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20. A system for presenting visual feedback in an interface, the system including: an input data storage system storing an input dataset; an output data storage system storing an output dataset; and a data processing system configured to provide an interface for receiving user input and presenting results of data processing, including receiving one or more mapped relationships between a given output and one or more inputs represented by input variables, at least one of the mapped relationships including a transformational expression executable on a data processing system, the transformational expression defining an output of a mapped relationship based on at least one input variable mapped to an element of an input dataset; receiving identification of elements of an output dataset mapped to outputs of respective mapped relationships; generating output data from the data processing system according to the transformational expression based on input data from the input dataset associated with the element of the input dataset mapped to the input variable, including applying the transformational expressions to input values in respective fields of input records of the input dataset and storing output values in respective fields of output records of the output dataset, including executing a dataflow graph including nodes representing data processing components, links representing data flows between the data processing components, a node representing the input dataset providing a data flow of the input records, and a node representing the output dataset receiving a data flow of the output records; determining validation information in response to the generated output data based on validation criteria defining one or more characteristics of valid values associated with one or more of the identified elements of the output dataset; and presenting in the interface visual feedback based on the determined validation information.
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20. A system for presenting visual feedback in an interface, the system including: an input data storage system storing an input dataset; an output data storage system storing an output dataset; and a data processing system configured to provide an interface for receiving user input and presenting results of data processing, including receiving one or more mapped relationships between a given output and one or more inputs represented by input variables, at least one of the mapped relationships including a transformational expression executable on a data processing system, the transformational expression defining an output of a mapped relationship based on at least one input variable mapped to an element of an input dataset; receiving identification of elements of an output dataset mapped to outputs of respective mapped relationships; generating output data from the data processing system according to the transformational expression based on input data from the input dataset associated with the element of the input dataset mapped to the input variable, including applying the transformational expressions to input values in respective fields of input records of the input dataset and storing output values in respective fields of output records of the output dataset, including executing a dataflow graph including nodes representing data processing components, links representing data flows between the data processing components, a node representing the input dataset providing a data flow of the input records, and a node representing the output dataset receiving a data flow of the output records; determining validation information in response to the generated output data based on validation criteria defining one or more characteristics of valid values associated with one or more of the identified elements of the output dataset; and presenting in the interface visual feedback based on the determined validation information. 24. The system of claim 20 , further including presenting in the interface a value representing the generated output data.
| 0.576468 |
16. A system of a mobile device, Alpha, and a mobile device, Beta; where Alpha shows an image held at a server; where Alpha encodes an URL of a webpage at the server; where Alpha transmits the encoding; where Beta decodes the encoding; where Beta extracts the URL; where Beta displays the webpage; where Beta reviews the image by altering the webpage; where Beta sends the altered webpage to the server.
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16. A system of a mobile device, Alpha, and a mobile device, Beta; where Alpha shows an image held at a server; where Alpha encodes an URL of a webpage at the server; where Alpha transmits the encoding; where Beta decodes the encoding; where Beta extracts the URL; where Beta displays the webpage; where Beta reviews the image by altering the webpage; where Beta sends the altered webpage to the server. 18. The system of claim 16 , where the server alters a second webpage showing the image, to include the results of the webpage from Beta.
| 0.786924 |
1. A computer-implemented method of automatically evaluating the linguistic quality of free-response text answers submitted by students in response to examination prompts, the method comprising: (A) configuring a computer device to embody an automated computerized text assessment system which is thereafter enabled to evaluate free-response text answers in response to examination prompts using discriminative preference ranking of predetermined linguistic text features, the configuring including generating a trained model weight vector for subsequent use in automatically evaluating said free-response text answers, by: accessing a plurality of training linguistic vectors (x 1 , x 2 , x 3 , . . . x n ), each training linguistic vector comprising a plurality of numerical values representing predetermined linguistic features of text comprising sentences within a training text, at least some of said predetermined linguistic features representing at least one of lexical, part-of-speech or parsing of words within said sentences; accessing, for each of a plurality of predetermined pairs of said training linguistic vectors (x i , x j ), predetermined ranking data (r i , r j ) that defines which one of the pair of training linguistic vectors (x i , x j ) is representative of a better training text; accessing an initial weight vector (w i ) comprising a plurality of numerical weights corresponding to the plurality of numerical values in the training vectors; generating pairwise difference training vectors for a plurality of ranked pairs of training vectors (x j −x i ) each pairwise difference training vector being calculated as a difference between a ranked pair of said training linguistic vectors; and performing an iterative process to adapt said initial weight vector (w i ) to a trained model weight vector (w m ) by: i) calculating a dot product between a current weight vector and each pairwise difference training vector to generate a respective scalar value for each pairwise difference training vector; ii) determining, for each pairwise difference training vector, if the current weight vector misclassified the pairwise difference training vector in dependence upon a comparison result obtained by comparing the scalar value for the pairwise difference training vector with a predetermined threshold; iii) generating an aggregate vector (ã) by summing the pairwise difference training vectors that said determining step determines are misclassified and normalizing the summed result with a current timing factor; iv) calculating a new weight vector by arithmetically combining numerical values of the current weight vector with respectively corresponding numerical values of the generated aggregate vector; and v) repeating steps i) through iv) until the current timing factor reaches a predetermined condition, whereupon the then current weight vector becomes said trained model weight vector (w m ); and (B) subsequently using said trained model weight vector to automatically evaluate the linguistic quality of each of plural input free-text answers submitted for evaluation by: generating a linguistic vector for an input free-text answer that is to be evaluated; calculating, using a processor, a dot product between the trained model weight vector and the linguistic vector for the input free-text answer that is to be evaluated to generate a scalar value for the input free-text answer; and outputting an evaluation of the input free-text answer using the scalar value generated for the input free-text answer.
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1. A computer-implemented method of automatically evaluating the linguistic quality of free-response text answers submitted by students in response to examination prompts, the method comprising: (A) configuring a computer device to embody an automated computerized text assessment system which is thereafter enabled to evaluate free-response text answers in response to examination prompts using discriminative preference ranking of predetermined linguistic text features, the configuring including generating a trained model weight vector for subsequent use in automatically evaluating said free-response text answers, by: accessing a plurality of training linguistic vectors (x 1 , x 2 , x 3 , . . . x n ), each training linguistic vector comprising a plurality of numerical values representing predetermined linguistic features of text comprising sentences within a training text, at least some of said predetermined linguistic features representing at least one of lexical, part-of-speech or parsing of words within said sentences; accessing, for each of a plurality of predetermined pairs of said training linguistic vectors (x i , x j ), predetermined ranking data (r i , r j ) that defines which one of the pair of training linguistic vectors (x i , x j ) is representative of a better training text; accessing an initial weight vector (w i ) comprising a plurality of numerical weights corresponding to the plurality of numerical values in the training vectors; generating pairwise difference training vectors for a plurality of ranked pairs of training vectors (x j −x i ) each pairwise difference training vector being calculated as a difference between a ranked pair of said training linguistic vectors; and performing an iterative process to adapt said initial weight vector (w i ) to a trained model weight vector (w m ) by: i) calculating a dot product between a current weight vector and each pairwise difference training vector to generate a respective scalar value for each pairwise difference training vector; ii) determining, for each pairwise difference training vector, if the current weight vector misclassified the pairwise difference training vector in dependence upon a comparison result obtained by comparing the scalar value for the pairwise difference training vector with a predetermined threshold; iii) generating an aggregate vector (ã) by summing the pairwise difference training vectors that said determining step determines are misclassified and normalizing the summed result with a current timing factor; iv) calculating a new weight vector by arithmetically combining numerical values of the current weight vector with respectively corresponding numerical values of the generated aggregate vector; and v) repeating steps i) through iv) until the current timing factor reaches a predetermined condition, whereupon the then current weight vector becomes said trained model weight vector (w m ); and (B) subsequently using said trained model weight vector to automatically evaluate the linguistic quality of each of plural input free-text answers submitted for evaluation by: generating a linguistic vector for an input free-text answer that is to be evaluated; calculating, using a processor, a dot product between the trained model weight vector and the linguistic vector for the input free-text answer that is to be evaluated to generate a scalar value for the input free-text answer; and outputting an evaluation of the input free-text answer using the scalar value generated for the input free-text answer. 5. The method of claim 1 , further comprising analyzing one or more training texts to generate the training linguistic vectors.
| 0.535873 |
8. The method of claim 7 , wherein said step of assigning on the computing device a second rating to the translation's accuracy as compared to the source material for its type as determined in step (d) is comprised of the step of assigning on the computing device a second rating to the translation's accuracy selected from the group of translation accuracy ratings consisting of extremely accurate, very accurate, average accuracy, below average accuracy, and not accurate.
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8. The method of claim 7 , wherein said step of assigning on the computing device a second rating to the translation's accuracy as compared to the source material for its type as determined in step (d) is comprised of the step of assigning on the computing device a second rating to the translation's accuracy selected from the group of translation accuracy ratings consisting of extremely accurate, very accurate, average accuracy, below average accuracy, and not accurate. 9. The method of claim 8 , wherein said step of assigning on the computing device a third rating to the degree to which the translation interprets the source material's intended message is comprised of the step of assigning on the computing device a third rating to the degree to which the translation interprets the source material as a function of the inclusion in the translation of characteristics selected from the group of characteristics consisting of correct identification of subject, scenario, and significance of source material; identification of who, what, where, when, why, how, and to what extent in source material; identification of people in source material by name and position, identification of references in source material to known events, explanation of obscure references in source material, inclusion of all relevant information in source material, exclusion of irrelevant information in source material, identification of information of interest for further analysis, and inclusion of analytic comments.
| 0.740307 |
21. The method of claim 19 , wherein the customer document processing system performs the acts comprising: receiving the flagged electronic record and storing the flagged electronic record in a memory of the customer document processing system; receiving a plurality of documents in an input receptacle of the customer document processing system; transporting the documents from the input receptacle to a single output receptacle via a transport mechanism; determining if any of the documents correspond with the flagged electronic record during the transporting act; and halting the transport mechanism such that a document that has been determined to correspond with the flagged electronic record is the last document delivered to the single output receptacle.
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21. The method of claim 19 , wherein the customer document processing system performs the acts comprising: receiving the flagged electronic record and storing the flagged electronic record in a memory of the customer document processing system; receiving a plurality of documents in an input receptacle of the customer document processing system; transporting the documents from the input receptacle to a single output receptacle via a transport mechanism; determining if any of the documents correspond with the flagged electronic record during the transporting act; and halting the transport mechanism such that a document that has been determined to correspond with the flagged electronic record is the last document delivered to the single output receptacle. 28. The method of claim 21 , wherein the plurality of documents received in the input receptacle of the customer document processing system are transported at a rate of at least about 1000 documents per minute.
| 0.774352 |
2. The method of claim 1 , wherein assigning unique union identifiers to each of the union tuples belonging to the union relation comprises generating a union id relation for the union relation, wherein the union id relation defines uniquely identified union tuples that each assign a unique number to each of the union tuples.
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2. The method of claim 1 , wherein assigning unique union identifiers to each of the union tuples belonging to the union relation comprises generating a union id relation for the union relation, wherein the union id relation defines uniquely identified union tuples that each assign a unique number to each of the union tuples. 3. The method of claim 2 , wherein generating a respective injector relation for each of the alternative subtypes comprises generating injector tuples by matching domain identifiers in a domain id relation for the alternative subtype to domain identifiers in a union id relation for the algebraic data type to determine domain tuples that should be paired with respective union identifiers in the injector tuples.
| 0.891533 |
8. The system of claim 1 , wherein the litigation management application further contains computer executable instructions permitting the litigation management application to generate a notification to the first user at a designated time prior to the event.
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8. The system of claim 1 , wherein the litigation management application further contains computer executable instructions permitting the litigation management application to generate a notification to the first user at a designated time prior to the event. 9. The system of claim 8 , wherein the litigation management application further contains computer executable instructions permitting the litigation management application to receive inputs from the first user selecting that the date for the event is confirmed.
| 0.939024 |
13. A non-transitory computer readable medium storing a question and answer data editing program for causing a computer to execute a method of editing content of a dialogue to generate question and answer data, the method comprising: detecting a first question part or a first answer part from a history data of the content of the dialogue as being similar to a first question and answer data in existing question and answer data; extracting a) a second answer part from the history data, when a second question part in the history data is similar to the first question and answer data and a second answer part in the history data is not similar to the first question and answer data, and b) a third question part from the history data, when a third answer part in the history data is similar to the first question and answer data and the third question part is not similar to the first question and answer data; and registering said third question part or said second answer part from said content of the dialogue as a variation of said first question and answer data.
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13. A non-transitory computer readable medium storing a question and answer data editing program for causing a computer to execute a method of editing content of a dialogue to generate question and answer data, the method comprising: detecting a first question part or a first answer part from a history data of the content of the dialogue as being similar to a first question and answer data in existing question and answer data; extracting a) a second answer part from the history data, when a second question part in the history data is similar to the first question and answer data and a second answer part in the history data is not similar to the first question and answer data, and b) a third question part from the history data, when a third answer part in the history data is similar to the first question and answer data and the third question part is not similar to the first question and answer data; and registering said third question part or said second answer part from said content of the dialogue as a variation of said first question and answer data. 17. The non-transitory computer readable medium according to any one of claims 13 to 16 , wherein first question and answer data editing program further comprising the functions of: receiving input of conditions of said dialogue content and said question and answer data to be read from a dialogue history data base for recording history data of said dialogue content and a question and answer data base for recording existing question and answer data and to be processed, and reading said dialogue content and said question and answer data coincident with the input conditions from said dialogue history data base and said question and answer data base.
| 0.662921 |
49. The method of claim 48 wherein: said inserted record includes a cell that contains a pointer to a searched cell that contains the keyword corresponding to said inserted record; and said searched cell that contains a keyword corresponding to said inserted record contains a pointer to said inserted record.
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49. The method of claim 48 wherein: said inserted record includes a cell that contains a pointer to a searched cell that contains the keyword corresponding to said inserted record; and said searched cell that contains a keyword corresponding to said inserted record contains a pointer to said inserted record. 51. The method of claim 49 wherein said searched cell includes an anchor that marks said key word.
| 0.885135 |
10. The method of claim 1 , further including reading a request to decommission a variable associated with said variable identifier, wherein said request includes at least one of: decommission date, authorization request, model dependency data, variable dependency data, and model owner identifier.
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10. The method of claim 1 , further including reading a request to decommission a variable associated with said variable identifier, wherein said request includes at least one of: decommission date, authorization request, model dependency data, variable dependency data, and model owner identifier. 11. The method of claim 10 , wherein said variable may be decommissioned only when dependencies are resolved.
| 0.948639 |
1. A personalized service method of a system comprising a user profile ontology in which a first subject is associated with a first object through a first relationship name and a personalized service ontology in which a second subject is associated with a second object through a second relationship name, the method comprising: (a) if a user inputs personal information, storing the personal information in the user profile ontology as one of ontology data structures including the first subject, the first object, and the first relationship name; (b) storing a personalized service using the personal information in the personalized service ontology as one of ontology data structures including the second subject, the second object, and the second relationship name; (c) associating the first subject with the second object through a third relationship name or associating the second subject with the first object through the third relationship name, wherein the third relationship name is a way in which the personalized service uses the personal information associated therewith; (d) selecting a certain personalized service by the user; (e) acquiring the personal information in the personalized service ontology associated with the selected personalized service through the third relationship name; and (f) executing the selected personalized service using the acquired personal information.
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1. A personalized service method of a system comprising a user profile ontology in which a first subject is associated with a first object through a first relationship name and a personalized service ontology in which a second subject is associated with a second object through a second relationship name, the method comprising: (a) if a user inputs personal information, storing the personal information in the user profile ontology as one of ontology data structures including the first subject, the first object, and the first relationship name; (b) storing a personalized service using the personal information in the personalized service ontology as one of ontology data structures including the second subject, the second object, and the second relationship name; (c) associating the first subject with the second object through a third relationship name or associating the second subject with the first object through the third relationship name, wherein the third relationship name is a way in which the personalized service uses the personal information associated therewith; (d) selecting a certain personalized service by the user; (e) acquiring the personal information in the personalized service ontology associated with the selected personalized service through the third relationship name; and (f) executing the selected personalized service using the acquired personal information. 2. The method according to claim 1 , wherein in step (a), the personal information includes static information.
| 0.551461 |
1. A system, comprising: an electronic commerce computer system comprising a plurality of computing devices, the computer system including: a first user interface, generated on a first computing device of the computer system, through which buyers place orders over a network with a merchant and view the status of such orders, the first interface including: a first portion for displaying at least a subset of the negotiated terms between a buyer and the merchant for an accepted order, and a second portion including: a message field for a buyer to generate and submit to the merchant messages that are linked to particular orders, and a display of at least a subset of a record of at least one message previously exchanged between the buyer and the merchant linked to the accepted order, wherein the at least one message is separate from the negotiated terms between the buyer and the merchant for an accepted order; and a second user interface, generated on a second computing device of the computer system, through which the merchant views accepted orders, order-specific messages from buyers, and status information of accepted orders, the second interface including a message field for the merchant to generate and submit messages to the buyers that are linked to specific accepted orders.
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1. A system, comprising: an electronic commerce computer system comprising a plurality of computing devices, the computer system including: a first user interface, generated on a first computing device of the computer system, through which buyers place orders over a network with a merchant and view the status of such orders, the first interface including: a first portion for displaying at least a subset of the negotiated terms between a buyer and the merchant for an accepted order, and a second portion including: a message field for a buyer to generate and submit to the merchant messages that are linked to particular orders, and a display of at least a subset of a record of at least one message previously exchanged between the buyer and the merchant linked to the accepted order, wherein the at least one message is separate from the negotiated terms between the buyer and the merchant for an accepted order; and a second user interface, generated on a second computing device of the computer system, through which the merchant views accepted orders, order-specific messages from buyers, and status information of accepted orders, the second interface including a message field for the merchant to generate and submit messages to the buyers that are linked to specific accepted orders. 7. The system of claim 1 , wherein the first and second user interfaces are linked to a common order database that stores information about said orders.
| 0.713899 |
10. A computing system, comprising: a processor configured to execute instructions; and a memory system comprising one or more computer readable media, wherein the memory system stores computer instructions that, when executed by the process, cause the processor to perform a method comprising: receiving a plurality of masks, each mask comprising a string of one or more characters; accessing a list of URLs; for each URL in the list of URLs: identifying any portions of the URL that match the one or more characters in the plurality of masks, and removing from the URL the identified portions to create a resultant URL; and collapsing all identical resultant URLs into one URL.
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10. A computing system, comprising: a processor configured to execute instructions; and a memory system comprising one or more computer readable media, wherein the memory system stores computer instructions that, when executed by the process, cause the processor to perform a method comprising: receiving a plurality of masks, each mask comprising a string of one or more characters; accessing a list of URLs; for each URL in the list of URLs: identifying any portions of the URL that match the one or more characters in the plurality of masks, and removing from the URL the identified portions to create a resultant URL; and collapsing all identical resultant URLs into one URL. 14. The system of claim 10 , wherein one or more of the URLs include content indicating a linking URL associated with media.
| 0.758588 |
1. A method implemented by one or more computing devices for generating a narrative summary including at least one assertion describing an activity, the method comprising: receiving, by at least one of the one or more computing devices, a data record, the data record having associated activity information; retrieving, by at least one of the one or more computing devices, an assertion model, wherein the assertion model comprises at least one assertion template having a data field, wherein the data field is associated with one of a plurality of scenarios and wherein the plurality of scenarios include an activity scenario; filling, by at least one of the one or more computing devices, the data field of the at least one assertion template with the associated activity information based at least in part on a determination that the scenario associated with the data field is an activity scenario to thereby generate an assertion describing the associated activity information; and publishing, by at least one of the one or more computing devices, a narrative based on the assertion.
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1. A method implemented by one or more computing devices for generating a narrative summary including at least one assertion describing an activity, the method comprising: receiving, by at least one of the one or more computing devices, a data record, the data record having associated activity information; retrieving, by at least one of the one or more computing devices, an assertion model, wherein the assertion model comprises at least one assertion template having a data field, wherein the data field is associated with one of a plurality of scenarios and wherein the plurality of scenarios include an activity scenario; filling, by at least one of the one or more computing devices, the data field of the at least one assertion template with the associated activity information based at least in part on a determination that the scenario associated with the data field is an activity scenario to thereby generate an assertion describing the associated activity information; and publishing, by at least one of the one or more computing devices, a narrative based on the assertion. 2. The method of claim 1 , wherein the at least one assertion template includes a grammatical pattern and a field name representing the data field.
| 0.574002 |
16. A computer-readable storage medium encoded with instructions that, when executed, cause at least one processor of a computing device to: detect a change to a power mode of the computing device; responsive to detecting the change to the power mode, process, from among a set of elements within a page of content that each specify a respective portion of the content in accordance with a markup language, the page of content to identify one or more elements of the set of elements that each have at least one respective attribute designated to be modified in response to the change to the power mode; modify, based on the change to the power mode, at least a portion of the at least one respective attribute of each of the identified one or more elements to associate the respective portion of the content specified by each of the identified one or more elements with a set of presentation properties; and render, for display in accordance with the set of presentation properties, the respective portion of the content specified by each of the identified one or more elements.
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16. A computer-readable storage medium encoded with instructions that, when executed, cause at least one processor of a computing device to: detect a change to a power mode of the computing device; responsive to detecting the change to the power mode, process, from among a set of elements within a page of content that each specify a respective portion of the content in accordance with a markup language, the page of content to identify one or more elements of the set of elements that each have at least one respective attribute designated to be modified in response to the change to the power mode; modify, based on the change to the power mode, at least a portion of the at least one respective attribute of each of the identified one or more elements to associate the respective portion of the content specified by each of the identified one or more elements with a set of presentation properties; and render, for display in accordance with the set of presentation properties, the respective portion of the content specified by each of the identified one or more elements. 19. The computer-readable storage medium of claim 16 , being further encoded with instructions that, when executed, cause the at least one processor of the computing device to output, for display, a graphical indication of the rendered respective portion of the content.
| 0.611073 |
1. A computer-implemented method, comprising: receiving, at a computing device having one or more processors, a speech input representing a question; converting, at the computing device, the speech input to a string of characters in a natural language; obtaining, at the computing device, tokens corresponding to the string of characters in the natural language, each token representing a potential word including at least one character of the string of characters; determining, at the computing device, one or more part-of-speech (POS) tags for each token; determining, at the computing device, sequences of the POS tags for the tokens, each sequence of the POS tags including one POS tag per token; determining, at the computing device, one or more parses for each sequence of the POS tags for the tokens; determining, at the computing device, a most-likely parse and its corresponding sequence of the POS tags for the tokens to obtain a selected parse and a selected sequence of the POS tags for the tokens by solving a maximum-a-posteriori (MAP) inference problem defined as: ( x * , y * ) = arg max x ∈ X , y ∈ Y θ T T F ( w ) x + θ P T G ( x , w ) y , where x* and y* represent a specific sequence of the POS tags and a specific parse, respectively, X represents a set of the POS tags x, Y represents a set of the parses y, θ T T represents a transformed tagging weight vector, F (w) represents a tagging feature matrix, θ P T represents a transformed parsing weight vector, and G (x,w) represents a parsing feature matrix; determining, at the computing device, a most-likely answer to the question using the selected parse and the selected sequence of the POS tags for the tokens; and outputting, by the computing device, the most-likely answer.
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1. A computer-implemented method, comprising: receiving, at a computing device having one or more processors, a speech input representing a question; converting, at the computing device, the speech input to a string of characters in a natural language; obtaining, at the computing device, tokens corresponding to the string of characters in the natural language, each token representing a potential word including at least one character of the string of characters; determining, at the computing device, one or more part-of-speech (POS) tags for each token; determining, at the computing device, sequences of the POS tags for the tokens, each sequence of the POS tags including one POS tag per token; determining, at the computing device, one or more parses for each sequence of the POS tags for the tokens; determining, at the computing device, a most-likely parse and its corresponding sequence of the POS tags for the tokens to obtain a selected parse and a selected sequence of the POS tags for the tokens by solving a maximum-a-posteriori (MAP) inference problem defined as: ( x * , y * ) = arg max x ∈ X , y ∈ Y θ T T F ( w ) x + θ P T G ( x , w ) y , where x* and y* represent a specific sequence of the POS tags and a specific parse, respectively, X represents a set of the POS tags x, Y represents a set of the parses y, θ T T represents a transformed tagging weight vector, F (w) represents a tagging feature matrix, θ P T represents a transformed parsing weight vector, and G (x,w) represents a parsing feature matrix; determining, at the computing device, a most-likely answer to the question using the selected parse and the selected sequence of the POS tags for the tokens; and outputting, by the computing device, the most-likely answer. 7. The computer-implemented method of claim 1 , further comprising tokenizing, at the computing device, the string of characters to obtain the tokens.
| 0.673142 |
95. A text-to-speech synthesis system comprising a voice table, wherein the voice table is pruned from an original voice table according to a machine-implemented method comprising: identifying instances in the original voice table; creating feature vectors derived from a machine perception transformation of time-domain samples corresponding to the instances of speech segments in the original voice table onto a feature space, wherein the machine perception transformation is correlated with human perception by using the time-domain samples retaining both amplitude and phase information of the speech segments; clustering the feature vectors using a similarity measure in the feature space; and replacing the clustered instances corresponding to the clustered feature vectors within a radius by a single instance.
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95. A text-to-speech synthesis system comprising a voice table, wherein the voice table is pruned from an original voice table according to a machine-implemented method comprising: identifying instances in the original voice table; creating feature vectors derived from a machine perception transformation of time-domain samples corresponding to the instances of speech segments in the original voice table onto a feature space, wherein the machine perception transformation is correlated with human perception by using the time-domain samples retaining both amplitude and phase information of the speech segments; clustering the feature vectors using a similarity measure in the feature space; and replacing the clustered instances corresponding to the clustered feature vectors within a radius by a single instance. 100. The text-to-speech synthesis system of claim 95 wherein the feature vectors represent the instances are created by matrix-style modal analysis via singular value decomposition of a matrix W, wherein the matrix W is an M×N matrix where M is the number of instances, N is the maximum number of segment samples corresponding to an instance, with the matrix W being zero padded to N samples, wherein the singular value decomposition is represented by
W=USV T where U is the M×R left singular matrix with row vectors u i (1≦i≦M), S is the R×R diagonal matrix of singular values s 1 ≧s 2 ≧ . . . ≧s R >0, V is the N×R right singular matrix with row vectors v j (1≦j≦N), R≦min (M, N), and T denotes matrix transposition, wherein the feature vector ū i is calculated as
ū i =u i S where u i is a row vector associated with an instance i, and S is the singular diagonal matrix, and wherein the distance between two feature vectors is determined by a metric comprising a similarity measure, C, between two feature vectors, ū i and ū j , wherein C is calculated as C ( u _ i , u _ j ) = cos ( u i S , u j S ) = u i S 2 u j T u i S u j S for any 1≦i, j≦M.
| 0.560513 |
8. A data-processing system for generating code from a class model for a modeled system, said class model specifying a plurality of elements of a modeling language and dependencies between elements of said plurality of elements, the data-processing system comprising: a processor for implementing the functions below; a class model analyzer for analyzing said class model to identify a first possible source of under-specification with respect to the modeled system in said class model by using pattern recognition to find an occurrence of a first problem pattern of a plurality of problem patterns in said class model, said plurality of problem patterns being stored in a repository; a pattern selector for selecting a set of constraint patterns comprising at least a first constraint pattern, said at least first constraint pattern being linked in said repository to said first problem pattern, said at least first constraint pattern being a resolution to said first possible source of under-specification in the class model, the pattern selector further configured for determining whether there are any conflicts between constraints in the class model and the set of constraint patterns; an output device for presenting one or more non-conflicting constraint patterns of the set of constraint patterns to a user upon determining by the pattern selector whether there are any conflicts between constraints in the class model and the set of constraint patterns; an input device for receiving a user selection from said user, said user selection comprising a selected constraint pattern from a plurality of non-conflicting constraint patterns; an instantiator for instantiating constraints from said selected constraint pattern, wherein the selected constraint pattern is to be instantiated and added to the class model using an instance of the selected constraint pattern; and a code generator for generating code based on said class model and the instantiated constraints.
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8. A data-processing system for generating code from a class model for a modeled system, said class model specifying a plurality of elements of a modeling language and dependencies between elements of said plurality of elements, the data-processing system comprising: a processor for implementing the functions below; a class model analyzer for analyzing said class model to identify a first possible source of under-specification with respect to the modeled system in said class model by using pattern recognition to find an occurrence of a first problem pattern of a plurality of problem patterns in said class model, said plurality of problem patterns being stored in a repository; a pattern selector for selecting a set of constraint patterns comprising at least a first constraint pattern, said at least first constraint pattern being linked in said repository to said first problem pattern, said at least first constraint pattern being a resolution to said first possible source of under-specification in the class model, the pattern selector further configured for determining whether there are any conflicts between constraints in the class model and the set of constraint patterns; an output device for presenting one or more non-conflicting constraint patterns of the set of constraint patterns to a user upon determining by the pattern selector whether there are any conflicts between constraints in the class model and the set of constraint patterns; an input device for receiving a user selection from said user, said user selection comprising a selected constraint pattern from a plurality of non-conflicting constraint patterns; an instantiator for instantiating constraints from said selected constraint pattern, wherein the selected constraint pattern is to be instantiated and added to the class model using an instance of the selected constraint pattern; and a code generator for generating code based on said class model and the instantiated constraints. 13. The data-processing system of a claim 8 wherein the output device is further adapted for presenting a context, a description and potential resolution alternatives as a table to said user, wherein said context comprises an identifier of the element of said plurality of elements associated with said first possible source of under-specification, said description describes said first possible source of under-specification, and said potential resolution alternatives comprise identifiers of said at least first constraint pattern.
| 0.5 |
1. A data storage medium for web page classification system, comprising: a web crawler for crawling a corpus of web pages; a feature extractor for extracting at least one of the following features from a web page received from the web crawler: a first uniform resource locator (URL) corresponding to the hosting site of the web page, a second URL contained inside the web page that is indicative of a hyperlink to a blog site, at least one substring that is a part of the first URL, and whether the web page contains an ATOM or RSS feed, the feature extractor further configured for extracting the contents of the web page and generating therefrom a set of observed values, wherein each observed value is associated with a feature in the web page that provides an indication that the web page is a blog page, the set of observed values including a first observed value that is generated based on the number of occurrences in the web page of a non-markup word indicative of a blog; and a machine learning classifier communicatively coupled to the feature extractor for evaluating the extracted features and generating a prediction indicating the probability that the web page is a blog page, the classifier containing an algorithm that is trained to apply i) a heavier classifier weight to the first URL corresponding to the hosting site of the web page than to the second URL contained inside the web page, and ii) a heavier classifier weight to the second URL than the substring that is a part of the first URL.
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1. A data storage medium for web page classification system, comprising: a web crawler for crawling a corpus of web pages; a feature extractor for extracting at least one of the following features from a web page received from the web crawler: a first uniform resource locator (URL) corresponding to the hosting site of the web page, a second URL contained inside the web page that is indicative of a hyperlink to a blog site, at least one substring that is a part of the first URL, and whether the web page contains an ATOM or RSS feed, the feature extractor further configured for extracting the contents of the web page and generating therefrom a set of observed values, wherein each observed value is associated with a feature in the web page that provides an indication that the web page is a blog page, the set of observed values including a first observed value that is generated based on the number of occurrences in the web page of a non-markup word indicative of a blog; and a machine learning classifier communicatively coupled to the feature extractor for evaluating the extracted features and generating a prediction indicating the probability that the web page is a blog page, the classifier containing an algorithm that is trained to apply i) a heavier classifier weight to the first URL corresponding to the hosting site of the web page than to the second URL contained inside the web page, and ii) a heavier classifier weight to the second URL than the substring that is a part of the first URL. 2. The data storage medium of claim 1 , wherein the extracted feature further comprises at least one phrase contained in the web page in combination with at least one of the other extracted features.
| 0.50599 |
1. A method for characterizing a corpus of documents each having one or more links, comprising: forming a Bayesian network using the documents; determining a Bayesian network structure using the one or more links; generating a content link model where the model is a generative probabilistic model of the corpus along with citation information among documents, each document represented as a mixture over latent topics, and each relationship among documents is modeled by another generative process with a topic distribution of each document being a mixture of distributions associated with related documents; using a citation-topic (CT) model with a generative process for each word w in the document d in the corpus, with document probabilities Ξ, topic distribution matrix Θ and word probabilities matrix Ψ, including: choosing a related document c from p (c|d,Ξ), a multinomial probability conditioned on the document d; choosing a topic z from the topic distribution of the document c, p(z|c,Θ); choosing a word w which follows the multinomial distribution p(w|z,Ψ) conditioned on the topic z; and determining one or more topics in the corpus and topic distribution for each document wherein the content link model captures direct and indirect relationships represented by the links.
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1. A method for characterizing a corpus of documents each having one or more links, comprising: forming a Bayesian network using the documents; determining a Bayesian network structure using the one or more links; generating a content link model where the model is a generative probabilistic model of the corpus along with citation information among documents, each document represented as a mixture over latent topics, and each relationship among documents is modeled by another generative process with a topic distribution of each document being a mixture of distributions associated with related documents; using a citation-topic (CT) model with a generative process for each word w in the document d in the corpus, with document probabilities Ξ, topic distribution matrix Θ and word probabilities matrix Ψ, including: choosing a related document c from p (c|d,Ξ), a multinomial probability conditioned on the document d; choosing a topic z from the topic distribution of the document c, p(z|c,Θ); choosing a word w which follows the multinomial distribution p(w|z,Ψ) conditioned on the topic z; and determining one or more topics in the corpus and topic distribution for each document wherein the content link model captures direct and indirect relationships represented by the links. 6. The method of claim 1 , wherein the Bayesian network encodes direct and indirect relations, and wherein relationships are derived explicitly from links or implicitly from similarities among documents.
| 0.691062 |
10. The method of claim 1 , wherein said accessing a prediction of query runtime tree built from historical query information regarding historical database queries previously executed on said database comprises: accessing a prediction of query runtime tree built by a method comprising: receiving historical query information regarding a group of historical database queries previously executed on a loaded database; determining feature vectors for a plurality of said historical database queries, such that said feature vectors comprise load attributes related to the impact of database load upon said plurality of historical database queries; using machine learning to build said prediction of query runtime tree, such that node elements and leaf elements of said prediction of query runtime tree correspond to query execution runtime ranges associated with sets of said plurality of historical database queries; and developing a classifier function for a node element of said prediction of query runtime tree, said classifier function developed from at least one attribute of feature vectors of a set of said plurality of historical database queries associated with said node, said classifier function configured for selecting a branching path for processing a database query through said prediction of query runtime tree to estimate a loaded execution runtime of said database query.
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10. The method of claim 1 , wherein said accessing a prediction of query runtime tree built from historical query information regarding historical database queries previously executed on said database comprises: accessing a prediction of query runtime tree built by a method comprising: receiving historical query information regarding a group of historical database queries previously executed on a loaded database; determining feature vectors for a plurality of said historical database queries, such that said feature vectors comprise load attributes related to the impact of database load upon said plurality of historical database queries; using machine learning to build said prediction of query runtime tree, such that node elements and leaf elements of said prediction of query runtime tree correspond to query execution runtime ranges associated with sets of said plurality of historical database queries; and developing a classifier function for a node element of said prediction of query runtime tree, said classifier function developed from at least one attribute of feature vectors of a set of said plurality of historical database queries associated with said node, said classifier function configured for selecting a branching path for processing a database query through said prediction of query runtime tree to estimate a loaded execution runtime of said database query. 11. The method as recited in claim 10 wherein said determining feature vectors for a plurality of historical database queries from said group of historical database queries further comprises: extracting historical query features from an historical database query of said plurality of historical database queries; and utilizing a plurality of said historical query features to develop a query plan vector for said historical query.
| 0.620155 |
2. The apparatus of claim 1 , wherein the sentence boundary candidate extracting unit comprises a punctuation mark candidate extractor extracting a punctuation mark as the sentence boundary candidate, the punctuation mark being used as a sentence ending.
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2. The apparatus of claim 1 , wherein the sentence boundary candidate extracting unit comprises a punctuation mark candidate extractor extracting a punctuation mark as the sentence boundary candidate, the punctuation mark being used as a sentence ending. 4. The apparatus of claim 2 , wherein the sentence boundary candidate extracting unit further comprises an other-candidate extractor pre-extracting all syllables used in sentence termination from learning data tagged with sentence termination symbols, and extracting the sentence boundary candidate from a list of the pre-extracted syllables.
| 0.923909 |
1. A method comprising: receiving, at a computer memory, a communication sent from a first individual having a first skill level in a target language and at a first computing device, the communication intended to be sent from the first individual at the first computing device to a second individual having a second skill level in the target language less than the first skill level and at a second computing device, the communication having vocabulary in the target language; determining, at a computer processor, whether the vocabulary in the communication is within the second skill level such that the second individual will likely understand the vocabulary in the communication; and if the result of the determining step indicates that the vocabulary in the communication is within the second skill level, forwarding the communication from the computer memory to the second individual at the second computing device; if the result of the determining step indicates that the vocabulary in the communication is not within the second skill level, sending, to the second individual at the second computing device, alternative communication terminology in the target language that will likely be understood by the second individual.
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1. A method comprising: receiving, at a computer memory, a communication sent from a first individual having a first skill level in a target language and at a first computing device, the communication intended to be sent from the first individual at the first computing device to a second individual having a second skill level in the target language less than the first skill level and at a second computing device, the communication having vocabulary in the target language; determining, at a computer processor, whether the vocabulary in the communication is within the second skill level such that the second individual will likely understand the vocabulary in the communication; and if the result of the determining step indicates that the vocabulary in the communication is within the second skill level, forwarding the communication from the computer memory to the second individual at the second computing device; if the result of the determining step indicates that the vocabulary in the communication is not within the second skill level, sending, to the second individual at the second computing device, alternative communication terminology in the target language that will likely be understood by the second individual. 3. The method of claim 1 , wherein the sending step includes: providing to the first individual at the first computing device an instruction related to the communication or suggesting alternative communication terminology that will likely be understood by the second individual; and upon the first individual's adoption of the alternative terminology, sending the alternative communication terminology to the lesser skilled second individual at the second computing device.
| 0.5 |
12. A method for analyzing a document comprising a plurality of primitive elements, the method comprising: identifying aligned gaps in a plurality of text lines in a column of the document; determining which of the aligned gaps are indicative of spacing between a list item label and a list item in order to identify text lines that linclude the aligned gaps as list items; identifying hierarchical levels for the list items based on alignment, spacing, and content of the list items; and defining a hierarchically-organized set of lists for the column in which list items with the same hierarchical level are in the same list.
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12. A method for analyzing a document comprising a plurality of primitive elements, the method comprising: identifying aligned gaps in a plurality of text lines in a column of the document; determining which of the aligned gaps are indicative of spacing between a list item label and a list item in order to identify text lines that linclude the aligned gaps as list items; identifying hierarchical levels for the list items based on alignment, spacing, and content of the list items; and defining a hierarchically-organized set of lists for the column in which list items with the same hierarchical level are in the same list. 14. The method of claim 12 , determining which of the aligned gaps are indicative of spacing comprises identifying gaps that have a single short word to the left and left-aligned text to the right.
| 0.755991 |
7. The method of claim 6 , wherein the main workspace comprises a service candidate area having a service candidate header information section comprised of one or more service candidate header fields.
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7. The method of claim 6 , wherein the main workspace comprises a service candidate area having a service candidate header information section comprised of one or more service candidate header fields. 10. The method of claim 7 , wherein the service candidate area comprises an operation candidate section comprising an operation candidate field.
| 0.927036 |
10. A speech recognition method for a speech recognition system comprising the steps of: (a) receiving input speech from a user; (b) processing said input speech to obtain at least one parameter value; (c) determining the user's level of experience with using automatic speech recognition, using the at least one parameter value; and (d) adjusting an amount of prompting provided to the user based upon said user's level of experience to assist the user in delivering speech commands to the system wherein the adjusting includes providing users having less experience with automatic speech recognition with prompting that is more detailed than that provided for users having more experience with automatic speech recognition.
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10. A speech recognition method for a speech recognition system comprising the steps of: (a) receiving input speech from a user; (b) processing said input speech to obtain at least one parameter value; (c) determining the user's level of experience with using automatic speech recognition, using the at least one parameter value; and (d) adjusting an amount of prompting provided to the user based upon said user's level of experience to assist the user in delivering speech commands to the system wherein the adjusting includes providing users having less experience with automatic speech recognition with prompting that is more detailed than that provided for users having more experience with automatic speech recognition. 12. The speech recognition method of claim 10 , wherein step (d) further comprises providing the user with instructions to guide the user depending on the user's level of experience with using automatic speech recognition.
| 0.590355 |
1. A computer readable storage device having computer readable program instructions embodied thereon for programming a processor, said instructions consisting of: a computer software application manifesting an entirely declarative system for creating a software program comprising properties for declaratively establishing relationships between data elements, said relationships comprising descriptions of logic and data, wherein said entirely declarative system comprises one or more declarative lattice structures, each respective lattice having a plurality of configurable constructs comprising: (i) one or more declarative attributes, each attribute configurable to select an internal behavior of said respective lattice; (ii) one or more declarative data access sites, each site configurable to define respective data access points for accessing lattices external to said respective lattice, and wherein said attributes and data access sites configure each said respective lattice to complete a singular computing task, and each respective lattice is configured to instantiate and execute, either alone or in relation to other lattices of said declarative system.
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1. A computer readable storage device having computer readable program instructions embodied thereon for programming a processor, said instructions consisting of: a computer software application manifesting an entirely declarative system for creating a software program comprising properties for declaratively establishing relationships between data elements, said relationships comprising descriptions of logic and data, wherein said entirely declarative system comprises one or more declarative lattice structures, each respective lattice having a plurality of configurable constructs comprising: (i) one or more declarative attributes, each attribute configurable to select an internal behavior of said respective lattice; (ii) one or more declarative data access sites, each site configurable to define respective data access points for accessing lattices external to said respective lattice, and wherein said attributes and data access sites configure each said respective lattice to complete a singular computing task, and each respective lattice is configured to instantiate and execute, either alone or in relation to other lattices of said declarative system. 13. The computer readable storage device of claim 1 , wherein said one or more declarative lattice structures comprises a call function structure having one or more sites which act as input/output parameters.
| 0.679851 |
7. A method of parsing a plurality of portions of a hierarchically organized data document in parallel, comprising: providing a hierarchical skeleton of the data document, the hierarchical skeleton representing a hierarchical arrangement of data document elements, wherein at least one node of the hierarchical skeleton has a plurality of subtrees; providing a plurality of processors, each processor executing in parallel; automatically allocating to the plurality of processors respective tasks, each task representing a parsing operation on an element of the data document selected in dependence on the hierarchical skeleton; generating a set of tasks by iteratively removing a remaining branch of the hierarchical skeleton which represents a largest task, and elevating the root of the subtree represented by the largest task to a next higher level, wherein a sufficient number of tasks is generated to permit efficient balancing, wherein an assignment of tasks to respective processors is balanced; and automatically generating a data structure or procedural function calls representing the parsed data structure elements.
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7. A method of parsing a plurality of portions of a hierarchically organized data document in parallel, comprising: providing a hierarchical skeleton of the data document, the hierarchical skeleton representing a hierarchical arrangement of data document elements, wherein at least one node of the hierarchical skeleton has a plurality of subtrees; providing a plurality of processors, each processor executing in parallel; automatically allocating to the plurality of processors respective tasks, each task representing a parsing operation on an element of the data document selected in dependence on the hierarchical skeleton; generating a set of tasks by iteratively removing a remaining branch of the hierarchical skeleton which represents a largest task, and elevating the root of the subtree represented by the largest task to a next higher level, wherein a sufficient number of tasks is generated to permit efficient balancing, wherein an assignment of tasks to respective processors is balanced; and automatically generating a data structure or procedural function calls representing the parsed data structure elements. 15. The method according to claim 7 , wherein said generating a data structure or procedural function calls comprises maintaining ordering, and eliminating race conditions by inserting placeholder nodes within an interim data structure, and thereafter removing the placeholder nodes when no longer required.
| 0.5 |
15. A method for generating speech output via a speech-enabled application, the method comprising: generating, using at least one computer system executing the speech-enabled application, a plurality of text strings, each of the plurality of text strings corresponding to a portion of a desired speech output; inputting the plurality of text strings to at least one software module configured to identify a first portion of a first text string of the plurality of text strings as differing from a corresponding first portion of a second text string of the plurality of text strings, and a second portion of the first text string as not differing from a corresponding second portion of the second text string; receiving, from the at least one software module, speech synthesis output to render the plurality of text strings with contrastive stress assigned to the identified first portion of the first text string, but not to the identified second portion of the first text string; and generating, using the speech synthesis output, an audio speech output corresponding to the desired speech output.
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15. A method for generating speech output via a speech-enabled application, the method comprising: generating, using at least one computer system executing the speech-enabled application, a plurality of text strings, each of the plurality of text strings corresponding to a portion of a desired speech output; inputting the plurality of text strings to at least one software module configured to identify a first portion of a first text string of the plurality of text strings as differing from a corresponding first portion of a second text string of the plurality of text strings, and a second portion of the first text string as not differing from a corresponding second portion of the second text string; receiving, from the at least one software module, speech synthesis output to render the plurality of text strings with contrastive stress assigned to the identified first portion of the first text string, but not to the identified second portion of the first text string; and generating, using the speech synthesis output, an audio speech output corresponding to the desired speech output. 16. The method of claim 15 , wherein the at least one software module is configured to identify the first portion of the first text string as differing from the corresponding first portion of the second text string based at least in part on a normalized orthography of the first and second text strings.
| 0.51118 |
2. The method of claim 1 , wherein developing the data field result list comprises gathering and structuring metadata of underlying databases.
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2. The method of claim 1 , wherein developing the data field result list comprises gathering and structuring metadata of underlying databases. 3. The method of claim 2 , wherein the gathered metadata is stored in a metadata database.
| 0.973207 |
1. A computer-implemented method for creating animated video content within an animation system, comprising: selecting, from a set of scenes stored in a computer-based scene memory, a first scene into which one or more characters, objects, or backgrounds are placed, said first scene comprising a plurality of scene attribute settings, wherein said plurality of scene attribute settings comprise audience attribute settings related to age of audiences; providing a timeline on a computer interface of said animation system into which said first scene is inserted in a time-wise manner among other scenes; selecting on said computer interface of said animation system a scene characteristic control label, from a set of scene characteristic control labels, in which said scene characteristic control label is scene mood; assigning said scene characteristic control label to said timeline on said computer interface overlaying at least a portion of a length of said first scene; said assignment of said scene characteristic control label to said timeline setting said scene attribute settings for said portion of the length of said selected first scene in accordance with a meaning associated with said characteristic control label; selecting on said computer interface of said animation system an audience attribute for setting an age appearance of said one or more characters; displaying said first scene having said scene attribute settings set in accordance with said characteristic control label and said audience attribute settings; and displaying on a map interface given scene mood of a character or object in said animated video content as a function of time per scene of said animated video content, wherein said map interface maps to said timeline on said computer interface, and in which said mood of said character is compared to the mood of another character at various points in time.
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1. A computer-implemented method for creating animated video content within an animation system, comprising: selecting, from a set of scenes stored in a computer-based scene memory, a first scene into which one or more characters, objects, or backgrounds are placed, said first scene comprising a plurality of scene attribute settings, wherein said plurality of scene attribute settings comprise audience attribute settings related to age of audiences; providing a timeline on a computer interface of said animation system into which said first scene is inserted in a time-wise manner among other scenes; selecting on said computer interface of said animation system a scene characteristic control label, from a set of scene characteristic control labels, in which said scene characteristic control label is scene mood; assigning said scene characteristic control label to said timeline on said computer interface overlaying at least a portion of a length of said first scene; said assignment of said scene characteristic control label to said timeline setting said scene attribute settings for said portion of the length of said selected first scene in accordance with a meaning associated with said characteristic control label; selecting on said computer interface of said animation system an audience attribute for setting an age appearance of said one or more characters; displaying said first scene having said scene attribute settings set in accordance with said characteristic control label and said audience attribute settings; and displaying on a map interface given scene mood of a character or object in said animated video content as a function of time per scene of said animated video content, wherein said map interface maps to said timeline on said computer interface, and in which said mood of said character is compared to the mood of another character at various points in time. 4. The computer-implemented method of claim 1 , wherein said scene attribute settings are selected from the group consisting of: scene lighting, view or camera angle, focus, scene layout, audio volume, background audio, response characteristics of characters in the scene, and response characteristics of objects in the scene.
| 0.658285 |
25. A computer-readable computer memory medium selected from the group consisting of: application-specific integrated circuits, standard integrated circuits, field-programmable gate arrays, complex programmable logic devices, hard disks, and memory, wherein the computer-readable computer memory medium is storing or executing instructions that, when executed on computer processor, facilitates searches for publications, by performing a method comprising: generating a search result snapshot history representation that is a data structure comprising a plurality of nodes that represent search result snapshot objects, each search result snapshot object storing data that corresponds to search results of a specific iteration of a search project, storing data sufficient to restore the specific iteration, and comprising a forward reference and a backward reference, wherein at least some of the plurality of search result snapshot objects are linked to some other of the plurality of search result snapshot objects through the respective forward and backward references of each of the linked search result snapshot objects, and wherein at least two of the plurality of search result snapshot objects have been produced to correspond to search iterations by different individuals or entities; and sharing the generated search result snapshot history representation between a plurality of different individuals and/or entities.
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25. A computer-readable computer memory medium selected from the group consisting of: application-specific integrated circuits, standard integrated circuits, field-programmable gate arrays, complex programmable logic devices, hard disks, and memory, wherein the computer-readable computer memory medium is storing or executing instructions that, when executed on computer processor, facilitates searches for publications, by performing a method comprising: generating a search result snapshot history representation that is a data structure comprising a plurality of nodes that represent search result snapshot objects, each search result snapshot object storing data that corresponds to search results of a specific iteration of a search project, storing data sufficient to restore the specific iteration, and comprising a forward reference and a backward reference, wherein at least some of the plurality of search result snapshot objects are linked to some other of the plurality of search result snapshot objects through the respective forward and backward references of each of the linked search result snapshot objects, and wherein at least two of the plurality of search result snapshot objects have been produced to correspond to search iterations by different individuals or entities; and sharing the generated search result snapshot history representation between a plurality of different individuals and/or entities. 34. The computer-readable computer memory medium of claim 25 wherein the sharing the generated search result snapshot history representation comprises sharing the generated search result snapshot history representation between members of a team.
| 0.546655 |
18. The computer-readable medium of claim 16 , further comprising: ranking the search result data based on a relevance of the entities and entity facts in relation to the query and member information of the member; and providing the search results, based on the search result data, in an order of the rankings to the member of the enterprise including data describing the entities and entity facts determined to be relevant to the query.
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18. The computer-readable medium of claim 16 , further comprising: ranking the search result data based on a relevance of the entities and entity facts in relation to the query and member information of the member; and providing the search results, based on the search result data, in an order of the rankings to the member of the enterprise including data describing the entities and entity facts determined to be relevant to the query. 20. The computer-readable medium of claim 18 , further comprises: receiving a selection from the search results provided to the member; and adjusting a quality score of the entities and entity facts based on the selection from the search results provided to the member.
| 0.916117 |
1. A method for analyzing an object being tracked in a sequence of video frames, comprising: receiving a representation of the tracked object, as depicted by a current video frame, of the sequence of video frames; evaluating, by operation of one or more computer processors, the representation of the tracked object using at least a first classifier and a second classifier, wherein the first classifier is configured to determine a first classification score indicating whether the tracked object depicts an instance of a first classification type, and wherein the second classifier is configured to determine a second classification score indicating whether the tracked object depicts an instance of a second classification type; adding the first classification score to a first rolling average, wherein the first rolling average provides an average of the first classification score determined for the tracked object for each of a specified number of previous video frames, of the plurality of; adding the second classification score to a second rolling average, wherein the second rolling average provides an average of the second classification score determined for the tracked object for each of a specified number of previous video frames, of the plurality, wherein the final classification value is determined from the first rolling average and the second rolling average; determining a final classification value for the tracked object in the current video frame, based on the first and second rolling averages; and passing the final classification value for the tracked objects to a machine learning engine configured to identify patterns of behavior engaged in by the tracked object, based at least in part on the final classification value.
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1. A method for analyzing an object being tracked in a sequence of video frames, comprising: receiving a representation of the tracked object, as depicted by a current video frame, of the sequence of video frames; evaluating, by operation of one or more computer processors, the representation of the tracked object using at least a first classifier and a second classifier, wherein the first classifier is configured to determine a first classification score indicating whether the tracked object depicts an instance of a first classification type, and wherein the second classifier is configured to determine a second classification score indicating whether the tracked object depicts an instance of a second classification type; adding the first classification score to a first rolling average, wherein the first rolling average provides an average of the first classification score determined for the tracked object for each of a specified number of previous video frames, of the plurality of; adding the second classification score to a second rolling average, wherein the second rolling average provides an average of the second classification score determined for the tracked object for each of a specified number of previous video frames, of the plurality, wherein the final classification value is determined from the first rolling average and the second rolling average; determining a final classification value for the tracked object in the current video frame, based on the first and second rolling averages; and passing the final classification value for the tracked objects to a machine learning engine configured to identify patterns of behavior engaged in by the tracked object, based at least in part on the final classification value. 4. The method of claim 1 , wherein the final classification value specifies that the tracked object depicts one of a car, a person, an unknown-object, or an other-object.
| 0.669992 |
7. At least one non-transitory computer-readable storage medium having encoded thereon processor-executable instructions that, when executed by the at least one processor, cause the at least one processor to carry out a method of processing a plurality of expressions each having a medical meaning, each expression comprising a series of one or more words, the method comprising: extracting from a first expression at least one first clinical fact relating to the medical meaning of the first expression; extracting from a second expression at least one second clinical fact relating to the medical meaning of the second expression; determining whether the at least one first clinical fact and the second clinical fact have inconsistent medical meanings; and in response to determining that the at least one first clinical fact and the at least one second clinical fact have inconsistent medical meanings, determining a first series of one or more words related to the at least one first clinical fact, the first series being in the first expression and not in the second expression, determining a second series of one or more words related to the at least one second clinical fact, the second series being in the second expression and not in the first expression, and adding the first series and the second series to a set of series of words and associating the first series with the second series in the set.
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7. At least one non-transitory computer-readable storage medium having encoded thereon processor-executable instructions that, when executed by the at least one processor, cause the at least one processor to carry out a method of processing a plurality of expressions each having a medical meaning, each expression comprising a series of one or more words, the method comprising: extracting from a first expression at least one first clinical fact relating to the medical meaning of the first expression; extracting from a second expression at least one second clinical fact relating to the medical meaning of the second expression; determining whether the at least one first clinical fact and the second clinical fact have inconsistent medical meanings; and in response to determining that the at least one first clinical fact and the at least one second clinical fact have inconsistent medical meanings, determining a first series of one or more words related to the at least one first clinical fact, the first series being in the first expression and not in the second expression, determining a second series of one or more words related to the at least one second clinical fact, the second series being in the second expression and not in the first expression, and adding the first series and the second series to a set of series of words and associating the first series with the second series in the set. 11. The at least one computer-readable storage medium of claim 7 , wherein the determining the first series of one or more words related to the at least one first clinical fact comprises: removing a removed word from the first expression to form a modified first expression; evaluating the modified first expression using a medical fact extractor to determine whether the modified first expression expresses the at least one first clinical fact; and when the modified first expression does not express the at least one first clinical fact, determining that the first series of one or more words related to the at least one first clinical fact comprises the removed word.
| 0.648472 |
19. The system of claim 17 , further comprising a search back-end containing an index into a collection of documents, the result sets of the displayed queries being relative to the collection of documents and being defined by the index, the computer accessing the search back-end over a network and obtaining results pages from the search back-end using a network interface.
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19. The system of claim 17 , further comprising a search back-end containing an index into a collection of documents, the result sets of the displayed queries being relative to the collection of documents and being defined by the index, the computer accessing the search back-end over a network and obtaining results pages from the search back-end using a network interface. 20. The system of claim 19 wherein the network interface comprises a Hypertext Transfer Protocol (HTTP) based interface.
| 0.906655 |
1. A computer implemented method for inferring a probability of an I th inference relating to a biological system, wherein I is an integer reflecting how many times a recursion process has been conducted, the computer implemented method comprising: receiving a I th query at a database, on a data processing system, regarding an I th fact related to the biological system, wherein the I th fact becomes a compound fact that includes multiple sub-facts on a subsequent iteration of the recursion process, wherein the I th inference is absent from the database, wherein the database comprises a plurality of divergent data, wherein the plurality of divergent data includes a plurality of cohort data, wherein each datum of the database is conformed to the dimensions of the database, wherein each datum of the plurality of data has associated metadata and an associated key, wherein the associated metadata comprises data regarding cohorts associated with the corresponding datum, data regarding hierarchies associated with the corresponding datum, data regarding a corresponding source of the datum, and data regarding probabilities associated with integrity, reliability, and importance of each associated datum; establishing the I th fact as a frame of reference for the I th query, by a processing unit of the data processing system; mathematically refocusing the database such that the fact is modeled as a first center of an inverted star schema, and modeling each datum of the plurality of data in the inverted star schema around the fact; applying a I th set of rules to the I th query, by the processing unit, wherein the I th set of rules are determined for the I th query according to a J th set of rules, wherein J is equal to I-1, wherein the set of rules determine how the plurality of data are to be compared to the I th fact, wherein the I th set of rules is prioritized, and wherein the set of rules determine a search space of for the I th query including the associated metadata and associated key, wherein the J th set of rules is a rule set used in a previous iteration of the recursive process; executing the I th query, by the processing unit, to create the probability of the inference, wherein the probability of the inference is determined from comparing the I th search space according to the I th set of rules; automatically generating cohort data for the I th fact; and storing the probability of the I th inference and the cohort data for the I th fact by the processing unit in a memory element of the data processing system, wherein the I th inference and the cohort data are stored in the database at an atomic level; wherein the first inference relating to a biological system is selected from the group consisting of an interaction between the biological system and an environmental factor, monitoring the biological system, monitoring the environmental factor, a relationship between a biological pathway and a drug, a relationship between the biological pathway and a food, a relationship between the biological pathway and a substance interacting with the biological pathway, a relationship between the biological pathway and a gene, a relationship between the biological pathway and the environmental factor, and combinations thereof.
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1. A computer implemented method for inferring a probability of an I th inference relating to a biological system, wherein I is an integer reflecting how many times a recursion process has been conducted, the computer implemented method comprising: receiving a I th query at a database, on a data processing system, regarding an I th fact related to the biological system, wherein the I th fact becomes a compound fact that includes multiple sub-facts on a subsequent iteration of the recursion process, wherein the I th inference is absent from the database, wherein the database comprises a plurality of divergent data, wherein the plurality of divergent data includes a plurality of cohort data, wherein each datum of the database is conformed to the dimensions of the database, wherein each datum of the plurality of data has associated metadata and an associated key, wherein the associated metadata comprises data regarding cohorts associated with the corresponding datum, data regarding hierarchies associated with the corresponding datum, data regarding a corresponding source of the datum, and data regarding probabilities associated with integrity, reliability, and importance of each associated datum; establishing the I th fact as a frame of reference for the I th query, by a processing unit of the data processing system; mathematically refocusing the database such that the fact is modeled as a first center of an inverted star schema, and modeling each datum of the plurality of data in the inverted star schema around the fact; applying a I th set of rules to the I th query, by the processing unit, wherein the I th set of rules are determined for the I th query according to a J th set of rules, wherein J is equal to I-1, wherein the set of rules determine how the plurality of data are to be compared to the I th fact, wherein the I th set of rules is prioritized, and wherein the set of rules determine a search space of for the I th query including the associated metadata and associated key, wherein the J th set of rules is a rule set used in a previous iteration of the recursive process; executing the I th query, by the processing unit, to create the probability of the inference, wherein the probability of the inference is determined from comparing the I th search space according to the I th set of rules; automatically generating cohort data for the I th fact; and storing the probability of the I th inference and the cohort data for the I th fact by the processing unit in a memory element of the data processing system, wherein the I th inference and the cohort data are stored in the database at an atomic level; wherein the first inference relating to a biological system is selected from the group consisting of an interaction between the biological system and an environmental factor, monitoring the biological system, monitoring the environmental factor, a relationship between a biological pathway and a drug, a relationship between the biological pathway and a food, a relationship between the biological pathway and a substance interacting with the biological pathway, a relationship between the biological pathway and a gene, a relationship between the biological pathway and the environmental factor, and combinations thereof. 7. The computer implemented method of claim 1 wherein the data regarding hierarchies further comprises how the corresponding datum is categorized with other data in the plurality of data.
| 0.79476 |
11. A processor-implemented method for modeling a pose of a hand of a user, comprising: obtaining depth pixels of the hand in one or more frames; processing the depth pixels of the one or more frames to identify articulated portions of the hand; accessing a model of the articulated portions of the hand, the articulated portions of the hand of the model comprising a palm and fingers, including finger segments; matching the articulated portions of the hand of the model to the identified articulated portions of the hand of the depth pixels of the one or more frames, to provide an initial match; evaluating an extent to which distance constraints are violated in the initial match by at least one of the fingers, the distance constraints comprise constraints on distances between finger segments of the at least one of the fingers; rasterizing the model to provide depth pixels of the model; comparing the depth pixels of the at least one of the fingers to the depth pixels of the one or more frames to identify, from among the depth pixels of the one or more frames, non-overlapping depth pixels of the one or more frames which are not overlapping in at least one comparison plane with the depth pixels of the at least one of the fingers of the model; and adjusting the model: (a) in an attempt to satisfy the distance constraints, including adjusting a length of at least one finger segments of at least one of the fingers of the model based on the extent to which the distance constraints are violated by the at least one of the fingers, and (b) based on the comparing, to cause the model to more closely match the non-overlapping depth pixels of the one or more frames, by increasing a width of the at least one of the finger segments of the at least one of the fingers of the model.
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11. A processor-implemented method for modeling a pose of a hand of a user, comprising: obtaining depth pixels of the hand in one or more frames; processing the depth pixels of the one or more frames to identify articulated portions of the hand; accessing a model of the articulated portions of the hand, the articulated portions of the hand of the model comprising a palm and fingers, including finger segments; matching the articulated portions of the hand of the model to the identified articulated portions of the hand of the depth pixels of the one or more frames, to provide an initial match; evaluating an extent to which distance constraints are violated in the initial match by at least one of the fingers, the distance constraints comprise constraints on distances between finger segments of the at least one of the fingers; rasterizing the model to provide depth pixels of the model; comparing the depth pixels of the at least one of the fingers to the depth pixels of the one or more frames to identify, from among the depth pixels of the one or more frames, non-overlapping depth pixels of the one or more frames which are not overlapping in at least one comparison plane with the depth pixels of the at least one of the fingers of the model; and adjusting the model: (a) in an attempt to satisfy the distance constraints, including adjusting a length of at least one finger segments of at least one of the fingers of the model based on the extent to which the distance constraints are violated by the at least one of the fingers, and (b) based on the comparing, to cause the model to more closely match the non-overlapping depth pixels of the one or more frames, by increasing a width of the at least one of the finger segments of the at least one of the fingers of the model. 12. The processor-implemented method of claim 11 , further comprising: adjusting the model based on the comparing to cause the model to more closely match the non-overlapping depth pixels of the one or more frames, by increasing a length of at least one of the finger segments of the at least one of the fingers of the model.
| 0.630231 |
14. The system of claim 5 , wherein the media stream further comprises an audio stream and the first application further comprises: logic that recognizes untranslated speech contained in the audio stream; logic that generates translated speech by translating the untranslated speech from the first language into the second language; and logic that inserts the translated speech into the audio stream of the media stream to replace the untranslated speech within the audio stream of the media stream.
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14. The system of claim 5 , wherein the media stream further comprises an audio stream and the first application further comprises: logic that recognizes untranslated speech contained in the audio stream; logic that generates translated speech by translating the untranslated speech from the first language into the second language; and logic that inserts the translated speech into the audio stream of the media stream to replace the untranslated speech within the audio stream of the media stream. 15. The system of claim 14 , wherein the logic that recognizes the untranslated speech is configured to generate recognized text corresponding to the untranslated speech, and the logic that generates the translated speech is configured to generate the translated speech from a translated version of the recognized text corresponding to the untranslated speech.
| 0.866965 |
22. The method of claim 21 , wherein the meaning that is different from the first meaning comprises at least one of a command, a punctuation mark, or an action.
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22. The method of claim 21 , wherein the meaning that is different from the first meaning comprises at least one of a command, a punctuation mark, or an action. 23. The method of claim 22 , wherein the first meaning comprises text associated with the audio waveform.
| 0.961848 |
1. A method of presenting a customized application page in an application, the method comprising: receiving an application package from a communications network, the application package containing markup data and one or more resources defining the customized application page; rendering an offering tile on a display by the application, the offering tile displaying a first graphic image defined by an image resource in the received application package when the offering tile is in focus, and a second graphic image defined by a second image resource in the received application package when the offering tile is not in focus; receiving a target page identifier in response to a user selection of the offering tile; and responsive to the receiving of the user selection of the offering tile, identifying markup data of the application package for the customized application page according to the received target page identifier, processing the identified markup data for the customized application page to identify at least one of the one or more resources of the application package referenced in the markup data, and rendering the customized application page defined by the identified markup data on the display to include the at least one resource.
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1. A method of presenting a customized application page in an application, the method comprising: receiving an application package from a communications network, the application package containing markup data and one or more resources defining the customized application page; rendering an offering tile on a display by the application, the offering tile displaying a first graphic image defined by an image resource in the received application package when the offering tile is in focus, and a second graphic image defined by a second image resource in the received application package when the offering tile is not in focus; receiving a target page identifier in response to a user selection of the offering tile; and responsive to the receiving of the user selection of the offering tile, identifying markup data of the application package for the customized application page according to the received target page identifier, processing the identified markup data for the customized application page to identify at least one of the one or more resources of the application package referenced in the markup data, and rendering the customized application page defined by the identified markup data on the display to include the at least one resource. 2. The method of claim 1 wherein the received application package replaces a previously received application package referenced by the same target page identifier.
| 0.775779 |
3. A system comprising: a client device; and an assisted shopping application executable in the client device, the assisted shopping application configured to cause the client device to: capture a speech input via the client device; transmit a request to establish a data session and a voice session with at least one computing device in response to capturing the speech input, the at least one computing device associated with a customer service agent; initiate the voice session and the data session with the at least one computing device, the voice session facilitating discussion with a customer service agent; receive at least one search result based at least upon a refinement by the customer service agent of the speech input captured by the client device, wherein the refinement of the speech input differs from the speech input and where the refinement is generated via a customer service agent user interface; render the at least one search result in a user interface rendered on a display of the client device in response to selection of the refinement by the customer service agent of the speech input; extract a proximity sensor state from a proximity sensor associated with the client device, the proximity sensor state associated with a proximity of the client device to a user; and transmit the proximity sensor state to the at least one computing device.
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3. A system comprising: a client device; and an assisted shopping application executable in the client device, the assisted shopping application configured to cause the client device to: capture a speech input via the client device; transmit a request to establish a data session and a voice session with at least one computing device in response to capturing the speech input, the at least one computing device associated with a customer service agent; initiate the voice session and the data session with the at least one computing device, the voice session facilitating discussion with a customer service agent; receive at least one search result based at least upon a refinement by the customer service agent of the speech input captured by the client device, wherein the refinement of the speech input differs from the speech input and where the refinement is generated via a customer service agent user interface; render the at least one search result in a user interface rendered on a display of the client device in response to selection of the refinement by the customer service agent of the speech input; extract a proximity sensor state from a proximity sensor associated with the client device, the proximity sensor state associated with a proximity of the client device to a user; and transmit the proximity sensor state to the at least one computing device. 10. The system of claim 3 , wherein the voice session and the data session are executed contemporaneously with one another.
| 0.721351 |
11. A machine readable non-transitory storage medium for use in a computer, the medium containing program instructions executable by the computer to perform a speech synthesis information editing process comprising: providing phoneme information that designates a duration of each phoneme of speech to be synthesized; providing feature information that designates a time variation in a feature of the speech; providing a phoneme expansion/compression rate that is set for each phoneme; and changing a duration of each phoneme designated by the phoneme information in accordance with an expansion/compression degree that is provided for each phoneme, wherein the expansion/compression degree is obtained according to the feature designated by the feature information for the phoneme and the phoneme expansion/compression rate that corresponds to the phoneme; and outputting for display a phoneme indicator having a length set according to the duration of each phoneme designated by the phoneme information, and updating the displayed length of the phoneme indicator based on the duration of each phoneme changed by the edition processing unit.
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11. A machine readable non-transitory storage medium for use in a computer, the medium containing program instructions executable by the computer to perform a speech synthesis information editing process comprising: providing phoneme information that designates a duration of each phoneme of speech to be synthesized; providing feature information that designates a time variation in a feature of the speech; providing a phoneme expansion/compression rate that is set for each phoneme; and changing a duration of each phoneme designated by the phoneme information in accordance with an expansion/compression degree that is provided for each phoneme, wherein the expansion/compression degree is obtained according to the feature designated by the feature information for the phoneme and the phoneme expansion/compression rate that corresponds to the phoneme; and outputting for display a phoneme indicator having a length set according to the duration of each phoneme designated by the phoneme information, and updating the displayed length of the phoneme indicator based on the duration of each phoneme changed by the edition processing unit. 16. The machine readable non-transitory storage medium according to claim 11 , wherein: an expansion/compression coefficient is obtained according to a duration, the expansion/compression rate and a pitch, and the expansion/compression degree is a ratio of the expansion/compression coefficient to a sum of expansion/compression coefficients of phonemes involved in a target interval.
| 0.596528 |
14. The apparatus of claim 13 , wherein the first behavioral pattern is one of a first plurality of behavioral patterns, and wherein the second behavioral pattern is one of a second plurality of behavioral patterns.
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14. The apparatus of claim 13 , wherein the first behavioral pattern is one of a first plurality of behavioral patterns, and wherein the second behavioral pattern is one of a second plurality of behavioral patterns. 17. The apparatus of claim 14 , wherein the prior user information data comprises user information data on a plurality of websites that comprise at least one social media site, and the first plurality of behavioral patterns are identified based on the user information data on the plurality of websites.
| 0.904394 |
3. The method of claim 1 , wherein one or more of the query properties correspond to a portion of an SQL statement.
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3. The method of claim 1 , wherein one or more of the query properties correspond to a portion of an SQL statement. 4. The method of claim 3 , wherein the query properties comprise a query text property for specifying the query string.
| 0.954093 |
1. A method comprising: connecting, with a computing device that executes a network configuration tool, to a first network device from a first vendor, wherein the first network device stores a first set of configuration information; adaptively extracting, with the network configuration tool, the first set of configuration information stored to the first network device by issuing vendor-specific commands to and receiving, in response to the commands, the first set of configuration information from a first management software interface presented by the first network device; parsing, with the network configuration tool, from the first set of configuration information a first tag, wherein the first tag defines a configuration property for the first network device; connecting, with the computing device, to a second network device from a second vendor, wherein the second network device stores a second set of configuration information; adaptively extracting, with the network configuration tool, the second set of configuration information stored to the second network device by issuing commands to and receiving, in response to the commands, the second set of configuration information from a second management software interface presented by the second network device; parsing, with the network configuration tool, from the second set of configuration information a second tag, wherein the second tag defines a configuration property for the second network device; determining, with the network configuration tool, whether the first tag and the second tag are of a same kind of tag; when the first and second tags are of the same kind of tag, determining that the first tag and second tag each define similar configuration properties that are comparable with the network configuration tool; and when the first and second tags are of the same kind of tag, presenting, with the network device, aggregate configuration information in a manner that organizes the first and second tags based primarily on the kind and second tags and secondarily on the network devices from which the first and second sets of configuration information was received.
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1. A method comprising: connecting, with a computing device that executes a network configuration tool, to a first network device from a first vendor, wherein the first network device stores a first set of configuration information; adaptively extracting, with the network configuration tool, the first set of configuration information stored to the first network device by issuing vendor-specific commands to and receiving, in response to the commands, the first set of configuration information from a first management software interface presented by the first network device; parsing, with the network configuration tool, from the first set of configuration information a first tag, wherein the first tag defines a configuration property for the first network device; connecting, with the computing device, to a second network device from a second vendor, wherein the second network device stores a second set of configuration information; adaptively extracting, with the network configuration tool, the second set of configuration information stored to the second network device by issuing commands to and receiving, in response to the commands, the second set of configuration information from a second management software interface presented by the second network device; parsing, with the network configuration tool, from the second set of configuration information a second tag, wherein the second tag defines a configuration property for the second network device; determining, with the network configuration tool, whether the first tag and the second tag are of a same kind of tag; when the first and second tags are of the same kind of tag, determining that the first tag and second tag each define similar configuration properties that are comparable with the network configuration tool; and when the first and second tags are of the same kind of tag, presenting, with the network device, aggregate configuration information in a manner that organizes the first and second tags based primarily on the kind and second tags and secondarily on the network devices from which the first and second sets of configuration information was received. 6. The method of claim 1 , wherein the first and second tags each further define a name of the respective first and second tag, a kind that identifies a category of similar tags, a context that identifies other tags from which each of the first and second tags depend, and a reference that identifies a file to which each of the respective first and second sets of configuration information are stored.
| 0.700807 |
1. A method comprising the steps of: receiving a particular query that comprises one or more terms; in response to receiving the particular query: making a first plurality of comparisons, wherein each comparison in the first plurality of comparisons is based on the particular query and a different query of a plurality of queries, wherein the number of the first plurality of comparisons and the number of the plurality of queries is the same; making a second plurality of comparisons, wherein each comparison in the second plurality of comparisons is based on the particular query and a different query of the plurality of queries; based on the first plurality of comparisons, generating a first numerical value; based on the second plurality of comparisons, generating a second numerical value that is different than the first numerical value; determining a ratio between the first numerical value and the second numerical value; and ranking documents in a document set based, at least in part, on the ratio; wherein the steps are performed by one or more computer systems.
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1. A method comprising the steps of: receiving a particular query that comprises one or more terms; in response to receiving the particular query: making a first plurality of comparisons, wherein each comparison in the first plurality of comparisons is based on the particular query and a different query of a plurality of queries, wherein the number of the first plurality of comparisons and the number of the plurality of queries is the same; making a second plurality of comparisons, wherein each comparison in the second plurality of comparisons is based on the particular query and a different query of the plurality of queries; based on the first plurality of comparisons, generating a first numerical value; based on the second plurality of comparisons, generating a second numerical value that is different than the first numerical value; determining a ratio between the first numerical value and the second numerical value; and ranking documents in a document set based, at least in part, on the ratio; wherein the steps are performed by one or more computer systems. 21. A volatile or non-volatile machine-readable medium storing one or more sequences of instructions which, when executed by one or more processors, causes the one or more processors to perform the method recited in claim 1 .
| 0.563401 |
1. A method comprising: receiving, at a first origin, a request for a web page from a user agent, wherein the user agent is configured to implement a domain security model disallowing interaction between content from different origins across inline frames; accessing, by a processor, a data store of layout information to identify one or more module objects to add to a base document; and transmitting, by the processor from the first origin, the base document to the user agent, wherein the base document comprises one or more module inline frame elements each configured to cause the user agent to load a module document from a second origin within an inline frame, wherein the module document comprises a messenger object and one or more of the identified module objects; wherein each messenger object is configured, within the context of the user agent, to create, within a corresponding module inline frame, a messenger inline frame element including a location attribute identifying the first origin; responsive to a message sent by the module object, add the message to the location attribute; and provide a new message detected in the location attribute of the messenger in line frame element to the module object; wherein the base document further comprises a module connector object configured, within the context of the user agent, to access location attributes of one or more messenger inline frame elements to check for new messages; and responsive to a new message, add the new message to one or more location attributes of corresponding messenger inline frame elements.
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1. A method comprising: receiving, at a first origin, a request for a web page from a user agent, wherein the user agent is configured to implement a domain security model disallowing interaction between content from different origins across inline frames; accessing, by a processor, a data store of layout information to identify one or more module objects to add to a base document; and transmitting, by the processor from the first origin, the base document to the user agent, wherein the base document comprises one or more module inline frame elements each configured to cause the user agent to load a module document from a second origin within an inline frame, wherein the module document comprises a messenger object and one or more of the identified module objects; wherein each messenger object is configured, within the context of the user agent, to create, within a corresponding module inline frame, a messenger inline frame element including a location attribute identifying the first origin; responsive to a message sent by the module object, add the message to the location attribute; and provide a new message detected in the location attribute of the messenger in line frame element to the module object; wherein the base document further comprises a module connector object configured, within the context of the user agent, to access location attributes of one or more messenger inline frame elements to check for new messages; and responsive to a new message, add the new message to one or more location attributes of corresponding messenger inline frame elements. 2. The method of claim 1 wherein the messenger object is further configured to register with the module connector object.
| 0.75029 |
9. A computer-implemented method to assist a human analyst in analyzing large amounts of trend data of computing devices, the computer-implemented method comprising: storing on one or more computer readable storage devices: a clustering strategy; a plurality of host-based events associated with one or more computing devices; and a plurality of activity trend-related data items and properties associated with respective activity trend-related data items, each of the properties including associated property values, the activity trend-related data items including at least one of: data items associated with captured host-based events, Internet Protocol addresses, external domains, users, or computing devices, wherein hosts comprise computing devices in a network; designating one or more seeds by: accessing, by one or more hardware computing devices configured with specific computer executable instructions, and from the one or more computer readable storage devices, the plurality host-based events; determining, by the one or more hardware computing devices, a first group of the plurality of host-based events each indicating a same particular activity type and associated with a particular host and a reference time period; determining, by the one or more hardware computing devices and based at least on the first group of host-based events, a first statistical deviation in the same particular activity type of host-based events on the particular host for the reference time period; determining, by the one or more hardware computing devices, a second group of the plurality of host-based events each indicating the same particular activity type and associated with the particular host and a test time period; determining, by the one or more hardware computing devices and based at least on the second group of host-based events, a second statistical deviation in the same particular activity type of host-based events on the particular host for the test time period; and in response to determining that the first statistical deviation compared to the second statistical deviation satisfies a particular threshold, designating, by the one or more hardware computing devices, a host-based event from the second group as a seed; and for each designated host-based event seed: identifying, by the one or more hardware computing devices, one or more activity trend-related data items determined to be associated with the designated host-based event seed based at least on the clustering strategy, wherein the clustering strategy queries the one or more cluster data sources to determine at least one of: the particular host associated with the designated host-based event seed, one or more host-based events associated with the particular host, one or more host-based events associated with the designated host-based event seed, users of the particular host, data items associated with the particular host, other hosts associated with the same particular activity type of host-based events, Internet Protocol addresses associated with the particular host, external domains associated with the designated host-based event seed, computing devices associated with the particular host; generating, by the one or more hardware computing devices, a data item cluster based at least on the designated host-based event seed, wherein generating the data item cluster comprises: adding the designated host-based event seed to the data item cluster; adding the identified one or more activity trend-related data items to the data item cluster; identifying an additional one or more activity trend-related data items associated with any data item of the data item cluster; adding the additional one or more activity trend-related data items to the item data cluster; and storing the generated data item cluster in the one or more computer readable storage devices; and determining, by the one or more hardware computing devices, a score for the generated data item cluster; and causing presentation, by the one or more hardware computing devices, of at least one generated data item cluster and the determined score for the at least one generated data item cluster in a user interface of a client computing device.
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9. A computer-implemented method to assist a human analyst in analyzing large amounts of trend data of computing devices, the computer-implemented method comprising: storing on one or more computer readable storage devices: a clustering strategy; a plurality of host-based events associated with one or more computing devices; and a plurality of activity trend-related data items and properties associated with respective activity trend-related data items, each of the properties including associated property values, the activity trend-related data items including at least one of: data items associated with captured host-based events, Internet Protocol addresses, external domains, users, or computing devices, wherein hosts comprise computing devices in a network; designating one or more seeds by: accessing, by one or more hardware computing devices configured with specific computer executable instructions, and from the one or more computer readable storage devices, the plurality host-based events; determining, by the one or more hardware computing devices, a first group of the plurality of host-based events each indicating a same particular activity type and associated with a particular host and a reference time period; determining, by the one or more hardware computing devices and based at least on the first group of host-based events, a first statistical deviation in the same particular activity type of host-based events on the particular host for the reference time period; determining, by the one or more hardware computing devices, a second group of the plurality of host-based events each indicating the same particular activity type and associated with the particular host and a test time period; determining, by the one or more hardware computing devices and based at least on the second group of host-based events, a second statistical deviation in the same particular activity type of host-based events on the particular host for the test time period; and in response to determining that the first statistical deviation compared to the second statistical deviation satisfies a particular threshold, designating, by the one or more hardware computing devices, a host-based event from the second group as a seed; and for each designated host-based event seed: identifying, by the one or more hardware computing devices, one or more activity trend-related data items determined to be associated with the designated host-based event seed based at least on the clustering strategy, wherein the clustering strategy queries the one or more cluster data sources to determine at least one of: the particular host associated with the designated host-based event seed, one or more host-based events associated with the particular host, one or more host-based events associated with the designated host-based event seed, users of the particular host, data items associated with the particular host, other hosts associated with the same particular activity type of host-based events, Internet Protocol addresses associated with the particular host, external domains associated with the designated host-based event seed, computing devices associated with the particular host; generating, by the one or more hardware computing devices, a data item cluster based at least on the designated host-based event seed, wherein generating the data item cluster comprises: adding the designated host-based event seed to the data item cluster; adding the identified one or more activity trend-related data items to the data item cluster; identifying an additional one or more activity trend-related data items associated with any data item of the data item cluster; adding the additional one or more activity trend-related data items to the item data cluster; and storing the generated data item cluster in the one or more computer readable storage devices; and determining, by the one or more hardware computing devices, a score for the generated data item cluster; and causing presentation, by the one or more hardware computing devices, of at least one generated data item cluster and the determined score for the at least one generated data item cluster in a user interface of a client computing device. 10. The computer-implemented method of claim 9 , wherein determining, by the one or more hardware computing devices, the score for the generated data item cluster further comprises: determining an activity type of the designated host-based event seed; determining a reference group of host-based events from the plurality of host-based events on the network that have a respective activity type that is the same as the activity type of the designated host-based event seed; determining a universe statistical deviation from reference group of host-based events; and generating a deviation score based at least on a comparison between the second statistical deviation and the universe statistical deviation.
| 0.5 |
7. The method of claim 1 , wherein the group hierarchy comprises a static root group and one or more sub-groups, the second group being among the one or more sub-groups.
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7. The method of claim 1 , wherein the group hierarchy comprises a static root group and one or more sub-groups, the second group being among the one or more sub-groups. 8. The method of claim 7 , wherein the static root group is defined manually, and the one or more sub-groups is defined dynamically.
| 0.953399 |
11. A system including memory and one or more processors configured to execute instructions, stored in the memory, to: receive from a promoter's system a selection of an uploaded target audio reference and one or more bids to deliver one or more promotional content items responsive to an audio query matching the selected uploaded target audio reference; process the selected uploaded target audio reference and prepare it to be recognized; link the uploaded target audio reference to the one or more bids to deliver promotional content items; and store with a campaign at least the link from the uploaded target audio reference to the bids and the promotional content items.
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11. A system including memory and one or more processors configured to execute instructions, stored in the memory, to: receive from a promoter's system a selection of an uploaded target audio reference and one or more bids to deliver one or more promotional content items responsive to an audio query matching the selected uploaded target audio reference; process the selected uploaded target audio reference and prepare it to be recognized; link the uploaded target audio reference to the one or more bids to deliver promotional content items; and store with a campaign at least the link from the uploaded target audio reference to the bids and the promotional content items. 12. The system of claim 11 , wherein the uploaded target audio reference includes: a mix of background music and other sounds; information identifying the background music; and a selection of at least one aggregate experience category to which the background music belongs; and the one or more processors configured to execute further instructions stored in the memory to store the selection of the at least one aggregate experience category with the campaign.
| 0.527124 |
2. The method of claim 1 , comprising, when the disassembled message corresponds to a reference event category: verifying that the reference event category is not already present in a first storage device; and upon a positive verification, storing the reference event category in the first storage device.
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2. The method of claim 1 , comprising, when the disassembled message corresponds to a reference event category: verifying that the reference event category is not already present in a first storage device; and upon a positive verification, storing the reference event category in the first storage device. 3. The method of claim 2 , comprising storing the message in a second storage device.
| 0.980302 |
1. A method of translation, comprising: uploading a source text portion to be translated to a back end processor that identifies a subset of translation knowledge specifically associated with the uploaded source text portion and downloading the subset; and running a translation engine on a processor other than the back end processor to generate a translation of the source text portion as a function of the subset, wherein uploading the source text portion to the back end processor, which identifies the subset of translation knowledge specifically associated with the source text portion, is carried out prior to any attempt to translate the source text portion on the processor other than the back end processor, and wherein the back end processor splits the source text portion into minimal independent translation segments, and wherein the back end processor identifies, for each minimal independent translation segment of the minimal independent translation segments, a corresponding knowledge segment, and wherein the back end processor assembles the identified knowledge segments corresponding to respective ones of the minimal independent translation segments to form the subset of translation knowledge.
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1. A method of translation, comprising: uploading a source text portion to be translated to a back end processor that identifies a subset of translation knowledge specifically associated with the uploaded source text portion and downloading the subset; and running a translation engine on a processor other than the back end processor to generate a translation of the source text portion as a function of the subset, wherein uploading the source text portion to the back end processor, which identifies the subset of translation knowledge specifically associated with the source text portion, is carried out prior to any attempt to translate the source text portion on the processor other than the back end processor, and wherein the back end processor splits the source text portion into minimal independent translation segments, and wherein the back end processor identifies, for each minimal independent translation segment of the minimal independent translation segments, a corresponding knowledge segment, and wherein the back end processor assembles the identified knowledge segments corresponding to respective ones of the minimal independent translation segments to form the subset of translation knowledge. 3. The method of claim 1 wherein the identifying comprises limiting the subset to a limited number of words and phrases potentially in the source text portion.
| 0.633907 |
9. A system including: at least one processor; a value generator module that is executable by the at least one processor to receive an aspect and a request from a user, the aspect used to describe a data item and the request to solicit at least one candidate value to associate with the aspect; a string analyzer module that is executable by the at least one processor to identify a string of text in a database based on the aspect, wherein the string analyzer module identifies the aspect in the string of text, wherein the string analyzer module identifies a synonym of the aspect in the string of text, wherein the string identifier module identifies an acronym of the aspect in the string of text, and wherein the string identifier module identifies an alternate spelling of the aspect in the string of text, the database is a sample of data items from a first database that is utilized by a plurality of buyers and a plurality of sellers that utilize a network-based marketplace, the sample of data items includes a seasonal sample; the string analyzer module to analyze the string of text based on the aspect to identify at least one candidate value in the string of text, the at least one candidate value to include a first candidate value that is selected; a value generator module to communicate the at least one candidate value to a user; a processing module to receive a rule that includes an aspect-value pair that includes the aspect and the first candidate value; and a network-based marketplace to publish the rule in a production environment on the network-based marketplace, the network-based marketplace further to associate the aspect-value pair to a first data item responsive to the publication of the rule, the network-based marketplace to concatenate the aspect-value pair to the first data item responsive to an identification of the first candidate value in the first data item to generate a first data item that includes the concatenated aspect-value pair; the network-based marketplace to further receive a first query, the network-based marketplace to associate the aspect-value pair to the query, based on the rule; the network-based marketplace to identify the first data item that includes the concatenated aspect-value pair for inclusion in an interface based on the association of the aspect-value pair to the first query based on the first rule; a dictionary publisher module to receive a request to publish a dictionary for a particular domain in a preview environment in the network-based marketplace; wherein the preview environment is utilized to test a rule before the rule is applied to at least one of the first data item and the first query in a production environment; and wherein the dictionary includes a plurality of domain rules that are utilized to associate a first category on the network-based marketplace with a first product type, and wherein the first category and the first product type are further associated with the first data item that is for sale on the network-based marketplace.
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9. A system including: at least one processor; a value generator module that is executable by the at least one processor to receive an aspect and a request from a user, the aspect used to describe a data item and the request to solicit at least one candidate value to associate with the aspect; a string analyzer module that is executable by the at least one processor to identify a string of text in a database based on the aspect, wherein the string analyzer module identifies the aspect in the string of text, wherein the string analyzer module identifies a synonym of the aspect in the string of text, wherein the string identifier module identifies an acronym of the aspect in the string of text, and wherein the string identifier module identifies an alternate spelling of the aspect in the string of text, the database is a sample of data items from a first database that is utilized by a plurality of buyers and a plurality of sellers that utilize a network-based marketplace, the sample of data items includes a seasonal sample; the string analyzer module to analyze the string of text based on the aspect to identify at least one candidate value in the string of text, the at least one candidate value to include a first candidate value that is selected; a value generator module to communicate the at least one candidate value to a user; a processing module to receive a rule that includes an aspect-value pair that includes the aspect and the first candidate value; and a network-based marketplace to publish the rule in a production environment on the network-based marketplace, the network-based marketplace further to associate the aspect-value pair to a first data item responsive to the publication of the rule, the network-based marketplace to concatenate the aspect-value pair to the first data item responsive to an identification of the first candidate value in the first data item to generate a first data item that includes the concatenated aspect-value pair; the network-based marketplace to further receive a first query, the network-based marketplace to associate the aspect-value pair to the query, based on the rule; the network-based marketplace to identify the first data item that includes the concatenated aspect-value pair for inclusion in an interface based on the association of the aspect-value pair to the first query based on the first rule; a dictionary publisher module to receive a request to publish a dictionary for a particular domain in a preview environment in the network-based marketplace; wherein the preview environment is utilized to test a rule before the rule is applied to at least one of the first data item and the first query in a production environment; and wherein the dictionary includes a plurality of domain rules that are utilized to associate a first category on the network-based marketplace with a first product type, and wherein the first category and the first product type are further associated with the first data item that is for sale on the network-based marketplace. 10. The system of claim 9 , wherein the aspect is utilized to describe the first data item that is offered by a seller on the network-based marketplace, wherein the first query is received from a user that searches for date items on the network-based marketplace.
| 0.5 |
12. The method as claimed in claim 10 , wherein the obtaining comprises calculating reliability per phoneme included in the user voice and obtains the pronunciation pattern based on the calculated reliability.
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12. The method as claimed in claim 10 , wherein the obtaining comprises calculating reliability per phoneme included in the user voice and obtains the pronunciation pattern based on the calculated reliability. 13. The method as claimed in claim 12 , wherein the obtaining comprises comparing a pronunciation per phoneme stored in the user pronunciation lexicon and a pronunciation per phoneme included in the user voice and calculating the reliability per phoneme by determining a weight value according to a similarity.
| 0.846259 |
2. A prefiltering system for processing speech, said speech including a succession of utterances spoken in any of continuous and discrete form, comprising: A. cluster data storage means for storing a plurality of M cluster data sets, C.sub.1, . . . , C.sub.M, where M is an integer greater than 1, each of said cluster data sets including data representative of a plurality of word models; B. frame data means for generating a succession of w frame data sets v.sub.t, v.sub.t+1, . . . v.sub.t+w-1, beginning at a frame start time t during said succession of utterances spoken in any of continuous and discrete form, where w is an integer greater than 1, said succession of frame data sets being representative of a corresponding succession of temporal segments of said utterances spoken in any of continuous and discrete form, each of said frame data sets including k values representative of different frame parameters, where k.gtoreq.1; C. data reduction means selectively operable on said w frame data sets for generating s reduced frame data sets Y.sub.1, Y.sub.2, . . . , Y.sub.3, where s<w, each of said reduced frame data sets being related to an associated plurality of said frame data sets and including j values representative of different reduced frame data set parameters; D. scoring means for evaluating each of said reduced frame data sets against succession of said cluster data sets to generate a cluster score S.sub.Y for each of said cluster data sets; E. selectively operable identifying means for identifying each of said word models of said cluster data sets having a cluster score bearing a predetermined relation to at least one threshold score T, said identified word models defining a candidate word list; F. control means for determining said frame start times t, where successive start times t are spaced apart arbitrarily, said frame start times being independent of identification of an initial anchor; and G. means for generating a signal representative of said candidate word list for preselected ones of said frame start times t determined by said control means.
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2. A prefiltering system for processing speech, said speech including a succession of utterances spoken in any of continuous and discrete form, comprising: A. cluster data storage means for storing a plurality of M cluster data sets, C.sub.1, . . . , C.sub.M, where M is an integer greater than 1, each of said cluster data sets including data representative of a plurality of word models; B. frame data means for generating a succession of w frame data sets v.sub.t, v.sub.t+1, . . . v.sub.t+w-1, beginning at a frame start time t during said succession of utterances spoken in any of continuous and discrete form, where w is an integer greater than 1, said succession of frame data sets being representative of a corresponding succession of temporal segments of said utterances spoken in any of continuous and discrete form, each of said frame data sets including k values representative of different frame parameters, where k.gtoreq.1; C. data reduction means selectively operable on said w frame data sets for generating s reduced frame data sets Y.sub.1, Y.sub.2, . . . , Y.sub.3, where s<w, each of said reduced frame data sets being related to an associated plurality of said frame data sets and including j values representative of different reduced frame data set parameters; D. scoring means for evaluating each of said reduced frame data sets against succession of said cluster data sets to generate a cluster score S.sub.Y for each of said cluster data sets; E. selectively operable identifying means for identifying each of said word models of said cluster data sets having a cluster score bearing a predetermined relation to at least one threshold score T, said identified word models defining a candidate word list; F. control means for determining said frame start times t, where successive start times t are spaced apart arbitrarily, said frame start times being independent of identification of an initial anchor; and G. means for generating a signal representative of said candidate word list for preselected ones of said frame start times t determined by said control means. 3. A system according to claim 2 wherein said cluster data storage means and said frame data means are adapted whereby each of said frame data sets are associated with duration D.sub.1, and wherein said cluster data sets are each associated with duration D.sub.2, such that: EQU D.sub.1 .ltoreq.D.sub.2.
| 0.555598 |
1. A system for dynamically reclassifying and retrieving at least a target information object among a plurality of information objects, comprising: a memory, storing the information objects and a plurality of attribute classifiers corresponding to the information objects, wherein each of the information objects has at least one of the attribute classifiers; and a central processing unit in signal connection with the memory, wherein after the central processing unit receives a determined first attribute classifier, the central processing unit determines a plurality of first information objects, wherein each of the first information objects has the determined first attribute classifier; the central processing unit removes the attribute classifiers which do not correspond to any of the first information objects, wherein the attribute classifiers not removed by the central processing unit comprise remained attribute classifiers each corresponding to at least one of the first information objects; wherein the remained attribute classifiers are visibly displayable through the system, the remained attribute classifiers are a part of a search result, at least two of the remained attribute classifiers which correspond to a same subset of the first information objects are combined by the central processing unit in a combined form to serve as a hint, and the system displays the hint, wherein the combined form of the remained attribute classifiers are simply listed, grouped, circled, or marked.
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1. A system for dynamically reclassifying and retrieving at least a target information object among a plurality of information objects, comprising: a memory, storing the information objects and a plurality of attribute classifiers corresponding to the information objects, wherein each of the information objects has at least one of the attribute classifiers; and a central processing unit in signal connection with the memory, wherein after the central processing unit receives a determined first attribute classifier, the central processing unit determines a plurality of first information objects, wherein each of the first information objects has the determined first attribute classifier; the central processing unit removes the attribute classifiers which do not correspond to any of the first information objects, wherein the attribute classifiers not removed by the central processing unit comprise remained attribute classifiers each corresponding to at least one of the first information objects; wherein the remained attribute classifiers are visibly displayable through the system, the remained attribute classifiers are a part of a search result, at least two of the remained attribute classifiers which correspond to a same subset of the first information objects are combined by the central processing unit in a combined form to serve as a hint, and the system displays the hint, wherein the combined form of the remained attribute classifiers are simply listed, grouped, circled, or marked. 8. The system according to claim 1 , wherein a concentration level of the search result is visibly displayed upon a user selection of at least one of the remained attribute classifiers.
| 0.678952 |
3. A speech recognition apparatus comprising: a generating unit configured to generate a speech feature vector expressing a speech feature for each of a plurality of frames obtained by dividing an input speech between a start time and an end time and including frames from a start frame to an end frame; a first storage unit configured to store a first acoustic model obtained by modeling a speech feature of each word by using a state transition model including a plurality of states and a plurality of transition paths, each word being included in the input speech; a second storage unit configured to store at least one second acoustic model different from the first acoustic model; a first calculation unit configured to calculate, for each state, a first probability of transition to a state at the end frame for each word from the first acoustic model and a speech feature vector sequence from the start frame to the end frame to obtain a plurality of first probabilities for each word, and select a maximum probability of the first probabilities; a selection unit configured to select, for each word, a maximum probability transition path corresponding to the maximum probability, the maximum probability transition path indicating transition from a start state at the start frame to an end state at the end frame; a conversion unit configured to convert, for each word, the maximum probability transition path into a corresponding transition path corresponding to the second acoustic model; a second calculation unit configured to calculate, for each word, a second probability of transition to the state at the end frame on the corresponding transition path from the second acoustic model and the speech feature vector sequence; and a finding unit configured to calculate, for each word, an absolute value of a difference between the maximum probability at the end frame and the second probability at the end frame and finds, as a recognized word, a finding word of words exhibiting absolute values not less than a threshold, the finding word corresponding to a maximum value among the maximum probability at the end frame and the probability at the end frame.
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3. A speech recognition apparatus comprising: a generating unit configured to generate a speech feature vector expressing a speech feature for each of a plurality of frames obtained by dividing an input speech between a start time and an end time and including frames from a start frame to an end frame; a first storage unit configured to store a first acoustic model obtained by modeling a speech feature of each word by using a state transition model including a plurality of states and a plurality of transition paths, each word being included in the input speech; a second storage unit configured to store at least one second acoustic model different from the first acoustic model; a first calculation unit configured to calculate, for each state, a first probability of transition to a state at the end frame for each word from the first acoustic model and a speech feature vector sequence from the start frame to the end frame to obtain a plurality of first probabilities for each word, and select a maximum probability of the first probabilities; a selection unit configured to select, for each word, a maximum probability transition path corresponding to the maximum probability, the maximum probability transition path indicating transition from a start state at the start frame to an end state at the end frame; a conversion unit configured to convert, for each word, the maximum probability transition path into a corresponding transition path corresponding to the second acoustic model; a second calculation unit configured to calculate, for each word, a second probability of transition to the state at the end frame on the corresponding transition path from the second acoustic model and the speech feature vector sequence; and a finding unit configured to calculate, for each word, an absolute value of a difference between the maximum probability at the end frame and the second probability at the end frame and finds, as a recognized word, a finding word of words exhibiting absolute values not less than a threshold, the finding word corresponding to a maximum value among the maximum probability at the end frame and the probability at the end frame. 4. The apparatus according to claim 3 , wherein the first acoustic model and the second acoustic model use state transition models having the same topology.
| 0.935178 |
23. A computer program product comprising a non-transitory computer readable storage medium having instructions encoded thereon that, when executed by a processor, cause the processor to perform steps comprising: receiving a plurality of advertisement requests, each advertising request comprising advertising content and an identification of one or more objects in a social networking system; identifying a viewing user to receive advertising; identifying one or more other users who are connected to the viewing user in the social networking system; identifying a plurality of objects in the social networking system with which the identified one or more other users have interacted; identifying one or more candidate advertisements based on the advertisement requests, where each candidate advertisement is associated with an advertisement request that identified at least one of the identified objects with which the identified one or more other users have interacted; selecting a candidate advertisement for display to the viewing user; generating by a processor a social advertisement that comprises (1) the advertising content for the advertisement request associated with the selected candidate advertisement and (2) a social story that describes an interaction between a user who is connected with the viewing user and an object in the social networking system; and sending the social advertisement for display to the viewing user.
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23. A computer program product comprising a non-transitory computer readable storage medium having instructions encoded thereon that, when executed by a processor, cause the processor to perform steps comprising: receiving a plurality of advertisement requests, each advertising request comprising advertising content and an identification of one or more objects in a social networking system; identifying a viewing user to receive advertising; identifying one or more other users who are connected to the viewing user in the social networking system; identifying a plurality of objects in the social networking system with which the identified one or more other users have interacted; identifying one or more candidate advertisements based on the advertisement requests, where each candidate advertisement is associated with an advertisement request that identified at least one of the identified objects with which the identified one or more other users have interacted; selecting a candidate advertisement for display to the viewing user; generating by a processor a social advertisement that comprises (1) the advertising content for the advertisement request associated with the selected candidate advertisement and (2) a social story that describes an interaction between a user who is connected with the viewing user and an object in the social networking system; and sending the social advertisement for display to the viewing user. 32. The computer program product of claim 23 , wherein the generated social advertisement is provided to the viewing user responsive to the viewing user requesting a social networking content.
| 0.577002 |
1. An automated method for isolating one or more causes of misprocessing in a semiconductor process comprising the steps of: a. processing a plurality of wafers; b. measuring a plurality of process parameters during said processing for each of said plurality of wafers; c. creating a wafer tracking database which contains said plurality of process parameters and a plurality of identifying information associated with each wafer; d. generating a first plurality queries wherein each query in said first plurality of queries corresponds to at least one of said plurality of process parameters; e. applying each query of said first plurality of queries to said wafer tracking database to obtain a set of observations for each query of said first plurality of queries; f. automatically determining from a pattern of each of said set of observations whether each query of said first plurality of queries is interesting for fault isolation; g. dividing said first plurality of queries into a second plurality of queries wherein said second plurality contains queries determined to be interesting for fault isolation; and h. displaying said second group of queries so that at least one cause of misprocessing can be determined.
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1. An automated method for isolating one or more causes of misprocessing in a semiconductor process comprising the steps of: a. processing a plurality of wafers; b. measuring a plurality of process parameters during said processing for each of said plurality of wafers; c. creating a wafer tracking database which contains said plurality of process parameters and a plurality of identifying information associated with each wafer; d. generating a first plurality queries wherein each query in said first plurality of queries corresponds to at least one of said plurality of process parameters; e. applying each query of said first plurality of queries to said wafer tracking database to obtain a set of observations for each query of said first plurality of queries; f. automatically determining from a pattern of each of said set of observations whether each query of said first plurality of queries is interesting for fault isolation; g. dividing said first plurality of queries into a second plurality of queries wherein said second plurality contains queries determined to be interesting for fault isolation; and h. displaying said second group of queries so that at least one cause of misprocessing can be determined. 4. The method of claim 1 wherein the step for determining whether each query of said first plurality of queries is interesting comprises determining whether each query contains trends.
| 0.69694 |
1. A method implemented in a data processing and printing system for generating a self-authenticating printed document, comprising: (a) obtaining an original document image; (b) processing the original document image to generate processed data; (c) generating a barcode stamp element encoding a code calculated from the processed data generated in step (b); (d) generating a hierarchical barcode stamp by repeating the barcode stamp element in accordance with a pre-defined pattern; (e) printing the hierarchical barcode stamp and the original document image on a front side of a recording medium, wherein the hierarchical barcode stamp is printed with gray tone tiles and the original document image is printed in a black color, the hierarchical barcode stamp and the original document image overlapping each other such that at least some content of the original document image printed in the black color overlaps some gray tone tiles of the hierarchical barcode stamp.
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1. A method implemented in a data processing and printing system for generating a self-authenticating printed document, comprising: (a) obtaining an original document image; (b) processing the original document image to generate processed data; (c) generating a barcode stamp element encoding a code calculated from the processed data generated in step (b); (d) generating a hierarchical barcode stamp by repeating the barcode stamp element in accordance with a pre-defined pattern; (e) printing the hierarchical barcode stamp and the original document image on a front side of a recording medium, wherein the hierarchical barcode stamp is printed with gray tone tiles and the original document image is printed in a black color, the hierarchical barcode stamp and the original document image overlapping each other such that at least some content of the original document image printed in the black color overlaps some gray tone tiles of the hierarchical barcode stamp. 3. The method of claim 1 , wherein the processed data includes one or more of extracted graphics objects, extracted bitmap image objects, extracted text, a lower spatial resolution version of the original document image, and a compressed version of the original document image.
| 0.65095 |
7. The method of claim 6 , further comprising selecting a subset of the one or more product biological molecules based on results of assaying the one or more product biological molecules.
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7. The method of claim 6 , further comprising selecting a subset of the one or more product biological molecules based on results of assaying the one or more product biological molecules. 8. The method of claim 7 , wherein selecting is based on one or more of the following: a temperature stability, a level of enzymatic activity, a pH level in a solution, one or more solubility limits, and one or more affinity limits.
| 0.863038 |
1. A method for receiving and processing a claim file and authoring and electronically filing a legal document for a legal action in a court, comprising the steps of: (A) electronically receiving the claim file in electronic form wherein the claim file includes a plurality of data fields in a native format; (B) mapping, using an electronic processor, one or more of the data fields from the native format to a desired format different from the native format to form a modified claim file; (C) selecting a court, using the processor, at least in part on data included in the modified claim file and predetermined court selection criteria; (D) generating, using the processor, a legal document in electronic form configured for electronic filing in the selected court and which is compliant with requirements of the selected court, using data in the modified claim file and predetermined filing requirements data associated with the selected court; and (E) electronically filing the generated legal document in the selected court.
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1. A method for receiving and processing a claim file and authoring and electronically filing a legal document for a legal action in a court, comprising the steps of: (A) electronically receiving the claim file in electronic form wherein the claim file includes a plurality of data fields in a native format; (B) mapping, using an electronic processor, one or more of the data fields from the native format to a desired format different from the native format to form a modified claim file; (C) selecting a court, using the processor, at least in part on data included in the modified claim file and predetermined court selection criteria; (D) generating, using the processor, a legal document in electronic form configured for electronic filing in the selected court and which is compliant with requirements of the selected court, using data in the modified claim file and predetermined filing requirements data associated with the selected court; and (E) electronically filing the generated legal document in the selected court. 2. The method of claim 1 wherein said step of receiving a claim file includes the sub-steps of: presenting a user interface configured to solicit claim data from a user; capturing the claim data through the user interface; and storing the claim data in the claim file.
| 0.749532 |
14. The system of claim 11 , wherein the memory further stores computer usable program code executed by the processor to: analyze the content of the companion guides and to build an organizer of companion guide rules where each companion guide is associated with one of the plurality of entities; and employ the organizer of companion guide rules to update companion guide rules to the inventory of rules.
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14. The system of claim 11 , wherein the memory further stores computer usable program code executed by the processor to: analyze the content of the companion guides and to build an organizer of companion guide rules where each companion guide is associated with one of the plurality of entities; and employ the organizer of companion guide rules to update companion guide rules to the inventory of rules. 17. The system of claim 14 , wherein the memory further stores computer usable program code executed by the processor to: create human-readable hierarchies of rules from companion guides.
| 0.957379 |
20. A system for improving ranking results for a data crawl, comprising: at least one data source operable to store queryable data; and a processing device in communication with the at least one data source and operable to execute a query against the queryable data, the processing device being further operable to receive a selection of an attribute to be used in adjusting the ranking results for a query and to adjust the relevancy scores of query results for an executed query based on the selected attribute, the processing device being further operable to return the query results with the adjusted relevancy scores in response to the query, wherein the processing device is further operable to order the query results by integer number keys, each key having a high segment of digits occupied by a relevancy score and a lower segment of digits occupied by a recency, such that the lower segment if digits is enabled as a score tie breaking factor.
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20. A system for improving ranking results for a data crawl, comprising: at least one data source operable to store queryable data; and a processing device in communication with the at least one data source and operable to execute a query against the queryable data, the processing device being further operable to receive a selection of an attribute to be used in adjusting the ranking results for a query and to adjust the relevancy scores of query results for an executed query based on the selected attribute, the processing device being further operable to return the query results with the adjusted relevancy scores in response to the query, wherein the processing device is further operable to order the query results by integer number keys, each key having a high segment of digits occupied by a relevancy score and a lower segment of digits occupied by a recency, such that the lower segment if digits is enabled as a score tie breaking factor. 25. A system according to claim 20 , wherein: the keys take the form of: (max relevant_score−relevant score)*1000000+recency*10000+sequence wherein max_relevant_score is the maximum relevancy score, relevant_score is the relevancy score determined for a current query result, recency is a difference in time, and sequence is a sequence number from an original hit list, and wherein relevant_score, recency, and sequence are all integers.
| 0.5 |
17. A method for segmenting one or more claims from a patent document, the method comprising: receiving text from the patent document, the text comprising a preamble and at least one substantive claim limitation, wherein said at least one first substantive claim limitation recites a limitation to an invention; segmenting the preamble into at least one title phrase and at least one attribute phrase, wherein the attribute phrase comprises at least one second substantive claim limitation; identifying an opening and a closing of the at least one first substantive claim limitation to extract the substantive claim limitation from a remainder of the text; and displaying the preamble and the at least one first substantive claim limitation in a position indicating hierarchical subordination to the preamble.
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17. A method for segmenting one or more claims from a patent document, the method comprising: receiving text from the patent document, the text comprising a preamble and at least one substantive claim limitation, wherein said at least one first substantive claim limitation recites a limitation to an invention; segmenting the preamble into at least one title phrase and at least one attribute phrase, wherein the attribute phrase comprises at least one second substantive claim limitation; identifying an opening and a closing of the at least one first substantive claim limitation to extract the substantive claim limitation from a remainder of the text; and displaying the preamble and the at least one first substantive claim limitation in a position indicating hierarchical subordination to the preamble. 22. The method of claim 17 , further comprising classifying each claim of the one or more claims to indicate whether each claim is independent or dependent, and to indicate which claim each dependent claim depends from.
| 0.751873 |
2. A method as claimed in claim 1 wherein the step of determining includes dynamically querying the application program for the support file.
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2. A method as claimed in claim 1 wherein the step of determining includes dynamically querying the application program for the support file. 3. A method as claimed in claim 2 wherein the step of dynamically querying includes: determining the second language from displayed text of the application program; determining the resource name and URL for the second language; and locating support file according to determined resource name and second language.
| 0.867597 |
6. A system for characterizing a subject annotator according to a reference annotation type system, comprising: a machine-readable storage medium; a machine-readable code, stored on said machine-readable storage medium, having instructions for the machine to apply a plurality of document annotators using a common annotation type system, stored on said machine-readable storage medium; providing a machine-readable plurality of documents, stored on said machine-readable storage medium; a machine-readable code, stored on said machine-readable storage medium, having instructions for annotating each of said plurality of documents using at least one of said document annotators to generate a pre-annotated reference document set; a machine-readable code, stored on said machine-readable storage medium, having instructions for annotating said plurality of documents using said subject annotator to generate an evaluation annotated document set; a machine-readable code, stored on said machine-readable storage medium, having instructions for comparing at least one of said documents in said evaluation annotated document set to its corresponding documents in said pre-annotated reference document set, to generate a matching data representing matches in location, within said compared documents, between instances of annotations using the subject annotation type system and instances of annotations using the common annotation type system; a machine-readable code, stored on said machine-readable storage medium, having instructions for selecting, based on said matching data, a reference document annotation type system, comprised of one or more types from said common annotation type system, that meets a pre-determined correlation criterion with respect to said subject annotation type system; and a machine-readable code, stored on said machine-readable storage medium, having instructions for identifying a taxonomy category for at least one annotation type in said reference annotation type system from among a set of known industry taxonomies.
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6. A system for characterizing a subject annotator according to a reference annotation type system, comprising: a machine-readable storage medium; a machine-readable code, stored on said machine-readable storage medium, having instructions for the machine to apply a plurality of document annotators using a common annotation type system, stored on said machine-readable storage medium; providing a machine-readable plurality of documents, stored on said machine-readable storage medium; a machine-readable code, stored on said machine-readable storage medium, having instructions for annotating each of said plurality of documents using at least one of said document annotators to generate a pre-annotated reference document set; a machine-readable code, stored on said machine-readable storage medium, having instructions for annotating said plurality of documents using said subject annotator to generate an evaluation annotated document set; a machine-readable code, stored on said machine-readable storage medium, having instructions for comparing at least one of said documents in said evaluation annotated document set to its corresponding documents in said pre-annotated reference document set, to generate a matching data representing matches in location, within said compared documents, between instances of annotations using the subject annotation type system and instances of annotations using the common annotation type system; a machine-readable code, stored on said machine-readable storage medium, having instructions for selecting, based on said matching data, a reference document annotation type system, comprised of one or more types from said common annotation type system, that meets a pre-determined correlation criterion with respect to said subject annotation type system; and a machine-readable code, stored on said machine-readable storage medium, having instructions for identifying a taxonomy category for at least one annotation type in said reference annotation type system from among a set of known industry taxonomies. 10. The system of claim 6 , wherein said instruction for selecting include instructions for detecting whether none of said reference document annotation type systems meets said pre-determined correlation criterion and, in response to said detecting, generating a data indicating a match failure.
| 0.555994 |
8. The method of claim 1 , wherein distributing the query count for the particular query among the multiple different entities comprises: obtaining a probability score for each of the multiple different entities, wherein each of the probability scores indicates a probability that the particular query refers to the entity associated with the probability score; and assigning the partial query counts to the multiple different entities based on the probability scores.
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8. The method of claim 1 , wherein distributing the query count for the particular query among the multiple different entities comprises: obtaining a probability score for each of the multiple different entities, wherein each of the probability scores indicates a probability that the particular query refers to the entity associated with the probability score; and assigning the partial query counts to the multiple different entities based on the probability scores. 9. The method of claim 8 , wherein obtaining a probability score for each of the multiple different entities comprises obtaining the probability scores for the multiple different entities based on the entity-descriptive portion of the particular query and the suffix of the particular query.
| 0.852477 |
1. A computer-implemented method executed by one or more processors of a social video search system, the method comprising: receiving a query from a user; obtaining, by the one or more processors, social context information about interactions of the user from a social graph; obtaining, by the one or more processors, a search result using the query; generating, by the one or more processors, an annotation for at least one search result where the annotation indicates the association with a particular source and the relation to the user; and providing, for display to the user, the modified search result and the annotation.
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1. A computer-implemented method executed by one or more processors of a social video search system, the method comprising: receiving a query from a user; obtaining, by the one or more processors, social context information about interactions of the user from a social graph; obtaining, by the one or more processors, a search result using the query; generating, by the one or more processors, an annotation for at least one search result where the annotation indicates the association with a particular source and the relation to the user; and providing, for display to the user, the modified search result and the annotation. 6. The method of claim 1 wherein the social context information include video context information.
| 0.713143 |
12. A non-transitory computer readable storage medium storing computer program instructions capable of being executed by a computer processor on a computing device, the computer program instructions defining the steps of: receiving input from a user via a web address bar to navigate to a web site; navigating to the web site; storing information about the web site in a file unless predetermined characteristics of actions performed by the user on the web site once the user has navigated to the web site are present; repeating the navigating and storing steps for each requested web site; determining web sites associated with a search query of the user as the search query is being entered by the user into a search area of a visibly displayed user interface of an application program executed by the computing device, the search area separate from the web address bar, the associated web sites being sites that have been previously navigated to by the user, the determining step comprising obtaining the web sites associated with the search query from a data structure previously generated by the computing device from the file, the data structure comprising parsed entries of Uniform Resource Locators (URLs) associated with the previously navigated web sites; and based on the determining step, causing web site links corresponding to the associated web sites to be visibly displayed on a display of the computing device as the search query is being entered, the web site links comprising, in addition to the URLs associated with the previously navigated web sites, information previously collected for the web sites and available via a network, the information comprising a timestamp of a most recent visit to the previously navigated web sites by the user, the predetermined characteristics of actions performed by the user selected from a group of characteristics consisting of the user selecting a new window or tab within a predetermined amount of time after navigating to the web site, and detecting a new navigation request not associated with the web site within a predetermined amount of time after navigating to the web site, wherein the obtaining the web sites associated with the search query from a data structure further comprises: for each Uniform Resource Locator (URL) entry associated with a web site, adding an entry to the data structure for each search term associated with the URL, for each URL entry associated with a web site, parsing a title of the entry into tokens, for each URL entry associated with a web site, tokenizing its domain name into a plurality of words, for the each URL entry having its domain name tokenized, adding the plurality of words to the data structure for the URL, for each URL entry having a filename, tokenizing the filename, and adding the filename to the data structure for the each URL entry having the filename.
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12. A non-transitory computer readable storage medium storing computer program instructions capable of being executed by a computer processor on a computing device, the computer program instructions defining the steps of: receiving input from a user via a web address bar to navigate to a web site; navigating to the web site; storing information about the web site in a file unless predetermined characteristics of actions performed by the user on the web site once the user has navigated to the web site are present; repeating the navigating and storing steps for each requested web site; determining web sites associated with a search query of the user as the search query is being entered by the user into a search area of a visibly displayed user interface of an application program executed by the computing device, the search area separate from the web address bar, the associated web sites being sites that have been previously navigated to by the user, the determining step comprising obtaining the web sites associated with the search query from a data structure previously generated by the computing device from the file, the data structure comprising parsed entries of Uniform Resource Locators (URLs) associated with the previously navigated web sites; and based on the determining step, causing web site links corresponding to the associated web sites to be visibly displayed on a display of the computing device as the search query is being entered, the web site links comprising, in addition to the URLs associated with the previously navigated web sites, information previously collected for the web sites and available via a network, the information comprising a timestamp of a most recent visit to the previously navigated web sites by the user, the predetermined characteristics of actions performed by the user selected from a group of characteristics consisting of the user selecting a new window or tab within a predetermined amount of time after navigating to the web site, and detecting a new navigation request not associated with the web site within a predetermined amount of time after navigating to the web site, wherein the obtaining the web sites associated with the search query from a data structure further comprises: for each Uniform Resource Locator (URL) entry associated with a web site, adding an entry to the data structure for each search term associated with the URL, for each URL entry associated with a web site, parsing a title of the entry into tokens, for each URL entry associated with a web site, tokenizing its domain name into a plurality of words, for the each URL entry having its domain name tokenized, adding the plurality of words to the data structure for the URL, for each URL entry having a filename, tokenizing the filename, and adding the filename to the data structure for the each URL entry having the filename. 20. The non-transitory computer readable storage medium of claim 12 wherein the information previously collected for the web sites further comprises a search term used to reach the URL.
| 0.562147 |
6. An apparatus, comprising: an interconnect fabricated on an interposer device; and an integrated circuit die coupled to the interposer device, the integrated circuit die fabricated to include: a data transmitter circuit, configured to: receive an input data word for transmission, wherein the input data word includes two or more independent bits of digital data; encode the input data word into a code word; and drive the code word on to the interconnect for transmission, wherein the interconnect includes signal wires corresponding to bits comprising the code word; and a data receiver circuit, wherein the code word that is transmitted through the interconnect is received and decoded by the data receiver circuit to generate an output data word that is equivalent to the input data word.
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6. An apparatus, comprising: an interconnect fabricated on an interposer device; and an integrated circuit die coupled to the interposer device, the integrated circuit die fabricated to include: a data transmitter circuit, configured to: receive an input data word for transmission, wherein the input data word includes two or more independent bits of digital data; encode the input data word into a code word; and drive the code word on to the interconnect for transmission, wherein the interconnect includes signal wires corresponding to bits comprising the code word; and a data receiver circuit, wherein the code word that is transmitted through the interconnect is received and decoded by the data receiver circuit to generate an output data word that is equivalent to the input data word. 12. The apparatus of claim 6 , wherein the interconnect includes double-twist structures.
| 0.619597 |
15. A computer-readable memory storage device having stored thereon: a data structure that comprises at least some data defined according to an extensible markup language (XML) schema, comprising: a first set of data that associates the data structure with a software component programmed in a dynamically-typed programming language; a second set of data comprising descriptive information with respect to the software component; a third set of data comprising an explicit data type identification for the software component; and a programming environment configured to: provide a design surface comprising icons representing other software components also programmed in a dynamically-typed programming language; access the data structure upon selection of an icon representing the software component based on the first set of data and connection of the icon to at least one other icon of the design surface, uses the second set of data to provide descriptive information, and validate usage of the software component based on the data type identification in the third set of data to provide a type system for the software component that does not rely upon inference by enforcing at least one constraint setting a default value and validating at least one type corresponding to at least one date value of the software component at runtime during execution of the software component and a runtime environment configured to validate execution of the software component at runtime by performing enhanced type matching during execution, including inserting executable code into the selected programming language component that converts one date type to an appropriate type for input or output.
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15. A computer-readable memory storage device having stored thereon: a data structure that comprises at least some data defined according to an extensible markup language (XML) schema, comprising: a first set of data that associates the data structure with a software component programmed in a dynamically-typed programming language; a second set of data comprising descriptive information with respect to the software component; a third set of data comprising an explicit data type identification for the software component; and a programming environment configured to: provide a design surface comprising icons representing other software components also programmed in a dynamically-typed programming language; access the data structure upon selection of an icon representing the software component based on the first set of data and connection of the icon to at least one other icon of the design surface, uses the second set of data to provide descriptive information, and validate usage of the software component based on the data type identification in the third set of data to provide a type system for the software component that does not rely upon inference by enforcing at least one constraint setting a default value and validating at least one type corresponding to at least one date value of the software component at runtime during execution of the software component and a runtime environment configured to validate execution of the software component at runtime by performing enhanced type matching during execution, including inserting executable code into the selected programming language component that converts one date type to an appropriate type for input or output. 17. The computer-readable memory storage device of claim 15 wherein the third set of data comprises type data corresponding to a type of data that the software component inputs, outputs or both inputs and outputs.
| 0.570433 |
14. A method for processing speech, comprising: receiving speech as an input; processing the received speech within alternate concurrent instances of a virtual processing environment executing on at least one automated data processing system; automatically communicating, between respective alternate instances of the virtual processing environment, at least one status message to coordinate a reduction in a number of the alternate instances of the virtual processing environment; analyzing: (1) the received speech to determine a command; (2) the received speech to determine data associated with the command; (3) a completeness and unambiguity of the received speech with respect to an ability to execute the command; and if the received speech is complete and unambiguous with respect to the ability to execute the command, executing the command, within at least one virtual processing environment, in conjunction with data associated with the command, and if the received speech is incomplete or ambiguous with respect to the ability to execute the command, prompting for additional input.
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14. A method for processing speech, comprising: receiving speech as an input; processing the received speech within alternate concurrent instances of a virtual processing environment executing on at least one automated data processing system; automatically communicating, between respective alternate instances of the virtual processing environment, at least one status message to coordinate a reduction in a number of the alternate instances of the virtual processing environment; analyzing: (1) the received speech to determine a command; (2) the received speech to determine data associated with the command; (3) a completeness and unambiguity of the received speech with respect to an ability to execute the command; and if the received speech is complete and unambiguous with respect to the ability to execute the command, executing the command, within at least one virtual processing environment, in conjunction with data associated with the command, and if the received speech is incomplete or ambiguous with respect to the ability to execute the command, prompting for additional input. 15. The method according to claim 14 , further comprising parsing the received speech according to at least one predetermined grammar prior to analyzing.
| 0.567054 |
33. A computer-readable storage medium containing a hypermedia file, the hypermedia file comprising: informational content for rendering to a user; a hyperlink among the informational content that can be activated by the user when the informational content is rendered; the hyperlink including a query formulation that can be submitted to a database for resolution of the hyperlink; wherein the hyperlink further includes: one or more executable rules associated respectively with sets of mandatory attributes; one or more bound attributes for inclusion in a list of bound attributes maintained on an individual computer; the rules being executable to examine the list of bound attributes and to potentially add query predicates to the query formulation depending on said examination of the list of bound attributes.
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33. A computer-readable storage medium containing a hypermedia file, the hypermedia file comprising: informational content for rendering to a user; a hyperlink among the informational content that can be activated by the user when the informational content is rendered; the hyperlink including a query formulation that can be submitted to a database for resolution of the hyperlink; wherein the hyperlink further includes: one or more executable rules associated respectively with sets of mandatory attributes; one or more bound attributes for inclusion in a list of bound attributes maintained on an individual computer; the rules being executable to examine the list of bound attributes and to potentially add query predicates to the query formulation depending on said examination of the list of bound attributes. 36. A computer-readable storage medium as recited in claim 33, said rules being executable to potentially add attributes to a list of bound attributes.
| 0.813673 |
1. A system, comprising: a first server to: generate a custom news document, where the custom news document includes a plurality of custom news sections, assign one or more of a keyword or phrase, a topical category, or a geographic category to each one of the plurality of custom news sections, embed search queries into the custom news document, where each of the embedded search queries includes a respective one of the assigned one or more keywords or phrases, one or more topical categories, or one or more geographic categories associated with a respective one of the plurality of custom news sections, receive, from a client device, a request to access the custom news document, and send the embedded search queries across a network to a second server, in response to receiving the request; and the second server to: receive the embedded search queries, crawl a corpus of news documents hosted at a plurality of remote servers to obtain news content, search the obtained news content based on the received embedded search queries to obtain search results, and provide news content to the first server based on the search results; where the first server is further to: populate the plurality of custom news sections with the received news content, and permit a plurality of users to access, from across the network, the custom news document that includes the received news content, where the first server, the second server, and the plurality of remote servers comprise different network devices that connect to the network.
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1. A system, comprising: a first server to: generate a custom news document, where the custom news document includes a plurality of custom news sections, assign one or more of a keyword or phrase, a topical category, or a geographic category to each one of the plurality of custom news sections, embed search queries into the custom news document, where each of the embedded search queries includes a respective one of the assigned one or more keywords or phrases, one or more topical categories, or one or more geographic categories associated with a respective one of the plurality of custom news sections, receive, from a client device, a request to access the custom news document, and send the embedded search queries across a network to a second server, in response to receiving the request; and the second server to: receive the embedded search queries, crawl a corpus of news documents hosted at a plurality of remote servers to obtain news content, search the obtained news content based on the received embedded search queries to obtain search results, and provide news content to the first server based on the search results; where the first server is further to: populate the plurality of custom news sections with the received news content, and permit a plurality of users to access, from across the network, the custom news document that includes the received news content, where the first server, the second server, and the plurality of remote servers comprise different network devices that connect to the network. 12. The system of claim 1 , where the plurality of custom news sections includes one or more of: a title section; a news section; a local news section; a related stories section; a photo section; or a blog section.
| 0.638734 |
8. The process of claim 6 further comprising: automatically aligning the first musical score and a corresponding musical audio input; and segmenting the musical audio input into samples corresponding to the first musical score to form note-score pairs in the database.
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8. The process of claim 6 further comprising: automatically aligning the first musical score and a corresponding musical audio input; and segmenting the musical audio input into samples corresponding to the first musical score to form note-score pairs in the database. 9. The process of claim 8 wherein the musical audio input and the first musical score represents a user selected rendition of a particular song.
| 0.967749 |
7. An apparatus for providing information about a main knowledge stream, the apparatus comprising: a storage module for storing information about a plurality of documents; an information process module for obtaining reference links representing reference relationships among reference documents for each of the documents from information about the documents stored in the storage module, defining one or more paths connecting the reference links for each of the plurality of documents, determining a longest path among the defined paths as a basic path for each of the plurality of documents, calculating probability values of the reference links by overlapping the determined basic paths, determining a first document from among the documents and an input reference link for the first document, performing a Markov chain model using a probability value of the input reference link, and calculating the information about the main knowledge stream for the first document using a result obtained by performing the Markov chain model; and an output module for providing the information about the main knowledge stream for the first document calculated by the information process module.
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7. An apparatus for providing information about a main knowledge stream, the apparatus comprising: a storage module for storing information about a plurality of documents; an information process module for obtaining reference links representing reference relationships among reference documents for each of the documents from information about the documents stored in the storage module, defining one or more paths connecting the reference links for each of the plurality of documents, determining a longest path among the defined paths as a basic path for each of the plurality of documents, calculating probability values of the reference links by overlapping the determined basic paths, determining a first document from among the documents and an input reference link for the first document, performing a Markov chain model using a probability value of the input reference link, and calculating the information about the main knowledge stream for the first document using a result obtained by performing the Markov chain model; and an output module for providing the information about the main knowledge stream for the first document calculated by the information process module. 11. The apparatus according to claim 7 , wherein the information process module defines the paths connecting the reference links by defining paths from an oldest reference document to a most recent reference document.
| 0.600418 |
12. The system of claim 1 wherein the value indicative of an application program in the link table is a location of the application program in the memory.
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12. The system of claim 1 wherein the value indicative of an application program in the link table is a location of the application program in the memory. 13. The system of claim 12, wherein the means for retrieving a message from the message file includes means, within the operating system and responsive to a current application program outputting an output value, for identifying the current application program, and for searching the link table for a link indicative of the current application program.
| 0.93073 |
7. A client, comprising: a collecting unit configured to collect font parameters and layout parameters of a text block; a transmitting unit configured to transmit the font parameters and the layout parameters of the text block to a server; and a drawing command executing unit configured to receive vector description information of the text block, generated according to the font parameters and the layout parameters of the text block, sent from the server, and to execute drawing commands to draw the text block and display the text block on a screen; wherein the vector description information of the text block is encoded and compressed by the server and then the drawing command executing unit receives encoded and compressed vector description information of the text block sent from the server; wherein the server encodes and compresses the vector description information of the text block specifically as follows: encoding a name of each drawing command to shorten length of the name of each drawing command; retaining one or two decimal places of floating point data in the vector description information of the text block to obtain simplified floating point data; and converting the simplified floating point data into decimal integer data by multiplying the simplified floating point data with a fixed coefficient, and then converting the decimal integer data into hexadecimal data; and the client decodes and decompresses the vector description information of the text block specifically as follows: decoding the received name of each drawing command to recover the name of each drawing command; and converting the received hexadecimal data into the decimal integer data, and dividing the decimal integer data by the fixed coefficient to obtain the simplified floating point data.
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7. A client, comprising: a collecting unit configured to collect font parameters and layout parameters of a text block; a transmitting unit configured to transmit the font parameters and the layout parameters of the text block to a server; and a drawing command executing unit configured to receive vector description information of the text block, generated according to the font parameters and the layout parameters of the text block, sent from the server, and to execute drawing commands to draw the text block and display the text block on a screen; wherein the vector description information of the text block is encoded and compressed by the server and then the drawing command executing unit receives encoded and compressed vector description information of the text block sent from the server; wherein the server encodes and compresses the vector description information of the text block specifically as follows: encoding a name of each drawing command to shorten length of the name of each drawing command; retaining one or two decimal places of floating point data in the vector description information of the text block to obtain simplified floating point data; and converting the simplified floating point data into decimal integer data by multiplying the simplified floating point data with a fixed coefficient, and then converting the decimal integer data into hexadecimal data; and the client decodes and decompresses the vector description information of the text block specifically as follows: decoding the received name of each drawing command to recover the name of each drawing command; and converting the received hexadecimal data into the decimal integer data, and dividing the decimal integer data by the fixed coefficient to obtain the simplified floating point data. 9. The client according to claim 7 , wherein the font parameters of the text block include a name, size, color, bold or not, italic or not and underline or not of a text font; and the layout parameters of the text block include width of the text block, height of the text block, row spacing of the text block, horizontal and vertical alignment patterns, line spacing, a first line indent distance and contents of the text block.
| 0.5 |
1. A system using one or more servers comprising one or more processors for providing a recommended search query and an advertising word, the system comprising: a non-transitory storage device coupled to the one or more servers, the non-transitory storage device comprising a plurality of search queries and a plurality of advertising words, wherein an index component configured to make an index of the search queries and the advertising words according to one of a consonant/vowel, a syllable, a suffix or any combination thereof and the index is classified and stored in the non-transitory storage device; a web server configured to receive a partial or full search query in real-time and to transmit the partial or full search query to a query autocompletion server, the partial or full search query being entered in a search display area of a web page; and upon detection of the partial or full search query, the query autocompletion server is configured to generate an auto-completed search query and an auto-completed advertising word according to the index, the generation occurring in real-time as the partial or full search query is entered, wherein the generated auto-completed search query and the auto-completed advertising word are displayed in real-time in a user interface window associated with the search display area, the displaying including using a visual indicator to distinguish the auto-completed advertising word from the auto-completed search query.
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1. A system using one or more servers comprising one or more processors for providing a recommended search query and an advertising word, the system comprising: a non-transitory storage device coupled to the one or more servers, the non-transitory storage device comprising a plurality of search queries and a plurality of advertising words, wherein an index component configured to make an index of the search queries and the advertising words according to one of a consonant/vowel, a syllable, a suffix or any combination thereof and the index is classified and stored in the non-transitory storage device; a web server configured to receive a partial or full search query in real-time and to transmit the partial or full search query to a query autocompletion server, the partial or full search query being entered in a search display area of a web page; and upon detection of the partial or full search query, the query autocompletion server is configured to generate an auto-completed search query and an auto-completed advertising word according to the index, the generation occurring in real-time as the partial or full search query is entered, wherein the generated auto-completed search query and the auto-completed advertising word are displayed in real-time in a user interface window associated with the search display area, the displaying including using a visual indicator to distinguish the auto-completed advertising word from the auto-completed search query. 2. The system of claim 1 , wherein the web server is configured to display the auto-completed advertising word distinguishable from the auto-completed search query using one of a larger font, a different color, an underline or any combination thereof.
| 0.503719 |
1. A method comprising: receiving, from a first client device, a request for a font; determining whether the request for the font specifies a set of glyphs that includes less than all glyphs defined for the font; in response to determining that the specified set of glyphs includes less than all of the glyphs defined for the font, generating a reduced glyph font file that includes only the specified set of glyphs; caching, at a font server different from the first client device, the reduced glyph font file in association with an identifier of a network document corresponding to the request for the font; receiving, from a second client device, a request for the network document, wherein the request for the network document includes the identifier of the network document; and in response to receiving the request for the network document and based on the identifier of the network document, providing the cached reduced glyph font file to the second client device.
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1. A method comprising: receiving, from a first client device, a request for a font; determining whether the request for the font specifies a set of glyphs that includes less than all glyphs defined for the font; in response to determining that the specified set of glyphs includes less than all of the glyphs defined for the font, generating a reduced glyph font file that includes only the specified set of glyphs; caching, at a font server different from the first client device, the reduced glyph font file in association with an identifier of a network document corresponding to the request for the font; receiving, from a second client device, a request for the network document, wherein the request for the network document includes the identifier of the network document; and in response to receiving the request for the network document and based on the identifier of the network document, providing the cached reduced glyph font file to the second client device. 2. The method of claim 1 , wherein the set of glyphs is specified using Unicode.
| 0.947943 |
61. At least one non-transitory computer-readable storage medium encoded with computer-executable instructions that, when executed, perform a method comprising: transcribing audio data comprising audio of one or more clinical personnel speaking while performing a surgical procedure, the audio data comprising audio of a first clinician speaking to one or more other clinical personnel while performing the surgical procedure; analyzing the transcribed audio data, including the transcribed audio of the first clinician speaking to the one or more other clinical personnel while performing the surgical procedure, at least in part by automatically extracting one or more clinical facts from the transcribed audio data, to identify relevant information for documenting the surgical procedure, wherein analyzing the transcribed audio data comprises identifying within the transcribed audio data a present-tense narration by the first clinician stating to the other clinical personnel that the first clinician is currently performing a particular step of the surgical procedure; automatically generating a text report including the relevant information documenting the surgical procedure, wherein automatically generating the text report comprises automatically transforming the present-tense narration into a non-present-tense portion in the report, stating that the particular step of the surgical procedure was performed; and outputting the automatically generated text report for review via a user interface on an audio and/or visual display device.
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61. At least one non-transitory computer-readable storage medium encoded with computer-executable instructions that, when executed, perform a method comprising: transcribing audio data comprising audio of one or more clinical personnel speaking while performing a surgical procedure, the audio data comprising audio of a first clinician speaking to one or more other clinical personnel while performing the surgical procedure; analyzing the transcribed audio data, including the transcribed audio of the first clinician speaking to the one or more other clinical personnel while performing the surgical procedure, at least in part by automatically extracting one or more clinical facts from the transcribed audio data, to identify relevant information for documenting the surgical procedure, wherein analyzing the transcribed audio data comprises identifying within the transcribed audio data a present-tense narration by the first clinician stating to the other clinical personnel that the first clinician is currently performing a particular step of the surgical procedure; automatically generating a text report including the relevant information documenting the surgical procedure, wherein automatically generating the text report comprises automatically transforming the present-tense narration into a non-present-tense portion in the report, stating that the particular step of the surgical procedure was performed; and outputting the automatically generated text report for review via a user interface on an audio and/or visual display device. 66. The at least one non-transitory computer-readable storage medium of claim 61 , wherein the surgical procedure is performed on a patient, and wherein the audio data comprises audio of the one or more clinical personnel orally identifying one or more substances administered to the patient in connection with the surgical procedure.
| 0.637896 |
13. A speech recognition method comprising: in a computer processor, generating recognition result hypotheses for a speech supplied from one speech input unit, the recognition result hypotheses not being biased to either a first application or a second application; and the computer processor receiving the recognition result hypotheses and simultaneously generating a first recognition result specialized for the first application and a second recognition result, different from the first recognition result, specialized for the second application, and outputting the recognition results to the respective applications.
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13. A speech recognition method comprising: in a computer processor, generating recognition result hypotheses for a speech supplied from one speech input unit, the recognition result hypotheses not being biased to either a first application or a second application; and the computer processor receiving the recognition result hypotheses and simultaneously generating a first recognition result specialized for the first application and a second recognition result, different from the first recognition result, specialized for the second application, and outputting the recognition results to the respective applications. 17. The method according to claim 13 , wherein the applications include applications that obtain the speech recognition results and perform original processes, respectively; and the applications include a plurality of types of: an application that converts an operator's call to characters and displays the characters on a terminal of an operator; an application that extracts a keyword from a call and performs information retrieval on the terminal of the operator; an application that presents information on a call converted to characters on a terminal of a supervisor of the operator; and an application that detects a situation that needs help for the operator and presents the situation on the terminal of the supervisor of the operator.
| 0.755773 |
15. A method of operating a handheld electronic device that stores contact information for a plurality of contacts, comprising: detecting a phone call either placed by or received by said handheld electronic device, said phone call being associated with a particular one of said contacts; in response to detecting said phone call, determining whether said particular one of said contacts has a preferred language; and if it is determined that said particular one of said contacts has a preferred language, providing information reflecting said preferred language while said phone call is in progress.
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15. A method of operating a handheld electronic device that stores contact information for a plurality of contacts, comprising: detecting a phone call either placed by or received by said handheld electronic device, said phone call being associated with a particular one of said contacts; in response to detecting said phone call, determining whether said particular one of said contacts has a preferred language; and if it is determined that said particular one of said contacts has a preferred language, providing information reflecting said preferred language while said phone call is in progress. 17. The method according to claim 15 , wherein said information is provided audibly.
| 0.836245 |
2. The computing device of claim 1 , further comprising instructions for: detecting a selection of a truncated autosuggest candidate; and displaying a modified search query within in the search box by appending the truncated autosuggest candidate to the preliminary search query, without automatically initiating a web search for the modified search query.
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2. The computing device of claim 1 , further comprising instructions for: detecting a selection of a truncated autosuggest candidate; and displaying a modified search query within in the search box by appending the truncated autosuggest candidate to the preliminary search query, without automatically initiating a web search for the modified search query. 3. The computing device of claim 2 , further comprising instructions for: receiving updated autosuggest candidates having the modified search query as a new common prefix; generating truncated autosuggest candidates by removing the new common prefix from each updated autosuggest candidate; and appending a selected truncated autosuggest candidate to the modified search query.
| 0.8 |
1. A device for manipulating and viewing documents, comprising: a touchscreen display for detecting tactile input and for displaying content in an integrated display of at least a current page of a first document and at least one other page from said first document or from a second document, a processor configured for controlling the displaying of content of at least the current page of the first document and said at least one other page from said first document or from the second document on the touchscreen display according to proportional distance criteria, and wherein the current page and said at least one other page from said first document or from the second document comprise text, image, graphics, or a combination thereof; wherein the current page or said at least one other page from said first document or from the second document is displayed on the touchscreen display in response to a pan command; wherein the pan command causes display according to inertia and velocity sensed by the device.
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1. A device for manipulating and viewing documents, comprising: a touchscreen display for detecting tactile input and for displaying content in an integrated display of at least a current page of a first document and at least one other page from said first document or from a second document, a processor configured for controlling the displaying of content of at least the current page of the first document and said at least one other page from said first document or from the second document on the touchscreen display according to proportional distance criteria, and wherein the current page and said at least one other page from said first document or from the second document comprise text, image, graphics, or a combination thereof; wherein the current page or said at least one other page from said first document or from the second document is displayed on the touchscreen display in response to a pan command; wherein the pan command causes display according to inertia and velocity sensed by the device. 7. The device according to claim 1 , wherein the proportional distance criteria comprises a sequence of pages in the first document.
| 0.611706 |
4. The method of claim 2 wherein the learning graph further comprises a plurality of learning goal nodes, wherein one or more person nodes have one or more edges to one or more learning goal nodes.
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4. The method of claim 2 wherein the learning graph further comprises a plurality of learning goal nodes, wherein one or more person nodes have one or more edges to one or more learning goal nodes. 5. The method of claim 4 wherein one or more learning goal nodes have one or more edges to one or more learning collection nodes.
| 0.956996 |
13. A system for validating a markup language document against a markup language schema definition, the system comprising: a markup language schema compilation for generating an annotated automaton encoding corresponding to the markup language schema definition; and a runtime validation engine comprising a markup language schema validation parser, the runtime validation engine to receive the markup language document and the annotated automaton encoding as input, wherein the markup language schema validation parser associated with the runtime validation engine utilizes the annotated automaton encoding to validate the markup language document against the markup language schema definition including ensuring that the markup language document complies with a format specified by the markup language schema definition.
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13. A system for validating a markup language document against a markup language schema definition, the system comprising: a markup language schema compilation for generating an annotated automaton encoding corresponding to the markup language schema definition; and a runtime validation engine comprising a markup language schema validation parser, the runtime validation engine to receive the markup language document and the annotated automaton encoding as input, wherein the markup language schema validation parser associated with the runtime validation engine utilizes the annotated automaton encoding to validate the markup language document against the markup language schema definition including ensuring that the markup language document complies with a format specified by the markup language schema definition. 14. The system of claim 13 , wherein the markup language comprises an Extensible Markup Language (XML).
| 0.716418 |
7. The method of claim 6 , further comprising attaching a semantic tag to entities within a cluster of the one or more clusters.
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7. The method of claim 6 , further comprising attaching a semantic tag to entities within a cluster of the one or more clusters. 9. The method of claim 7 , wherein the selectively removing items from the cluster that do not meet at least one relatedness criteria is performed in response to a previous selectively adding the candidate entity based changing the one or more degrees of relatedness and one or more degree of relatedness criteria of the selectively removed items.
| 0.898007 |
15. An apparatus, comprising: a memory element for storing data; a processor that executes instructions associated with the data; an analyzer configured to interface with the processor and the memory element such that the apparatus is configured for: receiving a video bitstream in a network environment; decoding an audio portion of the video bitstream; automatically detecting a question in the decoded audio portion of the video bitstream; marking a segment of the video bitstream with a tag corresponding to a location of the automatically detected question in the video bitstream, wherein the tag can facilitate consumption of the video bitstream; receiving a search query seeking the automatically detected question; and returning the segment marked with the tag.
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15. An apparatus, comprising: a memory element for storing data; a processor that executes instructions associated with the data; an analyzer configured to interface with the processor and the memory element such that the apparatus is configured for: receiving a video bitstream in a network environment; decoding an audio portion of the video bitstream; automatically detecting a question in the decoded audio portion of the video bitstream; marking a segment of the video bitstream with a tag corresponding to a location of the automatically detected question in the video bitstream, wherein the tag can facilitate consumption of the video bitstream; receiving a search query seeking the automatically detected question; and returning the segment marked with the tag. 19. The apparatus of claim 15 , wherein the apparatus is further configured for: counting a number of questions in the video bitstream.
| 0.536095 |
1. A non-transitory machine-readable medium including instructions for transmitting a message to a secondary computing device, which when executed by a machine, cause the machine to perform operations comprising: receiving a communication message at a primary computing device of a user; transmitting a default response option, from the primary computing device to the secondary computing device, to respond to the communication message based on a context of the user, the context of the user determined by using a sensor included in the primary computing device; identifying a message mode for communicating with a secondary computing device of the user based on a context of the user determined by using a sensor included in the primary computing device; and determining that the communication message is to be transmitted to the secondary computing device of the user based on the message mode, and based on the determining: translating the communication message into a translated message according to the message mode, the translating comprising truncating content of the communication message; and transmitting the translated message to the secondary computing device from the primary computing device.
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1. A non-transitory machine-readable medium including instructions for transmitting a message to a secondary computing device, which when executed by a machine, cause the machine to perform operations comprising: receiving a communication message at a primary computing device of a user; transmitting a default response option, from the primary computing device to the secondary computing device, to respond to the communication message based on a context of the user, the context of the user determined by using a sensor included in the primary computing device; identifying a message mode for communicating with a secondary computing device of the user based on a context of the user determined by using a sensor included in the primary computing device; and determining that the communication message is to be transmitted to the secondary computing device of the user based on the message mode, and based on the determining: translating the communication message into a translated message according to the message mode, the translating comprising truncating content of the communication message; and transmitting the translated message to the secondary computing device from the primary computing device. 2. The machine-readable medium of claim 1 , wherein determining that the communication message is to be transmitted comprises: comparing a type of communication message permitted for transmittal to the secondary computing device, according to the message mode, with the type of the received communication message.
| 0.537874 |
1. A method, comprising: receiving, via an element included in a user interface, a user-defined, structured input; selecting, in real time, an active input from the user-defined, structured input based at least in part on context associated with the user interface; using a processor to determine a context-sensitive rule that applies to the active input, wherein: the context-sensitive rule requires that the active input be a specific data type; and using the processor to determine the context-sensitive rule includes: setting one or more of the following: a permitted values bit or a permitted formats bit; dividing, based at least in part on the active input, inactive inputs from the user-defined, structured input into two groups: (1) those inactive inputs that affect the active input with respect to a format or content limitation and (2) those inactive inputs that do not affect the active input with respect to a format or content limitation; determining if any inactive inputs affect the active input with respect to a format or content limitation; and in the event it is determined none of the inactive inputs affect the active input with respect to a format or content limitation: determining, without taking into consideration any of the inactive inputs, if the active input is limited to certain permitted values; and determining, without taking into consideration any of the inactive inputs, if the active input is limited to certain permitted formats; and providing, in real time via the user interface, guidance associated with the active input and the context-sensitive rule, including by performing the following: displaying, in the user interface, format assistance which includes one or more of the following: (1) identification of the specific data type that satisfies the context-sensitive rule or (2) automatic configuration of the user interface so that the active input has a data type which matches the specific data type that satisfies the context-sensitive rule; and displaying, in the user interface, format validation which indicates whether the context-sensitive rule is satisfied based at least in part on a current data type of the active input.
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1. A method, comprising: receiving, via an element included in a user interface, a user-defined, structured input; selecting, in real time, an active input from the user-defined, structured input based at least in part on context associated with the user interface; using a processor to determine a context-sensitive rule that applies to the active input, wherein: the context-sensitive rule requires that the active input be a specific data type; and using the processor to determine the context-sensitive rule includes: setting one or more of the following: a permitted values bit or a permitted formats bit; dividing, based at least in part on the active input, inactive inputs from the user-defined, structured input into two groups: (1) those inactive inputs that affect the active input with respect to a format or content limitation and (2) those inactive inputs that do not affect the active input with respect to a format or content limitation; determining if any inactive inputs affect the active input with respect to a format or content limitation; and in the event it is determined none of the inactive inputs affect the active input with respect to a format or content limitation: determining, without taking into consideration any of the inactive inputs, if the active input is limited to certain permitted values; and determining, without taking into consideration any of the inactive inputs, if the active input is limited to certain permitted formats; and providing, in real time via the user interface, guidance associated with the active input and the context-sensitive rule, including by performing the following: displaying, in the user interface, format assistance which includes one or more of the following: (1) identification of the specific data type that satisfies the context-sensitive rule or (2) automatic configuration of the user interface so that the active input has a data type which matches the specific data type that satisfies the context-sensitive rule; and displaying, in the user interface, format validation which indicates whether the context-sensitive rule is satisfied based at least in part on a current data type of the active input. 5. The method of claim 1 , wherein the specific data type that satisfies the context-sensitive rule includes one or more of the following: a string, an integer, a floating point, a regular expression, or a Boolean.
| 0.733911 |
1. A method for reproducing a 2D drawing from an annotated 3D computer-aided design (CAD) model, the method comprising: receiving, at a processing circuit, an annotated 3D CAD model of a physical part or assembly; generating, by the processing circuit, a 2D drawing of the physical part of assembly using the annotated 3D CAD model; receiving, at the processing circuit via a user interface, a modification to the 2D drawing; storing, by the processing circuit, the modification to the 2D drawing as 2D drawing parameters within the annotated 3D CAD model to amend the annotated 3D CAD model, wherein the 2D drawing parameters provide instructions for reproducing the 2D drawing including the modification, such that the 2D drawing is not saved; and reproducing, by the processing circuit, the 2D drawing including the modification using the 2D drawing parameters within the annotated 3D CAD model.
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1. A method for reproducing a 2D drawing from an annotated 3D computer-aided design (CAD) model, the method comprising: receiving, at a processing circuit, an annotated 3D CAD model of a physical part or assembly; generating, by the processing circuit, a 2D drawing of the physical part of assembly using the annotated 3D CAD model; receiving, at the processing circuit via a user interface, a modification to the 2D drawing; storing, by the processing circuit, the modification to the 2D drawing as 2D drawing parameters within the annotated 3D CAD model to amend the annotated 3D CAD model, wherein the 2D drawing parameters provide instructions for reproducing the 2D drawing including the modification, such that the 2D drawing is not saved; and reproducing, by the processing circuit, the 2D drawing including the modification using the 2D drawing parameters within the annotated 3D CAD model. 7. The method of claim 1 , wherein the modification to the 2D drawing comprises a non-standard view of the annotated 3D CAD model; wherein storing the modification within the annotated 3D CAD model comprises storing a view object defining the non-standard view as a 3D view of the annotated 3D CAD model.
| 0.557265 |
1. A computer implemented method of sharing information between a semantic network stored in a memory of a first computer system and a knowledge sharing repository, comprising: retrieving, from the semantic network, a set of data based on information included in the semantic network; accessing the knowledge sharing repository from the first computer system; and transferring, from the first computer system, the set of data to a computer system hosting the knowledge sharing repository for incorporation into the knowledge sharing repository.
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1. A computer implemented method of sharing information between a semantic network stored in a memory of a first computer system and a knowledge sharing repository, comprising: retrieving, from the semantic network, a set of data based on information included in the semantic network; accessing the knowledge sharing repository from the first computer system; and transferring, from the first computer system, the set of data to a computer system hosting the knowledge sharing repository for incorporation into the knowledge sharing repository. 17. The method of claim 1 wherein: said retrieving comprises extracting a content document comprising at least a portion of the set of data; and said transferring comprises inserting the content document into a page of the knowledge sharing repository.
| 0.667063 |
1. A method for removing a mark in a document image, the method comprising: extracting connected components from a binary image corresponding to the document image; clustering the connected components based on grayscale features of the connected components to obtain one clustering center; searching, within numerical ranges of a clustering radius R from the clustering center and a grayscale threshold T, for a combination (R, T) which causes an evaluation value based on the grayscale features of the connected components to be higher than a first evaluation threshold; and removing the mark in the document image based on the grayscale threshold in the combination; wherein the grayscale features of the connected components comprise: a minimum one of grayscale values of pixels in the document image, which correspond to all black pixels in each of connected components; wherein the removing the mark in the document image based on the grayscale threshold in the combination comprises: removing the connected components, the grayscale features of which are greater than the grayscale threshold, as the mark in the document image.
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1. A method for removing a mark in a document image, the method comprising: extracting connected components from a binary image corresponding to the document image; clustering the connected components based on grayscale features of the connected components to obtain one clustering center; searching, within numerical ranges of a clustering radius R from the clustering center and a grayscale threshold T, for a combination (R, T) which causes an evaluation value based on the grayscale features of the connected components to be higher than a first evaluation threshold; and removing the mark in the document image based on the grayscale threshold in the combination; wherein the grayscale features of the connected components comprise: a minimum one of grayscale values of pixels in the document image, which correspond to all black pixels in each of connected components; wherein the removing the mark in the document image based on the grayscale threshold in the combination comprises: removing the connected components, the grayscale features of which are greater than the grayscale threshold, as the mark in the document image. 5. The method according to claim 1 , wherein the evaluation value reflects a degree of matching of a result of classifying the connected components based on the clustering center and the clustering radius with a result of classifying the connected components based on the grayscale threshold.
| 0.790115 |
9. The sleeve system for beverage containers set forth in claim 8 , further comprising a second face also defined by said first and second edges, and said first and second lateral edges.
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9. The sleeve system for beverage containers set forth in claim 8 , further comprising a second face also defined by said first and second edges, and said first and second lateral edges. 10. The sleeve system for beverage containers set forth in claim 9 , further characterized in that extending from said first edge is a hook-fastening section that extends said first predetermined distance to said third edge.
| 0.809132 |
5. The method as recited in claim 1 wherein said method is further comprised of the steps of: f) determining if said generated document clusters provides acceptable clustering results; g) if said generated document clusters does not provide acceptable clustering results, varying the value of said link frequency threshold; and h) repeating steps b)-e).
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5. The method as recited in claim 1 wherein said method is further comprised of the steps of: f) determining if said generated document clusters provides acceptable clustering results; g) if said generated document clusters does not provide acceptable clustering results, varying the value of said link frequency threshold; and h) repeating steps b)-e). 7. The method as recited in claim 5 wherein an unacceptable clustering result is a combination of fewer clusters with fewer documents in the clusters, said step of varying the value of said link frequency threshold causes said link frequency threshold to increase.
| 0.786076 |
10. A computer-implemented method comprising: accessing positive sample entities that belong to an entity class and negative sample entities that do not belong to the entity class; identifying clicked URLs from search click logs for at least a portion of the positive sample entities and negative sample entities; identifying search result URLs for at least a portion of the positive sample entities and negative sample entities; identifying attributes from an entity graph for at least a portion of the positive sample entities and negative sample entities; training, using a computing device, a classifier model using the clicked URLs, search result URLs, and attributes from the entity graph as features of the positive sample entities and negative sample entities; and employing the classifier model to weight entities in a candidate dictionary to provide weightings for the entities from the candidate dictionary.
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10. A computer-implemented method comprising: accessing positive sample entities that belong to an entity class and negative sample entities that do not belong to the entity class; identifying clicked URLs from search click logs for at least a portion of the positive sample entities and negative sample entities; identifying search result URLs for at least a portion of the positive sample entities and negative sample entities; identifying attributes from an entity graph for at least a portion of the positive sample entities and negative sample entities; training, using a computing device, a classifier model using the clicked URLs, search result URLs, and attributes from the entity graph as features of the positive sample entities and negative sample entities; and employing the classifier model to weight entities in a candidate dictionary to provide weightings for the entities from the candidate dictionary. 11. The method of claim 10 , wherein the positive sample entities and the negative sample entities are identified based on information from at least one selected from the following: an existing entity graph and training data from a spoken language understanding system.
| 0.606855 |
4. The method of claim 1 further comprising, after storing at least one unaccepted element for subsequent analysis, adjusting the acceptance threshold and comparing the confidence factor for at least one stored element to the adjusted acceptance threshold.
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4. The method of claim 1 further comprising, after storing at least one unaccepted element for subsequent analysis, adjusting the acceptance threshold and comparing the confidence factor for at least one stored element to the adjusted acceptance threshold. 10. The method of claim 4 wherein an adjustment amount for the acceptance threshold is a variable amount.
| 0.930633 |
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