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14. A non-transitory computer readable medium comprising instructions executable by a processor for: receiving records from a player database comprising records related to players of a plurality of players, a record including, for a player, a player ID of the player and demographic data of the player; receiving records related to game rounds from a game data database, wherein a game round record includes an answer and a list of clues that can be offered from a clue-giving player to a guessing player for the guessing player to attempt to guess the answer; receiving cost weights from a weighting generator for a plurality of clues in the list of clues for a game round record, wherein the weighting generator generates the cost weights such that, over a distributed plurality of game rounds played a plurality of times, selections of clues by the clue-giving player from the list of clues is more reflective of revealed sentiment than of stated opinion, wherein cost weights for more obvious clues are greater than cost weights for less obvious clues and clues more reflective of revealed sentiment than of stated opinion; recording clue selections by a plurality of clue-giving players in a game results database that records the clue selections by a plurality of clue-giving players, wherein the plurality of clue-giving players comprises a large enough number of clue-giving players to result in the selections of clues by the plurality of clue-giving players being more reflective of revealed sentiment distributed over the large enough number of clue-giving players than of individual stated opinions or preferences; and converting game results from the game results database into marketing data. | 14. A non-transitory computer readable medium comprising instructions executable by a processor for: receiving records from a player database comprising records related to players of a plurality of players, a record including, for a player, a player ID of the player and demographic data of the player; receiving records related to game rounds from a game data database, wherein a game round record includes an answer and a list of clues that can be offered from a clue-giving player to a guessing player for the guessing player to attempt to guess the answer; receiving cost weights from a weighting generator for a plurality of clues in the list of clues for a game round record, wherein the weighting generator generates the cost weights such that, over a distributed plurality of game rounds played a plurality of times, selections of clues by the clue-giving player from the list of clues is more reflective of revealed sentiment than of stated opinion, wherein cost weights for more obvious clues are greater than cost weights for less obvious clues and clues more reflective of revealed sentiment than of stated opinion; recording clue selections by a plurality of clue-giving players in a game results database that records the clue selections by a plurality of clue-giving players, wherein the plurality of clue-giving players comprises a large enough number of clue-giving players to result in the selections of clues by the plurality of clue-giving players being more reflective of revealed sentiment distributed over the large enough number of clue-giving players than of individual stated opinions or preferences; and converting game results from the game results database into marketing data. 20. The computer readable medium of claim 14 , further comprising instructions for: presenting a plurality of clue-selection game displays to at least some of the plurality of players including the clue-giving player, wherein a clue-selection game display includes a representation of the list of clues and their respective cost weights, thereby allowing the clue-giving player to select clues from among the list of clues; and presenting a plurality of guessing game displays to at least some of the plurality of players including the guessing player, wherein a guessing game display includes a representation of clues selected by the clue-giving player and a countdown timer, wherein an initial value of the countdown timer is a function of cost weights assigned to the clues selected by the clue-giving player and shown to the guessing player, with more obvious clues causing the countdown timer to be more decremented than for less obvious clues, for sentiment-oriented words, and/or for words more useful for market research purposes. | 0.575389 |
2. The system of claim 1 , wherein the information provided in response to the request comprises an indication of a type of the object. | 2. The system of claim 1 , wherein the information provided in response to the request comprises an indication of a type of the object. 3. The system of claim 2 , wherein based on the indication of the type of the object corresponding to the classification of the object by the perception system, the feedback system is configured to add the one or more portions of data to training data that is used to determine the parameters associated with the machine learning classifier. | 0.873634 |
17. A computer system for processing handwritten equations comprising: a) means for receiving an input pattern comprising an equation which was derived from user handwritten strokes on an input tablet; b) a parser for parsing said input pattern, said parser including: i) means for recognizing said input pattern as a valid pattern utilizing a defined constrained attribute grammar, said grammar including a set of production rules and a grammar start symbol, wherein said means for recognizing determines when said input pattern is valid by determining when said set of input subpatterns can be rewritten as said start symbol according to said set of production rules, wherein said production rules include a syntactic part, a semantic part, a constraints part, and an action part, said constraints part including spatial constraints that require predetermined spatial relationships be satisfied between said input subpatterns; and ii) means for providing a parsed tree when said means for recognizing recognizes said input pattern as a valid pattern; c) data manipulation means for deriving a result of said equation utilizing said parsed tree by executing an operator at nodes of said parsed tree using operands included in said parsed tree; and d) editing means for detecting an edit to said equation and for editing said parsed tree in response to said edit to said equation and without changing a structure of said parsed tree. | 17. A computer system for processing handwritten equations comprising: a) means for receiving an input pattern comprising an equation which was derived from user handwritten strokes on an input tablet; b) a parser for parsing said input pattern, said parser including: i) means for recognizing said input pattern as a valid pattern utilizing a defined constrained attribute grammar, said grammar including a set of production rules and a grammar start symbol, wherein said means for recognizing determines when said input pattern is valid by determining when said set of input subpatterns can be rewritten as said start symbol according to said set of production rules, wherein said production rules include a syntactic part, a semantic part, a constraints part, and an action part, said constraints part including spatial constraints that require predetermined spatial relationships be satisfied between said input subpatterns; and ii) means for providing a parsed tree when said means for recognizing recognizes said input pattern as a valid pattern; c) data manipulation means for deriving a result of said equation utilizing said parsed tree by executing an operator at nodes of said parsed tree using operands included in said parsed tree; and d) editing means for detecting an edit to said equation and for editing said parsed tree in response to said edit to said equation and without changing a structure of said parsed tree. 24. A method as recited in claim 17 wherein said step of determining that one of said subpatterns satisfies a spatial constraint includes determining that one of said subpatterns has multi-dimensional relationships with different subpatterns. | 0.601618 |
53. The method of claim 36 , further comprising defining compound profiled score criteria that are based on a set of profiled score criteria, wherein the compound profiled score criteria are instantiated as compound profiled score criteria values, the simple profiled score criteria values and the compound profiled score criteria values each being composed of sub-profiled score criteria. | 53. The method of claim 36 , further comprising defining compound profiled score criteria that are based on a set of profiled score criteria, wherein the compound profiled score criteria are instantiated as compound profiled score criteria values, the simple profiled score criteria values and the compound profiled score criteria values each being composed of sub-profiled score criteria. 58. The method of claim 53 , wherein a partial score of a compound profiled score criteria value is computed by computing a score for each of the sub-profiled score criteria, and aggregating results using a score integration function. | 0.923271 |
1. A method of processing data, the method comprising: receiving identification of a plurality of concepts via a user interface, the concepts representing a top level of a hierarchy of topics; processing a data set to extract children of the top level of the hierarchy of topics, wherein at least the children of the hierarchy of topics is based on a hierarchy of the data set identified from a source of the data set; linking a portion of the data set to a subset of the hierarchy of topics, wherein the subset of the hierarchy of topics comprises one or more subtopics; extracting selected terms from the portion of the data set, wherein the selected terms were identified as important based on calculated information retrieval measurements of the portion of the data set; training topic models for the subset of the hierarchy of topics and the one or more subtopics using the selected terms from the portion of the data set and a probabilistic learning technique, wherein for each topic model the training comprises: determining a prior knowledge estimate based on estimated prior knowledge of a portion of the data set belonging to the topic model; determining a plurality of term contribution estimates by processing each term of the selected terms to estimate a measure of evidence that the term contributes to the portion of the data set belonging to the topic model; and combining the prior knowledge estimate and the plurality of term contribution estimates to determine a probability that the portion of the data set belongs to the topic model; evaluating an accuracy and evaluating a complexity of each topic model of the topic models in response to a determination that a topic model has been trained for at least one subtopic; determining, using one or more processors, that the subset of the hierarchy of topics is an appropriate topic for textual data generated via a social networking service by determining that the subset of the hierarchy of topics balances the accuracy and the complexity of the topic models, wherein the subset of the hierarchy of topics is at a median hierarchy level relative to the hierarchy of topics; and detecting one or more appropriate subtopics of the appropriate topic that are most appropriate for the textual data generated via the social networking service by examining the accuracy of each topic model associated with the one or more subtopics of the appropriate topic, wherein the detecting one or more appropriate subtopics of the appropriate topic comprises applying a locality-sensitive hashing (LSH) technique to the textual data generated via the social networking service and the portion of the data set. | 1. A method of processing data, the method comprising: receiving identification of a plurality of concepts via a user interface, the concepts representing a top level of a hierarchy of topics; processing a data set to extract children of the top level of the hierarchy of topics, wherein at least the children of the hierarchy of topics is based on a hierarchy of the data set identified from a source of the data set; linking a portion of the data set to a subset of the hierarchy of topics, wherein the subset of the hierarchy of topics comprises one or more subtopics; extracting selected terms from the portion of the data set, wherein the selected terms were identified as important based on calculated information retrieval measurements of the portion of the data set; training topic models for the subset of the hierarchy of topics and the one or more subtopics using the selected terms from the portion of the data set and a probabilistic learning technique, wherein for each topic model the training comprises: determining a prior knowledge estimate based on estimated prior knowledge of a portion of the data set belonging to the topic model; determining a plurality of term contribution estimates by processing each term of the selected terms to estimate a measure of evidence that the term contributes to the portion of the data set belonging to the topic model; and combining the prior knowledge estimate and the plurality of term contribution estimates to determine a probability that the portion of the data set belongs to the topic model; evaluating an accuracy and evaluating a complexity of each topic model of the topic models in response to a determination that a topic model has been trained for at least one subtopic; determining, using one or more processors, that the subset of the hierarchy of topics is an appropriate topic for textual data generated via a social networking service by determining that the subset of the hierarchy of topics balances the accuracy and the complexity of the topic models, wherein the subset of the hierarchy of topics is at a median hierarchy level relative to the hierarchy of topics; and detecting one or more appropriate subtopics of the appropriate topic that are most appropriate for the textual data generated via the social networking service by examining the accuracy of each topic model associated with the one or more subtopics of the appropriate topic, wherein the detecting one or more appropriate subtopics of the appropriate topic comprises applying a locality-sensitive hashing (LSH) technique to the textual data generated via the social networking service and the portion of the data set. 2. The method of claim 1 , wherein evaluating the accuracy of each topic model of the topic models comprises: identifying a label from the textual data generated via the social networking service according to the portion of data set; assigning the label to the appropriate topic; performing a topic detection technique; and comparing a result of the topic detection technique to but an references in order to determine the accuracy of each topic model of the topic models. | 0.518584 |
15. A computer program product for summarizing a first unit of text data with relation to the contents of multiple documents in an existing document collection, the computer program product including a computer-readable medium encoded with computer program instructions, wherein the computer program instructions, when executed by a processor, cause the processor to perform predetermined operations comprising: creating a subspace for the existing document collection without first posting a query, an input involving latent semantic indexing; performing one of a domain driven text summarization, an example type query driven text summarization, and a term type query driven text summarization on a selected document; recomposing a vector using a projection in the subspace representing the contents of multiple documents in the existing document collection when performing the domain driven text summarization or the example type query driven text summarization; computing term relationships representing similarities between query terms and the contents of multiple documents in the existing document collection using a term-term matrix associated with an original term space when performing the term type query driven text summarization; computing a term weight that is representative of the relevance of a term to a second unit of text data with relation to the contents of multiple documents in the document collection, the computing of the term weight including generation of the subspace using the document collection for projection of the text data into the subspace and back into term space in order to get weights for all the terms in the document collection; comparing the computed term weight to a predetermined threshold; returning a relevant term based at least in part on a result of the comparison; summing a plurality of relevant term weights based on a number of occurrences of a plurality of corresponding relevant terms in a segment of the first unit of text data; comparing a plurality of summations based on a plurality of corresponding segments of the first unit of text data to identify a text summarization segment; and returning the text summarization segment. | 15. A computer program product for summarizing a first unit of text data with relation to the contents of multiple documents in an existing document collection, the computer program product including a computer-readable medium encoded with computer program instructions, wherein the computer program instructions, when executed by a processor, cause the processor to perform predetermined operations comprising: creating a subspace for the existing document collection without first posting a query, an input involving latent semantic indexing; performing one of a domain driven text summarization, an example type query driven text summarization, and a term type query driven text summarization on a selected document; recomposing a vector using a projection in the subspace representing the contents of multiple documents in the existing document collection when performing the domain driven text summarization or the example type query driven text summarization; computing term relationships representing similarities between query terms and the contents of multiple documents in the existing document collection using a term-term matrix associated with an original term space when performing the term type query driven text summarization; computing a term weight that is representative of the relevance of a term to a second unit of text data with relation to the contents of multiple documents in the document collection, the computing of the term weight including generation of the subspace using the document collection for projection of the text data into the subspace and back into term space in order to get weights for all the terms in the document collection; comparing the computed term weight to a predetermined threshold; returning a relevant term based at least in part on a result of the comparison; summing a plurality of relevant term weights based on a number of occurrences of a plurality of corresponding relevant terms in a segment of the first unit of text data; comparing a plurality of summations based on a plurality of corresponding segments of the first unit of text data to identify a text summarization segment; and returning the text summarization segment. 26. The computer program product of claim 15 , wherein the step of computing further comprises computing an original vector representation in the original term space and transforming the original vector representation into a projection in a predetermined vector subspace. | 0.64403 |
16. A method for transmitting code comprising: transmitting code to calculate a plurality of topic distributions of content associated with a plurality of entities; transmitting code to compare a first topic distribution based on content associated with a first entity with a second topic distribution based on content associated with a second entity to determine a first divergence between the first topic distribution and the second topic distribution; transmitting code to compare the first topic distribution with a third topic distribution based on content associated with a third entity to determine a second divergence between the first topic distribution and the third topic distribution; if the first divergence is less than the second divergence, transmitting code to display an indication of the second entity on a webpage profile of the first entity to permit the first entity to follow the second entity; and if the second divergence is less than the first divergence, transmitting code to display an indication of the third entity on the webpage profile of the first entity to permit the first entity to follow the third entity. | 16. A method for transmitting code comprising: transmitting code to calculate a plurality of topic distributions of content associated with a plurality of entities; transmitting code to compare a first topic distribution based on content associated with a first entity with a second topic distribution based on content associated with a second entity to determine a first divergence between the first topic distribution and the second topic distribution; transmitting code to compare the first topic distribution with a third topic distribution based on content associated with a third entity to determine a second divergence between the first topic distribution and the third topic distribution; if the first divergence is less than the second divergence, transmitting code to display an indication of the second entity on a webpage profile of the first entity to permit the first entity to follow the second entity; and if the second divergence is less than the first divergence, transmitting code to display an indication of the third entity on the webpage profile of the first entity to permit the first entity to follow the third entity. 17. The method of claim 16 , wherein the content comprises words. | 0.851307 |
2. The method of claim 1 wherein the application is executed by the client computer system and the determining operation comprises: evaluating a constraint in the constraint expression against a configuration parameter of the client computer system. | 2. The method of claim 1 wherein the application is executed by the client computer system and the determining operation comprises: evaluating a constraint in the constraint expression against a configuration parameter of the client computer system. 4. The method of claim 2 wherein the configuration parameter of the client computer system indicates which processor architecture the client computer system supports. | 0.950083 |
1. A method, in a data processing system comprising a processor and a memory having instructions which, when executed by the processor, cause the processor to generate candidate answers to an explanatory question, the method comprising: responsive to identifying an input question as the explanatory question, decomposing, by the data processing system, the explanatory question into one or more explanatory queries; identifying, by the data processing system, one or more passages within a corpus of information that comprise an explanatory clause that provides an explanatory answer to the explanatory question based on pre-determined explanatory clause terms, wherein a passage within the one or more passages within the corpus of information that comprises the explanatory clause is identified by the method comprising: comparing, by the data processing system, each identified clause within a passage to a set of previously identified explanatory clauses; and responsive to the identified clause within a passage corresponding to one of the set of previously identified explanatory clauses, tagging, by the data processing system, the clause within the passage with an ‘EXPLANATORY’ tag; receiving, by the data processing system, hypothesis evidence with one or more passages comprising explanatory clauses from the corpus of information; generating, by the data processing system, one or more candidate explanatory answers based on hypothesis evidence; ranking and merging, by the data processing system, the one or more candidate explanatory answers; and outputting, by the data processing system, the one or more candidate explanatory answers. | 1. A method, in a data processing system comprising a processor and a memory having instructions which, when executed by the processor, cause the processor to generate candidate answers to an explanatory question, the method comprising: responsive to identifying an input question as the explanatory question, decomposing, by the data processing system, the explanatory question into one or more explanatory queries; identifying, by the data processing system, one or more passages within a corpus of information that comprise an explanatory clause that provides an explanatory answer to the explanatory question based on pre-determined explanatory clause terms, wherein a passage within the one or more passages within the corpus of information that comprises the explanatory clause is identified by the method comprising: comparing, by the data processing system, each identified clause within a passage to a set of previously identified explanatory clauses; and responsive to the identified clause within a passage corresponding to one of the set of previously identified explanatory clauses, tagging, by the data processing system, the clause within the passage with an ‘EXPLANATORY’ tag; receiving, by the data processing system, hypothesis evidence with one or more passages comprising explanatory clauses from the corpus of information; generating, by the data processing system, one or more candidate explanatory answers based on hypothesis evidence; ranking and merging, by the data processing system, the one or more candidate explanatory answers; and outputting, by the data processing system, the one or more candidate explanatory answers. 2. The method of claim 1 , wherein identifying the input question as the explanatory question comprises: comparing, by the data processing system, the input question to a set of annotated questions in order to identify whether or not the input question is seeking an explanation of an underlying reasoning as to the existence of a particular fact; and responsive to the input question corresponding to one of the set of annotated questions, tagging, by the data processing system, the input question as a ‘EXPLANATORY’ question. | 0.513545 |
13. The method of claim 12 , wherein: the generating of the data structure includes generating an average feature vector that corresponds to the text token and indicates the identified image feature is a component of the average feature vector of the text token. | 13. The method of claim 12 , wherein: the generating of the data structure includes generating an average feature vector that corresponds to the text token and indicates the identified image feature is a component of the average feature vector of the text token. 14. The method of claim 13 , wherein: the generating of the average feature vector is based on multiple image features identified from multiple item images that correspond to multiple item descriptions that are each inclusive of the text token. | 0.931679 |
1. A computer-implemented method of making a presentation of data requested by questions received via a user interface of a database, wherein: the questions include respective sets of data items that are categorized as measures, which represent amounts, or categorized as dimensions, along which the measures can be arrayed, sets of data items in said questions include one data item of the measures categories, and another data item of the dimensions categories, and associations are combinations of related data items in the measures categories and data items in the dimensions categories, said associations specifying respective sets of data in the database that correspond to the combinations of data items, the method comprising the following steps: parsing, from a question received from a user via the user interface, a first data item belonging to one of the measures categories and a second data item belonging to one of the dimensions categories; determining a first association between the first data item belonging to the category of measures and the second data item belonging to the category of dimensions; searching a plurality of stored associations in a data storage device to find a second association similar to the first association; identifying presentation properties stored in said data storage device that correspond to the second association; selecting presentation properties for the first association from the identified presentation properties corresponding to the second association, the selected presentation properties for the first association describing how to present the data items of the first association; querying, based on the received question, the database to provide a set of result data corresponding to the set of the data items in the first association; and generating a presentation of the set of result data using the identified presentation properties. | 1. A computer-implemented method of making a presentation of data requested by questions received via a user interface of a database, wherein: the questions include respective sets of data items that are categorized as measures, which represent amounts, or categorized as dimensions, along which the measures can be arrayed, sets of data items in said questions include one data item of the measures categories, and another data item of the dimensions categories, and associations are combinations of related data items in the measures categories and data items in the dimensions categories, said associations specifying respective sets of data in the database that correspond to the combinations of data items, the method comprising the following steps: parsing, from a question received from a user via the user interface, a first data item belonging to one of the measures categories and a second data item belonging to one of the dimensions categories; determining a first association between the first data item belonging to the category of measures and the second data item belonging to the category of dimensions; searching a plurality of stored associations in a data storage device to find a second association similar to the first association; identifying presentation properties stored in said data storage device that correspond to the second association; selecting presentation properties for the first association from the identified presentation properties corresponding to the second association, the selected presentation properties for the first association describing how to present the data items of the first association; querying, based on the received question, the database to provide a set of result data corresponding to the set of the data items in the first association; and generating a presentation of the set of result data using the identified presentation properties. 3. The method according to claim 1 , wherein the method includes: determining combinations of associations; and determining presentation properties by searching stored combinations of associations with assigned presentation properties. | 0.528106 |
1. A method for performing dual mode speech recognition, comprising: receiving at a device a query from a user; sending the query to a first recognition system; sending the query to a second recognition system; receiving at least a first recognition result from either the first recognition system or the second recognition system; producing a final result considering the first recognition result; and setting a latency timer to a timeout value, wherein the first recognition system maintains a first vocabulary and the second recognition system maintains a second vocabulary, and whereby the final result is produced at or before the time that the latency timer reaches the timeout value. | 1. A method for performing dual mode speech recognition, comprising: receiving at a device a query from a user; sending the query to a first recognition system; sending the query to a second recognition system; receiving at least a first recognition result from either the first recognition system or the second recognition system; producing a final result considering the first recognition result; and setting a latency timer to a timeout value, wherein the first recognition system maintains a first vocabulary and the second recognition system maintains a second vocabulary, and whereby the final result is produced at or before the time that the latency timer reaches the timeout value. 7. The method of claim 1 , further comprising: determining that the second vocabulary contains at least one word that is not contained in the first vocabulary. | 0.591916 |
6. A computer program product comprising one or more computer-readable physical storage media having thereon computer-executable instructions that are structured such that, when executed by one or more processors of a computing system, the computing system is caused to perform a method for identifying validation errors in a visual representation of a graphical model, the graphical model comprising one or more objects that include interrelationship, at least some of the objects capable of being visualized on a display, the method comprising: reading a constraint that comprises one or more rules that the graphical model must adhere to in order to comply with the declarative constraint, the one or more rules specifying how the graphical model should function, and the one or more rules specifying properties, parameters, and relationships that objects of the graphical model should adhere to; imposing the constraint on the graphical model; identifying an object in the graphical model that does not conform with one or more rules of the constraint imposed on the graphical model; reading a declarative definition of the graphical model to ascertain a declarative relationship between the non-conforming object of the graphical model and its visual representation that is rendered on a display, the declarative definition including shapes, types, connectors, and decorators; interpreting the declarative relationship between the non-conforming object of the graphical model and its visual representation to formulate underlying code that when executed causes the computing system to provide a visually distinct attribute related to the visual representation on the display; and causing the computing system to execute the underlying code. | 6. A computer program product comprising one or more computer-readable physical storage media having thereon computer-executable instructions that are structured such that, when executed by one or more processors of a computing system, the computing system is caused to perform a method for identifying validation errors in a visual representation of a graphical model, the graphical model comprising one or more objects that include interrelationship, at least some of the objects capable of being visualized on a display, the method comprising: reading a constraint that comprises one or more rules that the graphical model must adhere to in order to comply with the declarative constraint, the one or more rules specifying how the graphical model should function, and the one or more rules specifying properties, parameters, and relationships that objects of the graphical model should adhere to; imposing the constraint on the graphical model; identifying an object in the graphical model that does not conform with one or more rules of the constraint imposed on the graphical model; reading a declarative definition of the graphical model to ascertain a declarative relationship between the non-conforming object of the graphical model and its visual representation that is rendered on a display, the declarative definition including shapes, types, connectors, and decorators; interpreting the declarative relationship between the non-conforming object of the graphical model and its visual representation to formulate underlying code that when executed causes the computing system to provide a visually distinct attribute related to the visual representation on the display; and causing the computing system to execute the underlying code. 10. The computer program product in accordance with claim 6 , wherein the computer-readable physical storage media has thereon computer-executable instructions that, when executed by the one or more processors, further cause the computing system to perform the following: attaching a smart tag to the visual representation of the non-conforming object. | 0.626771 |
1. A method for managing inventory sales advertisement information by a host company over a network, comprising the steps of: a. forming an inventory advertisement based information network having at least two tiers of access with at least one host server and at least one remote company user I/O device; b. configuring the host server with an interactive inventory listing builder for generating inventory listings; c. configuring the host server to manage remote company user access to the inventory listings; and d. enabling remote access to the at least one host server for the remote company user to create and manage inventory listings. | 1. A method for managing inventory sales advertisement information by a host company over a network, comprising the steps of: a. forming an inventory advertisement based information network having at least two tiers of access with at least one host server and at least one remote company user I/O device; b. configuring the host server with an interactive inventory listing builder for generating inventory listings; c. configuring the host server to manage remote company user access to the inventory listings; and d. enabling remote access to the at least one host server for the remote company user to create and manage inventory listings. 4. The method of claim 1 , wherein: a. the host company further distributes print advertisements from the inventory listings generated. | 0.677481 |
140. The system of claim 139 , wherein the term of experience is rounded down to a unit of time. | 140. The system of claim 139 , wherein the term of experience is rounded down to a unit of time. 143. The system of claim 140 , wherein the unit of time is not an integer. | 0.982119 |
8. A non-transitory computer-readable medium storing instructions that are configured to cause one or more processors to: receive, at a task completion service, an input comprising information in a natural language; determine, at a dialog manager of the task completion service, an intent of the input; determine, at the dialog manager, target information to fulfill the intent; identify, at the dialog manager, one or both of information among the target information that is available to the dialog manager or information among the target information that is not available to the dialog manager; generate a conversational understanding document comprising the intent and the identified information; and forward the conversational understanding document to a task completion handler separate from the dialog manager. | 8. A non-transitory computer-readable medium storing instructions that are configured to cause one or more processors to: receive, at a task completion service, an input comprising information in a natural language; determine, at a dialog manager of the task completion service, an intent of the input; determine, at the dialog manager, target information to fulfill the intent; identify, at the dialog manager, one or both of information among the target information that is available to the dialog manager or information among the target information that is not available to the dialog manager; generate a conversational understanding document comprising the intent and the identified information; and forward the conversational understanding document to a task completion handler separate from the dialog manager. 9. The non-transitory medium of claim 8 , further storing instructions configured to cause the one or more processors to select, at the task completion handler, missing information from among the identified information, and guide, at the task completion handler, a conversation to request the selected information, wherein the updated information is received by the dialog manager in response to the conversation requesting the selected information. | 0.526681 |
7. A non-transitory computer readable storage medium storing a plurality of instructions configured for execution by a computing device with one or more processors and a touch-sensitive display screen, the plurality of instructions comprising instructions that when executed cause the computing device to: display a first panel of a split keyboard in a first region of the touch-sensitive display screen, the first region of the touch-sensitive display screen being positioned along a first side of the touch-sensitive display screen, wherein the first panel includes a plurality of character keys from a first side of a respective keyboard; display a second panel of the split keyboard in a second region of the touch-sensitive display screen, the second region of the touch-sensitive display screen being positioned along a second side of the touch-sensitive display screen different from the first side, wherein the second panel includes a plurality of character keys from a second side of the respective keyboard; receive, via the first panel of the split keyboard and the second panel of the split keyboard, character input; and display a vertical candidate bar adjacent to the first panel of the split keyboard, between the first panel of the split keyboard and an edge of the touch-sensitive display screen on the first side of the touch-sensitive display screen, the vertical candidate bar having a single column of one or more candidates determined based on the character input. | 7. A non-transitory computer readable storage medium storing a plurality of instructions configured for execution by a computing device with one or more processors and a touch-sensitive display screen, the plurality of instructions comprising instructions that when executed cause the computing device to: display a first panel of a split keyboard in a first region of the touch-sensitive display screen, the first region of the touch-sensitive display screen being positioned along a first side of the touch-sensitive display screen, wherein the first panel includes a plurality of character keys from a first side of a respective keyboard; display a second panel of the split keyboard in a second region of the touch-sensitive display screen, the second region of the touch-sensitive display screen being positioned along a second side of the touch-sensitive display screen different from the first side, wherein the second panel includes a plurality of character keys from a second side of the respective keyboard; receive, via the first panel of the split keyboard and the second panel of the split keyboard, character input; and display a vertical candidate bar adjacent to the first panel of the split keyboard, between the first panel of the split keyboard and an edge of the touch-sensitive display screen on the first side of the touch-sensitive display screen, the vertical candidate bar having a single column of one or more candidates determined based on the character input. 8. The computer readable storage medium of claim 7 , wherein the plurality of instructions include instructions that when executed cause the computing device to: display content on the touch-sensitive display screen, wherein the first panel of the split keyboard and the second panel of the split keyboard are displayed as an overlay over at least a portion of the content. | 0.619085 |
24. The computer system of claim 14 wherein the code is further executable by the processor for: dividing a consolidated configuration model into the configuration sub-models. | 24. The computer system of claim 14 wherein the code is further executable by the processor for: dividing a consolidated configuration model into the configuration sub-models. 26. The computer system of claim 24 wherein each configuration sub-model represents a portion of the consolidated configuration model. | 0.938329 |
1. A computer-implemented method for generating multiple implicit search queries comprising: identifying a plurality of events responsive to monitoring real-time user interactions with a client device; identifying a plurality of user-context attributes based at least in part on the plurality of events, wherein the plurality of user-context attributes indicate aspects of the real-time user interactions with the client device; generating a plurality of implicit search queries comprising terms, wherein the terms are based at least in part on the plurality of user-context attributes; receiving a plurality of search results generated responsive to the plurality of implicit search queries; and updating a display of search results responsive to receiving the plurality of search results. | 1. A computer-implemented method for generating multiple implicit search queries comprising: identifying a plurality of events responsive to monitoring real-time user interactions with a client device; identifying a plurality of user-context attributes based at least in part on the plurality of events, wherein the plurality of user-context attributes indicate aspects of the real-time user interactions with the client device; generating a plurality of implicit search queries comprising terms, wherein the terms are based at least in part on the plurality of user-context attributes; receiving a plurality of search results generated responsive to the plurality of implicit search queries; and updating a display of search results responsive to receiving the plurality of search results. 42. The method of claim 1 , wherein the event comprises receiving a text buffer and the user-context attribute comprises one or more words in the text buffer, wherein the one or more words are near a position of a cursor. | 0.707143 |
1. A computer-implemented method comprising: identifying, by a computer system, a plurality of comments associated with a media content item; generating, by the computer system for each of the plurality of comments, a sentiment score indicating a likelihood that the comment expresses a type of sentiment; adjusting, by the computer system, the sentiment score generated for a comment from the plurality of comments based on information associated with a user that provided the comment from the plurality of comments, the information describing sentiment expressed by the user in additional comments for additional media content items; determining, by the computer system, an aggregate score for the media content item based on the sentiment scores for the plurality of comments; receiving, by the computer system from a device, a search query searching for media content associated with the type of sentiment; responsive to receiving the search query, identifying, by the computer system, the media content item based on the aggregate score indicating that comments associated with the media content item express the type of sentiment; and providing, by the computer system to the device, search results including the media content item. | 1. A computer-implemented method comprising: identifying, by a computer system, a plurality of comments associated with a media content item; generating, by the computer system for each of the plurality of comments, a sentiment score indicating a likelihood that the comment expresses a type of sentiment; adjusting, by the computer system, the sentiment score generated for a comment from the plurality of comments based on information associated with a user that provided the comment from the plurality of comments, the information describing sentiment expressed by the user in additional comments for additional media content items; determining, by the computer system, an aggregate score for the media content item based on the sentiment scores for the plurality of comments; receiving, by the computer system from a device, a search query searching for media content associated with the type of sentiment; responsive to receiving the search query, identifying, by the computer system, the media content item based on the aggregate score indicating that comments associated with the media content item express the type of sentiment; and providing, by the computer system to the device, search results including the media content item. 5. The method of claim 1 , wherein the aggregate score is determined by selecting a top percentile of the sentiment scores for the plurality of comments. | 0.808933 |
12. A computer-readable storage medium having computer-executable instructions for performing steps comprising: allowing, at a computing device, a user to select a document style from document styles of a document in a first column portion and a corresponding style from styles of a web page in a second column portion on a same interface which the first and second column portions are presented; allowing the user to choose between styles that are used to transform the document, the styles including a first style that approximates formatting of the document, a second style that maps the document to particular style of the web page, and a third style that transforms an extensible markup language (XML) document to the web page; allowing the user to select between different layout templates to define how the web page is rendered; allowing the user to choose to create and store the web page in a current publishing site or to select a publishing site; mapping the document styles in a document to the styles of the web page; extracting resources from the document; storing the extracted resources at a location defined by a content type; assigning each of the extracted resources a name to uniquely identify each resource; converting contents of the document into hypertext markup language based on the mapping; rendering the web page based on the hypertext markup language; and outputting the web page. | 12. A computer-readable storage medium having computer-executable instructions for performing steps comprising: allowing, at a computing device, a user to select a document style from document styles of a document in a first column portion and a corresponding style from styles of a web page in a second column portion on a same interface which the first and second column portions are presented; allowing the user to choose between styles that are used to transform the document, the styles including a first style that approximates formatting of the document, a second style that maps the document to particular style of the web page, and a third style that transforms an extensible markup language (XML) document to the web page; allowing the user to select between different layout templates to define how the web page is rendered; allowing the user to choose to create and store the web page in a current publishing site or to select a publishing site; mapping the document styles in a document to the styles of the web page; extracting resources from the document; storing the extracted resources at a location defined by a content type; assigning each of the extracted resources a name to uniquely identify each resource; converting contents of the document into hypertext markup language based on the mapping; rendering the web page based on the hypertext markup language; and outputting the web page. 13. The computer-readable storage medium of claim 12 , further comprising: creating the document; and uploading the document to a server. | 0.676444 |
34. The method as recited in claim 27 , further comprising plugging a different pluggable converter module into the framework, wherein the different converter module is configured to convert office documents in a different office document format to and from small device documents in a different small device format. | 34. The method as recited in claim 27 , further comprising plugging a different pluggable converter module into the framework, wherein the different converter module is configured to convert office documents in a different office document format to and from small device documents in a different small device format. 38. The method as recited in claim 34 , further comprising plugging a pluggable merger module into the framework, wherein the merger module is configured to merge modified versions of small device documents in the different small device format with corresponding office documents in the different office document format to generate synchronized versions of the office documents. | 0.879821 |
12. A computer-implemented method for managing comment data generated when interacting with a page module, the computer-implemented method comprising: detecting at least one comment data being expressed when interacting with the page module, the comment data being text; analyzing content of the comment data to identify a context for the comment data; if the comment data is identified to be associated with a context based on the analyzing, tagging the comment data with a context association, and if the comment data is not associated with a context then maintaining the comment data associated only with the page module; and carrying over the comment data as text to one or more other page modules that were identified to have the context association with the comment data; wherein the populating enables display presentation of the comment data aggregated at the page module and carried over to one or more page modules having the context association; wherein the page module and the related page modules each have a subject context that is contextually related to a word. | 12. A computer-implemented method for managing comment data generated when interacting with a page module, the computer-implemented method comprising: detecting at least one comment data being expressed when interacting with the page module, the comment data being text; analyzing content of the comment data to identify a context for the comment data; if the comment data is identified to be associated with a context based on the analyzing, tagging the comment data with a context association, and if the comment data is not associated with a context then maintaining the comment data associated only with the page module; and carrying over the comment data as text to one or more other page modules that were identified to have the context association with the comment data; wherein the populating enables display presentation of the comment data aggregated at the page module and carried over to one or more page modules having the context association; wherein the page module and the related page modules each have a subject context that is contextually related to a word. 15. The computer-implemented method for managing comment data as recited in claim 12 , wherein the analyzing includes looking up stored relationships in a relational database. | 0.56217 |
1. A method for populating one or more search indexes with atoms identified in a plurality of documents, the method comprising: identifying a set of documents to be indexed in a search index; for each document in the set of documents, identifying a plurality of atoms, the plurality of atoms comprising one or more unigrams, one or more n-grams, and one or more n-tuples; based on the identified set of documents and the plurality of atoms, generating a list of atom/document pairs; computing an information metric for each atom/document pair, wherein the information metric represents a pre-computed ranking of the atom used during a search query in relation to the particular document; based on the information metric for each atom/document pair, selecting a subset of the atom/document pairs that are most relevant to the particular document from which the atoms were identified; populating the search index using the subset of the atom/document pairs for the particular document, wherein identifying relevant documents for the search query from the search index is based on a pruning algorithm that computes a preliminary score for each of the documents to select a subset of the set of documents based on the preliminary score, wherein the preliminary score is computed using the information metric pre-computed for each atom/document pair and a simplified scoring function that approximates a final ranking algorithm utilized in identifying the relevant documents. | 1. A method for populating one or more search indexes with atoms identified in a plurality of documents, the method comprising: identifying a set of documents to be indexed in a search index; for each document in the set of documents, identifying a plurality of atoms, the plurality of atoms comprising one or more unigrams, one or more n-grams, and one or more n-tuples; based on the identified set of documents and the plurality of atoms, generating a list of atom/document pairs; computing an information metric for each atom/document pair, wherein the information metric represents a pre-computed ranking of the atom used during a search query in relation to the particular document; based on the information metric for each atom/document pair, selecting a subset of the atom/document pairs that are most relevant to the particular document from which the atoms were identified; populating the search index using the subset of the atom/document pairs for the particular document, wherein identifying relevant documents for the search query from the search index is based on a pruning algorithm that computes a preliminary score for each of the documents to select a subset of the set of documents based on the preliminary score, wherein the preliminary score is computed using the information metric pre-computed for each atom/document pair and a simplified scoring function that approximates a final ranking algorithm utilized in identifying the relevant documents. 4. The method of claim 1 , wherein an n-gram is a sequence of consecutive or almost consecutive terms extracted from a particular document, wherein n is a quantity of consecutive terms. | 0.772563 |
1. A computer-implemented method comprising computer-executable instructions, the method comprising: accessing information that a user is currently working with, wherein the information that the user is currently working with comprises at least one of a current email application, a currently browsed web page, a current instant message, or a current RSS feed the user is browsing; extracting one or more keywords from the information, by utilizing term frequency-inverse document frequency techniques to identify keywords; suppressing one or more extracted keywords by utilizing a feedback loop, wherein the feedback loop enables the one or more keywords to be suppressed for a period of time when the one or more keywords fail to result in a sponsored ad; calculating a term frequency by dividing a number of occurrences of a word or a collection of words by a number of occurrences of terms in the information that the user is currently working with; calculating an inverse document frequency by calculating a logarithm of the number of documents divided by the number of documents containing an identified keyword; calculating the term frequency-inverse document frequency by multiplying the term frequency by the inverse document frequency; determining the identified keyword based in part on a high weight in the term frequency-inverse document frequency; ascertaining whether the keywords likely constitute search terms, wherein the act of ascertaining comprises performing one or more of: removing one or more tag lines, or removing one or more header lines; based at least in part on said ascertaining, displaying selected keywords for the user; and displaying supplemental information that is related to at least one displayed keyword, wherein the acts of displaying selected keywords and supplemental information comprise displaying the selected keywords and the supplemental information alongside the information that the user is currently working with. | 1. A computer-implemented method comprising computer-executable instructions, the method comprising: accessing information that a user is currently working with, wherein the information that the user is currently working with comprises at least one of a current email application, a currently browsed web page, a current instant message, or a current RSS feed the user is browsing; extracting one or more keywords from the information, by utilizing term frequency-inverse document frequency techniques to identify keywords; suppressing one or more extracted keywords by utilizing a feedback loop, wherein the feedback loop enables the one or more keywords to be suppressed for a period of time when the one or more keywords fail to result in a sponsored ad; calculating a term frequency by dividing a number of occurrences of a word or a collection of words by a number of occurrences of terms in the information that the user is currently working with; calculating an inverse document frequency by calculating a logarithm of the number of documents divided by the number of documents containing an identified keyword; calculating the term frequency-inverse document frequency by multiplying the term frequency by the inverse document frequency; determining the identified keyword based in part on a high weight in the term frequency-inverse document frequency; ascertaining whether the keywords likely constitute search terms, wherein the act of ascertaining comprises performing one or more of: removing one or more tag lines, or removing one or more header lines; based at least in part on said ascertaining, displaying selected keywords for the user; and displaying supplemental information that is related to at least one displayed keyword, wherein the acts of displaying selected keywords and supplemental information comprise displaying the selected keywords and the supplemental information alongside the information that the user is currently working with. 3. The method of claim 1 , wherein the act of displaying selected keywords comprises removing duplicate words that are found to be similar. | 0.552671 |
1. A system for assessing the selectivity of categorization rules, the system comprising: a computer system including at least one processor, a non-transitory data storage medium interfaced with the at least one processor, and input/output facilities, the data storage medium containing instructions that, when executed by the at least one processor, implement: a categorization rule application engine configured to apply at least one categorization rule to a set of un-categorized objects to produce a categorization result set representing assignment of objects of the set into at least two categories into which the objects of the set are divided when the categorization rule is applied, the categorization rule application engine further configured to gather statistical information relating to the categorization result set based on properties of objects assigned to each of the at least two categories, and including at least one rule-specific aggregating statistic characterizing the application of to the categorization rule to all of the objects and at least one categorization-specific statistic characterizing the objects of one of the at least two categories; a selectivity determination engine configured to assess a numerical selectivity score for the at least one categorization rule, the numerical selectivity score representing an estimation of selectivity accuracy of the at least one categorization rule to provide an evaluation of the at least one categorization rule, the numerical selectivity score being calculated by the application of at least one trained selectivity determination algorithm to the statistical information including the at least one rule-specific aggregating statistic representing information on the set of files belonging to each of the categories defined in the categorization rule, the application of the at least one trained selectivity determination algorithm to the statistical information including considering each of a plurality of parameters derived from the statistical information and in accordance with the at least one categorization rule, and compare the selectivity score against a predefined selectivity threshold, wherein a selectivity score that exceeds the selectivity threshold is deemed highly selective; and an algorithm training engine configured to produce each of the at least one trained selectivity determination algorithm based on application of a plurality of specially-selected categorization rules to a set of pre-categorized training data, wherein the application of each one of the specially-selected categorization rules to the set of training data produces at least one uniform grouping of objects in which the objects all meet a predefined similarity criterion, and wherein the trained selectivity determination algorithms are unrelated to the plurality of specially-selected categorization rules. | 1. A system for assessing the selectivity of categorization rules, the system comprising: a computer system including at least one processor, a non-transitory data storage medium interfaced with the at least one processor, and input/output facilities, the data storage medium containing instructions that, when executed by the at least one processor, implement: a categorization rule application engine configured to apply at least one categorization rule to a set of un-categorized objects to produce a categorization result set representing assignment of objects of the set into at least two categories into which the objects of the set are divided when the categorization rule is applied, the categorization rule application engine further configured to gather statistical information relating to the categorization result set based on properties of objects assigned to each of the at least two categories, and including at least one rule-specific aggregating statistic characterizing the application of to the categorization rule to all of the objects and at least one categorization-specific statistic characterizing the objects of one of the at least two categories; a selectivity determination engine configured to assess a numerical selectivity score for the at least one categorization rule, the numerical selectivity score representing an estimation of selectivity accuracy of the at least one categorization rule to provide an evaluation of the at least one categorization rule, the numerical selectivity score being calculated by the application of at least one trained selectivity determination algorithm to the statistical information including the at least one rule-specific aggregating statistic representing information on the set of files belonging to each of the categories defined in the categorization rule, the application of the at least one trained selectivity determination algorithm to the statistical information including considering each of a plurality of parameters derived from the statistical information and in accordance with the at least one categorization rule, and compare the selectivity score against a predefined selectivity threshold, wherein a selectivity score that exceeds the selectivity threshold is deemed highly selective; and an algorithm training engine configured to produce each of the at least one trained selectivity determination algorithm based on application of a plurality of specially-selected categorization rules to a set of pre-categorized training data, wherein the application of each one of the specially-selected categorization rules to the set of training data produces at least one uniform grouping of objects in which the objects all meet a predefined similarity criterion, and wherein the trained selectivity determination algorithms are unrelated to the plurality of specially-selected categorization rules. 9. The system of claim 1 , wherein the properties of objects assigned to each of the at least two categories on which the categorization result set is based include at least one set of properties selected from the group consisting of: unique compilers used to create objects categorized into a category by application of a categorization rule, unique packagers used to create objects categorized into a category by application of a categorization rule, or any combination thereof. | 0.513751 |
8. A system comprising: a storage device configured to store a database; and a processing device configured to receive a request from a request processor of a database connection pool to access the database, to determine whether a database connection from the database connection pool is available for the request, each database connection based on a first security assertion mark-up language (SAML) assertion, to generate a second SAML, assertion in response to determining that the database connection pool does not have an available database connection for the request, to build a new database connection to the database using the second SAML, assertion based on updated credentials from the first SAML assertion; and maintaining existing database connections that are based on the first SAML assertion open a life cycle of the new database connection independent from a life cycle of the second SAML assertion. | 8. A system comprising: a storage device configured to store a database; and a processing device configured to receive a request from a request processor of a database connection pool to access the database, to determine whether a database connection from the database connection pool is available for the request, each database connection based on a first security assertion mark-up language (SAML) assertion, to generate a second SAML, assertion in response to determining that the database connection pool does not have an available database connection for the request, to build a new database connection to the database using the second SAML, assertion based on updated credentials from the first SAML assertion; and maintaining existing database connections that are based on the first SAML assertion open a life cycle of the new database connection independent from a life cycle of the second SAML assertion. 14. The system of claim 8 , wherein the database connection pool comprises a plurality of request processors, each request processor having a corresponding database connection to the database based on their corresponding SAML assertion. | 0.662025 |
18. The computer-implemented method according to claim 17 , further comprising: assigning a value to the activation attribute. | 18. The computer-implemented method according to claim 17 , further comprising: assigning a value to the activation attribute. 20. The computer-implemented method according to claim 18 , wherein modeling the context representation includes varying in a time dependent manner the value of the activation attribute of the at least one context entity. | 0.932581 |
1. An audio system, comprising: a filtered volume determiner configured to receive a first signal, wherein the filtered volume determiner is configured to generate a second signal corresponding to a volume envelope for a first range of selected frequencies of the first signal; a filtered noise generator configured to generate a third signal corresponding to noise substantially within a second range of selected frequencies; a signal modulator, coupled to the filtered volume determiner and to the filtered noise generator, wherein the signal modulator is configured to receive from the filtered volume determiner the second signal, and wherein the signal modulator is configured to receive from the filtered noise generator the third signal, and wherein the signal modulator is configured to generate a fourth signal substantially similar to a product of a weighted second signal and a weighted third signal; a mixer, coupled to the signal modulator, wherein the mixer is configured to receive from the signal modulator the fourth signal, and wherein the mixer is configured to receive a fifth signal substantially similar to the first signal, and wherein the mixer is configured to generate a sixth signal substantially similar to a sum of a weighted fourth signal and a weighted fifth signal, and an output filter coupled to the mixer to receive the sixth signal and generate a seventh signal substantially within a third range of selected frequencies. | 1. An audio system, comprising: a filtered volume determiner configured to receive a first signal, wherein the filtered volume determiner is configured to generate a second signal corresponding to a volume envelope for a first range of selected frequencies of the first signal; a filtered noise generator configured to generate a third signal corresponding to noise substantially within a second range of selected frequencies; a signal modulator, coupled to the filtered volume determiner and to the filtered noise generator, wherein the signal modulator is configured to receive from the filtered volume determiner the second signal, and wherein the signal modulator is configured to receive from the filtered noise generator the third signal, and wherein the signal modulator is configured to generate a fourth signal substantially similar to a product of a weighted second signal and a weighted third signal; a mixer, coupled to the signal modulator, wherein the mixer is configured to receive from the signal modulator the fourth signal, and wherein the mixer is configured to receive a fifth signal substantially similar to the first signal, and wherein the mixer is configured to generate a sixth signal substantially similar to a sum of a weighted fourth signal and a weighted fifth signal, and an output filter coupled to the mixer to receive the sixth signal and generate a seventh signal substantially within a third range of selected frequencies. 8. The audio system of claim 1 , wherein the second range of selected frequencies comprises frequencies for which a user's audiometric thresholds are less than a threshold for severe hearing loss. | 0.595694 |
1. A computer implemented method comprising: for each of a plurality of members of a social networking system, maintaining a respective set of connections to other members of the social networking system; receiving translations of text phrases from members of the social network, the text phrases comprising content displayed in a social networking system; providing content to a particular member, the content including a text phrase in a first language; responsive to receiving a request from the particular member to translate the text phrase from the first language to a second language: selecting, by a computer system, a translation of the text phrase from a set of translations of the text phrase in the second language, wherein the selecting is based on one or more actions by one or more other members identified in the set of connections for the particular member maintained by the social networking system, wherein the actions are associated with translations from the set of translations; and presenting the selected translation of the text phrase to the member requesting the translation. | 1. A computer implemented method comprising: for each of a plurality of members of a social networking system, maintaining a respective set of connections to other members of the social networking system; receiving translations of text phrases from members of the social network, the text phrases comprising content displayed in a social networking system; providing content to a particular member, the content including a text phrase in a first language; responsive to receiving a request from the particular member to translate the text phrase from the first language to a second language: selecting, by a computer system, a translation of the text phrase from a set of translations of the text phrase in the second language, wherein the selecting is based on one or more actions by one or more other members identified in the set of connections for the particular member maintained by the social networking system, wherein the actions are associated with translations from the set of translations; and presenting the selected translation of the text phrase to the member requesting the translation. 7. The method of claim 1 , wherein the selecting is based on which of the translations from the set of translations were rejected by the one or more other members connected to the particular member, the rejecting of a translation comprising a member connected to the particular member requesting an alternate translation after viewing the translation. | 0.575174 |
11. A method for providing annotated video content comprising: receiving a video content; identifying one or more objects in the video content using object recognition; generating one or more language tags for at least one of the one or more objects; and annotating the video content by overlaying the one of more language tags on the video content in a way as to label the at least one of the or more objects in the video content; and providing the video content annotated with language tags to a user device over a network. | 11. A method for providing annotated video content comprising: receiving a video content; identifying one or more objects in the video content using object recognition; generating one or more language tags for at least one of the one or more objects; and annotating the video content by overlaying the one of more language tags on the video content in a way as to label the at least one of the or more objects in the video content; and providing the video content annotated with language tags to a user device over a network. 12. The method of claim 11 , wherein the annotating of the video content is based on user settings. | 0.67166 |
1. In a system including a television and a video transmission medium, wherein interactive broadcast data text descriptions such as electronic program guide information, news headlines, sports scores, or other similar kinds of periodically updated information that can be displayed as text simultaneously with other programming is transmitted across the video transmission medium, and wherein the system also includes a management system having a digital processor for processing one or more unique digital signatures that correspond to the interactive broadcast data, and an input device for inputting other digital data that corresponds to user instructions input by a user when searching for particular interactive broadcast data, a method for efficiently searching the interactive broadcast data in response to a string of text input by a user in order to identify the particular interactive broadcast data desired by the user, the method comprising: receiving interactive broadcast data at the management system, said interactive broadcast data having unique binary signatures, each unique binary signature generated for an electronic program guide entry using programming information from a plurality of information fields of the electronic program guide entry, wherein each of the unique binary signatures is created prior to transmission across the video transmission medium using a first function adapted to convert alphanumeric text in fields of the electronic program guide entries into unique binary signatures having a fixed number of bytes, wherein at least one of the unique binary signatures includes a plurality of distinct four bit binary representations corresponding to a plurality of distinct terms found within a single electronic program guide entry, with each of the distinct four bit binary representations in the unique binary signature corresponding to a distinct term, and with all of the distinct four bit binary representations being concatenated into a single binary signature comprising the fixed number of bytes, storing the unique binary signatures at the management system; receiving a first user-entered text string; using a second function to convert the first user-entered text string into a unique binary signature; retrieving and comparing the stored unique binary signatures corresponding to the interactive broadcast data text descriptions to the unique binary signature of the user-entered text string; and based on the comparison, the management system identifying at least one item of interactive broadcast data that matches the user-entered text string. | 1. In a system including a television and a video transmission medium, wherein interactive broadcast data text descriptions such as electronic program guide information, news headlines, sports scores, or other similar kinds of periodically updated information that can be displayed as text simultaneously with other programming is transmitted across the video transmission medium, and wherein the system also includes a management system having a digital processor for processing one or more unique digital signatures that correspond to the interactive broadcast data, and an input device for inputting other digital data that corresponds to user instructions input by a user when searching for particular interactive broadcast data, a method for efficiently searching the interactive broadcast data in response to a string of text input by a user in order to identify the particular interactive broadcast data desired by the user, the method comprising: receiving interactive broadcast data at the management system, said interactive broadcast data having unique binary signatures, each unique binary signature generated for an electronic program guide entry using programming information from a plurality of information fields of the electronic program guide entry, wherein each of the unique binary signatures is created prior to transmission across the video transmission medium using a first function adapted to convert alphanumeric text in fields of the electronic program guide entries into unique binary signatures having a fixed number of bytes, wherein at least one of the unique binary signatures includes a plurality of distinct four bit binary representations corresponding to a plurality of distinct terms found within a single electronic program guide entry, with each of the distinct four bit binary representations in the unique binary signature corresponding to a distinct term, and with all of the distinct four bit binary representations being concatenated into a single binary signature comprising the fixed number of bytes, storing the unique binary signatures at the management system; receiving a first user-entered text string; using a second function to convert the first user-entered text string into a unique binary signature; retrieving and comparing the stored unique binary signatures corresponding to the interactive broadcast data text descriptions to the unique binary signature of the user-entered text string; and based on the comparison, the management system identifying at least one item of interactive broadcast data that matches the user-entered text string. 17. The method of claim 1 , wherein the unique binary signatures for the interactive broadcast data are created prior to transmission to the management system. | 0.565152 |
1. A method performed at an electronic device having a display and a touch-sensitive surface, comprising: displaying at least a portion of an electronic document that includes a first region; detecting a gesture on the touch-sensitive surface, wherein the gesture comprises an initial portion comprising touchdown of a contact on the touch-sensitive surface, and a subsequent portion after the touchdown; determining whether the initial portion of the gesture is detected at a location corresponding to the first region of the electronic document; in response to determining that the initial portion of the gesture is detected at a location corresponding to the first region of the electronic document, selecting a first dynamic disambiguation threshold used to determine whether to perform navigation or annotation; in response to detecting movement of the contact: in accordance with a determination that the initial portion of the gesture is detected at the first region of the electronic document and that the subsequent portion of the gesture satisfies the first dynamic disambiguation threshold, performing a navigation operation on the electronic document; and in accordance with a determination that the initial portion of the gesture is detected at the first region of the electronic document and that the subsequent portion of the gesture does not satisfy the first dynamic disambiguation threshold, performing an annotation operation on the electronic document. | 1. A method performed at an electronic device having a display and a touch-sensitive surface, comprising: displaying at least a portion of an electronic document that includes a first region; detecting a gesture on the touch-sensitive surface, wherein the gesture comprises an initial portion comprising touchdown of a contact on the touch-sensitive surface, and a subsequent portion after the touchdown; determining whether the initial portion of the gesture is detected at a location corresponding to the first region of the electronic document; in response to determining that the initial portion of the gesture is detected at a location corresponding to the first region of the electronic document, selecting a first dynamic disambiguation threshold used to determine whether to perform navigation or annotation; in response to detecting movement of the contact: in accordance with a determination that the initial portion of the gesture is detected at the first region of the electronic document and that the subsequent portion of the gesture satisfies the first dynamic disambiguation threshold, performing a navigation operation on the electronic document; and in accordance with a determination that the initial portion of the gesture is detected at the first region of the electronic document and that the subsequent portion of the gesture does not satisfy the first dynamic disambiguation threshold, performing an annotation operation on the electronic document. 8. The method of claim 1 , further comprising: in response to determining that the initial portion of the gesture is detected at a location corresponding to a second region of the electronic document, selecting a second dynamic disambiguation threshold used to determine whether to perform navigation or annotation. | 0.569785 |
11. A system for annotating a stimulus comprising: an image capture device; and a computer coupled to the image capture device, wherein the computer executes an annotation generation module that interacts with the image capture device, and wherein the annotation generation module comprises logic for performing the steps of: detecting a plurality of facial expressions in an audience of the stimulus; interpreting the facial expressions to estimate a mood for a time period of the stimulus, wherein interpreting the facial expressions comprises: classifying each of the facial expressions as corresponding to an emotion from a set of emotions; and statistically analyzing the respective emotions corresponding to the plurality of facial expressions to estimate the mood; generating an annotation of the stimulus based on the mood estimated; repeating the measuring, interpreting, and generating steps to produce a plurality of the annotations that respectively correspond to different time periods of the stimulus; and indexing the annotations according to the respective moods, wherein the indexing provides a two-way linkage between the annotations and the time periods of the stimulus. | 11. A system for annotating a stimulus comprising: an image capture device; and a computer coupled to the image capture device, wherein the computer executes an annotation generation module that interacts with the image capture device, and wherein the annotation generation module comprises logic for performing the steps of: detecting a plurality of facial expressions in an audience of the stimulus; interpreting the facial expressions to estimate a mood for a time period of the stimulus, wherein interpreting the facial expressions comprises: classifying each of the facial expressions as corresponding to an emotion from a set of emotions; and statistically analyzing the respective emotions corresponding to the plurality of facial expressions to estimate the mood; generating an annotation of the stimulus based on the mood estimated; repeating the measuring, interpreting, and generating steps to produce a plurality of the annotations that respectively correspond to different time periods of the stimulus; and indexing the annotations according to the respective moods, wherein the indexing provides a two-way linkage between the annotations and the time periods of the stimulus. 14. The system of claim 11 , wherein detecting a plurality of facial expressions comprises: scanning the audience in real time; and detecting face locations in the audience. | 0.553517 |
1. A position estimation device, comprising: a processor and associated program memory, the processor being programmed to execute: mathematical expression model processing that: i. obtains attitude information and positioning information indicating an attitude and a measured position of a mobile object from sensors; and ii. calculates a position of the mobile object, a condition quantity indicating a moving condition of the mobile object, and an error in the condition quantity through filtering processing executed by using a probability model based upon the attitude information, the positioning information, and a specific mathematical expression model among a plurality of mathematical expression models expressing behavior of the mobile object, which are acquired in advance, the specific mathematical expression model being selected based upon a threshold value; threshold calculation that calculates a threshold candidate value based upon the error having been calculated by the mathematical expression model processing, wherein the threshold candidate value represents a value of the condition quantity at which a plurality of mathematical expression models intersect; threshold value setting that updates the threshold value based upon the threshold candidate value; and mathematical expression model selection that selects the specific mathematical expression model to be used in a next stage of mathematical expression model processing from among the plurality of mathematical expression models, based upon the threshold value updated by the threshold value setting. | 1. A position estimation device, comprising: a processor and associated program memory, the processor being programmed to execute: mathematical expression model processing that: i. obtains attitude information and positioning information indicating an attitude and a measured position of a mobile object from sensors; and ii. calculates a position of the mobile object, a condition quantity indicating a moving condition of the mobile object, and an error in the condition quantity through filtering processing executed by using a probability model based upon the attitude information, the positioning information, and a specific mathematical expression model among a plurality of mathematical expression models expressing behavior of the mobile object, which are acquired in advance, the specific mathematical expression model being selected based upon a threshold value; threshold calculation that calculates a threshold candidate value based upon the error having been calculated by the mathematical expression model processing, wherein the threshold candidate value represents a value of the condition quantity at which a plurality of mathematical expression models intersect; threshold value setting that updates the threshold value based upon the threshold candidate value; and mathematical expression model selection that selects the specific mathematical expression model to be used in a next stage of mathematical expression model processing from among the plurality of mathematical expression models, based upon the threshold value updated by the threshold value setting. 2. A position estimation device according to claim 1 , wherein: restrictions imposed with regard to a valid range within which each of the plurality of mathematical expression models expressing the behavior is applicable to the behavior, are defined based upon information that can be collected through observation made from outside or based upon the position, the condition quantity and the error calculated by the mathematical expression model processing; the threshold value determining determines the threshold value based upon values representing extents of the error calculated each in correspondence to one of the plurality of mathematical expression models; and the mathematical expression model selection selects the specific mathematical expression model in correspondence to the restrictions. | 0.5 |
1. A method comprising, by one or more computing devices: receiving from a first user of an online social network an unstructured text query, the online social network being associated with a social graph comprising a plurality of nodes and a plurality of edges connecting the nodes; parsing the text query to identify one or more n-grams; determining a score for each n-gram that the n-gram corresponds to an edge or a node, wherein the score for each n-gram is a probability that the n-gram corresponds to an edge or a node; identifying one or more edges and one or more nodes based on their scores, each identified node and identified edge corresponding to at least one of the n-grams, each of the identified nodes being connected to at least one of the identified edges; and generating one or more structured queries that each comprise references to one or more of the identified edges and one or more of the identified nodes. | 1. A method comprising, by one or more computing devices: receiving from a first user of an online social network an unstructured text query, the online social network being associated with a social graph comprising a plurality of nodes and a plurality of edges connecting the nodes; parsing the text query to identify one or more n-grams; determining a score for each n-gram that the n-gram corresponds to an edge or a node, wherein the score for each n-gram is a probability that the n-gram corresponds to an edge or a node; identifying one or more edges and one or more nodes based on their scores, each identified node and identified edge corresponding to at least one of the n-grams, each of the identified nodes being connected to at least one of the identified edges; and generating one or more structured queries that each comprise references to one or more of the identified edges and one or more of the identified nodes. 17. The method of claim 1 , wherein the unstructured text query is received from a third-party system via a call through an application programming interface associated with the online social network. | 0.612741 |
6. A computer program product for hierarchical database compression, the computer program product comprising: a non-transitory computer readable storage medium having program code embodied therewith, the program code executable by a processor to: apply a first level of a first type of compression to a first partition of a column of a database and store data generated from an application of the first level of the first type of compression to the first partition in a memory buffer external to the database; and apply a second level of the first type of compression to a subset of the data, wherein the first level of the first type of compression comprises a first first-level dictionary and the second level of the first type of compression comprises a first second-level dictionary, and wherein a code size of the first first-level dictionary is larger than a code size of the first second-level dictionary, wherein to apply the second level of the first type of compression further comprises: adding a first data entry to a set of data corresponding to a page of the database; determining an amount of space saved by applying the second level of the first type of compression to the set of data; determining a size of the first second-level dictionary corresponding to the first type of compression; based on determining that the amount of space is larger than the size of the first second-level dictionary, adding a second data entry to the set of data corresponding to the page; determining, based on the adding of the second data entry to the set of data, that there is a change to at least one of size of the first second-level dictionary and the code size of the first second-level dictionary; calculating a size of the page based on the determined change; determining that the page is full based on the calculated size of the page; removing the second data entry from the set of data corresponding to the page; applying the second level of the first type of compression without the determined change to the set of data corresponding to the page; performing predicate evaluation on the subset of the first partition by converting a predicate value into a compressed predicate value using the first first-level dictionary and the first second-level dictionary, and comparing the predicate value directly to compressed data in the subset of the first partition, wherein the compressed data is compressed using the first level and the second level of the first type of compression; performing join/groupby processing on the subset of the first partition by converting of second-level codes to first-level codes using the first second-level dictionary, and performing the join/groupby processing on the first-level codes; and performing expression evaluation on the subset of the first partition by converting second-level codes to uncompressed data using the first first-level dictionary and the first second-level dictionary. | 6. A computer program product for hierarchical database compression, the computer program product comprising: a non-transitory computer readable storage medium having program code embodied therewith, the program code executable by a processor to: apply a first level of a first type of compression to a first partition of a column of a database and store data generated from an application of the first level of the first type of compression to the first partition in a memory buffer external to the database; and apply a second level of the first type of compression to a subset of the data, wherein the first level of the first type of compression comprises a first first-level dictionary and the second level of the first type of compression comprises a first second-level dictionary, and wherein a code size of the first first-level dictionary is larger than a code size of the first second-level dictionary, wherein to apply the second level of the first type of compression further comprises: adding a first data entry to a set of data corresponding to a page of the database; determining an amount of space saved by applying the second level of the first type of compression to the set of data; determining a size of the first second-level dictionary corresponding to the first type of compression; based on determining that the amount of space is larger than the size of the first second-level dictionary, adding a second data entry to the set of data corresponding to the page; determining, based on the adding of the second data entry to the set of data, that there is a change to at least one of size of the first second-level dictionary and the code size of the first second-level dictionary; calculating a size of the page based on the determined change; determining that the page is full based on the calculated size of the page; removing the second data entry from the set of data corresponding to the page; applying the second level of the first type of compression without the determined change to the set of data corresponding to the page; performing predicate evaluation on the subset of the first partition by converting a predicate value into a compressed predicate value using the first first-level dictionary and the first second-level dictionary, and comparing the predicate value directly to compressed data in the subset of the first partition, wherein the compressed data is compressed using the first level and the second level of the first type of compression; performing join/groupby processing on the subset of the first partition by converting of second-level codes to first-level codes using the first second-level dictionary, and performing the join/groupby processing on the first-level codes; and performing expression evaluation on the subset of the first partition by converting second-level codes to uncompressed data using the first first-level dictionary and the first second-level dictionary. 10. The computer program product of claim 6 , further comprising a third partition of the column of the database, wherein the third partition is uncoded; and applying a third type of compression to a subset of a third partition of the column of the database, wherein third type of compression comprises one of dictionary coding and minus coding. | 0.734589 |
1. A method for document analysis, comprising the steps of: designating a subset of relevant documents from a document collection; using a greedy algorithm to establish a query coverage set of words or terms, wherein at each stage thereof a single word or term from the subset of relevant documents is included in the query coverage set, wherein the single word or term minimizes a distance measurement between the document collection and the query coverage set, wherein the distance measurement is determined by constructing a difficulty model for a topic by computing a plurality of distances comprising a first distance between the query coverage set and the document collection (d(Q,C)), a second distance among the query coverage set (d(Q,Q)); a third distance between the subset of relevant documents and the document collection (d(R,C)), a fourth distance among the subset of relevant documents (d(R,R)), and a fifth distance between the query coverage set and the subset of relevant documents (d(Q,R)); storing the query coverage set in a database; constructing a set of queries from the query coverage set, each of the queries having a number of terms; executing the queries in a search engine to generate respective results; responsively to the respective results determining an average precision for each of the queries by considering the subset of relevant documents as representing the document collection; categorizing the queries by analyzing the average precision against the number of terms thereof; and reporting respective abilities of the categorized queries to find information in the subset of relevant documents. | 1. A method for document analysis, comprising the steps of: designating a subset of relevant documents from a document collection; using a greedy algorithm to establish a query coverage set of words or terms, wherein at each stage thereof a single word or term from the subset of relevant documents is included in the query coverage set, wherein the single word or term minimizes a distance measurement between the document collection and the query coverage set, wherein the distance measurement is determined by constructing a difficulty model for a topic by computing a plurality of distances comprising a first distance between the query coverage set and the document collection (d(Q,C)), a second distance among the query coverage set (d(Q,Q)); a third distance between the subset of relevant documents and the document collection (d(R,C)), a fourth distance among the subset of relevant documents (d(R,R)), and a fifth distance between the query coverage set and the subset of relevant documents (d(Q,R)); storing the query coverage set in a database; constructing a set of queries from the query coverage set, each of the queries having a number of terms; executing the queries in a search engine to generate respective results; responsively to the respective results determining an average precision for each of the queries by considering the subset of relevant documents as representing the document collection; categorizing the queries by analyzing the average precision against the number of terms thereof; and reporting respective abilities of the categorized queries to find information in the subset of relevant documents. 12. The method according to claim 1 , wherein reporting respective abilities of the categorized queries to find information comprises estimating clarity of the topic according to the first distance. | 0.578546 |
1. A method for collection of data from documents present in machine-readable form, the method performed by a computer system with a processor and memory, the method comprising the steps of: associating at least one already-processed document stored as a template and subsequently designated as a template document with a document to be processed that is designated as a read document, fields for data to be extracted being defined in the template document, wherein associating the at least one already-processed document with the document to be processed is performed by the processor executing instructions stored in the memory; automatically extracting data from the read document, the data contained in regions of the read document that correspond to the fields in the template document, wherein automatically extracting data is performed by the processor executing instructions stored in the memory; and if an error occurs, or if no suitable template document is associated: showing the read document on a screen and manually inputting fields in the read document from which the data are extracted; and storing the read document with field specifications as a new template document, or correcting the at least one already-processed template document corresponding to the newly input fields. | 1. A method for collection of data from documents present in machine-readable form, the method performed by a computer system with a processor and memory, the method comprising the steps of: associating at least one already-processed document stored as a template and subsequently designated as a template document with a document to be processed that is designated as a read document, fields for data to be extracted being defined in the template document, wherein associating the at least one already-processed document with the document to be processed is performed by the processor executing instructions stored in the memory; automatically extracting data from the read document, the data contained in regions of the read document that correspond to the fields in the template document, wherein automatically extracting data is performed by the processor executing instructions stored in the memory; and if an error occurs, or if no suitable template document is associated: showing the read document on a screen and manually inputting fields in the read document from which the data are extracted; and storing the read document with field specifications as a new template document, or correcting the at least one already-processed template document corresponding to the newly input fields. 6. A method according to claim 1 wherein a plurality of read documents are evaluated as to whether surroundings are constant with regard to a field in the template document, and when this is the case this is stored and considered as a further criterion in mapping of a field of the template document to the read document. | 0.640157 |
1. A system, comprising: a client comprising a client Web services stack that supports both a markup language protocol and a binary encoding protocol, wherein the markup language protocol is based on XML (eXtensible Markup Language); and a server comprising a server Web services stack that supports both the markup language protocol and the binary encoding protocol, wherein the server Web services stack is configured to: communicate with the client Web services stack according to the markup language protocol; and dynamically switch to communicate with the client Web services stack according to the binary encoding protocol, wherein communication according to the binary encoding protocol comprises mapping from an XML schema to a binary encoding schema and generating a binary encoding from the binary encoding schema; wherein the client Web services stack and the server Web services stack each support the markup language protocol and the binary encoding protocol with a single API (application programming interface). | 1. A system, comprising: a client comprising a client Web services stack that supports both a markup language protocol and a binary encoding protocol, wherein the markup language protocol is based on XML (eXtensible Markup Language); and a server comprising a server Web services stack that supports both the markup language protocol and the binary encoding protocol, wherein the server Web services stack is configured to: communicate with the client Web services stack according to the markup language protocol; and dynamically switch to communicate with the client Web services stack according to the binary encoding protocol, wherein communication according to the binary encoding protocol comprises mapping from an XML schema to a binary encoding schema and generating a binary encoding from the binary encoding schema; wherein the client Web services stack and the server Web services stack each support the markup language protocol and the binary encoding protocol with a single API (application programming interface). 3. The system as recited in claim 1 , wherein the client is a J2ME (Java 2 Micro Edition) client. | 0.645241 |
17. A system that facilitates an automatic machine-learning process for an online social network, comprising: a computing system including a processor and a memory; wherein the computing system is configured to run an online social network; and wherein the online social network is configured to, automatically collect labeled training events; snapshot raw entity data associated with subjects from the collected training events; generate features for each training event using the snapshotted entity data and the current entity data to produce training examples; consolidate the training examples from one or more time periods to produce a consolidated set of training examples; determine one or more contradictory user actions upon a set of entity data in the consolidated set of training examples, wherein a contradictory user action involves a same user responding differently to the same entity data over different time intervals; resolve the contradictory user actions for the consolidated set of training examples; split the training examples into a training set and a test set; use a machine-learning technique to train a set of models and select the best model based on one or more evaluation metrics using the training set; evaluate the performance of the best model on the test set; and if the performance of the best model satisfies a performance criterion, use the best model to predict responses for the online social network. | 17. A system that facilitates an automatic machine-learning process for an online social network, comprising: a computing system including a processor and a memory; wherein the computing system is configured to run an online social network; and wherein the online social network is configured to, automatically collect labeled training events; snapshot raw entity data associated with subjects from the collected training events; generate features for each training event using the snapshotted entity data and the current entity data to produce training examples; consolidate the training examples from one or more time periods to produce a consolidated set of training examples; determine one or more contradictory user actions upon a set of entity data in the consolidated set of training examples, wherein a contradictory user action involves a same user responding differently to the same entity data over different time intervals; resolve the contradictory user actions for the consolidated set of training examples; split the training examples into a training set and a test set; use a machine-learning technique to train a set of models and select the best model based on one or more evaluation metrics using the training set; evaluate the performance of the best model on the test set; and if the performance of the best model satisfies a performance criterion, use the best model to predict responses for the online social network. 22. The system of claim 17 , wherein the response to be predicted is associated with one or more of: a classification of an item; a prediction of a user preference; and a prediction of a user action. | 0.807327 |
12. The computer-implemented process of claim 1 , further comprising: searching for documents in a repository of documents that contain an entity with an associated sentiment value. | 12. The computer-implemented process of claim 1 , further comprising: searching for documents in a repository of documents that contain an entity with an associated sentiment value. 13. The computer-implemented process of claim 12 , further comprising: displaying sentiment values associated with entities in a document in search results. | 0.923643 |
1. A method for adaptive information recommendation, the method comprising: storing user-specific information in memory, the user-specific information concerning interactions with a plurality of documents; and executing instructions stored in memory, wherein execution of the instructions by a processor: assembles an interest set of documents corresponding to the user-specific information concerning interactions with the plurality of documents, wherein the interactions include a previous view of a document by the user, groups the documents in the interest set into a plurality of clusters based on a level of similarity between words in the documents, determines a keyword for a cluster of the one or more clusters, the keyword identified based on a plurality of terms identified via natural language understanding and representing the theme of the documents in the cluster, wherein the keyword is not one of the terms identified via natural language understanding, determines a set of eligible documents within the cluster, each identified document including either the keyword representing the theme of the documents or a portion of the terms identified via natural language understanding, constructs from the eligible documents a recommended set of documents for the cluster based on a relevance score of each document in the cluster, wherein the relevance score is based on: the frequency that the keyword or the portion of the terms identified via natural language understanding appears in each document in the set of eligible documents, and a user-defined limit on document age, and provides the recommended set of documents. | 1. A method for adaptive information recommendation, the method comprising: storing user-specific information in memory, the user-specific information concerning interactions with a plurality of documents; and executing instructions stored in memory, wherein execution of the instructions by a processor: assembles an interest set of documents corresponding to the user-specific information concerning interactions with the plurality of documents, wherein the interactions include a previous view of a document by the user, groups the documents in the interest set into a plurality of clusters based on a level of similarity between words in the documents, determines a keyword for a cluster of the one or more clusters, the keyword identified based on a plurality of terms identified via natural language understanding and representing the theme of the documents in the cluster, wherein the keyword is not one of the terms identified via natural language understanding, determines a set of eligible documents within the cluster, each identified document including either the keyword representing the theme of the documents or a portion of the terms identified via natural language understanding, constructs from the eligible documents a recommended set of documents for the cluster based on a relevance score of each document in the cluster, wherein the relevance score is based on: the frequency that the keyword or the portion of the terms identified via natural language understanding appears in each document in the set of eligible documents, and a user-defined limit on document age, and provides the recommended set of documents. 2. The method of claim 1 , wherein the interactions include searches previously conducted by the user. | 0.78178 |
1. A method for determining a logical structure of a document, the method comprising: acquiring an image of the document; identifying one or more blocks in the image of the document; generating a hypothesis for at least one of the identified blocks in the image of the document (a “block hypothesis”); generating at least one document hypothesis for the image of the document, wherein said generating included referencing a plurality of document models, wherein each document model describes one or more possible logical structures, and wherein such logical structures are based on the presence of one or more blocks; selecting a document hypothesis based on its degree of correspondence with at least one block hypothesis; and forming a representation of the document based on the selected document hypothesis. | 1. A method for determining a logical structure of a document, the method comprising: acquiring an image of the document; identifying one or more blocks in the image of the document; generating a hypothesis for at least one of the identified blocks in the image of the document (a “block hypothesis”); generating at least one document hypothesis for the image of the document, wherein said generating included referencing a plurality of document models, wherein each document model describes one or more possible logical structures, and wherein such logical structures are based on the presence of one or more blocks; selecting a document hypothesis based on its degree of correspondence with at least one block hypothesis; and forming a representation of the document based on the selected document hypothesis. 10. The system of claim 1 , wherein the generating the at least one document hypothesis for the document includes generating a plurality of document hypotheses in order of differing probabilities. | 0.692188 |
1. A computer-implemented method, the computer having processor circuitry configured to execute one or more computer programs, which, when executed, cause instructions for implementing the method to be performed, the computer-implemented method comprising: identifying a set of users associated with at least one collaboration artifact; identifying a set of networks including a plurality of candidate social Internet or intranet networks; and determining, at the computer having the processor circuitry configured to execute the one or more computer programs, a relationship strength between the set of users associated with the at least one collaboration artifact, the at least one collaboration artifact comprising at least a work product that enables cooperation between two or more users, and each of the candidate social Internet or intranet networks to identify at least one relevant social Internet or intranet network from the candidate social Internet or intranet networks. | 1. A computer-implemented method, the computer having processor circuitry configured to execute one or more computer programs, which, when executed, cause instructions for implementing the method to be performed, the computer-implemented method comprising: identifying a set of users associated with at least one collaboration artifact; identifying a set of networks including a plurality of candidate social Internet or intranet networks; and determining, at the computer having the processor circuitry configured to execute the one or more computer programs, a relationship strength between the set of users associated with the at least one collaboration artifact, the at least one collaboration artifact comprising at least a work product that enables cooperation between two or more users, and each of the candidate social Internet or intranet networks to identify at least one relevant social Internet or intranet network from the candidate social Internet or intranet networks. 6. The computer-implemented method of claim 1 , further comprising sorting each of the candidate social Internet or intranet networks based on the relationship strength to identify the at least one relevant social Internet or intranet networks from the candidate social Internet or intranet networks. | 0.57074 |
9. A method for activating a document handler comprising the steps of: receiving a timing ticket at an inlet in a document validator of the document handler, the ticket providing an activation code, the document validator comprising at least one of: a validation passageway for guiding the document inserted into the inlet, a validation conveyor for transporting the document along the validation passageway, and a validation sensor for detecting optical or magnetic features of the document to produce detection signals; reading the activation code from the timing ticket by the validation sensor; transmitting an electronic signal of the activation code from the validation sensor to a control device of the document handler, the control device receiving detection signals from the validation sensor to decide whether the document is genuine or not; determining a time period for operation of the document handler based on one of the group comprising at least one of: (a) a match of the activation code to a unique time code in a set of time codes accessed by the control device from a memory associated with the control device; (b) a value provided in the activation code; or (c) a value provided separately on the ticket; activating the document handler for operation for a predefined period of time corresponding to the activation code in the event that the activation code matches one of the unique time codes; and initiating a countdown representing the predefined time period in a clock to track the predefined time period for activation of the document handler. | 9. A method for activating a document handler comprising the steps of: receiving a timing ticket at an inlet in a document validator of the document handler, the ticket providing an activation code, the document validator comprising at least one of: a validation passageway for guiding the document inserted into the inlet, a validation conveyor for transporting the document along the validation passageway, and a validation sensor for detecting optical or magnetic features of the document to produce detection signals; reading the activation code from the timing ticket by the validation sensor; transmitting an electronic signal of the activation code from the validation sensor to a control device of the document handler, the control device receiving detection signals from the validation sensor to decide whether the document is genuine or not; determining a time period for operation of the document handler based on one of the group comprising at least one of: (a) a match of the activation code to a unique time code in a set of time codes accessed by the control device from a memory associated with the control device; (b) a value provided in the activation code; or (c) a value provided separately on the ticket; activating the document handler for operation for a predefined period of time corresponding to the activation code in the event that the activation code matches one of the unique time codes; and initiating a countdown representing the predefined time period in a clock to track the predefined time period for activation of the document handler. 10. The method of claim 9 wherein the timing ticket is a document comprising readable information in a form from a group comprising: a printed code; a bar code, a magnetic strip; an electronic transmitter or transponder; or other machine or human readable value representing the activation code printed on the timing ticket. | 0.694861 |
1. A navigation apparatus including a voice receiver to receive an instruction by voice input, and a voice recognizer to carry out voice recognition of the instruction received by the voice receiver, the navigation apparatus comprising: a recognition vocabulary comprehension level decider to decide a user comprehension level of a recognition vocabulary for instructions recognizable by the voice recognizer, from at least one of correction operation frequency and time-out frequency in an operation of recognizing the instruction which is carried out during the voice recognition by the voice recognizer and corresponds to the instruction; an operational transition determiner to determine an operational transition from a plurality of potential operational transitions in accordance with a decision result of the recognition vocabulary comprehension level decider, each of the potential operational transitions including a different number of input steps by which the instruction is voice-recognized, such that different input steps correspond to different subsets of the recognition vocabulary for each potential operation transition that includes multiple input steps; and an operational transition provider to provide the operational transition determined by the operational transition determiner, wherein the operational transition determiner, when determining the operational transition in accordance with the decision result output from the recognition vocabulary comprehension level decider, switches the operational transition thereby limiting an input content per step by increasing the number of input steps in a specific operational transition, or reducing the number of input steps by increasing an amount of information capable of being input per step in the specific operational transition. | 1. A navigation apparatus including a voice receiver to receive an instruction by voice input, and a voice recognizer to carry out voice recognition of the instruction received by the voice receiver, the navigation apparatus comprising: a recognition vocabulary comprehension level decider to decide a user comprehension level of a recognition vocabulary for instructions recognizable by the voice recognizer, from at least one of correction operation frequency and time-out frequency in an operation of recognizing the instruction which is carried out during the voice recognition by the voice recognizer and corresponds to the instruction; an operational transition determiner to determine an operational transition from a plurality of potential operational transitions in accordance with a decision result of the recognition vocabulary comprehension level decider, each of the potential operational transitions including a different number of input steps by which the instruction is voice-recognized, such that different input steps correspond to different subsets of the recognition vocabulary for each potential operation transition that includes multiple input steps; and an operational transition provider to provide the operational transition determined by the operational transition determiner, wherein the operational transition determiner, when determining the operational transition in accordance with the decision result output from the recognition vocabulary comprehension level decider, switches the operational transition thereby limiting an input content per step by increasing the number of input steps in a specific operational transition, or reducing the number of input steps by increasing an amount of information capable of being input per step in the specific operational transition. 16. The navigation apparatus according to claim 1 , further comprising: a user designator to designate any desired user from a user list that has already been registered, wherein the recognition vocabulary comprehension level decider and the operational transition determiner make a decision of the recognition vocabulary comprehension level and a determination of the operational transition on a user-by-user basis designated by the user designator. | 0.500747 |
1. A method for reuse of a software code, the method comprising the steps of: (a) a processor of a computer system obfuscating the software code from an original state of the software code; (b) presenting the obfuscated software code to a first participant and a second participant; (c) collecting communications between the first participant and the second participant, wherein the communications comprise questions about the obfuscated software code posed by the first participant to the second participant, answers provided by the second participant to the questions, and guesses by the first participant of a functionality of the obfuscated software code; (d) the processor generating associations between the collected communications and respective portions of the obfuscated software code; (e) storing the generated associations in a database of the computer system; (f) after the storing, the processor determining that the second participant has not indicated that the first participant understands the obfuscated software code, and in response, partially reversing the obfuscated software code to transform the obfuscated software code to a partially obfuscated software code that is closer to the original state of the software code than the obfuscated software code generated in step (a), and repeating steps (b), (c), (d) and (e) with the partially obfuscated software code instead of the obfuscated software code generated in step (a); and (g) after the partially reversing in step (f), the processor determining if the second participant has indicated that the first participant understands the partially obfuscated software code, and if not, further reversing the partially obfuscated software code to transform the partially obfuscated software code to the original state of the software code or closer to the original state of the software code than the partially obfuscated software code generated in step (f), and repeating steps (b), (c), (d) and (e) with the further reversed partially obfuscated software code instead of the partially obfuscated software code generated in step (f). | 1. A method for reuse of a software code, the method comprising the steps of: (a) a processor of a computer system obfuscating the software code from an original state of the software code; (b) presenting the obfuscated software code to a first participant and a second participant; (c) collecting communications between the first participant and the second participant, wherein the communications comprise questions about the obfuscated software code posed by the first participant to the second participant, answers provided by the second participant to the questions, and guesses by the first participant of a functionality of the obfuscated software code; (d) the processor generating associations between the collected communications and respective portions of the obfuscated software code; (e) storing the generated associations in a database of the computer system; (f) after the storing, the processor determining that the second participant has not indicated that the first participant understands the obfuscated software code, and in response, partially reversing the obfuscated software code to transform the obfuscated software code to a partially obfuscated software code that is closer to the original state of the software code than the obfuscated software code generated in step (a), and repeating steps (b), (c), (d) and (e) with the partially obfuscated software code instead of the obfuscated software code generated in step (a); and (g) after the partially reversing in step (f), the processor determining if the second participant has indicated that the first participant understands the partially obfuscated software code, and if not, further reversing the partially obfuscated software code to transform the partially obfuscated software code to the original state of the software code or closer to the original state of the software code than the partially obfuscated software code generated in step (f), and repeating steps (b), (c), (d) and (e) with the further reversed partially obfuscated software code instead of the partially obfuscated software code generated in step (f). 6. The method of claim 1 , wherein in step (g) the determining determines that the second participant has not indicated that the first participant understands the partially obfuscated software code, and wherein the further reversing transforms the partially obfuscated software code to the original state of the software code. | 0.861441 |
37. A method as claimed in claim 36 wherein the step of executing knowledge sources further includes the step of, after determining whether an interrupted knowledge source should be rescheduled for execution, rescheduling that knowledge source in accordance with the determination. | 37. A method as claimed in claim 36 wherein the step of executing knowledge sources further includes the step of, after determining whether an interrupted knowledge source should be rescheduled for execution, rescheduling that knowledge source in accordance with the determination. 38. A method as claimed in claim 37 wherein the step of determining includes the steps of determining when knowledge source execution preconditions are met and checking only a knowledge source whose execution preconditiions are met for execution availability. | 0.89675 |
1. A method comprising: in a computing device: determining a plurality of categories of a web page; extracting notes from the web page by automatically applying a set of parsing rules that, at least in part, identify respective sentences from sentence structure and punctuation in the web page; in response to a query of the web page, displaying a result of the query of the web page, the displayed result being segregated by the plurality of categories, wherein the displayed result comprises the notes extracted from the web page, the notes comprising a single word, name, sentence, group of sentences, uniform resource locator (URL), image, audio clip or video clip; and changing, without performing another query, a presentation of the web page on a category basis, allowing presentation of the web page with flexible access, wherein the presentation includes formatting said presentation for an access device according to one or more templates, formatting said presentation for a display device so that more notes are displayed on larger display areas and fewer notes are displayed on smaller display areas; and providing control selections allowing selectable display of notes in a note set regardless of display size, and formatting said presentation based on a user information goal. | 1. A method comprising: in a computing device: determining a plurality of categories of a web page; extracting notes from the web page by automatically applying a set of parsing rules that, at least in part, identify respective sentences from sentence structure and punctuation in the web page; in response to a query of the web page, displaying a result of the query of the web page, the displayed result being segregated by the plurality of categories, wherein the displayed result comprises the notes extracted from the web page, the notes comprising a single word, name, sentence, group of sentences, uniform resource locator (URL), image, audio clip or video clip; and changing, without performing another query, a presentation of the web page on a category basis, allowing presentation of the web page with flexible access, wherein the presentation includes formatting said presentation for an access device according to one or more templates, formatting said presentation for a display device so that more notes are displayed on larger display areas and fewer notes are displayed on smaller display areas; and providing control selections allowing selectable display of notes in a note set regardless of display size, and formatting said presentation based on a user information goal. 8. The method according to claim 1 further comprising: exporting one or more notes into Word, Excel or other common user file formats. | 0.534624 |
1. A method of using at least two n-gram models, at least one of which is based on a training set of entities of interest and at least one of which is based on a training set of entities not of interest, the method comprising: tokenizing a document to produce a string of tokens corresponding to terms within the document; for each token, evaluating the token against the n-gram models to determine which model is most likely to be associated with the token; identifying tokens corresponding to at least one n-gram model of interest; and annotating the identified tokens with at least one name for said at least one n-gram model of interest. | 1. A method of using at least two n-gram models, at least one of which is based on a training set of entities of interest and at least one of which is based on a training set of entities not of interest, the method comprising: tokenizing a document to produce a string of tokens corresponding to terms within the document; for each token, evaluating the token against the n-gram models to determine which model is most likely to be associated with the token; identifying tokens corresponding to at least one n-gram model of interest; and annotating the identified tokens with at least one name for said at least one n-gram model of interest. 4. The method of claim 1 , wherein said evaluating comprises: calculating a relative probability that a given token has been generated by a model of interest; calculating a relative probability that the given token has been generated by a model that is not of interest; comparing the calculated relative probabilities; and associating each token with the model that yields the greater relative probability. | 0.5 |
1. A method for treating an apraxia of speech in a child, said method comprises: (a) determining that the child has an apraxia of speech comprising nonverbal development; (b) determining that the child has a cognitive development of at least 18-24 months; (c) administering a therapeutically effective dose of a dopamine agonist to the child, said dopamine agonist efficaciously affecting the apraxia effecting verbal development and wherein the dopamine agonist comprises a methylphenidate; whereby there is verbal development and the apraxia of speech is diminished. | 1. A method for treating an apraxia of speech in a child, said method comprises: (a) determining that the child has an apraxia of speech comprising nonverbal development; (b) determining that the child has a cognitive development of at least 18-24 months; (c) administering a therapeutically effective dose of a dopamine agonist to the child, said dopamine agonist efficaciously affecting the apraxia effecting verbal development and wherein the dopamine agonist comprises a methylphenidate; whereby there is verbal development and the apraxia of speech is diminished. 7. The method of claim 1 , wherein the dopamine agonist comprises an analog of methylphenidate. | 0.567901 |
17. A system for visually indicating a voice speaker to a listener in a context of a computing gaming session, comprising: (a) a processor; (b) a display in communication with the processor; and (c) a memory in communication with the processor, said memory storing machine instructions that cause the processor to carry out a plurality of functions, including: (i) obtaining a speaker identifier, the speaker identifier including a user name gamertag, from voice data transmitted by the voice speaker; (ii) associating the speaker identifier with a visual indicator used for indicating voice speakers; (iii) selectively and temporarily, when the voice speaker is speaking, displaying the visual indicator and selectively and temporarily, when the voice speaker is speaking, displaying the user name gamertag, and when the visual indicator and the user name gamertag are displayed, displaying the visual indicator and the user name adjacent to one another, on the display to indicate that the voice speaker is speaking; (iv) receiving user input selecting a players tab view that provides information on players in a current game session and in response to receiving user input selecting a players tab view: displaying a player's list including a player ID column listing gamertags for players in a current game session, and displaying a voice communication column capable of selectively displaying for each of the players in the player ID column each of: a muted icon that indicates that a local listener has muted voice communication from a selected player, a persistent bidirectional mute icon that indicates that the local listener or the network gaming service has prohibited the corresponding player from speaking to the listener and hearing any voice communication from the listener, a null icon that indicates that a corresponding player does not have a voice communicator, and a hear-only icon that indicates that a corresponding player can hear voice communication but does not have a microphone for speaking to other players. | 17. A system for visually indicating a voice speaker to a listener in a context of a computing gaming session, comprising: (a) a processor; (b) a display in communication with the processor; and (c) a memory in communication with the processor, said memory storing machine instructions that cause the processor to carry out a plurality of functions, including: (i) obtaining a speaker identifier, the speaker identifier including a user name gamertag, from voice data transmitted by the voice speaker; (ii) associating the speaker identifier with a visual indicator used for indicating voice speakers; (iii) selectively and temporarily, when the voice speaker is speaking, displaying the visual indicator and selectively and temporarily, when the voice speaker is speaking, displaying the user name gamertag, and when the visual indicator and the user name gamertag are displayed, displaying the visual indicator and the user name adjacent to one another, on the display to indicate that the voice speaker is speaking; (iv) receiving user input selecting a players tab view that provides information on players in a current game session and in response to receiving user input selecting a players tab view: displaying a player's list including a player ID column listing gamertags for players in a current game session, and displaying a voice communication column capable of selectively displaying for each of the players in the player ID column each of: a muted icon that indicates that a local listener has muted voice communication from a selected player, a persistent bidirectional mute icon that indicates that the local listener or the network gaming service has prohibited the corresponding player from speaking to the listener and hearing any voice communication from the listener, a null icon that indicates that a corresponding player does not have a voice communicator, and a hear-only icon that indicates that a corresponding player can hear voice communication but does not have a microphone for speaking to other players. 20. The system of claim 17 , wherein prior to displaying the visual indicator, the machine instructions further cause the processor to carry out the function of determining whether the listener is prohibited from hearing voice communications from the voice speaker. | 0.5 |
11. A system comprising: a display device; and at least one processor configured to: electronically translate, during an automated translation process, a first plurality of words in a source language so as to obtain a second plurality of words in a target language, wherein, to electronically translate, the processor is to: perform lexical-morphological analysis of the first plurality of words to generate a lexical-morphological structure of at least one sentence in the first plurality of words, perform syntactic analysis using the lexical-morphological structure of the at least one sentence to generate a language-independent semantic structure, perform syntactic synthesis based on the language-independent semantic structure to generate the second plurality of words, and identify first one or more potentially erroneous words in the first plurality of words and corresponding second one or more potentially erroneous words in the second plurality of words; display, on the display device, the first plurality of words in the source language; display, on the display device, the second plurality of words in the target language; automatically indicate, on the display device as part of the automated translation process, the first one or more potentially erroneous words within the displayed first plurality of words in the source language; automatically indicate, on the display device as part of the automated translation process, the second one or more potentially erroneous words within the displayed second plurality of words in the target language; receive a change to the first one or more potentially erroneous words; and modify the second plurality of words to provide another translation in the target language based on the change in the first one or more potentially erroneous words. | 11. A system comprising: a display device; and at least one processor configured to: electronically translate, during an automated translation process, a first plurality of words in a source language so as to obtain a second plurality of words in a target language, wherein, to electronically translate, the processor is to: perform lexical-morphological analysis of the first plurality of words to generate a lexical-morphological structure of at least one sentence in the first plurality of words, perform syntactic analysis using the lexical-morphological structure of the at least one sentence to generate a language-independent semantic structure, perform syntactic synthesis based on the language-independent semantic structure to generate the second plurality of words, and identify first one or more potentially erroneous words in the first plurality of words and corresponding second one or more potentially erroneous words in the second plurality of words; display, on the display device, the first plurality of words in the source language; display, on the display device, the second plurality of words in the target language; automatically indicate, on the display device as part of the automated translation process, the first one or more potentially erroneous words within the displayed first plurality of words in the source language; automatically indicate, on the display device as part of the automated translation process, the second one or more potentially erroneous words within the displayed second plurality of words in the target language; receive a change to the first one or more potentially erroneous words; and modify the second plurality of words to provide another translation in the target language based on the change in the first one or more potentially erroneous words. 12. The system of claim 11 , wherein the first one or more potentially erroneous words comprise a word with a lexical error. | 0.574807 |
1. A computer-implemented method comprising: identifying, by a first driver executed by a processing device, a first file comprising a first plurality of rules written in a first rule language, wherein the first driver corresponds to the first rule language; converting, by the first driver, the first plurality of rules written in the first rule language into a plurality of descriptor classes using a plurality of rule patterns, wherein the plurality of descriptor classes are used to model rule concepts supported by a rule engine; generating, by the first driver, an intermediate structure comprising an abstract syntax tree of the plurality of descriptor classes; inputting, by the processing device, the intermediate structure to a second driver, wherein the second driver corresponds to a second rule language; translating, by the second driver executed by the processing device, the plurality of descriptor classes in the abstract syntax tree in the intermediate structure into a second plurality of rules written in the second rule language; and generating, by the second driver, a second file comprising the second plurality of rules written in the second rule language. | 1. A computer-implemented method comprising: identifying, by a first driver executed by a processing device, a first file comprising a first plurality of rules written in a first rule language, wherein the first driver corresponds to the first rule language; converting, by the first driver, the first plurality of rules written in the first rule language into a plurality of descriptor classes using a plurality of rule patterns, wherein the plurality of descriptor classes are used to model rule concepts supported by a rule engine; generating, by the first driver, an intermediate structure comprising an abstract syntax tree of the plurality of descriptor classes; inputting, by the processing device, the intermediate structure to a second driver, wherein the second driver corresponds to a second rule language; translating, by the second driver executed by the processing device, the plurality of descriptor classes in the abstract syntax tree in the intermediate structure into a second plurality of rules written in the second rule language; and generating, by the second driver, a second file comprising the second plurality of rules written in the second rule language. 2. The method of claim 1 , wherein the plurality of descriptor classes comprises at least one of RuleDescr, ConditionalElementDescr, or ConstraintDescr. | 0.733146 |
8. One or more non-transitory computer-readable tangible media encoding software operable when executed to: access a document stored in one or more tangible media; receive a set of target tags for the document; identify a plurality of terms, each identified term selected to reduce an ontology space of the document due to the identified term having a higher affinity with a target tag and a lower affinity with the other identified terms; send the plurality of identified terms to a computer to recommend the plurality of identified terms as tags; receive a selection by a user of one or more terms of the plurality of identified terms and identifying one or more of the plurality of identified terms that were not selected by the user; determine a plurality of next terms that have both (i) an affinity with the one or more terms selected by the user that is above a first affinity threshold and (ii) an affinity with the one or more terms that were not selected by the user that is below a second affinity threshold; and send the next terms to the computer to recommend the terms as tags. | 8. One or more non-transitory computer-readable tangible media encoding software operable when executed to: access a document stored in one or more tangible media; receive a set of target tags for the document; identify a plurality of terms, each identified term selected to reduce an ontology space of the document due to the identified term having a higher affinity with a target tag and a lower affinity with the other identified terms; send the plurality of identified terms to a computer to recommend the plurality of identified terms as tags; receive a selection by a user of one or more terms of the plurality of identified terms and identifying one or more of the plurality of identified terms that were not selected by the user; determine a plurality of next terms that have both (i) an affinity with the one or more terms selected by the user that is above a first affinity threshold and (ii) an affinity with the one or more terms that were not selected by the user that is below a second affinity threshold; and send the next terms to the computer to recommend the terms as tags. 14. The computer-readable tangible media of claim 8 , the software when executed operable to identify the plurality of terms according to affinity, the affinity further comprising one or more affinities selected from a group consisting of an affinity, an average affinity, a directional affinity, and a differential affinity. | 0.61412 |
11. A non-transitory computer readable medium configured to store a text mining program configured to cause a computer to execute text mining processing, said computer is connected to a text set storage unit configured to store a plurality of text obtained by forming a plurality of non-text data into the plurality of text and a reliability storage unit configured to store an all-class reliability for each of the plurality of text stored in said text set storage unit, said all-class reliability being derived from the formation of said plurality of non-text data into said plurality of text, said text mining processing including: a text mining processing of searching, the plurality of text for a plurality of text of a same class, where said plurality of text of the same class has a characteristic the same as the plurality of text stored in said text set storage unit; and a text selection processing of reading, when said plurality of texts of the same class are searched, a same-class reliability of each of said plurality of text of the same class from said reliability storage unit, and selecting a part of said plurality of text of the same class from the plurality of text of the same class based on the same-class reliability, wherein said text selection processing includes: a degree of assurance generation processing of generating, for each of said plurality of text of the same class, a degree of assurance indicative of a degree of correlation between said plurality of text of the same class and said plurality of non-text data based on the same-class reliability of said plurality of text of the same class; and a selection processing of selecting a portion of said plurality of text of the same class having the highest degree of assurance as said part of said plurality of text of the same class from among said plurality of text of the same class. | 11. A non-transitory computer readable medium configured to store a text mining program configured to cause a computer to execute text mining processing, said computer is connected to a text set storage unit configured to store a plurality of text obtained by forming a plurality of non-text data into the plurality of text and a reliability storage unit configured to store an all-class reliability for each of the plurality of text stored in said text set storage unit, said all-class reliability being derived from the formation of said plurality of non-text data into said plurality of text, said text mining processing including: a text mining processing of searching, the plurality of text for a plurality of text of a same class, where said plurality of text of the same class has a characteristic the same as the plurality of text stored in said text set storage unit; and a text selection processing of reading, when said plurality of texts of the same class are searched, a same-class reliability of each of said plurality of text of the same class from said reliability storage unit, and selecting a part of said plurality of text of the same class from the plurality of text of the same class based on the same-class reliability, wherein said text selection processing includes: a degree of assurance generation processing of generating, for each of said plurality of text of the same class, a degree of assurance indicative of a degree of correlation between said plurality of text of the same class and said plurality of non-text data based on the same-class reliability of said plurality of text of the same class; and a selection processing of selecting a portion of said plurality of text of the same class having the highest degree of assurance as said part of said plurality of text of the same class from among said plurality of text of the same class. 13. The non-transitory computer readable medium configured to store the text mining program according to claim 11 , wherein in said text mining processing, a word is used as said characteristic, and in said degree of assurance generation processing, for each of said plurality of text of the same class, said same-class reliability of said word used as said characteristic and a proximate-word reliability of a word in proximity to the word used as said characteristic are read from said reliability storage unit to generate, for each of said plurality of text of the same class, said degree of assurance based on said same-class reliability of the word used as said characteristic and said proximate-word reliability of the word in proximity to the word used as said characteristic. | 0.5 |
11. A process for supporting computing infrastructure, said process comprising providing at least one support service for at least one of creating, integrating, hosting, maintaining, and deploying computer-readable code in a computing system, wherein the code in combination with the computing system is capable of performing a method of developing an information technology solution via development of a conceptual model, said method comprising: defining, by one or more business stakeholders associated with a business, a plurality of requirements of an information technology (IT) solution owned by said business, wherein said requirements indicate a plurality of functions of said business to be supported by said IT solution; said one or more business stakeholders and one or more IT stakeholders associated with said business developing a conceptual model by developing a conceptual structure and subsequently developing a plurality of operational concepts, said conceptual model including said conceptual structure and said plurality of operational concepts and providing a representation of said IT solution, said conceptual structure including a plurality of conceptual components, said plurality of conceptual components being icons, forms, shapes and/or figures determined by outlines that modularly represent one or more IT systems, one or more hardware components of said one or more IT systems and one or more software components of said one or more IT systems, said one or more IT systems, said one or more hardware components and said one or more IT systems being manifestations (manifested conceptual components) of said plurality of conceptual components in an implementation of said IT solution, and said plurality of operational concepts indicating interactions among said manifested conceptual components to perform said plurality of functions of said business, wherein said developing said conceptual structure includes: defining said conceptual structure based on a functional analysis of said plurality of functions of said business by said one or more business stakeholders and said one or more IT stakeholders; and subsequent to said defining said conceptual structure, refining said conceptual structure by: refining said conceptual structure based on a first analysis of interactions of one or more users with said IT solution; refining said conceptual structure based on a second analysis of a business model of said business; refining said conceptual structure based on a third analysis of how said manifested conceptual components interact with each other to support a business operational model of said business, said business operational model being a description by said one or more business stakeholders of how said business operates to attain one or more operational goals of said business; refining said conceptual structure based on a fourth analysis of one or more internal processes and one or more algorithms, said one or more internal processes associated with an operation of a set of manifested conceptual components included in said manifested conceptual components and with interactions therebetween, and said one or more algorithms associated with said operation of said set of manifested conceptual components and with said interactions therebetween; refining said conceptual structure based on a fifth analysis of one or more requirements for communication among said manifested conceptual components, between said IT solution and one or more systems of said IT solution, and between said IT solution and one or more systems external to said IT solution; refining said conceptual structure based on a sixth analysis of one or more requirements for capturing, storing, retrieving and managing information internal to said one or more systems of said IT solution; and refining said conceptual structure based on a seventh analysis of non-functional requirements of said IT solution, wherein a result of said refining said conceptual structure is a refinement of said conceptual structure, wherein said refinement includes a new conceptual component added to said plurality of conceptual components, wherein said refinement further includes a partition of a conceptual component of said plurality of conceptual components into two or more conceptual components that are added to said plurality of conceptual components and/or an aggregation of at least two conceptual components of said plurality of conceptual components into a new composite conceptual component added to said plurality of conceptual components, wherein said subsequently developing said plurality of operational concepts includes: prior to developing an architecture and a design of said IT solution, generating a description of said plurality of operational concepts based on said refinement of said conceptual structure, said description including: a first description of said plurality of conceptual components included in said refinement of said conceptual structure, a second description of said plurality of functions, said one or more internal processes, and said one or more algorithms supported by said manifested conceptual components represented by said plurality of conceptual components included in said refinement of said conceptual structure, a third description of information management needs of said manifested conceptual components represented by said plurality of conceptual components included in said refinement of said conceptual structure, a fourth description of how said manifested conceptual components represented by said plurality of conceptual components included in said refinement of said conceptual structure interact among themselves to perform said plurality of functions of said business, a fifth description of how said business model relates to an organization of said plurality of conceptual components included in said refinement of said conceptual structure, and a sixth description of how said non-functional requirements are addressed by said IT solution and by said manifested conceptual components represented by said plurality of components included in said refinement of said conceptual structure; and generating a diagram representing an overview of said IT solution and including said refinement of said conceptual structure; a computing system retrieving said diagram representing said overview of said IT solution and including said refinement of said conceptual structure and generating a documentation that includes said diagram and said description of said plurality of operational concepts; developing said architecture and said design of said IT solution by said one or more IT stakeholders based on said developed conceptual model and said documentation that includes said diagram representing said overview of said IT solution and said description of said plurality of operational concepts, wherein said description of said plurality of operational concepts included in said documentation that is a basis for said architecture and said design of said IT solution indicates said interactions among said manifested conceptual components to perform said plurality of functions of said business; and generating, by said one or more IT stakeholders, a second documentation of said architecture and said design of said IT solution. | 11. A process for supporting computing infrastructure, said process comprising providing at least one support service for at least one of creating, integrating, hosting, maintaining, and deploying computer-readable code in a computing system, wherein the code in combination with the computing system is capable of performing a method of developing an information technology solution via development of a conceptual model, said method comprising: defining, by one or more business stakeholders associated with a business, a plurality of requirements of an information technology (IT) solution owned by said business, wherein said requirements indicate a plurality of functions of said business to be supported by said IT solution; said one or more business stakeholders and one or more IT stakeholders associated with said business developing a conceptual model by developing a conceptual structure and subsequently developing a plurality of operational concepts, said conceptual model including said conceptual structure and said plurality of operational concepts and providing a representation of said IT solution, said conceptual structure including a plurality of conceptual components, said plurality of conceptual components being icons, forms, shapes and/or figures determined by outlines that modularly represent one or more IT systems, one or more hardware components of said one or more IT systems and one or more software components of said one or more IT systems, said one or more IT systems, said one or more hardware components and said one or more IT systems being manifestations (manifested conceptual components) of said plurality of conceptual components in an implementation of said IT solution, and said plurality of operational concepts indicating interactions among said manifested conceptual components to perform said plurality of functions of said business, wherein said developing said conceptual structure includes: defining said conceptual structure based on a functional analysis of said plurality of functions of said business by said one or more business stakeholders and said one or more IT stakeholders; and subsequent to said defining said conceptual structure, refining said conceptual structure by: refining said conceptual structure based on a first analysis of interactions of one or more users with said IT solution; refining said conceptual structure based on a second analysis of a business model of said business; refining said conceptual structure based on a third analysis of how said manifested conceptual components interact with each other to support a business operational model of said business, said business operational model being a description by said one or more business stakeholders of how said business operates to attain one or more operational goals of said business; refining said conceptual structure based on a fourth analysis of one or more internal processes and one or more algorithms, said one or more internal processes associated with an operation of a set of manifested conceptual components included in said manifested conceptual components and with interactions therebetween, and said one or more algorithms associated with said operation of said set of manifested conceptual components and with said interactions therebetween; refining said conceptual structure based on a fifth analysis of one or more requirements for communication among said manifested conceptual components, between said IT solution and one or more systems of said IT solution, and between said IT solution and one or more systems external to said IT solution; refining said conceptual structure based on a sixth analysis of one or more requirements for capturing, storing, retrieving and managing information internal to said one or more systems of said IT solution; and refining said conceptual structure based on a seventh analysis of non-functional requirements of said IT solution, wherein a result of said refining said conceptual structure is a refinement of said conceptual structure, wherein said refinement includes a new conceptual component added to said plurality of conceptual components, wherein said refinement further includes a partition of a conceptual component of said plurality of conceptual components into two or more conceptual components that are added to said plurality of conceptual components and/or an aggregation of at least two conceptual components of said plurality of conceptual components into a new composite conceptual component added to said plurality of conceptual components, wherein said subsequently developing said plurality of operational concepts includes: prior to developing an architecture and a design of said IT solution, generating a description of said plurality of operational concepts based on said refinement of said conceptual structure, said description including: a first description of said plurality of conceptual components included in said refinement of said conceptual structure, a second description of said plurality of functions, said one or more internal processes, and said one or more algorithms supported by said manifested conceptual components represented by said plurality of conceptual components included in said refinement of said conceptual structure, a third description of information management needs of said manifested conceptual components represented by said plurality of conceptual components included in said refinement of said conceptual structure, a fourth description of how said manifested conceptual components represented by said plurality of conceptual components included in said refinement of said conceptual structure interact among themselves to perform said plurality of functions of said business, a fifth description of how said business model relates to an organization of said plurality of conceptual components included in said refinement of said conceptual structure, and a sixth description of how said non-functional requirements are addressed by said IT solution and by said manifested conceptual components represented by said plurality of components included in said refinement of said conceptual structure; and generating a diagram representing an overview of said IT solution and including said refinement of said conceptual structure; a computing system retrieving said diagram representing said overview of said IT solution and including said refinement of said conceptual structure and generating a documentation that includes said diagram and said description of said plurality of operational concepts; developing said architecture and said design of said IT solution by said one or more IT stakeholders based on said developed conceptual model and said documentation that includes said diagram representing said overview of said IT solution and said description of said plurality of operational concepts, wherein said description of said plurality of operational concepts included in said documentation that is a basis for said architecture and said design of said IT solution indicates said interactions among said manifested conceptual components to perform said plurality of functions of said business; and generating, by said one or more IT stakeholders, a second documentation of said architecture and said design of said IT solution. 14. The process of claim 11 , wherein said refining said conceptual structure includes generating said plurality of conceptual components as a plurality of modular representations that are independent of any technology used to implement said one or more IT systems represented by said plurality of conceptual components. | 0.905905 |
11. The system of claim 8 , said program code further comprising: program code for, in the event said sub-thread is determined to be off-topic with respect to said discussion thread, notifying said moderator user that said sub-thread has been determined to be off-topic, and enabling said moderator user to indicate that said sub-thread is to be moved to a new discussion thread. | 11. The system of claim 8 , said program code further comprising: program code for, in the event said sub-thread is determined to be off-topic with respect to said discussion thread, notifying said moderator user that said sub-thread has been determined to be off-topic, and enabling said moderator user to indicate that said sub-thread is to be moved to a new discussion thread. 12. The system of claim 11 , said program code further comprising: program code for, in the event said sub-thread is determined to be off-topic with respect to said discussion thread, enabling said moderator user to indicate that said sub-thread is to be deleted. | 0.867595 |
1. A method of communicating information in a telecommunications system that is organized into a plurality of heterogeneous telecommunication domains, the method comprising: receiving, in a processor of a first domain orchestrator component, an implementation agnostic policy-charging service request message from a continuum orchestrator component, wherein: all components in the telecommunications system involved in delivery of a first service are grouped into at least one of a plurality of domains, each domain in the plurality of domains includes different components than every other domain in plurality of domains, the plurality of domains includes at least a first domain and a second domain, each of the components in the first domain implement domain-specific rules that are specific to the first domain, the components in the first domain collectively provide a first functionality for the delivery of the first service, the components in the second domain collectively provide a second functionality for the delivery of the first service, each of the components in the second domain implement domain-specific rules that are specific to the second domain, the first domain includes the first domain orchestrator component, the second domain includes a second domain orchestrator component, and the received implementation agnostic policy-charging service request message includes information identifying a functional service requirement for the delivery of the first service generating, by the processor of the first domain orchestrator component, implementation-and-domain-specific resource rules based on information included in the received implementation agnostic policy-charging service request message, the generated implementation-and-domain-specific resource rules including at least one domain-specific charging rule that is specific to the first domain; identifying, by the processor of the first domain orchestrator component, a policy component and a charging component in the first domain for enforcing the generated implementation-and-domain-specific resource rules; and sending at least one of the generated implementation-and-domain-specific resource rules to each of the identified policy and charging components. | 1. A method of communicating information in a telecommunications system that is organized into a plurality of heterogeneous telecommunication domains, the method comprising: receiving, in a processor of a first domain orchestrator component, an implementation agnostic policy-charging service request message from a continuum orchestrator component, wherein: all components in the telecommunications system involved in delivery of a first service are grouped into at least one of a plurality of domains, each domain in the plurality of domains includes different components than every other domain in plurality of domains, the plurality of domains includes at least a first domain and a second domain, each of the components in the first domain implement domain-specific rules that are specific to the first domain, the components in the first domain collectively provide a first functionality for the delivery of the first service, the components in the second domain collectively provide a second functionality for the delivery of the first service, each of the components in the second domain implement domain-specific rules that are specific to the second domain, the first domain includes the first domain orchestrator component, the second domain includes a second domain orchestrator component, and the received implementation agnostic policy-charging service request message includes information identifying a functional service requirement for the delivery of the first service generating, by the processor of the first domain orchestrator component, implementation-and-domain-specific resource rules based on information included in the received implementation agnostic policy-charging service request message, the generated implementation-and-domain-specific resource rules including at least one domain-specific charging rule that is specific to the first domain; identifying, by the processor of the first domain orchestrator component, a policy component and a charging component in the first domain for enforcing the generated implementation-and-domain-specific resource rules; and sending at least one of the generated implementation-and-domain-specific resource rules to each of the identified policy and charging components. 5. The method of claim 1 , wherein the first domain is a user equipment domain. | 0.65187 |
11. The computer program product of claim 10 including the further program instruction using historical statistics data to identify the past behavior of said components and combining the enriched alert and identified past behavior of said components to generate at least one alert resolution action. | 11. The computer program product of claim 10 including the further program instruction using historical statistics data to identify the past behavior of said components and combining the enriched alert and identified past behavior of said components to generate at least one alert resolution action. 14. The computer program product of claim 11 wherein the said computer network is made of several data centers. | 0.919607 |
8. The method as in claim 1 , where said regular expressions comprise a plurality of patterns, individual ones of which are comprised of at least one of characters, numbers and punctuation. | 8. The method as in claim 1 , where said regular expressions comprise a plurality of patterns, individual ones of which are comprised of at least one of characters, numbers and punctuation. 10. The method as in claim 8 , where the characters comprise upper case C, O, R, N and H. | 0.989501 |
8. The apparatus according to claim 1 , wherein the dialog unit further comprises a receiving unit configured to receive an oral input from the user, the managing unit stores speech-recognition grammars in association with the items, the dialog unit recognizes the oral input from the user in accordance with the speech-recognition grammars, and the referring unit outputs the use-disapproval notice based on recognition results. | 8. The apparatus according to claim 1 , wherein the dialog unit further comprises a receiving unit configured to receive an oral input from the user, the managing unit stores speech-recognition grammars in association with the items, the dialog unit recognizes the oral input from the user in accordance with the speech-recognition grammars, and the referring unit outputs the use-disapproval notice based on recognition results. 10. The apparatus according to claim 8 , wherein the detecting unit deletes a part of the speech-recognition grammars from the managing unit, the part being associated with an item for which the use-disapproval notice has been output. | 0.892792 |
14. The computer system of claim 13 , wherein each textual item comprises text describing events of the media file. | 14. The computer system of claim 13 , wherein each textual item comprises text describing events of the media file. 15. The computer system of claim 14 , wherein the media file comprises a video file. | 0.971144 |
25. The method of claim 24 , wherein the distributed computing cluster is an APACHE HADOOP™ cluster, the distributed file system is a HADOOP DISTRIBUTED FILE SYSTEM (HDFS™) and the data store is a “NoSQL” (No Structured Query Language) data store. | 25. The method of claim 24 , wherein the distributed computing cluster is an APACHE HADOOP™ cluster, the distributed file system is a HADOOP DISTRIBUTED FILE SYSTEM (HDFS™) and the data store is a “NoSQL” (No Structured Query Language) data store. 34. The method of claim 25 , wherein the fragments of the query correspond to plans that include partitions along scan boundaries. | 0.927411 |
16. The method of claim 1 , comprising accessing the user-specific profile to, in an automated fashion, associate at least one related word, topic, sub-topic, concept, context or connotation with the search term prior to formulating the at least one computer-executable query. | 16. The method of claim 1 , comprising accessing the user-specific profile to, in an automated fashion, associate at least one related word, topic, sub-topic, concept, context or connotation with the search term prior to formulating the at least one computer-executable query. 17. The method of claim 16 , comprising, in an automated fashion, modifying the search request to include the at least one related word, topic, sub-topic, concept, context or connotation associated with the search term as the user is inputting the search request. | 0.90575 |
15. A computer program product for creating a semantically searchable electronic medical record, said computer program product comprising a computer readable storage medium having program instructions embodied therewith, the program instructions being readable/executable by a processor, to cause said processor to perform a method comprising: receiving a query for information from an electronic medical record (EMR) comprising structured data and unstructured data; annotating contents of said unstructured data and said structured data to produce annotations; using said annotations to create concept unique identifiers (CUIs); identifying clinically relevant semantic relationships between said structured data and unstructured data in said EMR based on statistical associations between said CUIs; producing a score for relevant information from said EMR that is semantically related to said query based on strength of said clinically relevant semantic relationships between said structured data and unstructured data; prioritizing a display of said relevant information based on said score; and providing, in response to said query, said relevant information, said relevant information comprising at least one of clinical notes, medications, test results, treatments, and contraindications. | 15. A computer program product for creating a semantically searchable electronic medical record, said computer program product comprising a computer readable storage medium having program instructions embodied therewith, the program instructions being readable/executable by a processor, to cause said processor to perform a method comprising: receiving a query for information from an electronic medical record (EMR) comprising structured data and unstructured data; annotating contents of said unstructured data and said structured data to produce annotations; using said annotations to create concept unique identifiers (CUIs); identifying clinically relevant semantic relationships between said structured data and unstructured data in said EMR based on statistical associations between said CUIs; producing a score for relevant information from said EMR that is semantically related to said query based on strength of said clinically relevant semantic relationships between said structured data and unstructured data; prioritizing a display of said relevant information based on said score; and providing, in response to said query, said relevant information, said relevant information comprising at least one of clinical notes, medications, test results, treatments, and contraindications. 20. The computer program product according to claim 15 , said CUIs provide standardized identifiers relating to medical disorders related to said information in said unstructured data and said structured data. | 0.579144 |
1. A computer system for providing user-to-user online networking service over a network providing online networking service to a plurality of users, including members and non-members, comprising: a processor; a memory storing instructions that, when executed by said processor, cause said computer system to: provide functionality for said plurality of users to compose personal reviews for other users and tag said other users with words describing personality attributes; provide a first user of said plurality of users to initiate and send an anonymous message to a recipient via said network, wherein said anonymous message includes profile of said first user; insert at least two additional profiles selected from at least two of said plurality of users to said anonymous message before sending said anonymous message thereby making sender of said anonymous message unknown to said recipient; allow the recipient to respond to said anonymous message with: a) deleting said anonymous message; or b) selecting one of the profiles in said anonymous message; reveal said first user as the sender of said anonymous message to the recipient if the recipient selected the profile of said first user in said anonymous message; and generate a new anonymous message, if the recipient selected a profile other than the profile of said first user, to include profile of the recipient and at least two additional profiles selected from another at least two of said plurality of users, and deliver the new anonymous message to the user of the selected profile. | 1. A computer system for providing user-to-user online networking service over a network providing online networking service to a plurality of users, including members and non-members, comprising: a processor; a memory storing instructions that, when executed by said processor, cause said computer system to: provide functionality for said plurality of users to compose personal reviews for other users and tag said other users with words describing personality attributes; provide a first user of said plurality of users to initiate and send an anonymous message to a recipient via said network, wherein said anonymous message includes profile of said first user; insert at least two additional profiles selected from at least two of said plurality of users to said anonymous message before sending said anonymous message thereby making sender of said anonymous message unknown to said recipient; allow the recipient to respond to said anonymous message with: a) deleting said anonymous message; or b) selecting one of the profiles in said anonymous message; reveal said first user as the sender of said anonymous message to the recipient if the recipient selected the profile of said first user in said anonymous message; and generate a new anonymous message, if the recipient selected a profile other than the profile of said first user, to include profile of the recipient and at least two additional profiles selected from another at least two of said plurality of users, and deliver the new anonymous message to the user of the selected profile. 4. The computer system of claim 1 , further comprising instructions that, when executed by said processor, cause said computer system to: allow a first member of said members to make match for a second member with another user and sending a matching request to said second member and said another user. | 0.5 |
15. A method comprising: generating a wiki-type application model, the wiki-type application model being accessible or modifiable by one or more users; using the wiki-type application model to employ one or more features including data suggestion; and modifying the wiki-type application model based upon a context of a user. | 15. A method comprising: generating a wiki-type application model, the wiki-type application model being accessible or modifiable by one or more users; using the wiki-type application model to employ one or more features including data suggestion; and modifying the wiki-type application model based upon a context of a user. 16. The method of claim 15 , further comprising storing the wiki-type application model with another wiki-type application model in an Internet-accessible environment. | 0.741477 |
19. A computerized method for automatically categorizing a stroke as a line-type or shape-type, said method comprising the steps of: determining a bounding box for the stroke; determining a length, L, of a longest side of the bounding box; determining a width, W, of an adjacent side the bounding box; determining a position of a beginning point of the stroke; determining a position of an ending point of the stroke; setting the stroke to be a line-type if the position of the beginning point is within a predetermined percentage of L and W of a first corner of the bounding box, and the position of the end point is within the predetermined percentage of L and W of a second corner of the bounding box, and wherein the first and second corners are opposite corners. | 19. A computerized method for automatically categorizing a stroke as a line-type or shape-type, said method comprising the steps of: determining a bounding box for the stroke; determining a length, L, of a longest side of the bounding box; determining a width, W, of an adjacent side the bounding box; determining a position of a beginning point of the stroke; determining a position of an ending point of the stroke; setting the stroke to be a line-type if the position of the beginning point is within a predetermined percentage of L and W of a first corner of the bounding box, and the position of the end point is within the predetermined percentage of L and W of a second corner of the bounding box, and wherein the first and second corners are opposite corners. 20. The method of claim 19, wherein the predetermined percentage is less than 25%. | 0.859701 |
16. A system comprising: one or more processors; and a memory coupled to the one or more processors comprising instructions executable by the one or more processors, the one or more processors being operable when executing the instructions to: receive a search query comprising a plurality of search terms; identify in the search query a first search term of the plurality of search terms, wherein the first search term is determined to be associated with a first object type of a plurality of object types; modify the search query by optionalizing the first search term in the search query, the optionalizing being based on the first search term being determined to be associated with the first object type, wherein the optionalizing comprises requiring, from execution of the search query as modified, a particular ratio of results matching the first search term to all results; and send the search query as modified for execution against a first data store from a plurality of data stores, the first data store storing objects of the first object type. | 16. A system comprising: one or more processors; and a memory coupled to the one or more processors comprising instructions executable by the one or more processors, the one or more processors being operable when executing the instructions to: receive a search query comprising a plurality of search terms; identify in the search query a first search term of the plurality of search terms, wherein the first search term is determined to be associated with a first object type of a plurality of object types; modify the search query by optionalizing the first search term in the search query, the optionalizing being based on the first search term being determined to be associated with the first object type, wherein the optionalizing comprises requiring, from execution of the search query as modified, a particular ratio of results matching the first search term to all results; and send the search query as modified for execution against a first data store from a plurality of data stores, the first data store storing objects of the first object type. 20. The system of claim 16 , wherein to modify the search query by optionalizing the search term, the processors are operable when executing the instructions to assign a value to the search term in the search query, the search query as modified requiring, from execution of the search query as modified, the particular ratio to correspond to the assigned value. | 0.536205 |
2. The apparatus of claim 1 , wherein, the document is expressed in a nested-structure, document-specific markup language and the query further comprises: links that are associated with join conditions that define relationships among the query nodes as being children, parents, ancestors or descendants of each other; and a query root node that represents answers to be returned. | 2. The apparatus of claim 1 , wherein, the document is expressed in a nested-structure, document-specific markup language and the query further comprises: links that are associated with join conditions that define relationships among the query nodes as being children, parents, ancestors or descendants of each other; and a query root node that represents answers to be returned. 11. The computer readable medium of claim 2 , wherein the answers include a complete answer to an original, non-relaxed query, satisfying all requirements of the original query. | 0.962715 |
1. A computer implemented method comprising: receiving an abstract phrase comprising a text phrase and a variable at a particular position in the text phrase; receiving a text value for the variable; combining the text phrase of the abstract phrase and the text value according to the particular position of the variable; and applying, by a computer system, an integration rule at a boundary of the text phrase of the abstract phrase and the text value to produce an integrated phrase, the integration rule based on a language rule, wherein the integration rule changes a portion of a word of the text phrase of the abstract phrase or a portion of a word of the text value so that the text phrase and the text value comply with the integration rule. | 1. A computer implemented method comprising: receiving an abstract phrase comprising a text phrase and a variable at a particular position in the text phrase; receiving a text value for the variable; combining the text phrase of the abstract phrase and the text value according to the particular position of the variable; and applying, by a computer system, an integration rule at a boundary of the text phrase of the abstract phrase and the text value to produce an integrated phrase, the integration rule based on a language rule, wherein the integration rule changes a portion of a word of the text phrase of the abstract phrase or a portion of a word of the text value so that the text phrase and the text value comply with the integration rule. 9. The method of claim 1 , wherein the integration rule is based on a phonological rule of a language. | 0.8148 |
1. A server, comprising: a processor configured to execute a chat application, the processor receiving a request from a first electronic device of a first user to perform a first chat session utilizing the chat application with a first representative utilizing a second electronic device, the first user being an aviation industry professional and the first representative having access to field condition report data related to an aviation industry, the first chat session being viewable by the first user and a second user such that the first and second users receive the field condition report data concurrently, wherein the second electronic device receives input from the first representative in response to an inquiry input by the first user, wherein the inquiry and the input are parsed to automatically determine a subject of the first chat session, the subject relating at least to a flight location, wherein an additional user is selectively excluded access from the input received by the second electronic device, wherein the additional user is selectively excluded when the additional user is a member of an airline that does not have a flight associated with the subject of the first chat session; and a transceiver configured to receive first input data from the first user and second input data from the first representative, the first and second input data being first text to be shown in the first chat session. | 1. A server, comprising: a processor configured to execute a chat application, the processor receiving a request from a first electronic device of a first user to perform a first chat session utilizing the chat application with a first representative utilizing a second electronic device, the first user being an aviation industry professional and the first representative having access to field condition report data related to an aviation industry, the first chat session being viewable by the first user and a second user such that the first and second users receive the field condition report data concurrently, wherein the second electronic device receives input from the first representative in response to an inquiry input by the first user, wherein the inquiry and the input are parsed to automatically determine a subject of the first chat session, the subject relating at least to a flight location, wherein an additional user is selectively excluded access from the input received by the second electronic device, wherein the additional user is selectively excluded when the additional user is a member of an airline that does not have a flight associated with the subject of the first chat session; and a transceiver configured to receive first input data from the first user and second input data from the first representative, the first and second input data being first text to be shown in the first chat session. 10. The server of claim 1 , wherein the chat application is a functionality of a website. | 0.633385 |
53. A computer-readable medium encoded with a computer program comprising commands that, when executed, operate to cause a computer to perform operations comprising: receiving multiple context files from one or more third-party content providers, wherein each set of commands contains one or more commands for controlling an operation of the search engine in processing a search query input and in presenting search results, each context file is one of a plurality of predefined context files; receiving in a search engine the search query input, the search query input received from an interface provided by one of the third party content providers; aggregating the commands in the multiple context files into a set of aggregated commands; using the aggregated commands to control an organization and a presentation of the search results resulting from the processing of the search query input, including: processing the search query input using the aggregated commands to produce a context processed search query; generating context processed search results responsive to the context processed search query; and providing the context processed search results in accordance with the aggregated commands. | 53. A computer-readable medium encoded with a computer program comprising commands that, when executed, operate to cause a computer to perform operations comprising: receiving multiple context files from one or more third-party content providers, wherein each set of commands contains one or more commands for controlling an operation of the search engine in processing a search query input and in presenting search results, each context file is one of a plurality of predefined context files; receiving in a search engine the search query input, the search query input received from an interface provided by one of the third party content providers; aggregating the commands in the multiple context files into a set of aggregated commands; using the aggregated commands to control an organization and a presentation of the search results resulting from the processing of the search query input, including: processing the search query input using the aggregated commands to produce a context processed search query; generating context processed search results responsive to the context processed search query; and providing the context processed search results in accordance with the aggregated commands. 63. The computer-readable medium of claim 53 , wherein the multiple context files comprise a first context file provided by a third-party content provider having specialized knowledge of a subject identified by the search query input. | 0.570631 |
1. A data evaluation system comprising: at least one module, executing on one or more computer processors, to implement: a language and character set phase, to receive from a client device an authorized character set comprising some authorized characters from among one or more libraries of characters; a document phase including receipt of an input document, the input document comprising document characters; a detection phase including a comparison of the document characters against the authorized characters in the authorized character set to detect unauthorized characters in the input document not forming part of the authorized character set; and a reporting phase to receive from the client device a report configuration, and based on the report configuration cause display of the unauthorized characters to a user within a report. | 1. A data evaluation system comprising: at least one module, executing on one or more computer processors, to implement: a language and character set phase, to receive from a client device an authorized character set comprising some authorized characters from among one or more libraries of characters; a document phase including receipt of an input document, the input document comprising document characters; a detection phase including a comparison of the document characters against the authorized characters in the authorized character set to detect unauthorized characters in the input document not forming part of the authorized character set; and a reporting phase to receive from the client device a report configuration, and based on the report configuration cause display of the unauthorized characters to a user within a report. 4. The system of claim 1 , wherein the character set includes a group of one or more alpha, numeric, punctuation and symbols for a specific language, and wherein the specific language is a predefined or standardized language, or a custom configured language. | 0.524859 |
1. A method comprising: receiving a first query comprising an outer query that: includes one or more set operators; instantiates a particular data object using a first name; references a first instance of the particular data object using said first name; wherein at least a particular set operator of the one or more set operators includes a particular subquery that: instantiates the particular data object using a second name; references a second instance of the particular data object using said second name; based at least in part on the first query, transforming the first query to a second query that does not contain at least the particular subquery or the particular set operator; wherein the second query comprises an added predicate that is based at least in part on the particular subquery; wherein the added predicate references the first instance of the particular data object using said first name without referencing the second instance of the particular data object using said second name; and wherein the second query is semantically equivalent to the first query; generating an execution plan for executing the second query; causing execution of the second query instead of the first query based on the execution plan for executing the second query; wherein the method is performed by one or more computing devices. | 1. A method comprising: receiving a first query comprising an outer query that: includes one or more set operators; instantiates a particular data object using a first name; references a first instance of the particular data object using said first name; wherein at least a particular set operator of the one or more set operators includes a particular subquery that: instantiates the particular data object using a second name; references a second instance of the particular data object using said second name; based at least in part on the first query, transforming the first query to a second query that does not contain at least the particular subquery or the particular set operator; wherein the second query comprises an added predicate that is based at least in part on the particular subquery; wherein the added predicate references the first instance of the particular data object using said first name without referencing the second instance of the particular data object using said second name; and wherein the second query is semantically equivalent to the first query; generating an execution plan for executing the second query; causing execution of the second query instead of the first query based on the execution plan for executing the second query; wherein the method is performed by one or more computing devices. 10. The method of claim 1 , wherein the particular data object is a particular table in a database, the method further comprising: determining that the outer query and the particular subquery reference a same column of the particular table; based at least in part on determining that the outer query and the particular subquery reference a same column of the particular table, eliminating the particular subquery and generating the added predicate. | 0.640825 |
1. A method comprising: receiving invoice information from each of a plurality of applications, wherein the invoice information from the each of the plurality of applications is received in an application-specific data object format of the each of the plurality of applications; translating the invoice information into a common invoice data object format, wherein the translating is performed by a processor, the common invoice data object format comprises at least one relationship data element, and at least one custom data element, the relationship data element specifies at least one relationship between a plurality of entities, and the at least one custom data element facilitates customization of the common invoice data object format; determining essential data elements of the common invoice data object format, wherein the essential data elements are stored in a memory coupled to the processor, the essential data elements comprise an identification data element, a base data element, a pricing data element, a shipping data element, and a line item details data element, and the determining comprises invoking a business routine, wherein the business routine is one of a standard library of business routines stored by an integration server, the business routine is invoked by a business process, the business process is used to define the common data object format, the common data object format comprises a plurality of invoice objects, and an invoice object of the plurality of invoice objects comprises a globally unique identifier; and translating the invoice information in the common invoice data object to another application-specific data object format, wherein the another application-specific data object format is used by a respective application. | 1. A method comprising: receiving invoice information from each of a plurality of applications, wherein the invoice information from the each of the plurality of applications is received in an application-specific data object format of the each of the plurality of applications; translating the invoice information into a common invoice data object format, wherein the translating is performed by a processor, the common invoice data object format comprises at least one relationship data element, and at least one custom data element, the relationship data element specifies at least one relationship between a plurality of entities, and the at least one custom data element facilitates customization of the common invoice data object format; determining essential data elements of the common invoice data object format, wherein the essential data elements are stored in a memory coupled to the processor, the essential data elements comprise an identification data element, a base data element, a pricing data element, a shipping data element, and a line item details data element, and the determining comprises invoking a business routine, wherein the business routine is one of a standard library of business routines stored by an integration server, the business routine is invoked by a business process, the business process is used to define the common data object format, the common data object format comprises a plurality of invoice objects, and an invoice object of the plurality of invoice objects comprises a globally unique identifier; and translating the invoice information in the common invoice data object to another application-specific data object format, wherein the another application-specific data object format is used by a respective application. 5. The method of claim 1 , wherein the essential data elements are determined based upon elements of a plurality of application-specific data object formats. | 0.552515 |
12. A system for reducing response time in a speech interface comprising: an automatic speech recognition detector including a processor configured to construct a partially completed word sequence from a partially received utterance from a speaker received by an audio sensor; a word predictor configured to model a remainder portion for the partially received utterance using a processor based on a rich predictive model to predict the remainder portion; and a natural language vocalization generator configured to respond to the partially completed word sequence and the predicted remainder portion for the partially received utterance using a natural language vocalization generator with a vocalization, wherein the vocalization is prepared before a complete utterance is received from the speaker and conveyed to the speaker by an audio transducer. | 12. A system for reducing response time in a speech interface comprising: an automatic speech recognition detector including a processor configured to construct a partially completed word sequence from a partially received utterance from a speaker received by an audio sensor; a word predictor configured to model a remainder portion for the partially received utterance using a processor based on a rich predictive model to predict the remainder portion; and a natural language vocalization generator configured to respond to the partially completed word sequence and the predicted remainder portion for the partially received utterance using a natural language vocalization generator with a vocalization, wherein the vocalization is prepared before a complete utterance is received from the speaker and conveyed to the speaker by an audio transducer. 13. The system according to claim 12 , wherein the rich predictive model is trained with a training corpus for an automatic speech recognition detector and a training corpus for the natural guage utterance generator. | 0.570658 |
14. A system that is capable of combining rankers to perform a search operation, the system comprising: one or more processors; one or more processor-accessible tangible media storing instructions executable via the one or more processors to implement: a data log to maintain log data that includes instances of respective query-identifier pairs and user interaction information from which associated respective relevance scores may be derived, each query-identifier pair recorded to reflect a submission of a corresponding query by a user; a search unit to perform a search for a particular query to produce a set of search results; and a ranker combining unit to rank the set of search results by relevance score by combining scores from a document-based ranker and a log-based ranker into a combined score for each query-identifier pair using a weighting factor that is adapted as a function of a count of instances of a respective query-identifier pair that includes the particular query in the log data as the count changes, the weighting factor being adapted by at least decreasing a contribution of the document-based ranker to the combined score of the respective query-identifier pair as the count of the instances of the respective query-identifier pair in the log data increases. | 14. A system that is capable of combining rankers to perform a search operation, the system comprising: one or more processors; one or more processor-accessible tangible media storing instructions executable via the one or more processors to implement: a data log to maintain log data that includes instances of respective query-identifier pairs and user interaction information from which associated respective relevance scores may be derived, each query-identifier pair recorded to reflect a submission of a corresponding query by a user; a search unit to perform a search for a particular query to produce a set of search results; and a ranker combining unit to rank the set of search results by relevance score by combining scores from a document-based ranker and a log-based ranker into a combined score for each query-identifier pair using a weighting factor that is adapted as a function of a count of instances of a respective query-identifier pair that includes the particular query in the log data as the count changes, the weighting factor being adapted by at least decreasing a contribution of the document-based ranker to the combined score of the respective query-identifier pair as the count of the instances of the respective query-identifier pair in the log data increases. 20. The system as recited in claim 14 , wherein the document-based ranker is further configured to: create a feature vector from the respective query-identifier pair; and assign the feature vector a unique relevance score based on a pre-trained ranking model. | 0.538845 |
10. The one or more non-transitory computer-readable media of claim 9 , the instructions further comprising instructions, which when executed by one or more hardware processors cause: extracting a second set of data from one or more data sources; and applying a data modification rule to the second set of data to generate, at least in part, the first set of data. | 10. The one or more non-transitory computer-readable media of claim 9 , the instructions further comprising instructions, which when executed by one or more hardware processors cause: extracting a second set of data from one or more data sources; and applying a data modification rule to the second set of data to generate, at least in part, the first set of data. 13. The one or more non-transitory computer-readable media of claim 10 , wherein the data modification rule comprises a rule for joining the second set of data with a third set of data. | 0.901584 |
1. A method, performed by a computing system, for generating trending action statistics that match a query, comprising: receiving, by a server, the query identifying one or more of: a search action or a search action target; selecting a set of posts relevant to the query, the set of posts comprising one or more action posts that contain at least one sentence that specifies a post action and a post action target; for one or more selected action posts of the one or more action posts: dividing the selected action post into one or more sentences; creating, for at least one action sentence of the one or more sentences, a dependency structure correlating a performed action identified in the action sentence with an action target identified in the action sentence, wherein the identification of the performed action comprises a first identifier, within the action sentence, corresponding to the performed action, and wherein the identification of the action target comprises a second identifier, within the action sentence, corresponding to one or more objects of the action sentence; determining, based on the dependency structure, that the selected action post matches the query by: determining that the search action specified in the query matches the performed action identified in the dependency structure; or determining that the search action target specified in the query matches the action target identified in the dependency structure; in response to determining that the selected action post matches the query, updating a count of matching actions or a count of matching action targets corresponding to the action or action target identified in the dependency structure; communicating between the server and a database to generate a response to the query by computing statistics based on the count of matching actions or the count of matching action targets; and providing the response to the query. | 1. A method, performed by a computing system, for generating trending action statistics that match a query, comprising: receiving, by a server, the query identifying one or more of: a search action or a search action target; selecting a set of posts relevant to the query, the set of posts comprising one or more action posts that contain at least one sentence that specifies a post action and a post action target; for one or more selected action posts of the one or more action posts: dividing the selected action post into one or more sentences; creating, for at least one action sentence of the one or more sentences, a dependency structure correlating a performed action identified in the action sentence with an action target identified in the action sentence, wherein the identification of the performed action comprises a first identifier, within the action sentence, corresponding to the performed action, and wherein the identification of the action target comprises a second identifier, within the action sentence, corresponding to one or more objects of the action sentence; determining, based on the dependency structure, that the selected action post matches the query by: determining that the search action specified in the query matches the performed action identified in the dependency structure; or determining that the search action target specified in the query matches the action target identified in the dependency structure; in response to determining that the selected action post matches the query, updating a count of matching actions or a count of matching action targets corresponding to the action or action target identified in the dependency structure; communicating between the server and a database to generate a response to the query by computing statistics based on the count of matching actions or the count of matching action targets; and providing the response to the query. 3. The method of claim 1 wherein creating the dependency structure comprises identifying words on a predefined action word list. | 0.601085 |
14. A trap semaphore as recited in claim 13 wherein said second means includes a trap event processing demand device for establishing an interest in at least a second type event occurrence which is not certain to occur in at least a second of said processes. | 14. A trap semaphore as recited in claim 13 wherein said second means includes a trap event processing demand device for establishing an interest in at least a second type event occurrence which is not certain to occur in at least a second of said processes. 15. A trap semaphore as recited in claim 14 including an event variable device, associated with said event processing device, for posting thereon said first type event occurrences as they occur. | 0.884876 |
1. A computer implemented method of enabling an ontology system to provide enhanced search capability, wherein said ontology system maintains information in the form of a plurality of ontologies, wherein each of said plurality of ontologies contains a corresponding plurality of nodes and a corresponding plurality of edges, some of said plurality of edges being of a corresponding one of a plurality of relationship types between a corresponding pair of said plurality of nodes, wherein the relationship type of an edge identifies the specific relation represented by the edge, said method comprising: receiving a search request specifying a set of nodes and a set of edges of interest, said search request further specifying a corresponding one of a set of relationship types for each of said set of edges of interest, wherein said received search request contains express data which explicitly identifies each of said set of nodes, said set of edges of interest and said set of relationship types, wherein said set of relationship types is contained in said plurality of relationship types; determining a set of ontologies matching said search request based on said set of nodes and said set of edges of interest, wherein said set of ontologies is contained in said plurality of ontologies, wherein said set of ontologies contains a first ontology and a second ontology, said first ontology and said second ontology respectively containing a first edge and a second edge, wherein both of said first edge and said second edge are between a same pair of nodes of said first ontology and said second ontology, wherein both of said same pair of nodes are contained in said set of nodes received in said search request, wherein said first edge in said first ontology is of a first relationship type matching the corresponding relationship type explicitly identified for a first edge of interest in said search request, wherein said first edge of interest is also between said same pair of nodes in said search request, wherein said second edge in said second ontology is not of said first relationship type; computing a match score for each of said set of ontologies, wherein a first match score and a second match score are respectively computed for said first ontology and said second ontology, wherein said first edge contributes more to said first match score than said second edge contributes to said second match score in view of said first edge being of said first relationship type in said first ontology, and said second edge not being of said first relationship type in said second ontology, ranking said set of ontologies according to the computed match scores; and sending a data indicating said set of ontologies and corresponding ranks as a result of said search request. | 1. A computer implemented method of enabling an ontology system to provide enhanced search capability, wherein said ontology system maintains information in the form of a plurality of ontologies, wherein each of said plurality of ontologies contains a corresponding plurality of nodes and a corresponding plurality of edges, some of said plurality of edges being of a corresponding one of a plurality of relationship types between a corresponding pair of said plurality of nodes, wherein the relationship type of an edge identifies the specific relation represented by the edge, said method comprising: receiving a search request specifying a set of nodes and a set of edges of interest, said search request further specifying a corresponding one of a set of relationship types for each of said set of edges of interest, wherein said received search request contains express data which explicitly identifies each of said set of nodes, said set of edges of interest and said set of relationship types, wherein said set of relationship types is contained in said plurality of relationship types; determining a set of ontologies matching said search request based on said set of nodes and said set of edges of interest, wherein said set of ontologies is contained in said plurality of ontologies, wherein said set of ontologies contains a first ontology and a second ontology, said first ontology and said second ontology respectively containing a first edge and a second edge, wherein both of said first edge and said second edge are between a same pair of nodes of said first ontology and said second ontology, wherein both of said same pair of nodes are contained in said set of nodes received in said search request, wherein said first edge in said first ontology is of a first relationship type matching the corresponding relationship type explicitly identified for a first edge of interest in said search request, wherein said first edge of interest is also between said same pair of nodes in said search request, wherein said second edge in said second ontology is not of said first relationship type; computing a match score for each of said set of ontologies, wherein a first match score and a second match score are respectively computed for said first ontology and said second ontology, wherein said first edge contributes more to said first match score than said second edge contributes to said second match score in view of said first edge being of said first relationship type in said first ontology, and said second edge not being of said first relationship type in said second ontology, ranking said set of ontologies according to the computed match scores; and sending a data indicating said set of ontologies and corresponding ranks as a result of said search request. 6. The method of claim 1 , wherein each node of interest represents one of a concept, instance, and property, and each edge of interest represents one of a relation and a link existing between two nodes, said computing further comprising: associating a corresponding importance for each of said set of nodes of interest, wherein the importance of a node of interest is determined based on whether each of the adjacent nodes of interest is a concept, instance or property, wherein nodes of interest connected by a corresponding single edge to a specific node of interest are said to be adjacent nodes with respect to said specific node of interest; calculating the match score for each ontology to be higher if the ontology contains a matching node of higher importance than if the ontology contains matching node of lower importance. | 0.502787 |
1. A method for identifying one or more queries related to a given query, the method comprising: receiving a query written according to one or more writing systems of a language with multiple writing systems; identifying a candidate set of queries written according to one or more writing systems of the language with multiple writing systems; calculating a number of common characters in a given candidate query before disagreement with the query received; calculating a number of total common characters between the given candidate query and the query received; calculating a quotient of the frequency with which a selected query from the candidate set follows the received query in one or more query logs and the frequency of the received query in the one or more query logs; and calculating a similarity score on the basis of the number of characters before disagreements, the number of total common characters and the quotient of the frequency with which a selected query from the candidate set follows the received query in one or more query logs and the frequency of the received query in the one or more query logs, wherein the similarity score indicates the similarity of the one or more queries with respect to the query received. | 1. A method for identifying one or more queries related to a given query, the method comprising: receiving a query written according to one or more writing systems of a language with multiple writing systems; identifying a candidate set of queries written according to one or more writing systems of the language with multiple writing systems; calculating a number of common characters in a given candidate query before disagreement with the query received; calculating a number of total common characters between the given candidate query and the query received; calculating a quotient of the frequency with which a selected query from the candidate set follows the received query in one or more query logs and the frequency of the received query in the one or more query logs; and calculating a similarity score on the basis of the number of characters before disagreements, the number of total common characters and the quotient of the frequency with which a selected query from the candidate set follows the received query in one or more query logs and the frequency of the received query in the one or more query logs, wherein the similarity score indicates the similarity of the one or more queries with respect to the query received. 21. The method of claim 1 comprising selecting one or more of the queries from the candidate set for distribution. | 0.72629 |
14. The non-transitory computer readable medium of claim 13 , wherein the data structure is further partitioned based on at least one selected from a group consisting of a class, a type, and a length of the target OSN user profile tokens, wherein the class comprises a key attribute class where the target OSN user profile key token belongs, a derivable attribute class where the target OSN user profile derived token belongs, and a statistical attribute class, and wherein the type comprises an alphabetic type and a numeric type. | 14. The non-transitory computer readable medium of claim 13 , wherein the data structure is further partitioned based on at least one selected from a group consisting of a class, a type, and a length of the target OSN user profile tokens, wherein the class comprises a key attribute class where the target OSN user profile key token belongs, a derivable attribute class where the target OSN user profile derived token belongs, and a statistical attribute class, and wherein the type comprises an alphabetic type and a numeric type. 15. The non-transitory computer readable medium of claim 14 , wherein the first tally and the second tally are generated using the data structure based on at least one of the class, the type, and the length. | 0.9373 |
37. A computer system for generating a computer program, the computer program having a plurality of high-level computational constructs, each high-level computational construct having a behavior, the computer system comprising: a component that creates an intentional program tree by direct manipulation of the intentional program tree, the intentional program tree having nodes representing the high-level computational constructs of the computer program; a component that reduces the intentional program tree to a reduced program tree, the reduced program tree having nodes representing low-level computational constructs, each high-level computational construct having a reduction enzyme for reducing a node representing the high-level computational construct into one or more nodes that implement the behavior of the high-level computational construct, each of the nodes representing a low-level computational construct; a component that adds a new high-level computational construct for use in creating the intentional program tree, the new high-level computational construct having a reduction enzyme, the new high-level computational construct for use in the intentional program tree; and a component that generates executable code based in the reduced program tree. | 37. A computer system for generating a computer program, the computer program having a plurality of high-level computational constructs, each high-level computational construct having a behavior, the computer system comprising: a component that creates an intentional program tree by direct manipulation of the intentional program tree, the intentional program tree having nodes representing the high-level computational constructs of the computer program; a component that reduces the intentional program tree to a reduced program tree, the reduced program tree having nodes representing low-level computational constructs, each high-level computational construct having a reduction enzyme for reducing a node representing the high-level computational construct into one or more nodes that implement the behavior of the high-level computational construct, each of the nodes representing a low-level computational construct; a component that adds a new high-level computational construct for use in creating the intentional program tree, the new high-level computational construct having a reduction enzyme, the new high-level computational construct for use in the intentional program tree; and a component that generates executable code based in the reduced program tree. 38. The computer system of claim 37 wherein a high-level computational construct has two different reduction enzymes and a user selects one of the different reduction enzymes for reducing the high-level computational construct. | 0.542703 |
9. An article of manufacture comprising at least one data storage device having one or more computer programs stored thereon and operable on one or more computing systems to: normalize a plurality of keywords received from a source, the source being from the group: a search query and a product listing; filter the normalized plurality of keywords against one or more keyword filtration lists; produce site-specific variants of the filtered plurality of keywords; associate a plurality of levels of dimension data with each of the plurality of keywords, the plurality of levels of dimension data including information indicative of a probability that a keyword of the plurality of keywords belongs to a particular product category in a product category hierarchy, the plurality of levels of dimension data including keyword clustering dimension data, the keyword clustering dimension data including information indicative of a probability that a keyword of the plurality of keywords belongs to a particular keyword cluster of a plurality of pre-defined keyword clusters, the plurality of levels of dimension data including keyword traffic dimension data, the keyword traffic dimension data including information indicative of a probability that a keyword of the plurality of keywords was trafficked by a particular search engine, wherein the probability that a keyword of the plurality of keywords was trafficked by a particular search engine is maintained for each of a plurality of search engines, the keyword traffic dimension data including information indicative of a probability that a keyword of the plurality of keywords will achieve a predicted revenue per click level, the keyword traffic dimension data including information indicative of a value related to confirmed registered users, the keyword traffic dimension data including information indicative of a landing page related to a particular cluster of keywords; define a time period of measurement for a metric corresponding to the plurality of levels of dimension data; and store the processed plurality of keywords and dimension data in a keyword database and select at least one keyword from the stored processed plurality of keywords according to the dimension data in the keyword database. | 9. An article of manufacture comprising at least one data storage device having one or more computer programs stored thereon and operable on one or more computing systems to: normalize a plurality of keywords received from a source, the source being from the group: a search query and a product listing; filter the normalized plurality of keywords against one or more keyword filtration lists; produce site-specific variants of the filtered plurality of keywords; associate a plurality of levels of dimension data with each of the plurality of keywords, the plurality of levels of dimension data including information indicative of a probability that a keyword of the plurality of keywords belongs to a particular product category in a product category hierarchy, the plurality of levels of dimension data including keyword clustering dimension data, the keyword clustering dimension data including information indicative of a probability that a keyword of the plurality of keywords belongs to a particular keyword cluster of a plurality of pre-defined keyword clusters, the plurality of levels of dimension data including keyword traffic dimension data, the keyword traffic dimension data including information indicative of a probability that a keyword of the plurality of keywords was trafficked by a particular search engine, wherein the probability that a keyword of the plurality of keywords was trafficked by a particular search engine is maintained for each of a plurality of search engines, the keyword traffic dimension data including information indicative of a probability that a keyword of the plurality of keywords will achieve a predicted revenue per click level, the keyword traffic dimension data including information indicative of a value related to confirmed registered users, the keyword traffic dimension data including information indicative of a landing page related to a particular cluster of keywords; define a time period of measurement for a metric corresponding to the plurality of levels of dimension data; and store the processed plurality of keywords and dimension data in a keyword database and select at least one keyword from the stored processed plurality of keywords according to the dimension data in the keyword database. 15. The article of manufacture as claimed in claim 9 being further operable to associate with a keyword prediction criteria useful to predict keywords that are likely to be valuable. | 0.631841 |
6. A computing device comprising: one or more processors; one or more computer-readable storage media storing instructions executable by the one or more processors to perform acts comprising: receiving point input specifying a plurality of visual points associated with a presentation; receiving linkage input specifying one or more connections between at least two points of the plurality of visual points; receiving content input specifying contents of at least one of the plurality of visual points; receiving one or more edits associated with the presentation; editing one or more of the plurality of visual points, the one or more connections, or the contents of at least one of the plurality of visual points based on the one or more edits; generating the presentation based on the point input, the linkage input, the content input, and the one or more edits, the presentation comprising a plurality of slides having a hierarchical organization including a story level, a scene level, and a detail level; and generating, based at least in part on the linkage input, a plurality of linkages, including: a first vertical linkage between a first slide at the story level and a second slide at the scene level; and a second vertical linkage between the second slide at the scene level and a third slide at the detail level. | 6. A computing device comprising: one or more processors; one or more computer-readable storage media storing instructions executable by the one or more processors to perform acts comprising: receiving point input specifying a plurality of visual points associated with a presentation; receiving linkage input specifying one or more connections between at least two points of the plurality of visual points; receiving content input specifying contents of at least one of the plurality of visual points; receiving one or more edits associated with the presentation; editing one or more of the plurality of visual points, the one or more connections, or the contents of at least one of the plurality of visual points based on the one or more edits; generating the presentation based on the point input, the linkage input, the content input, and the one or more edits, the presentation comprising a plurality of slides having a hierarchical organization including a story level, a scene level, and a detail level; and generating, based at least in part on the linkage input, a plurality of linkages, including: a first vertical linkage between a first slide at the story level and a second slide at the scene level; and a second vertical linkage between the second slide at the scene level and a third slide at the detail level. 11. The computing device as recited in claim 6 , wherein the point input and the linkage input are specified using a graphical user interface. | 0.611299 |
1. A method comprising: receiving, by a computer system, first event data indicative of computer network activity of a plurality of users and network devices in a computer network; generating, by the computer system, classification metadata for each of the network devices and users, based on the first event data, to indicate relevance in a network security context of each of the users and network devices; identifying, by the computer system, usage relationships between one or more of the users and one or more of the network devices, based on first event data; assigning, by the computer system, usage similarity scores to the network devices based on the identified usage relationships, the usage similarity scores being indicative of which of the network devices have been used by the same or similar group of users; receiving, by the computer system, second event data indicative of computer network activity of a particular user of the plurality of users; and detecting, by the computer system and in response to the second event data, an anomaly indicative that the particular user has interacted with a particular network device with which the particular user does not normally interact, based on the usage similarity scores and the classification metadata. | 1. A method comprising: receiving, by a computer system, first event data indicative of computer network activity of a plurality of users and network devices in a computer network; generating, by the computer system, classification metadata for each of the network devices and users, based on the first event data, to indicate relevance in a network security context of each of the users and network devices; identifying, by the computer system, usage relationships between one or more of the users and one or more of the network devices, based on first event data; assigning, by the computer system, usage similarity scores to the network devices based on the identified usage relationships, the usage similarity scores being indicative of which of the network devices have been used by the same or similar group of users; receiving, by the computer system, second event data indicative of computer network activity of a particular user of the plurality of users; and detecting, by the computer system and in response to the second event data, an anomaly indicative that the particular user has interacted with a particular network device with which the particular user does not normally interact, based on the usage similarity scores and the classification metadata. 16. The method of claim 1 , wherein said assigning usage similarity scores comprises: assigning usage similarity scores to the network devices based on relationships between the users and the network devices, such that particular network devices having only a single shared user interacting with all of the particular network devices have different usage similarity scores. | 0.813187 |
17. An apparatus, comprising: one or more processors; means for creating and storing an ontology for a data store in response to receiving first user input defining the ontology, wherein the ontology comprises a plurality of data object types and a plurality of object property types; wherein each object property type, of the plurality of object property types, includes a data type of data that is associated with said each object property type; means for creating one or more parser definitions in response to receiving second user input defining the parser definitions, wherein each of the parser definitions specifies one or more sub-definitions of how to transform first input data into modified input data that is compatible with one of the object property types of the ontology for the data store; means for storing each of the one or more parser definitions in association with one of the plurality of object property types of the ontology for the data store. | 17. An apparatus, comprising: one or more processors; means for creating and storing an ontology for a data store in response to receiving first user input defining the ontology, wherein the ontology comprises a plurality of data object types and a plurality of object property types; wherein each object property type, of the plurality of object property types, includes a data type of data that is associated with said each object property type; means for creating one or more parser definitions in response to receiving second user input defining the parser definitions, wherein each of the parser definitions specifies one or more sub-definitions of how to transform first input data into modified input data that is compatible with one of the object property types of the ontology for the data store; means for storing each of the one or more parser definitions in association with one of the plurality of object property types of the ontology for the data store. 20. The apparatus of claim 17 , wherein the means for creating and storing one or more parser definitions comprises means for creating and storing one or more transformation expressions, wherein each of the transformation expressions comprises one or more syntactic patterns and a property type identifier associated with each of the syntactic patterns. | 0.835911 |
1. A method, at least partially implemented on a computer, comprising: displaying a first free floating field, a second free floating field, and text from a document written in eXtensible Markup Language (XML); determining a type of content already in the first free floating field; displaying a first user interface if the first type of content determined to already be in the first free floating field is a formula and displaying a second user interface if the first type of content determined to already be in the free floating field is text, wherein the first user interface is distinct from the second user interface, the first user interface being associated with formula entry and the second user interface being associated with text entry; receiving first additional content entered into the first free floating field by a user; interpreting the first additional content based upon the first type of content already in the first free floating field, as determined; automatically recalculating any formulas within the document, as needed, upon receipt of the first additional content; determining that a second type of content already in the second free floating field is a different type than the first type; displaying the other of the first user interface and the second user interface not displayed in the second-mentioned act of displaying; receiving second additional content entered into the second free floating field by the user; interpreting the second additional content based on the second type of content already in the second free floating field, as determined; and automatically recalculating any formulas within the document, as needed, upon receipt of the second additional content. | 1. A method, at least partially implemented on a computer, comprising: displaying a first free floating field, a second free floating field, and text from a document written in eXtensible Markup Language (XML); determining a type of content already in the first free floating field; displaying a first user interface if the first type of content determined to already be in the first free floating field is a formula and displaying a second user interface if the first type of content determined to already be in the free floating field is text, wherein the first user interface is distinct from the second user interface, the first user interface being associated with formula entry and the second user interface being associated with text entry; receiving first additional content entered into the first free floating field by a user; interpreting the first additional content based upon the first type of content already in the first free floating field, as determined; automatically recalculating any formulas within the document, as needed, upon receipt of the first additional content; determining that a second type of content already in the second free floating field is a different type than the first type; displaying the other of the first user interface and the second user interface not displayed in the second-mentioned act of displaying; receiving second additional content entered into the second free floating field by the user; interpreting the second additional content based on the second type of content already in the second free floating field, as determined; and automatically recalculating any formulas within the document, as needed, upon receipt of the second additional content. 6. The method of claim 1 , wherein a first formula is in the first free floating field, the method further comprising: displaying a third free floating field in the document; enabling the user to enter a second formula into the third free floating field, the second formula referencing the first free floating field; and upon modification of one of the first and third free floating fields, automatically recalculating the other of the first and third free floating fields. | 0.530412 |
17. A non-transitory computer readable medium storing computer executable instructions which when executed on a computer simulate a process, the instructions comprising instructions to: identify a first change made by an advertiser to a paid portion of the search advertising campaign, the first change affecting a cost of the paid portion; determine one or more effects of the first change, the one or more effects being indicative of: a change in a volume of search traffic resulting from the paid portion, and a change in a volume of search traffic resulting from an unpaid portion of the search advertising campaign; process the one or more determined effects to generate a first synergy score, wherein the first synergy score quantifies an impact of the first change on the volume of search traffic resulting from the unpaid portion; and store the first synergy score in a machine readable memory in association with an indication of the first change. | 17. A non-transitory computer readable medium storing computer executable instructions which when executed on a computer simulate a process, the instructions comprising instructions to: identify a first change made by an advertiser to a paid portion of the search advertising campaign, the first change affecting a cost of the paid portion; determine one or more effects of the first change, the one or more effects being indicative of: a change in a volume of search traffic resulting from the paid portion, and a change in a volume of search traffic resulting from an unpaid portion of the search advertising campaign; process the one or more determined effects to generate a first synergy score, wherein the first synergy score quantifies an impact of the first change on the volume of search traffic resulting from the unpaid portion; and store the first synergy score in a machine readable memory in association with an indication of the first change. 21. The computer readable medium of claim 17 , wherein the instructions further comprise instructions to: generate a mathematical model for determining an estimated synergy score based on the first synergy score and data selected from the group consisting of data representing one or more additional synergy score associated with the paid portion of the search advertising campaign, data representing one or more synergy scores associated with one or more other paid portions of other search advertising campaigns, data representing one or more ranking of one or more websites in one or more organic listings at one or more search engines during one or more periods of time, data representing one or more ranking of the website in one or more paid search listings at one or more search engines during one or more periods of time, data representing one or more click-through-rates associated with one or more organic listings of the website at one or more organic listings of the website at one or more search engines, data representing one or more click-through-rates associated with one or more paid search listings of the website at one or more search engines, data representing structure of the website, data representing structure of one or more other websites and data representing a sematic similarity of text associated with one or more organic listings of one or more websites at one or more search engines and text associated with one or more paid search listings of the website at one or more search engine; and store the mathematical model in a machine readable memory. | 0.5 |
8. The method of claim 1, further comprising providing a code set, with locations, for performing said d), wherein said d) includes accessing a selected one of the locations in the code set. | 8. The method of claim 1, further comprising providing a code set, with locations, for performing said d), wherein said d) includes accessing a selected one of the locations in the code set. 9. The method of claim 8, wherein said accessing the selected one of the locations in the code set includes calculating the position of the selected location with the token set obtained by way of said c). | 0.920946 |
29. Computer instructions stored on a computer-readable storage medium, the computer instructions configured to cause one or more computers to perform operations comprising: receiving a search query, the search query including a query label; identifying, from a data store, one or more uniform resource locator (URL) patterns, each of the one or more URL patterns including a component of a URL and at least one of a wildcard or a regular expression, and each of the one or more URL patterns being associated with a label that matches the query label; constructing a filter including: determining a filter size based on a length of the one or more URL patterns and a count of a number of URL patterns having each respective length; and constructing the filter having the filter size; and filtering one or more results of the search query using the filter. | 29. Computer instructions stored on a computer-readable storage medium, the computer instructions configured to cause one or more computers to perform operations comprising: receiving a search query, the search query including a query label; identifying, from a data store, one or more uniform resource locator (URL) patterns, each of the one or more URL patterns including a component of a URL and at least one of a wildcard or a regular expression, and each of the one or more URL patterns being associated with a label that matches the query label; constructing a filter including: determining a filter size based on a length of the one or more URL patterns and a count of a number of URL patterns having each respective length; and constructing the filter having the filter size; and filtering one or more results of the search query using the filter. 38. The computer instructions of claim 29 , wherein the label includes a term being associated with at token that indicates that the term is a label. | 0.657569 |
11. One or more non-transitory machine-readable media storing instructions that are executable by one or more processing devices to perform operations comprising: receiving an input query for a subject having a web site; determining that the input query is a navigational query, the navigational query comprising a query to locate the web site of the subject; and in response to determining that the input query is a navigational query: identifying a first page on a social network, the first page being a page specific to the subject within the social network; obtaining content from the first page; obtaining search results corresponding to the input query; identifying a second page for the subject from among the search results, the second page comprising a page of the web site and being represented in the search results by a snippet of content associated with the second page; combining the content from the first page with the snippet to thereby produce combined content; and outputting data corresponding to the combined content to display the combined content in search results. | 11. One or more non-transitory machine-readable media storing instructions that are executable by one or more processing devices to perform operations comprising: receiving an input query for a subject having a web site; determining that the input query is a navigational query, the navigational query comprising a query to locate the web site of the subject; and in response to determining that the input query is a navigational query: identifying a first page on a social network, the first page being a page specific to the subject within the social network; obtaining content from the first page; obtaining search results corresponding to the input query; identifying a second page for the subject from among the search results, the second page comprising a page of the web site and being represented in the search results by a snippet of content associated with the second page; combining the content from the first page with the snippet to thereby produce combined content; and outputting data corresponding to the combined content to display the combined content in search results. 17. The one or more non-transitory machine-readable media of claim 11 , wherein at least part of a first process that comprises determining that the input query is a navigational query, identifying the first page on the social network for the subject, and obtaining content from the first page is performed in parallel with at least part of a second process that comprises obtaining the search results corresponding to the input query. | 0.5 |
23. A non-transitory computer readable storage medium storing at least one program for execution by a computer system, the at least one program comprising instructions for: storing, for each website of a multiplicity of websites, a corresponding current crawl rate limit; comparing a maximum crawl rate for the respective website over a defined period of time with the current crawl rate limit for crawling the respective website to determine if the current crawl rate limit is a limiting factor in crawling the respective website; and performing a website crawling management function in accordance with the determination of whether the current crawl rate limit is the limiting factor in crawling the respective website; and providing a crawl rate control mechanism to a respective owner of the respective website, wherein the crawl rate control mechanism enables selection of a new crawl rate limit corresponding to the respective website by the respective owner. | 23. A non-transitory computer readable storage medium storing at least one program for execution by a computer system, the at least one program comprising instructions for: storing, for each website of a multiplicity of websites, a corresponding current crawl rate limit; comparing a maximum crawl rate for the respective website over a defined period of time with the current crawl rate limit for crawling the respective website to determine if the current crawl rate limit is a limiting factor in crawling the respective website; and performing a website crawling management function in accordance with the determination of whether the current crawl rate limit is the limiting factor in crawling the respective website; and providing a crawl rate control mechanism to a respective owner of the respective website, wherein the crawl rate control mechanism enables selection of a new crawl rate limit corresponding to the respective website by the respective owner. 31. The non-transitory computer program product of claim 23 , wherein the at least one program further comprises instructions for providing, for display, resource usage statistics corresponding to resources of the respective website used during a plurality of prior crawl visits of the website. | 0.570911 |
6. The method of claim 1 , further comprising: detecting an additional key selection as a further ambiguous input; generating a second set of predicted language objects corresponding to the ambiguous input and the further ambiguous input; and replacing the first predicted language object provided at the text input location with a second predicted language object selected from the second set of predicted language objects. | 6. The method of claim 1 , further comprising: detecting an additional key selection as a further ambiguous input; generating a second set of predicted language objects corresponding to the ambiguous input and the further ambiguous input; and replacing the first predicted language object provided at the text input location with a second predicted language object selected from the second set of predicted language objects. 7. The method of claim 6 , wherein a number of predicted language objects in the first set is larger than a number of predicted language objects in the second set. | 0.817947 |
1. A method for classifying a video file according to one or more scene classes, the video file including a plurality of frames, where each frame of the plurality of frames includes a plurality of pixels, and where each pixel of the plurality of pixels is associated with a vector of material classification scores describing material content in its respective frame, comprising: for each frame of the plurality of frames, generating one or more scene classification scores associated with each of the one or more scene classes by: dividing the frame into a plurality of grid cells; retrieving the vector of material classification scores for each pixel in the frame; for each grid cell of the plurality of grid cells, averaging the material classification scores across each pixel in the grid cell to form a material occurrence vector for the grid cell; concatenating the material occurrence vectors for each grid cell of the plurality of grid cells to generate a material arrangement vector for the frame; and based on the material arrangement vector generated for the frame, generating the one or more scene classification scores associated with each of the one or more scene classes using one or more scene classifiers; based on the one or more scene classification scores generated for each frame of the plurality of frames, generating a representative scene classification score for each of the one or more scene classes; and for each of the generated representative scene classification scores that is above a predetermined threshold value, labeling the video file according to the respective scene classes associated with the scene classification scores that are above the predetermined threshold value. | 1. A method for classifying a video file according to one or more scene classes, the video file including a plurality of frames, where each frame of the plurality of frames includes a plurality of pixels, and where each pixel of the plurality of pixels is associated with a vector of material classification scores describing material content in its respective frame, comprising: for each frame of the plurality of frames, generating one or more scene classification scores associated with each of the one or more scene classes by: dividing the frame into a plurality of grid cells; retrieving the vector of material classification scores for each pixel in the frame; for each grid cell of the plurality of grid cells, averaging the material classification scores across each pixel in the grid cell to form a material occurrence vector for the grid cell; concatenating the material occurrence vectors for each grid cell of the plurality of grid cells to generate a material arrangement vector for the frame; and based on the material arrangement vector generated for the frame, generating the one or more scene classification scores associated with each of the one or more scene classes using one or more scene classifiers; based on the one or more scene classification scores generated for each frame of the plurality of frames, generating a representative scene classification score for each of the one or more scene classes; and for each of the generated representative scene classification scores that is above a predetermined threshold value, labeling the video file according to the respective scene classes associated with the scene classification scores that are above the predetermined threshold value. 8. The method of claim 1 , where each of the one or more scene classification scores represents the probability that the frame includes content associated with each of the respective one or more scene classes. | 0.54191 |
2. The method of claim 1 , wherein the determining a preferred language comprises accessing a client processing device associated with the second user. | 2. The method of claim 1 , wherein the determining a preferred language comprises accessing a client processing device associated with the second user. 3. The method of claim 2 , further comprising: outputting the electronic message in the preferred language for display in a transcript window associated with the second user. | 0.929092 |
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