparing said length, direction and sequence of said primitives for said word with primitives of words stored in a memory device and generating a list of words having a high probability of matching said word. | 7. The method according to claim 1 wherein said classifying comprises: determining the length and direction of each of said primitives; and comparing said length, direction and sequence of said primitives for said word with primitives of words stored in a memory device and generating a list of words having a high probability of matching said word. 8. The method according to claim 7 wherein said step of determining the length and direction comprises: counting the number of said pixels constituting said primitive, said primitive having an original feature point and a terminal feature point; and measuring: the angle formed with horizontal by an imaginary straight line between said original and terminal feature points, the angle formed with horizontal by an imaginary straight line between said original feature point and a pixel adjacent said original feature point; and the angle formed with horizontal by an imaginary straight line between said terminal feature point and a pixel adjacent said terminal feature point. | 0.794502 |
1. A method for sorting a list of elements, the elements being adapted for use in improving recognition accuracy of a speech-recognition system through at least one of supervised adaptation and unsupervised adaptation, the method comprising: providing a non-optimized list of elements, with some of the elements having multiple terms, generating, by a processor circuit, a table of sub-elements from the elements list, with each sub-element having one term only and with a number of times a sub-element appears in the elements list being weighted in the sub-elements table, generating, by the processor circuit, a weighted singleton histogram table using a singleton dictionary, and computing a total popularity score of each singleton from the sub-elements table, for each element from the elements list, generating by the processor circuit, an elements score based on the total popularity score of each singleton within the element, and generating, by the processor circuit, an optimally sorted list of the elements list based on the elements scores. | 1. A method for sorting a list of elements, the elements being adapted for use in improving recognition accuracy of a speech-recognition system through at least one of supervised adaptation and unsupervised adaptation, the method comprising: providing a non-optimized list of elements, with some of the elements having multiple terms, generating, by a processor circuit, a table of sub-elements from the elements list, with each sub-element having one term only and with a number of times a sub-element appears in the elements list being weighted in the sub-elements table, generating, by the processor circuit, a weighted singleton histogram table using a singleton dictionary, and computing a total popularity score of each singleton from the sub-elements table, for each element from the elements list, generating by the processor circuit, an elements score based on the total popularity score of each singleton within the element, and generating, by the processor circuit, an optimally sorted list of the elements list based on the elements scores. 2. The method of claim 1 , wherein the step of generating the weighted singleton histogram includes: ordering the singletons from a largest total characters to a smallest total characters of the singletons. | 0.6758 |
1. A computer implemented method for classifying a document using a plurality of confidence grades, comprising: providing a training engine and a classification engine employing a computer system for classifying said document using said plurality of confidence grades, wherein said computer system further comprises a processor, a memory unit for storing programs and data, an input/output (I/O) controller, a network interface, and a data bus; training a classifier by said training engine using a plurality of training documents, wherein training said classifier comprises: obtaining a list of first words from said training documents, wherein each of said training documents is classified into one of a plurality of classes; for each class belonging to said classes: determining a prior probability of said class, wherein said prior probability is probability of occurrence of said training documents in said class given said training documents in said classes; calculating conditional probabilities for said list of first words; calculating a minimum posterior probability and a maximum posterior probability for said class; defining multiple threshold constants by evaluating empirically said calculated minimum and maximum posterior probabilities across a number of experimentations; determining a plurality of confidence thresholds using said list of first words, said prior probability of said class, and one of said multiple threshold constants; and defining said confidence grades using said determined confidence thresholds; classifying said document by said classification engine using said trained classifier, wherein classifying said document comprises: obtaining a list of second words from said document, wherein said second words are commonly present in said list of first words; determining conditional probabilities for said list of second words for each of said classes from said calculated conditional probabilities for said list of first words; calculating a posterior probability for each of said classes using said prior probability and said determined conditional probabilities; comparing said calculated posterior probability with said determined confidence thresholds for each of said classes; assigning each of said classes to one of said defined confidence grades based on said comparison of said calculated posterior probability with said determined confidence thresholds; and assigning said document to one of said classes based on said calculated posterior probability and said assigned confidence grades for each of said classes; whereby said document is classified into one of said classes using said confidence grades. | 1. A computer implemented method for classifying a document using a plurality of confidence grades, comprising: providing a training engine and a classification engine employing a computer system for classifying said document using said plurality of confidence grades, wherein said computer system further comprises a processor, a memory unit for storing programs and data, an input/output (I/O) controller, a network interface, and a data bus; training a classifier by said training engine using a plurality of training documents, wherein training said classifier comprises: obtaining a list of first words from said training documents, wherein each of said training documents is classified into one of a plurality of classes; for each class belonging to said classes: determining a prior probability of said class, wherein said prior probability is probability of occurrence of said training documents in said class given said training documents in said classes; calculating conditional probabilities for said list of first words; calculating a minimum posterior probability and a maximum posterior probability for said class; defining multiple threshold constants by evaluating empirically said calculated minimum and maximum posterior probabilities across a number of experimentations; determining a plurality of confidence thresholds using said list of first words, said prior probability of said class, and one of said multiple threshold constants; and defining said confidence grades using said determined confidence thresholds; classifying said document by said classification engine using said trained classifier, wherein classifying said document comprises: obtaining a list of second words from said document, wherein said second words are commonly present in said list of first words; determining conditional probabilities for said list of second words for each of said classes from said calculated conditional probabilities for said list of first words; calculating a posterior probability for each of said classes using said prior probability and said determined conditional probabilities; comparing said calculated posterior probability with said determined confidence thresholds for each of said classes; assigning each of said classes to one of said defined confidence grades based on said comparison of said calculated posterior probability with said determined confidence thresholds; and assigning said document to one of said classes based on said calculated posterior probability and said assigned confidence grades for each of said classes; whereby said document is classified into one of said classes using said confidence grades. 6. The computer implemented method of claim 1 , further comprising modifying said list of second words, comprising: removing stop words from said list of second words; removing numeric digits from said list of second words; and stemming each of said second words in said list of second words. | 0.825387 |
11. The method of claim 8 wherein the semantic analysis identifies a plurality of concepts in the one or more network nodes. | 11. The method of claim 8 wherein the semantic analysis identifies a plurality of concepts in the one or more network nodes. 12. The method of claim 11 wherein the plurality of concepts comprises concepts identified from patterns of terms in the contents of the one or more network nodes. | 0.951884 |
18. An auto-segmentation apparatus comprising: a processor configured to: perform atlas-based auto-segmentation on a plurality of points in a subject image using atlas images to generate first data representative of at least one structure in the subject image, wherein the processor is further configured to perform the atlas-based auto-segmentation by registering the subject image with a plurality of the atlas images to map point of the subject images to points of the atlas images, apply a plurality of points in the subject image to a trained classifier to generate second data representative of the a least one structure in the subject image, combine the first data with the second data to generate third data representative of the at least one structure in the subject image, and determine based on the data structure classification associated with the subject image. | 18. An auto-segmentation apparatus comprising: a processor configured to: perform atlas-based auto-segmentation on a plurality of points in a subject image using atlas images to generate first data representative of at least one structure in the subject image, wherein the processor is further configured to perform the atlas-based auto-segmentation by registering the subject image with a plurality of the atlas images to map point of the subject images to points of the atlas images, apply a plurality of points in the subject image to a trained classifier to generate second data representative of the a least one structure in the subject image, combine the first data with the second data to generate third data representative of the at least one structure in the subject image, and determine based on the data structure classification associated with the subject image. 34. The apparatus of claim 18 wherein the subject image comprises a computed tomography image. | 0.785102 |
8. A non-transitory computer readable storage medium embodying a computer program for performing a method, said method comprising: providing an engine in communication with a rule catalog comprising a plurality of query plan re-write rules including a first query plan re-write rule specifying a top-down traversal order and a second query plan re-write rule specifying a bottom-up traversal order; causing the engine to receive a query plan as an input; causing the engine to reference the rule catalog to generate a re-written query plan by selectively applying the first query plan re-write rule to the query plan; causing the engine to store the re-written query plan in a non-transitory computer readable storage medium; causing the engine to reference the rule catalog to generate a further re-written query plan by applying a third query plan re-write rule to the re-written query plan; causing the engine to reference the re-written query plan in order to generate a visualization comprising a graph including an operation node and a table node; and causing the engine to communicate the visualization to an interface for display in a dashboard, wherein the dashboard further includes a change log separate from the graph and reflecting changes to the re-written query plan in a format comprising an identifier of the operation node, an operation type, an updated parent node identifier, and an identifier of the query plan re-write rule. | 8. A non-transitory computer readable storage medium embodying a computer program for performing a method, said method comprising: providing an engine in communication with a rule catalog comprising a plurality of query plan re-write rules including a first query plan re-write rule specifying a top-down traversal order and a second query plan re-write rule specifying a bottom-up traversal order; causing the engine to receive a query plan as an input; causing the engine to reference the rule catalog to generate a re-written query plan by selectively applying the first query plan re-write rule to the query plan; causing the engine to store the re-written query plan in a non-transitory computer readable storage medium; causing the engine to reference the rule catalog to generate a further re-written query plan by applying a third query plan re-write rule to the re-written query plan; causing the engine to reference the re-written query plan in order to generate a visualization comprising a graph including an operation node and a table node; and causing the engine to communicate the visualization to an interface for display in a dashboard, wherein the dashboard further includes a change log separate from the graph and reflecting changes to the re-written query plan in a format comprising an identifier of the operation node, an operation type, an updated parent node identifier, and an identifier of the query plan re-write rule. 13. A non-transitory computer readable storage medium as in claim 8 wherein the rule catalog receives a user input specifying a sequence of applying the first query plan re-write rule prior to application of the third query plan re-write rule. | 0.534493 |
11. A system for determining the status of an answered telephone during the course of an outbound telephone call comprising: an automated telephone calling device for placing a telephone call to a location having a telephone number at which a target person is listed; and a speaker-independent speech recognition system which, upon said telephone call being answered, initiates a prerecorded greeting which asks for the target person, receives an initial response, determines whether said initial response is being provided by an answering machine by distinguishing between a live person and a machine according to whether the initial response is longer than a predetermined time or whether a beep tone is detected, determine that a spoken response from has been received by an answering person, and performs a speech recognition analysis on said spoken response to determine the meaning of said spoken response; wherein, if said speaker-independent speech recognition system determines that said answering person is said target person, said speaker-independent speech recognition system initiates a speaker-independent speech recognition application with said target person, wherein the speaker-independent speech recognition application is an interactive speech application configured and arranged to provide a series of acoustic prompts to the answering person by telephonic interaction, wherein the speech recognition application comprises a Web access application, an educational application, a learning and lesson application, or a compliance application, and wherein the speaker-independent speech recognition system is configured to provide conditional responses based on the meaning of the spoken response as determined by the speaker-independent speech recognition analysis in accordance with a speaker-independent speech recognition enabled state of conversation selected from the group consisting of (1) the answering person indicates that he or she is the target person, (2) the answering person indicates that he or she is not the target person, (3) the answering person indicates that the target person is not present at the location, (4) the answering person indicates a hold request, (5) the answering person requests the identity of the caller, (6) the answering person indicates that the telephone number is not the correct number for the target person, and (7) the speaker-independent speech recognition analysis cannot determine the meaning of the spoken response from the answering person. | 11. A system for determining the status of an answered telephone during the course of an outbound telephone call comprising: an automated telephone calling device for placing a telephone call to a location having a telephone number at which a target person is listed; and a speaker-independent speech recognition system which, upon said telephone call being answered, initiates a prerecorded greeting which asks for the target person, receives an initial response, determines whether said initial response is being provided by an answering machine by distinguishing between a live person and a machine according to whether the initial response is longer than a predetermined time or whether a beep tone is detected, determine that a spoken response from has been received by an answering person, and performs a speech recognition analysis on said spoken response to determine the meaning of said spoken response; wherein, if said speaker-independent speech recognition system determines that said answering person is said target person, said speaker-independent speech recognition system initiates a speaker-independent speech recognition application with said target person, wherein the speaker-independent speech recognition application is an interactive speech application configured and arranged to provide a series of acoustic prompts to the answering person by telephonic interaction, wherein the speech recognition application comprises a Web access application, an educational application, a learning and lesson application, or a compliance application, and wherein the speaker-independent speech recognition system is configured to provide conditional responses based on the meaning of the spoken response as determined by the speaker-independent speech recognition analysis in accordance with a speaker-independent speech recognition enabled state of conversation selected from the group consisting of (1) the answering person indicates that he or she is the target person, (2) the answering person indicates that he or she is not the target person, (3) the answering person indicates that the target person is not present at the location, (4) the answering person indicates a hold request, (5) the answering person requests the identity of the caller, (6) the answering person indicates that the telephone number is not the correct number for the target person, and (7) the speaker-independent speech recognition analysis cannot determine the meaning of the spoken response from the answering person. 17. The system of claim 11 wherein, if said speech recognition device determines that said spoken response is a request for the identity of the entity responsible for the automated calling device, the speech recognition system instructs said automated telephone calling device to initiate a prerecorded response indicating the identity of the entity and to repeat said prerecorded greeting which asks for the target person; wherein, upon receiving a spoken response from the answering person, said speech recognition device performs a speech recognition analysis on said spoken response to determine the status of said spoken response. | 0.5 |
3. The method of claim 1 , further comprising: identifying a context cue in the data, the context cue identifying characteristics of the target; and selecting a table from the one or more tables in which the substitution unit is compatible with the characteristics of target. | 3. The method of claim 1 , further comprising: identifying a context cue in the data, the context cue identifying characteristics of the target; and selecting a table from the one or more tables in which the substitution unit is compatible with the characteristics of target. 5. The method of claim 3 , wherein the context cue comprises text found in the content. | 0.892188 |
5. The apparatus of claim 1 , each of the plurality of phonemes comprising a plurality of states, each of the adjustment factors applied on a per-state basis. | 5. The apparatus of claim 1 , each of the plurality of phonemes comprising a plurality of states, each of the adjustment factors applied on a per-state basis. 6. The apparatus of claim 5 , each of the plurality of phonemes comprising three states. | 0.972377 |
1. A method for assigning work in a customer support environment, the method comprising the computer-implemented steps of: translating a customer communication received in a first language into a second language, the translation having a confidence of translation; obtaining a set of agents, each agent of the set of agents having an associated confidence factor based upon the confidence of translation and a language proficiency of the agent in at least one of the first language or the second language; generating a threshold confidence factor curve comprising a first curve, having a first rate of decrease over a first wait time period of the customer communication, and a second curve, having a second rate of decrease over a second wait time of the customer communication, the second rate of decrease being greater than the first rate of decrease; and assigning, at a time, the customer communication to one of the set of agents based on the associated confidence factor being greater than the threshold confidence factor curve at the time. | 1. A method for assigning work in a customer support environment, the method comprising the computer-implemented steps of: translating a customer communication received in a first language into a second language, the translation having a confidence of translation; obtaining a set of agents, each agent of the set of agents having an associated confidence factor based upon the confidence of translation and a language proficiency of the agent in at least one of the first language or the second language; generating a threshold confidence factor curve comprising a first curve, having a first rate of decrease over a first wait time period of the customer communication, and a second curve, having a second rate of decrease over a second wait time of the customer communication, the second rate of decrease being greater than the first rate of decrease; and assigning, at a time, the customer communication to one of the set of agents based on the associated confidence factor being greater than the threshold confidence factor curve at the time. 2. The method of claim 1 , further comprising the computer-implemented step of determining, in response to the received customer communication, whether an agent having a required proficiency in the first language is available to service the customer communication. | 0.789348 |
6. The method of claim 1 wherein processing the mathematical function forms included in the packages comprises: if the first sentence form is not mapped to a mathematical function: gathering the first mathematical function form and synonyms including explicit synonyms of the first mathematical function form from each of the packages as mathematical function forms in a working set; computing identity of the first mathematical function form; if the identity maps to a mathematical function, obtaining the mathematical function to which the identity maps; else creating a mathematical function; mapping each of the mathematical function forms in the working set as a representer of the mathematical function; and processing placeholders of each of the mathematical function forms in the working set; obtaining function forms to which the mathematical function maps; and if one of the function forms is a sentence form representing a fact type: creating an association indicating that the mathematical function is defined by the fact type represented by the sentence form. | 6. The method of claim 1 wherein processing the mathematical function forms included in the packages comprises: if the first sentence form is not mapped to a mathematical function: gathering the first mathematical function form and synonyms including explicit synonyms of the first mathematical function form from each of the packages as mathematical function forms in a working set; computing identity of the first mathematical function form; if the identity maps to a mathematical function, obtaining the mathematical function to which the identity maps; else creating a mathematical function; mapping each of the mathematical function forms in the working set as a representer of the mathematical function; and processing placeholders of each of the mathematical function forms in the working set; obtaining function forms to which the mathematical function maps; and if one of the function forms is a sentence form representing a fact type: creating an association indicating that the mathematical function is defined by the fact type represented by the sentence form. 7. The method of claim 6 wherein processing placeholders of each of the mathematical function forms in the working set comprises: if the first placeholder is from the first mathematical function form: creating an argument represented by the first placeholder, and creating an association relating the argument to the mathematical function to which the first mathematical function form maps; else if the first placeholder is not from one of the explicit synonyms of the first mathematical function form: setting the first placeholder as a representer of a previously created argument in corresponding ordinal position; else obtaining all placeholders that are mapped to the first placeholder, one of the mapped placeholders representing a role; locating the represented role; and setting the first placeholder as a representer of the located role. | 0.687839 |
1. A system including a processor and a memory for providing the ability to parallelize pre-existing arbitrary serial code involving one statement after another, the system further comprising: an analytic engine for importing and encapsulating said pre-existing arbitrary serial code into a flowcharting system employing an object oriented flowchart language having a plurality of flowchart elements for flowcharting of said pre-existing arbitrary serial code, said analytic engine building a flowchart image by importing each statement of the pre-existing arbitrary serial code into execution paths of blocks wherein each path is an executing sequence of the statement blocks, said analytic engine further determining an execution time for each block, and building a cross-reference table of data dependencies, said analytic engine numbering each block of the pre-existing arbitrary serial code in ascending order by using a partially-ordered transitive numbering algorithm for which flowcharts can be generated from said pre-existing arbitrary serial code, said analytic engine being coupled to an atomic time supervisor, said atomic time supervisor receiving an atomic time, via user input, wherein the atomic time is the maximum execution time allowed for any execution path corresponding to each of the numbered blocks, said analytic engine ascertaining what flowchart elements may be processed under the atomic time provided by the atomic time supervisor, wherein the ascertaining of flowchart elements comprises: determining whether the execution time for a particular block is under the atomic time; in response to determining that the execution time is under the atomic time, assigning a particular block as either a flowchart Action object, representing a function to be performed, or a flowchart Test object, representing an evaluation of an event question; in response to determining that the execution time is more than the atomic time, assigning a particular block as a flowchart Task object representing an object that can be executed from separate processors to effectuate a parallel processing of the pre-existing arbitrary serial code; said analytic engine creating an exportable flowchart that includes the ascertained flowchart elements; said analytic engine optimizing a parallel execution of the imported pre-existing arbitrary serial code by adjusting said atomic time to generate Tasks that are distributed to separate partially ordered transitive flowchart system processors, by mapping flowchart Task objects to said separate processors and mapping flowchart Action objects or flowchart Test objects to either the same or separate transitive flowchart system processors; and said analytic engine enabling the imported pre-existing arbitrary serial code to be efficiently executed by said flowcharting system in parallel. | 1. A system including a processor and a memory for providing the ability to parallelize pre-existing arbitrary serial code involving one statement after another, the system further comprising: an analytic engine for importing and encapsulating said pre-existing arbitrary serial code into a flowcharting system employing an object oriented flowchart language having a plurality of flowchart elements for flowcharting of said pre-existing arbitrary serial code, said analytic engine building a flowchart image by importing each statement of the pre-existing arbitrary serial code into execution paths of blocks wherein each path is an executing sequence of the statement blocks, said analytic engine further determining an execution time for each block, and building a cross-reference table of data dependencies, said analytic engine numbering each block of the pre-existing arbitrary serial code in ascending order by using a partially-ordered transitive numbering algorithm for which flowcharts can be generated from said pre-existing arbitrary serial code, said analytic engine being coupled to an atomic time supervisor, said atomic time supervisor receiving an atomic time, via user input, wherein the atomic time is the maximum execution time allowed for any execution path corresponding to each of the numbered blocks, said analytic engine ascertaining what flowchart elements may be processed under the atomic time provided by the atomic time supervisor, wherein the ascertaining of flowchart elements comprises: determining whether the execution time for a particular block is under the atomic time; in response to determining that the execution time is under the atomic time, assigning a particular block as either a flowchart Action object, representing a function to be performed, or a flowchart Test object, representing an evaluation of an event question; in response to determining that the execution time is more than the atomic time, assigning a particular block as a flowchart Task object representing an object that can be executed from separate processors to effectuate a parallel processing of the pre-existing arbitrary serial code; said analytic engine creating an exportable flowchart that includes the ascertained flowchart elements; said analytic engine optimizing a parallel execution of the imported pre-existing arbitrary serial code by adjusting said atomic time to generate Tasks that are distributed to separate partially ordered transitive flowchart system processors, by mapping flowchart Task objects to said separate processors and mapping flowchart Action objects or flowchart Test objects to either the same or separate transitive flowchart system processors; and said analytic engine enabling the imported pre-existing arbitrary serial code to be efficiently executed by said flowcharting system in parallel. 6. The system of claim 1 , wherein said atomic time is a fraction of a scan. | 0.561865 |
3. The method of claim 2 , where the information associated with the selected one of the one or more categories includes the at least one link to a topic, of the respective plurality of topics, the method further comprising: receiving a selection of a link, of the at least one link; and providing, for display, a document including content associated with the selected link. | 3. The method of claim 2 , where the information associated with the selected one of the one or more categories includes the at least one link to a topic, of the respective plurality of topics, the method further comprising: receiving a selection of a link, of the at least one link; and providing, for display, a document including content associated with the selected link. 6. The method of claim 3 , where the document includes one or more links to the one or more collections of topics, the method further comprising: providing, for display, the document and the link to the other, related topic and the one or more links to the one or more collections of topics. | 0.879039 |
10. A network device comprising: a receiver to receive requests to play a plurality of programs, wherein each program of the plurality of programs is associated with a plurality of scenes and each scene is associated with dialog text; a memory to store a plurality of profiles, wherein each profile of the plurality of profiles is associated with a corresponding one of a plurality of users; a processor to instruct playing the programs on a display, determine whether a particular user of the plurality of users is present during the playing of each scene of each program of the plurality of programs and determining a particular profile, of the plurality of profiles, corresponding to the particular user based on the determination of whether the particular user of the plurality of users is present, and associate, in response to receiving the requests, each scene of the plurality of scenes during which the particular user was present and the corresponding dialog text during which the particular user was present with the particular profile; wherein the receiver is configured to receive a search query from the particular user associated with the particular profile; wherein the processor is configured to search the dialog text associated with the particular profile for dialog text that matches the search query; and a transmitter to transmit, for displaying on the display, an identification of the program and the scene associated with the matching dialog text, wherein when the processor associates each scene of the plurality of scenes during which the particular user was present and the corresponding dialog text during which the particular user was present with the particular profile, the processor is configured to store an indication that the particular user was present during the playing of the scene associated with the dialog text, wherein when the processor searches the dialog text associated with the particular profile, the processor is configured to exclude searching of dialog text not associated with the indication that the particular user was present during the playing of the scene, wherein the particular profile is associated with less than all of the plurality of scenes of one of the programs, and wherein when the processor searches the dialog text associated with the particular profile for dialog text that matches the search query, the processor is configured to recognize an object in one of the scenes with the matching dialog text and wherein the object does not match the search query. | 10. A network device comprising: a receiver to receive requests to play a plurality of programs, wherein each program of the plurality of programs is associated with a plurality of scenes and each scene is associated with dialog text; a memory to store a plurality of profiles, wherein each profile of the plurality of profiles is associated with a corresponding one of a plurality of users; a processor to instruct playing the programs on a display, determine whether a particular user of the plurality of users is present during the playing of each scene of each program of the plurality of programs and determining a particular profile, of the plurality of profiles, corresponding to the particular user based on the determination of whether the particular user of the plurality of users is present, and associate, in response to receiving the requests, each scene of the plurality of scenes during which the particular user was present and the corresponding dialog text during which the particular user was present with the particular profile; wherein the receiver is configured to receive a search query from the particular user associated with the particular profile; wherein the processor is configured to search the dialog text associated with the particular profile for dialog text that matches the search query; and a transmitter to transmit, for displaying on the display, an identification of the program and the scene associated with the matching dialog text, wherein when the processor associates each scene of the plurality of scenes during which the particular user was present and the corresponding dialog text during which the particular user was present with the particular profile, the processor is configured to store an indication that the particular user was present during the playing of the scene associated with the dialog text, wherein when the processor searches the dialog text associated with the particular profile, the processor is configured to exclude searching of dialog text not associated with the indication that the particular user was present during the playing of the scene, wherein the particular profile is associated with less than all of the plurality of scenes of one of the programs, and wherein when the processor searches the dialog text associated with the particular profile for dialog text that matches the search query, the processor is configured to recognize an object in one of the scenes with the matching dialog text and wherein the object does not match the search query. 11. The network device of claim 10 , wherein the object is an inanimate object, wherein the receiver is configured to receive, from the user, a selection of the identified program associated with the matching dialog text and a selection of the object, wherein the processor instructs a display to play the selected program starting at a time corresponding to the matching dialog text, and wherein the processor is configured to perform a search, based on the selection of the object, and wherein the transmitter is configured to send results of the search based on the selection of the object for display to the user. | 0.501717 |
6. A system comprising: a processor; a storage medium for tangibly storing thereon program logic for execution by the processor, the program logic comprising: logic executed by the processor for generating a database that stores associations between each of a plurality of media objects and temporal, spatial, social network or topical data, wherein the database includes relationships between specific media objects and metadata sources associated with a specific media object, user profile data, social network data or interaction data; logic executed by the processor for receiving a request from a requesting device associated with a user for media; logic executed by the processor for parsing the request to identify at least two of social criteria, topical criteria, or temporal criteria included in the request, the social criteria describing one or more people or types of people associated with the requested media, the topical criteria describing one or more topics associated with the requested media, and the temporal criteria describing a past time period associated with the requested media; logic executed by the processor for determining, when the request includes social criteria, media associated with the one or more people or types of people defined by the social criteria based on the association; logic executed by the processor for identifying, when the request includes topical criteria, topics associated with the request and determining media associated with the identified topics based on the association; logic executed by the processor for identifying, when the request includes temporal criteria, a time associated with the request and determining media associated with the identified time based on the association; logic executed by the processor for locating a plurality of media files that each match the at least two of social criteria, topical criteria, or temporal criteria included in the request based on the determined media associated with the one or more people or types of people, media associated with the identified topics, or media associated with the identified time; and logic executed by the processor for transmitting the plurality of media files on the playlist over the network to the requesting device. | 6. A system comprising: a processor; a storage medium for tangibly storing thereon program logic for execution by the processor, the program logic comprising: logic executed by the processor for generating a database that stores associations between each of a plurality of media objects and temporal, spatial, social network or topical data, wherein the database includes relationships between specific media objects and metadata sources associated with a specific media object, user profile data, social network data or interaction data; logic executed by the processor for receiving a request from a requesting device associated with a user for media; logic executed by the processor for parsing the request to identify at least two of social criteria, topical criteria, or temporal criteria included in the request, the social criteria describing one or more people or types of people associated with the requested media, the topical criteria describing one or more topics associated with the requested media, and the temporal criteria describing a past time period associated with the requested media; logic executed by the processor for determining, when the request includes social criteria, media associated with the one or more people or types of people defined by the social criteria based on the association; logic executed by the processor for identifying, when the request includes topical criteria, topics associated with the request and determining media associated with the identified topics based on the association; logic executed by the processor for identifying, when the request includes temporal criteria, a time associated with the request and determining media associated with the identified time based on the association; logic executed by the processor for locating a plurality of media files that each match the at least two of social criteria, topical criteria, or temporal criteria included in the request based on the determined media associated with the one or more people or types of people, media associated with the identified topics, or media associated with the identified time; and logic executed by the processor for transmitting the plurality of media files on the playlist over the network to the requesting device. 8. The system of claim 6 wherein the request for media related to a context has a trigger condition and the request is not processed until the trigger condition occurs, wherein the trigger condition is selected from the list: a time, a date, a calendar event, the presence of the requesting device in a physical location, display of an advertisement on the requesting device, selection of an advertisement on the requesting device. | 0.5 |
17. A system for detecting graymail without explicit user feedback, comprising: a data analytics computer system, comprising: a processing element; and a memory, coupled to the processing element, on which is stored software for predicting whether a user would consider an email graymail, comprising instructions that when executed cause the processing element of the data analytics computer system to: receive a non-spam email for a user; extract features of the email; predict with a classifier model based on the extracted features whether the user would consider the email as graymail; and train the classifier model responsive to tracked user actions; and a tracking engine computer system, comprising: a processing element; a tracking database; and a memory coupled to the processing element, on which is stored software for tracking user actions on the email, comprising instructions that when executed cause the processing element of the tracking engine computer system to: modify the email by inserting tracking information before delivering the email to the user; storing the inserted tracking information in a tracking database; track user actions on the email without explicit user feedback using the inserted tracking information; update the tracking database upon detection of tracked user actions on the email; determine whether the user considered the email as graymail responsive to the tracked user actions without explicit user feedback; and provide information regarding the determination to the data analytics computer system for training the classifier model. | 17. A system for detecting graymail without explicit user feedback, comprising: a data analytics computer system, comprising: a processing element; and a memory, coupled to the processing element, on which is stored software for predicting whether a user would consider an email graymail, comprising instructions that when executed cause the processing element of the data analytics computer system to: receive a non-spam email for a user; extract features of the email; predict with a classifier model based on the extracted features whether the user would consider the email as graymail; and train the classifier model responsive to tracked user actions; and a tracking engine computer system, comprising: a processing element; a tracking database; and a memory coupled to the processing element, on which is stored software for tracking user actions on the email, comprising instructions that when executed cause the processing element of the tracking engine computer system to: modify the email by inserting tracking information before delivering the email to the user; storing the inserted tracking information in a tracking database; track user actions on the email without explicit user feedback using the inserted tracking information; update the tracking database upon detection of tracked user actions on the email; determine whether the user considered the email as graymail responsive to the tracked user actions without explicit user feedback; and provide information regarding the determination to the data analytics computer system for training the classifier model. 24. The system of claim 17 , wherein the instructions that when executed cause the processing element of the tracking engine computer system to modify the email by inserting tracking information before delivering the email to the user comprise instructions that when executed cause the processing element of the tracking engine computer system to: identify the email with a unique identification before providing the email to the user, and wherein the instructions that when executed cause the tracking engine computer system to track user actions on the email without explicit user feedback using the inserted tracking information comprise instructions that when executed cause the tracking engine computer system to associate the user actions with the unique identification of the email. | 0.503918 |
5. A document alignment method comprising: inputting source leaves of a source document in first tree structured format, the first tree structured format comprising nodes which are ultimately connected with the source leaves by paths, each source leaf comprising text content; inputting target leaves of a target document in second tree structured format, the second tree structured format comprising nodes which are ultimately connected with the target leaves by paths, each target leaf comprising text content; subdividing the leaves of the source document and the leaves of the target document into blocks, each block including a set of the source leaves and a set of the target leaves; for each block, assigning a cost to each of a plurality of matches, each match comprising a pair of elements selected from the group consisting of a source leaf and a target leaf, an unmatched source leaf, and an unmatched target leaf from the same block; identifying a set of matches for which a total cost is minimal, wherein each of the input source and target leaves is in at least one of the identified matches; identifying, from the set of identified matches, groups of matches wherein each match in the group has a leaf in common; identifying, from the groups, probable matches in which more than one target leaf is matched with at least one source leaf and probable matches where more than one source leaf is matched with a target leaf; and outputting an alignment between leaves of the target document and leaves of the source document which includes the probable matches. | 5. A document alignment method comprising: inputting source leaves of a source document in first tree structured format, the first tree structured format comprising nodes which are ultimately connected with the source leaves by paths, each source leaf comprising text content; inputting target leaves of a target document in second tree structured format, the second tree structured format comprising nodes which are ultimately connected with the target leaves by paths, each target leaf comprising text content; subdividing the leaves of the source document and the leaves of the target document into blocks, each block including a set of the source leaves and a set of the target leaves; for each block, assigning a cost to each of a plurality of matches, each match comprising a pair of elements selected from the group consisting of a source leaf and a target leaf, an unmatched source leaf, and an unmatched target leaf from the same block; identifying a set of matches for which a total cost is minimal, wherein each of the input source and target leaves is in at least one of the identified matches; identifying, from the set of identified matches, groups of matches wherein each match in the group has a leaf in common; identifying, from the groups, probable matches in which more than one target leaf is matched with at least one source leaf and probable matches where more than one source leaf is matched with a target leaf; and outputting an alignment between leaves of the target document and leaves of the source document which includes the probable matches. 6. The document alignment method of claim 5 , further comprising: within each of the blocks, identifying any matches wherein a similarity measure between a leaf of the source document and a leaf of the target document exceeds a threshold value; and subdividing the leaves of the source document and the leaves of the target document into partitions bounded by the identified matches wherein the similarity measure between the leaf of the source document and the leaf of the target document exceeds a threshold value. | 0.615476 |
13. The method of claim 1 , further comprising determining a substantial match based upon a probability, greater than a particular threshold, that said extracted word and said known word are the same. | 13. The method of claim 1 , further comprising determining a substantial match based upon a probability, greater than a particular threshold, that said extracted word and said known word are the same. 14. The method of claim 13 , wherein said determining includes using at least one of: a Gaussian Mixture Model, voice recognition software, tone segmentation software, fundamental frequency information, vocal energy information, frequency spectral features, formants, linear predictive coding, neural networks, ensembles of classifiers, spectral analyzers, or signal amplifiers. | 0.828782 |
1. A language processing method, comprising: receiving an user utterance as an input sequence of token elements; parsing, using a parsing processor, the input sequence of the token elements using a parsing algorithm in a first mode applying regular production rules on the token elements and on multi-token classifiers for phrases obtained from the token elements, wherein each token element contains a token of an input string and/or at least one corresponding token classifier; controlling, when the first mode parsing does not result in a multi-token phrase encompassing all tokens of the input string, the parsing processor to parse the input sequence using the parsing algorithm in a second mode applying both the regular and artificial production rules, wherein the second mode comprises generating the artificial production rules on the basis of the input sequence and intermediate results of the parsing using the parsing algorithm in the first mode, the intermediate results being based on lexical category of the token of the input string; and matching the parsed input sequence to one of a plurality of predefined machine commands to generate a command based on the input sequence, wherein the parsing algorithm comprises calculating probabilities for all possible subsequences and selecting, for each sequence of token classifiers within the input sequence, the subsequences with a highest probability, and each of the artificial production rules has a probability value lower than any of the regular production rules, the probability value being set such that at most one artificial production rule of the artificial production rules is used when parsing the input sequence using the parsing algorithm in the second mode, and the probability value being increased when the artificial production rule is successfully applied. | 1. A language processing method, comprising: receiving an user utterance as an input sequence of token elements; parsing, using a parsing processor, the input sequence of the token elements using a parsing algorithm in a first mode applying regular production rules on the token elements and on multi-token classifiers for phrases obtained from the token elements, wherein each token element contains a token of an input string and/or at least one corresponding token classifier; controlling, when the first mode parsing does not result in a multi-token phrase encompassing all tokens of the input string, the parsing processor to parse the input sequence using the parsing algorithm in a second mode applying both the regular and artificial production rules, wherein the second mode comprises generating the artificial production rules on the basis of the input sequence and intermediate results of the parsing using the parsing algorithm in the first mode, the intermediate results being based on lexical category of the token of the input string; and matching the parsed input sequence to one of a plurality of predefined machine commands to generate a command based on the input sequence, wherein the parsing algorithm comprises calculating probabilities for all possible subsequences and selecting, for each sequence of token classifiers within the input sequence, the subsequences with a highest probability, and each of the artificial production rules has a probability value lower than any of the regular production rules, the probability value being set such that at most one artificial production rule of the artificial production rules is used when parsing the input sequence using the parsing algorithm in the second mode, and the probability value being increased when the artificial production rule is successfully applied. 3. The method according to claim 1 , comprising checking, for every possible sequence of token elements within the input sequence, whether the sequence can be construed on the basis of the regular production rules, and applying, only when the sequence cannot be construed on the basis of the regular production rules, one of the artificial production rules to obtain constituent information descriptive for one or more grammatical functions of the sequence. | 0.69385 |
14. The system of claim 13 , the processing device to: receive the second software release comprising the second set of software packages, and parse the second software release to identify second modeling information comprising package information, package dependency information, and function dependency information associated with each software package in the second set of software packages. | 14. The system of claim 13 , the processing device to: receive the second software release comprising the second set of software packages, and parse the second software release to identify second modeling information comprising package information, package dependency information, and function dependency information associated with each software package in the second set of software packages. 17. The system of claim 14 , the processing device to search at least one of the first graph model or the second graph model using a depth-first search. | 0.954974 |
5. The system of claim 1 , wherein the report processed by the OLAP system includes one or more formatting macros, and the server system further processes the one or more formatting macros to format the report for presentation in the spreadsheet application displayed within the instance of the web browser. | 5. The system of claim 1 , wherein the report processed by the OLAP system includes one or more formatting macros, and the server system further processes the one or more formatting macros to format the report for presentation in the spreadsheet application displayed within the instance of the web browser. 6. The system of claim 5 , further comprising an application program interface that defines characteristics of the report processed by the OLAP system, wherein the OLAP system creates the one or more formatting macros from the characteristics of the report that the application program interface defines. | 0.914036 |
1. A method for augmenting an audio signal comprising acts of: receiving an audio signal, extracting features from said audio signal, generating a time ordered table of dramatic parameters according to the extracted features, wherein the dramatic parameters include mood, changes of pace and incidents, selecting a story template at least in part in dependence on said table of dramatic parameters, wherein said story template comprises dramatic parameter data related to a narrative story structure, obtaining media fragments at least in part in dependence on the table of dramatic parameters by matching the dramatic parameters of the selected story template with those of the media fragments, and outputting said media fragments in tandem with said audio signal. | 1. A method for augmenting an audio signal comprising acts of: receiving an audio signal, extracting features from said audio signal, generating a time ordered table of dramatic parameters according to the extracted features, wherein the dramatic parameters include mood, changes of pace and incidents, selecting a story template at least in part in dependence on said table of dramatic parameters, wherein said story template comprises dramatic parameter data related to a narrative story structure, obtaining media fragments at least in part in dependence on the table of dramatic parameters by matching the dramatic parameters of the selected story template with those of the media fragments, and outputting said media fragments in tandem with said audio signal. 10. The method according to claim 1 , wherein the story template for selection is generated according to logical story structure rules and the dramatic parameter list. | 0.612587 |
1. A method for encoding a plurality of key matching rules grouped in a chunk, each of the key matching rules beginning with a header and having at least one dimension, the method comprising: in a rule encoding engine, communicatively coupled to memory and provided with a chunk of key matching rules, building a multi-rule corresponding to the chunk comprising: storing in the memory a multi-rule header of the multi-rule, the multi-rule header representing, collectively, a plurality of headers stored one after the other, the multi-rule header being decoded by a rule matching engine in a single decode operation to extract the plurality of headers of the key matching rules, wherein the plurality of headers include values which control the rule matching engine processing of the key matching rules, including dimensions, the rule matching engine formats the key matching rules based on a key and matches the key matching rules against the key to find a match based on the values stored in the plurality of headers. | 1. A method for encoding a plurality of key matching rules grouped in a chunk, each of the key matching rules beginning with a header and having at least one dimension, the method comprising: in a rule encoding engine, communicatively coupled to memory and provided with a chunk of key matching rules, building a multi-rule corresponding to the chunk comprising: storing in the memory a multi-rule header of the multi-rule, the multi-rule header representing, collectively, a plurality of headers stored one after the other, the multi-rule header being decoded by a rule matching engine in a single decode operation to extract the plurality of headers of the key matching rules, wherein the plurality of headers include values which control the rule matching engine processing of the key matching rules, including dimensions, the rule matching engine formats the key matching rules based on a key and matches the key matching rules against the key to find a match based on the values stored in the plurality of headers. 2. The method of claim 1 wherein storing the multi-rule header of the multi-rule further includes storing, consecutively, a rule validity value for each of the key matching rules of the chunk in which storing a first value for the rule validity value corresponding to a subject key matching rule enables matching of the subject key matching rule, while storing a second value instead of the first value disables matching of the subject key matching rule. | 0.5 |
16. The non-transitory computer readable storage medium of claim 15 , further including instructions that, when executed by the processor, cause the processor to: query a structured data source for a set of token values to be protected; add the set of token values to a token list, each token value in the set representing one of the individual attributes in the structured data; sort the set of token values in the list based on one or more sorting rules; and pass the sorted token values to the first Bloom filter. | 16. The non-transitory computer readable storage medium of claim 15 , further including instructions that, when executed by the processor, cause the processor to: query a structured data source for a set of token values to be protected; add the set of token values to a token list, each token value in the set representing one of the individual attributes in the structured data; sort the set of token values in the list based on one or more sorting rules; and pass the sorted token values to the first Bloom filter. 17. The non-transitory computer readable storage medium of claim 16 , further including instructions that, when executed by the processor, cause the processor to: append one or more token values in the sorted list to form a concatenated token; and pass the concatenated token to the second Bloom filter. | 0.730627 |
1. A method for producing a dental shaped body from a blank having a corpus of tooth restoration material by a tool adapted to remove said material, wherein, to detect a position of said corpus inserted in a machining device, contact scanning is performed on said blank by said tool, the method including steps of: providing a machining tool in a first position; detecting at least one geometric structure on said blank, the at least one geometric structure defines information that corresponds to at least one relevant dimension of said blank corpus; and using the information that corresponds to said at least one relevant dimension of said blank corpus to preposition said machining tool to a second position at or close to a first reference surface or a first reference structure for a contacting operation; determining a position of the first reference surface or first reference structure by contact scanning from said second position; and using the determined position as a starting position to detect one or more other geometric structures and/or to perform one or more other contact scanning such that contacting times of the tool during contact scanning and/or machining times of the tool during machining are reduced. | 1. A method for producing a dental shaped body from a blank having a corpus of tooth restoration material by a tool adapted to remove said material, wherein, to detect a position of said corpus inserted in a machining device, contact scanning is performed on said blank by said tool, the method including steps of: providing a machining tool in a first position; detecting at least one geometric structure on said blank, the at least one geometric structure defines information that corresponds to at least one relevant dimension of said blank corpus; and using the information that corresponds to said at least one relevant dimension of said blank corpus to preposition said machining tool to a second position at or close to a first reference surface or a first reference structure for a contacting operation; determining a position of the first reference surface or first reference structure by contact scanning from said second position; and using the determined position as a starting position to detect one or more other geometric structures and/or to perform one or more other contact scanning such that contacting times of the tool during contact scanning and/or machining times of the tool during machining are reduced. 14. The method as defined in claim 1 , further comprising detecting a position of a structure located on said corpus by scanning a structure located on said corpus. | 0.563031 |
6. A method comprising: extracting features of input speech signals, by a feature extractor implemented by at least one hardware processor, and applying sequences of one or more labels to the extracted features; implementing, by the at least one hardware processor, a non-optimized composed weighted speech transducer based on signals representing a hidden Markov model (HMM) transducer, a context dependent phone model, a lexicon model for pronunciation dictionary, and an N-gram language model for sentence probability; and outputting decisions, by a decoder implemented by the at least one hardware processor, about the input speech signals based, at least in part, on the sequences of labels and the non-optimized composed weighted speech transducer. | 6. A method comprising: extracting features of input speech signals, by a feature extractor implemented by at least one hardware processor, and applying sequences of one or more labels to the extracted features; implementing, by the at least one hardware processor, a non-optimized composed weighted speech transducer based on signals representing a hidden Markov model (HMM) transducer, a context dependent phone model, a lexicon model for pronunciation dictionary, and an N-gram language model for sentence probability; and outputting decisions, by a decoder implemented by the at least one hardware processor, about the input speech signals based, at least in part, on the sequences of labels and the non-optimized composed weighted speech transducer. 10. The method of claim 6 , wherein: the feature extractor is configured to operate online and synchronously with the input speech signals; and the non-optimized composed weighted speech transducer is produced offline and asynchronously with the input speech signals. | 0.627917 |
36. The system of claim 35 , wherein the synonym recognition unit is for considering how many words or phrases within the fields are similar and how many words or phrases within the fields are dissimilar in determining whether the at least one input document contains any synonyms with terms that occur in the at least one existing document. | 36. The system of claim 35 , wherein the synonym recognition unit is for considering how many words or phrases within the fields are similar and how many words or phrases within the fields are dissimilar in determining whether the at least one input document contains any synonyms with terms that occur in the at least one existing document. 37. The system of claim 36 , wherein the synonym recognition unit is for outputting the dissimilar words or phrases within the fields as candidate synonyms. | 0.935593 |
4. The method of claim 2 including the further step of calculating a consistency measure indicative of speech quality for each class separately with a plurality of statistical models. | 4. The method of claim 2 including the further step of calculating a consistency measure indicative of speech quality for each class separately with a plurality of statistical models. 5. The method of claim 4 including the further step of employing the consistency measures to obtain an estimate of subjective scores. | 0.9375 |
2. The method of claim 1 further comprising the steps of setting a second threshold value and remaining in said non-speech recognition process until a likelihood cost of said silence template in better than said second threshold. | 2. The method of claim 1 further comprising the steps of setting a second threshold value and remaining in said non-speech recognition process until a likelihood cost of said silence template in better than said second threshold. 3. The method of claim 2 further wherein there are two silence template patterns, a first short silence pattern employed during said reverting step, and a second long silence pattern employed during said remaining step. | 0.917353 |
2. The computer-implemented method of claim 1 , wherein the preprocessing comprises: matching the prefix and the trailing context in the first document with the matching prefixes in the transformation database. | 2. The computer-implemented method of claim 1 , wherein the preprocessing comprises: matching the prefix and the trailing context in the first document with the matching prefixes in the transformation database. 8. The computer-implemented method of claim 2 , wherein the transformation database comprises a data model that allows a translation from one natural human language to another natural human language. | 0.941623 |
21. The one or more computer-readable storage devices of claim 19 , wherein the electronic content item includes an image area and the parameters comprise rule parameters indicating arrangement of the identifying area and arrangement of the image area with respect to display of the electronic content item, and characteristic parameters indicating style of the identifying area. | 21. The one or more computer-readable storage devices of claim 19 , wherein the electronic content item includes an image area and the parameters comprise rule parameters indicating arrangement of the identifying area and arrangement of the image area with respect to display of the electronic content item, and characteristic parameters indicating style of the identifying area. 22. The one or more computer-readable storage devices of claim 21 , wherein the electronic content item includes an item for sale in connection with an electronic marketplace, the image area being associated with the item and including an image depicting a feature or a use of the item for sale in connection with the electronic marketplace. | 0.856269 |
1. A computer-implemented method comprising: identifying a plurality of image search results that are responsive to a search query; determining that a relevance score for a particular image search result from the plurality of image search results meets a specified relevance score threshold, wherein the relevance score is determined independent of visual similarity between a particular image referenced by the particular image search result and other images that are referenced by the plurality of image search results; determining that image similarity data for the particular image indicates that the particular image meets a threshold level of visual similarity to at least a threshold number of the other images that are referenced by the plurality of image search results; determining that the particular image search result is a co-relevant image search result for the search query, the determination being performed in response to determining that both the relevance score meets the specified relevance score threshold, and the image similarity data for the particular image indicates that the particular image meets the threshold level of visual similarity to at least the threshold number of the other images; and generating an image rank score for the particular image search result based on the relevance score and an amplification factor for image search results that are determined to be co-relevant, wherein the amplification factor is used to increase or decrease the image rank score. | 1. A computer-implemented method comprising: identifying a plurality of image search results that are responsive to a search query; determining that a relevance score for a particular image search result from the plurality of image search results meets a specified relevance score threshold, wherein the relevance score is determined independent of visual similarity between a particular image referenced by the particular image search result and other images that are referenced by the plurality of image search results; determining that image similarity data for the particular image indicates that the particular image meets a threshold level of visual similarity to at least a threshold number of the other images that are referenced by the plurality of image search results; determining that the particular image search result is a co-relevant image search result for the search query, the determination being performed in response to determining that both the relevance score meets the specified relevance score threshold, and the image similarity data for the particular image indicates that the particular image meets the threshold level of visual similarity to at least the threshold number of the other images; and generating an image rank score for the particular image search result based on the relevance score and an amplification factor for image search results that are determined to be co-relevant, wherein the amplification factor is used to increase or decrease the image rank score. 4. The method of claim 1 , wherein generating the image rank score comprises determining a product of the amplification factor and the relevance score. | 0.760306 |
1. A database search method comprising the computer implemented steps of: providing access to a database having a plurality of records in respective categories of information, each record having one or more facets to the respective category of information; receiving user input of a first search term formed of a first parameter indicative of at least one category of information of the database; searching the database for records of the at least one category of information; in response to the user input of the first search term, simultaneously displaying both in a same screen view: (a) a set of search results, including records from the database of the at least one category of information, and (b) a listing of any one or combination of facets and facet values of the records in the set of search results, the listing serving as suggested additional parameters for further refining the first search term upon user selection of the any one or combination of facets and facet values; enabling user input of a second search term formed of a second parameter; and in response to user selection of any one or combination of facets and facet values from the listing or user input of the second search term, refining the first search term based on the user selection of the any one or combination of facets and facet values from the listing or user input of the second search term, resulting in (i) a refined search term formed of the first parameter plus the user-selected any one or combination of facets and facet values or user-inputted second search term, and (ii) a search of the database using the refined search term, wherein at least one of the any one or combination of facets and facet values is defined by a community of users and corresponds to content generated by the community of users. | 1. A database search method comprising the computer implemented steps of: providing access to a database having a plurality of records in respective categories of information, each record having one or more facets to the respective category of information; receiving user input of a first search term formed of a first parameter indicative of at least one category of information of the database; searching the database for records of the at least one category of information; in response to the user input of the first search term, simultaneously displaying both in a same screen view: (a) a set of search results, including records from the database of the at least one category of information, and (b) a listing of any one or combination of facets and facet values of the records in the set of search results, the listing serving as suggested additional parameters for further refining the first search term upon user selection of the any one or combination of facets and facet values; enabling user input of a second search term formed of a second parameter; and in response to user selection of any one or combination of facets and facet values from the listing or user input of the second search term, refining the first search term based on the user selection of the any one or combination of facets and facet values from the listing or user input of the second search term, resulting in (i) a refined search term formed of the first parameter plus the user-selected any one or combination of facets and facet values or user-inputted second search term, and (ii) a search of the database using the refined search term, wherein at least one of the any one or combination of facets and facet values is defined by a community of users and corresponds to content generated by the community of users. 11. A method as claimed in claim 1 , wherein for categories of information pertaining to people, the facets include any of gender, school, age, marital/family status, geographic location, group membership, company/business entity, entertainment/literature interest, and tags, by member connection, and by connection type/group. | 0.523016 |
1. A method comprising: determining that an electronic document includes a first phrase that is at least similar to a first phrase of a plurality of phrases in a database and a second phrase that is at least similar to a second phrase of a plurality of phrases in the database, wherein the electronic document includes content contributed by a plurality of contributors; determining that a first contributor of the plurality of contributors is associated with the first phrase in the electronic document and a second contributor of the plurality of contributors is associated with the second phrase in the electronic document; determining that the first phrase identifies a first text effect in the electronic document and that the second phrase identifies a second text effect in the electronic document; determining that metadata of the electronic document indicates that first content of the electronic document comprises the first text effect and that second content of the electronic document comprises the second text effect; creating a first mapping between the first contributor and the first text effect and a second mapping between the second contributor and the second text effect after determining that the metadata of the electronic document indicates that the first content comprises the first text effect and the second content comprises the second text effect; determining a first location in the electronic document of the first content and a second location in the electronic document of the second content; associating the first location with the first mapping and the second location with the second mapping; supplying the first mapping and the second mapping for presenting of the electronic document; and modifying the electronic document to include an indication of the first contributor at the first location and an indication of the second contributor at the second location. | 1. A method comprising: determining that an electronic document includes a first phrase that is at least similar to a first phrase of a plurality of phrases in a database and a second phrase that is at least similar to a second phrase of a plurality of phrases in the database, wherein the electronic document includes content contributed by a plurality of contributors; determining that a first contributor of the plurality of contributors is associated with the first phrase in the electronic document and a second contributor of the plurality of contributors is associated with the second phrase in the electronic document; determining that the first phrase identifies a first text effect in the electronic document and that the second phrase identifies a second text effect in the electronic document; determining that metadata of the electronic document indicates that first content of the electronic document comprises the first text effect and that second content of the electronic document comprises the second text effect; creating a first mapping between the first contributor and the first text effect and a second mapping between the second contributor and the second text effect after determining that the metadata of the electronic document indicates that the first content comprises the first text effect and the second content comprises the second text effect; determining a first location in the electronic document of the first content and a second location in the electronic document of the second content; associating the first location with the first mapping and the second location with the second mapping; supplying the first mapping and the second mapping for presenting of the electronic document; and modifying the electronic document to include an indication of the first contributor at the first location and an indication of the second contributor at the second location. 2. The method of claim 1 , wherein the supplying the first mapping and the second mapping comprises providing, to an accessibility device, the modified electronic document. | 0.832689 |
1. A computer implemented method for implementing a mixed-signal electronic design using standardized power data, comprising: at least one processor or at least one processor core executing a process, the process comprising: identifying a mixed-signal electronic design; identifying, generating, or modifying, with an aid of a standardized power format mechanism including or coupled with the at least one processor, standardized power data in a standardized power format having an illegal signal in the mixed-signal electronic design by introducing one or more changes to generate updated standardized power data from the standardized power data; and implementing the mixed-signal electronic design by using the updated standardized power data including the illegal signal for manufacturing of a mixed signal electronic circuit, wherein the illegal signal is not recognized by a standardized power format framework for the standardized power format and comprises at least one of a power control signal or an expression including an incompatible or illegal signal to implement power intent for the mixed-signal electronic design. | 1. A computer implemented method for implementing a mixed-signal electronic design using standardized power data, comprising: at least one processor or at least one processor core executing a process, the process comprising: identifying a mixed-signal electronic design; identifying, generating, or modifying, with an aid of a standardized power format mechanism including or coupled with the at least one processor, standardized power data in a standardized power format having an illegal signal in the mixed-signal electronic design by introducing one or more changes to generate updated standardized power data from the standardized power data; and implementing the mixed-signal electronic design by using the updated standardized power data including the illegal signal for manufacturing of a mixed signal electronic circuit, wherein the illegal signal is not recognized by a standardized power format framework for the standardized power format and comprises at least one of a power control signal or an expression including an incompatible or illegal signal to implement power intent for the mixed-signal electronic design. 6. The computer implemented method of claim 1 , the process further comprising: processing power related content in the mixed-signal electronic design using one or more native processes or modules in a standardized power format framework for the standardized power format; and performing virtual port mapping for a port of a circuit design block in the mixed-signal electronic circuit to generate a virtual port for the port. | 0.691017 |
18. The method of claim 17 , further comprising the steps of: selecting one or more of the zeta words to be anchor words; encoding in a vector a ζ , the probabilities of the anchor words, given that the process snippet contains one or more zeta words; creating a sparse vector a μ , that estimates the probabilities for the non-zeta words in the process snippet; and combining by direct weighted sum the vector a ζ and the sparse vector a μ into the sparse vector a of the process dot:
a=b ζ a ζ ⊕b μ a μ with weights b ζ and b μ . | 18. The method of claim 17 , further comprising the steps of: selecting one or more of the zeta words to be anchor words; encoding in a vector a ζ , the probabilities of the anchor words, given that the process snippet contains one or more zeta words; creating a sparse vector a μ , that estimates the probabilities for the non-zeta words in the process snippet; and combining by direct weighted sum the vector a ζ and the sparse vector a μ into the sparse vector a of the process dot:
a=b ζ a ζ ⊕b μ a μ with weights b ζ and b μ . 21. The method of claim 18 , wherein each entry in the sparse vector a of the compact representation is proportional to a probability that a feature is observed given an execution environment. | 0.803797 |
16. A system for multilingual data query, the system comprising: a user interface comprising hardware and configured to receive a query, the query including a base word in a source language used for a search of a database in a target language; a set of core enterprise services components; a set of multilingual service components; and a process flow manager configured to receive the query from the user interface and to select a subset of the components from the set of core enterprise services components and the set of multilingual service components based on a set of factors to process the query, the set of factors comprising: an interface factor to indicate a speed of a connection between the components, a component availability factor to indicate the availability of the components, a language identification factor to indicate the source language, a required speed factor for indicating an amount of time required by a user for the query to return a result, a required quality factor, and a user language fluency factor. | 16. A system for multilingual data query, the system comprising: a user interface comprising hardware and configured to receive a query, the query including a base word in a source language used for a search of a database in a target language; a set of core enterprise services components; a set of multilingual service components; and a process flow manager configured to receive the query from the user interface and to select a subset of the components from the set of core enterprise services components and the set of multilingual service components based on a set of factors to process the query, the set of factors comprising: an interface factor to indicate a speed of a connection between the components, a component availability factor to indicate the availability of the components, a language identification factor to indicate the source language, a required speed factor for indicating an amount of time required by a user for the query to return a result, a required quality factor, and a user language fluency factor. 17. The system of claim 16 wherein the subset of the components comprises at least one of: a lexer, a transcoder, a translator, a morphological analyzer, a word list, a corrector, and an optical character recognition (OCR) device. | 0.667787 |
1. A computer-server-based method for ranking Web pages in a Web search engine, the method comprising: receiving, over a network at the computer server, a Web search query from a particular user, the Web search query including at least one keyword, the computer server hosting the Web search engine; identifying one or more Web pages that contain the at least one keyword; determining, for each of the one or more Web pages, a raw page ranking; adjusting the raw page ranking of each of at least one Web page among the one or more Web pages based on direct evidence of how interesting the respective Web page is to users to produce an adjusted page ranking, the direct evidence being derived from clickstream data collected from the users; and presenting, as search results, the at least one Web page to the particular user in accordance with the adjusted page rankings, wherein the direct evidence of how interesting a Web page is to users includes a measure of how often the users traverse to or from the Web page in browsing the Web and a measure of how many users have recently visited the Web page compared with how many users normally visit the Web page, and wherein the measure of how many users have recently visited the Web page compared with how many users normally visit the Web page is given greater weight than the measure of how often the users traverse to or from the Web page in browsing the Web. | 1. A computer-server-based method for ranking Web pages in a Web search engine, the method comprising: receiving, over a network at the computer server, a Web search query from a particular user, the Web search query including at least one keyword, the computer server hosting the Web search engine; identifying one or more Web pages that contain the at least one keyword; determining, for each of the one or more Web pages, a raw page ranking; adjusting the raw page ranking of each of at least one Web page among the one or more Web pages based on direct evidence of how interesting the respective Web page is to users to produce an adjusted page ranking, the direct evidence being derived from clickstream data collected from the users; and presenting, as search results, the at least one Web page to the particular user in accordance with the adjusted page rankings, wherein the direct evidence of how interesting a Web page is to users includes a measure of how often the users traverse to or from the Web page in browsing the Web and a measure of how many users have recently visited the Web page compared with how many users normally visit the Web page, and wherein the measure of how many users have recently visited the Web page compared with how many users normally visit the Web page is given greater weight than the measure of how often the users traverse to or from the Web page in browsing the Web. 4. The computer-server-based method of claim 1 , wherein the measure of how many users have recently visited a Web page compared with how many users normally visit the Web page is based on how many users visited the Web page during a recent predetermined unit of time compared with how many users, on average, visited the Web page during one or more predetermined units of time preceding the recent predetermined unit of time, as indicated by the clickstream data. | 0.601884 |
6. The article of manufacture of claim 1 , wherein said developing pairs of alternatives statements further comprises identification of at least one of: expectations, requirements, frustrations, concerns, areas of strife within said participating entity, and areas of strife between said participating entities. | 6. The article of manufacture of claim 1 , wherein said developing pairs of alternatives statements further comprises identification of at least one of: expectations, requirements, frustrations, concerns, areas of strife within said participating entity, and areas of strife between said participating entities. 7. The article of manufacture of claim 6 , wherein said identification further considers differing approaches, preferences, norms, customs, styles, beliefs, mindsets, assumptions, and priorities among one or more members of said participating entity or entities. | 0.94622 |
7. A bundle database management method for generating, storing, and searching bundle data defining an association structure between individual words having relation to each other, the method comprising the steps of: (1) defining, with a processor, a core word, a relevant word connected to the core word, and another relevant word derived from the relevant word regarded as another core word, generating bundle data defining an nth connection relation between the core word and the relevant word as a graph hierarchy structure, and storing the generated bundle data; (2) storing description data in a memory, the description data corresponding to the core word and the relevant word; (3) receiving a search request including a specific search word input by a user; (4) generating, with a processor, a search result page including the bundle data having a search word as its core word and the description data relating to the core word; and (5) transmitting the search result page to a user terminal, wherein the step (4) comprises connecting a first bundle with a second bundle to generate a single nth bundle data; and in the case of connecting the first bundle with the second bundle having, as a core word, a same word as an arbitrary word of the first bundle to generate a connected bundle, the step (4) comprises, while maintaining word association structures of the first and second bundles in the connected bundle, integrating each same word of the first bundle and the second bundle into one word relative to the first bundle, connecting bundle data of the first and second bundles in such a way to add words of the second bundle to the first bundle, and integrating each description data of the first and second bundles into a description data of the integrated word, wherein the step of (4) generating a search result page includes the step of including the bundle data in the search result page, the bundle data being in odd bundles (n=1, 3, 5, . . . ) represented in such a graphic structure that at least one relevant word for each core word are horizontally connects and in even bundles (n=2, 4, 6, . . . ) represented in such a graphic structure that at least one relevant word for each core word are vertically connected. | 7. A bundle database management method for generating, storing, and searching bundle data defining an association structure between individual words having relation to each other, the method comprising the steps of: (1) defining, with a processor, a core word, a relevant word connected to the core word, and another relevant word derived from the relevant word regarded as another core word, generating bundle data defining an nth connection relation between the core word and the relevant word as a graph hierarchy structure, and storing the generated bundle data; (2) storing description data in a memory, the description data corresponding to the core word and the relevant word; (3) receiving a search request including a specific search word input by a user; (4) generating, with a processor, a search result page including the bundle data having a search word as its core word and the description data relating to the core word; and (5) transmitting the search result page to a user terminal, wherein the step (4) comprises connecting a first bundle with a second bundle to generate a single nth bundle data; and in the case of connecting the first bundle with the second bundle having, as a core word, a same word as an arbitrary word of the first bundle to generate a connected bundle, the step (4) comprises, while maintaining word association structures of the first and second bundles in the connected bundle, integrating each same word of the first bundle and the second bundle into one word relative to the first bundle, connecting bundle data of the first and second bundles in such a way to add words of the second bundle to the first bundle, and integrating each description data of the first and second bundles into a description data of the integrated word, wherein the step of (4) generating a search result page includes the step of including the bundle data in the search result page, the bundle data being in odd bundles (n=1, 3, 5, . . . ) represented in such a graphic structure that at least one relevant word for each core word are horizontally connects and in even bundles (n=2, 4, 6, . . . ) represented in such a graphic structure that at least one relevant word for each core word are vertically connected. 10. The bundle database management method of claim 7 , wherein the step of (4) generating a search result page includes the steps of: (4-1) setting the received search word as a core word; (4-2) retrieving the bundle data DB by the core word to search for the bundle data; (4-3) retrieving the description data DB by the core word to search for the corresponding description data; and (4-4) generating the search result page including the bundle data and the description data. | 0.847895 |
18. One or more processor-readable storage mediums storing processor-readable program code implemented at least in part by one or more processors for executing acts comprising: providing a community question-answer (CQA) application for presenting a CQA website implemented at a first CQA server; obtaining a plurality of positive first question-answer (q-a) pairs, each positive first q-a pair containing a first question and a first answer previously identified as a high-quality answer, and a plurality of negative first q-a pairs, each negative first q-a pair containing a first question and a first answer that is not a high-quality answer; storing the plurality of positive and negative first q-a pairs in a knowledge base on a memory at the first CQA server; creating a link prediction model from the plurality of positive and negative first q-a pairs; receiving a second question from a first computer in communication with the first CQA server; receiving a plurality of candidate second answers from one or more second computers in communication with the first CQA server in response to the second question; identifying a set of the first questions that are similar to the second question by considering only the first questions that are part of the positive first q-a pairs; determining first linking features between the identified set of first questions and the corresponding first answers making up each first q-a pair in the identified set; identifying a plurality of candidate second q-a pairs, each comprising the second question and one of the candidate second answers; determining second linking features between the second question and each of the candidate second answers for each candidate second q-a pair; using the link prediction model in combination with the first linking features for determining a likelihood of the second linking features of each candidate second q-a pair being analogous to the first linking features; obtaining a score for each candidate second q-a pair based upon the determined likelihood; ranking the candidate second q-a pairs according to the scores; and selecting the candidate second q-a pair having a score indicating a highest probability of analogy to the first linking features as containing a best answer. | 18. One or more processor-readable storage mediums storing processor-readable program code implemented at least in part by one or more processors for executing acts comprising: providing a community question-answer (CQA) application for presenting a CQA website implemented at a first CQA server; obtaining a plurality of positive first question-answer (q-a) pairs, each positive first q-a pair containing a first question and a first answer previously identified as a high-quality answer, and a plurality of negative first q-a pairs, each negative first q-a pair containing a first question and a first answer that is not a high-quality answer; storing the plurality of positive and negative first q-a pairs in a knowledge base on a memory at the first CQA server; creating a link prediction model from the plurality of positive and negative first q-a pairs; receiving a second question from a first computer in communication with the first CQA server; receiving a plurality of candidate second answers from one or more second computers in communication with the first CQA server in response to the second question; identifying a set of the first questions that are similar to the second question by considering only the first questions that are part of the positive first q-a pairs; determining first linking features between the identified set of first questions and the corresponding first answers making up each first q-a pair in the identified set; identifying a plurality of candidate second q-a pairs, each comprising the second question and one of the candidate second answers; determining second linking features between the second question and each of the candidate second answers for each candidate second q-a pair; using the link prediction model in combination with the first linking features for determining a likelihood of the second linking features of each candidate second q-a pair being analogous to the first linking features; obtaining a score for each candidate second q-a pair based upon the determined likelihood; ranking the candidate second q-a pairs according to the scores; and selecting the candidate second q-a pair having a score indicating a highest probability of analogy to the first linking features as containing a best answer. 19. The one or more processor-accessible storage mediums according to claim 18 , further comprising: marking the selected second candidate answer determined to be the best answer and presenting the selected second candidate answer as the best answer to users of the CQA website in conjunction with the second question. | 0.513439 |
19. A non-transitory computer-readable media for directing a computer to facilitate the encoding of communication data, the computer-readable media comprising: instructions for defining a bitmask table having a bitmask character value, wherein the bitmask character value identifies one or more character sets that include a character and the bitmask character value is adjusted based on an origin language corresponding to the character when the origin language is a Chinese, Japanese, or Korean (CJK) language and wherein the adjusted bitmask character value excludes a character set for a non-origin CJK language that includes the character; instructions for receiving communication data, wherein the communication data includes the character; instructions for generating a bit value based on the bitmask character value; instructions for selecting the character set based on the generated bit value; and instructions for encoding the character, wherein the character is encoded based on the selected character set. | 19. A non-transitory computer-readable media for directing a computer to facilitate the encoding of communication data, the computer-readable media comprising: instructions for defining a bitmask table having a bitmask character value, wherein the bitmask character value identifies one or more character sets that include a character and the bitmask character value is adjusted based on an origin language corresponding to the character when the origin language is a Chinese, Japanese, or Korean (CJK) language and wherein the adjusted bitmask character value excludes a character set for a non-origin CJK language that includes the character; instructions for receiving communication data, wherein the communication data includes the character; instructions for generating a bit value based on the bitmask character value; instructions for selecting the character set based on the generated bit value; and instructions for encoding the character, wherein the character is encoded based on the selected character set. 22. The computer-readable media as recited in claim 19 , wherein a preferred language is a Chinese, Japanese, or Korean (CJK) language. | 0.5 |
1. A method of searching for desired information, the method comprising: receiving, from a user having user profile data associated therewith, a search request comprising a search argument; providing, to a first search engine, the received search argument for correlation with first contextual information in a database of network related information; providing, to a second search engine, the received search argument and the user profile data for correlation with a first advertisement in an advertisement database; providing the first contextual information and the first advertisement to the user as a first search result; updating the user profile data based on at least one of the first contextual information, the first advertisement, selection of the first advertisement by the user, and non-selection of the first advertisement by the user; receiving refinement information comprising a refined search argument from the user; providing, to the first search engine, the refined search argument for correlation with second contextual information in the database of network related information; providing, to the second search engine, the refined search argument and the updated user profile data for correlation with a second advertisement in the advertisement database; and providing the second contextual information and the second advertisement to the user. | 1. A method of searching for desired information, the method comprising: receiving, from a user having user profile data associated therewith, a search request comprising a search argument; providing, to a first search engine, the received search argument for correlation with first contextual information in a database of network related information; providing, to a second search engine, the received search argument and the user profile data for correlation with a first advertisement in an advertisement database; providing the first contextual information and the first advertisement to the user as a first search result; updating the user profile data based on at least one of the first contextual information, the first advertisement, selection of the first advertisement by the user, and non-selection of the first advertisement by the user; receiving refinement information comprising a refined search argument from the user; providing, to the first search engine, the refined search argument for correlation with second contextual information in the database of network related information; providing, to the second search engine, the refined search argument and the updated user profile data for correlation with a second advertisement in the advertisement database; and providing the second contextual information and the second advertisement to the user. 4. The method of claim 1 , wherein the user profile data comprises data determined from previous search activity of the user. | 0.541145 |
12. A method of translating an input word to an output word, said method comprising the steps of: providing a memory lookup table, said memory lookup table comprised of a memory location for each possible input word in a series of consecutively valued binary input words, and an output word in each location, said output word determined by the steps of: translating each said possible input word to an approximate output word corresponding to each said input word; determining each series of consecutively valued input words that translate to the same approximate output word; producing an error signal for each input word in each series of consecutively valued input words, said error signal determined by said series of consecutively valued input words and the relative location of said each consecutively valued input word within said series of consecutively valued input words; adding said error signal for each consecutively valued input word to said approximate output word to produce said output word; and storing said output word in a memory location corresponding to each said input word; addressing said memory lookup table using said input word; and reading said output word from said memory lookup table. | 12. A method of translating an input word to an output word, said method comprising the steps of: providing a memory lookup table, said memory lookup table comprised of a memory location for each possible input word in a series of consecutively valued binary input words, and an output word in each location, said output word determined by the steps of: translating each said possible input word to an approximate output word corresponding to each said input word; determining each series of consecutively valued input words that translate to the same approximate output word; producing an error signal for each input word in each series of consecutively valued input words, said error signal determined by said series of consecutively valued input words and the relative location of said each consecutively valued input word within said series of consecutively valued input words; adding said error signal for each consecutively valued input word to said approximate output word to produce said output word; and storing said output word in a memory location corresponding to each said input word; addressing said memory lookup table using said input word; and reading said output word from said memory lookup table. 14. The method of claim 12, said step of producing an error signal comprising: producing an accumulated error signal for each input word in said series of consecutively valued input words that translate to the same approximate output word, said accumulated error signal equal to: EQU ACC.sub.I =ACC.sub.I-1 +(I-1)/RPC where: RPC is said number of consecutive input words that translate to the same output word in each of said series of sequential input words that translate to the same approximate output word; and I is a location of said output word in said series; and if said accumulated error signal is greater than one, said error signal is equal to one and one is subtracted from said accumulated error signal, if said accumulated error signal is not greater than one, said error signal is equal to zero. | 0.5 |
1. A method of querying one or more structured documents with an original query, the method comprising the steps of: providing a list of indexing components of the structured documents to be queried wherein said indexing components comprise at least markup tags; parsing at least one schema of the structured documents to determine predefined deterministic relationships between the indexing components; removing from the list those indexing components whose occurrences can be inferred, using said determined predefined deterministic relationships, from occurrences of another indexing component, to provide a reduced list of indexing components; indexing said structured documents by generating indices using said reduced list of indexing components, wherein the generated indices point to occurrences of the indexing components included in the reduced list of indexing components within the structured documents; generating a mapping list that maps the removed indexing components to indexing components in the reduced list of indexing components used to generate the indices; reformulating an original query by substituting references to one or more removed indexing components in the original query with references to indexing components in said reduced list of indexing components, using the generated mapping list; querying said one or more structured documents by using said generated indices and said reformulated query to provide one or more sets of intermediate results; and performing post-retrieval processing on the one or more sets of intermediate results to form a final result of said original query, wherein said post-retrieval processing comprises the sub-steps of: locating the removed indexing components existing in the one or more sets of intermediate results; and generating the final result set to satisfy the original query using the located removed indexing components. | 1. A method of querying one or more structured documents with an original query, the method comprising the steps of: providing a list of indexing components of the structured documents to be queried wherein said indexing components comprise at least markup tags; parsing at least one schema of the structured documents to determine predefined deterministic relationships between the indexing components; removing from the list those indexing components whose occurrences can be inferred, using said determined predefined deterministic relationships, from occurrences of another indexing component, to provide a reduced list of indexing components; indexing said structured documents by generating indices using said reduced list of indexing components, wherein the generated indices point to occurrences of the indexing components included in the reduced list of indexing components within the structured documents; generating a mapping list that maps the removed indexing components to indexing components in the reduced list of indexing components used to generate the indices; reformulating an original query by substituting references to one or more removed indexing components in the original query with references to indexing components in said reduced list of indexing components, using the generated mapping list; querying said one or more structured documents by using said generated indices and said reformulated query to provide one or more sets of intermediate results; and performing post-retrieval processing on the one or more sets of intermediate results to form a final result of said original query, wherein said post-retrieval processing comprises the sub-steps of: locating the removed indexing components existing in the one or more sets of intermediate results; and generating the final result set to satisfy the original query using the located removed indexing components. 6. A method as claimed in claim 1 , wherein the locating sub-step further comprises computing an offset of the substituted indexing components existing in the one or more sets of intermediate results to an associated indexing component. | 0.578903 |
1. A method, performed on a computer system, for determining a matching level of a plurality of source texts stored in a translation memory to a lookup segment to be translated, the method comprising: using the computer system to perform the following: determining any exact matches for the lookup segment in the plurality of source texts; determining, in the case that at least one exact match is determined, that a respective exact match is an in-context exact (ICE) match for the lookup segment in the case that a context of the lookup segment matches that of the respective exact match, wherein the context includes at least two levels, wherein the at least two levels includes a usage context level and an asset context level, the usage context level including a preceding usage context level and a post usage context level, the preceding usage context level having a preceding usage context hash code associated therewith and the post usage context level having a post usage context hash code associated therewith; and determining, in the case that greater than one ICE match is determined, a prioritization for each ICE match that is based on a degree of context matching, wherein a more appropriate ICE match is prioritized over one or more other ICE matches, wherein the prioritization includes: first preferring an ICE match having a full usage context match with the lookup segment over an ICE match having only a partial usage context match with the lookup segment, wherein the full usage context match with the lookup segment includes a match with both the preceding usage context hash code and the post usage context hash code and the partial usage context match with the lookup segment includes a match with only one of the preceding usage context hash code and the post usage context hash code, where if the first preferring step is non-conclusive, second preferring an ICE match from the same asset as the lookup segment over an ICE match from a different asset. | 1. A method, performed on a computer system, for determining a matching level of a plurality of source texts stored in a translation memory to a lookup segment to be translated, the method comprising: using the computer system to perform the following: determining any exact matches for the lookup segment in the plurality of source texts; determining, in the case that at least one exact match is determined, that a respective exact match is an in-context exact (ICE) match for the lookup segment in the case that a context of the lookup segment matches that of the respective exact match, wherein the context includes at least two levels, wherein the at least two levels includes a usage context level and an asset context level, the usage context level including a preceding usage context level and a post usage context level, the preceding usage context level having a preceding usage context hash code associated therewith and the post usage context level having a post usage context hash code associated therewith; and determining, in the case that greater than one ICE match is determined, a prioritization for each ICE match that is based on a degree of context matching, wherein a more appropriate ICE match is prioritized over one or more other ICE matches, wherein the prioritization includes: first preferring an ICE match having a full usage context match with the lookup segment over an ICE match having only a partial usage context match with the lookup segment, wherein the full usage context match with the lookup segment includes a match with both the preceding usage context hash code and the post usage context hash code and the partial usage context match with the lookup segment includes a match with only one of the preceding usage context hash code and the post usage context hash code, where if the first preferring step is non-conclusive, second preferring an ICE match from the same asset as the lookup segment over an ICE match from a different asset. 6. The method of claim 1 , wherein the lookup segment includes a plurality of lookup segments that are substantially identical in terms of content, and wherein the ICE match determining includes determining an ICE match for each lookup segment. | 0.618858 |
15. A system comprising: a processor; and a memory storing instructions that, when executed, cause the system to: determine one or more topics associated with a message based at least in part on message data included in the message; determine knowledge data describing the one or more topics associated with the message; determine social activity data describing one or more user activities associated with a group of one or more social users based at least in part on the knowledge data, the one or more user activities describing the one or more topics; generate a selectable tag based at least in part on the social activity data describing the one or more user activities, a selection of the selectable tag causing a display of the social activity data associated with the message; and generate graphical user interface data for displaying the social activity data associated with the message in response to the selectable tag being selected. | 15. A system comprising: a processor; and a memory storing instructions that, when executed, cause the system to: determine one or more topics associated with a message based at least in part on message data included in the message; determine knowledge data describing the one or more topics associated with the message; determine social activity data describing one or more user activities associated with a group of one or more social users based at least in part on the knowledge data, the one or more user activities describing the one or more topics; generate a selectable tag based at least in part on the social activity data describing the one or more user activities, a selection of the selectable tag causing a display of the social activity data associated with the message; and generate graphical user interface data for displaying the social activity data associated with the message in response to the selectable tag being selected. 17. The system of claim 15 , wherein the instructions, when executed, cause the system to also: identify a first user associated with the message; determine whether the group of one or more social users is associated with the first user; and rank the social activity data based at least in part on whether the group of one or more social users is associated with the first user. | 0.636973 |
1. A method for modal progress dialog, implement by processor, comprising: receiving an action request associated with a resource; processing the action on the resource; determining when a progress dialog is to be displayed, the determination triggered when a predicted duration of processing the action request exceeds a threshold, where the predicted duration is a function of any one or more of: the action requested, the resource associated with the action requested, a location of the resource, a measured time to execute a portion of the action; displaying the progress dialog when the determination is triggered; and returning a result of the action request. | 1. A method for modal progress dialog, implement by processor, comprising: receiving an action request associated with a resource; processing the action on the resource; determining when a progress dialog is to be displayed, the determination triggered when a predicted duration of processing the action request exceeds a threshold, where the predicted duration is a function of any one or more of: the action requested, the resource associated with the action requested, a location of the resource, a measured time to execute a portion of the action; displaying the progress dialog when the determination is triggered; and returning a result of the action request. 6. The method for modal progress dialog of claim 1 , where the progress dialog includes a visual indication of an approximate degree of completion of the processing of the action. | 0.557692 |
1. A computer-implemented method of ranking search results based on a likelihood of user selection, the method comprising: receiving a search query from a user; obtaining a plurality of search results that satisfy the search query, wherein each search result identifies a respective document of a plurality of documents; identifying a respective condition for each document of the plurality of documents, wherein each condition comprises one or more features of the user, the search query, and the document; obtaining a ranking model that produces a score for a particular document given a particular condition for the particular document, the score representing a likelihood that the user will select the particular document when identified by a search result provided in response to the search query, the ranking model being trained on training instances that each identify a first document selected by a particular user when the first document was identified in search results provided to the particular user in response to a particular search query; using the ranking model to compute a respective score for each document of the plurality of documents; and ranking the plurality of search results according to the respective computed score for each document of the plurality of documents. | 1. A computer-implemented method of ranking search results based on a likelihood of user selection, the method comprising: receiving a search query from a user; obtaining a plurality of search results that satisfy the search query, wherein each search result identifies a respective document of a plurality of documents; identifying a respective condition for each document of the plurality of documents, wherein each condition comprises one or more features of the user, the search query, and the document; obtaining a ranking model that produces a score for a particular document given a particular condition for the particular document, the score representing a likelihood that the user will select the particular document when identified by a search result provided in response to the search query, the ranking model being trained on training instances that each identify a first document selected by a particular user when the first document was identified in search results provided to the particular user in response to a particular search query; using the ranking model to compute a respective score for each document of the plurality of documents; and ranking the plurality of search results according to the respective computed score for each document of the plurality of documents. 3. The method of claim 1 , wherein each training instance identifies one or more second documents that the particular user did not select when the one or more second documents were identified by the search results provided to the particular user in response to the particular search query. | 0.646341 |
1. A computer-implemented method performed by a computer system of one or more processors and at least one non-transitory computer-readable storage device storing software instructions executable by the computer system to perform the method comprising: receiving, from a first user, a request to identify an individual, the request including descriptive metadata associated with the individual and/or an event attended by the individual; accessing a plurality of stories stored on the non-transitory computer-readable storage device, each story of the plurality of stories previously submitted by a user and comprising respective intersection metadata indicating one or more of a time or location of the story; determining, using the descriptive metadata, one or more candidate individuals included in respective stories having intersection metadata corresponding to at least a portion of the descriptive metadata; providing, to the first user, indications of the one or more candidate individuals; receiving, from the first user, a selection of a particular candidate individual as the individual; and establishing respective user introductions between the first user and the particular candidate individual. | 1. A computer-implemented method performed by a computer system of one or more processors and at least one non-transitory computer-readable storage device storing software instructions executable by the computer system to perform the method comprising: receiving, from a first user, a request to identify an individual, the request including descriptive metadata associated with the individual and/or an event attended by the individual; accessing a plurality of stories stored on the non-transitory computer-readable storage device, each story of the plurality of stories previously submitted by a user and comprising respective intersection metadata indicating one or more of a time or location of the story; determining, using the descriptive metadata, one or more candidate individuals included in respective stories having intersection metadata corresponding to at least a portion of the descriptive metadata; providing, to the first user, indications of the one or more candidate individuals; receiving, from the first user, a selection of a particular candidate individual as the individual; and establishing respective user introductions between the first user and the particular candidate individual. 11. The computer-implemented method of claim 1 , wherein establishing respective user introductions between the first user and the particular candidate individual comprises: providing, for presentation to the individual, information describing the descriptive metadata included in the request, and an option to approve the user introduction; receiving information identifying that the individual approved the user introduction; in response to receiving the information, providing, for presentation to the first user, a photo lineup of disparate users including the individual; and receiving a selection of the individual in the photo lineup, and providing user introductions to the first user and the individual, wherein the user introductions include user profile information associated with the first user and the individual. | 0.5 |
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