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1. A method for enabling a mobile device to print a document at a printing device, comprising: receiving the document at the mobile device, wherein the document includes text and identifies at least one target font reference for each character; determining if a name of the target font reference is listed in a font strategy table, then employing at least one of a corresponding logic component, substitute font data, and character data to provide substitute font information and width for each character to the printing device; determining if the name of the target font reference is unlisted in the font strategy table, then updating the font strategy table to include the name of the unlisted target font reference, wherein each updated target font reference corresponds to at least one logic component, substitute font data or character data; generating a first character table for the target font reference that includes at least a glyph index and a unicode; generating a second character table for the target font reference that includes at least a width and a glyph name; and enabling the printing device to employ provided font information and width for each character to print text included in the document.
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1. A method for enabling a mobile device to print a document at a printing device, comprising: receiving the document at the mobile device, wherein the document includes text and identifies at least one target font reference for each character; determining if a name of the target font reference is listed in a font strategy table, then employing at least one of a corresponding logic component, substitute font data, and character data to provide substitute font information and width for each character to the printing device; determining if the name of the target font reference is unlisted in the font strategy table, then updating the font strategy table to include the name of the unlisted target font reference, wherein each updated target font reference corresponds to at least one logic component, substitute font data or character data; generating a first character table for the target font reference that includes at least a glyph index and a unicode; generating a second character table for the target font reference that includes at least a width and a glyph name; and enabling the printing device to employ provided font information and width for each character to print text included in the document. 2. The method of claim 1 , further comprising determining if the name of the target font reference is non-listed in the font strategy table and target information is available in a runtime environment for the mobile device, then providing the target font information and width for each character to the printing device.
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4. The method of claim 1, comprising the further steps of: selecting a subset of run-time components called for by said standard execution model; and fixing only said subset of run-time components within a system.
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4. The method of claim 1, comprising the further steps of: selecting a subset of run-time components called for by said standard execution model; and fixing only said subset of run-time components within a system. 5. The method of claim 4, comprising the further steps of: including within said system, software realizing a virtual machine for executing said machine-independent code instructions, and communications software for downloading a file of said machine-independent code instructions.
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1. A document acceptor for authenticating and storing documents, the document acceptor comprising: a document validator configured to authenticate received documents; a document cassette configured to store the documents received by the document validator; and a displacement actuator including a housing, a lever, and a cam operatively coupled to the lever, wherein rotation of the lever causes the cam to transition between a first cam position and a second cam position, wherein the cam is configured to interface with the document cassette when moving to the second cam position to change a position of the document cassette from a first position to a second position to mate the document cassette with the document validator, wherein the housing is adapted to removably secure the displacement actuator to a document acceptor, and wherein the housing is held in a fixed position relative to the document validator while the position of the document cassette is changed.
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1. A document acceptor for authenticating and storing documents, the document acceptor comprising: a document validator configured to authenticate received documents; a document cassette configured to store the documents received by the document validator; and a displacement actuator including a housing, a lever, and a cam operatively coupled to the lever, wherein rotation of the lever causes the cam to transition between a first cam position and a second cam position, wherein the cam is configured to interface with the document cassette when moving to the second cam position to change a position of the document cassette from a first position to a second position to mate the document cassette with the document validator, wherein the housing is adapted to removably secure the displacement actuator to a document acceptor, and wherein the housing is held in a fixed position relative to the document validator while the position of the document cassette is changed. 4. The document acceptor of claim 1 , further comprising a chassis coupling the document validator and the displacement actuator, the chassis adapted to allow insertion and removal of the document cassette in a first direction.
| 0.59599 |
1. A method executed at least in part in a computing device to generate automatic command shell command code based on a schema, the method comprising: receiving the schema that includes one or more of: element declarations, attribute declarations, simple type definitions and complex type definitions; reading the schema to create a model for classes that include an interface and a structure, wherein the classes validate constraints in the schema; optimizing the model to translate the schema to an application programming interface (API); and inserting a plug-in to the optimized model to generate a command for a command shell based on the optimized model by; disabling generation of a default code for the command, using the plug-in; and generating a plug-in code for the command, using the plug-in, wherein the command manipulates data that is structured based on the classes according to a class definition in a data store associated with the schema defined by the optimized model at runtime.
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1. A method executed at least in part in a computing device to generate automatic command shell command code based on a schema, the method comprising: receiving the schema that includes one or more of: element declarations, attribute declarations, simple type definitions and complex type definitions; reading the schema to create a model for classes that include an interface and a structure, wherein the classes validate constraints in the schema; optimizing the model to translate the schema to an application programming interface (API); and inserting a plug-in to the optimized model to generate a command for a command shell based on the optimized model by; disabling generation of a default code for the command, using the plug-in; and generating a plug-in code for the command, using the plug-in, wherein the command manipulates data that is structured based on the classes according to a class definition in a data store associated with the schema defined by the optimized model at runtime. 6. The method of claim 1 , wherein the command is a cmdlet for the command shell.
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12. An article of manufacture storing processor-executable instructions thereon for merging a first version of a computer design model with a second version of a computer design model, the article of manufacture comprising: instructions to compare a first history section within a first model description document for the first version of the computer design model with a second history section within a second model description document for the second version of the computer design model to identify a baseline, the history section of each model description document comprising a list of model versions from which its version of the computer design model was modified and the baseline being the most recent model version present in both the first and second history sections; instructions to compare elements of the first version of the computer design model to elements of the second version of the computer design model and to compare the elements of both the first and second versions of the computer design model to the baseline to identify elements newly-added to, deleted from, or changed in the first version subsequent to the baseline and to identify elements newly-added to, deleted from, or changed in the second version subsequent to the baseline; instructions to present the elements newly-added to, deleted from, or changed in the first version subsequent to the baseline and the elements newly-added to, deleted from, or changed in the second version subsequent to the baseline; instructions to facilitate selection of elements in the second version of the computer design model for merging into the first version of the computer design model; instructions to present an indication of the merging action to be taken for each selected element; and instructions to take the indicated actions, thereby merging the first version with the second version.
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12. An article of manufacture storing processor-executable instructions thereon for merging a first version of a computer design model with a second version of a computer design model, the article of manufacture comprising: instructions to compare a first history section within a first model description document for the first version of the computer design model with a second history section within a second model description document for the second version of the computer design model to identify a baseline, the history section of each model description document comprising a list of model versions from which its version of the computer design model was modified and the baseline being the most recent model version present in both the first and second history sections; instructions to compare elements of the first version of the computer design model to elements of the second version of the computer design model and to compare the elements of both the first and second versions of the computer design model to the baseline to identify elements newly-added to, deleted from, or changed in the first version subsequent to the baseline and to identify elements newly-added to, deleted from, or changed in the second version subsequent to the baseline; instructions to present the elements newly-added to, deleted from, or changed in the first version subsequent to the baseline and the elements newly-added to, deleted from, or changed in the second version subsequent to the baseline; instructions to facilitate selection of elements in the second version of the computer design model for merging into the first version of the computer design model; instructions to present an indication of the merging action to be taken for each selected element; and instructions to take the indicated actions, thereby merging the first version with the second version. 13. The article of manufacture of claim 12 , wherein the indicated actions are each selected from the group consisting of creating, overwriting, and deleting a selected element.
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16. The medium of claim 15 , wherein the heuristic indicators are associated with environmental settings to allow adjustment between effectiveness of the protection and efficiency of execution of the code stream.
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16. The medium of claim 15 , wherein the heuristic indicators are associated with environmental settings to allow adjustment between effectiveness of the protection and efficiency of execution of the code stream. 18. The medium of claim 16 , wherein the heuristic indicators include a decay factor configured according to the environmental settings, and wherein the amount of un-trusted code represents number of bytes in the un-trusted code dynamically adjusted by the decay factor to prevent penalizing code sized with a large number of bytes.
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36. A system comprising: one or more computers programmed to perform operations comprising: calculating one or more time trend statistics for a plurality of quality of result statistics for a first document as a search result for a first query, each of the quality of result statistics corresponding to a different time period and being an estimate of a respective portion of users that found the first document relevant to the first query out of a total number of users who viewed the first document as a search result for the first query during the time period, the one or more time trend statistics estimating changes in the quality of result statistics over time; generating a first modified quality of result statistic by modifying a first quality of result statistic for the first document as a search result for the first query by a factor, where the factor is based on the one or more time trend statistics; and providing the first modified quality of result statistic as an input to a document ranking process for the first document and the first query.
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36. A system comprising: one or more computers programmed to perform operations comprising: calculating one or more time trend statistics for a plurality of quality of result statistics for a first document as a search result for a first query, each of the quality of result statistics corresponding to a different time period and being an estimate of a respective portion of users that found the first document relevant to the first query out of a total number of users who viewed the first document as a search result for the first query during the time period, the one or more time trend statistics estimating changes in the quality of result statistics over time; generating a first modified quality of result statistic by modifying a first quality of result statistic for the first document as a search result for the first query by a factor, where the factor is based on the one or more time trend statistics; and providing the first modified quality of result statistic as an input to a document ranking process for the first document and the first query. 37. The system of claim 36 , wherein the one or more time trend statistics include a quality of result difference between two of the quality of result statistics.
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1. A method for extraction of text from a set of text documents, the method comprising the steps of: a) identifying a plurality of document segments within a given text document; b) for each given document segment identified in a), generating and storing at least one structured annotation embedded within the document and associated with the given segment, the at least one structured annotation specifying the start and end of the given document segment and a rhetorical relation associated with the given segment; c) processing the structured annotations generated and stored in b) to generate a plurality of variables that represent document segments and associated rhetorical relations as specified by the structured annotations; d) storing the variables generated in c) in a repository; e) receiving query input from a user that specifies at least one rhetorical relation of interest; and f) in response to receipt of said query input, querying the variables stored in the repository to identify zero or more document segments that are associated with a rhetorical relation that matches the at least one rhetorical relation of interest specified by said query input for output to the user.
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1. A method for extraction of text from a set of text documents, the method comprising the steps of: a) identifying a plurality of document segments within a given text document; b) for each given document segment identified in a), generating and storing at least one structured annotation embedded within the document and associated with the given segment, the at least one structured annotation specifying the start and end of the given document segment and a rhetorical relation associated with the given segment; c) processing the structured annotations generated and stored in b) to generate a plurality of variables that represent document segments and associated rhetorical relations as specified by the structured annotations; d) storing the variables generated in c) in a repository; e) receiving query input from a user that specifies at least one rhetorical relation of interest; and f) in response to receipt of said query input, querying the variables stored in the repository to identify zero or more document segments that are associated with a rhetorical relation that matches the at least one rhetorical relation of interest specified by said query input for output to the user. 6. A method according to claim 1 , wherein: said at least one structured annotation generated and stored in b) is an XML tag.
| 0.655152 |
1. A method comprising: analyzing, by a computing device, a previous conversation with a first virtual assistant to identify a topic that has been discussed in the previous conversation more than a predetermined number of times; identifying a second virtual assistant that is not currently associated with an account of a user and that is configured to perform one or more tasks that are relevant to the topic that has been discussed in the previous conversation more than the predetermined number of times; providing, to a device associated with the user, a suggestion to add the second virtual assistant to a group of virtual assistants that are associated with the account of the user, the group of virtual assistants being configured with different personas; receiving user input indicating a selection of the second virtual assistant to be added to the group of virtual assistants; and based at least in part on the user input, adding, by the computing device, the second virtual assistant to the group of virtual assistants by associating the second virtual assistant with the account of the user.
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1. A method comprising: analyzing, by a computing device, a previous conversation with a first virtual assistant to identify a topic that has been discussed in the previous conversation more than a predetermined number of times; identifying a second virtual assistant that is not currently associated with an account of a user and that is configured to perform one or more tasks that are relevant to the topic that has been discussed in the previous conversation more than the predetermined number of times; providing, to a device associated with the user, a suggestion to add the second virtual assistant to a group of virtual assistants that are associated with the account of the user, the group of virtual assistants being configured with different personas; receiving user input indicating a selection of the second virtual assistant to be added to the group of virtual assistants; and based at least in part on the user input, adding, by the computing device, the second virtual assistant to the group of virtual assistants by associating the second virtual assistant with the account of the user. 3. The method of claim 1 , further comprising: updating an existing group of virtual assistants to include a third virtual assistant, the existing group of virtual assistants being associated with at least one of the user or the device associated with the user.
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4. The task manager of claim 1 wherein at least one of the events comprises a current vehicle location satisfying a specified vehicle location.
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4. The task manager of claim 1 wherein at least one of the events comprises a current vehicle location satisfying a specified vehicle location. 5. The task manager of claim 4 wherein the computer is further configured to determine whether a current vehicle location satisfies the specified vehicle location.
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1. A computer-implemented system for creating one or more multi-relational ontologies having a predetermined structure, the system comprising: at least one processor and a memory having instructions causing the processor to: (i) create an upper ontology that includes: a set of predetermined concept types, a set of predetermined relationship types, a set of concept type pairs, and for each concept type pair, a set of relationships permitted to be used to connect the concept types of the concept type pair; (ii) receive raw data and arrange the raw data into a plurality of individual assertions according to the upper ontology, each assertion comprising a first concept, a second concept, and a relationship between the first and second concept, wherein the first and second concept of each assertion have a concept type from the set of predetermined concept types, wherein the relationship of each assertion has a relationship type from the set of predetermined relationship types, wherein the first and second concept of each assertion belong to a concept type pair of the set of concept type pairs and are connected by a relationship from the set of possible relationships permitted for the concept type pair, wherein at least one concept within the plurality of assertions is part of more than one assertion, wherein one or more relationships in the plurality of individual assertions comprise relationships unconstrained by any hierarchical arrangement of concepts, wherein each concept within each assertion of the plurality of individual assertions is associated with a label, a concept type, and at least one property, and wherein the at least one property includes at least a version of a data source from which the concept was derived; and (iii) store on at least one data storage device: the plurality of individual assertions as one or more multi-relational ontologies, and one or more pieces of evidence supporting information contained in each assertion of the plurality of assertions, wherein each of the one or more pieces of evidence are linked to their corresponding assertion such that each of the one or more pieces of evidence are able to be accessed along with their corresponding assertion, and wherein the one or more pieces of evidence are each associated with at least a data source from which the evidence is derived.
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1. A computer-implemented system for creating one or more multi-relational ontologies having a predetermined structure, the system comprising: at least one processor and a memory having instructions causing the processor to: (i) create an upper ontology that includes: a set of predetermined concept types, a set of predetermined relationship types, a set of concept type pairs, and for each concept type pair, a set of relationships permitted to be used to connect the concept types of the concept type pair; (ii) receive raw data and arrange the raw data into a plurality of individual assertions according to the upper ontology, each assertion comprising a first concept, a second concept, and a relationship between the first and second concept, wherein the first and second concept of each assertion have a concept type from the set of predetermined concept types, wherein the relationship of each assertion has a relationship type from the set of predetermined relationship types, wherein the first and second concept of each assertion belong to a concept type pair of the set of concept type pairs and are connected by a relationship from the set of possible relationships permitted for the concept type pair, wherein at least one concept within the plurality of assertions is part of more than one assertion, wherein one or more relationships in the plurality of individual assertions comprise relationships unconstrained by any hierarchical arrangement of concepts, wherein each concept within each assertion of the plurality of individual assertions is associated with a label, a concept type, and at least one property, and wherein the at least one property includes at least a version of a data source from which the concept was derived; and (iii) store on at least one data storage device: the plurality of individual assertions as one or more multi-relational ontologies, and one or more pieces of evidence supporting information contained in each assertion of the plurality of assertions, wherein each of the one or more pieces of evidence are linked to their corresponding assertion such that each of the one or more pieces of evidence are able to be accessed along with their corresponding assertion, and wherein the one or more pieces of evidence are each associated with at least a data source from which the evidence is derived. 7. The system of claim 1 , wherein at least one concept from the plurality of individual assertions is associated with one or more synonyms.
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23. A computer-implemented method for parsing and exporting data from one or more multi-relational ontologies, the method comprising: selecting two or more concepts from one or more master multi-relational ontologies, wherein the one or more master ontologies include a plurality of individual assertions, wherein an individual assertion comprises a first concept, a second concept, and a relationship between the first concept and the second concept, wherein at least one concept in a first assertion of the plurality of individual assertions is a concept in at least a second assertion of the plurality of individual assertions, wherein one or more relationships in the plurality of individual assertions comprise relationships unconstrained by any hierarchical arrangement of concepts, and wherein each of the individual assertions of the one or more master multi-relational ontologies is associated with a confidence weight that is an indication of the confidence in the truth of the assertion; applying one or more path-finding constraints to the two or more concepts to produce a subset of individual assertions from the plurality of individual assertions of the one or more master multi-relational ontologies, wherein the path finding constraints identify one or more individual assertions from the plurality of individual assertions of the one or more master multi-relational ontologies that connect, directly or indirectly, the two or more concepts; and selecting a starting concept from the subset of individual assertions; applying one or more expansion parameters to the starting concept to yield a redacted subset of individual assertions from the subset of individual assertions, wherein the one or more expansion parameters include one or more selectable characteristics of the subset of individual assertions, and wherein the redacted subset of individual assertions includes at least one assertion that includes the starting concept; outputting the redacted subset of individual assertions to a predetermined location in a predetermined format.
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23. A computer-implemented method for parsing and exporting data from one or more multi-relational ontologies, the method comprising: selecting two or more concepts from one or more master multi-relational ontologies, wherein the one or more master ontologies include a plurality of individual assertions, wherein an individual assertion comprises a first concept, a second concept, and a relationship between the first concept and the second concept, wherein at least one concept in a first assertion of the plurality of individual assertions is a concept in at least a second assertion of the plurality of individual assertions, wherein one or more relationships in the plurality of individual assertions comprise relationships unconstrained by any hierarchical arrangement of concepts, and wherein each of the individual assertions of the one or more master multi-relational ontologies is associated with a confidence weight that is an indication of the confidence in the truth of the assertion; applying one or more path-finding constraints to the two or more concepts to produce a subset of individual assertions from the plurality of individual assertions of the one or more master multi-relational ontologies, wherein the path finding constraints identify one or more individual assertions from the plurality of individual assertions of the one or more master multi-relational ontologies that connect, directly or indirectly, the two or more concepts; and selecting a starting concept from the subset of individual assertions; applying one or more expansion parameters to the starting concept to yield a redacted subset of individual assertions from the subset of individual assertions, wherein the one or more expansion parameters include one or more selectable characteristics of the subset of individual assertions, and wherein the redacted subset of individual assertions includes at least one assertion that includes the starting concept; outputting the redacted subset of individual assertions to a predetermined location in a predetermined format. 40. The method of claim 23 , wherein outputting the redacted subset of individual assertions further comprises outputting the redacted subset of individual assertions to one or more computer applications.
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1. An attribute extraction method of extracting an attribute name and an attribute value associated with an input word inputted by a user from documents by a computer, wherein the computer: extracts a document including the input word inputted by the user from the pre-stored documents; delimits said extracted document into strings or images based upon a predetermined rule, and calculates a drawing position of each of said delimited strings or images; extracts a group of the strings or images of which said calculated drawing positions are arranged in one direction as an attribute group; calculates an attribute name score indicative of an extent to which said attribute group is an aggregation of attribute names based upon a statistical index employing the appearance number of each word in all of the attribute groups that is obtained from said delimited strings or images of said attribute group, and selects an attribute name group from said attribute group based upon said attribute name score; selects, from said extracted attribute group, the attribute group in which the strings or images identical to said delimited strings or images of said attribute name group are contained, and the drawing position of the above identical string or image is identical to that of said attribute name group; extracts an attribute name from the strings or image of which the drawing position is identical between said attribute name group and said selected attribute group; and extracts an attribute value corresponding to said extracted attribute name from the strings or images of said selected attribute group except for the string or image corresponding to said extracted attribute name.
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1. An attribute extraction method of extracting an attribute name and an attribute value associated with an input word inputted by a user from documents by a computer, wherein the computer: extracts a document including the input word inputted by the user from the pre-stored documents; delimits said extracted document into strings or images based upon a predetermined rule, and calculates a drawing position of each of said delimited strings or images; extracts a group of the strings or images of which said calculated drawing positions are arranged in one direction as an attribute group; calculates an attribute name score indicative of an extent to which said attribute group is an aggregation of attribute names based upon a statistical index employing the appearance number of each word in all of the attribute groups that is obtained from said delimited strings or images of said attribute group, and selects an attribute name group from said attribute group based upon said attribute name score; selects, from said extracted attribute group, the attribute group in which the strings or images identical to said delimited strings or images of said attribute name group are contained, and the drawing position of the above identical string or image is identical to that of said attribute name group; extracts an attribute name from the strings or image of which the drawing position is identical between said attribute name group and said selected attribute group; and extracts an attribute value corresponding to said extracted attribute name from the strings or images of said selected attribute group except for the string or image corresponding to said extracted attribute name. 3. The attribute extraction method according to claim 1 , wherein the computer selects the attribute group having said attribute name score larger than a predetermined threshold as an attribute name group.
| 0.893375 |
11. A system for displaying an n-dimensional textual data set as a word cloud comprising one electronic device, or a set of two or more electronic devices linked by a network, coupled to a display and to data entry means including manual data entry means, each electronic device having a memory, and a processor, said processors together or singly operable to execute instructions to perform functions comprising: a Processing Component configured to: generate a textual data set whose members comprise a set of words, each of which is associated with an n-dimensional vector populated by n numerical values, said vectors defining an n-dimensional data space; calculate a size attribute for each word in said textual data set; create an initial two-dimensional subspace of the n-dimensional data space; calculate the projection of each said n-dimensional vector onto said subspace; and derive a new subspace and vector projections thereon given a user-selected vector in said n-dimensional vector space and a variable representing change in position within a display space; a Display Component configured to display word clouds in a display space with a two dimensional coordinate system, and specifically to perform steps comprising displaying a word cloud given a set of n-dimensional vectors with calculated projections and corresponding words with calculated size attributes by: placing each word at coordinates determined by its vector's projection; and displaying said word with a font size corresponding to its size attribute; a Data Entry Component configured to capture data entered by the user via said data entry means, and particularly to: capture a selection of a word displayed in said word cloud by a user via said manual data entry means, and record the selection of that word's corresponding n-dimensional vector; capture a user motion input by: selecting a frame rate for animating the movement corresponding to said user's motion input; for each frame, calculating the change in position corresponding to the portion of said user's motion input that occurred during said frame; and repeating for each frame until the cessation of said motion input; and identifying the cessation of the motion input; a Data Storage Component configured to store said textual data set in said memory so as to preserve each word's relationship with its associated vector; store said subspace in said memory; and store each vector's projection in said memory.
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11. A system for displaying an n-dimensional textual data set as a word cloud comprising one electronic device, or a set of two or more electronic devices linked by a network, coupled to a display and to data entry means including manual data entry means, each electronic device having a memory, and a processor, said processors together or singly operable to execute instructions to perform functions comprising: a Processing Component configured to: generate a textual data set whose members comprise a set of words, each of which is associated with an n-dimensional vector populated by n numerical values, said vectors defining an n-dimensional data space; calculate a size attribute for each word in said textual data set; create an initial two-dimensional subspace of the n-dimensional data space; calculate the projection of each said n-dimensional vector onto said subspace; and derive a new subspace and vector projections thereon given a user-selected vector in said n-dimensional vector space and a variable representing change in position within a display space; a Display Component configured to display word clouds in a display space with a two dimensional coordinate system, and specifically to perform steps comprising displaying a word cloud given a set of n-dimensional vectors with calculated projections and corresponding words with calculated size attributes by: placing each word at coordinates determined by its vector's projection; and displaying said word with a font size corresponding to its size attribute; a Data Entry Component configured to capture data entered by the user via said data entry means, and particularly to: capture a selection of a word displayed in said word cloud by a user via said manual data entry means, and record the selection of that word's corresponding n-dimensional vector; capture a user motion input by: selecting a frame rate for animating the movement corresponding to said user's motion input; for each frame, calculating the change in position corresponding to the portion of said user's motion input that occurred during said frame; and repeating for each frame until the cessation of said motion input; and identifying the cessation of the motion input; a Data Storage Component configured to store said textual data set in said memory so as to preserve each word's relationship with its associated vector; store said subspace in said memory; and store each vector's projection in said memory. 17. A system according to claim 11 , wherein said Processing Component is configured to calculate a metric for degree of relatedness between two words and wherein said Display Component is configured to display said selected word in a color that contrasts with the default display color and to display all other words with coloration indicating the degree of relatedness between each word and the selected word.
| 0.523536 |
9. A computer system comprising: a processor for executing instructions; a computer readable medium with said instructions stored thereon, wherein said instructions implement; a market-characteristic-based-on-historical-auctions-selector configured for selecting characteristics of said market based at least in part on stored historical bids data that includes data for historical auctions performed in the past for a plurality of bidders; a relevant-bidding-model-selector-based-on-privately-held-bidder-information-and-based-on-segments-of-past-auctions configured for selecting a relevant bidding model that specifies past bidding behavior as a function of information held privately by a bidder, that is determined based at least in part on said past auctions data, and said characteristics of said market based on segments of said past auctions related to a specified item; an estimated-structure-of-market-selector configured for selecting at least a first and a second estimated structure of said market, wherein said first estimated structure of said market describes at least a first factor that affects how bidders behave and wherein said second estimated structure of said market describes at least a second factor that affects how bidders behave; a bidding-behavior-based-on-estimated-market-structure-predictor configured for predicting a first bidding behavior utilizing said first estimated structure of said market, said characteristics of said market and said relevant bidding model; a market-outcome-based-on-bidding-behavior-predictor configured for predicting a first outcome of said market based on said first bidding behavior; said bidding-behavior-based-on-estimated-market-structure-predictor configured for predicting at least a second bidding behavior utilizing at least said second estimated structure of said market, said characteristics of said market and said relevant bidding model; said market-outcome-based-on-bidding-behavior-predictor configured for predicting a second outcome of said market based on at least said second bidding behavior prediction; and a determiner-of-auction-format-based-on-evaluating-market-outcome configured for determining an auction format by evaluating said first outcome of said market and at least said second outcome of said market.
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9. A computer system comprising: a processor for executing instructions; a computer readable medium with said instructions stored thereon, wherein said instructions implement; a market-characteristic-based-on-historical-auctions-selector configured for selecting characteristics of said market based at least in part on stored historical bids data that includes data for historical auctions performed in the past for a plurality of bidders; a relevant-bidding-model-selector-based-on-privately-held-bidder-information-and-based-on-segments-of-past-auctions configured for selecting a relevant bidding model that specifies past bidding behavior as a function of information held privately by a bidder, that is determined based at least in part on said past auctions data, and said characteristics of said market based on segments of said past auctions related to a specified item; an estimated-structure-of-market-selector configured for selecting at least a first and a second estimated structure of said market, wherein said first estimated structure of said market describes at least a first factor that affects how bidders behave and wherein said second estimated structure of said market describes at least a second factor that affects how bidders behave; a bidding-behavior-based-on-estimated-market-structure-predictor configured for predicting a first bidding behavior utilizing said first estimated structure of said market, said characteristics of said market and said relevant bidding model; a market-outcome-based-on-bidding-behavior-predictor configured for predicting a first outcome of said market based on said first bidding behavior; said bidding-behavior-based-on-estimated-market-structure-predictor configured for predicting at least a second bidding behavior utilizing at least said second estimated structure of said market, said characteristics of said market and said relevant bidding model; said market-outcome-based-on-bidding-behavior-predictor configured for predicting a second outcome of said market based on at least said second bidding behavior prediction; and a determiner-of-auction-format-based-on-evaluating-market-outcome configured for determining an auction format by evaluating said first outcome of said market and at least said second outcome of said market. 12. The system as recited in claim 9 , wherein said estimated-structure-of-market-selector is further configured for: receiving said relevant bidding model; receiving said historical bids data; expressing unobservable variables in terms of observable bids, wherein said unobservable variables are expressed in terms of said observable bids by inverting said relevant bidding model; transforming said historical bids data to a sample of inverted bids, wherein said historical bids data are transformed by inverting said relevant bidding model; estimating an estimated latent structure of said market, wherein said sample of inverted bids receives application of statistical density estimation techniques to obtain said estimated latent structure of said market; and outputting said estimated latent structure of said market.
| 0.500414 |
8. A method, comprising: providing, in a user interface, a graphical element that includes an identification of a context in relation to a product or service; in response to receiving a selection of the graphical element in the user interface: processing information from a plurality of users of a network marketplace regarding the product or service to determine attributes relevant to the context, and displaying, in the user interface, a list of the determined attributes; in response to receiving a selection of at least one of the determined attributes: generating result data by retrieving data associated with the context and filtering the retrieved data according to the at least one selected attribute, grouping the result data based on corresponding data types, and providing graphical tabs, in the user interface, for each group of result data, each tab including an identification of the corresponding data type; and in response to receiving a selection of a graphical tab, updating the user interface to display an entry field for entering a new result data of the corresponding data type for which the selected graphical tab is provided.
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8. A method, comprising: providing, in a user interface, a graphical element that includes an identification of a context in relation to a product or service; in response to receiving a selection of the graphical element in the user interface: processing information from a plurality of users of a network marketplace regarding the product or service to determine attributes relevant to the context, and displaying, in the user interface, a list of the determined attributes; in response to receiving a selection of at least one of the determined attributes: generating result data by retrieving data associated with the context and filtering the retrieved data according to the at least one selected attribute, grouping the result data based on corresponding data types, and providing graphical tabs, in the user interface, for each group of result data, each tab including an identification of the corresponding data type; and in response to receiving a selection of a graphical tab, updating the user interface to display an entry field for entering a new result data of the corresponding data type for which the selected graphical tab is provided. 11. The method of claim 8 , wherein the result data types include at least one from a group consisting of: a review list, a recommendation list, research from other users, research from the user, a seller list, and a buyer list.
| 0.76343 |
3. The method of claim 2 , wherein the data received comprises first data, the data generated comprises second data, and wherein the method further comprises: receiving third data indicative of a progression of the dictation; and causing the speech recognition to be performed on the third data, during performance of the dictation correction.
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3. The method of claim 2 , wherein the data received comprises first data, the data generated comprises second data, and wherein the method further comprises: receiving third data indicative of a progression of the dictation; and causing the speech recognition to be performed on the third data, during performance of the dictation correction. 4. The method of claim 3 , further comprising: generating fourth data for replacing, in the graphical user interface, the visual indicator of the recently dictated unit with a visual representation of the third data.
| 0.870607 |
1. A method of training a speech model, comprising: obtaining model parameters for the speech model; processing a known speech input using the speech model with the model parameters to generate a process result; calculating a distance between a true result and the process result, given the model parameters and the known speech input, the true result comprising a true transcription, the true transcription corresponding to only the following waveform states: silence, noise, onset and speech, instead of a phonetic transcription; and modifying the model parameters to reduce the distance between the true result and the process result, to obtain a modified model, wherein reducing the distance between the true result and the process result comprises maximizing a function comprising a parameter set for an acoustic model and a super utterance, the super utterance comprising a feature vector sequence, the true result and the process result.
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1. A method of training a speech model, comprising: obtaining model parameters for the speech model; processing a known speech input using the speech model with the model parameters to generate a process result; calculating a distance between a true result and the process result, given the model parameters and the known speech input, the true result comprising a true transcription, the true transcription corresponding to only the following waveform states: silence, noise, onset and speech, instead of a phonetic transcription; and modifying the model parameters to reduce the distance between the true result and the process result, to obtain a modified model, wherein reducing the distance between the true result and the process result comprises maximizing a function comprising a parameter set for an acoustic model and a super utterance, the super utterance comprising a feature vector sequence, the true result and the process result. 5. The method of claim 1 wherein the speech model comprises a speech detection model, and wherein processing a known speech input to generate a process result comprises: performing speech detection on acoustic data indicative of an input signal to generate a detection state output indicative of a decision made by the speech detection model as to whether the input signal represents speech or non-speech.
| 0.722345 |
37. A system for activating a font, comprising: an input for receiving input data requesting activation of a font; and a processor system programmed and adapted to: (a) determine that the font does not exist in a font management vault, (b) upon determining that the font does not exist in the font management vault: (i) identify the font in one multi-font suitcase file of a plurality of multi-font suitcase files, each multi-font suitcase file of the plurality including a similarly named version of the font, (ii) separate the font from the multi-font suitcase file, and (iii) save the separated font in the font management vault, and (c) activate the font from the font management vault.
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37. A system for activating a font, comprising: an input for receiving input data requesting activation of a font; and a processor system programmed and adapted to: (a) determine that the font does not exist in a font management vault, (b) upon determining that the font does not exist in the font management vault: (i) identify the font in one multi-font suitcase file of a plurality of multi-font suitcase files, each multi-font suitcase file of the plurality including a similarly named version of the font, (ii) separate the font from the multi-font suitcase file, and (iii) save the separated font in the font management vault, and (c) activate the font from the font management vault. 47. A system according to claim 37 , wherein the input data requesting activation of the font is generated when an application program is opened.
| 0.859363 |
6. A system for utilizing a plurality of recognizers to process an utterance based on a markup language document, the system comprising a client computing device, the client computing device comprising: a memory for storing executable program code; and a processor, functionally coupled to the memory, the processor being responsive to computer-executable instructions contained in the program code and operative: to receive the markup language document; to receive the utterance; to select at least one of the plurality of recognizers for returning a results set for the utterance based on markup language in the markup language document, the at least one of the plurality of recognizers for returning the results set for the utterance being selected based on markup language in the markup language document, the selection based on the markup language comprising: recognizing a grammar used in the utterance; parsing the markup language document for at least one markup language tag identifying at least one of the plurality of recognizers for returning the results set for the utterance based on the grammar; and selecting, by an event handler, the at least one of the plurality of recognizers identified by the at least one markup language tag, the selected at least one of the plurality of recognizers comprising a local recognizer embedded on a client computing device, when the grammar includes data stored on the client computing device, the selected at least one of the plurality of recognizers comprising a network recognizer on a network server, when the grammar includes data which is retrieved via a query from the network server to a remote search engine; to receive the results set from the selected at least one of the plurality of recognizers in a format determined by a processing method specified in the markup language document; and to execute an event in response to receiving the results set, the event comprising determining actions in response to receiving the results set, the actions being based on at least an assigned confidence score indicating an accuracy of a speech recognition for the utterance, the actions comprising ignoring the results set when the results sets comprises unprocessed results for the utterance and the confidence score is below a predetermined threshold, the actions further comprising preventing the results set from being displayed to a user.
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6. A system for utilizing a plurality of recognizers to process an utterance based on a markup language document, the system comprising a client computing device, the client computing device comprising: a memory for storing executable program code; and a processor, functionally coupled to the memory, the processor being responsive to computer-executable instructions contained in the program code and operative: to receive the markup language document; to receive the utterance; to select at least one of the plurality of recognizers for returning a results set for the utterance based on markup language in the markup language document, the at least one of the plurality of recognizers for returning the results set for the utterance being selected based on markup language in the markup language document, the selection based on the markup language comprising: recognizing a grammar used in the utterance; parsing the markup language document for at least one markup language tag identifying at least one of the plurality of recognizers for returning the results set for the utterance based on the grammar; and selecting, by an event handler, the at least one of the plurality of recognizers identified by the at least one markup language tag, the selected at least one of the plurality of recognizers comprising a local recognizer embedded on a client computing device, when the grammar includes data stored on the client computing device, the selected at least one of the plurality of recognizers comprising a network recognizer on a network server, when the grammar includes data which is retrieved via a query from the network server to a remote search engine; to receive the results set from the selected at least one of the plurality of recognizers in a format determined by a processing method specified in the markup language document; and to execute an event in response to receiving the results set, the event comprising determining actions in response to receiving the results set, the actions being based on at least an assigned confidence score indicating an accuracy of a speech recognition for the utterance, the actions comprising ignoring the results set when the results sets comprises unprocessed results for the utterance and the confidence score is below a predetermined threshold, the actions further comprising preventing the results set from being displayed to a user. 7. The system of claim 6 , wherein the processor is further operative to: determine whether an updated version is available for at least one of the plurality of recognizers; and if an updated version is available for the at least one of the plurality of recognizers, then receive an updated markup language document comprising additional markup language for handling newly added features in the updated version.
| 0.67041 |
1. A computer-readable storage medium, with instructions stored thereon, which when executed by at least one processor of a computing device, cause the computing device to: within an Internet browsing application, present a search box adjacent to a last of at least one tab header in a tabbed area of the Internet browsing application, the tabbed area defined as an area of the Internet browsing application where tab headers are displayed, the search box displayed within the tabbed area but outside of any tab and outside of any tab header of any tab, the search box to receive text input of a search query to be submitted against at least one search engine, add at least one tracking code, associated with at least one of a user and the Internet browsing application, to the search query submitted to each respective search engine of the at least one search engine, the Internet browsing application including an address bar, the tabbed area including at least one tab header that can be selected to view a browsing area associated with the selected tab, the browsing area of each tab to provide a view of content retrieved by the Internet browsing application, at least a portion of the content retrieved from a location identified in the address bar; upon addition of a new tab header to the tabbed area: identify a new area within the tabbed area to present the search box, the new area adjacent to a last tab header presented in the tabbed area; remove the presented search box; and redraw the search box in the identified new area to present the search box.
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1. A computer-readable storage medium, with instructions stored thereon, which when executed by at least one processor of a computing device, cause the computing device to: within an Internet browsing application, present a search box adjacent to a last of at least one tab header in a tabbed area of the Internet browsing application, the tabbed area defined as an area of the Internet browsing application where tab headers are displayed, the search box displayed within the tabbed area but outside of any tab and outside of any tab header of any tab, the search box to receive text input of a search query to be submitted against at least one search engine, add at least one tracking code, associated with at least one of a user and the Internet browsing application, to the search query submitted to each respective search engine of the at least one search engine, the Internet browsing application including an address bar, the tabbed area including at least one tab header that can be selected to view a browsing area associated with the selected tab, the browsing area of each tab to provide a view of content retrieved by the Internet browsing application, at least a portion of the content retrieved from a location identified in the address bar; upon addition of a new tab header to the tabbed area: identify a new area within the tabbed area to present the search box, the new area adjacent to a last tab header presented in the tabbed area; remove the presented search box; and redraw the search box in the identified new area to present the search box. 6. The computer-readable storage medium of claim 1 , with further instructions stored thereon which when executed by the at least one processor, cause the computing device to: intercept text input into any of the following Internet browser application components: the search box, default search box, address bar, new tab search, and start/home page search; and submit the inputted text to at least one search engine.
| 0.603191 |
7. The system of claim 6 , wherein the new set of data includes data sampled from disparate data sources.
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7. The system of claim 6 , wherein the new set of data includes data sampled from disparate data sources. 8. The system of claim 7 , further comprising a selection component that selects the data that is sampled from the disparate data sources.
| 0.895802 |
4. The system as recited in claim 2, wherein the second processing means includes means for decomposing the two-dimensional matrix into compressed data structures representative of the two-dimensional matrix, with the compressed data structures having information regarding a location and an importance of each element of the two-dimensional matrix, according to a predetermined translation means and with at least the subset of the compressed data structures being enhanced with respect to a remainder of the compressed data structures by modifying the subset of the compressed data structures.
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4. The system as recited in claim 2, wherein the second processing means includes means for decomposing the two-dimensional matrix into compressed data structures representative of the two-dimensional matrix, with the compressed data structures having information regarding a location and an importance of each element of the two-dimensional matrix, according to a predetermined translation means and with at least the subset of the compressed data structures being enhanced with respect to a remainder of the compressed data structures by modifying the subset of the compressed data structures. 8. The system of claim 4, wherein the first processing means converts the input data from a first form to a three-dimensional matrix and converts the three-dimensional matrix to a two-dimensional matrix.
| 0.831699 |
10. A method for identifying potential malware domain names comprising: receiving, at a potential malware domain identification module, a request for network data, wherein the request for network data comprises a domain name; applying a lexical and linguistic analysis to the domain name, wherein the lexical and linguistic analysis comprises machine learning configured to establish at least one classifier for performing and fine-tuning potential malware domain name detection; and identifying whether the domain name is a potential malware domain name based on the lexical and linguistic analysis.
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10. A method for identifying potential malware domain names comprising: receiving, at a potential malware domain identification module, a request for network data, wherein the request for network data comprises a domain name; applying a lexical and linguistic analysis to the domain name, wherein the lexical and linguistic analysis comprises machine learning configured to establish at least one classifier for performing and fine-tuning potential malware domain name detection; and identifying whether the domain name is a potential malware domain name based on the lexical and linguistic analysis. 11. The method of claim 10 , wherein the domain name comprises a Uniform Resource Locator (URL).
| 0.745005 |
15. The one or more memories of claim 14 , the method further comprising: compiling the second version of the formula method to obtain machine code for the second version of the formula method.
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15. The one or more memories of claim 14 , the method further comprising: compiling the second version of the formula method to obtain machine code for the second version of the formula method. 18. The one or more memories of claim 15 , the method further comprising: for each particular database row of the plurality of database rows in a database table: causing the machine code for the second version of the formula method to be executed to determine a value for the distinguished database field of the particular database row based on values of one or more database fields of the particular database row other than the distinguished database field.
| 0.904481 |
19. A computer program product encoded on one or more non-transitory computer readable media, the computer program product comprising instructions that when executed by one or more computers cause the one or more computers to perform operations comprising: sending, to a client, client software that, when executed on the client, causes the client to: receive real-time search results for a first search query and a time token, wherein the time token is data that identifies a most-recent time that any resource identified by any of the received real-time search results was updated, present the real-time search results for the first search query, re-submit the first search query with the time token, obtain additional real-time search results that are more recent than the most-recent time identified by the time token, wherein an additional real-time search result is more recent than the most-recent time identified by the time token when a resource identified by the additional real-time search result was last updated more recently than the most-recent time identified by the time token, and present the additional real-time search results.
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19. A computer program product encoded on one or more non-transitory computer readable media, the computer program product comprising instructions that when executed by one or more computers cause the one or more computers to perform operations comprising: sending, to a client, client software that, when executed on the client, causes the client to: receive real-time search results for a first search query and a time token, wherein the time token is data that identifies a most-recent time that any resource identified by any of the received real-time search results was updated, present the real-time search results for the first search query, re-submit the first search query with the time token, obtain additional real-time search results that are more recent than the most-recent time identified by the time token, wherein an additional real-time search result is more recent than the most-recent time identified by the time token when a resource identified by the additional real-time search result was last updated more recently than the most-recent time identified by the time token, and present the additional real-time search results. 20. The computer program product of claim 19 , the operations further comprising: receiving the first search query from the client; determining that the first search query is a search query for which real-time search results should be returned; and sending to the client a user interface document that contains the client software as a response to the first search query.
| 0.5 |
11. The method as recited in claim 8 , further comprising receiving a user selection of at least one segment of the plurality of segments.
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11. The method as recited in claim 8 , further comprising receiving a user selection of at least one segment of the plurality of segments. 13. The method as recited in claim 11 , further comprising causing presentation of information related to the at least one segment on a display.
| 0.946573 |
7. The method of claim 4, further comprising: continuing a collaboration when the selection is the other, until the selection is the affirmative or the negative; completing the collaboration when the reply option is the affirmative; and aborting the collaboration when the reply option is the negative.
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7. The method of claim 4, further comprising: continuing a collaboration when the selection is the other, until the selection is the affirmative or the negative; completing the collaboration when the reply option is the affirmative; and aborting the collaboration when the reply option is the negative. 12. The method of claim 7 wherein said step of continuing the collaboration comprises continuing a negotiation cycle, the negotiation cycle comprising: receiving the reply with the reply option of the other; displaying the selection of the reply options; generating a new reply, including a new automatic reply content based on the selection; creating a new header; and sending the new reply, using the new header.
| 0.741206 |
1. A method comprising: parsing, by use of a processor, a secure message into lingual units, wherein each lingual unit is a phoneme; generating a validation nonce from the lingual units; generating at least one transform unit for each lingual unit by applying a lingual message transformation to each lingual unit as an encryption function; selecting one of the at least one transform unit for each lingual unit using a selection rule; generating an encrypted message from the selected transform units; parsing the encrypted message into transform units; generating a decrypted lingual unit for each transform unit by applying the lingual message transformation to each transform unit as a decryption function; regenerating at least one decrypted lingual unit from a selected transform unit with two or more corresponding lingual units with an alternate lingual unit if the validation nonce is not satisfied; in response to identifying a modification phrase in the communication data, generating a modification nonce from the communication data; selecting a transformation modification in response to the modification nonce and the lingual message transformation; and modifying one or more of the lingual message transformation and the selection rule in response to the transformation modification.
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1. A method comprising: parsing, by use of a processor, a secure message into lingual units, wherein each lingual unit is a phoneme; generating a validation nonce from the lingual units; generating at least one transform unit for each lingual unit by applying a lingual message transformation to each lingual unit as an encryption function; selecting one of the at least one transform unit for each lingual unit using a selection rule; generating an encrypted message from the selected transform units; parsing the encrypted message into transform units; generating a decrypted lingual unit for each transform unit by applying the lingual message transformation to each transform unit as a decryption function; regenerating at least one decrypted lingual unit from a selected transform unit with two or more corresponding lingual units with an alternate lingual unit if the validation nonce is not satisfied; in response to identifying a modification phrase in the communication data, generating a modification nonce from the communication data; selecting a transformation modification in response to the modification nonce and the lingual message transformation; and modifying one or more of the lingual message transformation and the selection rule in response to the transformation modification. 7. The method of claim 1 , wherein the lingual message transformation modifies a lingual unit order according to grammar modification rules.
| 0.711066 |
10. A method for creating a Kind feature vector, comprising: creating a Kind feature vector for a Kind using a set of initial features and one or more descriptors of a Kind classification characterizing the Kind, the creating comprising: creating one or more dimensions within the Kind feature vector; and for respective dimensions within the Kind feature vector, assigning a probabilistic value to a dimension based upon the probability the Kind relates to a characteristic of the dimension.
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10. A method for creating a Kind feature vector, comprising: creating a Kind feature vector for a Kind using a set of initial features and one or more descriptors of a Kind classification characterizing the Kind, the creating comprising: creating one or more dimensions within the Kind feature vector; and for respective dimensions within the Kind feature vector, assigning a probabilistic value to a dimension based upon the probability the Kind relates to a characteristic of the dimension. 15. The method of claim 10 , comprising: creating a user feature vector for a user based upon one or more Kind feature vectors of Kinds associated with the user.
| 0.680539 |
9. The party kit of claim 8 , wherein the interactive display is a plurality of web pages including at least one of: a home page, a theme page, a party experience page, a party package page, an explanation page and a registration page.
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9. The party kit of claim 8 , wherein the interactive display is a plurality of web pages including at least one of: a home page, a theme page, a party experience page, a party package page, an explanation page and a registration page. 12. The party kit of claim 9 , wherein the party package page is configured to show a list of items included with the party kit.
| 0.881164 |
1. A method of providing content upon request, the method comprising: receiving, from a first user, a configuration for a guide application, the guide application being configured for use by a second user, the second user being different than the first user; receiving, from the first user, authorization for the guide application to return search results for specific content; storing, in a database, searches and content selections of the specific content; receiving, from the second user, a request to open the guide application on a user device; and via the guide application: receiving a search request for items of content, the second user selecting a first selectable graphical icon among a plurality of first selectable graphical icons, and the second user selecting, based on a selection of the first selectable graphical icon, a second selectable graphical icon among a plurality of second selectable graphical icons, the search request for the items of content being received based on a selection of the second selectable graphical icon; recognizing, by a processor of the user device, a pattern of the content selections stored in the database; modifying, by the processor and based on recognition of the pattern, the search request before a search algorithm searches for the items of content to return in response to the search request; determining, based on the search request modified by the processor and from the specific content authorized by the first user, a plurality of listings for content; and converting text describing the plurality of listings to corresponding speech describing the plurality of listings.
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1. A method of providing content upon request, the method comprising: receiving, from a first user, a configuration for a guide application, the guide application being configured for use by a second user, the second user being different than the first user; receiving, from the first user, authorization for the guide application to return search results for specific content; storing, in a database, searches and content selections of the specific content; receiving, from the second user, a request to open the guide application on a user device; and via the guide application: receiving a search request for items of content, the second user selecting a first selectable graphical icon among a plurality of first selectable graphical icons, and the second user selecting, based on a selection of the first selectable graphical icon, a second selectable graphical icon among a plurality of second selectable graphical icons, the search request for the items of content being received based on a selection of the second selectable graphical icon; recognizing, by a processor of the user device, a pattern of the content selections stored in the database; modifying, by the processor and based on recognition of the pattern, the search request before a search algorithm searches for the items of content to return in response to the search request; determining, based on the search request modified by the processor and from the specific content authorized by the first user, a plurality of listings for content; and converting text describing the plurality of listings to corresponding speech describing the plurality of listings. 17. The method of claim 1 , wherein the guide application used to accept the search request is downloaded to the user device from an online store.
| 0.552083 |
1. A computer-implemented method for handling queries, comprising: storing associations that indicate how to modify user-submitted queries that are to be sent to a plurality of searchable sources; wherein the associations include a first association between a first modification, one or more keywords, and a first searchable source; wherein the associations include a second association between a second modification, the one or more keywords, and a second searchable source; after storing the associations that indicate how to modify user-submitted queries, receiving a user-submitted query, comprising the one or more keywords, to be sent to the plurality of searchable sources; in response to receiving the user-submitted query, performing the steps of: generating a first modified query to be sent to the first searchable source of the plurality of searchable sources; wherein the first modified query is generated by adding a first additional text to the user-submitted query based on existence of the one or more keywords in the user-submitted query and the first association; generating a second modified query to be sent to the second searchable source of the plurality of searchable sources; wherein the second modified query is generated by adding a second additional text to the user-submitted query based on existence of the one or more keywords in the user-submitted query and the second association; wherein the first association is different than the second association; wherein the first modification is different than the second modification; wherein the first searchable source is separate from the second searchable source; and wherein the method is performed by one or more computing devices.
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1. A computer-implemented method for handling queries, comprising: storing associations that indicate how to modify user-submitted queries that are to be sent to a plurality of searchable sources; wherein the associations include a first association between a first modification, one or more keywords, and a first searchable source; wherein the associations include a second association between a second modification, the one or more keywords, and a second searchable source; after storing the associations that indicate how to modify user-submitted queries, receiving a user-submitted query, comprising the one or more keywords, to be sent to the plurality of searchable sources; in response to receiving the user-submitted query, performing the steps of: generating a first modified query to be sent to the first searchable source of the plurality of searchable sources; wherein the first modified query is generated by adding a first additional text to the user-submitted query based on existence of the one or more keywords in the user-submitted query and the first association; generating a second modified query to be sent to the second searchable source of the plurality of searchable sources; wherein the second modified query is generated by adding a second additional text to the user-submitted query based on existence of the one or more keywords in the user-submitted query and the second association; wherein the first association is different than the second association; wherein the first modification is different than the second modification; wherein the first searchable source is separate from the second searchable source; and wherein the method is performed by one or more computing devices. 16. The method of claim 1 , further comprising: deleting one or more searchable sources from the plurality of searchable sources in response to a user's selection of the one or more searchable sources from the plurality of searchable sources; wherein said deleting of said one or more searchable sources causes said one or more searchable sources to be excluded from a search conducted in response to receipt of said user-submitted query.
| 0.62988 |
15. A method comprising: selecting a recursive transition network top level dialog flow controller to yield a selected recursive transition network top level flow controller; incorporating a context shift component; selecting available reusable subdialogs for being invoked by the selected recursive transition network top level flow controller to yield selected reusable subdialogs; and testing and deploying a spoken dialog service using the recursive transition network top level flow controller and selected reusable subdialogs, wherein when a user of the spoken dialog service changes a context of a spoken dialog while in a reusable subdialog, to yield a context shift, wherein the context shift causes a parent dialog of a subdialog to be set to a state described by the context shift.
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15. A method comprising: selecting a recursive transition network top level dialog flow controller to yield a selected recursive transition network top level flow controller; incorporating a context shift component; selecting available reusable subdialogs for being invoked by the selected recursive transition network top level flow controller to yield selected reusable subdialogs; and testing and deploying a spoken dialog service using the recursive transition network top level flow controller and selected reusable subdialogs, wherein when a user of the spoken dialog service changes a context of a spoken dialog while in a reusable subdialog, to yield a context shift, wherein the context shift causes a parent dialog of a subdialog to be set to a state described by the context shift. 20. The method of claim 15 , wherein the application dependencies are part of the selected recursive transition network top level flow controller.
| 0.531938 |
8. A system comprising: a processor; and a computer-readable storage medium having instructions stored which, when executed by the processor, cause the processor to perform operations comprising: receiving, at a network-based system configured to generate acoustic models and language models, inputs from a remote client via an application program interface, the inputs comprising: a feature stream of features extracted from speech processed by the remote client using a feature extraction algorithm which operates independent of the network-based system; and a transcription of the speech; generating an acoustic model according to an acoustic feature identified within the feature stream from the features extracted from the speech; generating a language model according to the transcription; and transmitting the acoustic model and the language model to the remote client.
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8. A system comprising: a processor; and a computer-readable storage medium having instructions stored which, when executed by the processor, cause the processor to perform operations comprising: receiving, at a network-based system configured to generate acoustic models and language models, inputs from a remote client via an application program interface, the inputs comprising: a feature stream of features extracted from speech processed by the remote client using a feature extraction algorithm which operates independent of the network-based system; and a transcription of the speech; generating an acoustic model according to an acoustic feature identified within the feature stream from the features extracted from the speech; generating a language model according to the transcription; and transmitting the acoustic model and the language model to the remote client. 10. The system of claim 8 , wherein the acoustic model and the language model are transmitted via a secured connection.
| 0.598075 |
17. An input system for a pictographic language, the system comprising: a touchscreen display; and a display controller programmed to display a first arrangement of pictographic characters on the touchscreen display, the first arrangement comprising a plurality of characters of the pictographic language, wherein the first arrangement comprises a plurality of discrete regions, each of the regions displaying a respective one of groups of characters selected from the plurality of characters, wherein the display controller is programmed to receive selection of one of the regions by receiving a touch on the selected region of the touchscreen display, and to receive selection of a character in the selected region after receiving the selection of the region, and wherein the regions are arranged at positions corresponding to positions of keys of a standard Roman character keyboard, such that the first phonetic sounds of the characters of the regions substantially correspond to the phonetic sounds of characters on the keys of the standard Roman character keyboard.
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17. An input system for a pictographic language, the system comprising: a touchscreen display; and a display controller programmed to display a first arrangement of pictographic characters on the touchscreen display, the first arrangement comprising a plurality of characters of the pictographic language, wherein the first arrangement comprises a plurality of discrete regions, each of the regions displaying a respective one of groups of characters selected from the plurality of characters, wherein the display controller is programmed to receive selection of one of the regions by receiving a touch on the selected region of the touchscreen display, and to receive selection of a character in the selected region after receiving the selection of the region, and wherein the regions are arranged at positions corresponding to positions of keys of a standard Roman character keyboard, such that the first phonetic sounds of the characters of the regions substantially correspond to the phonetic sounds of characters on the keys of the standard Roman character keyboard. 37. The system of claim 17 , further comprising a stylus pad programmed to recognize strokes provided to the stylus pad.
| 0.605114 |
14. The computer program product as recited in claim 13 , wherein if only one of said one or more of said plurality of language independent keys is identified, then said one of said one or more of said plurality of language independent keys is a unique language independent key.
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14. The computer program product as recited in claim 13 , wherein if only one of said one or more of said plurality of language independent keys is identified, then said one of said one or more of said plurality of language independent keys is a unique language independent key. 15. The computer program product as recited in claim 14 further comprising the programming step of: inserting said unique language independent key in a test script to allow said test script to execute in multiple locales.
| 0.901384 |
11. The method of claim 7 , wherein the selected question comprises: a question and a plurality of response options associated with the question.
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11. The method of claim 7 , wherein the selected question comprises: a question and a plurality of response options associated with the question. 12. The method of claim 11 , wherein the plurality of responses are selected based on one or more of affinity of the user for a response option and a probability of the user selecting the response option.
| 0.934959 |
14. A server for processing an application search query, the server comprising: a storage device that stores: a plurality of application representations, each application representation being a data structure representing a different application and including one or more features of the application, the features of the application being extracted from one or more documents obtained from one or more respective sources, each document relating to the application; and a search index that indexes the plurality of application representations, each application representation representing a different application and including one or more features of the application; a processing device that executes computer-readable instructions, the computer-executable instructions causing the processing device to: receive a search query from a partner device; determine a set of subqueries based on the search query; extract query features of the search query from the search query; determine an initial result set of application representations based on the set of subqueries and the search index, the initial result set including a set of one or more application representations from the plurality of application representations; determine a score for each application representation in the initial result set of application representations based on the set of query features and one or more machine-learned scoring models; determine a ranked result set based on the scores for the application representations of the initial result set, the ranked result set indicating one or more applications that correspond to the search query; and provide the ranked result set to the partner.
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14. A server for processing an application search query, the server comprising: a storage device that stores: a plurality of application representations, each application representation being a data structure representing a different application and including one or more features of the application, the features of the application being extracted from one or more documents obtained from one or more respective sources, each document relating to the application; and a search index that indexes the plurality of application representations, each application representation representing a different application and including one or more features of the application; a processing device that executes computer-readable instructions, the computer-executable instructions causing the processing device to: receive a search query from a partner device; determine a set of subqueries based on the search query; extract query features of the search query from the search query; determine an initial result set of application representations based on the set of subqueries and the search index, the initial result set including a set of one or more application representations from the plurality of application representations; determine a score for each application representation in the initial result set of application representations based on the set of query features and one or more machine-learned scoring models; determine a ranked result set based on the scores for the application representations of the initial result set, the ranked result set indicating one or more applications that correspond to the search query; and provide the ranked result set to the partner. 15. The server of claim 14 , wherein determining the initial result set includes: obtaining a pre-consideration set of application representations from the search index based on the set of subqueries, wherein the set of one or more application representations is a subset of the pre-consideration set; and deriving the initial result set from the pre-consideration set based on the query features of the search query.
| 0.647059 |
2. A method for creating a semantic object to represent a target referent of an object type, the semantic object being stored on a computer readable medium, the method, comprising, creating the semantic object of a semantic object type to represent the target referent of the object type, the semantic object having multiple meta-tags that are each associable with metadata; wherein, the semantic object of the semantic object type is suitable to represent the object type of the target referent; associating a meta-tag of the multiple meta-tags with the metadata; wherein the meta-tag or the metadata is definable using an ontology; and extracting a portion of the content from the target referent for inclusion in the semantic object; subsequently determining that the target referent has been revised, updating metadata associated with one or more meta-taps of the multiple meta-taps of the semantic object based on the revision; wherein the extraction is part of a data mining performed on selected resources including the ontology or the Internet. sharing, with another user, the semantic object having included therein the portion of the content extracted from the target referent.
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2. A method for creating a semantic object to represent a target referent of an object type, the semantic object being stored on a computer readable medium, the method, comprising, creating the semantic object of a semantic object type to represent the target referent of the object type, the semantic object having multiple meta-tags that are each associable with metadata; wherein, the semantic object of the semantic object type is suitable to represent the object type of the target referent; associating a meta-tag of the multiple meta-tags with the metadata; wherein the meta-tag or the metadata is definable using an ontology; and extracting a portion of the content from the target referent for inclusion in the semantic object; subsequently determining that the target referent has been revised, updating metadata associated with one or more meta-taps of the multiple meta-taps of the semantic object based on the revision; wherein the extraction is part of a data mining performed on selected resources including the ontology or the Internet. sharing, with another user, the semantic object having included therein the portion of the content extracted from the target referent. 21. The method of claim 2 , further comprising, creating the semantic object in response to, receiving an automatic trigger.
| 0.628022 |
1. A method for recommending content items, the method comprising: determining a plurality of accessed content items associated with a user, wherein each of the plurality of accessed content items is associated with a plurality of topics; generating a user interest model of interactions between the plurality of topics and the plurality of accessed content items, wherein the user interest model (i) determines a plurality of related topics associated with the plurality of topics from the plurality of accessed content items, (ii) generates user interest information associated with the user using at least a portion of the plurality of related topics, (iii) determines similarities between the user interest information associated with the user and user interest information of other users including the at least a portion of the plurality of related topics associated with the user, and (iv) determines a conjunction of between the similarities and the plurality of accessed content items; applying the model to determine, for a plurality of content items, a probability that the user selects a content item from the plurality of content items for presentation; ranking the plurality of content items based on the determined probabilities; and selecting at least one of the plurality of content items to recommend to the user based on the ranked plurality of content items.
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1. A method for recommending content items, the method comprising: determining a plurality of accessed content items associated with a user, wherein each of the plurality of accessed content items is associated with a plurality of topics; generating a user interest model of interactions between the plurality of topics and the plurality of accessed content items, wherein the user interest model (i) determines a plurality of related topics associated with the plurality of topics from the plurality of accessed content items, (ii) generates user interest information associated with the user using at least a portion of the plurality of related topics, (iii) determines similarities between the user interest information associated with the user and user interest information of other users including the at least a portion of the plurality of related topics associated with the user, and (iv) determines a conjunction of between the similarities and the plurality of accessed content items; applying the model to determine, for a plurality of content items, a probability that the user selects a content item from the plurality of content items for presentation; ranking the plurality of content items based on the determined probabilities; and selecting at least one of the plurality of content items to recommend to the user based on the ranked plurality of content items. 6. The method of claim 1 , wherein generating the model of user interests further comprises: generating a decision tree, wherein a portion of the decision tree identifies which of the user interest information of other users is similar to the user interest information of the user; determining a subset of the plurality of topics based on the decision tree; and determining a conjunction that models interaction between the subset of the plurality of topics and the plurality of content items.
| 0.70133 |
1. A method, comprising the steps of: A) receiving, by a server computer communicatively coupled to a network, a geographic location data identifying a plurality of place names, wherein the geographic location data comprises a geographic location within a geographic area, the geographic area comprises a planet, a continent, a country, a state, a region, a county, a city, an area, or a neighborhood, the geographic location comprises a continent, a country, a state, a region, a county, a city, an area, a neighborhood, a residence or a business within the geographic area and identified as local to the geographic location data, the geographic location data comprises a geographic location selection comprising a text string received from an online map software, or a geographic location received from, and displayed and selected within, a geographic area of a map rendered by the online map software, and the map software is configured to render a map of the geographic location within the geographic area, and zoom to a different geographic area comprising at least one geographic location; B) parsing, by the server computer, each place name in the plurality of place names into at least one keyword; C) identifying, by the server computer, in a database communicatively coupled to the network, a plurality of domain names, each of the plurality of domain names being available for registration; D) determining, by the server computer, whether each domain name in the plurality of domain names comprises a keyword parsed from the plurality of place names; and E) for each domain name in the plurality of domain names that comprises the keyword parsed from the plurality of place names: i) identifying, by the server computer, coordinates at which a place associated with the place name from which the keyword was parsed is displayed on a map graphic; ii) generating, by the server computer, a user interface component configured to receive input from a user; iii) rendering, by the server computer: a) the domain name within the user interface component; and b) the user interface component on the map graphic at the coordinates; and iv) transmitting, by the server computer, to a client computer communicatively coupled to the network, the map graphic comprising the user interface component at the coordinates.
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1. A method, comprising the steps of: A) receiving, by a server computer communicatively coupled to a network, a geographic location data identifying a plurality of place names, wherein the geographic location data comprises a geographic location within a geographic area, the geographic area comprises a planet, a continent, a country, a state, a region, a county, a city, an area, or a neighborhood, the geographic location comprises a continent, a country, a state, a region, a county, a city, an area, a neighborhood, a residence or a business within the geographic area and identified as local to the geographic location data, the geographic location data comprises a geographic location selection comprising a text string received from an online map software, or a geographic location received from, and displayed and selected within, a geographic area of a map rendered by the online map software, and the map software is configured to render a map of the geographic location within the geographic area, and zoom to a different geographic area comprising at least one geographic location; B) parsing, by the server computer, each place name in the plurality of place names into at least one keyword; C) identifying, by the server computer, in a database communicatively coupled to the network, a plurality of domain names, each of the plurality of domain names being available for registration; D) determining, by the server computer, whether each domain name in the plurality of domain names comprises a keyword parsed from the plurality of place names; and E) for each domain name in the plurality of domain names that comprises the keyword parsed from the plurality of place names: i) identifying, by the server computer, coordinates at which a place associated with the place name from which the keyword was parsed is displayed on a map graphic; ii) generating, by the server computer, a user interface component configured to receive input from a user; iii) rendering, by the server computer: a) the domain name within the user interface component; and b) the user interface component on the map graphic at the coordinates; and iv) transmitting, by the server computer, to a client computer communicatively coupled to the network, the map graphic comprising the user interface component at the coordinates. 3. The method of claim 1 , wherein the at least one keyword comprises an address or a name of a business identified as local to the geographic location data.
| 0.55299 |
20. A system for labeling, the system comprising one or more processors and one or more memory devices operably coupled to the one or more processors, the one or more memory devices storing executable and operational data effective to cause the one or more processors to: identify a plurality of patterns in a plurality of documents, the plurality of patterns not covered by a set of validated contextual rules; (a) select a batch of documents of the plurality of documents according to a frequency of usage of patterns included in the batch of documents of the plurality of documents, where the frequency of usage is for the plurality of documents; (b) submit the batch of documents of the plurality of documents to a crowdsourcing community for labeling; (c) receive labels for the batch of documents of the plurality of documents; (d) generate proposed contextual rules based on labeled documents of the plurality of documents by: identifying one or more patterns in the labeled documents and a usage frequency for the one or more patterns identified; selecting a top N patterns of the one or more patterns having highest usage frequencies; if a label of the labeled documents has a high correspondence to a pattern of the top N patterns of the one or more patterns, generating a proposed contextual rule relating the pattern of the top N patterns of the one or more patterns to the label; and otherwise, generating a proposed contextual rule that includes the pattern of the top N patterns of the one or more patterns but no related label; (e) submit the proposed contextual rules to an analyst community for validation; (f) receive validation of a portion of the proposed contextual rules; and (g) add the portion validated of the proposed contextual rules to the set of validated contextual rules.
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20. A system for labeling, the system comprising one or more processors and one or more memory devices operably coupled to the one or more processors, the one or more memory devices storing executable and operational data effective to cause the one or more processors to: identify a plurality of patterns in a plurality of documents, the plurality of patterns not covered by a set of validated contextual rules; (a) select a batch of documents of the plurality of documents according to a frequency of usage of patterns included in the batch of documents of the plurality of documents, where the frequency of usage is for the plurality of documents; (b) submit the batch of documents of the plurality of documents to a crowdsourcing community for labeling; (c) receive labels for the batch of documents of the plurality of documents; (d) generate proposed contextual rules based on labeled documents of the plurality of documents by: identifying one or more patterns in the labeled documents and a usage frequency for the one or more patterns identified; selecting a top N patterns of the one or more patterns having highest usage frequencies; if a label of the labeled documents has a high correspondence to a pattern of the top N patterns of the one or more patterns, generating a proposed contextual rule relating the pattern of the top N patterns of the one or more patterns to the label; and otherwise, generating a proposed contextual rule that includes the pattern of the top N patterns of the one or more patterns but no related label; (e) submit the proposed contextual rules to an analyst community for validation; (f) receive validation of a portion of the proposed contextual rules; and (g) add the portion validated of the proposed contextual rules to the set of validated contextual rules. 21. The system of claim 20 , wherein the executable and operational data are further effective to cause the one or more processors to apply the set of validated contextual rules to a document of the plurality of documents in order to determine labels thereof.
| 0.623619 |
13. The expert system of claim 11, wherein said computer elicits information concerning the type of physical trauma sustained by said patient by interactively displaying different classification of trauma to said user.
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13. The expert system of claim 11, wherein said computer elicits information concerning the type of physical trauma sustained by said patient by interactively displaying different classification of trauma to said user. 16. The expert system of claim 13, wherein said computer employs a touch-screen CRT.
| 0.939259 |
10. Computer hardware storage media having computer-executable instructions embodied thereon, that when executed, perform a method for presenting a web-accessible topic focused data mart, the method comprising: receiving health data from a data source comprising at least one of receiving internal health data collected by a health care facility and receiving public health data provided by a public agency; populating a topic focused data mart having at least a portion of the health data received from the data source, the topic focused data mart only comprising data relevant to a predetermined topic associated with the one topic focused data mart, the at least the portion of the health data being associated with the predetermined topic; associating the topic focused data mart with a web service; receiving demographic information from an Electronic Health Record (EHR) associated with a patient; querying the topic focused data mart based on the demographic information received from the EHR, the querying the topic focused data mart comprising querying only the at least the portion of the health data included in the topic focused data mart; and presenting context-specific data derived from the topic focused data mart in the EHR, the context-specific data being based on the demographic information, the receiving, querying, and presenting being performed without input from a clinician.
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10. Computer hardware storage media having computer-executable instructions embodied thereon, that when executed, perform a method for presenting a web-accessible topic focused data mart, the method comprising: receiving health data from a data source comprising at least one of receiving internal health data collected by a health care facility and receiving public health data provided by a public agency; populating a topic focused data mart having at least a portion of the health data received from the data source, the topic focused data mart only comprising data relevant to a predetermined topic associated with the one topic focused data mart, the at least the portion of the health data being associated with the predetermined topic; associating the topic focused data mart with a web service; receiving demographic information from an Electronic Health Record (EHR) associated with a patient; querying the topic focused data mart based on the demographic information received from the EHR, the querying the topic focused data mart comprising querying only the at least the portion of the health data included in the topic focused data mart; and presenting context-specific data derived from the topic focused data mart in the EHR, the context-specific data being based on the demographic information, the receiving, querying, and presenting being performed without input from a clinician. 16. The media of claim 10 , wherein the context-specific data is epidemic information.
| 0.73024 |
8. A display controller suitable for use with a display device and an input device for simultaneously displaying multiple documents in a virtual workspace, said display controller comprising: memory means comprising a parent document comprising parent attributes; and, a plurality of child documents each comprising corresponding child attributes; processor means coupled with said memory means and with said display device, said processor means for displaying a parent document display outline and a plurality of child document display outlines in the display device, said parent document display outline corresponding to said parent document and each said child document display outline corresponding to one said child document; parent document rendering means coupled with said memory means, for rendering a portion of said parent document within said parent document display outline, and, child document rendering means coupled with said memory means, for rendering at least a portion of each said child document within a corresponding said child document display outline, said child document rendering means responsive to the input device and to said child document attributes for defining said corresponding child document portion to be displayed within said corresponding document display outline.
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8. A display controller suitable for use with a display device and an input device for simultaneously displaying multiple documents in a virtual workspace, said display controller comprising: memory means comprising a parent document comprising parent attributes; and, a plurality of child documents each comprising corresponding child attributes; processor means coupled with said memory means and with said display device, said processor means for displaying a parent document display outline and a plurality of child document display outlines in the display device, said parent document display outline corresponding to said parent document and each said child document display outline corresponding to one said child document; parent document rendering means coupled with said memory means, for rendering a portion of said parent document within said parent document display outline, and, child document rendering means coupled with said memory means, for rendering at least a portion of each said child document within a corresponding said child document display outline, said child document rendering means responsive to the input device and to said child document attributes for defining said corresponding child document portion to be displayed within said corresponding document display outline. 14. A display controller as in claim 8 wherein said attributes comprise coordinate positions.
| 0.5625 |
1. A computer-implemented method comprising: receiving audio data that encodes an utterance of a user; determining that the user has been classified as a novice user of a speech recognizer, comprising determining that an amount of training data that has been collected for the user does not satisfy a threshold; in response to determining that the user has been classified as a novice user of a speech recognizer, selecting a speech recognizer setting that is used by the speech recognizer in generating a transcription of the utterance, wherein the selected speech recognizer setting is different than a default speech recognizer setting that is used by the speech recognizer in generating transcriptions of utterances of users that are not classified as novice users, and wherein the selected speech recognizer setting results in increased speech recognition accuracy for the utterance in comparison with the default setting, and wherein the selected speech recognizer setting results in increased speech recognition latency for the utterance in comparison with the default setting; and obtaining a transcription of the utterance that is generated by the speech recognizer using the selected speech recognizer setting.
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1. A computer-implemented method comprising: receiving audio data that encodes an utterance of a user; determining that the user has been classified as a novice user of a speech recognizer, comprising determining that an amount of training data that has been collected for the user does not satisfy a threshold; in response to determining that the user has been classified as a novice user of a speech recognizer, selecting a speech recognizer setting that is used by the speech recognizer in generating a transcription of the utterance, wherein the selected speech recognizer setting is different than a default speech recognizer setting that is used by the speech recognizer in generating transcriptions of utterances of users that are not classified as novice users, and wherein the selected speech recognizer setting results in increased speech recognition accuracy for the utterance in comparison with the default setting, and wherein the selected speech recognizer setting results in increased speech recognition latency for the utterance in comparison with the default setting; and obtaining a transcription of the utterance that is generated by the speech recognizer using the selected speech recognizer setting. 8. The method of claim 1 , wherein selecting a speech recognizer setting comprises adjusting an endpoint parameter.
| 0.871681 |
15. The method of claim 13 , wherein providing the query-completion suggestion comprises providing one or more selectable indicators each of which represents an actionable query-completion selection.
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15. The method of claim 13 , wherein providing the query-completion suggestion comprises providing one or more selectable indicators each of which represents an actionable query-completion selection. 16. The method of claim 15 , further comprising: receiving a user selection of one of the one or more selectable indicators; and, in response to the user selection of the one of the one or more selectable indicators, navigating the user to a vertical associated with a search engine for furtherance of the associated task-oriented user intent.
| 0.901938 |
1. A general digital semantic database for mechanical language translation, characterized in that all words are decomposed according to part-of-speech characteristics and semantic characteristics to form basic semantic points which cannot be further decomposed; and the basic semantic points are categorized and arranged orderly in sequence according to semantic characteristics, part-of-speech characteristics, contextual backgrounds and syntactic relationships; and two or more languages are configured at the basic semantic points according to synonym relationships; and free interchange between languages is performed by using a machine according to basic semantic points; and according to grammatical rules and commands of syntactic formulae, the machine can perform rearrangement in sequence by using semantic meanings of various languages configured in the semantic database and formulae of syntactic relationships so as to accomplish automatic translation that fits language patterns of various different languages; the general digital semantic database for mechanical language translation is “digital”, which means all basic semantic points in the semantic database are each allocated with a set of digits in order to differentiate all basic semantic points in the digital semantic database from one another; and the sets of digits are all different from one another; the sets of digits in a next level of groups are increased by 2 digits; and the first digits of all sets of digits within the same level of groups are the same but different in different levels of grows; and within the same level of groups, sets of digits in the first level are the same in their first digits and those in the second level are the same in their first two digits and those in the third level are the same in their first four digits, so and so forth; and regardless of number of levels of groups, a set of digits in any level should have its digits prior to the last two digits being the same as the set of digits from which it is expanded; and within the same level of groups, a parallel relationship is established between sets of digits which are only different in their last two digits, a subordinate relationship is established between sets of digits which are different in their first two digits and if the sets of digits are different in their first digits, they belong to different levels of groups and the relationship between them is called a cross relationship; and thus a machine digital semantic database is constituted.
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1. A general digital semantic database for mechanical language translation, characterized in that all words are decomposed according to part-of-speech characteristics and semantic characteristics to form basic semantic points which cannot be further decomposed; and the basic semantic points are categorized and arranged orderly in sequence according to semantic characteristics, part-of-speech characteristics, contextual backgrounds and syntactic relationships; and two or more languages are configured at the basic semantic points according to synonym relationships; and free interchange between languages is performed by using a machine according to basic semantic points; and according to grammatical rules and commands of syntactic formulae, the machine can perform rearrangement in sequence by using semantic meanings of various languages configured in the semantic database and formulae of syntactic relationships so as to accomplish automatic translation that fits language patterns of various different languages; the general digital semantic database for mechanical language translation is “digital”, which means all basic semantic points in the semantic database are each allocated with a set of digits in order to differentiate all basic semantic points in the digital semantic database from one another; and the sets of digits are all different from one another; the sets of digits in a next level of groups are increased by 2 digits; and the first digits of all sets of digits within the same level of groups are the same but different in different levels of grows; and within the same level of groups, sets of digits in the first level are the same in their first digits and those in the second level are the same in their first two digits and those in the third level are the same in their first four digits, so and so forth; and regardless of number of levels of groups, a set of digits in any level should have its digits prior to the last two digits being the same as the set of digits from which it is expanded; and within the same level of groups, a parallel relationship is established between sets of digits which are only different in their last two digits, a subordinate relationship is established between sets of digits which are different in their first two digits and if the sets of digits are different in their first digits, they belong to different levels of groups and the relationship between them is called a cross relationship; and thus a machine digital semantic database is constituted. 3. The general digital semantic database for mechanical language translation as in claim 1 , characterized in that “semantic meaning” among the three major elements of a word, namely “phonetic sound, visual form and semantic meaning”, is used as a subject for preparation of semantic meanings in the general digital semantic database; and a digital semantic database is formed by decomposing existing words to establish basic semantic points which cannot be further decomposed; and a digital semantic database is formed by categorizing all the basic semantic points according to scopes to which their semantic characteristics belong and their subordinate relationships and then arranging them orderly in sequence.
| 0.523555 |
56. The computer program product of claim 29 , wherein the computer program product is configured such that the at least one computer-readable XML-compliant data document includes an extensible semantic tag-equipped markup language component and a hypertext markup language (HTML) component.
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56. The computer program product of claim 29 , wherein the computer program product is configured such that the at least one computer-readable XML-compliant data document includes an extensible semantic tag-equipped markup language component and a hypertext markup language (HTML) component. 57. The computer program product of claim 56 , wherein the computer program product is configured such that the at least one computer-readable XML-compliant data document is capable of being displayed utilizing an HTML browser for allowing review of the HTML component in addition to access, through one or more additional actions, the extensible semantic tag-equipped markup language component.
| 0.953732 |
1. A method utilized during a testimonial proceeding, the method comprising: capturing representations of spoken words in real time at a first premises; converting the representations into text in real time; delivering the text in real time to a remote system, the remote system being disposed at a second premises; communicatively coupling at least one terminal and the remote system; delivering, by the remote system, the text in real time to the at least one terminal, the at least one terminal being disposed at at least a third premises; and displaying at the at least one terminal the delivered text for real time review.
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1. A method utilized during a testimonial proceeding, the method comprising: capturing representations of spoken words in real time at a first premises; converting the representations into text in real time; delivering the text in real time to a remote system, the remote system being disposed at a second premises; communicatively coupling at least one terminal and the remote system; delivering, by the remote system, the text in real time to the at least one terminal, the at least one terminal being disposed at at least a third premises; and displaying at the at least one terminal the delivered text for real time review. 7. The method of claim 1 further comprising: capturing video corresponding to the spoken words; delivering the captured video to the at least one terminal via the remote system; and reproducing at the at least one terminal the delivered video.
| 0.633616 |
2. The apparatus of claim 1 , wherein said segment group information includes a level information.
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2. The apparatus of claim 1 , wherein said segment group information includes a level information. 3. The apparatus of claim 2 , wherein said level information defines multiple levels.
| 0.982913 |
4. The method of claim 1 , further comprising: persisting the normalization cache on a non-volatile computer-readable storage medium.
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4. The method of claim 1 , further comprising: persisting the normalization cache on a non-volatile computer-readable storage medium. 6. The method of claim 4 , further comprising: comparing the names in a current version of a source of names to a version of the source of names from a time when the normalization cache was generated; and rebuilding the cache when a difference between the versions of the source of names exceeds a threshold.
| 0.874594 |
9. A handheld electronic device comprising: an input apparatus having a number of input keys; a processor; and memory storing instructions which, when executed by the processor, cause the processor to perform operations comprising: detecting a first input key selection; detecting a second input key selection, wherein a primary punctuation and a secondary punctuation are assigned to the second input key; determining said first input is associated with a predetermined characteristic; determining a preference for said secondary punctuation based on the determination that said first input is associated with said predetermined characteristic; and outputting said secondary punctuation as an output.
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9. A handheld electronic device comprising: an input apparatus having a number of input keys; a processor; and memory storing instructions which, when executed by the processor, cause the processor to perform operations comprising: detecting a first input key selection; detecting a second input key selection, wherein a primary punctuation and a secondary punctuation are assigned to the second input key; determining said first input is associated with a predetermined characteristic; determining a preference for said secondary punctuation based on the determination that said first input is associated with said predetermined characteristic; and outputting said secondary punctuation as an output. 10. The handheld electronic device of claim 9 , wherein said primary punctuation is a comma and said secondary punctuation is an apostrophe.
| 0.547879 |
7. The computer implemented method of claim 6 wherein when multiple instances of classification information containing the same text string have been received, each timestamp corresponds to receipt of a different instance of classification information, and wherein the profiling rules decay a significance of the text-timestamped classification information records over time.
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7. The computer implemented method of claim 6 wherein when multiple instances of classification information containing the same text string have been received, each timestamp corresponds to receipt of a different instance of classification information, and wherein the profiling rules decay a significance of the text-timestamped classification information records over time. 8. The computer implemented method of claim 7 wherein a timestamp older than a predetermined threshold is removed.
| 0.93607 |
1. A method comprising: a code processor pre-processing a set of statements that conform to a computer programming language standard, said set of statements including a first aliasing directive and a second aliasing directive, both of which conform to a syntax defined by the computer programming language standard; wherein said syntax specifies that an aliasing directive includes an alias expression and a substitute expression; wherein the first aliasing directive includes a first alias expression and a first substitute expression and the second aliasing directive includes a second alias expression and a second substitute expression; wherein a semantic specified by said computer programming language standard for an aliasing directive is that instances of an alias expression in the set of statements are replaced with a substitute expression corresponding to the aliasing directive during pre-processing of the set of statements; wherein the second substitute expression specifies a processing directive having a semantic different than any semantic specified by said computer programming language standard for a substitute expression of an aliasing directive; wherein said set of statements does not refer to the second alias expression outside of the second aliasing directive; wherein said code processor pre-processing the set of statements includes: replacing the first alias expression with the first substitute expression; pre-processing the second aliasing directive by generating code to carry out the processing directive specified in the second substitute expression.
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1. A method comprising: a code processor pre-processing a set of statements that conform to a computer programming language standard, said set of statements including a first aliasing directive and a second aliasing directive, both of which conform to a syntax defined by the computer programming language standard; wherein said syntax specifies that an aliasing directive includes an alias expression and a substitute expression; wherein the first aliasing directive includes a first alias expression and a first substitute expression and the second aliasing directive includes a second alias expression and a second substitute expression; wherein a semantic specified by said computer programming language standard for an aliasing directive is that instances of an alias expression in the set of statements are replaced with a substitute expression corresponding to the aliasing directive during pre-processing of the set of statements; wherein the second substitute expression specifies a processing directive having a semantic different than any semantic specified by said computer programming language standard for a substitute expression of an aliasing directive; wherein said set of statements does not refer to the second alias expression outside of the second aliasing directive; wherein said code processor pre-processing the set of statements includes: replacing the first alias expression with the first substitute expression; pre-processing the second aliasing directive by generating code to carry out the processing directive specified in the second substitute expression. 3. The method of claim 1 , wherein said computer programming language standard defines a first programming language; the substitute expression of said second aliasing directive contains program source code for a second programming language, wherein the program source code for the second programming language is not syntactically correct in said first programming language.
| 0.556689 |
15. A system comprising: one or more processors; and memory having one or more instructions stored thereon that, responsive to execution by the one or more processors, causes the one or more processors to perform operations comprising: presenting a first user interface having, and enabling selection of, multiple characters or character strings through a gesture or gesture portion, the multiple characters or character strings presented at least partially obscuring an unselected character entry control or adjacent to or surrounding a selected character entry control, at least one of the character strings having or completing a long word and a short word, the short word being shorter than the long word and being a constituent part of the long word, the short word and the long word being presented at a same time in the first user interface; and responsive to selection through the first user interface to select the short word or the long word through selection of one or more of the multiple characters or character strings, wherein selecting the multiple characters or character strings for the short word would be selecting a portion of the multiple characters or character strings for the long word, providing the selected short word or long word.
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15. A system comprising: one or more processors; and memory having one or more instructions stored thereon that, responsive to execution by the one or more processors, causes the one or more processors to perform operations comprising: presenting a first user interface having, and enabling selection of, multiple characters or character strings through a gesture or gesture portion, the multiple characters or character strings presented at least partially obscuring an unselected character entry control or adjacent to or surrounding a selected character entry control, at least one of the character strings having or completing a long word and a short word, the short word being shorter than the long word and being a constituent part of the long word, the short word and the long word being presented at a same time in the first user interface; and responsive to selection through the first user interface to select the short word or the long word through selection of one or more of the multiple characters or character strings, wherein selecting the multiple characters or character strings for the short word would be selecting a portion of the multiple characters or character strings for the long word, providing the selected short word or long word. 20. The system of claim 15 , wherein the multiple characters are determined based on words of a language, acronyms or text strings of the language, words or acronyms or text strings based on a user history, or lengths of the words of the language, and also an aggregate likelihood of selection of the long word and the short word.
| 0.726446 |
11. The method of claim 10 , further comprising scoring the search results based on one or more of the search intents.
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11. The method of claim 10 , further comprising scoring the search results based on one or more of the search intents. 12. The method of claim 11 , wherein the one or more search intents comprise an intent to exclude converse search results, and wherein scoring the search results comprises downgrading the score of each search result corresponding to at least one of the selected nodes referenced in the structured query.
| 0.894518 |
16. The method of claim 13 , further comprising: receiving, from the second user, a search query to search for document information in the database, wherein the search query from the second user is identical to the search query from the first user.
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16. The method of claim 13 , further comprising: receiving, from the second user, a search query to search for document information in the database, wherein the search query from the second user is identical to the search query from the first user. 17. The method of claim 16 , further comprising: determining the terms of the search query from the second user are not in accordance with the dictionary information corresponding to the second user.
| 0.933066 |
10. A method of organising and storing documents in a computer system for subsequent retrieval, the documents having associated metadata terms, the method comprising: providing access to a store of existing metadata in the computer system; analysing the existing metadata to generate statistical data as to co-occurrence of pairs of terms in the metadata of a single document; analysing a fresh document to assign to the fresh document a set of terms and determine for each term of the set a measure of a strength of association of the term with the document; determining for each term of the set a score that is a monotonically increasing function of (a) the strength of association with the document and of (b) a relative frequency of co-ocurrence, in the existing metadata, of the term and another term that occurs in the set; and selecting, as metadata for the fresh document, a subset of the terms in the set having highest scores.
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10. A method of organising and storing documents in a computer system for subsequent retrieval, the documents having associated metadata terms, the method comprising: providing access to a store of existing metadata in the computer system; analysing the existing metadata to generate statistical data as to co-occurrence of pairs of terms in the metadata of a single document; analysing a fresh document to assign to the fresh document a set of terms and determine for each term of the set a measure of a strength of association of the term with the document; determining for each term of the set a score that is a monotonically increasing function of (a) the strength of association with the document and of (b) a relative frequency of co-ocurrence, in the existing metadata, of the term and another term that occurs in the set; and selecting, as metadata for the fresh document, a subset of the terms in the set having highest scores. 17. The method according to claim 10 , in which the score for a term is also a function of the weights in the set of weights for that term.
| 0.617239 |
1. A computer-implemented method of rendering regular expression side-effect statements to 100% Java™ or C# code, the method comprising the steps of: a. defining a programming language or grammar that produces scripts that compile to Java™ or C# classes and run within the host Java or C# system; b. including among regular expression forms in this grammar a DoPattern as a means to wrap a matching sub-expression (regex) with side-effect producing functional statements that fire before and after the match and whose side-effect statements have access to variables in all outer scopes; and the CapturePattern as a means to capture the match to the wrapped sub-expression (regex) into a variable available in the scope of the regular expression in which it is found; c. compiling the side-effects of the DoPattern (the pre- and post-statement lists) as bodies of Java functions that are accessible as implementations of abstract functions of an abstract DoPattern class that includes abstract prelist ( ) and postlist ( ) functions; d. adding to the abstract prelist and postlist functions of the DoPattern class access to the parameters $rein and $repos so that the CapturePattern can be implemented as a specialized variation of the DoPattern; e. providing a regular expression execution engine capable of calling the java functions that compile the pre-list and post-list statements of the DoPattern at the proper points relative to the data stream being matched, whereby the DoPattern and especially the CapturePattern can properly reference matching points of the stream; f. obtaining hot-spot execution speeds for all of the side-effects of the regular expression (DoPattern statements and CapturePattern data substring to variable capture) as these side-effects are compiled to the implementations of the abstract prelist and postlist Java™ or C# functions; and g. including a translator that compiles this specialized scripting grammar entirely to Java™/C# classes.
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1. A computer-implemented method of rendering regular expression side-effect statements to 100% Java™ or C# code, the method comprising the steps of: a. defining a programming language or grammar that produces scripts that compile to Java™ or C# classes and run within the host Java or C# system; b. including among regular expression forms in this grammar a DoPattern as a means to wrap a matching sub-expression (regex) with side-effect producing functional statements that fire before and after the match and whose side-effect statements have access to variables in all outer scopes; and the CapturePattern as a means to capture the match to the wrapped sub-expression (regex) into a variable available in the scope of the regular expression in which it is found; c. compiling the side-effects of the DoPattern (the pre- and post-statement lists) as bodies of Java functions that are accessible as implementations of abstract functions of an abstract DoPattern class that includes abstract prelist ( ) and postlist ( ) functions; d. adding to the abstract prelist and postlist functions of the DoPattern class access to the parameters $rein and $repos so that the CapturePattern can be implemented as a specialized variation of the DoPattern; e. providing a regular expression execution engine capable of calling the java functions that compile the pre-list and post-list statements of the DoPattern at the proper points relative to the data stream being matched, whereby the DoPattern and especially the CapturePattern can properly reference matching points of the stream; f. obtaining hot-spot execution speeds for all of the side-effects of the regular expression (DoPattern statements and CapturePattern data substring to variable capture) as these side-effects are compiled to the implementations of the abstract prelist and postlist Java™ or C# functions; and g. including a translator that compiles this specialized scripting grammar entirely to Java™/C# classes. 2. The computer-implemented method of claim 1 , further comprising the step of modeling a DoPatternImpl as a pure abstract class with an abstract body function, an abstract prelist function, and an abstract postlist function.
| 0.561333 |
11. A computer program product comprising: a computer readable non-transitory storage medium having computer readable program code embodied in the non-transitory storage medium that when executed by a processor of a computer system causes the computer system to perform operations comprising: generating a list of unique terms, each comprising prefix data and associated property data, contained in a defined web ontology language; receiving a resource descriptive framework (RDF) statement about a web resource; generating a list of unique terms, each comprising prefix data and associated property data, contained in the RDF statement; identifying a first problem term within the list of unique terms contained in the RDF statement that is not present among the list of unique terms contained in the defined web ontology language, the first problem term comprising an error in the RDF statement; generating a list of candidate terms contained in the defined web ontology that satisfy a threshold similarity to the first problem term; selecting a candidate term from among the list of candidate terms having a data type for the property data that matches a data type for the property data of the first problem term; and substituting the candidate term for each occurrence of the first problem term contained in the RDF statement.
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11. A computer program product comprising: a computer readable non-transitory storage medium having computer readable program code embodied in the non-transitory storage medium that when executed by a processor of a computer system causes the computer system to perform operations comprising: generating a list of unique terms, each comprising prefix data and associated property data, contained in a defined web ontology language; receiving a resource descriptive framework (RDF) statement about a web resource; generating a list of unique terms, each comprising prefix data and associated property data, contained in the RDF statement; identifying a first problem term within the list of unique terms contained in the RDF statement that is not present among the list of unique terms contained in the defined web ontology language, the first problem term comprising an error in the RDF statement; generating a list of candidate terms contained in the defined web ontology that satisfy a threshold similarity to the first problem term; selecting a candidate term from among the list of candidate terms having a data type for the property data that matches a data type for the property data of the first problem term; and substituting the candidate term for each occurrence of the first problem term contained in the RDF statement. 19. The computer program product of claim 11 , wherein the operations further comprise: identifying a second problem term within the list of unique terms contained in the RDF statement that is not present among the list of unique terms contained in the defined web ontology language, the second problem term comprising an error in the RDF statement; determining that the defined web ontology contains a single candidate term that satisfies a threshold similarity to the second problem term; and substituting the single candidate term for each occurrence of the second problem term contained in the RDF statement.
| 0.54865 |
12. A computer program product for automatic transformation of messages between service versions, the computer program product comprising a computer-readable storage medium having computer-readable program code embodied therewith, the computer-readable program code executable by a computer to cause the computer to: collect message data of messages sent to two or more versions of a service; identify message data as relating to a version of a service; infer relationships between structure and content of messages sent to different versions of the service; create message transformation rules based on the inferred relationships wherein creating message transformation rules creates transformation rules for transforming a message format for an earlier version of a service to a message format for a later version of the service; receiving a message for a version of the service using a proxy system; identifying if the message is for the earlier version of the service for which there is the later version of the service, using the proxy system; transforming the message using transformation rules for transforming the message format for the earlier version of the service to the message format for the later version of the service, using the proxy system; and forwarding the transformed message to the later version of the service, using the proxy system.
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12. A computer program product for automatic transformation of messages between service versions, the computer program product comprising a computer-readable storage medium having computer-readable program code embodied therewith, the computer-readable program code executable by a computer to cause the computer to: collect message data of messages sent to two or more versions of a service; identify message data as relating to a version of a service; infer relationships between structure and content of messages sent to different versions of the service; create message transformation rules based on the inferred relationships wherein creating message transformation rules creates transformation rules for transforming a message format for an earlier version of a service to a message format for a later version of the service; receiving a message for a version of the service using a proxy system; identifying if the message is for the earlier version of the service for which there is the later version of the service, using the proxy system; transforming the message using transformation rules for transforming the message format for the earlier version of the service to the message format for the later version of the service, using the proxy system; and forwarding the transformed message to the later version of the service, using the proxy system. 13. The computer program product of claim 12 , including: monitoring message traffic to discover available service versions to which messages are sent.
| 0.644247 |
7. One or more non-transitory computer-readable storage media that includes code for execution and when executed by a processor operable to perform operations comprising: providing a search interface to a user for installation on a remote computer; receiving results of an Internet search query initiated by a user using the search interface, wherein the Internet search query comprises a number of search terms entered by the user using an input device and wherein the results comprise links to resources that meet criteria specified in the search query; evaluating the received results in relation to a personal profile of the user, wherein the personal profile includes a plurality of characteristics associated with the user and wherein the evaluating comprises comparing the plurality of characteristics to the results, wherein the plurality of characteristics comprise at least one characteristic derived from observing the user's behavioral patterns over a period of time and at least one characteristic declared by the user; evaluating the results based on attributes of the user; ranking the results to generate a resultant that reflects a ranking of the results in order of likely meaningfulness to the user based on the evaluation; and communicating the resultant to the user via the search interface such that the user cause to be displayed a web page associated with a selected one of the results by activating the selected one of the results via the search interface; wherein the plurality of characteristics includes at least one of a media type preferred by the user, a tag cloud associated with the user, a personal vocabulary of the user, and a rating of similar searches.
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7. One or more non-transitory computer-readable storage media that includes code for execution and when executed by a processor operable to perform operations comprising: providing a search interface to a user for installation on a remote computer; receiving results of an Internet search query initiated by a user using the search interface, wherein the Internet search query comprises a number of search terms entered by the user using an input device and wherein the results comprise links to resources that meet criteria specified in the search query; evaluating the received results in relation to a personal profile of the user, wherein the personal profile includes a plurality of characteristics associated with the user and wherein the evaluating comprises comparing the plurality of characteristics to the results, wherein the plurality of characteristics comprise at least one characteristic derived from observing the user's behavioral patterns over a period of time and at least one characteristic declared by the user; evaluating the results based on attributes of the user; ranking the results to generate a resultant that reflects a ranking of the results in order of likely meaningfulness to the user based on the evaluation; and communicating the resultant to the user via the search interface such that the user cause to be displayed a web page associated with a selected one of the results by activating the selected one of the results via the search interface; wherein the plurality of characteristics includes at least one of a media type preferred by the user, a tag cloud associated with the user, a personal vocabulary of the user, and a rating of similar searches. 9. The one or more non-transitory computer-readable storage media of claim 7 , further comprising: evaluating the results based on a social network of the user; evaluating the results based on attributes of the user; and evaluating the results based on preferences declared by the user.
| 0.520891 |
6. The method of claim 1 , wherein identifying a subset of less than all of the multiple avatars includes: identifying an attribute associated with an avatar of the multiple avatars; determining whether the identified attribute associated with the avatar corresponds to one or more of the inferred user profile attributes; and including the avatar in the subset based on a determination that the identified attribute associated with the avatar corresponds to one or more of the inferred user profile attributes.
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6. The method of claim 1 , wherein identifying a subset of less than all of the multiple avatars includes: identifying an attribute associated with an avatar of the multiple avatars; determining whether the identified attribute associated with the avatar corresponds to one or more of the inferred user profile attributes; and including the avatar in the subset based on a determination that the identified attribute associated with the avatar corresponds to one or more of the inferred user profile attributes. 7. The method of claim 6 , wherein identifying an attribute associated with the avatar includes identifying the attribute based on the avatar itself.
| 0.896256 |
6. A computer system for estimating a labor cost to reconcile semantic conflicts between data schema terms used in different data sources, the computer system comprising: a CPU, a computer readable memory and a computer readable storage media; first program instructions to estimate a labor cost for mapping, to shared ontology terms, respective pairs of the data schema terms having semantic conflicts with each other, the first program instructions estimating the labor cost based on at least five of the following: (a) a number of the data sources that contain the data schema terms having the semantic conflicts, (b) an approximate number of the data schema terms in each of the data sources, (c) an approximate labor cost for implementing the shared ontology terms for each of the data sources, (d) an approximate labor cost to manually map to the shared ontology terms a percent of the data schema terms in each of the data sources, (e) an approximate labor cost to validate a percent of the mappings from the data schema terms to the shared ontology terms, (f) an approximate labor cost to perform functional computation for a percent of the mappings from the data schema terms to the shared ontology terms, and (g) an approximate labor cost to perform structural heterogeneity semantic mapping between a percent of the data schema terms and the shared ontology terms; and second program instructions to initiate display on a monitor the estimated labor cost for the mapping, to the shared ontology terms, the data schema terms having semantic conflicts with each other; and wherein the first and second program instructions are stored on the computer readable storage media for execution by the CPU via the computer readable memory.
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6. A computer system for estimating a labor cost to reconcile semantic conflicts between data schema terms used in different data sources, the computer system comprising: a CPU, a computer readable memory and a computer readable storage media; first program instructions to estimate a labor cost for mapping, to shared ontology terms, respective pairs of the data schema terms having semantic conflicts with each other, the first program instructions estimating the labor cost based on at least five of the following: (a) a number of the data sources that contain the data schema terms having the semantic conflicts, (b) an approximate number of the data schema terms in each of the data sources, (c) an approximate labor cost for implementing the shared ontology terms for each of the data sources, (d) an approximate labor cost to manually map to the shared ontology terms a percent of the data schema terms in each of the data sources, (e) an approximate labor cost to validate a percent of the mappings from the data schema terms to the shared ontology terms, (f) an approximate labor cost to perform functional computation for a percent of the mappings from the data schema terms to the shared ontology terms, and (g) an approximate labor cost to perform structural heterogeneity semantic mapping between a percent of the data schema terms and the shared ontology terms; and second program instructions to initiate display on a monitor the estimated labor cost for the mapping, to the shared ontology terms, the data schema terms having semantic conflicts with each other; and wherein the first and second program instructions are stored on the computer readable storage media for execution by the CPU via the computer readable memory. 8. The computer system of claim 6 wherein the first program instructions estimate the labor cost for the mapping, to the shared ontology terms, the data schema terms having semantic conflicts with each other, based on all of the following: (a) the number of the data sources that contain the data schema terms having the semantic conflicts, (b) the approximate number of the data schema terms in each of the data sources, (c) the approximate labor cost for implementing the shared ontology terms for each of the data sources, (d) the approximate labor cost to manually map to the shared ontology terms a percent of the data schema terms in each of the data sources, (e) the approximate labor cost to validate a percent of the mappings from the data schema terms to the shared ontology terms, (f) the approximate labor cost to perform functional computation for a percent of the mappings from the data schema terms to the shared ontology terms, and (g) the approximate labor cost to perform structural heterogeneity semantic mapping between a percent of the data schema terms and the shared ontology terms.
| 0.503196 |
18. The system of claim 13 , wherein the classifier module is further configured to: build a model having n-grams of the domain-specific sentiment lexicon as features; and train the model on a training corpus having domain-specific documents having manually-labeled sentiment scores.
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18. The system of claim 13 , wherein the classifier module is further configured to: build a model having n-grams of the domain-specific sentiment lexicon as features; and train the model on a training corpus having domain-specific documents having manually-labeled sentiment scores. 20. The system of claim 18 , wherein the training generates sentiment scores for the n-grams of the domain-specific sentiment lexicon and wherein the storing module is further configured to: store the sentiment scores for the n-grams of the domain-specific sentiment lexicon with the domain-specific sentiment lexicon.
| 0.881148 |
20. The computer-readable storage device of claim 17 , wherein the operations further comprise displaying a first document indication associated with the first document neuron, in response to being excited, wherein the first document indication is positioned relative to the plurality of word indications based on weight of each of the plurality of connections to the first document neuron.
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20. The computer-readable storage device of claim 17 , wherein the operations further comprise displaying a first document indication associated with the first document neuron, in response to being excited, wherein the first document indication is positioned relative to the plurality of word indications based on weight of each of the plurality of connections to the first document neuron. 21. The computer-readable storage device of claim 20 , wherein the operations further comprise displaying a hyperlink associated with the first document indication.
| 0.942432 |
1. A computerized system for creating interactive electronic books over a network, comprising: a) an effects library module including a plurality of interactive effects wizard modules that automate code generation for customized interactive effects in electronic books, wherein one of the interactive effects wizard modules automates code generation for an effect selected from the group of effects consisting of: performing a mathematical function on user input; animating a graphic on a trigger; changing a background to a custom background on a trigger; changing text in a body of text to a user input text on a trigger; changing text in a body of text on a trigger; playing an author uploaded audio file on a trigger; and scrolling a user view on a trigger other than a usual scroll trigger; triggering code generated by an interactive effects wizard module; delaying operation of code generated by an interactive effects wizard module; requesting a user input and storing the same in memory; operating a user interface effect; changing a display characteristic of a displayed object; selecting a displayed item; sending data on a trigger; controlling the display of media by a user; and randomizing an effect; b) a first database module including a relational database stored in a memory device that stores information associated with electronic book generation including information related to selected interactive effects wizard modules; c) a second database module including a database; d) a database federation module including a processor functionally coupled between the first database and the second database such that changes to one of the first and second databases are automatically updated in the other; and e) a user interface module functionally coupled to each of the effects library module and the first database module such that a user is able to selectably manipulate the same in creation of an electronic book and including a network module including a network communication device over a network.
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1. A computerized system for creating interactive electronic books over a network, comprising: a) an effects library module including a plurality of interactive effects wizard modules that automate code generation for customized interactive effects in electronic books, wherein one of the interactive effects wizard modules automates code generation for an effect selected from the group of effects consisting of: performing a mathematical function on user input; animating a graphic on a trigger; changing a background to a custom background on a trigger; changing text in a body of text to a user input text on a trigger; changing text in a body of text on a trigger; playing an author uploaded audio file on a trigger; and scrolling a user view on a trigger other than a usual scroll trigger; triggering code generated by an interactive effects wizard module; delaying operation of code generated by an interactive effects wizard module; requesting a user input and storing the same in memory; operating a user interface effect; changing a display characteristic of a displayed object; selecting a displayed item; sending data on a trigger; controlling the display of media by a user; and randomizing an effect; b) a first database module including a relational database stored in a memory device that stores information associated with electronic book generation including information related to selected interactive effects wizard modules; c) a second database module including a database; d) a database federation module including a processor functionally coupled between the first database and the second database such that changes to one of the first and second databases are automatically updated in the other; and e) a user interface module functionally coupled to each of the effects library module and the first database module such that a user is able to selectably manipulate the same in creation of an electronic book and including a network module including a network communication device over a network. 4. The system of claim 1 , wherein the database is a textual data format.
| 0.590134 |
1. A method performed by a data processing system, comprising: receiving a document having fragments with attribute/value pairs; receiving logical expressions that define relationships between fragments of the document; analyzing the logical expressions to identify fragment names and attributes; creating an index based on the analysis that includes names of the fragments to be candidates for selection into subdocuments; extracting, from the document, all fragments named in the index; creating, in the index, an entry for each attribute/value pair; creating a plurality of subdocuments corresponding to the document, including finding top-level fragments in the index, finding second-level fragments related to each top-level fragment, and finding third-level fragments related to each second-level fragment; and storing the subdocuments, including the respective related fragments.
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1. A method performed by a data processing system, comprising: receiving a document having fragments with attribute/value pairs; receiving logical expressions that define relationships between fragments of the document; analyzing the logical expressions to identify fragment names and attributes; creating an index based on the analysis that includes names of the fragments to be candidates for selection into subdocuments; extracting, from the document, all fragments named in the index; creating, in the index, an entry for each attribute/value pair; creating a plurality of subdocuments corresponding to the document, including finding top-level fragments in the index, finding second-level fragments related to each top-level fragment, and finding third-level fragments related to each second-level fragment; and storing the subdocuments, including the respective related fragments. 6. The method of claim 1 , wherein the logical expressions are Xpath expressions.
| 0.856643 |
1. A method for searching a database of digital media assets, comprising: a processor receiving a search query; the processor analyzing the search query to extract a specialized search condition corresponding to a specialized semantic concept; the processor selecting, from a pre-existing ontology of indexers, a specialized indexer based on a determination that the selected specialized indexer can be used to identify digital media assets that correspond to the specialized semantic concept; the processor analyzing the search query to extract a general search condition corresponding to a related higher level semantic concept; the processor identifying, from a database of digital media assets, a subset of digital media assets that satisfy the general search condition responsive to general metadata for each of the digital media assets; the processor applying the selected specialized indexer to the subset of digital media assets to determine specialized metadata for a digital media asset in the subset of digital media assets, wherein the specialized metadata provides an indication of whether the digital media asset corresponds to the specialized semantic concept; and the processor converting the specialized indexer into a general indexer based at least on a frequency with which the specialized semantic concept is queried, wherein the processor is configured to convert the specialized indexer into the general indexer based further on a computational cost associated with the specialized indexer, wherein the general indexer is applied to the digital media assets independent of a search query, wherein the general indexer is operable to identify a digital media asset that corresponds to a higher level semantic concept and determine the general metadata for the identified digital media asset based at least upon an analysis of pixel data associated with the digital media asset, and wherein the general metadata provides an indication of the higher level semantic concept to which the identified digital media asset corresponds.
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1. A method for searching a database of digital media assets, comprising: a processor receiving a search query; the processor analyzing the search query to extract a specialized search condition corresponding to a specialized semantic concept; the processor selecting, from a pre-existing ontology of indexers, a specialized indexer based on a determination that the selected specialized indexer can be used to identify digital media assets that correspond to the specialized semantic concept; the processor analyzing the search query to extract a general search condition corresponding to a related higher level semantic concept; the processor identifying, from a database of digital media assets, a subset of digital media assets that satisfy the general search condition responsive to general metadata for each of the digital media assets; the processor applying the selected specialized indexer to the subset of digital media assets to determine specialized metadata for a digital media asset in the subset of digital media assets, wherein the specialized metadata provides an indication of whether the digital media asset corresponds to the specialized semantic concept; and the processor converting the specialized indexer into a general indexer based at least on a frequency with which the specialized semantic concept is queried, wherein the processor is configured to convert the specialized indexer into the general indexer based further on a computational cost associated with the specialized indexer, wherein the general indexer is applied to the digital media assets independent of a search query, wherein the general indexer is operable to identify a digital media asset that corresponds to a higher level semantic concept and determine the general metadata for the identified digital media asset based at least upon an analysis of pixel data associated with the digital media asset, and wherein the general metadata provides an indication of the higher level semantic concept to which the identified digital media asset corresponds. 7. The method of claim 1 wherein general search conditions are identified from elements of the search query by using concept expansion.
| 0.544886 |
8. The method of claim 1 wherein, for each placeholder of each sentential form in the vocabulary, operation (d) comprises the operation of: creating an attribute for the placeholder within the class created for the corresponding sentential form.
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8. The method of claim 1 wherein, for each placeholder of each sentential form in the vocabulary, operation (d) comprises the operation of: creating an attribute for the placeholder within the class created for the corresponding sentential form. 10. The method of claim 8 wherein the operation of creating an attribute for the placeholder further includes the operation of: setting the type of the attribute to be a general type representing a thing, the thing being the subject of facts expressed by the vocabulary.
| 0.920009 |
1. A method comprising: defining, by a computing system, a user accessible meta-object referencing contextual content, wherein said user accessible meta-object comprises a functional operation referenced object, a service referenced object, or a content specific referenced object; defining, by said computing system, a schema based structured definition for said user accessible meta-object; defining, by said computing system from said schema based structured definition, a predefined user access content mapped hierarchical taxonomy and a configuration data map associated with said predefined user access content mapped hierarchical taxonomy; determining, by said computing system, that content is required for said computing system; creating, by a processor of said computing system, said content, wherein said content comprises user accessible contextual content associated with said predefined user access content mapped hierarchical taxonomy; associating, by said computing system, user accessible topics of relevant tangible content of said content with specified logical storage room representations, wherein each storage room of said specified logical storage room representations comprises contextual content storage address spaces; associating, by said computing system, reference coordinates with said predefined user access content mapped hierarchical taxonomy, wherein said reference coordinates are associated with said specified logical storage room representations; determining, by said computing system, a change associated with a relative point of view associated with each node of said predefined user access content mapped hierarchical taxonomy; updating, by said computing system, said configuration data map, wherein said updating said configuration data map comprises generating updated configuration data, wherein said updated configuration data comprises reference coordinate pointers pointing to the contextual content storage address spaces, and wherein the contextual content storage address spaces are comprised by a plurality of different storage mediums and a plurality of different physical storage locations; generating, by said computing system, a uniform resource identifier (URI) associated with said content enabling a direct internal access mapping to the contextual content storage address spaces associated with said reference coordinate pointers; determining, by said computing system, metering charges for usage of an account per paid subscription to the user accessible contextual content; applying, by said computing system, key performance indicators to transactional analysis usage patterns of said user accessible contextual content; generating, by said computing system, a report associated with said account, said transactional analysis usage patterns, and said usage; presenting, by said computing system, analysis of said report via a dashboard view; and storing, by said computing system, said report.
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1. A method comprising: defining, by a computing system, a user accessible meta-object referencing contextual content, wherein said user accessible meta-object comprises a functional operation referenced object, a service referenced object, or a content specific referenced object; defining, by said computing system, a schema based structured definition for said user accessible meta-object; defining, by said computing system from said schema based structured definition, a predefined user access content mapped hierarchical taxonomy and a configuration data map associated with said predefined user access content mapped hierarchical taxonomy; determining, by said computing system, that content is required for said computing system; creating, by a processor of said computing system, said content, wherein said content comprises user accessible contextual content associated with said predefined user access content mapped hierarchical taxonomy; associating, by said computing system, user accessible topics of relevant tangible content of said content with specified logical storage room representations, wherein each storage room of said specified logical storage room representations comprises contextual content storage address spaces; associating, by said computing system, reference coordinates with said predefined user access content mapped hierarchical taxonomy, wherein said reference coordinates are associated with said specified logical storage room representations; determining, by said computing system, a change associated with a relative point of view associated with each node of said predefined user access content mapped hierarchical taxonomy; updating, by said computing system, said configuration data map, wherein said updating said configuration data map comprises generating updated configuration data, wherein said updated configuration data comprises reference coordinate pointers pointing to the contextual content storage address spaces, and wherein the contextual content storage address spaces are comprised by a plurality of different storage mediums and a plurality of different physical storage locations; generating, by said computing system, a uniform resource identifier (URI) associated with said content enabling a direct internal access mapping to the contextual content storage address spaces associated with said reference coordinate pointers; determining, by said computing system, metering charges for usage of an account per paid subscription to the user accessible contextual content; applying, by said computing system, key performance indicators to transactional analysis usage patterns of said user accessible contextual content; generating, by said computing system, a report associated with said account, said transactional analysis usage patterns, and said usage; presenting, by said computing system, analysis of said report via a dashboard view; and storing, by said computing system, said report. 5. The method of claim 1 , wherein said creating said content comprises: updating, by said computing system, said predefined user access content mapped hierarchical taxonomy with said topic; updating, by said computing system, said predefined user access content mapped hierarchical taxonomy with elements associated with said schema based structured definition; and updating, by said computing system, said predefined user access content mapped hierarchical taxonomy with attributes associated with said elements.
| 0.571232 |
1. A computer-implemented method for detecting differences between first and second graphical programs, wherein the method executes on a computer including a display, the method comprising: determining differences between said first graphical program and said second graphical program, wherein said first graphical program and said second gaphical program each comprise graphical code; and displaying an indication of said differences on the display; wherein said differences are used to evaluate at least one of the first graphical program and the second graphical program.
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1. A computer-implemented method for detecting differences between first and second graphical programs, wherein the method executes on a computer including a display, the method comprising: determining differences between said first graphical program and said second graphical program, wherein said first graphical program and said second gaphical program each comprise graphical code; and displaying an indication of said differences on the display; wherein said differences are used to evaluate at least one of the first graphical program and the second graphical program. 8. The method of claim 1, wherein said first and second graphical programs each comprise a block diagram comprising graphical code, a user interface panel for displaying one or more of data output from the block diagram and data input to the block diagram, and graphical program attributes; wherein said determining differences between said first graphical program and said second graphical program comprises: determining differences between said block diagrams of said first and second graphical programs; determining differences between said user interface panels of said first and second graphical programs; determining differences between said graphical program attributes of said first and second graphical programs.
| 0.7373 |
6. A system comprising: one or more computers; a computer-readable medium coupled to the one or more computers having instructions stored thereon which, when executed by the one or more computers, causes the one or more computers to perform operations comprising: receiving a search query over a network, the search query comprising a query term and a categorical identifier; selecting a domain name associated with the categorical identifier; generating, based on selecting a first result set of resources responsive to the query term, a second result set of resources in which a respective domain name for each resource matches the determined domain name associated with the categorical identifier; selecting a resource identifier associated with the categorical identifier, the selected resource identifier comprising the determined domain name and a path; enhancing a respective relevance score of each resource in the second result set whose respective resource identifier includes the selected resource identifier, a magnitude of enhancement being based on a weight associated with the categorical identifier, the respective relevance score indicating a degree of relevance between the resource and the query term; ranking each of the resources in the second result set based on the respective relevance scores; annotating, with the categorical identifier, one or more indicia identifying the resources of the ranked second result set whose respective resource identifier matches the selected resource identifier associated with the categorical identifier; and providing the annotated indicia over the network as a search engine result of the search query.
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6. A system comprising: one or more computers; a computer-readable medium coupled to the one or more computers having instructions stored thereon which, when executed by the one or more computers, causes the one or more computers to perform operations comprising: receiving a search query over a network, the search query comprising a query term and a categorical identifier; selecting a domain name associated with the categorical identifier; generating, based on selecting a first result set of resources responsive to the query term, a second result set of resources in which a respective domain name for each resource matches the determined domain name associated with the categorical identifier; selecting a resource identifier associated with the categorical identifier, the selected resource identifier comprising the determined domain name and a path; enhancing a respective relevance score of each resource in the second result set whose respective resource identifier includes the selected resource identifier, a magnitude of enhancement being based on a weight associated with the categorical identifier, the respective relevance score indicating a degree of relevance between the resource and the query term; ranking each of the resources in the second result set based on the respective relevance scores; annotating, with the categorical identifier, one or more indicia identifying the resources of the ranked second result set whose respective resource identifier matches the selected resource identifier associated with the categorical identifier; and providing the annotated indicia over the network as a search engine result of the search query. 8. The system of claim 6 , wherein the operations further comprise: extracting the domain name from the selected resource identifier.
| 0.595771 |
11. The system of claim 8 , wherein the computing domain comprises a directory server, an authentication server, and the LDAP repository.
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11. The system of claim 8 , wherein the computing domain comprises a directory server, an authentication server, and the LDAP repository. 12. The system of claim 11 , wherein the configuration file is stored in the LDAP repository.
| 0.95297 |
6. A system embodied on a computer readable storage medium for enhancing query results provided independent of a search engine, the system comprising: a module that sends a query to a search engine separate from the computer; a module that receives query results from the search engine; a module that retrieves documents identified by the query results; a module that enhances the query based at least in part upon a user model; a module that applies the enhanced query to the retrieved documents; and a module that generated information regarding relevancy of the retrieved documents based at least in part upon the enhanced query and the user model, wherein a name of a person and name of a company are identified with the retrieved documents and a relationship between the person and company is identified, the module that generates information regarding relevancy provides links to retrieved documents that contain the name of the person and the name of the company mentioned in the identified relationship.
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6. A system embodied on a computer readable storage medium for enhancing query results provided independent of a search engine, the system comprising: a module that sends a query to a search engine separate from the computer; a module that receives query results from the search engine; a module that retrieves documents identified by the query results; a module that enhances the query based at least in part upon a user model; a module that applies the enhanced query to the retrieved documents; and a module that generated information regarding relevancy of the retrieved documents based at least in part upon the enhanced query and the user model, wherein a name of a person and name of a company are identified with the retrieved documents and a relationship between the person and company is identified, the module that generates information regarding relevancy provides links to retrieved documents that contain the name of the person and the name of the company mentioned in the identified relationship. 7. The system of claim 6 , the query is enhanced based on at least one of linguistic analysis, a general interest profile, a model of user interest generated independent of search result.
| 0.5 |
18. A device for printing data, the device comprising: a data transmitting and receiving module that receives a printing information document comprising a first markup document that describes a file to be printed, the first mark-up document comprising text data and link data that indicates a location at which the file is stored in a storage unit, and a second markup document that describes the file, the second mark-up document comprising identification information that identifies the file at the location indicated by the link data; a data processing module that extracts the link data and the identification information from the printing information document, wherein the data transmitting and receiving module transmits a request for the file to be printed based on the extracted link data and the extracted identification information and receives the file to be printed based on the extracted link data and the extracted identification information; and an outputting module that prints the received file based on the extracted link data and the extracted identification information.
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18. A device for printing data, the device comprising: a data transmitting and receiving module that receives a printing information document comprising a first markup document that describes a file to be printed, the first mark-up document comprising text data and link data that indicates a location at which the file is stored in a storage unit, and a second markup document that describes the file, the second mark-up document comprising identification information that identifies the file at the location indicated by the link data; a data processing module that extracts the link data and the identification information from the printing information document, wherein the data transmitting and receiving module transmits a request for the file to be printed based on the extracted link data and the extracted identification information and receives the file to be printed based on the extracted link data and the extracted identification information; and an outputting module that prints the received file based on the extracted link data and the extracted identification information. 19. The device according to claim 18 , wherein the printing information document is prepared in accordance with a Multipurpose Internet Mail Extension (MIME) standard.
| 0.65113 |
1. A processor-implemented method for generating and utilizing a dimensionally constrained hierarchical synthetic context-based object library for multiple synthetic context-based objects, the processor-implemented method comprising: associating, by a processor, a non-contextual data object with a context object to define a synthetic context-based object, wherein the non-contextual data object ambiguously relates to multiple subject-matters, and wherein the context object provides a context that identifies a specific subject-matter, from the multiple subject-matters, of the non-contextual data object; associating, by the processor, the synthetic context-based object with at least one specific data store, wherein said at least one specific data store comprises data that is associated with data contained in the non-contextual data object and the context object; constructing, by the processor, a dimensionally constrained hierarchical synthetic context-based object library for multiple synthetic context-based objects, wherein synthetic context-based objects within a same dimension of the dimensionally constrained hierarchical synthetic context-based object library share data from a same non-contextual data object, and wherein synthetic context-based objects within the same dimension of the dimensionally constrained hierarchical synthetic context-based object library contain disparate data from different context objects; receiving, from a requester, a request for at least one data store that is associated with synthetic context-based objects within the same dimension of the dimensionally constrained hierarchical synthetic context-based object library; and returning, to the requester, said at least one specific data store that is associated with synthetic context-based objects within the same dimension of the dimensionally constrained hierarchical synthetic context-based object library.
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1. A processor-implemented method for generating and utilizing a dimensionally constrained hierarchical synthetic context-based object library for multiple synthetic context-based objects, the processor-implemented method comprising: associating, by a processor, a non-contextual data object with a context object to define a synthetic context-based object, wherein the non-contextual data object ambiguously relates to multiple subject-matters, and wherein the context object provides a context that identifies a specific subject-matter, from the multiple subject-matters, of the non-contextual data object; associating, by the processor, the synthetic context-based object with at least one specific data store, wherein said at least one specific data store comprises data that is associated with data contained in the non-contextual data object and the context object; constructing, by the processor, a dimensionally constrained hierarchical synthetic context-based object library for multiple synthetic context-based objects, wherein synthetic context-based objects within a same dimension of the dimensionally constrained hierarchical synthetic context-based object library share data from a same non-contextual data object, and wherein synthetic context-based objects within the same dimension of the dimensionally constrained hierarchical synthetic context-based object library contain disparate data from different context objects; receiving, from a requester, a request for at least one data store that is associated with synthetic context-based objects within the same dimension of the dimensionally constrained hierarchical synthetic context-based object library; and returning, to the requester, said at least one specific data store that is associated with synthetic context-based objects within the same dimension of the dimensionally constrained hierarchical synthetic context-based object library. 5. The processor-implemented method of claim 1 , wherein the data store is a text document, and wherein the processor-implemented method further comprises: searching, by the processor, the text document for text data that is part of the synthetic context-based object; and associating the text document that contains said text data with the synthetic context-based object.
| 0.713518 |
1. A method for using map objects to access properties of an object in a dynamic object-oriented programming language, wherein dynamic object-oriented programming languages allow additional properties to be defined for objects during execution, comprising: receiving an object of a given object type, wherein the object is associated with, a memory region and a given map object in a set of map objects associated with the given object type; wherein the given map object describes how properties of the object are mapped to fields in the memory region, and wherein the set of map objects are linked hierarchically using a set of map transitions based on the order in which properties are defined for one or more objects of the given object type; receiving a request to access a property for the object; determining, by a computing device, whether the given map object includes a mapping for the property; if the given map object includes a mapping for the property, accessing, by the computing device, a field associated with the property using the mapping; if the given map object does not include the mapping for the property, determining, by the computing device, whether a direct descendant of the given map object includes the mapping for the property; if a direct descendant of the given map object includes the mapping for the property: determining, by the computing device, a descendant map object for the given map object that maps the property to a new field in the memory region; wherein the descendant map object is the direct descendant of the given map object which includes substantially the same field mappings as the given map object, and wherein an additional field mapping for the property is added to the field mappings that are defined for the given map object; updating, by the computing device, the object to be associated with the descendant map object; and accessing, by the computing device, the new field associated with the property using the mapping in the descendant map object; and if no direct descendant of the given map object includes the mapping for the property: allocating, by the computing device, a new map object that defines a new field in the memory region for the property in addition to the fields defined for the properties of the given map object; creating, by the computing device, a new map transition that adds the new map object to the hierarchical set of map objects as a direct descendant of the given map object; and updating, by the computing device, the object to be associated with the new map object.
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1. A method for using map objects to access properties of an object in a dynamic object-oriented programming language, wherein dynamic object-oriented programming languages allow additional properties to be defined for objects during execution, comprising: receiving an object of a given object type, wherein the object is associated with, a memory region and a given map object in a set of map objects associated with the given object type; wherein the given map object describes how properties of the object are mapped to fields in the memory region, and wherein the set of map objects are linked hierarchically using a set of map transitions based on the order in which properties are defined for one or more objects of the given object type; receiving a request to access a property for the object; determining, by a computing device, whether the given map object includes a mapping for the property; if the given map object includes a mapping for the property, accessing, by the computing device, a field associated with the property using the mapping; if the given map object does not include the mapping for the property, determining, by the computing device, whether a direct descendant of the given map object includes the mapping for the property; if a direct descendant of the given map object includes the mapping for the property: determining, by the computing device, a descendant map object for the given map object that maps the property to a new field in the memory region; wherein the descendant map object is the direct descendant of the given map object which includes substantially the same field mappings as the given map object, and wherein an additional field mapping for the property is added to the field mappings that are defined for the given map object; updating, by the computing device, the object to be associated with the descendant map object; and accessing, by the computing device, the new field associated with the property using the mapping in the descendant map object; and if no direct descendant of the given map object includes the mapping for the property: allocating, by the computing device, a new map object that defines a new field in the memory region for the property in addition to the fields defined for the properties of the given map object; creating, by the computing device, a new map transition that adds the new map object to the hierarchical set of map objects as a direct descendant of the given map object; and updating, by the computing device, the object to be associated with the new map object. 3. The method of claim 1 , wherein additional objects of the given object type that access properties in the same order as the object do not need to allocate new map objects, but can instead re-use existing map objects; and wherein sharing map objects across one or more objects facilitates using inline caching to improve performance.
| 0.523108 |
7. A system comprising: a processor configured to perform speech recognition; and a computer-readable storage medium having instructions stored which, when executed by the processor, cause the processor to perform operations comprising: nominating, via a processor configured to use a partially observable Markov decision process in parallel with a conventional dialog state, a set of dialog actions and a set of contextual features; and generating an audible response in a dialog between a user and a spoken dialog system based at least in part on the set of contextual features.
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7. A system comprising: a processor configured to perform speech recognition; and a computer-readable storage medium having instructions stored which, when executed by the processor, cause the processor to perform operations comprising: nominating, via a processor configured to use a partially observable Markov decision process in parallel with a conventional dialog state, a set of dialog actions and a set of contextual features; and generating an audible response in a dialog between a user and a spoken dialog system based at least in part on the set of contextual features. 11. The system of claim 7 , the computer-readable storage medium having additional instructions stored which, when executed by the processor, cause the processor to perform operations comprising: assigning a reward to the set of dialog actions as part of the machine learning algorithm.
| 0.525166 |
1. A computer implemented method for annotating a displayable electronic document at a graphical user interface (GUI), the displayable electronic document comprising any one of a displayable image or text, the GUI comprising a GUI display, the method comprising the steps of: responsive to a first GUI action, selecting the displayable electronic document to be annotated, the displayable electronic document to be annotated selected from displayable electronic documents stored in a displayable electronic document database; and displaying the displayable electronic image at the GUI display; responsive to a second GUI action, selecting an annotation form from a plurality of annotation forms, the selection based on one or more predetermined parameters, the annotation form comprising one or more user prompts for annotation data; and displaying the selected annotation form at the GUI display, the displayed annotation form comprising one or more user prompts, the user prompts prompting a user for annotation data; responsive to a third user GUI action comprising moving a cursor to a position within the displayed electronic image, selecting the position of the cursor within the displayed image independent of content of the displayable electronic document, creating information associating the annotation form with the selected position of the selected displayable electronic document to be annotated; responsive to an event associated with the annotation form, performing by a computer program, an analytic action on the displayed electronic image by way of a first annotation runtime program, the analytic action analyzing characteristics of the displayed electronic image to produce an analytic result; receiving user provided annotation data associated with one of the one or more of said displayed user prompts; and storing in an annotation database each of the received annotation data, the selected position within the selected displayable electronic document and the produced analytic result; and responsive to a user fourth GUI action subsequent to said storing the annotation data, the user fourth GUI action selecting said position within the selected displayable electronic document, performing the steps comprising: finding in the annotation database, the annotation data; and displaying the found annotation data.
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1. A computer implemented method for annotating a displayable electronic document at a graphical user interface (GUI), the displayable electronic document comprising any one of a displayable image or text, the GUI comprising a GUI display, the method comprising the steps of: responsive to a first GUI action, selecting the displayable electronic document to be annotated, the displayable electronic document to be annotated selected from displayable electronic documents stored in a displayable electronic document database; and displaying the displayable electronic image at the GUI display; responsive to a second GUI action, selecting an annotation form from a plurality of annotation forms, the selection based on one or more predetermined parameters, the annotation form comprising one or more user prompts for annotation data; and displaying the selected annotation form at the GUI display, the displayed annotation form comprising one or more user prompts, the user prompts prompting a user for annotation data; responsive to a third user GUI action comprising moving a cursor to a position within the displayed electronic image, selecting the position of the cursor within the displayed image independent of content of the displayable electronic document, creating information associating the annotation form with the selected position of the selected displayable electronic document to be annotated; responsive to an event associated with the annotation form, performing by a computer program, an analytic action on the displayed electronic image by way of a first annotation runtime program, the analytic action analyzing characteristics of the displayed electronic image to produce an analytic result; receiving user provided annotation data associated with one of the one or more of said displayed user prompts; and storing in an annotation database each of the received annotation data, the selected position within the selected displayable electronic document and the produced analytic result; and responsive to a user fourth GUI action subsequent to said storing the annotation data, the user fourth GUI action selecting said position within the selected displayable electronic document, performing the steps comprising: finding in the annotation database, the annotation data; and displaying the found annotation data. 12. The method according to claim 1 , wherein the first annotation runtime program comprises an application program interface for connecting an application program to the first annotation program.
| 0.630384 |
13. A computer readable storage, having stored thereon a computer program having a plurality of code sections, that, when executed by a computer, cause the computer to perform a plurality of steps, the computer readable storage comprising: code for identifying a location of structured data described by a data model specification; code for automatically determining, by a computer, from the data model specification, relationships between a plurality of objects within the structured data, wherein the data model specification is automatically introspected to identify primary keys associated with each of the plurality of objects and foreign key relationships between the plurality of objects; code for automatically generating a plurality of portlets, wherein at least one portlet is automatically generated for each object of the plurality of objects according to the relationships specified within the data model specification, wherein at least one function, for querying the structured data, of each portlet is automatically determined by a foreign key relationship of the object associated with each portlet, and wherein automatically creating a plurality of portlets further comprises generating code in at least a first portlet of the plurality of portlets that triggers the action in at least a second portlet of the plurality of portlets according to the relationships specified within the data model specification; and code for automatically creating at least one communication link between at least two of the plurality of portlets according to the relationships specified within the data model specification, wherein over the communication link the first portlet of the at least two portlets triggers an action within the second portlet of the at least two portlets, and responsive to that action, the second portlet sends data to the first portlet, wherein at least one of the first portlet or the second portlet is displayed within a portal page.
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13. A computer readable storage, having stored thereon a computer program having a plurality of code sections, that, when executed by a computer, cause the computer to perform a plurality of steps, the computer readable storage comprising: code for identifying a location of structured data described by a data model specification; code for automatically determining, by a computer, from the data model specification, relationships between a plurality of objects within the structured data, wherein the data model specification is automatically introspected to identify primary keys associated with each of the plurality of objects and foreign key relationships between the plurality of objects; code for automatically generating a plurality of portlets, wherein at least one portlet is automatically generated for each object of the plurality of objects according to the relationships specified within the data model specification, wherein at least one function, for querying the structured data, of each portlet is automatically determined by a foreign key relationship of the object associated with each portlet, and wherein automatically creating a plurality of portlets further comprises generating code in at least a first portlet of the plurality of portlets that triggers the action in at least a second portlet of the plurality of portlets according to the relationships specified within the data model specification; and code for automatically creating at least one communication link between at least two of the plurality of portlets according to the relationships specified within the data model specification, wherein over the communication link the first portlet of the at least two portlets triggers an action within the second portlet of the at least two portlets, and responsive to that action, the second portlet sends data to the first portlet, wherein at least one of the first portlet or the second portlet is displayed within a portal page. 16. The computer readable storage of claim 13 , further comprising code for identifying transitive relationships between the plurality of objects within the structured data.
| 0.633803 |
1. A method performed by a handwriting recognition device for presenting a recognized handwritten symbol, the recognition device having a processor and detection means for detecting entry of a handwritten symbol, the method comprising the steps of: detecting, by the detection means, a handwritten pattern that is entered by a user, recognizing, by the processor, the detected handwritten pattern, wherein said step of recognizing comprises: comparing the handwritten pattern to a plurality of templates, wherein each of the plurality of templates represents at least one of a plurality of handwriting symbol patterns of handwritten ways of hand writing symbols, and returning a best template selected from the plurality of templates that represents one of the plurality of handwriting symbol patterns as a best handwriting symbol pattern which, according to a predefined rule, is most similar to the handwritten pattern, wherein at least two of the plurality of templates comprise different ones of the plurality of handwriting symbol patterns which represent different handwritten ways of handwriting a single symbol; and presenting the best handwriting symbol pattern of the best template.
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1. A method performed by a handwriting recognition device for presenting a recognized handwritten symbol, the recognition device having a processor and detection means for detecting entry of a handwritten symbol, the method comprising the steps of: detecting, by the detection means, a handwritten pattern that is entered by a user, recognizing, by the processor, the detected handwritten pattern, wherein said step of recognizing comprises: comparing the handwritten pattern to a plurality of templates, wherein each of the plurality of templates represents at least one of a plurality of handwriting symbol patterns of handwritten ways of hand writing symbols, and returning a best template selected from the plurality of templates that represents one of the plurality of handwriting symbol patterns as a best handwriting symbol pattern which, according to a predefined rule, is most similar to the handwritten pattern, wherein at least two of the plurality of templates comprise different ones of the plurality of handwriting symbol patterns which represent different handwritten ways of handwriting a single symbol; and presenting the best handwriting symbol pattern of the best template. 11. The method according to claim 1 , wherein each of the plurality of templates is associated with a category defining what kind of symbol is represented by each of the plurality of templates.
| 0.61337 |
1. A method comprising: receiving, in a processor associated with a vehicle, sound related vehicle information representing one or more sounds, the sound related vehicle information measured an exterior microphone located exterior to a cabin of the vehicle; and modifying spoken dialogue of a spoken dialogue system associated with the vehicle based on the sound related vehicle information; comprising determining interference profile records based on the sound related vehicle information; wherein modifying spoken dialogue of the spoken dialogue system associated with the vehicle based on the sound related vehicle information comprises: modifying pace and timing and pitch of audio prompts based on the interference profile records; and outputting the modified audio prompts.
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1. A method comprising: receiving, in a processor associated with a vehicle, sound related vehicle information representing one or more sounds, the sound related vehicle information measured an exterior microphone located exterior to a cabin of the vehicle; and modifying spoken dialogue of a spoken dialogue system associated with the vehicle based on the sound related vehicle information; comprising determining interference profile records based on the sound related vehicle information; wherein modifying spoken dialogue of the spoken dialogue system associated with the vehicle based on the sound related vehicle information comprises: modifying pace and timing and pitch of audio prompts based on the interference profile records; and outputting the modified audio prompts. 5. The method of claim 1 , wherein modifying spoken dialogue of the spoken dialogue system associated with the vehicle based on the sound related vehicle information comprises: modifying multi-modal dialogue based on the interference profile records.
| 0.681564 |
23. The method of claim 22 wherein the resource transition probabilities define a probability that, within a session, a second resource will be referenced, after a first resource has been referenced.
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23. The method of claim 22 wherein the resource transition probabilities define a probability that, within a session, a second resource will be referenced, after a first resource has been referenced. 24. The method of claim 23 wherein the probability is defined by: a) counting a number of times the second resources is referenced after the first resource has been referenced to generate a first count; b) counting a number of times the first resource has been referenced to generate a second count; and c) dividing the first count by the second count.
| 0.856331 |
1. A party kit associated with a party theme, the party kit comprising: party gifts having at least one character thereon related to one or more animated characters associated with a theme, the one or more animated characters being displayed on one or more systems in a bowling center; and party supplies having the at least one character thereon which are related to the one or more animated characters displayed on the one or more systems in the bowling center.
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1. A party kit associated with a party theme, the party kit comprising: party gifts having at least one character thereon related to one or more animated characters associated with a theme, the one or more animated characters being displayed on one or more systems in a bowling center; and party supplies having the at least one character thereon which are related to the one or more animated characters displayed on the one or more systems in the bowling center. 16. The party kit of claim 1 , wherein the party supplies includes party decorations and tableware, each having the at least one character thereon.
| 0.781326 |
1. A method for enabling structured communication among a social network including a computer, the method comprising: receiving, by the computer, input pertaining to a question; formulating by the computer the question based upon the input; generating by the computer an answer pattern including potential responses to the question based upon a form of the question; translating and transmitting by the computer a message including the question and the answer pattern having the potential responses to the question to a plurality of users over a corresponding plurality of preferred messaging platforms from among a plurality of different messaging platforms for eliciting responses to the question from two or more of the users using the answer pattern; collecting and aggregating by the computer the responses to the question from a corresponding two or more of the plurality of preferred messaging platforms; and presenting by the computer the responses in a summary format, wherein the plurality of preferred messaging platforms comprises, for each user of the plurality of users, a corresponding preferred messaging platform for that user from among the plurality of preferred messaging platforms.
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1. A method for enabling structured communication among a social network including a computer, the method comprising: receiving, by the computer, input pertaining to a question; formulating by the computer the question based upon the input; generating by the computer an answer pattern including potential responses to the question based upon a form of the question; translating and transmitting by the computer a message including the question and the answer pattern having the potential responses to the question to a plurality of users over a corresponding plurality of preferred messaging platforms from among a plurality of different messaging platforms for eliciting responses to the question from two or more of the users using the answer pattern; collecting and aggregating by the computer the responses to the question from a corresponding two or more of the plurality of preferred messaging platforms; and presenting by the computer the responses in a summary format, wherein the plurality of preferred messaging platforms comprises, for each user of the plurality of users, a corresponding preferred messaging platform for that user from among the plurality of preferred messaging platforms. 29. The method of claim 1 wherein the translating and transmitting step comprises translating a message into a format that depends upon a messaging network over which the message is transmitted.
| 0.686087 |
1. A method for controlling replay for video content in a trick mode of operation, the method comprising: receiving a trick mode command; determining a trick mode frame rate as a function of a time interval between consecutive semantics in the video content, a time duration of the video content, a number of occurrences for the semantics in the video content and a frame rate in a normal play mode of the video content; and wherein the video content related to the time interval in the trick mode defined by the received trick mode command is displayed at the trick mode frame rate, said trick mode frame rate, V i , is determined as V i =[T i /T]×(N×L×M), where T i is a time interval between an i th and an (i+1) th consecutive semantics in the video content, T is a time duration of the video content, N is a number of occurrences for the semantics in the video content, and M is a frame rate in a normal play mode.
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1. A method for controlling replay for video content in a trick mode of operation, the method comprising: receiving a trick mode command; determining a trick mode frame rate as a function of a time interval between consecutive semantics in the video content, a time duration of the video content, a number of occurrences for the semantics in the video content and a frame rate in a normal play mode of the video content; and wherein the video content related to the time interval in the trick mode defined by the received trick mode command is displayed at the trick mode frame rate, said trick mode frame rate, V i , is determined as V i =[T i /T]×(N×L×M), where T i is a time interval between an i th and an (i+1) th consecutive semantics in the video content, T is a time duration of the video content, N is a number of occurrences for the semantics in the video content, and M is a frame rate in a normal play mode. 3. The method as defined in claim 1 , wherein the consecutive semantics are selected from a group including at least one of scenes changes in the video content, selected metadata associated with the video content, selected tags associated with the video content, and selected audio associated with the video content, and selected statistic values of the video content.
| 0.560938 |
12. A computer-implemented method for automatically transferring a user from a speech response system to a human agent, the method comprising: during a dialog session, presenting a prompt to a user; receiving and processing a response from the user to the prompt; and when the response is a non-valid user response, assigning an error weight to the non-valid user response, wherein different non-valid user responses are assigned different error weights, wherein the assigning comprises categorizing the non-valid user response into one of a plurality of categories, wherein the error weight is assigned to the non-valid user response based at least in part upon the one of the plurality of categories into which the non-valid user response is categorized; adding the error weight to an error score for the dialog session; comparing the error score to an error threshold; and automatically transferring the user to a human agent when the error score exceeds the error threshold.
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12. A computer-implemented method for automatically transferring a user from a speech response system to a human agent, the method comprising: during a dialog session, presenting a prompt to a user; receiving and processing a response from the user to the prompt; and when the response is a non-valid user response, assigning an error weight to the non-valid user response, wherein different non-valid user responses are assigned different error weights, wherein the assigning comprises categorizing the non-valid user response into one of a plurality of categories, wherein the error weight is assigned to the non-valid user response based at least in part upon the one of the plurality of categories into which the non-valid user response is categorized; adding the error weight to an error score for the dialog session; comparing the error score to an error threshold; and automatically transferring the user to a human agent when the error score exceeds the error threshold. 14. The method of claim 12 , further comprising: when the response is a non-valid user response, determining an error severity level of the non-valid user response, wherein the assigning step assigns the error weight to the non-valid user response based at least in part upon the determined error severity level of the non-valid user response.
| 0.695035 |
8. The system as set forth in claim 6 wherein the first work of literature comprises at least one text source selected from the group consisting of a digital document, a digital book, a digital magazine, a data stream, and a web page, wherein the character characteristics are selected from the group consisting of gender, age, nationality, ethnicity, mood, profession, hero role, villain role, likability, and education level, and wherein the context is selected from the group consisting of genre, tempo, tone, pace, plot elements, subplot elements, and literary elements.
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8. The system as set forth in claim 6 wherein the first work of literature comprises at least one text source selected from the group consisting of a digital document, a digital book, a digital magazine, a data stream, and a web page, wherein the character characteristics are selected from the group consisting of gender, age, nationality, ethnicity, mood, profession, hero role, villain role, likability, and education level, and wherein the context is selected from the group consisting of genre, tempo, tone, pace, plot elements, subplot elements, and literary elements. 9. The system as set forth in claim 8 wherein the vocalization is adjusted to reflect changes according to plot elements.
| 0.957133 |
12. A computer system for displaying prominent elements in a text object, comprising: a user interface configured to provide a display area for displaying a text element extracted from a first text object; and a computer processor configured to receive the element and to enable the display of the element in the display area in the user interface, wherein the element is obtained based on a method comprising the steps of: (a) tokenizing the first text object into one or more tokens as instances of one or more terms, each term comprising one or more words or phrases, wherein the first text object includes a single document or a collection of documents containing text, or a document segment marked by a boundary or by a section heading, or a page of a multi-page document; (b) for the one or more terms in the first text object, incrementing a first value for the term based on the number of occurrences of the term in the first text object; (c) obtaining a second value based on the corresponding number of occurrences of the same term in a plurality of second text objects, wherein at least one of the plurality of second text objects is different from the first text object, or is randomly selected, wherein the second text objects can be referred to as external text objects; (d) for one or more terms in the first text object, producing a score value based on a measurement of the difference between the first value and the second value, wherein the first value is greater than the second value, wherein the score value is an importance score of the term representing an information focus in the text object; (e) selecting one or more terms in the first text object based at least on the respective score value; and (f) extracting, from the first text object, the selected terms or a sentence or paragraph containing the one or more selected terms for storage or display.
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12. A computer system for displaying prominent elements in a text object, comprising: a user interface configured to provide a display area for displaying a text element extracted from a first text object; and a computer processor configured to receive the element and to enable the display of the element in the display area in the user interface, wherein the element is obtained based on a method comprising the steps of: (a) tokenizing the first text object into one or more tokens as instances of one or more terms, each term comprising one or more words or phrases, wherein the first text object includes a single document or a collection of documents containing text, or a document segment marked by a boundary or by a section heading, or a page of a multi-page document; (b) for the one or more terms in the first text object, incrementing a first value for the term based on the number of occurrences of the term in the first text object; (c) obtaining a second value based on the corresponding number of occurrences of the same term in a plurality of second text objects, wherein at least one of the plurality of second text objects is different from the first text object, or is randomly selected, wherein the second text objects can be referred to as external text objects; (d) for one or more terms in the first text object, producing a score value based on a measurement of the difference between the first value and the second value, wherein the first value is greater than the second value, wherein the score value is an importance score of the term representing an information focus in the text object; (e) selecting one or more terms in the first text object based at least on the respective score value; and (f) extracting, from the first text object, the selected terms or a sentence or paragraph containing the one or more selected terms for storage or display. 16. The system of claim 12 , wherein the first text object and the second text objects are separated into a plurality of paragraphs, wherein the number of occurrences of the term in the first text object is the number of paragraphs containing the term divided by the total number of paragraphs in the first text object, wherein the corresponding number of occurrences of the same term in the second text objects is the number of paragraphs containing the term in the second text objects divided by the total number of paragraphs in the second text objects.
| 0.514357 |
2. The method of claim 1 , further comprising: accessing, using the computing device, a fourth database comprising information representative of at least one royalty statement, each royalty statement associated with at least one license agreement; accessing, using the computing device, a fifth database comprising information representative of at least one payment, each payment associated with at least one license agreement; and enabling processing of, using the computing device and at least one of said plurality of user-defined indexes, in a manner specified by a received command, information representative of at least one of: said at least one IP asset; said at least one IP asset package; said at least one license agreement; said at least one royalty statement; or said at least one payment.
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2. The method of claim 1 , further comprising: accessing, using the computing device, a fourth database comprising information representative of at least one royalty statement, each royalty statement associated with at least one license agreement; accessing, using the computing device, a fifth database comprising information representative of at least one payment, each payment associated with at least one license agreement; and enabling processing of, using the computing device and at least one of said plurality of user-defined indexes, in a manner specified by a received command, information representative of at least one of: said at least one IP asset; said at least one IP asset package; said at least one license agreement; said at least one royalty statement; or said at least one payment. 8. The method of claim 2 , wherein accessing the third database comprises generating an IP asset report listing any license agreements involving said at least one IP asset package, wherein the IP asset report includes information indicative of any payment amounts allocated to said at least one IP asset package, or any expected revenue of said at least one IP asset package.
| 0.805709 |
1. A method for retrieving information, comprising: receiving a search query within a first information corpus that comprises a first plurality of documents, wherein the first information corpus is a first non World Wide Web-based corpus whose first plurality of documents are not available on the World Wide Web; identifying search results for the search query; generating a score for each of a plurality of data items identified in the search results, wherein the score for a corresponding one of the plurality of data items is based on: a score dependent on the search query within the first information corpus; and at least one score independent of the search query, the at least one score independent of the search query comprising a ranking signal and at least one additional score, the ranking signal being associated with a search of the corresponding one of the plurality of data items using a second information corpus that comprises a second plurality of documents, wherein the second information corpus is a World Wide Web-based corpus whose second plurality of documents are available on an Internet, wherein the first information corpus comprising the first plurality of documents and the second information corpus comprising the second plurality of documents are non-overlapping, the ranking signal including a first score signal based on a number of times the search has been performed over a given period of time, the at least one additional score based on information from a second non World Wide Web-based corpus that includes a geographic location from where the search query originated and whose information is not available on the World Wide Web; and ranking the search results based on the generated score for each of the plurality of data items.
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1. A method for retrieving information, comprising: receiving a search query within a first information corpus that comprises a first plurality of documents, wherein the first information corpus is a first non World Wide Web-based corpus whose first plurality of documents are not available on the World Wide Web; identifying search results for the search query; generating a score for each of a plurality of data items identified in the search results, wherein the score for a corresponding one of the plurality of data items is based on: a score dependent on the search query within the first information corpus; and at least one score independent of the search query, the at least one score independent of the search query comprising a ranking signal and at least one additional score, the ranking signal being associated with a search of the corresponding one of the plurality of data items using a second information corpus that comprises a second plurality of documents, wherein the second information corpus is a World Wide Web-based corpus whose second plurality of documents are available on an Internet, wherein the first information corpus comprising the first plurality of documents and the second information corpus comprising the second plurality of documents are non-overlapping, the ranking signal including a first score signal based on a number of times the search has been performed over a given period of time, the at least one additional score based on information from a second non World Wide Web-based corpus that includes a geographic location from where the search query originated and whose information is not available on the World Wide Web; and ranking the search results based on the generated score for each of the plurality of data items. 3. The method according to claim 1 , wherein the first score signal is further based on the number of times the search has been performed.
| 0.606317 |
12. The method of claim 1 wherein the selected subset of features is used to generate a next group of features utilized in a next iteration.
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12. The method of claim 1 wherein the selected subset of features is used to generate a next group of features utilized in a next iteration. 13. The method of claim 12 wherein the selected subset of features is used to transform a feature of the selected subset to include additional information relating to a respective feature.
| 0.955425 |
6. In a computing environment, a system comprising; at least one processor; a computer readable storage medium communicatively coupled to the at least one processor and including components comprising; a framework configured to process a webpage to understand one or more entities of the webpage, the framework including a text understanding component and a structure understanding component for enabling bidirectional integration of webpage structure understanding and text understanding in an iterative manner until an iteration similarity stop criterion is met, the text understanding component configured to provide text-related data to the structure understanding component for identifying a structure of the webpage, the structure understanding component configured to use the text-related data and visual layout features of the webpage to produce a labeled block, the text understanding component configured to use the labeled block to understand text of the one or more entities.
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6. In a computing environment, a system comprising; at least one processor; a computer readable storage medium communicatively coupled to the at least one processor and including components comprising; a framework configured to process a webpage to understand one or more entities of the webpage, the framework including a text understanding component and a structure understanding component for enabling bidirectional integration of webpage structure understanding and text understanding in an iterative manner until an iteration similarity stop criterion is met, the text understanding component configured to provide text-related data to the structure understanding component for identifying a structure of the webpage, the structure understanding component configured to use the text-related data and visual layout features of the webpage to produce a labeled block, the text understanding component configured to use the labeled block to understand text of the one or more entities. 9. The system of claim 6 wherein the text understanding component processes text within leaf nodes of a vision tree corresponding to the webpage to provide the text-related data.
| 0.567046 |
1. An automatic price quotation system comprising, in combination: a seller automatic engine storing or receiving seller-specific business objectives, historic market data, and current market condition information and responsive to requests to create a price quotation based upon the request and within the respective guidelines of seller-specific predetermined information stored in the seller automatic engine; one or more price integrators within the seller automatic engine adapted to process at least two price optimizers configured for different goals to produce a price decision by applying one or more of computation, logic and pricing rules based upon price requests, sales targets, real-time sales data and price watch lists, the architectural implementations of connection between the one or more price integrators and the at least two price optimizers selected from the group consisting of a parallel processing architecture, a pipeline architecture, a hub and spoke architecture, and a hybrid architecture; and a processor for receiving price requests and outputting the price quotation.
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1. An automatic price quotation system comprising, in combination: a seller automatic engine storing or receiving seller-specific business objectives, historic market data, and current market condition information and responsive to requests to create a price quotation based upon the request and within the respective guidelines of seller-specific predetermined information stored in the seller automatic engine; one or more price integrators within the seller automatic engine adapted to process at least two price optimizers configured for different goals to produce a price decision by applying one or more of computation, logic and pricing rules based upon price requests, sales targets, real-time sales data and price watch lists, the architectural implementations of connection between the one or more price integrators and the at least two price optimizers selected from the group consisting of a parallel processing architecture, a pipeline architecture, a hub and spoke architecture, and a hybrid architecture; and a processor for receiving price requests and outputting the price quotation. 2. The automatic price quotation system of claim 1 , wherein the price integrators and price optimizers are configured to achieve long and short term sales targets simultaneously while the relative priority of each seller goal is changed based upon current market conditions.
| 0.577091 |
9. A computer readable storage medium comprising program code that when executed instructs a processor to perform a method for detecting templates within one or more web pages comprising a website, the method comprising: instructions for generating one or more groups of hyperlinks within a respective web page of the one or more web pages comprising the website; instructions for identifying 2-dimensional coordinates of the one or more hyperlinks within a given web page; instructions for placing hyperlinks with 2-dimensional coordinates that differ below a given threshold in a given group of hyperlinks; instructions for calculating an in-link score for a given uniform resource locator associated with the one or more web pages comprising the website, the in-link score calculated from other web pages of the website that point to the given uniform resource locator associated with the one or more web pares comprising the website; instructions for identifying the one or more hyperlink groups in which uniform resource locators associated with the one or more web pages comprising the website appear; instructions for assigning a template score to the one or more identified hyperlinks groups based upon the in-link score of the uniform resource locators associated with the one or more web pages comprising the website corresponding to the one or more hyperlinks of the (liven hyperlink group, wherein assigning a template score to the given hyperlink group comprises calculating an average in-link score of one or more uniform resource locators to which the one or more hyperlinks comprising the hyperlink group; instructions for identifying the hyperlink groups with template scores exceeding a given template score threshold as web page templates within a framework of the one or more web pares comprising the website; and instructions for determining one or more presences of web pare templates in a set of web pages comprising the website on the basis of the hyperlink groups identified as web page templates.
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9. A computer readable storage medium comprising program code that when executed instructs a processor to perform a method for detecting templates within one or more web pages comprising a website, the method comprising: instructions for generating one or more groups of hyperlinks within a respective web page of the one or more web pages comprising the website; instructions for identifying 2-dimensional coordinates of the one or more hyperlinks within a given web page; instructions for placing hyperlinks with 2-dimensional coordinates that differ below a given threshold in a given group of hyperlinks; instructions for calculating an in-link score for a given uniform resource locator associated with the one or more web pages comprising the website, the in-link score calculated from other web pages of the website that point to the given uniform resource locator associated with the one or more web pares comprising the website; instructions for identifying the one or more hyperlink groups in which uniform resource locators associated with the one or more web pages comprising the website appear; instructions for assigning a template score to the one or more identified hyperlinks groups based upon the in-link score of the uniform resource locators associated with the one or more web pages comprising the website corresponding to the one or more hyperlinks of the (liven hyperlink group, wherein assigning a template score to the given hyperlink group comprises calculating an average in-link score of one or more uniform resource locators to which the one or more hyperlinks comprising the hyperlink group; instructions for identifying the hyperlink groups with template scores exceeding a given template score threshold as web page templates within a framework of the one or more web pares comprising the website; and instructions for determining one or more presences of web pare templates in a set of web pages comprising the website on the basis of the hyperlink groups identified as web page templates. 11. The computer readable storage medium of claim 9 wherein the instructions for generating a group of hyperlinks within a given web page comprises instructions for placing hyperlinks that are consequent and equidistant in a given group of hyperlinks.
| 0.5637 |
1. A method comprising: receiving from a user an utterance in a first language including a first term; by a speech translation system, translating the utterance from the first language into a second language; receiving an indication from the user to initiate a user customization process for customizing one or more modules of the speech translation system to the user; and under the user customization process: receiving an indication from the user to add the first term to one or more modules of the speech translation system; in response to the received indication from the user, determining word class information for the first term; adding, by the speech translation system, the first term, the determined word class information, and at least a portion of the translation of the utterance in the second language to a first machine translation module associated with the first language of the speech translation system; and adding the first term and the at least a portion of the translation of the utterance in the second language to a shared database for a community such that the customization performed by the user is available for use by other users of the community in translations by the speech translation system.
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1. A method comprising: receiving from a user an utterance in a first language including a first term; by a speech translation system, translating the utterance from the first language into a second language; receiving an indication from the user to initiate a user customization process for customizing one or more modules of the speech translation system to the user; and under the user customization process: receiving an indication from the user to add the first term to one or more modules of the speech translation system; in response to the received indication from the user, determining word class information for the first term; adding, by the speech translation system, the first term, the determined word class information, and at least a portion of the translation of the utterance in the second language to a first machine translation module associated with the first language of the speech translation system; and adding the first term and the at least a portion of the translation of the utterance in the second language to a shared database for a community such that the customization performed by the user is available for use by other users of the community in translations by the speech translation system. 3. The method of claim 1 , wherein the at least a portion of the translation of the utterance in the second language added to the shared database comprises an incorrect or incomplete translation, and further comprising: requesting, with the first term added to the shared database, a translation correction for the first term.
| 0.582888 |
3. The method of claim 2 , wherein determining vowel/consonant ratio keyword feature information further comprises: counting the number of vowels in the message using the classifier; counting the number of consonants in the message using the classifier; and dividing the number of vowels in the message by the number of consonants in the message using the classifier.
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3. The method of claim 2 , wherein determining vowel/consonant ratio keyword feature information further comprises: counting the number of vowels in the message using the classifier; counting the number of consonants in the message using the classifier; and dividing the number of vowels in the message by the number of consonants in the message using the classifier. 4. The classifier of claim 3 , wherein the letter ‘y’ is excluded from the number of vowels in the message and from the number of consonants in the message.
| 0.923619 |
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