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1. An explanatory-description adding apparatus comprising: a collecting unit that collects the certain time associated with the scene and text information associated with the scene at the certain time; a clipping unit that clips partial text information from the text information collected by the collecting unit; an extracting unit that collectively extracts a plurality of scenes that are physically different but logically the same from among the collected scenes, as the same scenes; a weighting unit that analyzes the partial text information associated with the scenes that are collectively extracted by the extracting unit as the same scenes, and weights word information included in the partial text information for each of the scenes; an extracting unit that extracts the word information exceeding a predetermined threshold value, as the metadata of the scene associated with the word information; a storage unit that stores scene metadata as combinations of the scene at the certain time in video contents and a group of metadata representing characteristics of the scene; an input unit that inputs a scene group including a plurality of the scenes; a retrieving unit that retrieves a group of metadata corresponding to the respective scenes included in the scene group, from the scene metadata; and an adding unit that selects combinations of the metadata having a difference by deleting metadata appearing in all scenes of the scene group such that a distance among the metadata is a maximum for the scenes included in the scene group, based on a combination of the scene and the metadata retrieved by the retrieving unit, and adds the metadata to the scenes of the scene group, as explanatory descriptions, wherein, when the deleting of the metadata appearing in all scenes of the scene group deletes all of the metadata for a first scene in the scene group and a second scene in the scene group has remaining metadata, the adding unit adds metadata for the first scene as a time-series description using a temporal relationship with the second scene. | 1. An explanatory-description adding apparatus comprising: a collecting unit that collects the certain time associated with the scene and text information associated with the scene at the certain time; a clipping unit that clips partial text information from the text information collected by the collecting unit; an extracting unit that collectively extracts a plurality of scenes that are physically different but logically the same from among the collected scenes, as the same scenes; a weighting unit that analyzes the partial text information associated with the scenes that are collectively extracted by the extracting unit as the same scenes, and weights word information included in the partial text information for each of the scenes; an extracting unit that extracts the word information exceeding a predetermined threshold value, as the metadata of the scene associated with the word information; a storage unit that stores scene metadata as combinations of the scene at the certain time in video contents and a group of metadata representing characteristics of the scene; an input unit that inputs a scene group including a plurality of the scenes; a retrieving unit that retrieves a group of metadata corresponding to the respective scenes included in the scene group, from the scene metadata; and an adding unit that selects combinations of the metadata having a difference by deleting metadata appearing in all scenes of the scene group such that a distance among the metadata is a maximum for the scenes included in the scene group, based on a combination of the scene and the metadata retrieved by the retrieving unit, and adds the metadata to the scenes of the scene group, as explanatory descriptions, wherein, when the deleting of the metadata appearing in all scenes of the scene group deletes all of the metadata for a first scene in the scene group and a second scene in the scene group has remaining metadata, the adding unit adds metadata for the first scene as a time-series description using a temporal relationship with the second scene. 4. The apparatus according to claim 1 , wherein the text information collected by the collecting unit is an electronic program guide (EPG) that is text information associated with the scene at the certain time in the video contents. | 0.632492 |
3. The method of claim 1 , wherein generating a search result comprises: identifying topics that are commonly associated with the keyword; and including the identified topics in the search result. | 3. The method of claim 1 , wherein generating a search result comprises: identifying topics that are commonly associated with the keyword; and including the identified topics in the search result. 4. The method of claim 3 , wherein the search result comprises a plurality of topic categories, each category associated with an identified topic that is commonly associated with the keyword. | 0.934959 |
1. A control device that can be connected to and controls a recording device that records on a recording medium and stores a plurality of font groups each storing font data for a plurality of characters used to record text on the recording medium, the control device comprising a processor and a non-transitory computer readable medium having code executable by the processor, the control device comprising: a table processing unit that creates or updates a character code conversion table that correlates each of a plurality of universal character codes that are rendered in a single font group and are specified from the control device side to information identifying a font group on the recording device side containing font data corresponding to the universal character code and information denoting the storage address of the font data in the font group; and a conversion processing unit that, when a recording job instructing the recording device to record a character is asserted, converts a universal character code contained in the recording job to a font data address based on the character code conversion table created or updated by the table processing unit. | 1. A control device that can be connected to and controls a recording device that records on a recording medium and stores a plurality of font groups each storing font data for a plurality of characters used to record text on the recording medium, the control device comprising a processor and a non-transitory computer readable medium having code executable by the processor, the control device comprising: a table processing unit that creates or updates a character code conversion table that correlates each of a plurality of universal character codes that are rendered in a single font group and are specified from the control device side to information identifying a font group on the recording device side containing font data corresponding to the universal character code and information denoting the storage address of the font data in the font group; and a conversion processing unit that, when a recording job instructing the recording device to record a character is asserted, converts a universal character code contained in the recording job to a font data address based on the character code conversion table created or updated by the table processing unit. 5. The control device described in claim 1 , wherein: the universal character codes and font data stored in the font groups can be edited. | 0.872951 |
1. A method of personalizing user call features in a policy-based network management system for a telephony call processing system, comprising: receiving from a remote system a user-entered call feature policy entered in a natural language that is understandable to a user; translating said policy from said natural language into an executable feature language capable of execution by said telephony call processing system; translating said policy from said executable feature language into a policy conflict detection language and detecting common feature interaction errors in said policy or between said policy and other policies; translating said feature interaction errors from said policy conflict detection language to said natural language that is understandable to the user and reporting said errors to the user; providing the user with a recommendation for correction of said feature interaction errors and re-integration of said policy in said executable feature language; and uploading said policy for execution by said telephony call processing system, whereby said policy is personalized and local to only said user. | 1. A method of personalizing user call features in a policy-based network management system for a telephony call processing system, comprising: receiving from a remote system a user-entered call feature policy entered in a natural language that is understandable to a user; translating said policy from said natural language into an executable feature language capable of execution by said telephony call processing system; translating said policy from said executable feature language into a policy conflict detection language and detecting common feature interaction errors in said policy or between said policy and other policies; translating said feature interaction errors from said policy conflict detection language to said natural language that is understandable to the user and reporting said errors to the user; providing the user with a recommendation for correction of said feature interaction errors and re-integration of said policy in said executable feature language; and uploading said policy for execution by said telephony call processing system, whereby said policy is personalized and local to only said user. 2. The method of claim 1 , wherein said user enters said policy via a Web browser interface. | 0.682648 |
2. An equivalence determination system comprising: a processor; an object extracting unit, executed on the processor, that extracts, from respective electronic documents in a set of electronic documents, at least one object which forms the electronic document and includes at least one of a text, a figure, and an equation; a specifying unit that specifies predetermined number of objects in the respective electronic documents based on density calculated by referring to the extracted objects; a judging unit that judges that plural electronic documents are similar based on the specified objects; a hash value calculation unit that calculates hash values of the objects specified by said specifying unit; and a feature word extraction unit that extracts a feature character string from the objects specified by said specifying unit, wherein said hash value calculation unit calculates a hash value based on the feature character string extracted by said feature word extraction unit, wherein said judging unit determines, by using the hash values calculated by said hash value calculation unit, whether the objects specified by said specifying unit match each other, wherein said specifying unit calculates, based on a density of the at least one object extracted by the object extracting unit, an improbability of modifying the at least one object, and specifies objects based on a calculation result, said feature word extraction unit extracts at least one feature word as the feature character string from the specified object by said specifying unit, said hash value calculation unit calculates a hash value of a character string obtained by concatenating feature words extracted by said feature word extraction unit, and registers identification information of corresponding electronic documents in a hash table, and said judging unit judges, based on a match between hash values, that the corresponding electronic documents are equivalent. | 2. An equivalence determination system comprising: a processor; an object extracting unit, executed on the processor, that extracts, from respective electronic documents in a set of electronic documents, at least one object which forms the electronic document and includes at least one of a text, a figure, and an equation; a specifying unit that specifies predetermined number of objects in the respective electronic documents based on density calculated by referring to the extracted objects; a judging unit that judges that plural electronic documents are similar based on the specified objects; a hash value calculation unit that calculates hash values of the objects specified by said specifying unit; and a feature word extraction unit that extracts a feature character string from the objects specified by said specifying unit, wherein said hash value calculation unit calculates a hash value based on the feature character string extracted by said feature word extraction unit, wherein said judging unit determines, by using the hash values calculated by said hash value calculation unit, whether the objects specified by said specifying unit match each other, wherein said specifying unit calculates, based on a density of the at least one object extracted by the object extracting unit, an improbability of modifying the at least one object, and specifies objects based on a calculation result, said feature word extraction unit extracts at least one feature word as the feature character string from the specified object by said specifying unit, said hash value calculation unit calculates a hash value of a character string obtained by concatenating feature words extracted by said feature word extraction unit, and registers identification information of corresponding electronic documents in a hash table, and said judging unit judges, based on a match between hash values, that the corresponding electronic documents are equivalent. 4. An equivalence determination system according to claim 2 , wherein said specifying unit calculates an improbability of modifying the object, based on the density of the object and a density of a peripheral object. | 0.694815 |
13. A system for converting script code of a three dimensional (3D) video having relative dynamic descriptors of objects orientation into 3D video with absolute descriptors orientation for object in the video, said system comprised of: a parsing module for identifying exchangeable dynamic objects in the video; an optimization module for parsing each frame script code of the video for analyzing dynamic descriptors of objects for determining absolute values for each descriptors including the absolute orientation values for each object in each frame; and a template generation module for creating a video template which supports the creation of customized videos by altering or exchanging dynamic objects. | 13. A system for converting script code of a three dimensional (3D) video having relative dynamic descriptors of objects orientation into 3D video with absolute descriptors orientation for object in the video, said system comprised of: a parsing module for identifying exchangeable dynamic objects in the video; an optimization module for parsing each frame script code of the video for analyzing dynamic descriptors of objects for determining absolute values for each descriptors including the absolute orientation values for each object in each frame; and a template generation module for creating a video template which supports the creation of customized videos by altering or exchanging dynamic objects. 22. The system of claim 13 , wherein the template generation module integrates the static segments and optimized scripts of the dynamic layers with absolute values and create descriptive list of all dynamic parameters. | 0.636067 |
1. A computer implemented method for stress testing a service oriented architecture based application, the computer implemented method comprising: recording a business process flow; extracting an XML document from the recorded business process flow; creating an XML document file for the extracted XML document, an XML document descriptor file comprising XPath queries for data elements in the XML document file, a configuration file comprising user input parameters obtained from the recorded business process flow, and a test input data file; generating a test script using input of the XML document file, the XML document descriptor file, and the configuration file and inserting data values from the test input data file into a template defined by the XML document file at locations specified by the XPath queries; and executing the test script. | 1. A computer implemented method for stress testing a service oriented architecture based application, the computer implemented method comprising: recording a business process flow; extracting an XML document from the recorded business process flow; creating an XML document file for the extracted XML document, an XML document descriptor file comprising XPath queries for data elements in the XML document file, a configuration file comprising user input parameters obtained from the recorded business process flow, and a test input data file; generating a test script using input of the XML document file, the XML document descriptor file, and the configuration file and inserting data values from the test input data file into a template defined by the XML document file at locations specified by the XPath queries; and executing the test script. 3. The computer implemented method of claim 1 , wherein the XML document file, the XML document descriptor file, and the test input data file are created and stored external to the test script. | 0.726421 |
10. In a computing environment, a system, comprising: a store operable to provide access to a grammar, the grammar defining a format for serializing an object, the grammar representing rules for serializing the object that preserve embedded objects and relationships in a serialized representation of the object, the grammar defining a header and a payload for serializing the object, the header including metadata of the grammar the metadata usable in de-serializing objects serialized using the grammar, the grammar having rules for de-serializing the objects based on a difference between a minor version of a first serialization engine to serialize the object and a minor version of a first de-serialization engine to de-serialize the object and a difference between a major version of the first serialization engine to serialize the object and a major version of the first de-serialization engine to de-serialize the object, the payload including an identifier of each descendent object of the object, the payload further including reference data for each reference, if any, included in the object, the reference data indicating relationships of the object, the reference data potentially referring to one or more of: an object type supported by a scripting environment in which the object resides, an object type supported by a host environment of the scripting environment, and a foreign object type that is defined outside of both the scripting environment and the host environment; and the first serialization engine operable to use the grammar to serialize the object into serialized data. | 10. In a computing environment, a system, comprising: a store operable to provide access to a grammar, the grammar defining a format for serializing an object, the grammar representing rules for serializing the object that preserve embedded objects and relationships in a serialized representation of the object, the grammar defining a header and a payload for serializing the object, the header including metadata of the grammar the metadata usable in de-serializing objects serialized using the grammar, the grammar having rules for de-serializing the objects based on a difference between a minor version of a first serialization engine to serialize the object and a minor version of a first de-serialization engine to de-serialize the object and a difference between a major version of the first serialization engine to serialize the object and a major version of the first de-serialization engine to de-serialize the object, the payload including an identifier of each descendent object of the object, the payload further including reference data for each reference, if any, included in the object, the reference data indicating relationships of the object, the reference data potentially referring to one or more of: an object type supported by a scripting environment in which the object resides, an object type supported by a host environment of the scripting environment, and a foreign object type that is defined outside of both the scripting environment and the host environment; and the first serialization engine operable to use the grammar to serialize the object into serialized data. 11. The system of claim 10 , wherein the first serialization engine is hosted in a scripting environment operable to execute scripts. | 0.541008 |
11. An apparatus for presenting a collection of digital images comprising: an electronic controller configured to retrieve a plurality of collections of digital image files, each collection consolidating digital image files into groups based on metadata before receipt of an image display request, wherein the metadata includes at least data indicative of user interaction with the digital image files in the plurality of collections subsequent to initially acquiring the digital image files, and wherein the metadata is based on a frequency of access of the digital image files by the user; the electronic controller configured to display iconic representations of the digital images files by display of the collections in a visual metaphor, wherein the visual metaphor displays the iconic representations for different collections at different sizes and positions relative to one another, and wherein the different sizes of the collections in the visual metaphor are based on the frequency of access; and the electronic controller being responsive to user input by opening a digital image file selected by a user. | 11. An apparatus for presenting a collection of digital images comprising: an electronic controller configured to retrieve a plurality of collections of digital image files, each collection consolidating digital image files into groups based on metadata before receipt of an image display request, wherein the metadata includes at least data indicative of user interaction with the digital image files in the plurality of collections subsequent to initially acquiring the digital image files, and wherein the metadata is based on a frequency of access of the digital image files by the user; the electronic controller configured to display iconic representations of the digital images files by display of the collections in a visual metaphor, wherein the visual metaphor displays the iconic representations for different collections at different sizes and positions relative to one another, and wherein the different sizes of the collections in the visual metaphor are based on the frequency of access; and the electronic controller being responsive to user input by opening a digital image file selected by a user. 13. The apparatus for presenting a collection of digital images of claim 11 wherein the electronic controller is configured to interactively display the collections of iconic representations of digital image files on a map. | 0.530483 |
1. A data classification system, comprising: an input interface configured to receive documents comprising data entries, at least some of the data entries having associated features represented directly in the documents; a data warehouse backed by a non-transitory computer readable storage medium and configured to store curated and classified data elements; a model registry storing a plurality of different model stacks, each model stack including at least one classification model and at least one confidence model that is separate from the at least classification model in the respective model stack; and processing resources including at least one processor and a memory, the memory storing instructions, the instructions being executed by the at least one processor to at least: inspect documents received via the input interface to identify, as heterogeneous input data, data entries and associated features located in the inspected documents; segment the heterogeneous input data into different, respectively homogenous processing groups, the different processing groups having associated levels of information uncertainty; for each different processing group, starting with the processing group associated with a lowest level of information uncertainty and moving upwardly: (a) identify one or more model stacks from the model registry to be executed on the respective processing group; (b) execute each identified model stack on the respective processing group to arrive at a classification result and a confidence level for each data entry in the respective processing group using the classification and confidence models in the respective model stack, wherein classification results map features from the data entries to predefined concepts associated with the classification models; (c) ensemble results from the execution of each identified model stack, using the classification results and the confidence levels, to group the data entries in the processing group into one of first and second classification type groups, the first classification type group corresponding to a confirmed classification and the second classification type group corresponding to an unconfirmed classification; (d) move each data entry in the first classification type group to a final result set; and (e) for the second classification type group: determine, for each data entry in the second classification type group, the processing group from among those processing groups not yet processed that is most closely related to it; and move each data entry in the second classification type group to the corresponding determined most closely related processing group; once all of the different processing groups have been processed in accordance with (a) through (e), treat as unclassified any data entries remaining in the second classification type group; store each data entry in the final result set, with or without additional processing, to the data warehouse, in accordance with the corresponding arrived at classification result; and reference records in the data warehouse in response to queries from a computer terminal. | 1. A data classification system, comprising: an input interface configured to receive documents comprising data entries, at least some of the data entries having associated features represented directly in the documents; a data warehouse backed by a non-transitory computer readable storage medium and configured to store curated and classified data elements; a model registry storing a plurality of different model stacks, each model stack including at least one classification model and at least one confidence model that is separate from the at least classification model in the respective model stack; and processing resources including at least one processor and a memory, the memory storing instructions, the instructions being executed by the at least one processor to at least: inspect documents received via the input interface to identify, as heterogeneous input data, data entries and associated features located in the inspected documents; segment the heterogeneous input data into different, respectively homogenous processing groups, the different processing groups having associated levels of information uncertainty; for each different processing group, starting with the processing group associated with a lowest level of information uncertainty and moving upwardly: (a) identify one or more model stacks from the model registry to be executed on the respective processing group; (b) execute each identified model stack on the respective processing group to arrive at a classification result and a confidence level for each data entry in the respective processing group using the classification and confidence models in the respective model stack, wherein classification results map features from the data entries to predefined concepts associated with the classification models; (c) ensemble results from the execution of each identified model stack, using the classification results and the confidence levels, to group the data entries in the processing group into one of first and second classification type groups, the first classification type group corresponding to a confirmed classification and the second classification type group corresponding to an unconfirmed classification; (d) move each data entry in the first classification type group to a final result set; and (e) for the second classification type group: determine, for each data entry in the second classification type group, the processing group from among those processing groups not yet processed that is most closely related to it; and move each data entry in the second classification type group to the corresponding determined most closely related processing group; once all of the different processing groups have been processed in accordance with (a) through (e), treat as unclassified any data entries remaining in the second classification type group; store each data entry in the final result set, with or without additional processing, to the data warehouse, in accordance with the corresponding arrived at classification result; and reference records in the data warehouse in response to queries from a computer terminal. 8. The system of claim 1 , wherein the ensembling is performed as a function of a level of information uncertainty and a confidence level. | 0.61021 |
2. An apparatus comprising: an input device having input elements; and a processor programmed to receive an input code having component blocks that correspond to activation groupings of input elements of the input device, translate the input code to first text, check the first text against a dictionary, and when the first text does not match an entry in the dictionary, process the component blocks to generate one or more permutations that have different activation groupings of the input elements of the input device, translate the input code to second text, which is different than the first text, in accordance with the one or more permutations, and check the second text against the dictionary to determine if the second text is usable to replace the first text, wherein the processor is programmed to replace a current component block having one digit and a next, different component block having one digit, with a new component block having two digits, when the first text does not match an entry in the dictionary. | 2. An apparatus comprising: an input device having input elements; and a processor programmed to receive an input code having component blocks that correspond to activation groupings of input elements of the input device, translate the input code to first text, check the first text against a dictionary, and when the first text does not match an entry in the dictionary, process the component blocks to generate one or more permutations that have different activation groupings of the input elements of the input device, translate the input code to second text, which is different than the first text, in accordance with the one or more permutations, and check the second text against the dictionary to determine if the second text is usable to replace the first text, wherein the processor is programmed to replace a current component block having one digit and a next, different component block having one digit, with a new component block having two digits, when the first text does not match an entry in the dictionary. 7. The apparatus of claim 2 , wherein the processor is programmed to replace the component block having two digits and a first additional, different component block having two digits, with a second additional component block having a single digit of one of the component block or the first additional component block, and a third additional component block having another three digits of the component block and the first additional component block. | 0.5 |
10. A computer-implemented method for executing instructions stored on a non-transitory computer readable storage medium, the method comprising: selecting a plurality of queries, each query structured for repeated application against a database to yield a query result that is updated over time with each repeated application; identifying query parts of individual queries; determining for each query, a relation, if any, of an included query part to any query part of remaining queries of the plurality of queries; creating, for each query, a query relationship data structure in which the query is related to at least one other query of the plurality of queries, based on the determined relation of a query part of the query and a query part of the at least one other query of the plurality of queries; storing the query relationship data structures in a query relationship data structure (RELSTRUCT) repository; calculating, for a first query and a second query of the plurality of queries, a dependency between a first query result and a second query result thereof, based on the determined relation between the query parts of the first query and the second query as determined from a corresponding RELSTRUCT; and visually displaying the first query result, the second query result, and the dependency therebetween, including maintaining the dependency with each repeated application of the first query and the second query, using the stored, corresponding RELSTRUCT, wherein the first query result includes a first Key Performance Indicator (KPI) representing a state or value for an entity in a business context, and the second query result includes a second KPI. | 10. A computer-implemented method for executing instructions stored on a non-transitory computer readable storage medium, the method comprising: selecting a plurality of queries, each query structured for repeated application against a database to yield a query result that is updated over time with each repeated application; identifying query parts of individual queries; determining for each query, a relation, if any, of an included query part to any query part of remaining queries of the plurality of queries; creating, for each query, a query relationship data structure in which the query is related to at least one other query of the plurality of queries, based on the determined relation of a query part of the query and a query part of the at least one other query of the plurality of queries; storing the query relationship data structures in a query relationship data structure (RELSTRUCT) repository; calculating, for a first query and a second query of the plurality of queries, a dependency between a first query result and a second query result thereof, based on the determined relation between the query parts of the first query and the second query as determined from a corresponding RELSTRUCT; and visually displaying the first query result, the second query result, and the dependency therebetween, including maintaining the dependency with each repeated application of the first query and the second query, using the stored, corresponding RELSTRUCT, wherein the first query result includes a first Key Performance Indicator (KPI) representing a state or value for an entity in a business context, and the second query result includes a second KPI. 11. The method of claim 10 , wherein the query relationship data structure for each corresponding query includes a combined query listing one or more references to other query relationship data structures and corresponding queries. | 0.650143 |
1. A computer implemented method of generating a plurality of specialty-oriented document databases or indices from a master index of terms within a subject matter area, said method comprising steps of assigning one or more specialties to each document, wherein said step of assigning one or more specialties is carried out by an expert in said one or more specialties, assigning a limited number of terms from said master index or codes corresponding to said terms to each document, wherein said step of assigning one or more terms or codes is carried out separately from said step of assigning one or more specialties of said plurality of specialties by an expert in said one or more specialties, said expert being a person, and wherein said step of assigning a limited number of terms or codes is based on primary relevance of material described as determined by said expert, merging results of said step of assigning one or more specialties and results of said step of assigning a limited number of terms or codes, using a computer, to form respective specialty-oriented document databases comprising said documents or respective specialty-oriented indices comprising said terms or codes corresponding to documents using terms or codes from said master index assigned to documents and which are assigned to respective specialties by said step of assigning one or more specialties to each document, wherein said method generates said plurality of specialty-oriented databases or indices of said documents which are accessible from said databases or indices in accordance with terms or codes assigned in said step of assigning a limited number of terms or codes to said documents. | 1. A computer implemented method of generating a plurality of specialty-oriented document databases or indices from a master index of terms within a subject matter area, said method comprising steps of assigning one or more specialties to each document, wherein said step of assigning one or more specialties is carried out by an expert in said one or more specialties, assigning a limited number of terms from said master index or codes corresponding to said terms to each document, wherein said step of assigning one or more terms or codes is carried out separately from said step of assigning one or more specialties of said plurality of specialties by an expert in said one or more specialties, said expert being a person, and wherein said step of assigning a limited number of terms or codes is based on primary relevance of material described as determined by said expert, merging results of said step of assigning one or more specialties and results of said step of assigning a limited number of terms or codes, using a computer, to form respective specialty-oriented document databases comprising said documents or respective specialty-oriented indices comprising said terms or codes corresponding to documents using terms or codes from said master index assigned to documents and which are assigned to respective specialties by said step of assigning one or more specialties to each document, wherein said method generates said plurality of specialty-oriented databases or indices of said documents which are accessible from said databases or indices in accordance with terms or codes assigned in said step of assigning a limited number of terms or codes to said documents. 5. The method as recited in claim 1 , wherein the documents in a respective database are limited in number to 1 to 20,000. | 0.570148 |
3. A computer implemented method for determining if an advertisement is relevant to a target document, the method comprising: identifying targeting information for the advertisement; identifying a set of one or more topics of the target document by analyzing the content of the target document; comparing the targeting information to the set of one or more topics to determine if a match exists; determining that the advertisement is relevant to the target document if the match exists; making a serving determination using the determination of whether or not the advertisement is relevant to the target document; and controlling serving of the advertisement for presentation to a requestor via a client device using the serving determination, wherein the advertisement belongs to an advertiser, wherein the targeting information includes a set of one or more topics previously provided from the advertiser, wherein analyzing the content comprises identifying a set of one or more topics by calculating weighted terms for the target document based on text within the target document, and wherein the set of one or more topics contains those of the weighted terms whose weight exceeds a defined threshold. | 3. A computer implemented method for determining if an advertisement is relevant to a target document, the method comprising: identifying targeting information for the advertisement; identifying a set of one or more topics of the target document by analyzing the content of the target document; comparing the targeting information to the set of one or more topics to determine if a match exists; determining that the advertisement is relevant to the target document if the match exists; making a serving determination using the determination of whether or not the advertisement is relevant to the target document; and controlling serving of the advertisement for presentation to a requestor via a client device using the serving determination, wherein the advertisement belongs to an advertiser, wherein the targeting information includes a set of one or more topics previously provided from the advertiser, wherein analyzing the content comprises identifying a set of one or more topics by calculating weighted terms for the target document based on text within the target document, and wherein the set of one or more topics contains those of the weighted terms whose weight exceeds a defined threshold. 11. The computer implemented method of claim 3 , wherein comparing the targeting information to the topic comprises comparing the targeting information to the topic or a related topic to determine if a match exists. | 0.535815 |
12. A speech recognition system, comprising: a processor; and a tuning engine comprising instructions that are executable by the processor to tune a speech module with respect to a particular type of utterance in response to the processor determining that a frequency of occurrence of the particular type of utterance satisfies a threshold. | 12. A speech recognition system, comprising: a processor; and a tuning engine comprising instructions that are executable by the processor to tune a speech module with respect to a particular type of utterance in response to the processor determining that a frequency of occurrence of the particular type of utterance satisfies a threshold. 14. The speech recognition system of claim 12 , wherein the threshold is from a table of thresholds, the thresholds corresponding to a plurality of utterance types. | 0.686985 |
8. A computing device, comprising: one or more processors; memory; and one or more programs stored in the memory and configured for execution by the one or more processors, the one or more programs comprising instructions for: receiving a first text string S=s 1 s 2 . . . s n having Unicode encoding and a second text string T=t 1 t 2 . . . t m having Unicode encoding, wherein n and m are positive integers, s 1 , s 2 , . . . , s n and t 1 , t 2 , . . . , t m are Unicode characters, and S is not identical to T; (1) identifying a positive integer p with s 1 =t 1 , s 2 =t 2 , . . . , s p−1 =t p−1 and s p ≠t p , wherein at least one of s p and t p is a non-ASCII character; (2) looking up the characters s p and t p in a predefined lookup table to determine a weight v p for the character s p and a weight w p for the character t p ; (3) when at least one of s p and t p is not found in the lookup table, determining the collation order of the strings S and T using Unicode weights for the corresponding strings s p s p+1 . . . s n and t p t p+1 . . . t m ; (4) when both s p and t p are found in the lookup table and v p <w p , determining that S is collated before T; (5) when both s p and t p are found in the lookup table and w p <v p , determining that T is collated before S; (6) when both s p and t p are found in the lookup table, v p =w p , and s p+1 . . . s n =t p+1 . . . t m , determining that S and T have the same collation position; and when both s p and t p are found in the lookup table, v p =w p , and s p+1 . . . s n ≠t p+1 . . . t m , determining the collation order of S and T recursively according to steps (1)-(6) using the suffix strings s p+1 . . . s n and t p+1 . . . t m . | 8. A computing device, comprising: one or more processors; memory; and one or more programs stored in the memory and configured for execution by the one or more processors, the one or more programs comprising instructions for: receiving a first text string S=s 1 s 2 . . . s n having Unicode encoding and a second text string T=t 1 t 2 . . . t m having Unicode encoding, wherein n and m are positive integers, s 1 , s 2 , . . . , s n and t 1 , t 2 , . . . , t m are Unicode characters, and S is not identical to T; (1) identifying a positive integer p with s 1 =t 1 , s 2 =t 2 , . . . , s p−1 =t p−1 and s p ≠t p , wherein at least one of s p and t p is a non-ASCII character; (2) looking up the characters s p and t p in a predefined lookup table to determine a weight v p for the character s p and a weight w p for the character t p ; (3) when at least one of s p and t p is not found in the lookup table, determining the collation order of the strings S and T using Unicode weights for the corresponding strings s p s p+1 . . . s n and t p t p+1 . . . t m ; (4) when both s p and t p are found in the lookup table and v p <w p , determining that S is collated before T; (5) when both s p and t p are found in the lookup table and w p <v p , determining that T is collated before S; (6) when both s p and t p are found in the lookup table, v p =w p , and s p+1 . . . s n =t p+1 . . . t m , determining that S and T have the same collation position; and when both s p and t p are found in the lookup table, v p =w p , and s p+1 . . . s n ≠t p+1 . . . t m , determining the collation order of S and T recursively according to steps (1)-(6) using the suffix strings s p+1 . . . s n and t p+1 . . . t m . 13. The computing device of claim 8 , wherein the one or more programs comprise instructions for computing the Unicode weights for the strings s p s p+1 . . . s n and t p t p+1 . . . t m are computed, the computation comprising: for each character, performing a lookup in a Unicode weight table to identify a respective primary weight, a respective accent weight, and a respective case-weight; forming a primary Unicode weight w p as a concatenation of the identified primary weights; forming an accent Unicode weight w a as a concatenation of the identified accent weights; forming a case Unicode weight w c as a concatenation of the identified case weights; and forming the Unicode weight as a concatenation w p +w a +w c of the primary Unicode weight, the accent Unicode weight, and the case Unicode weight. | 0.503394 |
11. A non-volatile memory system configured to store in a memory plane words containing data bits and control bits allowing an error correction with an error correction code, together with at least one piece of digital information whose value is defined by at least one position of a modified bit in at least one digital word modified with respect to at least one initial digital word not having any erroneous bit, the modified bit having a modified value with respect to the value of this bit in said at least one initial digital word, the values of the other bits of the modified digital word being identical to those of these same data bits in the initial digital word. | 11. A non-volatile memory system configured to store in a memory plane words containing data bits and control bits allowing an error correction with an error correction code, together with at least one piece of digital information whose value is defined by at least one position of a modified bit in at least one digital word modified with respect to at least one initial digital word not having any erroneous bit, the modified bit having a modified value with respect to the value of this bit in said at least one initial digital word, the values of the other bits of the modified digital word being identical to those of these same data bits in the initial digital word. 13. The system according to claim 11 , wherein the non-volatile memory system is configured to store a plurality of digital words respectively modified with respect to a respective plurality of initial digital words not having any erroneous bit, each modified digital word containing a bit having a modified value with respect to the value of this bit in a corresponding initial digital word, the other bits of the modified digital word having values identical to those of these same bits in the corresponding initial digital word, the respective positions of the modified bits in the modified digital words defining together the value of the digital information. | 0.565982 |
10. In a computer system, a computer readable storage medium containing one or more instructions for performing a method for character encoding and decoding: said method comprising translating a source data into a sequence of Unicode code points occupying the Private Use Area of the Unicode Basic Multilingual Plane, said method comprising; using one or more bits of the first code point or code points of each sequence as an identification tag, each tag identifying both the type of data encoded and the length of the data encoded; said encoding method comprising one of the following methods: a. the construction of a Unicode code point as the mathematical “OR” of the constant E000 hexadecimal with a 12-bit data value from 0 to FFF hexadecimal; said code points occupying the Unicode Basic Multilingual Plane in the range from E000 to EFFF hexadecimal; the decoding of the original data value as the Boolean “AND” of the code point with the constant FFF hexadecimal; or b. the construction of a Unicode code point as the mathematical “addition” of a fixed constant in the range E000 to E900 hexadecimal with a 12-bit data value from 0 to FFF hexadecimal; said code points occupying the Unicode Basic Multilingual Plane in the range from E000 to F8FF hexadecimal; the decoding of the original data value as the mathematical “subtraction” of the same fixed constant from the code point. | 10. In a computer system, a computer readable storage medium containing one or more instructions for performing a method for character encoding and decoding: said method comprising translating a source data into a sequence of Unicode code points occupying the Private Use Area of the Unicode Basic Multilingual Plane, said method comprising; using one or more bits of the first code point or code points of each sequence as an identification tag, each tag identifying both the type of data encoded and the length of the data encoded; said encoding method comprising one of the following methods: a. the construction of a Unicode code point as the mathematical “OR” of the constant E000 hexadecimal with a 12-bit data value from 0 to FFF hexadecimal; said code points occupying the Unicode Basic Multilingual Plane in the range from E000 to EFFF hexadecimal; the decoding of the original data value as the Boolean “AND” of the code point with the constant FFF hexadecimal; or b. the construction of a Unicode code point as the mathematical “addition” of a fixed constant in the range E000 to E900 hexadecimal with a 12-bit data value from 0 to FFF hexadecimal; said code points occupying the Unicode Basic Multilingual Plane in the range from E000 to F8FF hexadecimal; the decoding of the original data value as the mathematical “subtraction” of the same fixed constant from the code point. 15. The method of claim 10 , wherein said tag identifies at least one of variable precision signed and unsigned integers, binary and decimal floating point numbers or arrays thereof. | 0.52975 |
1. A method comprising: monitoring by a social networking system one or more actions, each action performed by one or more users of the social networking system, each user having established a connection within the social networking system to at least one other user of the one or more users, the connection stored by the social networking system; receiving an entry from a first user of the one or more users, the received entry comprising a future status for the first user; storing the entry in a data store in association with an account of the first user; generating a plurality of stories, wherein the plurality of stories includes a first story and a second story, the first story being of a first story type comprising a description of a future status of a social networking system user, the first story comprising a description of the future status for the first user and one or more user interface elements for a viewing user to interact with the first story, and the second story being of a second story type, the second story comprising a description of one of the monitored actions comprising a previous status of a second social networking system user; selecting, by a computer system of the social networking system and without the first user's input, at least the first and second stories for display in a news feed of one or more other users of the plurality of users; and transmitting the selected stories for display to the news feed of the one or more other users. | 1. A method comprising: monitoring by a social networking system one or more actions, each action performed by one or more users of the social networking system, each user having established a connection within the social networking system to at least one other user of the one or more users, the connection stored by the social networking system; receiving an entry from a first user of the one or more users, the received entry comprising a future status for the first user; storing the entry in a data store in association with an account of the first user; generating a plurality of stories, wherein the plurality of stories includes a first story and a second story, the first story being of a first story type comprising a description of a future status of a social networking system user, the first story comprising a description of the future status for the first user and one or more user interface elements for a viewing user to interact with the first story, and the second story being of a second story type, the second story comprising a description of one of the monitored actions comprising a previous status of a second social networking system user; selecting, by a computer system of the social networking system and without the first user's input, at least the first and second stories for display in a news feed of one or more other users of the plurality of users; and transmitting the selected stories for display to the news feed of the one or more other users. 6. The method of claim 1 , wherein transmitting the selected for display in the news feed of one or more other users comprises: sending for display to a selected user a description of the future status of the first user. | 0.543504 |
8. One or more tangible computer readable storage media comprising instructions stored thereon that, responsive to execution by a computing system, causes the computing system to perform operations comprising: creating a snapshot of at least a portion of electronic content displayed in a user interface responsive to an indication to initiate an editing process; modifying the snapshot responsive to one or more edits; associating a comment, created in a previously non-existent field in response to creating or modifying the snapshot, with the modified snapshot for communication to one or more recipient devices, the comment providing context for the modified snapshot, the comment grouped together with the modified snapshot at a location in the user interface proximal to where the snapshot was modified; and displaying comments and further modifications made to the modified snapshot received from the one or more recipient devices in real time in the user interface. | 8. One or more tangible computer readable storage media comprising instructions stored thereon that, responsive to execution by a computing system, causes the computing system to perform operations comprising: creating a snapshot of at least a portion of electronic content displayed in a user interface responsive to an indication to initiate an editing process; modifying the snapshot responsive to one or more edits; associating a comment, created in a previously non-existent field in response to creating or modifying the snapshot, with the modified snapshot for communication to one or more recipient devices, the comment providing context for the modified snapshot, the comment grouped together with the modified snapshot at a location in the user interface proximal to where the snapshot was modified; and displaying comments and further modifications made to the modified snapshot received from the one or more recipient devices in real time in the user interface. 12. One or more tangible computer readable storage media as described in claim 8 , wherein the snapshot has a reduced size in comparison to a portion of the electronic content specified by an input that selects the portion. | 0.506604 |
12. A computer-implemented method for controlling a program by natural language commands, the method comprising: providing a list of natural language commands, each natural language command being associated with one or more commands of the program; generating a graphic user interface to receive inputs from a user, the graphic user interface comprising a filter field for entering characters and a list field for displaying natural language commands; receiving a plurality of n inputs from the user, entered in succession, wherein each of the number of n inputs corresponds to a character entered in the filter field; creating a subset of natural language commands comprising only those entries from the list of natural language commands having n or more words, wherein the respective first character of the first n words match the n inputs from the user; displaying the subset of natural language commands in the list field; enabling the user to select one of the natural language commands from the subset of natural language commands displayed in the list field; and causing the program to execute a command in response to the user's selection of a natural language command. | 12. A computer-implemented method for controlling a program by natural language commands, the method comprising: providing a list of natural language commands, each natural language command being associated with one or more commands of the program; generating a graphic user interface to receive inputs from a user, the graphic user interface comprising a filter field for entering characters and a list field for displaying natural language commands; receiving a plurality of n inputs from the user, entered in succession, wherein each of the number of n inputs corresponds to a character entered in the filter field; creating a subset of natural language commands comprising only those entries from the list of natural language commands having n or more words, wherein the respective first character of the first n words match the n inputs from the user; displaying the subset of natural language commands in the list field; enabling the user to select one of the natural language commands from the subset of natural language commands displayed in the list field; and causing the program to execute a command in response to the user's selection of a natural language command. 16. The method as in claim 12 , wherein natural language commands shown in the list field are associated with a numerical position, further comprising a step of receiving the numerical position of a natural language command shown in the list field and marking the natural language command that is associated with the received numerical position in response thereto. | 0.6908 |
1. A method for generating a translation rule to support natural language search, comprising: receiving a first expression and a second expression; generating a first representation based on the first expression; generating a second representation based on the second expression; determining aligned pairs of a first term in the first representation and a second term in the second representation; replacing, for each aligned pair, the first term in the first representation and the second term in the second representation with a variable associated the aligned pair; upon replacing the variables that correspond to the aligned pairs with the variable, removing word facts from the first representation and the second representation that occur in both the first representation and the second representation; upon removing the word facts that correspond to the replaced variables, replacing the remaining word facts in the first representation with a broader representation of the word facts; and upon replacing the remaining word facts in the first representation with the broader representation, generating the translation rule including the first representation, an operator, and the second semantic representation. | 1. A method for generating a translation rule to support natural language search, comprising: receiving a first expression and a second expression; generating a first representation based on the first expression; generating a second representation based on the second expression; determining aligned pairs of a first term in the first representation and a second term in the second representation; replacing, for each aligned pair, the first term in the first representation and the second term in the second representation with a variable associated the aligned pair; upon replacing the variables that correspond to the aligned pairs with the variable, removing word facts from the first representation and the second representation that occur in both the first representation and the second representation; upon removing the word facts that correspond to the replaced variables, replacing the remaining word facts in the first representation with a broader representation of the word facts; and upon replacing the remaining word facts in the first representation with the broader representation, generating the translation rule including the first representation, an operator, and the second semantic representation. 6. The method of claim 1 , wherein replacing the remaining word facts in the first representation with a broader representation of the word facts comprises replacing the remaining word facts in the first representation with a broader representation of the word facts that include at least one of synonyms, hyponyms, hypernyms, aliases, or valences. | 0.825848 |
10. A system comprising: a processor; and a computer-readable storage medium having instructions stored which, when executed by the processor, result in the processor performing operations comprising: for each dialect in a plurality of dialects identified within a speech utterance, selecting a corresponding dialect grammar, to yield a plurality of dialect grammars; blending the plurality of dialect grammars, to yield a blended dialect grammar; and recognizing speech utterances using the blended dialect grammar. | 10. A system comprising: a processor; and a computer-readable storage medium having instructions stored which, when executed by the processor, result in the processor performing operations comprising: for each dialect in a plurality of dialects identified within a speech utterance, selecting a corresponding dialect grammar, to yield a plurality of dialect grammars; blending the plurality of dialect grammars, to yield a blended dialect grammar; and recognizing speech utterances using the blended dialect grammar. 18. The system of claim 10 , wherein each dialect grammar of the plurality of dialect grammars is associated with parameters comprising one of vocabulary and sentence structure. | 0.570685 |
7. The system for managing churn of claim 1 wherein the end user access module is further executable by the processor to generate one or more reports configured to analyze churn based on customer data stored in the data mart. | 7. The system for managing churn of claim 1 wherein the end user access module is further executable by the processor to generate one or more reports configured to analyze churn based on customer data stored in the data mart. 11. The system of claim 7 wherein the end user access module is further executable by the processor to: calculate a churn rate; and generates a report that illustrates the churn rate versus a first behavioral cluster variable, and a second value cluster variable. | 0.927313 |
10. A system for automatically identifying portions of an image of a physical scene as depicting physical objects of predefined types in the physical scene, the system comprising: a digital camera capturing two-dimensional data from the physical scene, the two-dimensional data being in the form of the image of the physical scene; a lidar device capturing three-dimensional data from the physical scene; and a computing device comprising: one or more processing units; and computer-readable media comprising computer-executable instructions, which, when executed by the one or more processing units, cause the computing device to: generate correspondences between subsets of the two-dimensional data and subsets of the three-dimensional data; identify, based on a first subset of the two-dimensional data, a first portion of the image of the physical scene as depicting a physical object of a first predefined type; select a first subset of the three-dimensional data that corresponds to the first subset of the two-dimensional data based on the generated correspondences; and determine, based on the first subset of the three-dimensional data, that the identified first portion of the image does not actually depict a physical object of the first predefined type. | 10. A system for automatically identifying portions of an image of a physical scene as depicting physical objects of predefined types in the physical scene, the system comprising: a digital camera capturing two-dimensional data from the physical scene, the two-dimensional data being in the form of the image of the physical scene; a lidar device capturing three-dimensional data from the physical scene; and a computing device comprising: one or more processing units; and computer-readable media comprising computer-executable instructions, which, when executed by the one or more processing units, cause the computing device to: generate correspondences between subsets of the two-dimensional data and subsets of the three-dimensional data; identify, based on a first subset of the two-dimensional data, a first portion of the image of the physical scene as depicting a physical object of a first predefined type; select a first subset of the three-dimensional data that corresponds to the first subset of the two-dimensional data based on the generated correspondences; and determine, based on the first subset of the three-dimensional data, that the identified first portion of the image does not actually depict a physical object of the first predefined type. 12. The system of claim 10 , wherein the computer-executable instructions that cause the computing device to determine, based on the first subset of the three-dimensional data, that the identified first portion of the image does not actually depict a physical object of the first predefined type comprise computer-executable instructions, which, when executed by the one or more processing units, cause the computing device to: determine, based on the first subset of the three-dimensional data, that the identified first portion of the image depicts a physical object whose physical size, physical shape or physical location are inconsistent with physical objects of the first predefined type. | 0.632696 |
5. A method as claimed in claim 4 including the step of presenting questions which offer to the user an opportunity to change an answer which is inconsistent with a previous answer or to add data establishing a link with a consistent answer already given. | 5. A method as claimed in claim 4 including the step of presenting questions which offer to the user an opportunity to change an answer which is inconsistent with a previous answer or to add data establishing a link with a consistent answer already given. 6. A method of constructing a data model as claimed in claim 5 including the further step of comparing each identifying attribute entered by the user with all previously entered identifying attributes and if correspondence is discovered questioning the user in order to re-define the attribute until the attribute is rendered unique. | 0.818034 |
1. A voice messaging system for converting an audio message from a caller into text, the voice messaging system comprising: at least one automatic speech recognition (ASR) system to automatically recognize at least some of the audio message; a computer implemented preprocessing front-end to process the audio message from the caller and to detect if the audio message contains no voice content, wherein: if the preprocessing front-end detects that the audio message contains no voice content, the preprocessing front-end does not provide the audio message to the ASR component; and if the preprocessing front-end detects that the audio message contains voice content, the front-end provides the audio message to the ASR component, and wherein the computer implemented preprocessing front-end comprises a computer implemented speech quality detector to determine at least one measure of speech quality of the voice content of the audio message, and wherein the speech quality detector detects drop-outs, estimates noise levels and/or calculates an overall measure of voice quality using an adaptive threshold to reject lowest quality messages. | 1. A voice messaging system for converting an audio message from a caller into text, the voice messaging system comprising: at least one automatic speech recognition (ASR) system to automatically recognize at least some of the audio message; a computer implemented preprocessing front-end to process the audio message from the caller and to detect if the audio message contains no voice content, wherein: if the preprocessing front-end detects that the audio message contains no voice content, the preprocessing front-end does not provide the audio message to the ASR component; and if the preprocessing front-end detects that the audio message contains voice content, the front-end provides the audio message to the ASR component, and wherein the computer implemented preprocessing front-end comprises a computer implemented speech quality detector to determine at least one measure of speech quality of the voice content of the audio message, and wherein the speech quality detector detects drop-outs, estimates noise levels and/or calculates an overall measure of voice quality using an adaptive threshold to reject lowest quality messages. 6. The system of claim 1 , wherein the audio message corresponds to a voicemail intended for a user of a mobile telephone, and wherein the voice content is converted to text, at least in part by the ASR component, and sent to the mobile telephone. | 0.514752 |
17. A tangible computer-readable storage medium containing instructions which, when executed by a processor, cause the processor to perform a string matching method, the method comprising: storing a plurality of signature strings in a database; assigning values to characters in the signature strings; calculating differences between the assigned values of the characters in the signature strings; identifying common features of the signature strings using the calculated differences; grouping the signature strings into signature groups according to the common features; receiving an input string into a memory; detecting predetermined features of the input string; comparing the predetermined features of the input string with the common features of one or more of the signature groups; and comparing the input string with one or more individual signature strings in one of the signature groups if the predetermined features of the input string match the common features of the one of the signature groups. | 17. A tangible computer-readable storage medium containing instructions which, when executed by a processor, cause the processor to perform a string matching method, the method comprising: storing a plurality of signature strings in a database; assigning values to characters in the signature strings; calculating differences between the assigned values of the characters in the signature strings; identifying common features of the signature strings using the calculated differences; grouping the signature strings into signature groups according to the common features; receiving an input string into a memory; detecting predetermined features of the input string; comparing the predetermined features of the input string with the common features of one or more of the signature groups; and comparing the input string with one or more individual signature strings in one of the signature groups if the predetermined features of the input string match the common features of the one of the signature groups. 22. The tangible computer-readable storage medium of claim 17 , the method further comprising: selecting a sample space for the predetermined features of the input string and the common features of the signature strings. | 0.523423 |
16. Apparatus for recognizing a static handwritten word of cursive script, comprising; means for reading said word and forming a bit map of pixels representing said word; means for skeletonizing said word within said bit map; means for segmenting said skeletonized word into one or more primitives, said skeletonized word including a plurality of feature points and said primitives each comprising a continuous segment of said skeletonized word extending between an original feature point and a terminal feature point; means for forming a sequence representing the order in which said primitives were written by ordering said primitives in succession beginning at the left side of said word; and means for classifying said word by comparing said primitives and said sequence with each of a plurality of stored primitives and their associated sequences for known words, wherein said means for forming a sequence comprises: means for locating a primitive which is left-most in said word, examining said left-most primitive for the presence of one or more of said end points and designating said left-most primitive as a first primitive if it contains one or more of said end points; means for examining a primitive connected with said left-most primitive for the presence of an end point if said left-most primitive does not contain one or more of said end points, and for designating said connected primitive as said first primitive if it contains an end point and designating said left-most primitive as said first primitive if said connected primitive does not contain an end point; and means for ordinally designating as subsequent primitives each of said primitives which are connected with said first primitive and with said subsequent primitive. | 16. Apparatus for recognizing a static handwritten word of cursive script, comprising; means for reading said word and forming a bit map of pixels representing said word; means for skeletonizing said word within said bit map; means for segmenting said skeletonized word into one or more primitives, said skeletonized word including a plurality of feature points and said primitives each comprising a continuous segment of said skeletonized word extending between an original feature point and a terminal feature point; means for forming a sequence representing the order in which said primitives were written by ordering said primitives in succession beginning at the left side of said word; and means for classifying said word by comparing said primitives and said sequence with each of a plurality of stored primitives and their associated sequences for known words, wherein said means for forming a sequence comprises: means for locating a primitive which is left-most in said word, examining said left-most primitive for the presence of one or more of said end points and designating said left-most primitive as a first primitive if it contains one or more of said end points; means for examining a primitive connected with said left-most primitive for the presence of an end point if said left-most primitive does not contain one or more of said end points, and for designating said connected primitive as said first primitive if it contains an end point and designating said left-most primitive as said first primitive if said connected primitive does not contain an end point; and means for ordinally designating as subsequent primitives each of said primitives which are connected with said first primitive and with said subsequent primitive. 19. The apparatus according to claim 16 wherein said classifying comprises: means for determining the length and direction of each of said primitives; and means for comparing said length, direction and sequence of said primitives for said word with primitives of words stored in a memory device and for generating a list of words having a high probability of matching said word. | 0.545967 |
9. A computerized method of statistical machine translation, the method comprising: training a statistical machine translation engine on a bilingual parallel corpus including source language documents and a corresponding target human translation of the source language documents; training a phrasal decoder, separate and distinct from the statistical machine translation engine, on a monolingual parallel corpus, the monolingual parallel corpus including a machine translation output of the source language documents of the bilingual parallel corpus and the corresponding target human translation output of the source language documents of the bilingual parallel corpus, to thereby learn mappings and build a phrase table by establishing phrase pairs between the machine translation output and the target human translation output, wherein the machine translation output is unedited by human translators, assigning to each phrase pair a statistical score representing a utility of each phrase pair; performing statistical machine translation via the statistical machine translation engine trained on the bilingual parallel corpus of a translation input to thereby produce a raw machine translation output; and processing the raw machine translation output to thereby produce a corrected translation output based on the learned mappings and the phrase table, programmatically correcting the raw machine translation output if a statistical score for correspondence of the phrase pair is above a predetermined threshold. | 9. A computerized method of statistical machine translation, the method comprising: training a statistical machine translation engine on a bilingual parallel corpus including source language documents and a corresponding target human translation of the source language documents; training a phrasal decoder, separate and distinct from the statistical machine translation engine, on a monolingual parallel corpus, the monolingual parallel corpus including a machine translation output of the source language documents of the bilingual parallel corpus and the corresponding target human translation output of the source language documents of the bilingual parallel corpus, to thereby learn mappings and build a phrase table by establishing phrase pairs between the machine translation output and the target human translation output, wherein the machine translation output is unedited by human translators, assigning to each phrase pair a statistical score representing a utility of each phrase pair; performing statistical machine translation via the statistical machine translation engine trained on the bilingual parallel corpus of a translation input to thereby produce a raw machine translation output; and processing the raw machine translation output to thereby produce a corrected translation output based on the learned mappings and the phrase table, programmatically correcting the raw machine translation output if a statistical score for correspondence of the phrase pair is above a predetermined threshold. 16. The computerized method of claim 9 , wherein performing statistical machine translation of a translation input is accomplished at least in part by a syntax-based statistical machine translation engine; and wherein processing the raw machine translation output to thereby produce a corrected translation output is accomplished at least in part by a phrase-based statistical machine translation engine. | 0.636176 |
1. A method for variable data differential gloss font image comprising: selecting a font character; sub-sampling the selected font character into a sub-sample result; scaling the sub-sample result back up to a desired full size result; selecting a first halftone cell having a first anisotropic structure orientation; selecting a second halftone cell having a second anisotropic structure orientation; and in a digital front end, applying the first halftone cell to the desired full size result and applying the second halftone cell to a background field for the desired full size result to produce a variable data differential gloss font image. | 1. A method for variable data differential gloss font image comprising: selecting a font character; sub-sampling the selected font character into a sub-sample result; scaling the sub-sample result back up to a desired full size result; selecting a first halftone cell having a first anisotropic structure orientation; selecting a second halftone cell having a second anisotropic structure orientation; and in a digital front end, applying the first halftone cell to the desired full size result and applying the second halftone cell to a background field for the desired full size result to produce a variable data differential gloss font image. 14. The method of claim 1 wherein the variable data differential gloss font image indicates identification information. | 0.719638 |
1. A method for embedding symbols of a message into a document containing a set of glyphs, comprising: representing a glyph in a document as a distance field; representing a symbol in a message to be embedded in the document as a modification of a subset of values in the distance field; and modifying the subset of values in the distance field according to the modification to produce a modified glyph in a modified document, wherein the symbol in the message is embedded in the modified glyph, wherein steps of the method are performed by a processor. | 1. A method for embedding symbols of a message into a document containing a set of glyphs, comprising: representing a glyph in a document as a distance field; representing a symbol in a message to be embedded in the document as a modification of a subset of values in the distance field; and modifying the subset of values in the distance field according to the modification to produce a modified glyph in a modified document, wherein the symbol in the message is embedded in the modified glyph, wherein steps of the method are performed by a processor. 4. The method of claim 1 , wherein the distance field is a set of values stored in a data structure in a memory device. | 0.639634 |
2. The non-transitory machine-readable storage medium of claim 1 , wherein ranking the records that match the alphanumerical string comprises comparing the weights and the incremental values of the top hit database records corresponding to the records that match the alphanumerical string, wherein the weights and the incremental values are associated with the user and the user search query. | 2. The non-transitory machine-readable storage medium of claim 1 , wherein ranking the records that match the alphanumerical string comprises comparing the weights and the incremental values of the top hit database records corresponding to the records that match the alphanumerical string, wherein the weights and the incremental values are associated with the user and the user search query. 3. The non-transitory machine-readable storage medium of claim 2 , wherein the alphanumerical string comprises a word having a first letter and wherein an incremental value is assigned to a top hit database record for a first character that matches the first letter. | 0.832168 |
8. The system of claim 1 , wherein the AP is a patch AP (PAP) that is configured to extract items in the form of patches from the received MMDE. | 8. The system of claim 1 , wherein the AP is a patch AP (PAP) that is configured to extract items in the form of patches from the received MMDE. 9. The system of claim 8 , wherein the PAP is further configured to: determine which patches to provide for the signature generation based on at least one of: an entropy level of a patch, corners identified in a patch, and borders identified in a patch. | 0.910076 |
3. The computer system of claim 2 wherein the second subset of the state elements is designated by adding at least one selected register not in the combinational fan-in having a value which cannot be repeated in a state loop of the logic design between a start and an end of the loop. | 3. The computer system of claim 2 wherein the second subset of the state elements is designated by adding at least one selected register not in the combinational fan-in having a value which cannot be repeated in a state loop of the logic design between a start and an end of the loop. 4. The computer system of claim 3 wherein the second subset of the state elements includes all state elements in the initial subset. | 0.940495 |
1. A method of incorporating at least user-supplied text into an electronic product design having a first content area containing one or more content elements, the method comprising receiving a plurality of user text entries, the plurality of text entries comprising at least one text entry being of a first horizontal alignment type and at least one text entry being of a second horizontal alignment type, determining a first height, the first height being the height of all received text entries of the first horizontal alignment type positioned in a vertical arrangement, and a second height, the second height being the height of all received text entries of the second horizontal alignment type positioned in a vertical arrangement, modifying the electronic product design by sizing a second content area outside the first content area according to the larger of the first and second heights, positioning the plurality of user text entries in the product design in the second content area, and resizing the first content area to accommodate the second content area in the electronic product design, determining an available text width in the second content area, partitioning the available text width into a first maximum justified text width and a second maximum justified text width, and justifying the one or more user text entries of the first horizontal alignment type according to the first horizontal alignment type, wrapping such text entries as exceed the first maximum justified text width, and justifying the one or more user text entries of the second horizontal alignment type according to the second horizontal alignment type, wrapping such text entries as exceed the second maximum justified text width. | 1. A method of incorporating at least user-supplied text into an electronic product design having a first content area containing one or more content elements, the method comprising receiving a plurality of user text entries, the plurality of text entries comprising at least one text entry being of a first horizontal alignment type and at least one text entry being of a second horizontal alignment type, determining a first height, the first height being the height of all received text entries of the first horizontal alignment type positioned in a vertical arrangement, and a second height, the second height being the height of all received text entries of the second horizontal alignment type positioned in a vertical arrangement, modifying the electronic product design by sizing a second content area outside the first content area according to the larger of the first and second heights, positioning the plurality of user text entries in the product design in the second content area, and resizing the first content area to accommodate the second content area in the electronic product design, determining an available text width in the second content area, partitioning the available text width into a first maximum justified text width and a second maximum justified text width, and justifying the one or more user text entries of the first horizontal alignment type according to the first horizontal alignment type, wrapping such text entries as exceed the first maximum justified text width, and justifying the one or more user text entries of the second horizontal alignment type according to the second horizontal alignment type, wrapping such text entries as exceed the second maximum justified text width. 2. The method of claim 1 wherein the first horizontal alignment type is text to be positioned in a first position relative to the second content area and the second horizontal alignment type is text to be positioned in a second position relative to the second content area. | 0.633815 |
1. A method of developing a software product, comprising: receiving, on a computer system including at least one computing device, a request to evaluate a set of plug-ins and fragments corresponding to the software product as part of a quality engineering investigation of the software product; and evaluating the set of plug-ins and fragments in response to the request using the computer system, the evaluating including: obtaining, on the computer system, information pertaining to the set of plug-ins and fragments from a manifest corresponding to each plug-in and fragment in the set of plug-ins and fragments available from a set of sites registered with a particular instance of the software product, wherein each site in the set of sites includes at least one plug-in in the set of plug-ins and fragments, wherein each fragment in the set of plug-ins and fragments internationalizes a corresponding plug-in in the set of plug-ins and fragments, and wherein the information includes version information and dependency information for each plug-in and fragment in the set of plug-ins and fragments; analyzing the information and performing a set of tests using the computer system to determine whether the set of plug-ins and fragments have any one of a set of issues, wherein the set of issues includes: an error relating to the manifest, an error relating to the version information, and an error relating to the dependency information; and providing, using the computer system and for each issue determined to be present, details regarding the issue, a cause of the issue, and details corresponding to resolution of the issue for use during the quality engineering investigation. | 1. A method of developing a software product, comprising: receiving, on a computer system including at least one computing device, a request to evaluate a set of plug-ins and fragments corresponding to the software product as part of a quality engineering investigation of the software product; and evaluating the set of plug-ins and fragments in response to the request using the computer system, the evaluating including: obtaining, on the computer system, information pertaining to the set of plug-ins and fragments from a manifest corresponding to each plug-in and fragment in the set of plug-ins and fragments available from a set of sites registered with a particular instance of the software product, wherein each site in the set of sites includes at least one plug-in in the set of plug-ins and fragments, wherein each fragment in the set of plug-ins and fragments internationalizes a corresponding plug-in in the set of plug-ins and fragments, and wherein the information includes version information and dependency information for each plug-in and fragment in the set of plug-ins and fragments; analyzing the information and performing a set of tests using the computer system to determine whether the set of plug-ins and fragments have any one of a set of issues, wherein the set of issues includes: an error relating to the manifest, an error relating to the version information, and an error relating to the dependency information; and providing, using the computer system and for each issue determined to be present, details regarding the issue, a cause of the issue, and details corresponding to resolution of the issue for use during the quality engineering investigation. 2. The method of claim 1 , the evaluating further comprising identifying a complete set of plug-ins and fragments expected to compose the software product, wherein the obtaining and analyzing are performed for each plug-in and fragment in the complete set of plug-ins and fragments. | 0.666028 |
15. A method for creating customized definitions for user interfaces provided by a field device editor, the method comprising the steps of: maintaining in a device definition database a default device template, wherein the default device template includes a first definition of an editor interface; retrieving device description information corresponding to a selected device type from the device definition database; modifying on demand the first definition of the editor interface based on the retrieved information corresponding to the selected device type via a customization tool associated with the editor interface, thereby rendering a modified version of the first definition of the editor interface, wherein the customization tool is invoked via a control exposed by the editor interface corresponding to the selected device type; and storing the modified version. | 15. A method for creating customized definitions for user interfaces provided by a field device editor, the method comprising the steps of: maintaining in a device definition database a default device template, wherein the default device template includes a first definition of an editor interface; retrieving device description information corresponding to a selected device type from the device definition database; modifying on demand the first definition of the editor interface based on the retrieved information corresponding to the selected device type via a customization tool associated with the editor interface, thereby rendering a modified version of the first definition of the editor interface, wherein the customization tool is invoked via a control exposed by the editor interface corresponding to the selected device type; and storing the modified version. 20. The method of claim 15 wherein the modifying step comprises customizing permissions associated with particular user classes. | 0.639262 |
1. A method comprising: accessing a social graph comprising a plurality of nodes and a plurality of edges connecting the nodes, each of the edges between two of the nodes representing a single degree of separation between them, the nodes comprising: a first node corresponding to a first user associated with an online social network; and a plurality of second nodes that each correspond to a concept or a second user associated with the online social network; receiving from the first user a structured query comprising references to one or more selected nodes from the plurality of nodes and one or more selected edges from the plurality of edges; generating a query command based on the structured query, wherein the query command comprises an inner query constraint and an outer query constraint; identifying a first set of nodes matching the inner query constraint and at least in part matching the outer query constraint; identifying a second set of nodes matching the outer query constraint; and generating one or more search results based on the first and second sets of nodes, wherein each search result corresponds to a node of the plurality of nodes. | 1. A method comprising: accessing a social graph comprising a plurality of nodes and a plurality of edges connecting the nodes, each of the edges between two of the nodes representing a single degree of separation between them, the nodes comprising: a first node corresponding to a first user associated with an online social network; and a plurality of second nodes that each correspond to a concept or a second user associated with the online social network; receiving from the first user a structured query comprising references to one or more selected nodes from the plurality of nodes and one or more selected edges from the plurality of edges; generating a query command based on the structured query, wherein the query command comprises an inner query constraint and an outer query constraint; identifying a first set of nodes matching the inner query constraint and at least in part matching the outer query constraint; identifying a second set of nodes matching the outer query constraint; and generating one or more search results based on the first and second sets of nodes, wherein each search result corresponds to a node of the plurality of nodes. 9. The method of claim 1 , further comprising scoring the search results. | 0.612422 |
1. A speech recognition method executed by processing circuitry programmed to implement speech recognition, said method comprising: receiving a speech input from a speaker which comprises a sequence of observations; and determining, using the processing circuitry, a likelihood of a sequence of words arising from the sequence of observations using an acoustic model, said acoustic model having a plurality of model parameters describing probability distributions which relate a word or part thereof to an observation, said acoustic model having been trained using first training data and adapted using second training data to said speaker, determining, using the processing circuitry, a likelihood of a sequence of observations occurring in a given language using a language model; and combining, using the processing circuitry, the likelihoods determined by the acoustic model and the language model and outputting a sequence of words identified from said speech input signal, wherein said acoustic model is context based for said speaker, said context based information being contained in said model using a plurality of decision trees, the structure of said decision trees being based on second training data, the decision trees splitting at nodes and wherein the structure is determined from the splitting of the nodes of the trees that has been calculated using maximum a posteriori criteria implemented as: ( m ^ MAP , λ ^ MAP ) = arg max m , λ { log p ( O ❘ m , λ ) + α · log p ( O ′ ❘ m , λ ) } where O′ is the first training data, O is the second training data, m denotes a parameter tying structure, λ is a set of HMM parameters, {circumflex over (m)} MAP denotes the parameter tying structure under maximum a posteriori criteria, {circumflex over (λ)} MAP are the HMM parameters under maximum a posteriori criteria and α is a parameter to be set. | 1. A speech recognition method executed by processing circuitry programmed to implement speech recognition, said method comprising: receiving a speech input from a speaker which comprises a sequence of observations; and determining, using the processing circuitry, a likelihood of a sequence of words arising from the sequence of observations using an acoustic model, said acoustic model having a plurality of model parameters describing probability distributions which relate a word or part thereof to an observation, said acoustic model having been trained using first training data and adapted using second training data to said speaker, determining, using the processing circuitry, a likelihood of a sequence of observations occurring in a given language using a language model; and combining, using the processing circuitry, the likelihoods determined by the acoustic model and the language model and outputting a sequence of words identified from said speech input signal, wherein said acoustic model is context based for said speaker, said context based information being contained in said model using a plurality of decision trees, the structure of said decision trees being based on second training data, the decision trees splitting at nodes and wherein the structure is determined from the splitting of the nodes of the trees that has been calculated using maximum a posteriori criteria implemented as: ( m ^ MAP , λ ^ MAP ) = arg max m , λ { log p ( O ❘ m , λ ) + α · log p ( O ′ ❘ m , λ ) } where O′ is the first training data, O is the second training data, m denotes a parameter tying structure, λ is a set of HMM parameters, {circumflex over (m)} MAP denotes the parameter tying structure under maximum a posteriori criteria, {circumflex over (λ)} MAP are the HMM parameters under maximum a posteriori criteria and α is a parameter to be set. 4. The method according to claim 1 , wherein said acoustic model comprises probability distributions which are represented by means and variances and wherein said decision trees are provided for both means and variances. | 0.5 |
1. A method for indicating emotional attitudes of a speaker according to voice tone, said method comprising: a. obtaining a database comprising reference tones and reference emotional attitudes corresponding to each of said reference tones; b. pronouncing at least one word by a speaker for the duration of a sample period; c. recording said at least one word so as to obtain a signal representing sound volume as a function of frequency for said sample period; d. processing said signal so as to obtain voice characteristics of said speaker, wherein said processing includes determining a Function A, said Function A being defined as the average or maximum sound volume as a function of sound frequency, from within a range of frequencies measured in said sampled period, and wherein said processing further includes determining a Function B, said Function B defined as the averaging, or maximizing of said function A over said range of frequencies and dyadic multiples thereof; e. comparing said voice characteristics to said reference tones so as to indicate at least one of said reference emotional attitudes. | 1. A method for indicating emotional attitudes of a speaker according to voice tone, said method comprising: a. obtaining a database comprising reference tones and reference emotional attitudes corresponding to each of said reference tones; b. pronouncing at least one word by a speaker for the duration of a sample period; c. recording said at least one word so as to obtain a signal representing sound volume as a function of frequency for said sample period; d. processing said signal so as to obtain voice characteristics of said speaker, wherein said processing includes determining a Function A, said Function A being defined as the average or maximum sound volume as a function of sound frequency, from within a range of frequencies measured in said sampled period, and wherein said processing further includes determining a Function B, said Function B defined as the averaging, or maximizing of said function A over said range of frequencies and dyadic multiples thereof; e. comparing said voice characteristics to said reference tones so as to indicate at least one of said reference emotional attitudes. 5. A method according to claim 1 , wherein said step of comparing further comprises calculating the variation between said voice characteristics and tone characteristics related to said reference tones. | 0.767576 |
9. A system for determining whether to independently evaluate the trustworthiness of digitally signed files based on signer reputation, the system comprising: a file-analysis module programmed to: identify a file; determine that the file has been digitally signed; identify a signer responsible for digitally signing the file; a reputation module programmed to identify a reputation of the signer, the signer's reputation being based at least in part on the determined trustworthiness of at least one additional file that was previously signed by the signer; a security module programmed to: determine whether the signer's reputation satisfies a predetermined threshold; only perform an independent evaluation of the trustworthiness of the file if the signer's reputation fails to satisfy the predetermined threshold; at least one processor configured to execute the file-analysis module, the reputation module, and the security module. | 9. A system for determining whether to independently evaluate the trustworthiness of digitally signed files based on signer reputation, the system comprising: a file-analysis module programmed to: identify a file; determine that the file has been digitally signed; identify a signer responsible for digitally signing the file; a reputation module programmed to identify a reputation of the signer, the signer's reputation being based at least in part on the determined trustworthiness of at least one additional file that was previously signed by the signer; a security module programmed to: determine whether the signer's reputation satisfies a predetermined threshold; only perform an independent evaluation of the trustworthiness of the file if the signer's reputation fails to satisfy the predetermined threshold; at least one processor configured to execute the file-analysis module, the reputation module, and the security module. 14. The system of claim 9 , further comprising at least one of: a server-side computing device comprising at least one processor configured to execute at least one of the file-analysis module, the reputation module, and the security module; a client-side computing device comprising at least one processor configured to execute at least one of the file-analysis module, the reputation module, and the security module. | 0.583803 |
10. A computer tool, stored in a non-transitory medium, for a user to access an original plain text file which has been protected by being encrypted in a protected file, the computer tool being adapted to decrypt the protected file once authorized by a user license issued by an authority responsible for the protected file to produce an image of the original plain text file whilst protecting the image of the original plain text file from being copied to any file, other than a further protected file, wherein the image of the original plain text file cannot be found by other programs on the computer, and an editor program that (i) edits the image of the original plain text file to create an edited image of the original plaint text file and then (ii) saves changes made to the image of the original plain text file in an encrypted form, separate from the original plain text file, wherein the computer tool creates the edited image of the original plain text file from the protected file and a difference file using the editor program and user license, wherein, before allowing to produce the image of the original plain text file or to edit the image of the original plain text file, the computer tool checks its own validity by checking a digital signature to ensure the computer tool has not been modified, and wherein parts of the original plain text file are marked as non-editable, and the editor program prevents such parts being edited so that they will always be present in any image created from the original plain text file and any difference file or files. | 10. A computer tool, stored in a non-transitory medium, for a user to access an original plain text file which has been protected by being encrypted in a protected file, the computer tool being adapted to decrypt the protected file once authorized by a user license issued by an authority responsible for the protected file to produce an image of the original plain text file whilst protecting the image of the original plain text file from being copied to any file, other than a further protected file, wherein the image of the original plain text file cannot be found by other programs on the computer, and an editor program that (i) edits the image of the original plain text file to create an edited image of the original plaint text file and then (ii) saves changes made to the image of the original plain text file in an encrypted form, separate from the original plain text file, wherein the computer tool creates the edited image of the original plain text file from the protected file and a difference file using the editor program and user license, wherein, before allowing to produce the image of the original plain text file or to edit the image of the original plain text file, the computer tool checks its own validity by checking a digital signature to ensure the computer tool has not been modified, and wherein parts of the original plain text file are marked as non-editable, and the editor program prevents such parts being edited so that they will always be present in any image created from the original plain text file and any difference file or files. 16. The computer tool as claimed in claim 10 in which a user program comprises an obfuscator that generates from the image of the original plain text file an obfuscated output file which is intelligible to a specific software tool only. | 0.537427 |
13. A process for determining a user-specified scenario in order to add value to information, comprising: searching via a server, a collection of documents to find a document in the collection of documents relevant to a scenario, wherein the documents comprise chat dialogs, emails, blogs, and internet sites; processing the relevant documents to a scenario using one or more processors at the server to extract entities and relationships between the extracted entities, wherein the extracted entities comprise relevant nouns, magnitudes, numbers, or concepts contained within the text of the documents; setting influence values for a plurality of the extracted entities to indicate the amount of influence each of the plurality of the extracted entities has on another extracted entity to which an extracted relationship exists; associating a set of options with the plurality of the extracted entities; and populating a risk model comprising a plurality of nodes derived from the extracted entities, wherein at least one of the plurality of nodes is associated with an option from the set of options, the option including an associated value, the associated value usable for calculating an option value associated with a higher level node in the risk model; and rendering, for display at a user interface of one or more host computers in communication with the server, one or more of the plurality of extracted entities on a chart having two axes, a first axis indicating an amount of influence exerted on the extracted entities located on the chart as represented by the influence values, and the second axis indicating an amount of influence that the extracted entities located on the chart exert on other extracted entities, the amounts of influence being derived from the influence values. | 13. A process for determining a user-specified scenario in order to add value to information, comprising: searching via a server, a collection of documents to find a document in the collection of documents relevant to a scenario, wherein the documents comprise chat dialogs, emails, blogs, and internet sites; processing the relevant documents to a scenario using one or more processors at the server to extract entities and relationships between the extracted entities, wherein the extracted entities comprise relevant nouns, magnitudes, numbers, or concepts contained within the text of the documents; setting influence values for a plurality of the extracted entities to indicate the amount of influence each of the plurality of the extracted entities has on another extracted entity to which an extracted relationship exists; associating a set of options with the plurality of the extracted entities; and populating a risk model comprising a plurality of nodes derived from the extracted entities, wherein at least one of the plurality of nodes is associated with an option from the set of options, the option including an associated value, the associated value usable for calculating an option value associated with a higher level node in the risk model; and rendering, for display at a user interface of one or more host computers in communication with the server, one or more of the plurality of extracted entities on a chart having two axes, a first axis indicating an amount of influence exerted on the extracted entities located on the chart as represented by the influence values, and the second axis indicating an amount of influence that the extracted entities located on the chart exert on other extracted entities, the amounts of influence being derived from the influence values. 20. The process of claim 13 , wherein the influence values are set manually by a user. | 0.703623 |
1. A method for reducing response latency of intelligent automated assistants, the method comprising: at an electronic device: receiving, from a user, a speech input containing a user request; transmitting, to a server, a representation of the speech input; receiving, from the server, a domain signal defining a relevant domain of an actionable intent inferred from the user request; determining whether the relevant domain is associated with a predefined action of a set of predefined actions supported by the electronic device; in response to determining that the relevant domain is associated with a predefined action on the electronic device, performing the predefined action; after at least partially performing the predefined action, receiving, from the server, data content relevant to satisfying the user request, wherein the data content is generated according to an executed task flow corresponding to the actionable intent, and wherein performing the predefined action at least partially prepares the electronic device to process the received data content; and outputting a result based on the data content to at least partially satisfy the user request. | 1. A method for reducing response latency of intelligent automated assistants, the method comprising: at an electronic device: receiving, from a user, a speech input containing a user request; transmitting, to a server, a representation of the speech input; receiving, from the server, a domain signal defining a relevant domain of an actionable intent inferred from the user request; determining whether the relevant domain is associated with a predefined action of a set of predefined actions supported by the electronic device; in response to determining that the relevant domain is associated with a predefined action on the electronic device, performing the predefined action; after at least partially performing the predefined action, receiving, from the server, data content relevant to satisfying the user request, wherein the data content is generated according to an executed task flow corresponding to the actionable intent, and wherein performing the predefined action at least partially prepares the electronic device to process the received data content; and outputting a result based on the data content to at least partially satisfy the user request. 2. The method of claim 1 , further comprising processing the data content to obtain the result, wherein performing the predefined action is prerequisite to processing the data content. | 0.670283 |
6. A device comprising: content-addressable memory cells arranged in rows, two of the rows are timing reference rows and the remainder of the rows are data rows maintaining words of data, the data rows comprise individual matchlines, a first reference row of the reference rows comprises a precharge reference matchline, and a second reference row of the reference rows comprises an evaluation reference matchline; first-type of sense amplifiers connected to the individual matchlines and the evaluation reference matchline; and a second-type of sense amplifier, different from the first-type of sense amplifiers, connected to the precharge reference matchline, the precharge reference matchline is hardwired to match all bits and timing for the individual matchlines to precharge is based on a time to precharge the precharge reference matchline, and the evaluation reference matchline is hardwired to a one-bit-miss word that has only one bit not producing a match and timing for the individual matchlines to evaluate a search word is based on a time for the evaluation reference matchline to evaluate the search word. | 6. A device comprising: content-addressable memory cells arranged in rows, two of the rows are timing reference rows and the remainder of the rows are data rows maintaining words of data, the data rows comprise individual matchlines, a first reference row of the reference rows comprises a precharge reference matchline, and a second reference row of the reference rows comprises an evaluation reference matchline; first-type of sense amplifiers connected to the individual matchlines and the evaluation reference matchline; and a second-type of sense amplifier, different from the first-type of sense amplifiers, connected to the precharge reference matchline, the precharge reference matchline is hardwired to match all bits and timing for the individual matchlines to precharge is based on a time to precharge the precharge reference matchline, and the evaluation reference matchline is hardwired to a one-bit-miss word that has only one bit not producing a match and timing for the individual matchlines to evaluate a search word is based on a time for the evaluation reference matchline to evaluate the search word. 7. The device according to claim 6 , a location within the content-addressable memory cells is output in response to the search word being matched to the words of data during evaluation of the individual matchlines. | 0.715244 |
3. The method of claim 1 wherein identifying one or more items of video content responsive to the received query comprises identifying one or more items of video content associated with one or more items of metadata that match or are similar to the one or more terms comprising the query. | 3. The method of claim 1 wherein identifying one or more items of video content responsive to the received query comprises identifying one or more items of video content associated with one or more items of metadata that match or are similar to the one or more terms comprising the query. 5. The method of claim 3 wherein a given item of metadata comprises data identifying a given item of video content. | 0.916461 |
1. A method of generating test cases comprising: receiving, by a processor, a test application in an executable format, the test application including a plurality of forms; simulating the execution of the test application with the processor; iterating through each one of the plurality of forms of the test application; detecting a field in at least one form of the plurality of forms; inspecting a field included in the at least one form for metadata in the test application; generating, based on the metadata, at least one test case corresponding to the field; storing the test case in a first format; and storing the test case in a second format that is different from the first format. | 1. A method of generating test cases comprising: receiving, by a processor, a test application in an executable format, the test application including a plurality of forms; simulating the execution of the test application with the processor; iterating through each one of the plurality of forms of the test application; detecting a field in at least one form of the plurality of forms; inspecting a field included in the at least one form for metadata in the test application; generating, based on the metadata, at least one test case corresponding to the field; storing the test case in a first format; and storing the test case in a second format that is different from the first format. 7. The method of claim 1 , further comprising: receiving a navigation input from a user selection of a form from the plurality of forms; wherein the iterating through each one of the plurality of forms is based at least in part on the navigation input from the user. | 0.603098 |
1. A method for constructing a template image for recognition, comprising the steps of: obtaining a plurality of digitized images that belong to n categories, each image including location and gray level information of pixels of the image and category information of the image; for all categories, abstracting common features Ai for images belonging to a category Di (0<i≦n); comparing common features Ai of said category Di with common features Aj of a predetermined number m of categories other than category Di (0<j≦m≦n−1), to obtain discriminating features Σ(Aj T Ai) for category Di; and including features Σ(Aj T Ai) into said common features Ai to obtain template image Ai* for category Di, wherein the template image Ai* is obtained from the following formula in one single step: min A i , E i A i * + λ E i 1 + η ∑ j ≠ i A j T A i F 2 s . t . D i = A i + E i , wherein η and λ are constants. | 1. A method for constructing a template image for recognition, comprising the steps of: obtaining a plurality of digitized images that belong to n categories, each image including location and gray level information of pixels of the image and category information of the image; for all categories, abstracting common features Ai for images belonging to a category Di (0<i≦n); comparing common features Ai of said category Di with common features Aj of a predetermined number m of categories other than category Di (0<j≦m≦n−1), to obtain discriminating features Σ(Aj T Ai) for category Di; and including features Σ(Aj T Ai) into said common features Ai to obtain template image Ai* for category Di, wherein the template image Ai* is obtained from the following formula in one single step: min A i , E i A i * + λ E i 1 + η ∑ j ≠ i A j T A i F 2 s . t . D i = A i + E i , wherein η and λ are constants. 2. The method according to claim 1 , wherein m is n−1. | 0.54 |
1. A method for generating a distributed stream processing application, comprising the steps of: obtaining a declarative description of one or more data stream processing tasks from a graph of operators, wherein the declarative description expresses at least one stream processing task; generating one or more execution units from the declarative description of one or more data stream processing tasks, wherein the one or more execution units are deployable across one or more distributed computing nodes, and comprise a distributed data stream processing application binary; generating one or more coarse granularity containers that encompass one or more fine granularity stream processing operators; using the one or more coarse granularity containers to generate a distributed stream processing application; generating one or more containers that encompass a combination of one or more stream processing operators, wherein said generating comprises: coalescing a combination of one or more operators into one or more containers, wherein said coalescing comprises: using an optimizer to automatically decide which of the one or more operators are to be coalesced into which of the one or more containers; and using user input to manually group the one or more operators into the one or more containers; and fusing an outflow of an operator into an inflow of a downstream operator within a same container. | 1. A method for generating a distributed stream processing application, comprising the steps of: obtaining a declarative description of one or more data stream processing tasks from a graph of operators, wherein the declarative description expresses at least one stream processing task; generating one or more execution units from the declarative description of one or more data stream processing tasks, wherein the one or more execution units are deployable across one or more distributed computing nodes, and comprise a distributed data stream processing application binary; generating one or more coarse granularity containers that encompass one or more fine granularity stream processing operators; using the one or more coarse granularity containers to generate a distributed stream processing application; generating one or more containers that encompass a combination of one or more stream processing operators, wherein said generating comprises: coalescing a combination of one or more operators into one or more containers, wherein said coalescing comprises: using an optimizer to automatically decide which of the one or more operators are to be coalesced into which of the one or more containers; and using user input to manually group the one or more operators into the one or more containers; and fusing an outflow of an operator into an inflow of a downstream operator within a same container. 3. The method of claim 1 , further comprising using a stream-centric and operator based paradigm for declaring one or more stream processing applications. | 0.875 |
7. A system for recognizing a gesture, the system comprising: one or more processors configured to: determine a first set of metrics to differentiate gestures from among only a first subset of gestures of a plurality of gestures, the first subset of gestures recognizable as valid input in a particular context of a user interface environment of the system; receive user input that causes a gesture classification context to be applied from a plurality of gesture classification contexts available for a gesture analysis engine, wherein the gesture classification context indicates the first subset of gestures; apply the gesture classification context to the gesture analysis engine; after applying the gesture classification context, receive data indicative of the gesture performed by a user; and identify, based on the first set of metrics, using the gesture analysis engine, the gesture in accordance with the applied gesture classification context, wherein identifying includes identifying the gesture from only the first subset of gestures of the plurality of gestures indicated by the applied gesture classification context while the gesture classification context is applied; determine a second subset of gestures from the plurality of gestures, wherein each gesture of the second subset of gestures is valid in a second gesture classification context; calculate a second set of metrics for the second subset of gestures to differentiate gestures from among only the second subset of gestures, wherein: only the second subset of gestures are eligible to be identified when the second gesture classification context is applied, and at least one gesture of the second subset of gestures is not in the first subset of gestures; receive user input that causes the second gesture classification context to be applied to the gesture analysis engine; after applying the second gesture classification context, receive data indicative of a second gesture performed by the user; and identify, based on the second set of metrics, the second gesture in accordance with the applied second gesture classification context, wherein identifying includes identifying the second gesture from only the second subset of gestures indicated by the applied second gesture classification context. | 7. A system for recognizing a gesture, the system comprising: one or more processors configured to: determine a first set of metrics to differentiate gestures from among only a first subset of gestures of a plurality of gestures, the first subset of gestures recognizable as valid input in a particular context of a user interface environment of the system; receive user input that causes a gesture classification context to be applied from a plurality of gesture classification contexts available for a gesture analysis engine, wherein the gesture classification context indicates the first subset of gestures; apply the gesture classification context to the gesture analysis engine; after applying the gesture classification context, receive data indicative of the gesture performed by a user; and identify, based on the first set of metrics, using the gesture analysis engine, the gesture in accordance with the applied gesture classification context, wherein identifying includes identifying the gesture from only the first subset of gestures of the plurality of gestures indicated by the applied gesture classification context while the gesture classification context is applied; determine a second subset of gestures from the plurality of gestures, wherein each gesture of the second subset of gestures is valid in a second gesture classification context; calculate a second set of metrics for the second subset of gestures to differentiate gestures from among only the second subset of gestures, wherein: only the second subset of gestures are eligible to be identified when the second gesture classification context is applied, and at least one gesture of the second subset of gestures is not in the first subset of gestures; receive user input that causes the second gesture classification context to be applied to the gesture analysis engine; after applying the second gesture classification context, receive data indicative of a second gesture performed by the user; and identify, based on the second set of metrics, the second gesture in accordance with the applied second gesture classification context, wherein identifying includes identifying the second gesture from only the second subset of gestures indicated by the applied second gesture classification context. 12. The system for recognizing the gesture of claim 7 , wherein: determining the second subset of gestures from the plurality of gestures and determining the second set of metrics for the second subset of gestures to differentiate gestures from among only the second subset of gestures occur during creation of a gesture subset database, wherein the gesture subset database comprises gesture classification contexts for multiple subsets of the plurality of gestures. | 0.537504 |
20. The computer-implemented system according to claim 17 , wherein the DEPRECATED release status code indicates that the application platform supports the associated business object entity in a current release of the application platform and will not support the associated business object entity in a next software release of the application platform. | 20. The computer-implemented system according to claim 17 , wherein the DEPRECATED release status code indicates that the application platform supports the associated business object entity in a current release of the application platform and will not support the associated business object entity in a next software release of the application platform. 22. The computer-implemented system according to claim 20 , wherein the DELETED release status code that is associated with the second plurality of the business object entities by the second metadata that is associated with the second release of the application platform indicates that each of the second plurality of the business object entities is not visible in the second release of the application platform. | 0.8947 |
1. A method for editing text, comprising: in response to an instruction to apply editing to at least one sentence within a document that is displayed on a display screen changing a first word or phrase in the at least one sentence for a second word or phrase while maintaining semantic content of the first word or phrase and such that the at least one sentence falls within a predetermined range, wherein the changing the first word or phrase comprises one of: in response to the second word or phrase having more characters or words than the first word or phrase, changing a third word or phrase within the at least one sentence including the second word or phrase for a fourth word or phrase, such that the at least one sentence including the second word or phrase falls within the predetermined range; and in response the second word or phrase having fewer characters or words than the first word or phrase, changing a fifth word or phrase within the at least one sentence including the second word or phrase for a sixth word or phrase, such that the at least one sentence including the second word or phrase falls within the predetermined range; and displaying the at least one sentence including the second word or phrase, and one of the fourth word or phrase and the sixth word or phrase, on the display screen. | 1. A method for editing text, comprising: in response to an instruction to apply editing to at least one sentence within a document that is displayed on a display screen changing a first word or phrase in the at least one sentence for a second word or phrase while maintaining semantic content of the first word or phrase and such that the at least one sentence falls within a predetermined range, wherein the changing the first word or phrase comprises one of: in response to the second word or phrase having more characters or words than the first word or phrase, changing a third word or phrase within the at least one sentence including the second word or phrase for a fourth word or phrase, such that the at least one sentence including the second word or phrase falls within the predetermined range; and in response the second word or phrase having fewer characters or words than the first word or phrase, changing a fifth word or phrase within the at least one sentence including the second word or phrase for a sixth word or phrase, such that the at least one sentence including the second word or phrase falls within the predetermined range; and displaying the at least one sentence including the second word or phrase, and one of the fourth word or phrase and the sixth word or phrase, on the display screen. 2. The method according to claim 1 , wherein displaying the at least one sentence including the second word or phrase on the display screen comprises displaying at least one of the second word or phrase, the fourth word or phrase, and the sixth word or phrase to a user; the method further comprising: in response to at least one of the second word or phrase, the fourth word or phrase and the sixth word or phrase being selected by the user, displaying on the display screen a conversion list indicating at least one conversion candidate that maintains the semantic content of the selected word or phrase; and in response to a conversion candidate on the conversion list being selected by the user, replacing the selected word or phrase with the conversion candidate selected by the user. | 0.675603 |
16. The system of claim 13 , further comprising a display module to display a user interface, wherein the display module is further to visually present the ranking of the prior art document in the user interface. | 16. The system of claim 13 , further comprising a display module to display a user interface, wherein the display module is further to visually present the ranking of the prior art document in the user interface. 18. The system of claim 16 , wherein the display module is further to provide a visual indication of the degree of differentiation of the prior document in association with the time line. | 0.904263 |
1. A system for calculating the look ahead probabilities at the nodes in a language model look ahead tree, wherein the words of the vocabulary of the language are located at the leaves of the tree, said system comprising a processor adapted to: to obtain a first low order language model look ahead tree having a language first low order language model probability assigned to the words of the vocabulary and the language model look ahead probabilities calculated for nodes in said first low order language model look ahead tree; to determine if the language model probability of one or more words of said vocabulary can be calculated using a higher order language model and updating said words with the higher order language model; and to update the look ahead probability at the nodes of the first low order language model look ahead tree which are affected by the words where the language model has been updated, wherein the first low order language model look ahead tree is one order lower than the higher order language model. | 1. A system for calculating the look ahead probabilities at the nodes in a language model look ahead tree, wherein the words of the vocabulary of the language are located at the leaves of the tree, said system comprising a processor adapted to: to obtain a first low order language model look ahead tree having a language first low order language model probability assigned to the words of the vocabulary and the language model look ahead probabilities calculated for nodes in said first low order language model look ahead tree; to determine if the language model probability of one or more words of said vocabulary can be calculated using a higher order language model and updating said words with the higher order language model; and to update the look ahead probability at the nodes of the first low order language model look ahead tree which are affected by the words where the language model has been updated, wherein the first low order language model look ahead tree is one order lower than the higher order language model. 4. A system according to claim 1 , wherein the higher order model is a bigram, trigram, fourgram or higher order n-gram model. | 0.590151 |
14. The method as set forth in claim 1 , wherein said at least one policy is applied for the purpose of measuring network latency using network metadata on said network. | 14. The method as set forth in claim 1 , wherein said at least one policy is applied for the purpose of measuring network latency using network metadata on said network. 15. The method as set forth in claim 14 , wherein said at least one policy includes the steps of: establishing a threshold time period during which a network device which requested services of a Domain Name Server (DNS) must receive a response from said DNS service; monitoring network metadata describing communications between network devices and DNS services; computing time elapsed between said network device request for a DNS service and receiving a response from that DNS service; comparing said elapsed time with said threshold time period; and generating an alert message to inform of excessive network latency. | 0.852834 |
10. A method comprising: generating a single script block for placement at a single location on an HTML document in response to a creation of one or more ad units for the HTML document, the single script block including one or more section codes that correspond to one or more content blocks of the HTML document; generating a syndication script for obtaining logic and metadata for injecting native advertisements in the HTML document based on the one or more section codes; providing the syndication script in response to a request generated by the single script block; and providing one or more native advertisements in response to an ad call generated by the syndication script, the one or more native advertisements for injection in the one or more content blocks of the HTML document based on the logic and metadata, wherein the metadata includes an XPath per section identifying nodes within a Document Object Model of the HTML document as native ad placement containers, wherein the syndication script obtains, from an advertisement server, logic for filtering child nodes within the Document Object Model to include only matching structures of the XPath(s) for subsequent injections of native advertisements, and obtains metadata for auto formatting data based on content of the HTML document. | 10. A method comprising: generating a single script block for placement at a single location on an HTML document in response to a creation of one or more ad units for the HTML document, the single script block including one or more section codes that correspond to one or more content blocks of the HTML document; generating a syndication script for obtaining logic and metadata for injecting native advertisements in the HTML document based on the one or more section codes; providing the syndication script in response to a request generated by the single script block; and providing one or more native advertisements in response to an ad call generated by the syndication script, the one or more native advertisements for injection in the one or more content blocks of the HTML document based on the logic and metadata, wherein the metadata includes an XPath per section identifying nodes within a Document Object Model of the HTML document as native ad placement containers, wherein the syndication script obtains, from an advertisement server, logic for filtering child nodes within the Document Object Model to include only matching structures of the XPath(s) for subsequent injections of native advertisements, and obtains metadata for auto formatting data based on content of the HTML document. 17. The method of claim 10 , wherein the one or more native advertisements include a plurality of ad unit formats. | 0.720874 |
1. A method comprising: receiving first activity information for a sender of a message to at least one recipient by a collection resource at a Web site, wherein the message comprises text associated with the Web site, the collection resource adds a first link to the message, and no personally identifiable information of the sender is collected in collecting the first activity information; storing the first activity information at a storage server; receiving second activity information when a recipient accesses the first link sent by the sender corresponding to the first activity information stored at the storage server, wherein no personally identifiable information of the recipient is collected in collecting the second activity information; using at least one processor, attempting to identify a first node representative of the sender in a social graph; and when a first node representative of the sender in a social graph is not identified and after receiving the second activity information, creating a second node to represent the sender in the social graph. | 1. A method comprising: receiving first activity information for a sender of a message to at least one recipient by a collection resource at a Web site, wherein the message comprises text associated with the Web site, the collection resource adds a first link to the message, and no personally identifiable information of the sender is collected in collecting the first activity information; storing the first activity information at a storage server; receiving second activity information when a recipient accesses the first link sent by the sender corresponding to the first activity information stored at the storage server, wherein no personally identifiable information of the recipient is collected in collecting the second activity information; using at least one processor, attempting to identify a first node representative of the sender in a social graph; and when a first node representative of the sender in a social graph is not identified and after receiving the second activity information, creating a second node to represent the sender in the social graph. 22. The method of claim 1 wherein the first link is uniquely associated with the sender. | 0.685526 |
28. A computer readable storage medium comprising computer-executable instructions for: receiving an option list of allowable options for an application, the option list comprising a first option, wherein the list of allowable options comprises, for each allowable option, a command line option string, a minimum number of characters that uniquely identify the command line option, a command line option identifier and a parameter having a value indicative of a type of allowable arguments for the command line option string; receiving a command line for the application, the received command line comprising a second option; parsing the received command line to determine if the second option matches the first option of the option list, wherein a success result is returned when it is determined that the first command line option in the command line exactly matches a portion of an option name in the list, a number of characters in the first command line option in the command line being not less than a minimum number of characters of the portion of the option name in the list of allowable options. | 28. A computer readable storage medium comprising computer-executable instructions for: receiving an option list of allowable options for an application, the option list comprising a first option, wherein the list of allowable options comprises, for each allowable option, a command line option string, a minimum number of characters that uniquely identify the command line option, a command line option identifier and a parameter having a value indicative of a type of allowable arguments for the command line option string; receiving a command line for the application, the received command line comprising a second option; parsing the received command line to determine if the second option matches the first option of the option list, wherein a success result is returned when it is determined that the first command line option in the command line exactly matches a portion of an option name in the list, a number of characters in the first command line option in the command line being not less than a minimum number of characters of the portion of the option name in the list of allowable options. 33. The computer readable storage medium of claim 28 , comprising further computer-executable instructions for: in response to determining that the second option is associated with an argument and the first option indicates that the argument for the second option is required, returning a success result. | 0.549631 |
23. A web application server comprising: a promotion generation module coupled with a network interface through a communications module, the promotion generation module configured to: (1) integrate an online promotion campaign into an application integrated with a social media platform via an application programming interface (API), wherein the application is configured to enable accessing and harvesting of profile information of users of the social media platform from the social media platform for the online promotion campaign, wherein the social media platform further includes viral features that can be leveraged to disseminate the online promotion campaign, and wherein the online promotion campaign includes distributing coupons or vouchers to participants, wherein the coupons or vouchers are integrated with the API to provide personalized information about participants of the online promotion campaign on the coupons or vouchers; (2) receive interest in the online promotion campaign from a participant through an entry point; (3) harvest for the online promotion campaign identification information from a social media profile of the participant maintained by the social media platform; (4) in response to the received interest in the online promotion campaign from the participant, generate a personalized coupon or voucher for the participant containing at least some of the participant's identification information; and (5) distribute the personalized coupon or voucher to the participant, wherein the identification information on the coupon or voucher provides a higher level of security and authenticity than vouchers or coupons that do not contain such identification information; and a communications module configured to automatically send invitations to enter the online promotion campaign to a list of contacts provided by the participant. | 23. A web application server comprising: a promotion generation module coupled with a network interface through a communications module, the promotion generation module configured to: (1) integrate an online promotion campaign into an application integrated with a social media platform via an application programming interface (API), wherein the application is configured to enable accessing and harvesting of profile information of users of the social media platform from the social media platform for the online promotion campaign, wherein the social media platform further includes viral features that can be leveraged to disseminate the online promotion campaign, and wherein the online promotion campaign includes distributing coupons or vouchers to participants, wherein the coupons or vouchers are integrated with the API to provide personalized information about participants of the online promotion campaign on the coupons or vouchers; (2) receive interest in the online promotion campaign from a participant through an entry point; (3) harvest for the online promotion campaign identification information from a social media profile of the participant maintained by the social media platform; (4) in response to the received interest in the online promotion campaign from the participant, generate a personalized coupon or voucher for the participant containing at least some of the participant's identification information; and (5) distribute the personalized coupon or voucher to the participant, wherein the identification information on the coupon or voucher provides a higher level of security and authenticity than vouchers or coupons that do not contain such identification information; and a communications module configured to automatically send invitations to enter the online promotion campaign to a list of contacts provided by the participant. 28. The web application server of claim 23 , wherein the viral features include one or more of newsfeeds, minifeeds or contact invites. | 0.555189 |
1. An electronic typewriter comprising: (a) a keyboard generating a signal corresponding to a depressed key and comprising at least character keys for inputting character data, a space key for separating said inputted character data into groups, each of said groups forming an inputted word, and a release key; (b) a dictionary memory for storing a plurality of word data; (c) a working memory for storing said inputted word; (d) a spelling check control means for reading word data from said dictionary memory and said inputted word from said working memory and comparing the spelling of said inputted word with said word data; (e) means responsive to operation of said release key for disabling said spelling check control means from checking the spelling of only a first word inputted after the depression of said release key and for reenabling said spelling check control means after said first word has been inputted; and (f) visible outputting means for displaying said inputted character data. | 1. An electronic typewriter comprising: (a) a keyboard generating a signal corresponding to a depressed key and comprising at least character keys for inputting character data, a space key for separating said inputted character data into groups, each of said groups forming an inputted word, and a release key; (b) a dictionary memory for storing a plurality of word data; (c) a working memory for storing said inputted word; (d) a spelling check control means for reading word data from said dictionary memory and said inputted word from said working memory and comparing the spelling of said inputted word with said word data; (e) means responsive to operation of said release key for disabling said spelling check control means from checking the spelling of only a first word inputted after the depression of said release key and for reenabling said spelling check control means after said first word has been inputted; and (f) visible outputting means for displaying said inputted character data. 2. An electronic typewriter according to claim 1, further comprising: (e1) means for setting a digital signal indicative of the disabling of said spelling check control means in accordance with a depression of said release key; (e2) means for judging the state of said digital signal in accordance with a depression of said space key; and (e3) means for enabling said spelling check control means comprising resetting said digital signal. | 0.626406 |
17. The system according to claim 14 , wherein scoring a match further includes performing the mathematical operation using the query significance value associated with NLQ words and the query significance value associated with a corresponding match candidate words or corresponding synonyms of the words for substantially each word in the NLQ having a corresponding word or corresponding synonym of the word in the match candidate and performing for each of the match candidates an aggregation of the results of the mathematical operations performed using the query significance values, for each match candidate of the one or more match candidates. | 17. The system according to claim 14 , wherein scoring a match further includes performing the mathematical operation using the query significance value associated with NLQ words and the query significance value associated with a corresponding match candidate words or corresponding synonyms of the words for substantially each word in the NLQ having a corresponding word or corresponding synonym of the word in the match candidate and performing for each of the match candidates an aggregation of the results of the mathematical operations performed using the query significance values, for each match candidate of the one or more match candidates. 18. The system according to claim 17 , wherein scoring a match further includes comparing a result of the aggregation with a perfect match score, wherein a perfect match score is a score a match candidate identical to the NLQ would receive. | 0.928529 |
1. A computer-implemented method comprising: analyzing, by a computer system, a codebase comprising a first dynamically-typed variable or function; determining, by the computer system, a first set of characteristics relating to the codebase based on the analyzing the codebase, wherein the analyzing the codebase includes performing one or more scans with respect to the codebase to determine the first set of characteristics, and wherein the first set of characteristics comprises information regarding usage of the first dynamically-typed variable or function in the codebase; determining, by the computer system, a first set of potential data types for the first dynamically-typed variable or function based on the first set of characteristics; determining, by the computer system, a first candidate data type for the first dynamically-typed variable or function based on the first set of potential data types, wherein the first candidate data type is a superclass of data types in the first set of potential data types, and wherein each of the data types in the first set of potential data types is a subclass of the first candidate data type; converting, by the computer system, the first dynamically-typed variable or function in the codebase to a first statically-typed variable or function in the codebase based on the first candidate data type; and checking, by the computer system, the codebase for one or more errors in response to the converting the first dynamically-typed variable or function to the first statically-typed variable or function. | 1. A computer-implemented method comprising: analyzing, by a computer system, a codebase comprising a first dynamically-typed variable or function; determining, by the computer system, a first set of characteristics relating to the codebase based on the analyzing the codebase, wherein the analyzing the codebase includes performing one or more scans with respect to the codebase to determine the first set of characteristics, and wherein the first set of characteristics comprises information regarding usage of the first dynamically-typed variable or function in the codebase; determining, by the computer system, a first set of potential data types for the first dynamically-typed variable or function based on the first set of characteristics; determining, by the computer system, a first candidate data type for the first dynamically-typed variable or function based on the first set of potential data types, wherein the first candidate data type is a superclass of data types in the first set of potential data types, and wherein each of the data types in the first set of potential data types is a subclass of the first candidate data type; converting, by the computer system, the first dynamically-typed variable or function in the codebase to a first statically-typed variable or function in the codebase based on the first candidate data type; and checking, by the computer system, the codebase for one or more errors in response to the converting the first dynamically-typed variable or function to the first statically-typed variable or function. 4. The computer-implemented method of claim 1 , wherein the first candidate data type is a common ancestor data type to each of the data types in the first set of potential data types. | 0.686782 |
8. A data processing system comprising: a processor; at least one memory connected with the processor and storing computer software that is executable by the processor; a rule category database, a rule provision database, and a fares database, each database coupled with the processor, the fares database storing a plurality of fares, and the rule category database and the rule provision database each storing a plurality of rules establishing conditions under which the fares can be applied; and an interface configured to receive an input from a first user specifying an attribute set including at least one rule attribute, wherein the processor is configured with the computer software to cause the data processing system to: in response to receiving the input, perform a first search in the rule category database to retrieve the rule categories corresponding to the rule attribute set; perform a second search in the rule provision database to retrieve rule provisions corresponding to the attribute set; identify rules related to the rule categories retrieved from the rule category database and the rule provisions retrieved from the rule provision database, wherein identifying rules relating to the rule categories and the rule provisions comprises executing a pre-data collection sub-process that filters each retrieved rule to remove rules that are not applicable and stores surviving rules; perform a third search using the identified rules to retrieve, for each identified rule, fares corresponding to the identified rule from the fares database, wherein the third search is performed as N search processes that are executed in parallel; build a list of eligible fares that are not invalidated by the attribute set using the fares retrieved from the fares database, wherein the list of eligible fares is a merged list obtained from a list output from each of the N search processes; create a functional index including one or more entries, each entry associating one of the rule categories to one or more of the eligible fares based on a corresponding attribute defined by the entry; associate the functional index with the attribute set; and in response to a second user specifying the attribute set, retrieve the fares from the fares database using the functional index. | 8. A data processing system comprising: a processor; at least one memory connected with the processor and storing computer software that is executable by the processor; a rule category database, a rule provision database, and a fares database, each database coupled with the processor, the fares database storing a plurality of fares, and the rule category database and the rule provision database each storing a plurality of rules establishing conditions under which the fares can be applied; and an interface configured to receive an input from a first user specifying an attribute set including at least one rule attribute, wherein the processor is configured with the computer software to cause the data processing system to: in response to receiving the input, perform a first search in the rule category database to retrieve the rule categories corresponding to the rule attribute set; perform a second search in the rule provision database to retrieve rule provisions corresponding to the attribute set; identify rules related to the rule categories retrieved from the rule category database and the rule provisions retrieved from the rule provision database, wherein identifying rules relating to the rule categories and the rule provisions comprises executing a pre-data collection sub-process that filters each retrieved rule to remove rules that are not applicable and stores surviving rules; perform a third search using the identified rules to retrieve, for each identified rule, fares corresponding to the identified rule from the fares database, wherein the third search is performed as N search processes that are executed in parallel; build a list of eligible fares that are not invalidated by the attribute set using the fares retrieved from the fares database, wherein the list of eligible fares is a merged list obtained from a list output from each of the N search processes; create a functional index including one or more entries, each entry associating one of the rule categories to one or more of the eligible fares based on a corresponding attribute defined by the entry; associate the functional index with the attribute set; and in response to a second user specifying the attribute set, retrieve the fares from the fares database using the functional index. 9. The data processing system of claim 8 , wherein a value of N is determined based on a number of rules identified and on a set of predetermined thresholds, and N is an integer equal to one or greater than one. | 0.543649 |
50. A method of locating relevant documents within a universe of documents, the documents of said universe having been classified and appears in an inverted list, said inverted list comprising for each topic category of a classification system a weight associated with a particular document of the list of documents, each of the weights representing a degree to which the particular document relates to said each topic category, the weights obtained automatically from a computer program, the method having a scalable time complexity of O(N x ) where 0<=X<=1.0 for a universe of text on the world wide web and comprising: a computer processor creating a fingerprint for a first piece of text, the fingerprint comprising a list of weights associated with particular topic categories in the classification system, each of the weights in the fingerprint for said first piece of text representing a degree to which the first piece of text relates to the particular topic category that the weight in the fingerprint for said first piece of text is associated with, the weights in the fingerprint for said first piece of text obtained automatically from a computer program, a computer processor searching all or a portion of the universe of documents by comparing the fingerprint for the first piece of text with the fingerprint for each document in that all or a portion of the universe of documents, and selecting those documents whose fingerprints have a predetermined degree of mathematical overlap with the fingerprint of the first piece of text, the method configured to locate the relevant documents within the universe of documents whether the universe of documents includes text written in one language or in more than one language. | 50. A method of locating relevant documents within a universe of documents, the documents of said universe having been classified and appears in an inverted list, said inverted list comprising for each topic category of a classification system a weight associated with a particular document of the list of documents, each of the weights representing a degree to which the particular document relates to said each topic category, the weights obtained automatically from a computer program, the method having a scalable time complexity of O(N x ) where 0<=X<=1.0 for a universe of text on the world wide web and comprising: a computer processor creating a fingerprint for a first piece of text, the fingerprint comprising a list of weights associated with particular topic categories in the classification system, each of the weights in the fingerprint for said first piece of text representing a degree to which the first piece of text relates to the particular topic category that the weight in the fingerprint for said first piece of text is associated with, the weights in the fingerprint for said first piece of text obtained automatically from a computer program, a computer processor searching all or a portion of the universe of documents by comparing the fingerprint for the first piece of text with the fingerprint for each document in that all or a portion of the universe of documents, and selecting those documents whose fingerprints have a predetermined degree of mathematical overlap with the fingerprint of the first piece of text, the method configured to locate the relevant documents within the universe of documents whether the universe of documents includes text written in one language or in more than one language. 54. The method of claim 50 , wherein a selected number of weights is between 1 and 75 and the classification system is the Dewey Decimal System. | 0.521104 |
20. A computer program product for automatic speech recognition as in claim 19 , wherein whenever said language model provides more than one candidate having a probability within a threshold of each other, said context model iteratively adjusts likelihoods based on said context until a single candidate matches, and automatically updates said respective context responsive to said single candidate matching. | 20. A computer program product for automatic speech recognition as in claim 19 , wherein whenever said language model provides more than one candidate having a probability within a threshold of each other, said context model iteratively adjusts likelihoods based on said context until a single candidate matches, and automatically updates said respective context responsive to said single candidate matching. 21. A computer program product for automatic speech recognition as in claim 20 , wherein said context is described by a cross-relation between a plurality of situational variables including time, location, activity and social setting, and said dynamic context model weights said probability for each said more than one candidate according to the frequency each has occurred within said respective context. | 0.862754 |
51. The system of claim 50 , further comprising altering one or more permissions associated with the electronic document in accordance with the consent indication information. | 51. The system of claim 50 , further comprising altering one or more permissions associated with the electronic document in accordance with the consent indication information. 52. The system of claim 51 , wherein the consent query includes a predefined list of consent statements, and the consent indication comprises a selection from the predefined list of consent statements. | 0.926963 |
8. The method of claim 1 , wherein converting the electronic image into the mathematical graph includes minor feature editing. | 8. The method of claim 1 , wherein converting the electronic image into the mathematical graph includes minor feature editing. 11. The method of claim 8 , wherein the minor feature editing comprises combining a plurality of close vertices. | 0.889193 |
13. A method according to claim 11 , wherein the verification by the human transcriber comprises one of confirming one or more of the transcribed values and assigning a different transcribed value to one or more of the questionable utterances in the sample. | 13. A method according to claim 11 , wherein the verification by the human transcriber comprises one of confirming one or more of the transcribed values and assigning a different transcribed value to one or more of the questionable utterances in the sample. 15. A method according to claim 13 , further comprising: comparing the confirmed transcribed values and the different transcribed values of the questionable utterances in the sample; and when the confirmed transcribed values and the different transcribed values differ, providing the questionable utterances in the pool that are not included in the sample to a different human reviewer. | 0.849575 |
44. A method of retrieving a document in a document management system managed under a Document Management Alliance document object model, said method being embodied in a computer readable medium which when executed by a processing apparatus comprises: receiving a document request comprising a document ID including two character strings, the first character string being a route node and the second character string specifying at least one of a version, a rendition, or a content of a document object at a server, said document request including a plurality of hierarchical-tree parameters; separating said document ID into character strings for identifying at least one of said version, said rendition or said content of the document object; executing operations in accordance with said character strings separated by said separating step; providing a default value for at least one of said version, said rendition or said content of the document object; identifying at least one node of said document based on the first character string; identifying a document object using said second character string; and returning, at least, a portion of said document corresponding to said at least one node. | 44. A method of retrieving a document in a document management system managed under a Document Management Alliance document object model, said method being embodied in a computer readable medium which when executed by a processing apparatus comprises: receiving a document request comprising a document ID including two character strings, the first character string being a route node and the second character string specifying at least one of a version, a rendition, or a content of a document object at a server, said document request including a plurality of hierarchical-tree parameters; separating said document ID into character strings for identifying at least one of said version, said rendition or said content of the document object; executing operations in accordance with said character strings separated by said separating step; providing a default value for at least one of said version, said rendition or said content of the document object; identifying at least one node of said document based on the first character string; identifying a document object using said second character string; and returning, at least, a portion of said document corresponding to said at least one node. 45. A method of retrieving a document in a document management system as defined in claim 44 , wherein said plurality of hierarchical-tree parameters comprises: a document identification parameter. | 0.795517 |
8. The method of claim 7 , wherein the similar transaction phrase comprises at least one of the following: a synonym of the target user transaction phrase and a similar sounding word of the target user transaction phrase. | 8. The method of claim 7 , wherein the similar transaction phrase comprises at least one of the following: a synonym of the target user transaction phrase and a similar sounding word of the target user transaction phrase. 9. The method of claim 8 , further comprising weighting first candidate recommendations obtained by indexing the target user transaction phrase higher than second candidate recommendations obtained by indexing the synonym of the target user transaction phrase. | 0.865303 |
1. A method for unifying a fragmented document comprising: identifying structural information elements of a root document, wherein the structural information elements comprise at least one reference to a discrete document other than the root document; presenting to a user, the identified structural information elements within a rapid selection interface for selective acquisition of content from the discrete document; receiving at the rapid selection interface, a user initiated unification command including a user selection of one or more of the presented structural information elements; responsive to said unification command, acquiring content represented by the at least one reference from the discrete document without presenting the discrete document within a user interface window; and adding the acquired content to the root document. | 1. A method for unifying a fragmented document comprising: identifying structural information elements of a root document, wherein the structural information elements comprise at least one reference to a discrete document other than the root document; presenting to a user, the identified structural information elements within a rapid selection interface for selective acquisition of content from the discrete document; receiving at the rapid selection interface, a user initiated unification command including a user selection of one or more of the presented structural information elements; responsive to said unification command, acquiring content represented by the at least one reference from the discrete document without presenting the discrete document within a user interface window; and adding the acquired content to the root document. 5. The method of claim 1 , wherein said plurality of documents are stored in different storage mediums located in different geographic locations, wherein the different storage mediums are communicatively linked via a network. | 0.845095 |
14. The method of claim 7 , wherein said step of locating at least a first speech endpoint comprises: identifying a most likely word in said audio signal; and determining whether a duration of said most likely word is long enough to indicate that said most likely word represents said first speech endpoint. | 14. The method of claim 7 , wherein said step of locating at least a first speech endpoint comprises: identifying a most likely word in said audio signal; and determining whether a duration of said most likely word is long enough to indicate that said most likely word represents said first speech endpoint. 18. The method of claim 14 , wherein the step of identifying a most likely word comprises: identifying a most likely stopping word for speech in said audio signal, where said most likely stopping word represents a potential speech ending point; and selecting a predecessor word of said most likely stopping word as said most likely word in said audio signal. | 0.770403 |
19. A non-transitory computer-readable medium storing a set of computer instructions to provide a response to a received user input, wherein the set of computer instructions, when executed on a computer, causes the computer, automatically: (a) in response to receiving, from a user's device, a partial user input signifying a portion of an answerable statement, before receiving a full user input representing the entire answerable statement, to calculate for each of a plurality of predefined answerable statements, a match metric denoting a degree to which the partial user input matches the predefined answerable statement; and (b) (1) if the match metric for one of the predefined answerable statements exceeds a first threshold, to send, to the user's device, information representing a response associated with said one of the predefined answerable statements, and (2) if part (b)(1) does not apply but the match metric for at least one of the predefined answerable statements exceeds a second threshold, which second threshold is lower than the first threshold, to send, to the user's device, information representing the corresponding at least one of the predefined answerable statements. | 19. A non-transitory computer-readable medium storing a set of computer instructions to provide a response to a received user input, wherein the set of computer instructions, when executed on a computer, causes the computer, automatically: (a) in response to receiving, from a user's device, a partial user input signifying a portion of an answerable statement, before receiving a full user input representing the entire answerable statement, to calculate for each of a plurality of predefined answerable statements, a match metric denoting a degree to which the partial user input matches the predefined answerable statement; and (b) (1) if the match metric for one of the predefined answerable statements exceeds a first threshold, to send, to the user's device, information representing a response associated with said one of the predefined answerable statements, and (2) if part (b)(1) does not apply but the match metric for at least one of the predefined answerable statements exceeds a second threshold, which second threshold is lower than the first threshold, to send, to the user's device, information representing the corresponding at least one of the predefined answerable statements. 23. The non-transitory computer-readable medium of claim 19 wherein, further, the set of computer instructions, when executed on the computer, causes the computer, if part (b)(2) applies, to automatically send, to the user's device, information representing the match metric calculated for each of the corresponding at least one of the predefined answerable statements. | 0.561786 |
9. A computer-implemented method, comprising: accessing text by a processing system; identifying, by the processing system, a plurality of terms from the text; determining, by the processing system, a plurality of term vectors associated with the identified terms; calculating a weight of each of the determined term vectors; clustering, by the processing system, the determined term vectors into a plurality of clusters, each of the clusters being related to a distinct concept of the text, each cluster comprising at least one of the determined term vectors, the clustering comprising selecting the at least one of the determined term vectors based on the determined weights of the term vectors and distances between the determined term vectors; identifying, by the processing system using latent semantic analysis (LSA), a first set of terms associated with a first cluster of the plurality of clusters and a second set of terms associated with a second cluster of the plurality of clusters; determining, by the processing system, a first weight associated with the first cluster and a second weight associated with the second cluster, wherein the first weight is based at least on the weights of the term vectors of the first cluster, and wherein the second weight is based at least on the weights of the term vectors of the second cluster; determining, by the processing system, a first percentage of a list of output terms that should come from the first cluster and a second percentage of the list of output terms that should come from the second cluster, the first percentage based on a ratio of the first weight to a sum of the first and second weights, the second percentage based on a ratio of the second weight to the sum of the first and second weights; selecting, by the processing system, one or more terms from the first set of terms according to the determined first percentage; selecting, by the processing system, one or more terms from the second set of terms according to the determined second percentage; creating, by the processing system, the list of output terms using at least a portion of the selected terms from the first and second sets of terms, the list of output terms having the distinct concepts of the plurality of clusters; and storing, by the processing system, the list of output terms in one or more memory units. | 9. A computer-implemented method, comprising: accessing text by a processing system; identifying, by the processing system, a plurality of terms from the text; determining, by the processing system, a plurality of term vectors associated with the identified terms; calculating a weight of each of the determined term vectors; clustering, by the processing system, the determined term vectors into a plurality of clusters, each of the clusters being related to a distinct concept of the text, each cluster comprising at least one of the determined term vectors, the clustering comprising selecting the at least one of the determined term vectors based on the determined weights of the term vectors and distances between the determined term vectors; identifying, by the processing system using latent semantic analysis (LSA), a first set of terms associated with a first cluster of the plurality of clusters and a second set of terms associated with a second cluster of the plurality of clusters; determining, by the processing system, a first weight associated with the first cluster and a second weight associated with the second cluster, wherein the first weight is based at least on the weights of the term vectors of the first cluster, and wherein the second weight is based at least on the weights of the term vectors of the second cluster; determining, by the processing system, a first percentage of a list of output terms that should come from the first cluster and a second percentage of the list of output terms that should come from the second cluster, the first percentage based on a ratio of the first weight to a sum of the first and second weights, the second percentage based on a ratio of the second weight to the sum of the first and second weights; selecting, by the processing system, one or more terms from the first set of terms according to the determined first percentage; selecting, by the processing system, one or more terms from the second set of terms according to the determined second percentage; creating, by the processing system, the list of output terms using at least a portion of the selected terms from the first and second sets of terms, the list of output terms having the distinct concepts of the plurality of clusters; and storing, by the processing system, the list of output terms in one or more memory units. 14. The computer-implemented method of claim 9 , wherein: the weights of each of the determined term vectors comprise log-entropy weights; the first weight associated with the first cluster comprises a sum of the determined log-entropy weights of the term vectors of the first cluster; and the second weight associated with the second cluster comprises a sum of the determined log-entropy weights of the term vectors of the second cluster. | 0.535211 |
16. The non-transitory memory medium of claim 11 , wherein said detecting comprises use of an XML difference tracker detecting the differences between the template XML form and the modified XML form. | 16. The non-transitory memory medium of claim 11 , wherein said detecting comprises use of an XML difference tracker detecting the differences between the template XML form and the modified XML form. 17. The non-transitory memory medium of claim 16 , wherein the XML difference tracker is selectively namespace aware. | 0.949859 |
10. A computer-implemented method comprising: receiving at least a portion of an activity stream associated with an asset-modifying workflow and an abstraction of an asset associated with the asset-modifying workflow; determining a contextual identifier to associate with the received abstraction of the asset by generating a similarity score for each of a plurality of contextually identified abstractions when compared to the received abstraction to identify the contextual identifier from a first contextually identified abstraction from the plurality of contextually identified abstractions having a highest similarity score; determining a modification to the asset-modifying workflow based on the determined contextual identifier; and communicating a signal operable to apply the determined modification to the asset-modifying workflow. | 10. A computer-implemented method comprising: receiving at least a portion of an activity stream associated with an asset-modifying workflow and an abstraction of an asset associated with the asset-modifying workflow; determining a contextual identifier to associate with the received abstraction of the asset by generating a similarity score for each of a plurality of contextually identified abstractions when compared to the received abstraction to identify the contextual identifier from a first contextually identified abstraction from the plurality of contextually identified abstractions having a highest similarity score; determining a modification to the asset-modifying workflow based on the determined contextual identifier; and communicating a signal operable to apply the determined modification to the asset-modifying workflow. 11. The method of claim 10 , wherein the received abstraction is a hash. | 0.782105 |
32. A method of performing quality analysis on a plurality of interactions, each one of the interactions involving at least one agent, the method comprising at least the following: obtaining data representing at least a given one of the interactions, each one of the interactions having a respective actual duration parameter associated therewith; obtaining data representing at least one expected duration parameter evaluated by an automatic recognition component having a log record module that is applicable to at least the given one of the interactions; for at least the given one of the interactions, comparing the actual duration of the given one interaction to the expected duration parameter and comparing a plurality of duration parameters to respective portions of the actual duration of the given one interaction; dispositioning at least the given one interaction based on the comparing; wherein dispositioning at least the given transaction including assigning the given interaction for evaluation because the actual duration of the given interaction falls outside of a pre-defined range applicable to the given interaction. | 32. A method of performing quality analysis on a plurality of interactions, each one of the interactions involving at least one agent, the method comprising at least the following: obtaining data representing at least a given one of the interactions, each one of the interactions having a respective actual duration parameter associated therewith; obtaining data representing at least one expected duration parameter evaluated by an automatic recognition component having a log record module that is applicable to at least the given one of the interactions; for at least the given one of the interactions, comparing the actual duration of the given one interaction to the expected duration parameter and comparing a plurality of duration parameters to respective portions of the actual duration of the given one interaction; dispositioning at least the given one interaction based on the comparing; wherein dispositioning at least the given transaction including assigning the given interaction for evaluation because the actual duration of the given interaction falls outside of a pre-defined range applicable to the given interaction. 35. The method of claim 32 , wherein obtaining data representing the given one of the interactions includes receiving a respective voice record of the given one of the interactions involving an agent physically located remotely from a call center. | 0.697557 |
1. A computer-implemented method for vulnerability risk management of an enterprise computing system, comprising the steps of: instantiating, by a cloud computing system employing a software-as-a-service multi-tenant architecture, a vulnerability risk management module and an expert system coupled to the vulnerability risk management module, the vulnerability risk management module configured for: receiving from an end user a type of vulnerability; determining a list of potential vulnerabilities of the enterprise computing system based on a non-intrusive scan of the enterprise computing system for the received type of vulnerability, wherein the scan includes a scan of an asset of the enterprise computing system associated with the type of vulnerability and wherein the scan is based on a preference of the end user regarding a specified date and time to conduct the scan; transmitting the list of potential vulnerabilities to the expert system; receiving from the expert system a refined list of potential vulnerabilities; and reporting the refined list of vulnerabilities to the end user. | 1. A computer-implemented method for vulnerability risk management of an enterprise computing system, comprising the steps of: instantiating, by a cloud computing system employing a software-as-a-service multi-tenant architecture, a vulnerability risk management module and an expert system coupled to the vulnerability risk management module, the vulnerability risk management module configured for: receiving from an end user a type of vulnerability; determining a list of potential vulnerabilities of the enterprise computing system based on a non-intrusive scan of the enterprise computing system for the received type of vulnerability, wherein the scan includes a scan of an asset of the enterprise computing system associated with the type of vulnerability and wherein the scan is based on a preference of the end user regarding a specified date and time to conduct the scan; transmitting the list of potential vulnerabilities to the expert system; receiving from the expert system a refined list of potential vulnerabilities; and reporting the refined list of vulnerabilities to the end user. 9. The method of claim 1 , further comprising resolving at least one vulnerability on the refined list of vulnerabilities and removing the at least one vulnerability from the refined list of vulnerabilities. | 0.522368 |
11. A system of detecting punctuation errors in a text including one or more sentences, the system comprising: one or more data processors; one or more computer-readable mediums in communication with the data processors encoded with instructions for commanding the data processors to execute steps comprising: receiving a sentence including one or more preexisting punctuation marks; determining one or more punctuation marks that should be included in the sentence; comparing the determined punctuation marks with the preexisting punctuation marks; identifying a punctuation mark that should be inserted into a space between two words in the sentence based on said step of comparing, the space in the sentence not being punctuated by any of the preexisting punctuation marks; outputting a report of punctuation errors based on the comparison; and displaying a corrected form of the sentence that depicts the sentence with the one or more punctuation marks determined that should be included in the sentence; wherein said determining one or more punctuation marks that should be included in the sentence includes: identifying a target insertion point for a punctuation mark in the text; identifying a predetermined number of words surrounding the target insertion point; parsing the identified words into a plurality of n-grams; converting the plurality of n-grams into a corresponding plurality of part-of-speech n-grams; generating a combination unigram for each of the identified words, the combination unigram including the associated identified word and the part-of-speech of the associated identified word; and applying a statistical classifier using at least the plurality of n-grams, the plurality of part-of-speech n-grams, and the combination unigrams, the statistical classifier determining the one or more punctuation marks that should be included in the sentence. | 11. A system of detecting punctuation errors in a text including one or more sentences, the system comprising: one or more data processors; one or more computer-readable mediums in communication with the data processors encoded with instructions for commanding the data processors to execute steps comprising: receiving a sentence including one or more preexisting punctuation marks; determining one or more punctuation marks that should be included in the sentence; comparing the determined punctuation marks with the preexisting punctuation marks; identifying a punctuation mark that should be inserted into a space between two words in the sentence based on said step of comparing, the space in the sentence not being punctuated by any of the preexisting punctuation marks; outputting a report of punctuation errors based on the comparison; and displaying a corrected form of the sentence that depicts the sentence with the one or more punctuation marks determined that should be included in the sentence; wherein said determining one or more punctuation marks that should be included in the sentence includes: identifying a target insertion point for a punctuation mark in the text; identifying a predetermined number of words surrounding the target insertion point; parsing the identified words into a plurality of n-grams; converting the plurality of n-grams into a corresponding plurality of part-of-speech n-grams; generating a combination unigram for each of the identified words, the combination unigram including the associated identified word and the part-of-speech of the associated identified word; and applying a statistical classifier using at least the plurality of n-grams, the plurality of part-of-speech n-grams, and the combination unigrams, the statistical classifier determining the one or more punctuation marks that should be included in the sentence. 14. The system of claim 11 , wherein the one or more punctuation marks that should be included in the sentence are determined regardless of the preexisting punctuation marks. | 0.521298 |
58. A method according to claim 55, further including the step of keeping track of all points in the record which relate to a range for an assigned name representative of a set of data presentation characteristics. | 58. A method according to claim 55, further including the step of keeping track of all points in the record which relate to a range for an assigned name representative of a set of data presentation characteristics. 60. A method according to claim 58, including the steps of storing control information relating to each of the points and linking related points together. | 0.957734 |
1. A method, comprising: receiving, in a computing apparatus from a first computing device, a plurality of text strings, each of the text strings identifying a separate search query, wherein the text strings are from search queries previously entered by users on a first plurality of computing devices; applying, by the computing apparatus, each respective rule of a first plurality of rules to each respective text string of the plurality of text strings, including determining whether the respective text string satisfies a condition of the respective rule, wherein the condition of at least one respective rule is determined to be satisfied by the respective text string in response to a determining the respective text string includes a predetermined text pattern specified for the respective rule; in response to a determining the respective text string satisfies the condition of the respective rule, associating a set of metadata of the respective rule with a search query identified by the respective text string; sorting, by the computing apparatus, the plurality of text strings based at least in part on metadata associated with the search queries via the applying of the first plurality of rules; identifying, by the computing apparatus, a potential title based on the sorting of the plurality of text strings; providing, by the computing apparatus to a second computing device, the potential title for use in creating content, the providing further comprising providing key words obtained from the plurality of text strings, wherein the second computing device is different from the first computing device; receiving, from the second computing device, the created content, wherein the created content includes the key words; transforming the potential title to generate a final title using a second plurality of rules; and publishing, by the computing apparatus, the created content under the final title, wherein the publishing provides access via a website to a second plurality of computing devices, and the second plurality of computing devices is different from the first plurality of computing devices. | 1. A method, comprising: receiving, in a computing apparatus from a first computing device, a plurality of text strings, each of the text strings identifying a separate search query, wherein the text strings are from search queries previously entered by users on a first plurality of computing devices; applying, by the computing apparatus, each respective rule of a first plurality of rules to each respective text string of the plurality of text strings, including determining whether the respective text string satisfies a condition of the respective rule, wherein the condition of at least one respective rule is determined to be satisfied by the respective text string in response to a determining the respective text string includes a predetermined text pattern specified for the respective rule; in response to a determining the respective text string satisfies the condition of the respective rule, associating a set of metadata of the respective rule with a search query identified by the respective text string; sorting, by the computing apparatus, the plurality of text strings based at least in part on metadata associated with the search queries via the applying of the first plurality of rules; identifying, by the computing apparatus, a potential title based on the sorting of the plurality of text strings; providing, by the computing apparatus to a second computing device, the potential title for use in creating content, the providing further comprising providing key words obtained from the plurality of text strings, wherein the second computing device is different from the first computing device; receiving, from the second computing device, the created content, wherein the created content includes the key words; transforming the potential title to generate a final title using a second plurality of rules; and publishing, by the computing apparatus, the created content under the final title, wherein the publishing provides access via a website to a second plurality of computing devices, and the second plurality of computing devices is different from the first plurality of computing devices. 10. The method of claim 1 , wherein the query type is one of: informational, transactional, or navigational. | 0.532816 |
1. A method of compressing visual descriptors from at least one image by exploiting redundancy of natural image descriptors, comprising: extracting the visual descriptors from at least one image, said visual descriptors describing key points in images; creating model parameters of a generative probabilistic model from the extracted visual descriptors in a maximum likelihood sense; quantizing and encoding said model parameters; quantizing said extracted visual descriptors; and, applying a model-based arithmetic encoding to said quantized extracted visual descriptors using said encoded model parameters exploiting redundancy of the visual descriptors within the at least one image for compression of the visual descriptors. | 1. A method of compressing visual descriptors from at least one image by exploiting redundancy of natural image descriptors, comprising: extracting the visual descriptors from at least one image, said visual descriptors describing key points in images; creating model parameters of a generative probabilistic model from the extracted visual descriptors in a maximum likelihood sense; quantizing and encoding said model parameters; quantizing said extracted visual descriptors; and, applying a model-based arithmetic encoding to said quantized extracted visual descriptors using said encoded model parameters exploiting redundancy of the visual descriptors within the at least one image for compression of the visual descriptors. 3. The method of claim 1 , comprising transmitting at least one of said encoded model parameters and said encoded visual descriptors to a decoder. | 0.898481 |
39. The method of claim 38 wherein influencing comprises generating an interactive timeline based on the temporal profile of the search query. | 39. The method of claim 38 wherein influencing comprises generating an interactive timeline based on the temporal profile of the search query. 41. The method of claim 39 further comprising receiving the temporal relevance feedback from the user input to the interactive timeline. | 0.94057 |
1. A method for identifying books located on a bookshelf, the method comprising: capturing one or more photographic images of the bookshelf; segmenting the photographic images into regions, each of the regions corresponding to a respective book spine; analyzing at least one of the regions to identify a book corresponding thereto, wherein analyzing the at least one of the regions comprises: extracting one or more visual features descriptive of the at least one of the regions, the one or more visual features including machine-recognized text and a location of the machine-recognized text contained within the at least one of the regions, wherein the machine-recognized text and the location of the machine-recognized text are used as analogues of visual features; performing a matching operation based on the one or more visual features, the matching operation performed against stored data associating plural book identities with corresponding visual features; when the matching operation returns one of the book identities sufficiently closely matched with the one or more visual features, identifying the at least one of the regions as representing said one of the book identities; when the matching operation fails to return one of the book identities sufficiently closely matched with the one or more visual features, initiating a further analysis of the at least one of the regions to identify the book corresponding thereto; and when the further analysis returns a further book identity sufficiently closely matched with the one or more visual features, identifying the at least one of the regions as representing the further book identity; and browsing another user's bookshelf, wherein browsing another user's bookshelf comprises: comparing a first book title list of a first bookshelf belonging to a first user with a second book title list of a second bookshelf belonging to a second user, wherein the first book title list and the second book title list include book titles identified as a result of analyzing the at least one of the regions; and enabling the first user to access the second book title list of the second bookshelf when there is at least a predetermined amount of overlap between the book titles of the first user's bookshelf and the book titles of the second user's bookshelf. | 1. A method for identifying books located on a bookshelf, the method comprising: capturing one or more photographic images of the bookshelf; segmenting the photographic images into regions, each of the regions corresponding to a respective book spine; analyzing at least one of the regions to identify a book corresponding thereto, wherein analyzing the at least one of the regions comprises: extracting one or more visual features descriptive of the at least one of the regions, the one or more visual features including machine-recognized text and a location of the machine-recognized text contained within the at least one of the regions, wherein the machine-recognized text and the location of the machine-recognized text are used as analogues of visual features; performing a matching operation based on the one or more visual features, the matching operation performed against stored data associating plural book identities with corresponding visual features; when the matching operation returns one of the book identities sufficiently closely matched with the one or more visual features, identifying the at least one of the regions as representing said one of the book identities; when the matching operation fails to return one of the book identities sufficiently closely matched with the one or more visual features, initiating a further analysis of the at least one of the regions to identify the book corresponding thereto; and when the further analysis returns a further book identity sufficiently closely matched with the one or more visual features, identifying the at least one of the regions as representing the further book identity; and browsing another user's bookshelf, wherein browsing another user's bookshelf comprises: comparing a first book title list of a first bookshelf belonging to a first user with a second book title list of a second bookshelf belonging to a second user, wherein the first book title list and the second book title list include book titles identified as a result of analyzing the at least one of the regions; and enabling the first user to access the second book title list of the second bookshelf when there is at least a predetermined amount of overlap between the book titles of the first user's bookshelf and the book titles of the second user's bookshelf. 9. The method of claim 1 , wherein the one or more visual features further include one or more of: texture, colour and shape of the at least one of the regions. | 0.573428 |
1. A computer-implemented method for interactively exploring data objects associated with a business context, the method comprising: receiving a user action selecting a portion of a first one of the data objects, the selected portion of the first one of the data objects comprising at least one attribute correspondingly mapped to a meaning; retrieving at least one query comprising at least one input parameter correspondingly mapped to the meaning associated with the at least one attribute of the selected portion; in response to a user selection of the retrieved query, passing a value of the at least one attribute of the selected portion as input to the retrieved query; generating a search request based on the retrieved query with the passed value as the input parameter to obtain at least a second data object representing supplementary data related to the first one of the data objects; and routing the search request for execution of the query to a search connector defined as part of a query configuration of the retrieved query. | 1. A computer-implemented method for interactively exploring data objects associated with a business context, the method comprising: receiving a user action selecting a portion of a first one of the data objects, the selected portion of the first one of the data objects comprising at least one attribute correspondingly mapped to a meaning; retrieving at least one query comprising at least one input parameter correspondingly mapped to the meaning associated with the at least one attribute of the selected portion; in response to a user selection of the retrieved query, passing a value of the at least one attribute of the selected portion as input to the retrieved query; generating a search request based on the retrieved query with the passed value as the input parameter to obtain at least a second data object representing supplementary data related to the first one of the data objects; and routing the search request for execution of the query to a search connector defined as part of a query configuration of the retrieved query. 2. The method of claim 1 , wherein passing a value of the at least one attribute of the selected portion as input to the retrieved query further comprises matching the meaning of the at least one attribute with the meaning of the input parameter of the query. | 0.64562 |
3. The method of claim 1 , further comprising ranking the plurality of sentence plans. | 3. The method of claim 1 , further comprising ranking the plurality of sentence plans. 4. The method of claim 3 , wherein the selected sentence plan is the highest ranked sentence plan of the plurality of the sentence plans. | 0.943811 |
1. A method of integrating a visual menu with an audio menu, comprising: receiving an audio call from a user; initiating an interactive session based on the received audio call; correlating the user with an accessible interactive device, including mapping a user identification of the user with a virtual location of the user, wherein the user identification comprises a combination of a phone number, an employee identification, and a customer identification; registering the user with multiple entities that utilize the visual menu and the audio menu; transmitting an instant message including an embedded hyperlink to the virtual location of the user, wherein the instant message comprises an instruction displayed on an interactive display device for receiving the visual menu; initiating the audio menu by an interactive voice response unit using an audio control module; executing the instruction to receive the visual menu; providing the visual menu to the user by displaying it within an instant messaging window; synchronizing the visual menu and the audio menu using time stamp and dual-tone multi-frequency input from the accessible interactive device; and updating the visual menu with the audio menu as the user selects a menu option presented by at least one of the visual menu or the audio menu. | 1. A method of integrating a visual menu with an audio menu, comprising: receiving an audio call from a user; initiating an interactive session based on the received audio call; correlating the user with an accessible interactive device, including mapping a user identification of the user with a virtual location of the user, wherein the user identification comprises a combination of a phone number, an employee identification, and a customer identification; registering the user with multiple entities that utilize the visual menu and the audio menu; transmitting an instant message including an embedded hyperlink to the virtual location of the user, wherein the instant message comprises an instruction displayed on an interactive display device for receiving the visual menu; initiating the audio menu by an interactive voice response unit using an audio control module; executing the instruction to receive the visual menu; providing the visual menu to the user by displaying it within an instant messaging window; synchronizing the visual menu and the audio menu using time stamp and dual-tone multi-frequency input from the accessible interactive device; and updating the visual menu with the audio menu as the user selects a menu option presented by at least one of the visual menu or the audio menu. 5. The method of claim 1 , wherein transmitting the instant message to the virtual location of the user comprises transmitting the instant message over a network. | 0.65345 |
19. The system of claim 17 wherein the modified video signal is provided to a plurality of customer equipment. | 19. The system of claim 17 wherein the modified video signal is provided to a plurality of customer equipment. 20. The system of claim 19 wherein the customer equipment is located at different locations associated with different subscribers. | 0.918704 |
16. A non-transitory computer readable storage medium storing one or more programs, the one or more programs comprising instructions, which, when executed by an electronic device with one or more processors, cause the device to: train an acoustic model with an International Phonetic Alphabet (IPA) phoneme mapping collection and a plurality of audio samples in a plurality of different languages, wherein the acoustic model includes: a foreground model configured to match a phoneme in an input audio signal to a corresponding keyword, wherein the foreground model is trained by (i) obtaining a phoneme collection for each of the plurality of different languages, (ii) generating a plurality of triphones by linking phonemes in the phoneme collection corresponding to the language, and (iii) performing Gaussian splitting training on the triphones that are clustered with a decision tree corresponding to the language; and a background model configured to match a phoneme in the input audio signal to a corresponding non-keyword; after training the acoustic model, generate a phone decoder based on the trained acoustic model; obtain a keyword phoneme sequence for a respective keyword in a respective language of the plurality of different languages, wherein the obtaining includes: collecting a set of keyword audio samples for the respective keyword in the respective language; decoding the set of keyword audio samples with the phone decoder to generate a set of phoneme sequence candidates for the respective keyword, each phoneme sequence candidate corresponding to a respective keyword audio sample; and selecting the keyword phoneme sequence for the respective keyword from the set of phoneme sequence candidates by choosing a phoneme of a highest confidence measure from one of the set of phoneme sequence candidates at each location in the corresponding sequence and assembling the chosen phonemes into the keyword phoneme sequence according to their locations in the corresponding sequence; after obtaining the keyword phoneme sequence, detect one or more keywords in the input audio signal with the trained acoustic model, wherein the detecting includes: matching one or more phonemic keyword portions of the input audio signal with one or more phonemes in the keyword phoneme sequence with the foreground model; and filtering out one or more phonemic non-keyword portions of the input audio signal with the background model. | 16. A non-transitory computer readable storage medium storing one or more programs, the one or more programs comprising instructions, which, when executed by an electronic device with one or more processors, cause the device to: train an acoustic model with an International Phonetic Alphabet (IPA) phoneme mapping collection and a plurality of audio samples in a plurality of different languages, wherein the acoustic model includes: a foreground model configured to match a phoneme in an input audio signal to a corresponding keyword, wherein the foreground model is trained by (i) obtaining a phoneme collection for each of the plurality of different languages, (ii) generating a plurality of triphones by linking phonemes in the phoneme collection corresponding to the language, and (iii) performing Gaussian splitting training on the triphones that are clustered with a decision tree corresponding to the language; and a background model configured to match a phoneme in the input audio signal to a corresponding non-keyword; after training the acoustic model, generate a phone decoder based on the trained acoustic model; obtain a keyword phoneme sequence for a respective keyword in a respective language of the plurality of different languages, wherein the obtaining includes: collecting a set of keyword audio samples for the respective keyword in the respective language; decoding the set of keyword audio samples with the phone decoder to generate a set of phoneme sequence candidates for the respective keyword, each phoneme sequence candidate corresponding to a respective keyword audio sample; and selecting the keyword phoneme sequence for the respective keyword from the set of phoneme sequence candidates by choosing a phoneme of a highest confidence measure from one of the set of phoneme sequence candidates at each location in the corresponding sequence and assembling the chosen phonemes into the keyword phoneme sequence according to their locations in the corresponding sequence; after obtaining the keyword phoneme sequence, detect one or more keywords in the input audio signal with the trained acoustic model, wherein the detecting includes: matching one or more phonemic keyword portions of the input audio signal with one or more phonemes in the keyword phoneme sequence with the foreground model; and filtering out one or more phonemic non-keyword portions of the input audio signal with the background model. 18. The non-transitory computer readable storage medium of claim 16 , wherein the one or more programs comprising instructions, which further cause the device to: collect the plurality of audio samples in the plurality of different languages and labeled data for the plurality of audio samples; obtain a phoneme collection for each of the plurality of different languages; map phonemes from each phoneme collection to phonemes in the IPA so as to generate the IPA phoneme mapping collection; and wherein the acoustic model is trained based on the collected plurality of audio samples in the plurality of different languages, the collected labeled data for the plurality of audio samples, and the generated IPA phoneme mapping collection. | 0.535134 |
19. An automated shopping method for automated management of a process in which a user places an order for at least one provider, a degree of matching between each order-provider pairing is computed, and a score is reported to at least the user and optionally to at least one provider, the automated shopping method comprising: providing (a) at least one processor to receive and process information including at least one of (i) user information from at least one user including information that specifies provider criteria and order information that specifies order criteria for that particular order, (ii) provider information, and (iii) third party information; (b) at least one data storage device that communicates with the at least one processor, that includes at least one database, and that receives and stores the information in the at least one database; and (c) a knowledge base that is stored in a data storage device which may be said at least one data storage device, and that contains information on which to base requests for information by the automated shopping method; receiving information (a) from the user including information that specifies provider criteria and order information that specifies order criteria for that particular order, and (b) from the at least one provider; creating at least one virtual provider with program code within the at least one processor by pairing provider information of a particular provider with order information of a particular order to create an informational pair, and storing the at least one virtual provider within the at least one database; determining a score that reflects a degree of matching for each respective informational pair using a scoring system that resides in program code within the at least one processor, and that compares the provider information of a particular provider and the order information of a particular order within each respective informational pair in at least one step; and tracking each order-provider pairing through multiple steps using a management system that resides in program code within the at least one processor, and that uses sequencing to specify contents of each step of the multiple steps, the contents at least including instructions to at least one of (a) the user regarding the input of user information, (b) the provider regarding the input of provider information, and (c) third parties regarding the input of information. | 19. An automated shopping method for automated management of a process in which a user places an order for at least one provider, a degree of matching between each order-provider pairing is computed, and a score is reported to at least the user and optionally to at least one provider, the automated shopping method comprising: providing (a) at least one processor to receive and process information including at least one of (i) user information from at least one user including information that specifies provider criteria and order information that specifies order criteria for that particular order, (ii) provider information, and (iii) third party information; (b) at least one data storage device that communicates with the at least one processor, that includes at least one database, and that receives and stores the information in the at least one database; and (c) a knowledge base that is stored in a data storage device which may be said at least one data storage device, and that contains information on which to base requests for information by the automated shopping method; receiving information (a) from the user including information that specifies provider criteria and order information that specifies order criteria for that particular order, and (b) from the at least one provider; creating at least one virtual provider with program code within the at least one processor by pairing provider information of a particular provider with order information of a particular order to create an informational pair, and storing the at least one virtual provider within the at least one database; determining a score that reflects a degree of matching for each respective informational pair using a scoring system that resides in program code within the at least one processor, and that compares the provider information of a particular provider and the order information of a particular order within each respective informational pair in at least one step; and tracking each order-provider pairing through multiple steps using a management system that resides in program code within the at least one processor, and that uses sequencing to specify contents of each step of the multiple steps, the contents at least including instructions to at least one of (a) the user regarding the input of user information, (b) the provider regarding the input of provider information, and (c) third parties regarding the input of information. 30. The automated shopping method of claim 19 , wherein tracking further comprises using a device to accept input of the information requested in digital form or as verbal input converted into digital form. | 0.545125 |
17. A system comprising: a display; at least one input device; a communication device; a memory; and a processor, wherein the processor is configured to execute a character string input program for performing operations comprising: receiving one or more input characters supplied via one of the input devices; displaying on the display at least one selectable candidate character string based on the one or more input characters, wherein the displayed candidate character strings include only option character strings obtained from an option character string database; receiving a selection input supplied via one of the input devices for selecting one of the displayed candidate character strings; and supplying the character string selected from the displayed candidate character strings to the communication device, wherein the processor is further configured to supply only character strings selected from displayed candidate character strings to the communication device and to prevent option character strings which are not selected from the displayed candidate character strings from being supplied to the communication device. | 17. A system comprising: a display; at least one input device; a communication device; a memory; and a processor, wherein the processor is configured to execute a character string input program for performing operations comprising: receiving one or more input characters supplied via one of the input devices; displaying on the display at least one selectable candidate character string based on the one or more input characters, wherein the displayed candidate character strings include only option character strings obtained from an option character string database; receiving a selection input supplied via one of the input devices for selecting one of the displayed candidate character strings; and supplying the character string selected from the displayed candidate character strings to the communication device, wherein the processor is further configured to supply only character strings selected from displayed candidate character strings to the communication device and to prevent option character strings which are not selected from the displayed candidate character strings from being supplied to the communication device. 21. The system according to claim 17 , wherein the communication device is configured for wireless communication. | 0.77121 |
30. The computer readable medium of claim 29 , further comprising instructions to: collect feedback relating to the correspondence; and modify the correspondence responsive to the feedback. | 30. The computer readable medium of claim 29 , further comprising instructions to: collect feedback relating to the correspondence; and modify the correspondence responsive to the feedback. 31. The computer readable medium of claim 30 , wherein the feedback is collected from a plurality of end-users. | 0.833567 |
1. A computer-readable non-transitory storage medium configured with data and with instructions that when executed by at least one processor in a cloud computing environment and/or a cloud storage environment causes the processor(s) to perform a process for digital good library comparison, the process comprising: obtaining a first dataset, namely, first electronic organizational data and first electronic history data associated with a first library of digital goods; obtaining a second dataset, namely, second electronic organizational data and second electronic history data associated with a second library of digital goods; automatically comparing at least a portion of the first dataset with at least a portion of the second dataset; reporting at least one of the following results: a shared multiple natural languages presence, a shared genre frequency change, a shared artist frequency change, a shared digital good frequency change, a shared outlier presence, a shared recommendable goods presence; and wherein the process operates in a cloud computing environment and/or a cloud storage environment to perform at least one of the obtaining, comparing, or reporting steps, and the process reports at least one of the following shared outlier results: for both datasets the greatest number of plays in the past D days is in a category C, for predetermined values of D, C; for both datasets the greatest number of plays in the past D days is in a category C, for values of D, C determined at least in part by comparing at least a portion of the first dataset with at least a portion of the second dataset; both datasets have goods in categories C1 and C2 and no goods in category C3, for predetermined values of C1, C2, C3; both datasets have goods in categories C1 and C2 and no goods in category C3, for values of C1, C2, C3 determined at least in part by comparing at least a portion of the first dataset with at least a portion of the second dataset; both datasets have goods in category C1 but no playlist containing any goods in category C1, for a predetermined value of C1; both datasets have goods in category C1 but no playlist containing any goods in category C1, for a value of C1 determined at least in part by comparing at least a portion of the first dataset with at least a portion of the second dataset. | 1. A computer-readable non-transitory storage medium configured with data and with instructions that when executed by at least one processor in a cloud computing environment and/or a cloud storage environment causes the processor(s) to perform a process for digital good library comparison, the process comprising: obtaining a first dataset, namely, first electronic organizational data and first electronic history data associated with a first library of digital goods; obtaining a second dataset, namely, second electronic organizational data and second electronic history data associated with a second library of digital goods; automatically comparing at least a portion of the first dataset with at least a portion of the second dataset; reporting at least one of the following results: a shared multiple natural languages presence, a shared genre frequency change, a shared artist frequency change, a shared digital good frequency change, a shared outlier presence, a shared recommendable goods presence; and wherein the process operates in a cloud computing environment and/or a cloud storage environment to perform at least one of the obtaining, comparing, or reporting steps, and the process reports at least one of the following shared outlier results: for both datasets the greatest number of plays in the past D days is in a category C, for predetermined values of D, C; for both datasets the greatest number of plays in the past D days is in a category C, for values of D, C determined at least in part by comparing at least a portion of the first dataset with at least a portion of the second dataset; both datasets have goods in categories C1 and C2 and no goods in category C3, for predetermined values of C1, C2, C3; both datasets have goods in categories C1 and C2 and no goods in category C3, for values of C1, C2, C3 determined at least in part by comparing at least a portion of the first dataset with at least a portion of the second dataset; both datasets have goods in category C1 but no playlist containing any goods in category C1, for a predetermined value of C1; both datasets have goods in category C1 but no playlist containing any goods in category C1, for a value of C1 determined at least in part by comparing at least a portion of the first dataset with at least a portion of the second dataset. 9. The configured medium of claim 1 , wherein each library has an owner with at least one identity, such as an online identity and an offline identity, and the process further comprises at least one of the following: partially disclosing to each library owner at least one identity of the other library owner; partially disclosing only one library owner's identity(ies); fully disclosing to each library owner at least one identity of the other library owner; fully disclosing only one library owner's identity(ies). | 0.64782 |
23. The method of claim 1 , wherein the target macromolecule is a polypeptide or a nucleic acid. | 23. The method of claim 1 , wherein the target macromolecule is a polypeptide or a nucleic acid. 27. The method of claim 23 , wherein each output model comprises the 3-D spatial positions of H atoms of the target macromolecule. | 0.951887 |
13. A computer program product, the computer program product being embodied in a tangible non-transitory computer readable storage medium and comprising computer instructions for: extracting a subimage from a received image comprising information pertaining to a plurality of numerical characters, wherein the extracted subimage is associated with one of the plurality of numerical characters; and performing recognition based at least in part on a set of topological information associated with the subimage, including: processing the subimage to obtain the set of topological information associated with the subimage, wherein the processing of the subimage includes: obtaining the set of topological information by extracting one or more vertices and one or more edges associated with the subimage; and adding a central point representing a closed ring to the set of topological information; comparing the set of topological information associated with the subimage with a preset set of stored topological information, comprising: comparing an order in which the extracted one or more vertices were detected during a traversal process with an order of vertices of the preset set of stored topological information, the traversal process beginning from a predefined pixel of the subimage and continuing to a next filled in pixel in a predefined order; and determining that in the event that the set of topological information associated with the subimage matches the preset set of stored topological information, the subimage is associated with a recognized numerical character associated with the preset set of stored topological information. | 13. A computer program product, the computer program product being embodied in a tangible non-transitory computer readable storage medium and comprising computer instructions for: extracting a subimage from a received image comprising information pertaining to a plurality of numerical characters, wherein the extracted subimage is associated with one of the plurality of numerical characters; and performing recognition based at least in part on a set of topological information associated with the subimage, including: processing the subimage to obtain the set of topological information associated with the subimage, wherein the processing of the subimage includes: obtaining the set of topological information by extracting one or more vertices and one or more edges associated with the subimage; and adding a central point representing a closed ring to the set of topological information; comparing the set of topological information associated with the subimage with a preset set of stored topological information, comprising: comparing an order in which the extracted one or more vertices were detected during a traversal process with an order of vertices of the preset set of stored topological information, the traversal process beginning from a predefined pixel of the subimage and continuing to a next filled in pixel in a predefined order; and determining that in the event that the set of topological information associated with the subimage matches the preset set of stored topological information, the subimage is associated with a recognized numerical character associated with the preset set of stored topological information. 18. The computer program product of claim 13 , wherein the recognized numerical character is one of the following: 0, 1, 2, 3, 4, 5, 6, 7, 8, or 9. | 0.544421 |
1. A method of categorizing color palettes comprising: associating natural language terms with achromatic entity categories of a set of achromatic entity categories; mining a collection of color palettes which have been previously labeled with comments of reviewers to form a dataset of labeled color palettes; assigning entity categories from the set of achromatic entity categories to a subset of the labeled color palettes in the dataset of color palettes based on matching natural language terms in the labels of the color palettes with the natural language terms associated with the achromatic entity categories, each color palette in the subset consisting of a sequence of from two to one hundred swatches, each swatch in the color palette being of a different color, each color palette in the dataset of color palettes differing from each of the other color palettes in the dataset with respect to at least one of its swatches; extracting color-related features from each of the color palettes; and with a computer processor and based on the assigned entity categories and color related features of the labeled color palettes, training a classifier to categorize a color palette into at least one of the set of achromatic entity categories based on its extracted color-related features. | 1. A method of categorizing color palettes comprising: associating natural language terms with achromatic entity categories of a set of achromatic entity categories; mining a collection of color palettes which have been previously labeled with comments of reviewers to form a dataset of labeled color palettes; assigning entity categories from the set of achromatic entity categories to a subset of the labeled color palettes in the dataset of color palettes based on matching natural language terms in the labels of the color palettes with the natural language terms associated with the achromatic entity categories, each color palette in the subset consisting of a sequence of from two to one hundred swatches, each swatch in the color palette being of a different color, each color palette in the dataset of color palettes differing from each of the other color palettes in the dataset with respect to at least one of its swatches; extracting color-related features from each of the color palettes; and with a computer processor and based on the assigned entity categories and color related features of the labeled color palettes, training a classifier to categorize a color palette into at least one of the set of achromatic entity categories based on its extracted color-related features. 15. A system comprising memory which stores instructions for performing the method of claim 1 , and a processor, in communication with the memory for executing the instructions. | 0.599248 |
1. A method for presenting tags of a tag cloud in a more understandable and visually appealing manner, the method comprising: activating an analysis on tags of said tag cloud in response to detecting a modification by a user to said tag cloud; retrieving said tags of said tag cloud associated with an object, wherein said object comprises one of the following: a webpage, a document, a video, a folder and a multimedia application, wherein said tags of said tag cloud associated with said object are retrieved from a repository via a structured query language (SQL) query; assigning parts of speech to said tags, wherein said parts of speech comprises a verb, a noun, a pronoun, an adjective, an adverb, a preposition, a conjunction and an interjection; generating, by a processor, combination of said tags based on weights assigned to said tags using different linguistic combinations of said parts of speech assigned to said tags, wherein a value of a weight assigned to a tag is based on a type of a part of speech assigned to said tag and frequency of use of said tag to describe said object; determining a layout to display said generated combinations of tags; presenting said generated combination of tags of said tag cloud using said determined layout; modifying a manner in which a combination of said combinations of said tags is displayed in response to feedback regarding relationships between tags of said combination, wherein said feedback comprises at least one of the following: an indication of an inaccurate description, an indication of an inappropriate description and an indication of a not understandable description; determining a second layout to display said combinations of said tags upon said modification of said combination of said combinations of said tags; and presenting said combinations of said tags of said tag cloud using said determined second layout. | 1. A method for presenting tags of a tag cloud in a more understandable and visually appealing manner, the method comprising: activating an analysis on tags of said tag cloud in response to detecting a modification by a user to said tag cloud; retrieving said tags of said tag cloud associated with an object, wherein said object comprises one of the following: a webpage, a document, a video, a folder and a multimedia application, wherein said tags of said tag cloud associated with said object are retrieved from a repository via a structured query language (SQL) query; assigning parts of speech to said tags, wherein said parts of speech comprises a verb, a noun, a pronoun, an adjective, an adverb, a preposition, a conjunction and an interjection; generating, by a processor, combination of said tags based on weights assigned to said tags using different linguistic combinations of said parts of speech assigned to said tags, wherein a value of a weight assigned to a tag is based on a type of a part of speech assigned to said tag and frequency of use of said tag to describe said object; determining a layout to display said generated combinations of tags; presenting said generated combination of tags of said tag cloud using said determined layout; modifying a manner in which a combination of said combinations of said tags is displayed in response to feedback regarding relationships between tags of said combination, wherein said feedback comprises at least one of the following: an indication of an inaccurate description, an indication of an inappropriate description and an indication of a not understandable description; determining a second layout to display said combinations of said tags upon said modification of said combination of said combinations of said tags; and presenting said combinations of said tags of said tag cloud using said determined second layout. 9. The method as recited in claim 1 , wherein said parts of speech are assigned to said tags based on a library of terms stored in said repository, wherein a server performs a look-up of a tag in said library of terms. | 0.52758 |
2. The method of claim 1 , wherein correlating the received search argument to the particular advertisement includes the second search engine selecting the particular advertisement based on the received search argument and user profile data. | 2. The method of claim 1 , wherein correlating the received search argument to the particular advertisement includes the second search engine selecting the particular advertisement based on the received search argument and user profile data. 3. The method of claim 2 , wherein the user profile data includes selections of the user from previous search results. | 0.862538 |
1. A computer-implemented method of providing notifications to a user, the method comprising: receiving, by one or more computing devices, an input from a user indicative of a search query by the user; providing, by the one or more computing devices, data indicative of the search query by the user to a remote computing device; receiving, by the one or more computing devices, a plurality of search results associated with the search query, the plurality of search results including search results that each include a corresponding link to a corresponding website and a short descriptor of information included in the website; and providing for display, by the one or more computing devices, the plurality of search results along with at least one geofencing element that is based at least in part on the plurality of search results, the at least one geofencing element being selectable to establish a geofence around a geographic location associated with at least one search result of the plurality of search results; wherein a selection of the geofencing element causes, based on a subsequent detection of entry into the geofence established by the selection, at least one of the one or more computing devices to provide a notification associated with the geofence. | 1. A computer-implemented method of providing notifications to a user, the method comprising: receiving, by one or more computing devices, an input from a user indicative of a search query by the user; providing, by the one or more computing devices, data indicative of the search query by the user to a remote computing device; receiving, by the one or more computing devices, a plurality of search results associated with the search query, the plurality of search results including search results that each include a corresponding link to a corresponding website and a short descriptor of information included in the website; and providing for display, by the one or more computing devices, the plurality of search results along with at least one geofencing element that is based at least in part on the plurality of search results, the at least one geofencing element being selectable to establish a geofence around a geographic location associated with at least one search result of the plurality of search results; wherein a selection of the geofencing element causes, based on a subsequent detection of entry into the geofence established by the selection, at least one of the one or more computing devices to provide a notification associated with the geofence. 4. The computer-implemented method of claim 1 , further comprising: receiving, by the one or more computing devices, an input from the user indicative of the selection of the geofencing element; providing, by the one or more computing devices, data indicative of the selected geofencing element to the remote computing device; receiving, by the one or more computing devices, data indicative of the geofence to be established around the geographical location associated with the geofencing element; and establishing the geofence around the geographical location associated with the geofencing element based at least in part on the received data indicative of the geofence. | 0.5 |
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