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1. A method implemented in a computer infrastructure having computer executable code tangibly embodied on a non-transitory computer readable storage medium having programming instructions operable to: receive a current waveform of a communication between a plurality of participants; determining if the current waveform is of a human voice based on a frequency band of the current waveform; create a voiceprint from the current waveform if the current waveform is of the human voice; transcribe the current waveform into text; and display a match indication display (MID) comprising the current waveform, one or more library waveforms, and the text with its associated library waveform, wherein a degree of a correlation between the voiceprint and the one or more library waveforms is displayed as a match percentage for each of the one or more library waveforms.
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1. A method implemented in a computer infrastructure having computer executable code tangibly embodied on a non-transitory computer readable storage medium having programming instructions operable to: receive a current waveform of a communication between a plurality of participants; determining if the current waveform is of a human voice based on a frequency band of the current waveform; create a voiceprint from the current waveform if the current waveform is of the human voice; transcribe the current waveform into text; and display a match indication display (MID) comprising the current waveform, one or more library waveforms, and the text with its associated library waveform, wherein a degree of a correlation between the voiceprint and the one or more library waveforms is displayed as a match percentage for each of the one or more library waveforms. 2. The method of claim 1 , wherein the creating the voiceprint from the current waveform comprises: dividing the current waveform into equal lengths of frequency range; determining an average amplitude of the current waveform for each of the equal lengths of frequency range; storing the average amplitude of the current waveform for each of the equal lengths of frequency range as the voiceprint in a storage system; and updating the average amplitude of the current waveform for each of the equal lengths of frequency range.
| 0.505405 |
3. A composition according to claim 2 , wherein the fungus is a mutant strain of Chrysosporium lucknowense Garg 27K.
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3. A composition according to claim 2 , wherein the fungus is a mutant strain of Chrysosporium lucknowense Garg 27K. 47. The composition according to claim 3 , wherein the fungus is a mutant strain of Chrysosporium lucknowense Garg 27K having accession number VKM F-3632D.
| 0.883234 |
13. At least one non-transitory computer-readable medium storing computer-readable instructions that, when executed by one or more computing devices, cause at least one of the one or more computing devices to: generate a set of demographic nouns corresponding to a user based on one or more of: registration information provided by the user or data derived from an analysis of a connection of the user; generate one or more sets of taxonomic nouns corresponding to the user, wherein the one or more sets of taxonomic nouns comprise one or more of: a set of first taxonomic nouns based upon classification information generated by an author of at least one document in a set of documents; a set of second taxonomic nouns based upon one or more user-generated tags characterizing at least a portion of at least one document in the set of documents; a set of third taxonomic based upon one or more search terms utilized by the user to access at least one document in the set of documents; or a set of fourth taxonomic nouns based upon the attributes related to a method of access of at least one document in the set of documents; generate a set of fifth taxonomic nouns corresponding to the user by processing at least one document in the set of documents based upon one or more pattern rules and a dictionary of known terms, wherein the one or more pattern rules specify a method of extracting terms from the at least one document; aggregate at least one of the one or more sets of taxonomic nouns with the set of fifth taxonomic nouns into a composite set of taxonomic nouns corresponding to the user; and generate a value index corresponding to the user based at least in part on a comparison between: a quantity of nouns in the set of demographic nouns corresponding to the user and the composite set of taxonomic nouns corresponding to the user, and one or more quantities of nouns in one or more sets of demographic nouns corresponding to one or more other users and one or more composite sets of taxonomic nouns corresponding to the one or more other users.
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13. At least one non-transitory computer-readable medium storing computer-readable instructions that, when executed by one or more computing devices, cause at least one of the one or more computing devices to: generate a set of demographic nouns corresponding to a user based on one or more of: registration information provided by the user or data derived from an analysis of a connection of the user; generate one or more sets of taxonomic nouns corresponding to the user, wherein the one or more sets of taxonomic nouns comprise one or more of: a set of first taxonomic nouns based upon classification information generated by an author of at least one document in a set of documents; a set of second taxonomic nouns based upon one or more user-generated tags characterizing at least a portion of at least one document in the set of documents; a set of third taxonomic based upon one or more search terms utilized by the user to access at least one document in the set of documents; or a set of fourth taxonomic nouns based upon the attributes related to a method of access of at least one document in the set of documents; generate a set of fifth taxonomic nouns corresponding to the user by processing at least one document in the set of documents based upon one or more pattern rules and a dictionary of known terms, wherein the one or more pattern rules specify a method of extracting terms from the at least one document; aggregate at least one of the one or more sets of taxonomic nouns with the set of fifth taxonomic nouns into a composite set of taxonomic nouns corresponding to the user; and generate a value index corresponding to the user based at least in part on a comparison between: a quantity of nouns in the set of demographic nouns corresponding to the user and the composite set of taxonomic nouns corresponding to the user, and one or more quantities of nouns in one or more sets of demographic nouns corresponding to one or more other users and one or more composite sets of taxonomic nouns corresponding to the one or more other users. 15. The at least one non-transitory computer-readable medium of claim 13 , wherein the one or more user-generated tags characterizing at least a portion of at least one document in the set of documents comprise one or more of: a form of the at least one document, content of the at least one document, or a function of the at least one document.
| 0.810929 |
7. A computer program product, encoded on one or more non-transitory computer storage media, comprising instructions that when executed by one or more computers cause the one or more computers to perform operations comprising: receiving a search query from a user; obtaining a plurality of search results that satisfy the search query, wherein each search result identifies respective document of a plurality of documents; identifying a respective condition for each document of the plurality of documents, wherein each condition comprises one or more features of the user, the search query, and the document; obtaining a ranking model that produces a score for a particular document given a particular condition for the particular document, the score representing a likelihood that the user will select the particular document when identified by a search result provided in response to the search query, the ranking model being trained on training instances that each identify a first document selected by a particular user when the first document was identified in search results provided to the particular user in response to a particular search query; using the ranking model to compute a respective score for each document of the plurality of documents; and ranking the plurality of search results according to the respective computed score for each document of the plurality of documents.
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7. A computer program product, encoded on one or more non-transitory computer storage media, comprising instructions that when executed by one or more computers cause the one or more computers to perform operations comprising: receiving a search query from a user; obtaining a plurality of search results that satisfy the search query, wherein each search result identifies respective document of a plurality of documents; identifying a respective condition for each document of the plurality of documents, wherein each condition comprises one or more features of the user, the search query, and the document; obtaining a ranking model that produces a score for a particular document given a particular condition for the particular document, the score representing a likelihood that the user will select the particular document when identified by a search result provided in response to the search query, the ranking model being trained on training instances that each identify a first document selected by a particular user when the first document was identified in search results provided to the particular user in response to a particular search query; using the ranking model to compute a respective score for each document of the plurality of documents; and ranking the plurality of search results according to the respective computed score for each document of the plurality of documents. 12. The computer program product of claim 7 , wherein each training instance comprises data representing a number of documents ranked above the selected first document in the search results provided to the particular user in response to the particular search query.
| 0.55122 |
5. A system comprising: a classifier implemented in one or more computers, comprising: an embedding function layer configured to receive an input comprising an input word and map the input word into a numeric representation in a high-dimensional space, and a plurality of classifiers, wherein each of the classifiers corresponds to a respective position surrounding the input word in a sequence of words, and wherein each of the plurality of classifiers is configured to: process the numeric representation of the input word to generate a respective word score for each word in a pre-determined set of words, wherein each of the respective word scores represents a predicted likelihood that the corresponding word will be found in the corresponding position relative to the input word; and instructions to process each word in a vocabulary of words using the embedding function layer to obtain a respective numeric representation of each word in the vocabulary in the high-dimensional space and to associate each word in the vocabulary with the respective numeric representation of the word in the high-dimensional space.
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5. A system comprising: a classifier implemented in one or more computers, comprising: an embedding function layer configured to receive an input comprising an input word and map the input word into a numeric representation in a high-dimensional space, and a plurality of classifiers, wherein each of the classifiers corresponds to a respective position surrounding the input word in a sequence of words, and wherein each of the plurality of classifiers is configured to: process the numeric representation of the input word to generate a respective word score for each word in a pre-determined set of words, wherein each of the respective word scores represents a predicted likelihood that the corresponding word will be found in the corresponding position relative to the input word; and instructions to process each word in a vocabulary of words using the embedding function layer to obtain a respective numeric representation of each word in the vocabulary in the high-dimensional space and to associate each word in the vocabulary with the respective numeric representation of the word in the high-dimensional space. 7. The system of claim 5 , wherein positions of representations in the high-dimensional space reflect semantic similarities, syntactic similarities, or both, between words represented by the representations.
| 0.743207 |
1. A method performed by one or more server devices, the method comprising: receiving, by one or more processors associated with the one or more server devices, a plurality of search query/search result document pairings, where each search query/search result document pairing, of the plurality of search query/search result document pairings, includes a search query and a search result document responsive to the search query, and where the search result documents, of the search query/search result document pairings, are associated with business listings that are relevant to the search queries of the search query/search result document pairings; generating, by one or more processors associated with the one or more server devices, for each of the search query/search result document pairings, objective data derived from the search query/search result document pairings, where the objective data, for a particular one of the search query/search result document pairings that comprises a particular search query and a particular search document, includes: first data indicating whether a term in the particular search query matches a prefix portion of a name of a business, of a particular business listing of the business listings, the prefix portion including less than an entirety of the name of the business, and second data indicating whether the particular search query exactly matches the name of the business; obtaining, by one or more processors associated with the one or more server devices, information associated with a relevance evaluation for each of the search query/search result document pairings from a human evaluator, the relevance evaluation indicating a relevance of a search query to a corresponding search result document; and training, by one or more processors associated with the one or more server devices, an evaluation model, based on the obtained information associated with relevance evaluations and the objective data, to predict a human relevance evaluation that is used to rank another search query/search result document pairing.
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1. A method performed by one or more server devices, the method comprising: receiving, by one or more processors associated with the one or more server devices, a plurality of search query/search result document pairings, where each search query/search result document pairing, of the plurality of search query/search result document pairings, includes a search query and a search result document responsive to the search query, and where the search result documents, of the search query/search result document pairings, are associated with business listings that are relevant to the search queries of the search query/search result document pairings; generating, by one or more processors associated with the one or more server devices, for each of the search query/search result document pairings, objective data derived from the search query/search result document pairings, where the objective data, for a particular one of the search query/search result document pairings that comprises a particular search query and a particular search document, includes: first data indicating whether a term in the particular search query matches a prefix portion of a name of a business, of a particular business listing of the business listings, the prefix portion including less than an entirety of the name of the business, and second data indicating whether the particular search query exactly matches the name of the business; obtaining, by one or more processors associated with the one or more server devices, information associated with a relevance evaluation for each of the search query/search result document pairings from a human evaluator, the relevance evaluation indicating a relevance of a search query to a corresponding search result document; and training, by one or more processors associated with the one or more server devices, an evaluation model, based on the obtained information associated with relevance evaluations and the objective data, to predict a human relevance evaluation that is used to rank another search query/search result document pairing. 7. The method of claim 1 , where the objective data further includes: data obtained from historical logs of search activity.
| 0.602627 |
18. A server that sends a message expressing a statement on behalf of a user, the server comprising: a processor; and a memory storing: an expression set comprising at least one expression authored by the user; and instructions that, when executed by the processor, provide: an expression style identifier that examines the expression set to identify a phrase that appears in at least one prior expression previously authored by the user and that is relevant to the statement; and a message composer that: composes a message expressing the statement in an expression style of the user by: selecting a message template associated with the expression style of the user, wherein the message template comprises at least one slot for insertion of content to adapt the message template to the statement; and inserting the phrase previously authored by the user into the at least one message slot of the message template; presents the message to the user for confirmation; and responsive to receiving a confirmation of the message from the user, transmits the message to the recipient.
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18. A server that sends a message expressing a statement on behalf of a user, the server comprising: a processor; and a memory storing: an expression set comprising at least one expression authored by the user; and instructions that, when executed by the processor, provide: an expression style identifier that examines the expression set to identify a phrase that appears in at least one prior expression previously authored by the user and that is relevant to the statement; and a message composer that: composes a message expressing the statement in an expression style of the user by: selecting a message template associated with the expression style of the user, wherein the message template comprises at least one slot for insertion of content to adapt the message template to the statement; and inserting the phrase previously authored by the user into the at least one message slot of the message template; presents the message to the user for confirmation; and responsive to receiving a confirmation of the message from the user, transmits the message to the recipient. 19. The server of claim 18 , wherein: the statement is associated with a content item; and the message composer composes the message expressing the statement by: identifying a selected content item that is associated with the statement; and composing the message including the selected content item in the message.
| 0.541702 |
22. A computerized method for the retrieval of classified documents comprising: initiating a connection between a client software application in a client computer and a server computer; and causing at least one request by said client software application in said client computer, wherein said request initiates a method comprising: retrieving a document from a document collection, said document collection comprising at least one document(s), said document(s) having been classified according to a predefined classification scheme, said predefined classification scheme comprising classification codes, said classification codes comprising title(s) and definition(s), said document(s) further comprising at least one retrieval code, wherein said retrieval code corresponds with at least one of said classification code title(s) or classification code definition(s); retrieving from a database at least one keyword derived from at least one of said classification code title(s) or classification code definition(s); inserting said keyword into said document(s) to create a tagged document; and transmitting said tagged document to said search engine.
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22. A computerized method for the retrieval of classified documents comprising: initiating a connection between a client software application in a client computer and a server computer; and causing at least one request by said client software application in said client computer, wherein said request initiates a method comprising: retrieving a document from a document collection, said document collection comprising at least one document(s), said document(s) having been classified according to a predefined classification scheme, said predefined classification scheme comprising classification codes, said classification codes comprising title(s) and definition(s), said document(s) further comprising at least one retrieval code, wherein said retrieval code corresponds with at least one of said classification code title(s) or classification code definition(s); retrieving from a database at least one keyword derived from at least one of said classification code title(s) or classification code definition(s); inserting said keyword into said document(s) to create a tagged document; and transmitting said tagged document to said search engine. 25. The computerized method for the indexing and retrieval of classified documents of claim 22 , wherein the document collection contains at least one patent document.
| 0.549383 |
13. The method of claim 12, wherein the each processor station is assigned a usage number for the each grammar type, wherein the usage number is a measure of time the each processor is required to process its associated grammar type.
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13. The method of claim 12, wherein the each processor station is assigned a usage number for the each grammar type, wherein the usage number is a measure of time the each processor is required to process its associated grammar type. 14. The method of claim 13, wherein the step of measuring loads of the each processor comprises the step of summing all the usage numbers assigned to the each processor.
| 0.867281 |
1. A method of natural language training, the method comprising the steps of: selecting a plurality of texts in only a single predetermined natural language; automatically analyzing the plurality of texts to compile a list of words and phrases sorted by one or more characteristics; establishing from the list one or more groups of core words of the same natural language; and compiling teaching materials in the same natural language that comprise at least a predetermined percentage of words that are within one or more of the groups.
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1. A method of natural language training, the method comprising the steps of: selecting a plurality of texts in only a single predetermined natural language; automatically analyzing the plurality of texts to compile a list of words and phrases sorted by one or more characteristics; establishing from the list one or more groups of core words of the same natural language; and compiling teaching materials in the same natural language that comprise at least a predetermined percentage of words that are within one or more of the groups. 8. The method of claim 1 wherein the compiling step comprises providing to a student a time period's materials which collectively comprise a percentage of words within one or more of the groups above a predetermined percentage.
| 0.511173 |
12. An apparatus for handling contact requests among a plurality of dissimilar automatic contact distributors comprising: means for providing a plurality of universal workflow scripts at a common location wherein universal workflow scripts comprise a set of call routing instructions for a particular type of contact; means for translating each of the plurality of universal workflow scripts into a respective native scripting language of each of the plurality of dissimilar automatic contact distributors to provide respective equivalent scripts of substantially equivalent functionality within each respective dissimilar automatic contact distributor; means for tendering a contact request in response to a contact to a selected set of the plurality of dissimilar automatic contact distributors based upon processing the contact request in accordance with a selected one of the respective equivalent scripts selected based upon a classification of the contact; means for selecting an automatic contact distributor of the selected set of the plurality of dissimilar automatic contact distributors to handle the contact based upon a response to the tendered contact request from at least some of the plurality of dissimilar automatic contact distributors; and means for transferring the contact to the selected automatic contact distributor.
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12. An apparatus for handling contact requests among a plurality of dissimilar automatic contact distributors comprising: means for providing a plurality of universal workflow scripts at a common location wherein universal workflow scripts comprise a set of call routing instructions for a particular type of contact; means for translating each of the plurality of universal workflow scripts into a respective native scripting language of each of the plurality of dissimilar automatic contact distributors to provide respective equivalent scripts of substantially equivalent functionality within each respective dissimilar automatic contact distributor; means for tendering a contact request in response to a contact to a selected set of the plurality of dissimilar automatic contact distributors based upon processing the contact request in accordance with a selected one of the respective equivalent scripts selected based upon a classification of the contact; means for selecting an automatic contact distributor of the selected set of the plurality of dissimilar automatic contact distributors to handle the contact based upon a response to the tendered contact request from at least some of the plurality of dissimilar automatic contact distributors; and means for transferring the contact to the selected automatic contact distributor. 17. The apparatus for handling contact requests as in claim 12 further comprising a contact broker for receiving the contact from a public communication network.
| 0.531707 |
3. A system for containment of usage of a language interface, comprising: a processor; a memory having stored thereon: a unique client program generated based on a standard client program, wherein the unique client program is configured to issue a first service request expressed in a second grammar type directed to a second linguistic interface configured to be invoked by requests that conform to the second grammar type; and a first linguistic interface of a service implementation configured to receive a second service request from an interceptor, the second service request expressed in a first grammar type directed to the first linguistic interface, the service implementation including a plurality of directives executed by an operating system of a local computer, wherein the first linguistic interface is configured to be invoked by requests that conform to the first grammar type that is different from the second grammar type; wherein the interceptor (a) captures the first service request from the unique client program and (b) transforms the first service request to obtain the second service request, and wherein the second service request is subsequently directed to the first linguistic interface after the translating to interact with the service implementation, the first linguistic interface distinct from the second linguistic interface, and the second service request equivalent to the first service request.
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3. A system for containment of usage of a language interface, comprising: a processor; a memory having stored thereon: a unique client program generated based on a standard client program, wherein the unique client program is configured to issue a first service request expressed in a second grammar type directed to a second linguistic interface configured to be invoked by requests that conform to the second grammar type; and a first linguistic interface of a service implementation configured to receive a second service request from an interceptor, the second service request expressed in a first grammar type directed to the first linguistic interface, the service implementation including a plurality of directives executed by an operating system of a local computer, wherein the first linguistic interface is configured to be invoked by requests that conform to the first grammar type that is different from the second grammar type; wherein the interceptor (a) captures the first service request from the unique client program and (b) transforms the first service request to obtain the second service request, and wherein the second service request is subsequently directed to the first linguistic interface after the translating to interact with the service implementation, the first linguistic interface distinct from the second linguistic interface, and the second service request equivalent to the first service request. 4. The system of claim 3 , wherein the service implementation, the interceptor and the unique client program reside on the same host.
| 0.612819 |
2. The computer-implemented method of claim 1 , wherein analyzing content of textual information comprises: mapping a plurality of words in the content to a plurality of ontology categories; mapping the plurality of ontology categories to a plurality of question headings; identifying any subjects and direct objects in the content; identifying verb phrases including at least one main verb, and identifying participial and prepositional phrases corresponding to the verb phrases identified; and mapping the participial and prepositional phrases to a corresponding ontology category of the plurality of ontology categories.
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2. The computer-implemented method of claim 1 , wherein analyzing content of textual information comprises: mapping a plurality of words in the content to a plurality of ontology categories; mapping the plurality of ontology categories to a plurality of question headings; identifying any subjects and direct objects in the content; identifying verb phrases including at least one main verb, and identifying participial and prepositional phrases corresponding to the verb phrases identified; and mapping the participial and prepositional phrases to a corresponding ontology category of the plurality of ontology categories. 8. The computer-implemented method of claim 2 , further comprising storing the verb phrases as functions with an argument of an associated ontology category of the plurality of ontology categories.
| 0.81676 |
27. A color management apparatus for building a color transformation workflow for transforming source-side color image data into corresponding destination-side color image data, the color management apparatus comprising: a computer-readable memory which stores computer-executable process steps, a module library, a profile library and a rule library, and a processor constructed to execute the computer-executable process steps stored in the memory; wherein the module library includes plural module entries each corresponding to a respective function module which implements color processing functionality, wherein each module entry comprises at least a module locator specifying a location for the function module, wherein for at least some of the module entries of the module library, the module entry further comprises a profile interface definition which specifies an interface for supply of parameters which characterize the function module, wherein the profile library includes plural profile entries each corresponding to a respective source of parameters that characterize a function module, wherein each profile entry comprises at least a profile locator specifying a location for the source of parameters, and a profile interface definition which specifies an interface for supply of the parameters to the function module characterized thereby, wherein the rule library includes entries for plural external rules and entries for plural internal rules, wherein each such external rule is associated with function modules located by module entries in the module library, and wherein the external rules and the internal rules characterize color transformation workflows of the color management module, and wherein the process steps stored in the memory cause the processor to convert source-side color image data into corresponding destination-side color image data, and include computer-executable process steps to: receive factual input including factual input derived from the source-side color image data; determine a sequence of function modules and sources of parameters from the module library and profile library, respectively, by using the factual input from the interface and the plural internal and external rules in the rule library; and build the color transformation workflow from the determined sequence of function modules and sources of parameters.
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27. A color management apparatus for building a color transformation workflow for transforming source-side color image data into corresponding destination-side color image data, the color management apparatus comprising: a computer-readable memory which stores computer-executable process steps, a module library, a profile library and a rule library, and a processor constructed to execute the computer-executable process steps stored in the memory; wherein the module library includes plural module entries each corresponding to a respective function module which implements color processing functionality, wherein each module entry comprises at least a module locator specifying a location for the function module, wherein for at least some of the module entries of the module library, the module entry further comprises a profile interface definition which specifies an interface for supply of parameters which characterize the function module, wherein the profile library includes plural profile entries each corresponding to a respective source of parameters that characterize a function module, wherein each profile entry comprises at least a profile locator specifying a location for the source of parameters, and a profile interface definition which specifies an interface for supply of the parameters to the function module characterized thereby, wherein the rule library includes entries for plural external rules and entries for plural internal rules, wherein each such external rule is associated with function modules located by module entries in the module library, and wherein the external rules and the internal rules characterize color transformation workflows of the color management module, and wherein the process steps stored in the memory cause the processor to convert source-side color image data into corresponding destination-side color image data, and include computer-executable process steps to: receive factual input including factual input derived from the source-side color image data; determine a sequence of function modules and sources of parameters from the module library and profile library, respectively, by using the factual input from the interface and the plural internal and external rules in the rule library; and build the color transformation workflow from the determined sequence of function modules and sources of parameters. 31. A color management apparatus according to claim 27 , wherein each external rule specifies a rule condition that is used to determine whether the function module should be used, and a rule process that is executed when the rule condition is satisfied.
| 0.539382 |
24. One or more computer-readable non-transitory storage media containing instructions which, when executed by one or more processors disposed in an electronic device, implement a method for performing automated filings to various ones of web portals that are configured to accept filings electronically, the method comprising the steps of: receiving parameters through a user interface (UI) from a user, the parameters providing definition for a filing; acquiring data for the filing from a data source; generating the filing from the acquired data so that the filing meets the filing parameters; navigating to a specific web portal to which submission of the filing is appropriate; executing one or more workflow routines for performing a submission of the filing to the web portal; polling a docket and executing decision-making to identify associated filings with prior docketed events or other registered events or data from the polled docket for inclusion in the filing, the polling further comprising mining docket data to locate CM/ECF (Case Management/Electronic Case Filing) events that satisfy applicable requirements for cross-references for the identified associated filings, the cross-references including one of either a prior docket entry for the filing or an adversary case filing; monitoring errors as they occur during the submission; and modifying the one or more workflow routines or rerunning the workflow routines or aborting the filing in response to the monitored errors.
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24. One or more computer-readable non-transitory storage media containing instructions which, when executed by one or more processors disposed in an electronic device, implement a method for performing automated filings to various ones of web portals that are configured to accept filings electronically, the method comprising the steps of: receiving parameters through a user interface (UI) from a user, the parameters providing definition for a filing; acquiring data for the filing from a data source; generating the filing from the acquired data so that the filing meets the filing parameters; navigating to a specific web portal to which submission of the filing is appropriate; executing one or more workflow routines for performing a submission of the filing to the web portal; polling a docket and executing decision-making to identify associated filings with prior docketed events or other registered events or data from the polled docket for inclusion in the filing, the polling further comprising mining docket data to locate CM/ECF (Case Management/Electronic Case Filing) events that satisfy applicable requirements for cross-references for the identified associated filings, the cross-references including one of either a prior docket entry for the filing or an adversary case filing; monitoring errors as they occur during the submission; and modifying the one or more workflow routines or rerunning the workflow routines or aborting the filing in response to the monitored errors. 27. The one or more computer-readable non-transitory storage media of claim 24 in which the steps of acquiring, generating, navigating, and executing are performed automatically without intervention from the user.
| 0.629839 |
1. A computer-implemented method of allowing user-selected anonymous and pseudonymous access for a user to a relying party (RP), mediated by an identity provider (IdP), comprising: registering with an IdP to establish a first pseudonym; upon successful proof of possession of the first pseudonym to the IdP, receiving a first representation of an access token from the IdP for accessing the RP; transforming, by a processor, the first representation of the access token to obtain a second representation of the access token, the second representation of the access token being a valid access token and is unlinkable to the first representation of the access token by the IdP; receiving a request from the user to access the RP; determining whether the request is for accessing the RP anonymously or pseudonymously; if the request is for anonymous access, providing the second representation of the access token to the RP anonymously; and gaining access to the RP upon verification of the second representation of the access token, the anonymous access being unlinkable to any previous and any future access at the RP, and unlinkable to the IdP's interaction with any particular user; if the request is for pseudonymous access, providing to the RP the second representation of the access token and proof of possession of a second pseudonym that is previously registered with the RP; and gaining access to the RP upon successful verification of the second representation of the access token and proof of possession of the second pseudonym, wherein the pseudonymous access is linkable to the second pseudonym, unlinkable to the IdP's interaction with any particular user, and unlinkable to any past and future access to the RP that does not employ the second pseudonym.
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1. A computer-implemented method of allowing user-selected anonymous and pseudonymous access for a user to a relying party (RP), mediated by an identity provider (IdP), comprising: registering with an IdP to establish a first pseudonym; upon successful proof of possession of the first pseudonym to the IdP, receiving a first representation of an access token from the IdP for accessing the RP; transforming, by a processor, the first representation of the access token to obtain a second representation of the access token, the second representation of the access token being a valid access token and is unlinkable to the first representation of the access token by the IdP; receiving a request from the user to access the RP; determining whether the request is for accessing the RP anonymously or pseudonymously; if the request is for anonymous access, providing the second representation of the access token to the RP anonymously; and gaining access to the RP upon verification of the second representation of the access token, the anonymous access being unlinkable to any previous and any future access at the RP, and unlinkable to the IdP's interaction with any particular user; if the request is for pseudonymous access, providing to the RP the second representation of the access token and proof of possession of a second pseudonym that is previously registered with the RP; and gaining access to the RP upon successful verification of the second representation of the access token and proof of possession of the second pseudonym, wherein the pseudonymous access is linkable to the second pseudonym, unlinkable to the IdP's interaction with any particular user, and unlinkable to any past and future access to the RP that does not employ the second pseudonym. 15. The method of claim 1 , further comprising: sharing each component of a secret key with a distinct trusted authority among a plurality of trusted authorities, wherein the first representation of the access token and the second representation of the access token is linkable to the user when a quorum of the trusted authorities in possession of the each component collude to reveal the secret employed by the user.
| 0.682784 |
12. An organization system for cross-referencing data within a searchable database, wherein a directory tree structure is stored on a memory device and includes nodes and branches comprising links between the nodes, the directory tree structure including a designated category for each node, the organization system comprising: means for generating at least two data pointers corresponding to a specific node, wherein a first data pointer of the at least two data pointers points from the specific node to a first item of data within the searchable database via a first navigation path through the directory tree structure, wherein a second data pointer of the at least two data pointers points from the specific node to a second item of data within the searchable database via a second navigation path through the directory tree structure, and wherein the first and second items of data are related to the designated category of the specific node; and means for generating at least one node pointer, wherein the at least one node pointer points from a first node located in the first navigation path to a second node located in the second navigation path, wherein the first navigation path is different from the second navigation path, wherein the first node and the second node are each different from the specific node; wherein, at each node within the directory tree structure, the searchable database is searchable by selecting any data pointers or node pointers corresponding to the node or by performing one or more of a keyword search, a hierarchical search, a dichotomous key search, and a parametric search.
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12. An organization system for cross-referencing data within a searchable database, wherein a directory tree structure is stored on a memory device and includes nodes and branches comprising links between the nodes, the directory tree structure including a designated category for each node, the organization system comprising: means for generating at least two data pointers corresponding to a specific node, wherein a first data pointer of the at least two data pointers points from the specific node to a first item of data within the searchable database via a first navigation path through the directory tree structure, wherein a second data pointer of the at least two data pointers points from the specific node to a second item of data within the searchable database via a second navigation path through the directory tree structure, and wherein the first and second items of data are related to the designated category of the specific node; and means for generating at least one node pointer, wherein the at least one node pointer points from a first node located in the first navigation path to a second node located in the second navigation path, wherein the first navigation path is different from the second navigation path, wherein the first node and the second node are each different from the specific node; wherein, at each node within the directory tree structure, the searchable database is searchable by selecting any data pointers or node pointers corresponding to the node or by performing one or more of a keyword search, a hierarchical search, a dichotomous key search, and a parametric search. 15. The organization system as claimed in claim 12 , further comprising at least one of: means for adding a node to the directory tree structure; means for editing a node within the directory tree structure; and means for deleting a node form the directory tree structure.
| 0.551327 |
1. A method of indexing documents in websites, the method comprising: on a server system having one or more processors and memory storing programs to be executed by the one or more processors: storing, for each website of a multiplicity of websites, a corresponding current crawl rate limit; comparing a maximum crawl rate for a respective website over a defined period of time with the current crawl rate limit for crawling the respective website to determine if the current crawl rate limit is a limiting factor in crawling the respective website; performing a website crawling management function in accordance with the determination of whether the current crawl rate limit is the limiting factor in crawling the respective website; and providing a crawl rate control mechanism to a respective owner of the respective website, wherein the crawl rate control mechanism enables selection of a new crawl rate limit corresponding to the respective website by the respective owner.
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1. A method of indexing documents in websites, the method comprising: on a server system having one or more processors and memory storing programs to be executed by the one or more processors: storing, for each website of a multiplicity of websites, a corresponding current crawl rate limit; comparing a maximum crawl rate for a respective website over a defined period of time with the current crawl rate limit for crawling the respective website to determine if the current crawl rate limit is a limiting factor in crawling the respective website; performing a website crawling management function in accordance with the determination of whether the current crawl rate limit is the limiting factor in crawling the respective website; and providing a crawl rate control mechanism to a respective owner of the respective website, wherein the crawl rate control mechanism enables selection of a new crawl rate limit corresponding to the respective website by the respective owner. 8. The method of claim 1 , further comprising determining a number of bytes downloaded from the respective website during one or more crawl sessions and storing corresponding crawl data.
| 0.608783 |
4. The method of claim 3 , wherein the data and the ecology information comprise capabilities and configuration data for each of the plurality of target devices.
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4. The method of claim 3 , wherein the data and the ecology information comprise capabilities and configuration data for each of the plurality of target devices. 5. The method of claim 4 , wherein the capabilities and the configuration data comprise at least one of: device vendor identifiers, device type and model information, hardware maintenance level, device operating software, device software level, required bandwidth, protocols employed, nodal connectivity information, security requirements, management techniques, and networking properties.
| 0.771692 |
12. A method of informing a user that sufficient data has been scanned from a document to identify the document, the method comprising: scanning the document, via a portable device, to acquire a scanned image; executing program instructions, stored in memory of the portable device, to detect user-readable words within the scanned image and to count a number of words the portable device detected within the scanned image; comparing the number of words the portable device detected within the scanned image to a threshold number for identifying a document; and indicating, via a user interface of the portable device, that a sufficient number of user-readable words have been detected within the scanned image to identify the document.
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12. A method of informing a user that sufficient data has been scanned from a document to identify the document, the method comprising: scanning the document, via a portable device, to acquire a scanned image; executing program instructions, stored in memory of the portable device, to detect user-readable words within the scanned image and to count a number of words the portable device detected within the scanned image; comparing the number of words the portable device detected within the scanned image to a threshold number for identifying a document; and indicating, via a user interface of the portable device, that a sufficient number of user-readable words have been detected within the scanned image to identify the document. 16. The method of claim 12 , wherein the words in the count of the number of words the portable device detected within the scanned image only include words that comprise more than three characters.
| 0.616103 |
13. The computer-implemented method of claim 8 , wherein modifying output of the sequential content comprises at least one of: outputting the sequential content at a first rate when the distance between the input position and the position indicated by the output indicator satisfies a first threshold value for a first predetermined length of time; outputting the sequential content at a second rate when the distance between the input position and the position indicated by the output indicator satisfies a second threshold value for a second predetermined length of time, wherein the second rate is faster than the first rate; or outputting the sequential content at a third rate when the distance between the input position and the position indicated by the output indicator satisfies a third threshold value for a third predetermined length of time, wherein the third rate is faster than the second rate.
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13. The computer-implemented method of claim 8 , wherein modifying output of the sequential content comprises at least one of: outputting the sequential content at a first rate when the distance between the input position and the position indicated by the output indicator satisfies a first threshold value for a first predetermined length of time; outputting the sequential content at a second rate when the distance between the input position and the position indicated by the output indicator satisfies a second threshold value for a second predetermined length of time, wherein the second rate is faster than the first rate; or outputting the sequential content at a third rate when the distance between the input position and the position indicated by the output indicator satisfies a third threshold value for a third predetermined length of time, wherein the third rate is faster than the second rate. 14. The system of claim 13 , wherein the first rate corresponds to at least one of a rate at which the sequential content was recorded, a rate determined by a user of the system, or a rate determined by a provider of the sequential content.
| 0.694893 |
28. The computer-implemented method of claim 21 , comprising: receiving, at the coordinating device, an indication of a specified destination device to perform at least a third subtask, wherein the specified task comprises the third subtask and the destination device is to store data generated by performance of the specified task; retrieving from the specified destination device an indication of a destination processing environment currently available within at least the specified destination device in response to receiving the indication of the specified destination device, wherein the indication of the destination processing environment comprises indications of an identity and version level of a database routine of the specified destination device; determining a second set of one or more languages able to be interpreted by the database routine of the specified destination device based on the identity and version level of the database routine of the specified destination device; determining whether to perform the first and second subtasks sequentially or at least partly in parallel based on at least one aspect of the source processing environment and at least one aspect of the destination processing environment; selecting a language of the second set of languages in which to generate instructions to perform the third subtask based on the destination processing environment; generating the instructions to perform the third subtask; and transmitting second task instructions comprising the instructions generated to perform at least the third subtask to the specified destination device.
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28. The computer-implemented method of claim 21 , comprising: receiving, at the coordinating device, an indication of a specified destination device to perform at least a third subtask, wherein the specified task comprises the third subtask and the destination device is to store data generated by performance of the specified task; retrieving from the specified destination device an indication of a destination processing environment currently available within at least the specified destination device in response to receiving the indication of the specified destination device, wherein the indication of the destination processing environment comprises indications of an identity and version level of a database routine of the specified destination device; determining a second set of one or more languages able to be interpreted by the database routine of the specified destination device based on the identity and version level of the database routine of the specified destination device; determining whether to perform the first and second subtasks sequentially or at least partly in parallel based on at least one aspect of the source processing environment and at least one aspect of the destination processing environment; selecting a language of the second set of languages in which to generate instructions to perform the third subtask based on the destination processing environment; generating the instructions to perform the third subtask; and transmitting second task instructions comprising the instructions generated to perform at least the third subtask to the specified destination device. 29. The computer-implemented method of claim 28 , the method comprising determining the second set of languages based additionally on an identity and a version level of an add-on routine that augments the second set of languages able to be interpreted by the database routine of the specified destination device.
| 0.763725 |
11. A computer-implemented method comprised of a series of instructions that cause a computer to perform a process for gathering data related to a plurality of academic users and a process for determining a reputation ranking for an academic user, the method including the steps of: for each user, determining whether the user is an academic user or a non-academic user, creating an academic user profile for each of the academic users from attribute information gathered from a user profile prompt displayed on user computers associated with the academic users, allowing the academic users to upload academic articles, enabling the academic user profiles to be viewed by both other academic users and non-academic users, allowing each of the academic users to comment on the academic articles uploaded by other academic users while restricting the non-academic users from commenting on the articles, enabling email communications between the academic users while restricting the non-academic users from emailing the academic users, enabling the academic user profile of each academic user to be selected for ranking by other academic users and enabling the other academic users to provide rank selections for the academic user profile according to at least one of research quality, credentials, research articles, and user activity of the academic user associated with the academic user profile, assigning each of the rank selections a ranking weight based upon at least one of academic credentials or publication volume of the respective selecting academic user and multiplying the rank selection by the ranking weight to create a weighted rank selection, and determining reputation rankings for the academic user profiles from the weighted rank selections.
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11. A computer-implemented method comprised of a series of instructions that cause a computer to perform a process for gathering data related to a plurality of academic users and a process for determining a reputation ranking for an academic user, the method including the steps of: for each user, determining whether the user is an academic user or a non-academic user, creating an academic user profile for each of the academic users from attribute information gathered from a user profile prompt displayed on user computers associated with the academic users, allowing the academic users to upload academic articles, enabling the academic user profiles to be viewed by both other academic users and non-academic users, allowing each of the academic users to comment on the academic articles uploaded by other academic users while restricting the non-academic users from commenting on the articles, enabling email communications between the academic users while restricting the non-academic users from emailing the academic users, enabling the academic user profile of each academic user to be selected for ranking by other academic users and enabling the other academic users to provide rank selections for the academic user profile according to at least one of research quality, credentials, research articles, and user activity of the academic user associated with the academic user profile, assigning each of the rank selections a ranking weight based upon at least one of academic credentials or publication volume of the respective selecting academic user and multiplying the rank selection by the ranking weight to create a weighted rank selection, and determining reputation rankings for the academic user profiles from the weighted rank selections. 13. The computer-implemented method of claim 11 , further including the step of creating a user profile search prompt, the user profile search prompt being accessible to academic users and non-academic users, wherein non-academic users are restricted from creating user profiles.
| 0.771987 |
1. A computer program product for performing application search, the computer program product comprising a non-transitory computer-readable storage medium storing instructions that when executed cause at least one processor to perform steps comprising: receiving a search query including one or more search terms from a computing device; querying an entity index with at least one of the one or more search terms to identify one or more entities from a plurality of entities based on the one or more search terms included in the search query, the entity index indexing a plurality of entity records, each entity record respectively corresponding to a known entity and indicating an entity type of the entity; identifying a set of third-party applications based on the one or more search terms included in the search query, wherein each third-party application in the set of third-party applications is identified based on matches between one or more of the search terms and information conveyed in an application record corresponding to the third-party application; for each third-party application in the set of third party applications: determining a number of entities supported by the third-party application based on the respective entity types of the identified entities and a list of supported entity types in the application record of the third-party application; determining an entity match value of the third-party application with respect to the search query based on the number of entities supported by the third-party application; determining a result score of the third-party application based in part on the entity match value of the third party application; ranking the identified set of third-party applications based at least in part on the result scores thereof; generating search results based on the ranked set of third-party applications; and providing the search results to the computing device.
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1. A computer program product for performing application search, the computer program product comprising a non-transitory computer-readable storage medium storing instructions that when executed cause at least one processor to perform steps comprising: receiving a search query including one or more search terms from a computing device; querying an entity index with at least one of the one or more search terms to identify one or more entities from a plurality of entities based on the one or more search terms included in the search query, the entity index indexing a plurality of entity records, each entity record respectively corresponding to a known entity and indicating an entity type of the entity; identifying a set of third-party applications based on the one or more search terms included in the search query, wherein each third-party application in the set of third-party applications is identified based on matches between one or more of the search terms and information conveyed in an application record corresponding to the third-party application; for each third-party application in the set of third party applications: determining a number of entities supported by the third-party application based on the respective entity types of the identified entities and a list of supported entity types in the application record of the third-party application; determining an entity match value of the third-party application with respect to the search query based on the number of entities supported by the third-party application; determining a result score of the third-party application based in part on the entity match value of the third party application; ranking the identified set of third-party applications based at least in part on the result scores thereof; generating search results based on the ranked set of third-party applications; and providing the search results to the computing device. 5. The computer program product of claim 1 , wherein the instructions for identifying the one or more entities comprise: applying a parsing function to the one or more search terms; and identifying an entity based on the third-party application of the parsing function to the one or more search terms.
| 0.634264 |
17. The method of claim 11 , wherein the vertical position of the portion of text and the spacer element is defined by a top margin.
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17. The method of claim 11 , wherein the vertical position of the portion of text and the spacer element is defined by a top margin. 18. The method of claim 17 , wherein the offset is a negative value applied to the top margin.
| 0.953185 |
23. The method of claim 20 , further comprising distributing a plurality of groups of personalized offers from multiple sources to the consumers using multiple channel interfaces.
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23. The method of claim 20 , further comprising distributing a plurality of groups of personalized offers from multiple sources to the consumers using multiple channel interfaces. 25. The method of claim 23 , further comprising distributing a group of personalized offers to a consumer over a first channel in response to consumer access of the system over a second channel, wherein the second channel is different from the first channel.
| 0.887527 |
1. A method of operation in an automated Web portal generation system to generate sets of customizations of Web portal templates, the method comprising: parsing, by at least one component of the automated Web portal generation system, a number of Webpages of a first Website, represented by a domain or Universal Resource Locator (URL), from which a Web portal template to be customized is to be accessed; producing an entity feature set for the first Website based on a result of the parsing; processing the entity feature set for the first Website via a classifier executed by at least one component of the automated Web portal generation system to produce a set of data that represents, for each of a plurality of entities, a respective probability of the entity belonging to a respective one of a plurality of classes; performing color matching on the set of data produced via the classifier to generate a number of proposed color combinations for a proposed customization of the Web portal template, wherein performing color matching to generate a number of proposed color combinations includes identifying candidate background colors by evaluating contrast between colors of each pair of a plurality of pairs of colors in a device-independent color space; ranking pairs of color combinations based at least in part on the probabilities from the processing via the classifier; returning the ranking as a collection of results for user evaluation; and identifying one of the proposed color combinations for a proposed customization of the Web portal template.
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1. A method of operation in an automated Web portal generation system to generate sets of customizations of Web portal templates, the method comprising: parsing, by at least one component of the automated Web portal generation system, a number of Webpages of a first Website, represented by a domain or Universal Resource Locator (URL), from which a Web portal template to be customized is to be accessed; producing an entity feature set for the first Website based on a result of the parsing; processing the entity feature set for the first Website via a classifier executed by at least one component of the automated Web portal generation system to produce a set of data that represents, for each of a plurality of entities, a respective probability of the entity belonging to a respective one of a plurality of classes; performing color matching on the set of data produced via the classifier to generate a number of proposed color combinations for a proposed customization of the Web portal template, wherein performing color matching to generate a number of proposed color combinations includes identifying candidate background colors by evaluating contrast between colors of each pair of a plurality of pairs of colors in a device-independent color space; ranking pairs of color combinations based at least in part on the probabilities from the processing via the classifier; returning the ranking as a collection of results for user evaluation; and identifying one of the proposed color combinations for a proposed customization of the Web portal template. 7. The method of claim 1 , further comprising: crawling an n-level deep page tree of the first Website before parsing the number of Webpages of the first Website.
| 0.632353 |
1. A mobile device having a display screen, comprising: a processor; and a processor readable storage medium having processor readable program code embodied in said processor readable storage medium, said processor readable program code for programming the device to: find links within a page character array and filter out of the page character array characters which are not links; create one or more link groups each having a plurality of links; lay out each link group for display in optimum form on the display screen of the mobile device at predetermined display screen locations based upon hardware of the mobile device, wherein the predetermined screen locations correspond to discrete user locations; display on the display screen of the mobile device a first portion of the link group layout, wherein the first portion does not include all links of the link group; logically map each of the displayed links of the first portion of the link group to a distinct user input, in which correspondence between links in the link group and keystrokes or voice commands is created; alter the display of the link groups to display a second portion of the link group layout; and logically map each of the displayed links of the second portion of the link group to a distinct user input; wherein the mapping of each of the displayed links of the second portion of the link group does not alter the mapping of the first portion of the link group such that the mapping of links of the first and the second portions of the link group are maintained concurrently.
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1. A mobile device having a display screen, comprising: a processor; and a processor readable storage medium having processor readable program code embodied in said processor readable storage medium, said processor readable program code for programming the device to: find links within a page character array and filter out of the page character array characters which are not links; create one or more link groups each having a plurality of links; lay out each link group for display in optimum form on the display screen of the mobile device at predetermined display screen locations based upon hardware of the mobile device, wherein the predetermined screen locations correspond to discrete user locations; display on the display screen of the mobile device a first portion of the link group layout, wherein the first portion does not include all links of the link group; logically map each of the displayed links of the first portion of the link group to a distinct user input, in which correspondence between links in the link group and keystrokes or voice commands is created; alter the display of the link groups to display a second portion of the link group layout; and logically map each of the displayed links of the second portion of the link group to a distinct user input; wherein the mapping of each of the displayed links of the second portion of the link group does not alter the mapping of the first portion of the link group such that the mapping of links of the first and the second portions of the link group are maintained concurrently. 2. A mobile device as in claim 1 , wherein adjacent link characters comprise link characters separated in the page character array by any combination of: no other characters, blank space characters, line feed characters, and link separator characters.
| 0.5 |
8. A system, comprising: a data processing apparatus; and a memory storage apparatus in data communication with the data processing apparatus, the memory storage apparatus storing instructions executable by the data processing apparatus and that upon such execution cause the data processing apparatus to perform operations comprising: identifying, in a set of text sources that were previously published within a specified amount of time of a current time, two or more keywords that co-occur in at least one of the text sources; determining that the two or more identified keywords are not designated as co-occurring keywords in a data structure storing historically linked co-occurring keywords; in response to determining that the two or more identified keywords are not designated as co-occurring keywords and in response to the two or more identified keywords co-occurring in at least one of the text sources, temporarily linking the two or more identified keywords for a limited amount of time; and distributing, during the limited amount of time, content items based on the temporary link between the two or more identified keywords.
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8. A system, comprising: a data processing apparatus; and a memory storage apparatus in data communication with the data processing apparatus, the memory storage apparatus storing instructions executable by the data processing apparatus and that upon such execution cause the data processing apparatus to perform operations comprising: identifying, in a set of text sources that were previously published within a specified amount of time of a current time, two or more keywords that co-occur in at least one of the text sources; determining that the two or more identified keywords are not designated as co-occurring keywords in a data structure storing historically linked co-occurring keywords; in response to determining that the two or more identified keywords are not designated as co-occurring keywords and in response to the two or more identified keywords co-occurring in at least one of the text sources, temporarily linking the two or more identified keywords for a limited amount of time; and distributing, during the limited amount of time, content items based on the temporary link between the two or more identified keywords. 11. The system of claim 8 , wherein temporarily linking the two or more identified keywords comprises: identifying a frequency of occurrence of the two or more identified keywords in the set of text sources; determining that the frequency of occurrence satisfies a frequency threshold; and linking the two or more identified keywords in response to determining that the frequency of occurrence satisfies the frequency threshold.
| 0.57196 |
25. A computer-readable volatile or non-volatile medium storing one or more sequences of instructions which, when executed by one or more processors, cause the one or more processors to perform the steps of: after an XML processor, which is configured to send validated XML data to an application, starts performing a validation operation on an XML-based input stream, and before said XML processor completes performing said validation operation on said XML-based input stream, performing the steps of: after starting to validate a particular XML element in said XML-based input stream, and before completion of validating said particular XML element in said XML-based input stream, performing the computer-implemented step of said XML processor receiving one or more requests for particular information relating to said validation operation, wherein said one or more requests include at least one of: (a) a request for whether said particular XML element is defined in corresponding information that dictates the structure of said XML data in said XML-based input stream; (b) a request for the name of said particular XML element; (c) a request for the data type of said particular XML element; (d) a request for whether said particular XML element conforms to the corresponding information that dictates the structure of said XML data in said XML-based input stream; (e) a request for the current validation mode of said validation operation; (f) a request for the current state of said validation operation; or (g) a request for one or more annotations that are associated with said particular XML element; said XML processor generating one or more messages that include said particular information; and said XML processor responding to said one or more requests for said particular information by providing said one or more messages.
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25. A computer-readable volatile or non-volatile medium storing one or more sequences of instructions which, when executed by one or more processors, cause the one or more processors to perform the steps of: after an XML processor, which is configured to send validated XML data to an application, starts performing a validation operation on an XML-based input stream, and before said XML processor completes performing said validation operation on said XML-based input stream, performing the steps of: after starting to validate a particular XML element in said XML-based input stream, and before completion of validating said particular XML element in said XML-based input stream, performing the computer-implemented step of said XML processor receiving one or more requests for particular information relating to said validation operation, wherein said one or more requests include at least one of: (a) a request for whether said particular XML element is defined in corresponding information that dictates the structure of said XML data in said XML-based input stream; (b) a request for the name of said particular XML element; (c) a request for the data type of said particular XML element; (d) a request for whether said particular XML element conforms to the corresponding information that dictates the structure of said XML data in said XML-based input stream; (e) a request for the current validation mode of said validation operation; (f) a request for the current state of said validation operation; or (g) a request for one or more annotations that are associated with said particular XML element; said XML processor generating one or more messages that include said particular information; and said XML processor responding to said one or more requests for said particular information by providing said one or more messages. 28. The computer-readable volatile or non-volatile medium of claim 25 , wherein the instructions that cause the one or more processors to perform the step of said XML processor generating said one or more messages includes instructions which, when executed by the one or more processors, cause said XML processor to generate said one or more messages that are transmitted in an output stream.
| 0.629473 |
14. The computer-implemented method of either of claims 12 or 13 , wherein the step of searching through the database to locate a source document containing the selected number comprises: generating one or more alternative number representations for the selected number when no source document containing the selected number is found; searching through the database to locate a source document containing at least one of the alternative number representations; and stopping the search when a source document containing a one of the alternative number representations is located.
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14. The computer-implemented method of either of claims 12 or 13 , wherein the step of searching through the database to locate a source document containing the selected number comprises: generating one or more alternative number representations for the selected number when no source document containing the selected number is found; searching through the database to locate a source document containing at least one of the alternative number representations; and stopping the search when a source document containing a one of the alternative number representations is located. 15. The computer-implemented method of claim 14 : (a) wherein the alternative number representations comprise numerical digits representing units of money; (b) wherein at least one of the alternative number representations includes a unit of money symbol; (c) wherein at least one of the alternative number representations includes at least one comma between digits; (d) wherein at least one of the alternative number representations includes at least one period between digits; and (e) wherein at least one of the alternative number representations includes at least one space between digits.
| 0.554054 |
49. A server for recognizing an input environmental sound, the server comprising: a server database configured to store a plurality of sound models representing environmental sounds and a plurality of labels, wherein each of the plurality of labels identifies at least one of the plurality of sound models; a communication unit configured to receive an input sound model representing an input environmental sound from a client device if a confidence level determined by the client device and associated with a first label associated with the input environmental sound is less than a first confidence threshold; and a sound recognition unit configured to, if the confidence level determined by the client device is less than the first confidence threshold: determine similarity values between the input sound model and the plurality of sound models to identify one or more sound models of the plurality of sound models that are similar to the input sound model; select a second label from one or more labels of the plurality of labels associated with the one or more sound models; and associate the second label with the input environmental sound based on a confidence level of the first second label, wherein the communication unit is further configured to provide the second label or an indication of a failure in recognizing the input environmental sound to the client device based on the confidence level of the second label.
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49. A server for recognizing an input environmental sound, the server comprising: a server database configured to store a plurality of sound models representing environmental sounds and a plurality of labels, wherein each of the plurality of labels identifies at least one of the plurality of sound models; a communication unit configured to receive an input sound model representing an input environmental sound from a client device if a confidence level determined by the client device and associated with a first label associated with the input environmental sound is less than a first confidence threshold; and a sound recognition unit configured to, if the confidence level determined by the client device is less than the first confidence threshold: determine similarity values between the input sound model and the plurality of sound models to identify one or more sound models of the plurality of sound models that are similar to the input sound model; select a second label from one or more labels of the plurality of labels associated with the one or more sound models; and associate the second label with the input environmental sound based on a confidence level of the first second label, wherein the communication unit is further configured to provide the second label or an indication of a failure in recognizing the input environmental sound to the client device based on the confidence level of the second label. 50. The server of claim 49 , wherein the communication unit is further configured to provide the first label and the one or more sound models to the client device if the confidence level of the second label is greater than or equal to a second confidence threshold. and wherein the one or more sound models are identified based on the prior occurrence information.
| 0.5 |
26. The system of claim 25 in which the query comprises one or more of a product brand and a product model.
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26. The system of claim 25 in which the query comprises one or more of a product brand and a product model. 27. The system of claim 26 in which the query comprises the product brand, and wherein the operations further comprise identifying a popular product model associated with the product brand as the suggested product.
| 0.942058 |
17. A computer-readable medium storing a software program thereon, the program comprising computer executable instructions for implementing a method for representing type information for a typed intermediate language using a class hierarchy for representing different type classifications, the method comprising: defining a programming class of the class hierarchy as ‘PrimType’, wherein the programming class represents primitive type information for the typed intermediate language; associating a size with instances of the ‘PrimType’ class, wherein the size is settable to represent an actual size of instances of the ‘PrimType’ class, settable to represent a symbolic size of instances of the ‘PrimType’ class, and settable to represent an unknown size of instances of the ‘PrimType’ class, and wherein the actual size and the symbolic size are defined as a number of bits; and associating a kind of type with instances of the ‘PrimType’ class; wherein the class ‘PrimType’ represents a plurality of types comprising at least an unknown type, wherein the unknown type can represent any type, wherein the unknown type represents a lack of all type information, wherein a compiler drops type information during compilation by changing a known type to the unknown type, in the typed intermediate language, during a stage of lowering, wherein the unknown type is set independently of the size, and wherein the ‘PrimType’ class supports an unknown type with an unknown size.
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17. A computer-readable medium storing a software program thereon, the program comprising computer executable instructions for implementing a method for representing type information for a typed intermediate language using a class hierarchy for representing different type classifications, the method comprising: defining a programming class of the class hierarchy as ‘PrimType’, wherein the programming class represents primitive type information for the typed intermediate language; associating a size with instances of the ‘PrimType’ class, wherein the size is settable to represent an actual size of instances of the ‘PrimType’ class, settable to represent a symbolic size of instances of the ‘PrimType’ class, and settable to represent an unknown size of instances of the ‘PrimType’ class, and wherein the actual size and the symbolic size are defined as a number of bits; and associating a kind of type with instances of the ‘PrimType’ class; wherein the class ‘PrimType’ represents a plurality of types comprising at least an unknown type, wherein the unknown type can represent any type, wherein the unknown type represents a lack of all type information, wherein a compiler drops type information during compilation by changing a known type to the unknown type, in the typed intermediate language, during a stage of lowering, wherein the unknown type is set independently of the size, and wherein the ‘PrimType’ class supports an unknown type with an unknown size. 20. The computer-readable medium of claim 17 wherein associating a kind of primitive type with instances of the ‘PrimType’ class comprises defining the kind of type as ‘PrimTypekind’.
| 0.795189 |
1. A method for scheduling documents to be crawled by a search engine in an appropriate order to reduce visibility of stale content in web searching, comprising: on a computer system having one or more processors and memory storing one or more programs for execution by the one or more processors: associating with each of a plurality of documents a respective initial web crawl interval, wherein the initial web crawl interval is determined based at least in part on a document's importance metric; retrieving each of the plurality of documents from a respective host at one or more times associated with each document's respective initial web crawl interval; associating a revised web crawl interval with a respective document of the plurality of documents based on the document's respective initial web crawl interval and any changes to content of the document; partitioning the plurality of documents into multiple tiers according to their respective web crawl intervals, each tier having a distinct associated range of web crawl intervals, including storing data for each tier identifying documents in the plurality of documents assigned to that tier in accordance with the documents' respective web crawl intervals; for each tier of the multiple tiers, determining a web crawl order for the documents assigned to the tier in accordance with their respective revised web crawl interval; and moving a respective document between tiers of the multiple tiers when the respective revised web crawl interval of the respective document is associated with a different tier of the multiple tiers than a previous web crawl interval of the respective document.
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1. A method for scheduling documents to be crawled by a search engine in an appropriate order to reduce visibility of stale content in web searching, comprising: on a computer system having one or more processors and memory storing one or more programs for execution by the one or more processors: associating with each of a plurality of documents a respective initial web crawl interval, wherein the initial web crawl interval is determined based at least in part on a document's importance metric; retrieving each of the plurality of documents from a respective host at one or more times associated with each document's respective initial web crawl interval; associating a revised web crawl interval with a respective document of the plurality of documents based on the document's respective initial web crawl interval and any changes to content of the document; partitioning the plurality of documents into multiple tiers according to their respective web crawl intervals, each tier having a distinct associated range of web crawl intervals, including storing data for each tier identifying documents in the plurality of documents assigned to that tier in accordance with the documents' respective web crawl intervals; for each tier of the multiple tiers, determining a web crawl order for the documents assigned to the tier in accordance with their respective revised web crawl interval; and moving a respective document between tiers of the multiple tiers when the respective revised web crawl interval of the respective document is associated with a different tier of the multiple tiers than a previous web crawl interval of the respective document. 3. The method of claim 1 , further comprising: determining for respective documents of the plurality of documents, content update rates of the respective documents, user click rates of the respective documents, and at least one document importance metric of the respective documents; associating the revised web crawl interval with each document of the plurality of documents based on the document's respective initial web crawl interval, any changes to content of the document, the user click rate of the document, and the at least one document importance metric of the document; and downloading and recording new copies of at least a subset of the documents in accordance with the determined web crawl order.
| 0.562752 |
13. An apparatus for analyzing data, the apparatus comprising: a memory; and at least one processor coupled to the memory, the at least one processor being configured: to generate, by an entity, a query based at least in part on a topic of interest; to execute the query on a plurality of data sources, at least one of the plurality of data sources comprising customer information or financial information; to select, by the entity, a data source from the plurality of data sources for monitoring based on a correlation between the data source and the topic of interest, the correlation determined based on results of the executed query; to monitor, based on a set schedule, the data source for matches to the query to extract data from the data source when at least an update to stored data matches the query, newly added data matches the query, or a combination thereof; to extract data from the data source when at least an update to stored data matches the query, newly added data matches the query, or a combination thereof; to determine an extraction rate for extracting the data, the extraction rate indicating an amount of the data that is extracted over a first time period; to determine a first processing rate for processing the extracted data with a number of parallel processors, the first processing rate indicating an amount of extracted data that is processed over a second time period; to dynamically adjust the number of parallel processors for analyzing the extracted data based on the extraction rate to obtain a second processing rate that is greater than the first processing rate; to analyze, with the parallel processors, the extracted data to determine at least one of a sentiment, an index, a pattern, or a combination thereof; to establish a two-way communication channel, between at least the entity that selected the data source for monitoring and a user device of a user that provided data to the data source, based on the analysis of the extracted data; to transmit, from the entity via the two-way communication channel, a first message directed to the user device based on the analysis of the extracted data; and to receive, from the user device via the two-way communication channel, a second message in response to the first message directed to the user device.
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13. An apparatus for analyzing data, the apparatus comprising: a memory; and at least one processor coupled to the memory, the at least one processor being configured: to generate, by an entity, a query based at least in part on a topic of interest; to execute the query on a plurality of data sources, at least one of the plurality of data sources comprising customer information or financial information; to select, by the entity, a data source from the plurality of data sources for monitoring based on a correlation between the data source and the topic of interest, the correlation determined based on results of the executed query; to monitor, based on a set schedule, the data source for matches to the query to extract data from the data source when at least an update to stored data matches the query, newly added data matches the query, or a combination thereof; to extract data from the data source when at least an update to stored data matches the query, newly added data matches the query, or a combination thereof; to determine an extraction rate for extracting the data, the extraction rate indicating an amount of the data that is extracted over a first time period; to determine a first processing rate for processing the extracted data with a number of parallel processors, the first processing rate indicating an amount of extracted data that is processed over a second time period; to dynamically adjust the number of parallel processors for analyzing the extracted data based on the extraction rate to obtain a second processing rate that is greater than the first processing rate; to analyze, with the parallel processors, the extracted data to determine at least one of a sentiment, an index, a pattern, or a combination thereof; to establish a two-way communication channel, between at least the entity that selected the data source for monitoring and a user device of a user that provided data to the data source, based on the analysis of the extracted data; to transmit, from the entity via the two-way communication channel, a first message directed to the user device based on the analysis of the extracted data; and to receive, from the user device via the two-way communication channel, a second message in response to the first message directed to the user device. 14. The apparatus of claim 13 , in which: the customer information comprises at least one of a customer's location, credit score, account balance, income, or a combination thereof; and the financial information comprises at least one of mortgage rates, interest rates, housing prices, or a combination thereof.
| 0.536595 |
20. A tangible, non-transitory, computer-readable medium storing instructions that, when executed by one or more processors, cause the one or more processors to display a graphical programming interface that allows a user to: generate a typical component template that defines an implementation of a process control loop function that may be utilized by a plurality of plant equipment devices within a process plant; generate a first and a second adapter component template, the first and the second adapter component templates having one or more configurable logical expressions or one or more configurable logic algorithms; generate a graphical programming interface to allow for modification of the first and the second adapter component templates based on a specific process control operation associated with each of a first and a second plant equipment device, respectively, from among the plurality of plant equipment devices, wherein modification of the first and the second adapter component templates includes defining the one or more configurable logical expressions or the one or more configurable logic algorithms to specify how the first and the second adapter component templates interact with the typical component template and signals to or from the first and the second plant equipment devices, respectively to define for the first and the second plant equipment devices, respectively, the specific process control operation utilizing the process control loop function defined by the typical component template, wherein the process control loop function includes one or more of: (i) a proportional-integral-derivative control operation, (ii) a proportional-integral control operation, (iii) a start permit control operation, (iv) an alarm control operation, or (v) a native control component operation; and instantiate the typical component template with each of first and the second adapter component templates, respectively, to generate a first and a second native control component, respectively, wherein the first native control component, when executed, by one or more processors associated with one or more process controllers communicatively coupled to one or more host work stations and the plurality of plant equipment devices, performs the specific process control operation for the first plant equipment device utilizing the process control loop function defined by the typical component template in accordance with the modified first adapter component template, and wherein the second native control component, when executed, by one or more processors associated with one or more process controllers communicatively coupled to one or more host work stations and the plurality of plant equipment devices, performs the specific process control operation for the second plant equipment device utilizing the process control loop function defined by the typical component template in accordance with the modified second adapter component template.
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20. A tangible, non-transitory, computer-readable medium storing instructions that, when executed by one or more processors, cause the one or more processors to display a graphical programming interface that allows a user to: generate a typical component template that defines an implementation of a process control loop function that may be utilized by a plurality of plant equipment devices within a process plant; generate a first and a second adapter component template, the first and the second adapter component templates having one or more configurable logical expressions or one or more configurable logic algorithms; generate a graphical programming interface to allow for modification of the first and the second adapter component templates based on a specific process control operation associated with each of a first and a second plant equipment device, respectively, from among the plurality of plant equipment devices, wherein modification of the first and the second adapter component templates includes defining the one or more configurable logical expressions or the one or more configurable logic algorithms to specify how the first and the second adapter component templates interact with the typical component template and signals to or from the first and the second plant equipment devices, respectively to define for the first and the second plant equipment devices, respectively, the specific process control operation utilizing the process control loop function defined by the typical component template, wherein the process control loop function includes one or more of: (i) a proportional-integral-derivative control operation, (ii) a proportional-integral control operation, (iii) a start permit control operation, (iv) an alarm control operation, or (v) a native control component operation; and instantiate the typical component template with each of first and the second adapter component templates, respectively, to generate a first and a second native control component, respectively, wherein the first native control component, when executed, by one or more processors associated with one or more process controllers communicatively coupled to one or more host work stations and the plurality of plant equipment devices, performs the specific process control operation for the first plant equipment device utilizing the process control loop function defined by the typical component template in accordance with the modified first adapter component template, and wherein the second native control component, when executed, by one or more processors associated with one or more process controllers communicatively coupled to one or more host work stations and the plurality of plant equipment devices, performs the specific process control operation for the second plant equipment device utilizing the process control loop function defined by the typical component template in accordance with the modified second adapter component template. 26. The tangible, non-transitory, computer-readable medium of claim 20 , wherein the instructions, when executed by one or more processors, further cause modification of the first and the second adapter component templates to include (i) specifying signal connections between the first plant equipment device, the adapter component template, and the typical component template, and (ii) specifying signal connections between the second plant equipment device, the second adapter component template, and the typical component template.
| 0.528969 |
1. A method for translating data, the method comprising: obtaining, via a network, a first language translation file associated with and used to translate data from a first account system; obtaining, via a network, a second language translation file associated with and used to translate data from a second account system; obtaining, via a network, a third language translation file associated with and used to translate data from a third account system; the third account system generating an account file and determining that the account file requires translation of a plurality of language terms that are not translated by the third translation file, and in response, the third account system translating the plurality of language terms from the account file using the first and second language translation files, and translating other terms of the account file using the third language translation file; and the third account system sending to the second account system the account file which has been translated using the first, second and third language translation files.
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1. A method for translating data, the method comprising: obtaining, via a network, a first language translation file associated with and used to translate data from a first account system; obtaining, via a network, a second language translation file associated with and used to translate data from a second account system; obtaining, via a network, a third language translation file associated with and used to translate data from a third account system; the third account system generating an account file and determining that the account file requires translation of a plurality of language terms that are not translated by the third translation file, and in response, the third account system translating the plurality of language terms from the account file using the first and second language translation files, and translating other terms of the account file using the third language translation file; and the third account system sending to the second account system the account file which has been translated using the first, second and third language translation files. 5. The method of claim 1 , wherein translating comprises: determining whether the first language translation file has translations for less than all untranslated language terms of the account file; responsive to a determination that the first language translation file has translations for less than all untranslated language terms, using the translations in place of some untranslated account terms of the account file; responsive to a determination that the first language translation file has translations for less than all untranslated language terms, transmitting remaining untranslated language terms to a translation center; and receiving from the translation center the translated file corresponding to the remaining untranslated language terms.
| 0.665676 |
16. The system of claim 15 , wherein the term weights are based on inverse frequency scores.
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16. The system of claim 15 , wherein the term weights are based on inverse frequency scores. 17. The system of claim 16 , wherein the paragraph scores are generated using a limit on the number of times a matching search term can be counted for a paragraph.
| 0.953318 |
11. A system for sharing summaries indicative of a document, comprising: one or more processing units; and memory comprising instructions that when executed by at least some of the one or more processing units, perform a method comprising: providing, for presentation to a first distinctly identifiable entity, a first summary of the document, the first summary authored by a second distinctly identifiable entity; receiving feedback from the first distinctly identifiable entity resulting in a modification to the first summary to generate a first modified summary; providing, for presentation to a third distinctly identifiable entity, the first modified summary of the document and a second summary of the document in a first ranked order; receiving feedback from the third distinctly identifiable entity related to at least one of the first modified summary or the second summary; and providing the first modified summary and the second summary in a second ranked order, the second ranked order different than the first ranked order, the second ranked order a function of the feedback received from the third distinctly identifiable entity.
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11. A system for sharing summaries indicative of a document, comprising: one or more processing units; and memory comprising instructions that when executed by at least some of the one or more processing units, perform a method comprising: providing, for presentation to a first distinctly identifiable entity, a first summary of the document, the first summary authored by a second distinctly identifiable entity; receiving feedback from the first distinctly identifiable entity resulting in a modification to the first summary to generate a first modified summary; providing, for presentation to a third distinctly identifiable entity, the first modified summary of the document and a second summary of the document in a first ranked order; receiving feedback from the third distinctly identifiable entity related to at least one of the first modified summary or the second summary; and providing the first modified summary and the second summary in a second ranked order, the second ranked order different than the first ranked order, the second ranked order a function of the feedback received from the third distinctly identifiable entity. 19. The system of claim 11 , the receiving feedback from the first distinctly identifiable entity comprising: receiving a link to be inserted into the first summary.
| 0.569792 |
5. The computer program product of claim 3 , wherein the semantic profiling component comprises a thesaurus comprising clusters of similar terms.
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5. The computer program product of claim 3 , wherein the semantic profiling component comprises a thesaurus comprising clusters of similar terms. 6. The computer program product of claim 5 , wherein the thesaurus is further provided with an indication of the degree of similarity of each cluster or individual term.
| 0.904871 |
19. The method as claimed in claim 10 , wherein the step of receiving a plurality of attributes from a user further comprises: providing an attribute input user interface for receiving a plurality of attributes from a user for use in performing the online choice model, comprising: one or more attribute zones wherein each attribute zone receives an attribute and a plurality of attribute levels associated with the attribute from the user; and providing a model explorer user interface further comprises: an attribute level selection zone for each attribute in the choice model; wherein each attribute level selection zone allows a user to select one of the associated levels; a prediction output zone which displays an estimate of the predicted response and variability estimate from the online choice model for the current attribute levels selected in the attribute level selection zone.
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19. The method as claimed in claim 10 , wherein the step of receiving a plurality of attributes from a user further comprises: providing an attribute input user interface for receiving a plurality of attributes from a user for use in performing the online choice model, comprising: one or more attribute zones wherein each attribute zone receives an attribute and a plurality of attribute levels associated with the attribute from the user; and providing a model explorer user interface further comprises: an attribute level selection zone for each attribute in the choice model; wherein each attribute level selection zone allows a user to select one of the associated levels; a prediction output zone which displays an estimate of the predicted response and variability estimate from the online choice model for the current attribute levels selected in the attribute level selection zone. 25. The method as claimed in claim 19 , wherein the step of creating a plurality of survey template pages is performed using a survey assembly user interface comprises: a content and layout user interface for receiving content and layout parameters from a user and generating a plurality of survey template pages; wherein at least one of the plurality of survey template pages comprises at least one treatment display zone; wherein each treatment display zone comprises one or more associated layout parameters; and a content generator interface for generating a visual representation of each treatment for use in a treatment display zone.
| 0.851726 |
1. A conversation-sentence generation device that generates a conversation sentence of a virtual agent having a personified conversation with each of a plurality of users, comprising: a memory that stores a physical and psychological state of the agent as an agent state and stores a physical and psychological state of each of the plurality of users respectively as a user state, the agent state including an emotion value representing an emotion of the agent, and the user state including a degree of intimacy value representing a degree of intimacy between each of the plurality of users and the agent; and a processor configured to execute instructions to implement: an input unit that receives, as input information, a conversation sentence given from one of the plurality of users to the agent, first clue information based on which the physical and psychological state of the agent is estimated, and second clue information based on which the physical and psychological state of the one of the plurality of users is estimated; an agent state estimating unit that estimates a new agent state based on the input information and the agent state, the agent state estimating unit further estimating the emotion value of the agent state; a user state estimating unit that estimates a new user state based on the input information and the user state; an utterance intention generating unit that determines whether said one of the plurality of users is an opponent user based on the input information, and that generates an utterance intention directed from the agent to the opponent user based on the input information, the agent state including the emotion value, and the user state; a conversation sentence generating unit that generates, based on the input information, the agent state, the user state of the opponent user including the degree of intimacy between the agent and the opponent user, and the utterance intention, a conversation sentence given from the agent to the opponent user; and an output unit that outputs the conversation sentence generated by the conversation sentence generating unit.
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1. A conversation-sentence generation device that generates a conversation sentence of a virtual agent having a personified conversation with each of a plurality of users, comprising: a memory that stores a physical and psychological state of the agent as an agent state and stores a physical and psychological state of each of the plurality of users respectively as a user state, the agent state including an emotion value representing an emotion of the agent, and the user state including a degree of intimacy value representing a degree of intimacy between each of the plurality of users and the agent; and a processor configured to execute instructions to implement: an input unit that receives, as input information, a conversation sentence given from one of the plurality of users to the agent, first clue information based on which the physical and psychological state of the agent is estimated, and second clue information based on which the physical and psychological state of the one of the plurality of users is estimated; an agent state estimating unit that estimates a new agent state based on the input information and the agent state, the agent state estimating unit further estimating the emotion value of the agent state; a user state estimating unit that estimates a new user state based on the input information and the user state; an utterance intention generating unit that determines whether said one of the plurality of users is an opponent user based on the input information, and that generates an utterance intention directed from the agent to the opponent user based on the input information, the agent state including the emotion value, and the user state; a conversation sentence generating unit that generates, based on the input information, the agent state, the user state of the opponent user including the degree of intimacy between the agent and the opponent user, and the utterance intention, a conversation sentence given from the agent to the opponent user; and an output unit that outputs the conversation sentence generated by the conversation sentence generating unit. 5. The conversation-sentence generation device according to claim 1 , wherein a first score is attached to the utterance intention, a bonus point is given to the first score of the utterance intention when the utterance intension is generated within a threshold time period from a change of the agent state or the user state of the opponent user, and the utterance intention generating unit generates the utterance intention in accordance with the first score.
| 0.567542 |
1. A method to use dynamically prioritized email communications to establish and analyze organization social network maps, the method comprising the steps of: selecting a dynamically prioritized email dataset based on network boundaries and contextual framework; establishing a one-way trusted relationship score between an email recipient and sender; establishing a one-way trusted relationship score between an email sender and recipient; establishing a two-way trusted relationship score between two communicating entities; establishing an atomic unit of entities based on a decreasing order of at least one of the one-way trusted relationship score and the two-way trusted relationship score; and establishing a social network based on arranging atomic units and entities based on one or more of an email prioritization score, a trusted relationship score, and an email productivity and collaboration metric; wherein the entities are email senders and email recipients.
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1. A method to use dynamically prioritized email communications to establish and analyze organization social network maps, the method comprising the steps of: selecting a dynamically prioritized email dataset based on network boundaries and contextual framework; establishing a one-way trusted relationship score between an email recipient and sender; establishing a one-way trusted relationship score between an email sender and recipient; establishing a two-way trusted relationship score between two communicating entities; establishing an atomic unit of entities based on a decreasing order of at least one of the one-way trusted relationship score and the two-way trusted relationship score; and establishing a social network based on arranging atomic units and entities based on one or more of an email prioritization score, a trusted relationship score, and an email productivity and collaboration metric; wherein the entities are email senders and email recipients. 15. The method of claim 1 , further including the steps of: plotting the social network map, wherein an atomic unit of respective top trusted entities are established for a given contextual keyword or a set of keywords based on at least one of a relationship trust score, an email productivity metric, and an email collaboration metric; and establishing a second level of a network, wherein the respective top trusted entities of each of an entity on a first level of the network is displayed.
| 0.5 |
30. A computer-readable storage medium that includes data and instructions for enabling actions to be performed on a remote platform, comprising: a first component for enabling a request for a document from the remote platform, a type of the platform including a type of an operating system and type of a native browser that are employed to display the document; a second component for enabling a determination of the type of the remote platform and selectively associating a size ratio between a plurality of font sizes with the determined type of the remote platform, the enabling the determination of the type of the remote platform comprising enabling a determination of the type of the operating system and the determination of the type of the native browser, and the selective association being based on the determination of the type of the operating system and the determination of the type of the native browser; a third component for enabling the document with a plurality of font sizes for the document to be provided to the remote platform for display, the document is being locally scaled for display by the operation of the native browser with the size ratio for the plurality of font sizes; and a fourth component for enabling the plurality of font sizes to be changed by an execution of a script included with the document using at least one control of the native browser operating on the remote platform, the size ratio between the plurality of font sizes being determined by the native browser and maintained for a change to a size of at least one font displayed in the document at the remote platform, the execution changes the at least one font for at least one markup language text element displayed within the document.
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30. A computer-readable storage medium that includes data and instructions for enabling actions to be performed on a remote platform, comprising: a first component for enabling a request for a document from the remote platform, a type of the platform including a type of an operating system and type of a native browser that are employed to display the document; a second component for enabling a determination of the type of the remote platform and selectively associating a size ratio between a plurality of font sizes with the determined type of the remote platform, the enabling the determination of the type of the remote platform comprising enabling a determination of the type of the operating system and the determination of the type of the native browser, and the selective association being based on the determination of the type of the operating system and the determination of the type of the native browser; a third component for enabling the document with a plurality of font sizes for the document to be provided to the remote platform for display, the document is being locally scaled for display by the operation of the native browser with the size ratio for the plurality of font sizes; and a fourth component for enabling the plurality of font sizes to be changed by an execution of a script included with the document using at least one control of the native browser operating on the remote platform, the size ratio between the plurality of font sizes being determined by the native browser and maintained for a change to a size of at least one font displayed in the document at the remote platform, the execution changes the at least one font for at least one markup language text element displayed within the document. 34. The computer-readable storage medium of claim 30 , further comprising a component for enabling a determination of a version of the operating system for the remote platform.
| 0.681282 |
4. The feature compensation apparatus of claim 1 , wherein the feature extractor converts each frame of the corrupt speech signal from time domain to frequency domain, and calculates a log energy value by taking a logarithm of energy which has been calculated by applying a Mel-scale filter bank to the converted corrupt speech signal, thereby extracting the corrupt speech features.
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4. The feature compensation apparatus of claim 1 , wherein the feature extractor converts each frame of the corrupt speech signal from time domain to frequency domain, and calculates a log energy value by taking a logarithm of energy which has been calculated by applying a Mel-scale filter bank to the converted corrupt speech signal, thereby extracting the corrupt speech features. 5. The feature compensation apparatus of claim 4 , wherein the feature extractor smooths the corrupt speech signal before taking a logarithm of the energy which has been calculated by applying the Mel-scale filter bank to the converted corrupt speech signal.
| 0.929002 |
2. A method to display landmark information comprising: receiving, by one or more computers, a user query; identifying one or more trigger words in the user query; selecting one or more tags from a landmark database, the tags corresponding to the one or more trigger words; supplementing the user query with the one or more tags to generate a supplemented user query; retrieving, based on the supplemented user query, one or more visual clusters of landmark images; generating a user interface including the one or more visual clusters of retrieved landmark images; and causing one or more summary lists of visual clusters of landmark images to be displayed on the user interface, wherein each of the one or more summary lists includes descriptive information and access information for each visual cluster in the one or more summary lists displayed.
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2. A method to display landmark information comprising: receiving, by one or more computers, a user query; identifying one or more trigger words in the user query; selecting one or more tags from a landmark database, the tags corresponding to the one or more trigger words; supplementing the user query with the one or more tags to generate a supplemented user query; retrieving, based on the supplemented user query, one or more visual clusters of landmark images; generating a user interface including the one or more visual clusters of retrieved landmark images; and causing one or more summary lists of visual clusters of landmark images to be displayed on the user interface, wherein each of the one or more summary lists includes descriptive information and access information for each visual cluster in the one or more summary lists displayed. 11. The method of claim 2 , further comprising providing a user interface element to receive user input corresponding to each visual cluster.
| 0.675877 |
3. The method of claim 1 , further comprising the step of: representing asset topics using a vector-space model and UF-IDF (usage frequency, inverse document frequency) weighting.
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3. The method of claim 1 , further comprising the step of: representing asset topics using a vector-space model and UF-IDF (usage frequency, inverse document frequency) weighting. 4. The method of claim 3 , further comprising the steps of: maintaining asset topics on a per-user basis; and determining group topic assessments by combining individual user assessments.
| 0.959201 |
44. A server device comprising: a memory to store instructions; and a processor to execute the instructions to: receive the search query from a user, the search query including one or more search terms; generate additional terms that are related to the one or more search terms; generate a query context that includes web documents selected based on the search query; filter the additional terms using the query context to remove those of the additional terms that are not semantically similar to the one or more search terms; and incorporate one or more remaining ones of the additional terms into the search query to form a modified search query.
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44. A server device comprising: a memory to store instructions; and a processor to execute the instructions to: receive the search query from a user, the search query including one or more search terms; generate additional terms that are related to the one or more search terms; generate a query context that includes web documents selected based on the search query; filter the additional terms using the query context to remove those of the additional terms that are not semantically similar to the one or more search terms; and incorporate one or more remaining ones of the additional terms into the search query to form a modified search query. 45. The server device of claim 44 , where the processor is further to: perform a search for documents based on the modified search query.
| 0.700985 |
1. A proximity service (ProSe) information transmission method, comprising: receiving, by the receiving ProSe entity, a code message sent by the monitoring terminal, wherein the code message is configured to instruct the receiving ProSe entity to acquire a code word, the code word is allocated to the first terminal by a first ProSe entity, and the first ProSe entity is the ProSe entity in the HPLMN of the first terminal; acquiring, by the receiving ProSe entity, the code word; sending, by the receiving ProSe entity, a monitoring message to the monitoring terminal, wherein the monitoring message carries the code word; receiving, by a receiving ProSe entity at a 3GPP network layer in a home public land mobile network (HPLMN), a first message sent by a monitoring terminal, wherein the first message is configured to instruct the receiving ProSe entity to acquire an application user identity that is allocated to a first application user by a first application server, the first application user is a user of a first application of a first terminal, the first application server is an application server of the first application, and the receiving ProSe entity is a ProSe entity in the HPLMN; acquiring, by the receiving ProSe entity, the application user identity via the HPLMN; and sending, by the receiving ProSe entity at the 3GPP network layer in the HPLMN, a second message to the monitoring terminal, wherein the second message carries the application user identity, and the application user identity is configured to indicate the first application user discovered by the monitoring terminal in the HPLMN, wherein the second message further carries a first application identity, the first application identity is an application identity of the first application, and the first application identity is configured to indicate the first application corresponding to the application user identity.
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1. A proximity service (ProSe) information transmission method, comprising: receiving, by the receiving ProSe entity, a code message sent by the monitoring terminal, wherein the code message is configured to instruct the receiving ProSe entity to acquire a code word, the code word is allocated to the first terminal by a first ProSe entity, and the first ProSe entity is the ProSe entity in the HPLMN of the first terminal; acquiring, by the receiving ProSe entity, the code word; sending, by the receiving ProSe entity, a monitoring message to the monitoring terminal, wherein the monitoring message carries the code word; receiving, by a receiving ProSe entity at a 3GPP network layer in a home public land mobile network (HPLMN), a first message sent by a monitoring terminal, wherein the first message is configured to instruct the receiving ProSe entity to acquire an application user identity that is allocated to a first application user by a first application server, the first application user is a user of a first application of a first terminal, the first application server is an application server of the first application, and the receiving ProSe entity is a ProSe entity in the HPLMN; acquiring, by the receiving ProSe entity, the application user identity via the HPLMN; and sending, by the receiving ProSe entity at the 3GPP network layer in the HPLMN, a second message to the monitoring terminal, wherein the second message carries the application user identity, and the application user identity is configured to indicate the first application user discovered by the monitoring terminal in the HPLMN, wherein the second message further carries a first application identity, the first application identity is an application identity of the first application, and the first application identity is configured to indicate the first application corresponding to the application user identity. 5. The method according to claim 1 , wherein the first message carries a first code word, the first code word is allocated to the application user identity by a first ProSe entity, and the first ProSe entity is a ProSe entity in an HPLMN of the first terminal; and wherein acquiring, by the receiving ProSe entity, the application user identity comprises: acquiring, by the receiving ProSe entity, the application user identity according to the first code word.
| 0.681939 |
1. A computer-implemented method of enabling access control, the method comprising: automatically defining an access control statement, for determining authorization request validity using an authorization control engine for an asset, the access control statement comprising a first portion comprising one or more of a structural expression, and a conditional expression wherein the structural expression declares fixed relationships of the asset and a second portion comprising one or more of a classification expression comprising ontology expressions; and evaluating the first portion separately but simultaneously with the classification expression in the second portion of the access control statement, wherein the second portion uses an ontology engine.
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1. A computer-implemented method of enabling access control, the method comprising: automatically defining an access control statement, for determining authorization request validity using an authorization control engine for an asset, the access control statement comprising a first portion comprising one or more of a structural expression, and a conditional expression wherein the structural expression declares fixed relationships of the asset and a second portion comprising one or more of a classification expression comprising ontology expressions; and evaluating the first portion separately but simultaneously with the classification expression in the second portion of the access control statement, wherein the second portion uses an ontology engine. 2. The computer implemented method of claim 1 , further comprising: receiving an authorization query, the authorization query comprising an asset instance; and determining an access authorization based on the authorization query and the evaluation of the access control statement.
| 0.655529 |
1. A translation method adapted to a domain of interest comprising: receiving a source text string comprising a sequence of source words in a source language; generating a set of candidate translations of the source text string, each candidate translation comprising a sequence of target words in a target language; and with a processor, identifying an optimal translation from the set of candidate translations as a function of at least one domain-adapted feature, the at least one domain-adapted feature being computed based on: bilingual probabilities, each bilingual probability being for a source text fragment and a target text fragment of the source text string and candidate translation respectively, the bilingual probabilities being estimated on an out-of-domain parallel corpus comprising source and target strings; and monolingual probabilities for text fragments of one of the source text string and candidate translation, the monolingual probabilities being estimated on an in-domain monolingual corpus, wherein the domain-adapted feature comprises at least one of: a) a forward domain-adapted lexical feature which is a function of ∑ ( i , j ) ∈ a w in ( s i ❘ t j ) where w in (s i |t j ) is an adapted word probability and is a function of a product of w out (t j |s i ) and w in (s i ); b) a reverse domain-adapted lexical feature which is a function of ∑ ( i , j ) ∈ a w in ( t j ❘ s i ) where w in (t j |s i ) is an adapted word probability and is a function of a product of w out (t j |s i ) and w in (t j ); c) a forward domain-adapted phrasal feature which is a function of: ∑ ( i , j ) ∈ a phr in ( s _ i ❘ t _ j ) , where phr in ( s i | t j ) is an adapted phrase probability and is a function of a product of phr out ( t j | s i ) and p in ( s i ); d) a reverse domain-adapted phrasal feature which is a function of: ∑ ( i , j ) ∈ a phr in ( t _ j ❘ s _ i ) , where phr in ( t j | s i ) is an adapted phrase probability and is a function of a product of phr out ( s i | t j ) and p in ( t j ); where s i and t j represent words of the source string and candidate translation respectively which are aligned in an alignment α of the source string and candidate translation, w out (t j |s i ) represents the bilingual probability, which is a word probability for target word t j in the presence of source word s i , derived from the parallel corpus, and w in (s i ) represents the monolingual probability, which is the word probability for source word s i derived from the in-domain monolingual corpus; s i and t j represent phrases of the source string and candidate translation respectively which are aligned in the alignment α of the source string and candidate translation, phr out ( t j | s i )represents the bilingual probability, which is a phrasal probability for target phrase t j in the presence of source phrase s i , derived from the parallel corpus, p in ( s i ) represents the monolingual probability, which is the phrasal probability for source phrase s i derived from the in-domain monolingual corpus, and p in ( t j ) represents the monolingual probability, which is the phrasal probability for target phrase t j derived from the in-domain monolingual corpus.
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1. A translation method adapted to a domain of interest comprising: receiving a source text string comprising a sequence of source words in a source language; generating a set of candidate translations of the source text string, each candidate translation comprising a sequence of target words in a target language; and with a processor, identifying an optimal translation from the set of candidate translations as a function of at least one domain-adapted feature, the at least one domain-adapted feature being computed based on: bilingual probabilities, each bilingual probability being for a source text fragment and a target text fragment of the source text string and candidate translation respectively, the bilingual probabilities being estimated on an out-of-domain parallel corpus comprising source and target strings; and monolingual probabilities for text fragments of one of the source text string and candidate translation, the monolingual probabilities being estimated on an in-domain monolingual corpus, wherein the domain-adapted feature comprises at least one of: a) a forward domain-adapted lexical feature which is a function of ∑ ( i , j ) ∈ a w in ( s i ❘ t j ) where w in (s i |t j ) is an adapted word probability and is a function of a product of w out (t j |s i ) and w in (s i ); b) a reverse domain-adapted lexical feature which is a function of ∑ ( i , j ) ∈ a w in ( t j ❘ s i ) where w in (t j |s i ) is an adapted word probability and is a function of a product of w out (t j |s i ) and w in (t j ); c) a forward domain-adapted phrasal feature which is a function of: ∑ ( i , j ) ∈ a phr in ( s _ i ❘ t _ j ) , where phr in ( s i | t j ) is an adapted phrase probability and is a function of a product of phr out ( t j | s i ) and p in ( s i ); d) a reverse domain-adapted phrasal feature which is a function of: ∑ ( i , j ) ∈ a phr in ( t _ j ❘ s _ i ) , where phr in ( t j | s i ) is an adapted phrase probability and is a function of a product of phr out ( s i | t j ) and p in ( t j ); where s i and t j represent words of the source string and candidate translation respectively which are aligned in an alignment α of the source string and candidate translation, w out (t j |s i ) represents the bilingual probability, which is a word probability for target word t j in the presence of source word s i , derived from the parallel corpus, and w in (s i ) represents the monolingual probability, which is the word probability for source word s i derived from the in-domain monolingual corpus; s i and t j represent phrases of the source string and candidate translation respectively which are aligned in the alignment α of the source string and candidate translation, phr out ( t j | s i )represents the bilingual probability, which is a phrasal probability for target phrase t j in the presence of source phrase s i , derived from the parallel corpus, p in ( s i ) represents the monolingual probability, which is the phrasal probability for source phrase s i derived from the in-domain monolingual corpus, and p in ( t j ) represents the monolingual probability, which is the phrasal probability for target phrase t j derived from the in-domain monolingual corpus. 10. The method of claim 1 , further comprising learning the weight for the at least one domain-adapted feature using an in-domain parallel corpus different from the out-of-domain parallel corpus used to compute the bilingual probabilities.
| 0.53004 |
1. A board game, comprising: a game board having thereon a plurality of labeled scripture boxes arranged into a plurality of labeled categories, said scripture boxes being contiguous within each said category said categories being arranged in a closed circuit; and a plurality of scripture cards each identified by a corresponding scripture box label, each scripture card having thereon an indicia representing at least one biblical scripture such that each said scripture card is assignable to a corresponding scripture box during the play of the game; a chance box located in said closed circuit between a selected pair of categories; at least one each of a set of chance cards identified by label as CHALLENGE, FEEDBACK, PLAY AGAIN or LOSE TURN; and a plurality of CHALLENGE cards each identifying by label a permutation of challenge among a plurality of players.
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1. A board game, comprising: a game board having thereon a plurality of labeled scripture boxes arranged into a plurality of labeled categories, said scripture boxes being contiguous within each said category said categories being arranged in a closed circuit; and a plurality of scripture cards each identified by a corresponding scripture box label, each scripture card having thereon an indicia representing at least one biblical scripture such that each said scripture card is assignable to a corresponding scripture box during the play of the game; a chance box located in said closed circuit between a selected pair of categories; at least one each of a set of chance cards identified by label as CHALLENGE, FEEDBACK, PLAY AGAIN or LOSE TURN; and a plurality of CHALLENGE cards each identifying by label a permutation of challenge among a plurality of players. 4. The board game of claim 1, wherein each said scripture box is labeled with an attribute selected from a set of about 63 emotional and physical human attributes.
| 0.875 |
10. A method for defining a content relevance model for a particular category, the method comprising: identifying a set of key word sets for the particular category based on an analysis of (i) a first set of content segments previously defined as relevant to the particular category and (ii) a second set of content segments previously defined as not relevant to the particular category; identifying (i) a set of pairs of word sets that each comprise a key word set and a word set that appears in a defined context of the key word set and (ii) a score for each of the word set pairs, the score for a particular word set pair quantifying a likelihood that a content segment containing the particular word set pair is relevant to the particular category, wherein appearances of the particular word set pair in the first set of content segments increase the score for the particular word set pair and appearances of the particular word set pair in the second set of content segments decrease the score for the particular word set pair; and defining a content relevance model for the particular category, the content relevance model comprising (i) a context definition that indicates when a second word set appears within a context of a key word set and (ii) the set of word set pairs and corresponding scores.
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10. A method for defining a content relevance model for a particular category, the method comprising: identifying a set of key word sets for the particular category based on an analysis of (i) a first set of content segments previously defined as relevant to the particular category and (ii) a second set of content segments previously defined as not relevant to the particular category; identifying (i) a set of pairs of word sets that each comprise a key word set and a word set that appears in a defined context of the key word set and (ii) a score for each of the word set pairs, the score for a particular word set pair quantifying a likelihood that a content segment containing the particular word set pair is relevant to the particular category, wherein appearances of the particular word set pair in the first set of content segments increase the score for the particular word set pair and appearances of the particular word set pair in the second set of content segments decrease the score for the particular word set pair; and defining a content relevance model for the particular category, the content relevance model comprising (i) a context definition that indicates when a second word set appears within a context of a key word set and (ii) the set of word set pairs and corresponding scores. 14. The method of claim 10 , wherein a word set appears in the defined context of a key word set when the word set is in the same paragraph as the key word set.
| 0.624432 |
21. A system for processing search results, comprising: one or more computers; and a computer-readable medium coupled to the one or more computers having instructions stored thereon which, when executed by the one or more computers, cause the one or more computers to perform operations comprising: receiving documents responsive to a query, each document having a respective associated score indicative of the document's relevance to the query, wherein: each respective associated score is based on a plurality of different score factors; each score factor for a given associated score corresponds to a different criterion than each other score factor for the given associated score; and each score factor has a respective trustworthiness score that indicates a respective reliability of values determined based on the score factor; determining, based on the trustworthiness scores for the score factors of a plurality of the associated scores of a plurality of different documents, a value-based distribution of the trustworthiness scores for each of the different score factors of the plurality of associated scores along a dimension based on relative values of the trustworthiness scores, the distribution including trustworthiness scores for multiple score factors for each of the different documents; adjusting the value of at least one score factor of a given associated score by an amount that is determined based on: a relative position of the at least one score factor's respective trustworthiness score in the distribution with respect to other trustworthiness scores in the distribution; and a measure of how widely the trustworthiness scores for each of the different score factors of the plurality of associated scores are distributed in the distribution; adjusting the given associated score based on the adjusted value of the at least one score factor; and ranking the documents to account for the adjusted score.
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21. A system for processing search results, comprising: one or more computers; and a computer-readable medium coupled to the one or more computers having instructions stored thereon which, when executed by the one or more computers, cause the one or more computers to perform operations comprising: receiving documents responsive to a query, each document having a respective associated score indicative of the document's relevance to the query, wherein: each respective associated score is based on a plurality of different score factors; each score factor for a given associated score corresponds to a different criterion than each other score factor for the given associated score; and each score factor has a respective trustworthiness score that indicates a respective reliability of values determined based on the score factor; determining, based on the trustworthiness scores for the score factors of a plurality of the associated scores of a plurality of different documents, a value-based distribution of the trustworthiness scores for each of the different score factors of the plurality of associated scores along a dimension based on relative values of the trustworthiness scores, the distribution including trustworthiness scores for multiple score factors for each of the different documents; adjusting the value of at least one score factor of a given associated score by an amount that is determined based on: a relative position of the at least one score factor's respective trustworthiness score in the distribution with respect to other trustworthiness scores in the distribution; and a measure of how widely the trustworthiness scores for each of the different score factors of the plurality of associated scores are distributed in the distribution; adjusting the given associated score based on the adjusted value of the at least one score factor; and ranking the documents to account for the adjusted score. 23. The system of claim 21 , wherein the amount is determined based on a number of intervals in the distribution and the at least one score factor's trustworthiness score.
| 0.646026 |
15. A non-transitory computer-readable medium having computer-executable instructions for execution by at least one processor, that, when executed, cause the at least one processor to: receive a privacy preference specification relative to an indication of at least one user identity of a plurality of user identities for a single user; and generate at least one privacy preference relative to the at least one indication of at least one user identity; associate the at least one privacy preference to at least one information card; wherein the at least one information card is related to the one or more of the selected user identities; and retrieve and determine which of the at least one information card satisfy identity requirements of a security policy, enables the user to select one of the at least one information card determined to satisfy the security policy, and requests an issuance of a security token in reference to the at least one information card selected by the user.
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15. A non-transitory computer-readable medium having computer-executable instructions for execution by at least one processor, that, when executed, cause the at least one processor to: receive a privacy preference specification relative to an indication of at least one user identity of a plurality of user identities for a single user; and generate at least one privacy preference relative to the at least one indication of at least one user identity; associate the at least one privacy preference to at least one information card; wherein the at least one information card is related to the one or more of the selected user identities; and retrieve and determine which of the at least one information card satisfy identity requirements of a security policy, enables the user to select one of the at least one information card determined to satisfy the security policy, and requests an issuance of a security token in reference to the at least one information card selected by the user. 20. The non-transitory computer-readable medium of claim 15 , wherein the instructions further cause the processor to selectively associate the at least one privacy preference to at least one of at least one categorized group of user identity attributes, and a respective user identity attribute in a one-to-one correspondence.
| 0.592686 |
1. Vocabulary building playing cards comprising a deck having a multiplicity of cards, each card displaying symbolic indicia defining a suit designation, there being 4 suits in said deck, each suit having a prescribed number of different value denominaions, the value denominations of each suit being the same as each other suit, at least some of said cards being vocabulary cards having a vocabulary word thereon, each of said vocabulary cards displaying indicia comprising a correct definition and a plurality of incorrect definitions of the respective vocabulary word, indicia defining a different value denomination on each vocabulary card adjacent each correct and each incorrect definition, the value denomination of each vocabulary card being that corresponding to the correct definition of the vocabulary word.
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1. Vocabulary building playing cards comprising a deck having a multiplicity of cards, each card displaying symbolic indicia defining a suit designation, there being 4 suits in said deck, each suit having a prescribed number of different value denominaions, the value denominations of each suit being the same as each other suit, at least some of said cards being vocabulary cards having a vocabulary word thereon, each of said vocabulary cards displaying indicia comprising a correct definition and a plurality of incorrect definitions of the respective vocabulary word, indicia defining a different value denomination on each vocabulary card adjacent each correct and each incorrect definition, the value denomination of each vocabulary card being that corresponding to the correct definition of the vocabulary word. 4. Vocabulary building playing cards as recited in claim 1 wherein at least forty-eight cards are vocabulary cards.
| 0.52381 |
1. A method of teaching music comprising: a) teaching rote understanding of musical skills to the student; b) teaching basic structural elements of music to the student by using a two-line staff; c) teaching a five-line staff to the student; d) teaching rhythm to the student; and e) teaching the integration of steps c) and d) to the student.
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1. A method of teaching music comprising: a) teaching rote understanding of musical skills to the student; b) teaching basic structural elements of music to the student by using a two-line staff; c) teaching a five-line staff to the student; d) teaching rhythm to the student; and e) teaching the integration of steps c) and d) to the student. 4. The method of claim 1, wherein step c) includes the teaching of musical syllables.
| 0.87604 |
1. A computer-implemented method comprising: receiving a search query; obtaining a query language of the search query; obtaining search results responsive to the search query, wherein each search result identifies a respective content item of a plurality of content items, wherein each content item is associated with a plurality of language presentation counts for a plurality of languages, each language presentation count for each particular language representing how many times a plurality of users having a language preference matching the particular language were presented with an opportunity to select the content item, and wherein each content item is associated with a plurality of language selection counts for a plurality of languages, each language selection count for each particular language representing how many times a plurality of users having a language preference matching the particular language selected the content item when presented with an opportunity to select the content item; obtaining a respective language selection weight for the query language for each of the plurality of content items, wherein the language selection weight for the query language for a content item is based on the language presentation count for the query language associated with the content item and the language selection count for the query language associated with the content item; computing a respective score for each of the plurality content items, wherein the score is based on the language selection weight for each of the plurality of content items; generating a ranking of a plurality of content items based at least in part on the respective scores; and providing search results corresponding to the ranking of the plurality of content items in response to the search query.
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1. A computer-implemented method comprising: receiving a search query; obtaining a query language of the search query; obtaining search results responsive to the search query, wherein each search result identifies a respective content item of a plurality of content items, wherein each content item is associated with a plurality of language presentation counts for a plurality of languages, each language presentation count for each particular language representing how many times a plurality of users having a language preference matching the particular language were presented with an opportunity to select the content item, and wherein each content item is associated with a plurality of language selection counts for a plurality of languages, each language selection count for each particular language representing how many times a plurality of users having a language preference matching the particular language selected the content item when presented with an opportunity to select the content item; obtaining a respective language selection weight for the query language for each of the plurality of content items, wherein the language selection weight for the query language for a content item is based on the language presentation count for the query language associated with the content item and the language selection count for the query language associated with the content item; computing a respective score for each of the plurality content items, wherein the score is based on the language selection weight for each of the plurality of content items; generating a ranking of a plurality of content items based at least in part on the respective scores; and providing search results corresponding to the ranking of the plurality of content items in response to the search query. 3. The method of claim 1 , wherein computing the respective score for each of the plurality content items comprises adjusting, for each content item, an initial ranking score for the content item by the language selection weight for the content item.
| 0.897383 |
29. An associative memory method according to claim 27 : wherein observing comprises: observing into the network of entity associative memory networks, the associations among a respective observer entity and a plurality of observed entities that are observed by the respective observer entity, based on the plurality of input documents; observing into the network of document associative memory networks, the associations among observed entities in a respective observer input document; observing into the network of feedback associative memory networks, the associations among a plurality of observed entities for a respective observer positive and/or negative evaluation for a respective task of a respective user; and observing into the network of community associative memory networks, the associations among a respective observer entity, a plurality of observed entities that are observed by the respective observer entity and a plurality of observed tasks of a plurality of users in which the observer entity was queried; and wherein imagining comprises imagining associations of entities, documents, users and/or tasks from the network of entity associative memory networks, the network of document associative memory networks, the network of feedback associative memory networks and the network of community associative memory networks, in response to user queries.
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29. An associative memory method according to claim 27 : wherein observing comprises: observing into the network of entity associative memory networks, the associations among a respective observer entity and a plurality of observed entities that are observed by the respective observer entity, based on the plurality of input documents; observing into the network of document associative memory networks, the associations among observed entities in a respective observer input document; observing into the network of feedback associative memory networks, the associations among a plurality of observed entities for a respective observer positive and/or negative evaluation for a respective task of a respective user; and observing into the network of community associative memory networks, the associations among a respective observer entity, a plurality of observed entities that are observed by the respective observer entity and a plurality of observed tasks of a plurality of users in which the observer entity was queried; and wherein imagining comprises imagining associations of entities, documents, users and/or tasks from the network of entity associative memory networks, the network of document associative memory networks, the network of feedback associative memory networks and the network of community associative memory networks, in response to user queries. 30. An associative memory method according to claim 29 wherein observing into the network of entity associative memory networks and observing into the network of document associative memory networks are preceded by: producing document IDs and document data from the input documents; extracting entities from the document data; and identifying observer entities and observed entities from the entities that are extracted.
| 0.69724 |
21. The method of claim 1 , wherein: each abstract template of the plurality of abstract templates dictates a different manner of displaying information extracted from a resource than any other manner of displaying dictated by any other abstract template of the plurality of abstract templates; and information extracted from the first matching resource is Resource Description Framework (RDF) information extracted from the first matching resource.
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21. The method of claim 1 , wherein: each abstract template of the plurality of abstract templates dictates a different manner of displaying information extracted from a resource than any other manner of displaying dictated by any other abstract template of the plurality of abstract templates; and information extracted from the first matching resource is Resource Description Framework (RDF) information extracted from the first matching resource. 22. One or more storage media storing instructions which, when executed by one or more processors, cause the performance of the method of claim 21 .
| 0.915437 |
1. A system for machine-assisted programming of a target processor which can execute a target programming language, comprising: input means and graphical display means for displaying graphical images in accordance with interactive input by an operator; storage means for storing a representation of a program for said target processor, said program representation being expressed in a definition language; means operatively coupled to said display means, said input means and said storage means for editing said program representation by interactive manipulation of said displayed graphical images; means operatively coupled to said storage means for providing a simulation of an external environment of said target processor, and for simulating execution of said program by said target processor as if said program were expressed in said target programming language and including simulation of interaction of said target processor with said simulation of said environment in accordance with said program; means operatively coupled to said display means, said storage means and said simulation means for displaying said simulated execution of said program; and translation means operatively coupled to said storage means for translating said program representation in said definition language into a corresponding representation in said target programming language.
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1. A system for machine-assisted programming of a target processor which can execute a target programming language, comprising: input means and graphical display means for displaying graphical images in accordance with interactive input by an operator; storage means for storing a representation of a program for said target processor, said program representation being expressed in a definition language; means operatively coupled to said display means, said input means and said storage means for editing said program representation by interactive manipulation of said displayed graphical images; means operatively coupled to said storage means for providing a simulation of an external environment of said target processor, and for simulating execution of said program by said target processor as if said program were expressed in said target programming language and including simulation of interaction of said target processor with said simulation of said environment in accordance with said program; means operatively coupled to said display means, said storage means and said simulation means for displaying said simulated execution of said program; and translation means operatively coupled to said storage means for translating said program representation in said definition language into a corresponding representation in said target programming language. 2. The system of claim 1, wherein said simulated execution of said program is displayed graphically by modification of said displayed graphical images.
| 0.571203 |
11. An apparatus for revealing a document's marked structure, comprising: a look up table; an input adapted to receive a file that is representative of said document; a parser for identifying marked content in said file, said parser comprising: means for parsing said file into markers; means for building a vector of all markers, said vector comprising the function and location of each of said markers; wherein links are established between a vector that holds the tags from a newly read in document to all those tags that are currently held in a look up table, while the document is being parsed; wherein said vector is made of marked content in said document, and locations within a document information stream, when said document is read; an interface for user access to said marked content; means for accessing a glossary for each marker to determine what each marker is and what each marker does; a display for presenting said document and for providing instructions indicating marked structure in said document; wherein an interface is provided such that a person reviewing said document is instructed in the operation and recreation of said document from a casual on-screen review of said document.
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11. An apparatus for revealing a document's marked structure, comprising: a look up table; an input adapted to receive a file that is representative of said document; a parser for identifying marked content in said file, said parser comprising: means for parsing said file into markers; means for building a vector of all markers, said vector comprising the function and location of each of said markers; wherein links are established between a vector that holds the tags from a newly read in document to all those tags that are currently held in a look up table, while the document is being parsed; wherein said vector is made of marked content in said document, and locations within a document information stream, when said document is read; an interface for user access to said marked content; means for accessing a glossary for each marker to determine what each marker is and what each marker does; a display for presenting said document and for providing instructions indicating marked structure in said document; wherein an interface is provided such that a person reviewing said document is instructed in the operation and recreation of said document from a casual on-screen review of said document. 17. The apparatus of claim 11, further comprising: a tutor manager that comprises a document field which identifies a document of interest, and a user activated mode switch that allows a user to select between a learn mode and a performance support mode, wherein said learn mode enables a display for each marked object in said document, and said performance support mode enables a layered display for each marking and one or more next level displays that consist of more detailed information concerning said marking.
| 0.511215 |
3. The method of claim 2 , wherein the computing comprises computing scores only of feasible alternate candidate trees.
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3. The method of claim 2 , wherein the computing comprises computing scores only of feasible alternate candidate trees. 4. The method of claim 3 , wherein the fixed distance term for at least one path includes dimensions of at least one graphic assembly having a fixed area.
| 0.941509 |
1. A computer-readable storage medium configured with data and with instructions that when executed by at least one processor causes the processor(s) to perform a process for compile-time bounds checking of user-defined types, namely, types which are not built-in, the process comprising the following steps performed during compilation of a program from a source code through an intermediate language code to an executable code: identifying in the source code a user-defined class for safely accessing memory, namely, a user-defined class having as an annotated member a memory-accessing code which is annotated with a user-defined-bounds check annotation comprising one or more of: a field-contains bound annotation indicating that a field in the user-defined class contains a bound for the memory-accessing method and a bound-getter method annotation indicating that the bound-getting method in the user-defined class returns a bound for the memory-accessing method, and also having as another annotated member a bound-providing member which is annotated to indicate that it provides bound information for generating a bounds check on the memory-accessing code, wherein the user-defined class is defined free of any multi-element array type as a constituent type; inserting into the intermediate language code a bounds-check representation of the user-defined-bounds check annotation; and applying an optimization which reduces duplicative bounds checking that would otherwise occur in the executable code.
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1. A computer-readable storage medium configured with data and with instructions that when executed by at least one processor causes the processor(s) to perform a process for compile-time bounds checking of user-defined types, namely, types which are not built-in, the process comprising the following steps performed during compilation of a program from a source code through an intermediate language code to an executable code: identifying in the source code a user-defined class for safely accessing memory, namely, a user-defined class having as an annotated member a memory-accessing code which is annotated with a user-defined-bounds check annotation comprising one or more of: a field-contains bound annotation indicating that a field in the user-defined class contains a bound for the memory-accessing method and a bound-getter method annotation indicating that the bound-getting method in the user-defined class returns a bound for the memory-accessing method, and also having as another annotated member a bound-providing member which is annotated to indicate that it provides bound information for generating a bounds check on the memory-accessing code, wherein the user-defined class is defined free of any multi-element array type as a constituent type; inserting into the intermediate language code a bounds-check representation of the user-defined-bounds check annotation; and applying an optimization which reduces duplicative bounds checking that would otherwise occur in the executable code. 17. The configured medium of claim 1 , wherein the user-defined class wraps a built-in managed type.
| 0.688944 |
8. A non-transitory computer readable medium encoded with a plurality of instructions that, when executed by a computer, perform a method comprising: receiving, from a speech recognition component, one or more words corresponding to a voice input; searching a product information management (PIM) component to identify at least one matching item and/or category in a product catalog based, at least in part, on the one or more received words and at least one item attribute associated with at least one item and/or at least one category attribute associated with at least one category in the PIM component; and outputting coded results to a voice synthesis component in response to the search, wherein the coded results indicate whether the search resulted in the identification of at least one matching item and/or category in the PIM component.
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8. A non-transitory computer readable medium encoded with a plurality of instructions that, when executed by a computer, perform a method comprising: receiving, from a speech recognition component, one or more words corresponding to a voice input; searching a product information management (PIM) component to identify at least one matching item and/or category in a product catalog based, at least in part, on the one or more received words and at least one item attribute associated with at least one item and/or at least one category attribute associated with at least one category in the PIM component; and outputting coded results to a voice synthesis component in response to the search, wherein the coded results indicate whether the search resulted in the identification of at least one matching item and/or category in the PIM component. 9. The computer-readable medium of claim 8 , wherein the PIM component is configured to organize items, categories, and sub categories in a hierarchical structure of levels, wherein at least some levels of the hierarchical structure are associated with one or more attributes, and wherein searching the PIM component comprises searching the PIM component based, at least in part, on the one or more attributes associated with the levels of the hierarchical structure.
| 0.638679 |
1. A method performed by a device, the method comprising: identifying, by a processor of the device, a plurality of documents, where a first one of the identified documents is linked by a second one of the identified documents and the second document is one of a plurality of documents in an affiliated set of documents; calculating, by the processor, a first value for each document in the affiliated set of documents based on a ranking score of the document and a number of outbound links from the document; calculating, by the processor, a second value as a maximum of the first values for the documents in the affiliated set of documents; assigning, by the processor, a ranking score to the first document based the second value, where assigning the ranking score includes: determining whether the documents in the affiliated set of documents are weakly affiliated or strongly affiliated, and setting the amount that the second document contributes to the ranking score of the first document as a function that acts as a summation operator over the affiliated set of documents when the affiliated set is weakly affiliated and as a maximum operator over the affiliated set of documents when the affiliated set is strongly affiliated, where the function is defined as:
(CONTRIB(D 1 ) a +CONTRIB(D 2 ) a + . . . +CONTRIB(D k ) a ) 1/a , where CONTRIB for document D k represents an individual ranking score contribution for document k in the affiliated set, and a is defined as 1 ⅇ + ( 1 - ⅇ ) γ , where e is a constant and γ represents a continuous measure of the affiliation of the documents in the affiliated set; and storing, by the processor, the ranking score.
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1. A method performed by a device, the method comprising: identifying, by a processor of the device, a plurality of documents, where a first one of the identified documents is linked by a second one of the identified documents and the second document is one of a plurality of documents in an affiliated set of documents; calculating, by the processor, a first value for each document in the affiliated set of documents based on a ranking score of the document and a number of outbound links from the document; calculating, by the processor, a second value as a maximum of the first values for the documents in the affiliated set of documents; assigning, by the processor, a ranking score to the first document based the second value, where assigning the ranking score includes: determining whether the documents in the affiliated set of documents are weakly affiliated or strongly affiliated, and setting the amount that the second document contributes to the ranking score of the first document as a function that acts as a summation operator over the affiliated set of documents when the affiliated set is weakly affiliated and as a maximum operator over the affiliated set of documents when the affiliated set is strongly affiliated, where the function is defined as:
(CONTRIB(D 1 ) a +CONTRIB(D 2 ) a + . . . +CONTRIB(D k ) a ) 1/a , where CONTRIB for document D k represents an individual ranking score contribution for document k in the affiliated set, and a is defined as 1 ⅇ + ( 1 - ⅇ ) γ , where e is a constant and γ represents a continuous measure of the affiliation of the documents in the affiliated set; and storing, by the processor, the ranking score. 4. The method of claim 1 , wherein identifying a plurality of documents includes: identifying the plurality of documents by matching terms in a search query to terms in a collection of documents.
| 0.564796 |
21. A non-transitory computer readable medium including code that when executed by a computer system performs a method of assigning content with an entry in a directory, the method comprising: receiving content; parsing the content into text phrases; determining mappings between each entry in the directory and information in name fields of the directory; for each phrase, determining one or more name proposals for the phrase using the mappings, wherein each name proposal identifies a potential match between the content and one or more entries in the directory; and assigning the content to an entry in the directory associated with a name proposal of the one or more name proposals, wherein determining one or more name proposals for the phrase using the mappings comprises: parsing each phrase into tokens, wherein the tokens in the phrase are identified in a window having a size approximated by a size of a largest name; and determining the one or more name proposals for the tokens.
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21. A non-transitory computer readable medium including code that when executed by a computer system performs a method of assigning content with an entry in a directory, the method comprising: receiving content; parsing the content into text phrases; determining mappings between each entry in the directory and information in name fields of the directory; for each phrase, determining one or more name proposals for the phrase using the mappings, wherein each name proposal identifies a potential match between the content and one or more entries in the directory; and assigning the content to an entry in the directory associated with a name proposal of the one or more name proposals, wherein determining one or more name proposals for the phrase using the mappings comprises: parsing each phrase into tokens, wherein the tokens in the phrase are identified in a window having a size approximated by a size of a largest name; and determining the one or more name proposals for the tokens. 22. The non-transitory computer readable medium of claim 21 , wherein determining one or more name proposals for the phrase using the mappings further comprises: identifying mappings for adjacent non-overlapping tokens for the phrase; and determining the one or more name proposals from the identified mappings for the adjacent non-overlapping tokens.
| 0.601792 |
9. 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: receiving a stress pattern for both a language and an accent in the language; detecting, according to the stress pattern, incorrect stress patterns in selected acoustic units representing speech to be synthesized, wherein the selected acoustic units were selected by a separate unit-selection speech synthesizer; performing an analysis of the incorrect stress patterns, wherein the analysis comprises a word level analysis, a phrase level analysis, and a sentence level analysis on the incorrect stress patterns, wherein the word level analysis, the phrase level analysis, and the sentence level analysis are performed in series; and modifying, via a processor and prior to waveform synthesis, the incorrect stress patterns in the selected acoustic units according to the analysis, to yield corrected stress patterns, wherein the corrected stress patterns conform to the stress pattern for the language.
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9. 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: receiving a stress pattern for both a language and an accent in the language; detecting, according to the stress pattern, incorrect stress patterns in selected acoustic units representing speech to be synthesized, wherein the selected acoustic units were selected by a separate unit-selection speech synthesizer; performing an analysis of the incorrect stress patterns, wherein the analysis comprises a word level analysis, a phrase level analysis, and a sentence level analysis on the incorrect stress patterns, wherein the word level analysis, the phrase level analysis, and the sentence level analysis are performed in series; and modifying, via a processor and prior to waveform synthesis, the incorrect stress patterns in the selected acoustic units according to the analysis, to yield corrected stress patterns, wherein the corrected stress patterns conform to the stress pattern for the language. 13. The system of claim 9 , the computer-readable storage medium having additional instructions stored which, when executed by the processor, result in operations comprising synthesizing speech according to the corrected stress patterns.
| 0.5 |
37. An optical disc player for reproducing text subtitle streams recorded on an optical disc, the optical disc player comprising: an audio decoder configured to decode audio streams recorded on the optical disc into audio data; a video decoder configured to decode video streams recorded on the optical disc into video image data; a text subtitle decoder configured to decode a text subtitle stream recorded on the optical disc into text subtitle image data; and an image superimposition unit configured to superimpose the decoded text subtitle image data with the decoded video image data, wherein the text subtitle decoder comprises: a text subtitle processor configured to parse the text subtitle stream into composition information, rendering information, and text data for at least one region, the text data including one or more text strings for each region; a text renderer configured to render the text strings into graphic data for each region according to the rendering information; and a presentation controller configured to compose the rendered graphic data according to the composition information.
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37. An optical disc player for reproducing text subtitle streams recorded on an optical disc, the optical disc player comprising: an audio decoder configured to decode audio streams recorded on the optical disc into audio data; a video decoder configured to decode video streams recorded on the optical disc into video image data; a text subtitle decoder configured to decode a text subtitle stream recorded on the optical disc into text subtitle image data; and an image superimposition unit configured to superimpose the decoded text subtitle image data with the decoded video image data, wherein the text subtitle decoder comprises: a text subtitle processor configured to parse the text subtitle stream into composition information, rendering information, and text data for at least one region, the text data including one or more text strings for each region; a text renderer configured to render the text strings into graphic data for each region according to the rendering information; and a presentation controller configured to compose the rendered graphic data according to the composition information. 46. The optical disc player of claim 37 , wherein the presentation controller is configured to control the text render.
| 0.845624 |
21. A system, comprising: one or more processors; and a computer-readable storage device coupled to the one or more processors and having instructions stored thereon which, when executed by the one or more processors, cause the one or more processors to perform operations for providing an explanatory electronic document, the operations comprising: receiving, by the one or more processors, input from a user, the input comprising data that is at least partially representative of a subject; performing, by the one or more processors, semantic context association based on the user input, one or more computer-readable ontologies, and a computer-readable knowledge graph to provide a target subject profile, the target subject profile comprising two or more associations describing the subject at respective degrees of specificity, at least one association comprising concepts from the knowledge graph that are more general than respective entities provided in the input; providing, by the one or more processors, a set of peer user profiles based on a user profile and a superset of peer user profiles using semantic user profile association between the user profile and each peer user profile in the superset of peer user profiles; retrieving, by the one or more processors, one or more peer subject profiles from computer-readable memory, each peer subject profile being associated with a peer user profile in the set of peer user profiles, and comprising one or more associations, each association describing a past subject experienced by a peer user; filtering, by the one or more processors, at least one association from a peer subject profile based on a comparison with a respective association in the target subject profile and data provided in a knowledge graph; providing, by the one or more processors, at least one explanatory text string associated with the subject based on at least one remaining association in the peer subject profile; and providing, by the one or more processors, the explanatory electronic document comprising the at least one explanatory text string.
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21. A system, comprising: one or more processors; and a computer-readable storage device coupled to the one or more processors and having instructions stored thereon which, when executed by the one or more processors, cause the one or more processors to perform operations for providing an explanatory electronic document, the operations comprising: receiving, by the one or more processors, input from a user, the input comprising data that is at least partially representative of a subject; performing, by the one or more processors, semantic context association based on the user input, one or more computer-readable ontologies, and a computer-readable knowledge graph to provide a target subject profile, the target subject profile comprising two or more associations describing the subject at respective degrees of specificity, at least one association comprising concepts from the knowledge graph that are more general than respective entities provided in the input; providing, by the one or more processors, a set of peer user profiles based on a user profile and a superset of peer user profiles using semantic user profile association between the user profile and each peer user profile in the superset of peer user profiles; retrieving, by the one or more processors, one or more peer subject profiles from computer-readable memory, each peer subject profile being associated with a peer user profile in the set of peer user profiles, and comprising one or more associations, each association describing a past subject experienced by a peer user; filtering, by the one or more processors, at least one association from a peer subject profile based on a comparison with a respective association in the target subject profile and data provided in a knowledge graph; providing, by the one or more processors, at least one explanatory text string associated with the subject based on at least one remaining association in the peer subject profile; and providing, by the one or more processors, the explanatory electronic document comprising the at least one explanatory text string. 25. The system of claim 21 , wherein the explanatory electronic document provides explanations related to one or more expenses incurred, the at least one explanatory text string being associated with a respective expense.
| 0.635652 |
1. A computer based exercise method comprising the steps of: providing an exercise machine on which a person exercises, wherein said exercise machine resists the effort of said person when exercising; providing a computer and a computer-controlled video display for viewing by said person; electro-optically determining data concerning a plurality of points on at least one of said person and said machine; processing said data to determine a variable related to one or more of said points; and using said determined variable, controlling a video game program in said computer.
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1. A computer based exercise method comprising the steps of: providing an exercise machine on which a person exercises, wherein said exercise machine resists the effort of said person when exercising; providing a computer and a computer-controlled video display for viewing by said person; electro-optically determining data concerning a plurality of points on at least one of said person and said machine; processing said data to determine a variable related to one or more of said points; and using said determined variable, controlling a video game program in said computer. 16. A method according to claim 1 wherein said video game is designed to allow reliable sensing of said points while undertaking said game.
| 0.5 |
4. The one or more computer storage media of claim 1 , wherein the method further comprises: receiving user input that selects a first predefined type in one of the one or more fields; and in response to the selection of the first predefined type, displaying one or more additional user interface controls that the user can manipulate to define configurable parameters specific to the first predefined type.
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4. The one or more computer storage media of claim 1 , wherein the method further comprises: receiving user input that selects a first predefined type in one of the one or more fields; and in response to the selection of the first predefined type, displaying one or more additional user interface controls that the user can manipulate to define configurable parameters specific to the first predefined type. 5. The one or more computer storage media of claim 4 , wherein the one or more additional user interface controls include a node path field for receiving a node path, the node path field including a button for launching a node path lookup dialogue, the method further comprising: receiving user input that selects the button; displaying the node path lookup dialogue that includes a sample message; receiving user input that selects a node in the sample message; and automatically creating a node path to the selected node in the node path field.
| 0.863455 |
9. A non-transitory computer-readable storage medium storing instructions that when executed by a computer cause the computer to perform a method for graph pruning, comprising: storing in a storage device of a computer a data set comprising a plurality of data elements; determining, by the computer, a type and strength of relationship between a data element pair in the plurality of data elements; representing the type and strength of relationship as an edge between a vertex pair representing the data element pair in a graph; determining a minimum graph traversal threshold associated with an input query received by the computer for the graph, wherein the minimum graph traversal threshold indicates a minimum number of traversal steps needed for the input query in the graph; identifying that a number of traversal steps for a first connected component in the graph is greater than or equal to the minimum graph traversal threshold, and wherein a connected component includes a set of one or more vertices, which are coupled to each other via edges and are not couple to a vertex outside of the set; identifying that a number of traversal steps for a second connected component in the graph is smaller than the minimum graph traversal threshold; generating a second graph comprising the first connected component by pruning the second connected component from the graph; and processing the input query on the second graph to extract information of interest from the data set.
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9. A non-transitory computer-readable storage medium storing instructions that when executed by a computer cause the computer to perform a method for graph pruning, comprising: storing in a storage device of a computer a data set comprising a plurality of data elements; determining, by the computer, a type and strength of relationship between a data element pair in the plurality of data elements; representing the type and strength of relationship as an edge between a vertex pair representing the data element pair in a graph; determining a minimum graph traversal threshold associated with an input query received by the computer for the graph, wherein the minimum graph traversal threshold indicates a minimum number of traversal steps needed for the input query in the graph; identifying that a number of traversal steps for a first connected component in the graph is greater than or equal to the minimum graph traversal threshold, and wherein a connected component includes a set of one or more vertices, which are coupled to each other via edges and are not couple to a vertex outside of the set; identifying that a number of traversal steps for a second connected component in the graph is smaller than the minimum graph traversal threshold; generating a second graph comprising the first connected component by pruning the second connected component from the graph; and processing the input query on the second graph to extract information of interest from the data set. 14. The non-transitory computer-readable storage medium of claim 9 , wherein the method further comprises: assigning a label to a respective vertex in the graph; propagating a label from a first vertex to a second vertex; and identifying a set of vertices associated with the same label.
| 0.598095 |
10. A system for facilitating a translation and sampling the translation to determine an overall quality thereof, the system comprising: a first computer and a second computer operably connected to a database; the first computer comprising a first processor and first memory device operably connected to one another to operate as a translator workstation; the first computer, wherein the first processor is programmed to execute a translation assisting software module that assists a human translator by retrieving, from the database, a source document and storing, to the database, a target document that is a translation of the source document; the second computer comprising a second processor and second memory device operably connected to one another to operate as a reviewer work station; the second computer, wherein the second processor is programmed to execute a quality quantifying software module that operates to assist a human reviewer by retrieving a sample from the database, the sample comprising substantially less than an entirety of the translation, a subset of the target document, and a corresponding subset of the source document, providing a list of preset error categories, receiving selections from a reviewer as selected from the preset error categories, and generalizing the selections associated with the sample into an overall quality characterization of the entirety of the translation.
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10. A system for facilitating a translation and sampling the translation to determine an overall quality thereof, the system comprising: a first computer and a second computer operably connected to a database; the first computer comprising a first processor and first memory device operably connected to one another to operate as a translator workstation; the first computer, wherein the first processor is programmed to execute a translation assisting software module that assists a human translator by retrieving, from the database, a source document and storing, to the database, a target document that is a translation of the source document; the second computer comprising a second processor and second memory device operably connected to one another to operate as a reviewer work station; the second computer, wherein the second processor is programmed to execute a quality quantifying software module that operates to assist a human reviewer by retrieving a sample from the database, the sample comprising substantially less than an entirety of the translation, a subset of the target document, and a corresponding subset of the source document, providing a list of preset error categories, receiving selections from a reviewer as selected from the preset error categories, and generalizing the selections associated with the sample into an overall quality characterization of the entirety of the translation. 18. The system of claim 10 , wherein the database stores translator records, each translator record thereof identifying a human translator and corresponding the human translator with target text translated by the human translator.
| 0.610135 |
12. A computer program product comprising a computer readable storage medium having a computer readable program stored therein, wherein the computer readable program, when executed on a computing device, causes the computing device to: identify a set of features that contribute to generating candidate answers for input questions; identify a set of annotation engines in the ingestion pipeline that contribute to each of the set of features and at least one annotation engine on which the one or more annotation engines depend; generate a sub-pipeline for each set of annotation engines to form a plurality of sub-pipelines of annotation engines; receive new content to be ingested into a corpus of information; apply a plurality of sub-pipelines of annotation engines against the new content in order of effectiveness, wherein the plurality of sub-pipelines include all annotation engines of an ingestion pipeline and wherein each sub-pipeline within the plurality of sub-pipelines generates one or more intermediate output objects; and provide access to the one or more intermediate output objects, wherein the one or more intermediate output objects represent the partially ingested new content.
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12. A computer program product comprising a computer readable storage medium having a computer readable program stored therein, wherein the computer readable program, when executed on a computing device, causes the computing device to: identify a set of features that contribute to generating candidate answers for input questions; identify a set of annotation engines in the ingestion pipeline that contribute to each of the set of features and at least one annotation engine on which the one or more annotation engines depend; generate a sub-pipeline for each set of annotation engines to form a plurality of sub-pipelines of annotation engines; receive new content to be ingested into a corpus of information; apply a plurality of sub-pipelines of annotation engines against the new content in order of effectiveness, wherein the plurality of sub-pipelines include all annotation engines of an ingestion pipeline and wherein each sub-pipeline within the plurality of sub-pipelines generates one or more intermediate output objects; and provide access to the one or more intermediate output objects, wherein the one or more intermediate output objects represent the partially ingested new content. 13. The computer program product of claim 12 , wherein generating a sub-pipeline for each set of annotation engines comprises: determining performance or runtime cost of each annotation engine in the ingestion pipeline; determining an efficiency score for each set of annotation engines based on the performance or runtime costs of the set of annotation engines and a feature score weighting of a corresponding feature; and ranking the sub-pipelines by efficiency score.
| 0.556791 |
7. A computer implemented method of assigning grammatical elements using a computer with a processor; comprising: performing, with the processor, machine translation on a source language text fragment to obtain a target language text fragment; receiving the target language text fragment generated from the source language text fragment; after the target language text fragment is received, accessing, with the processor, a statistical grammatical element prediction model to assign grammatical elements, comprising words without semantic meaning, to the target language text fragment to obtain a first form of the target language text fragment that includes assigned grammatical elements, the statistical grammatical element prediction model predicting grammatical elements for portions of the target language text fragment using both monolingual features of the target language and bilingual features of both the source language and the target language; generating additional forms of the target language text fragment by using the statistical grammatical element prediction model to vary only grammatical elements assigned to the target language text fragment received; and ranking the first form and additional forms of the target language text fragment based on an accuracy measure indicative of an accuracy of the grammatical elements assigned to the first form and the additional forms, wherein the accuracy measure includes a count of the words without semantic meaning added to each of the additional forms.
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7. A computer implemented method of assigning grammatical elements using a computer with a processor; comprising: performing, with the processor, machine translation on a source language text fragment to obtain a target language text fragment; receiving the target language text fragment generated from the source language text fragment; after the target language text fragment is received, accessing, with the processor, a statistical grammatical element prediction model to assign grammatical elements, comprising words without semantic meaning, to the target language text fragment to obtain a first form of the target language text fragment that includes assigned grammatical elements, the statistical grammatical element prediction model predicting grammatical elements for portions of the target language text fragment using both monolingual features of the target language and bilingual features of both the source language and the target language; generating additional forms of the target language text fragment by using the statistical grammatical element prediction model to vary only grammatical elements assigned to the target language text fragment received; and ranking the first form and additional forms of the target language text fragment based on an accuracy measure indicative of an accuracy of the grammatical elements assigned to the first form and the additional forms, wherein the accuracy measure includes a count of the words without semantic meaning added to each of the additional forms. 8. The method of claim 7 wherein the source language text fragment includes a source parse tree from a natural language parse of the source language text fragment, and wherein assigning grammatical elements comprises: assigning the grammatical elements to the target language text fragment based on information in the source parse tree.
| 0.646271 |
1. A method of hosting electronic conversations, comprising: at a computer system having one or more processors and memory storing programs for execution by the one or more processors, maintaining a plurality of conversations, each having an identified set of participants; maintaining for each respective participant in one or more of the conversations, a respective participant-specific inverse index of terms in conversations for which the respective participant is an identified participant; in response to receiving a search query from a first participant of a first conversation in the plurality of conversations: using the participant-specific inverse index corresponding to the first participant to identify a second conversation in the plurality of conversations as relevant to the search query, and formatting all or a portion of the second conversation for display to the first participant; wherein the plurality of conversations are instant messaging conversations, and participants in each conversation in the plurality of conversations are instant messaging participants.
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1. A method of hosting electronic conversations, comprising: at a computer system having one or more processors and memory storing programs for execution by the one or more processors, maintaining a plurality of conversations, each having an identified set of participants; maintaining for each respective participant in one or more of the conversations, a respective participant-specific inverse index of terms in conversations for which the respective participant is an identified participant; in response to receiving a search query from a first participant of a first conversation in the plurality of conversations: using the participant-specific inverse index corresponding to the first participant to identify a second conversation in the plurality of conversations as relevant to the search query, and formatting all or a portion of the second conversation for display to the first participant; wherein the plurality of conversations are instant messaging conversations, and participants in each conversation in the plurality of conversations are instant messaging participants. 2. The method of claim 1 , further comprising maintaining for the first participant a list of conversations in which the first participant is a participant, updating a status of each such conversation in the list when a state of the respective conversation changes, and sending to the first participant a list that comprises at least a portion of the list of conversations in which the first participant is a participant, the list sent to the first participant including status information for the listed conversations.
| 0.578947 |
7. The electronic interface of claim 6 wherein the text description is automatically extracted from text of the document other than a caption of the figure.
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7. The electronic interface of claim 6 wherein the text description is automatically extracted from text of the document other than a caption of the figure. 8. The electronic interface of claim 7 wherein the text description provides at least one sentence selected to address categories of: introduction, methods, results, and discussion of the document generated from the text of the document.
| 0.872857 |
13. The method of claim 12 , further comprising: iteratively displaying additional portions of the text sample to the user, and dynamically assembling additional domain-specific target language models respectively based on each of the additional portions of the text sample while they are being displayed.
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13. The method of claim 12 , further comprising: iteratively displaying additional portions of the text sample to the user, and dynamically assembling additional domain-specific target language models respectively based on each of the additional portions of the text sample while they are being displayed. 17. The method of claim 13 , wherein a miscue is identified with one or more miscue categories and the user-perceptible feedback is based in part on one of the miscue categories with which the miscue in the acoustic input is identified, wherein the miscue categories comprise one or more of: word repetition, breath, partial word, pause, hesitation or elongation, wrong word, mispronunciation, background noise, interjection or insertion, non-speech sound, and hyperarticulation.
| 0.770103 |
2. The apparatus of claim 1 , comprising: a digital-to-analog (D/A) converter connected to receive the time domain digital output and convert it to analog signals.
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2. The apparatus of claim 1 , comprising: a digital-to-analog (D/A) converter connected to receive the time domain digital output and convert it to analog signals. 3. The apparatus of claim 2 , comprising: a receiver to convert the analog signals to sound.
| 0.967282 |
1. A computer-implemented method for optimal partitioning of segments in a consumer credit segmentation tree comprising: generating by a computer a first attribute-based independent variable on a segmentation tree using a primary dependent variable having two classes, wherein a value of the independent variable is selected that creates two groups that minimize misclassification of the two classes of the primary dependent variable; generating by the computer a second attribute-based independent variable on the tree using the primary dependent variable; generating by the computer risk tiers for the first attribute-based independent variable on the tree using a first risk score and the primary dependent variable, wherein values of the independent variable are selected that create two groups that minimize misclassification of the two classes of the primary dependent variable; generating by the computer risk tiers for a first segment of the second attribute-based independent variable on the tree using the first risk score and the primary dependent variable, wherein values of the independent variable are selected that create two groups that minimize misclassification of the two classes of the primary dependent variable; generating by the computer risk tiers for a second segment of the second attribute-based independent variable on the tree using a second risk score and the primary dependent variable; and generating by the computer profiles in the risk tiers for the second segment of the second attribute-based independent variable with a profile dependent variable having two classes to complete the tree, wherein values of a profile model are selected that create two groups that minimize misclassification of the two classes of the profile dependent variable.
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1. A computer-implemented method for optimal partitioning of segments in a consumer credit segmentation tree comprising: generating by a computer a first attribute-based independent variable on a segmentation tree using a primary dependent variable having two classes, wherein a value of the independent variable is selected that creates two groups that minimize misclassification of the two classes of the primary dependent variable; generating by the computer a second attribute-based independent variable on the tree using the primary dependent variable; generating by the computer risk tiers for the first attribute-based independent variable on the tree using a first risk score and the primary dependent variable, wherein values of the independent variable are selected that create two groups that minimize misclassification of the two classes of the primary dependent variable; generating by the computer risk tiers for a first segment of the second attribute-based independent variable on the tree using the first risk score and the primary dependent variable, wherein values of the independent variable are selected that create two groups that minimize misclassification of the two classes of the primary dependent variable; generating by the computer risk tiers for a second segment of the second attribute-based independent variable on the tree using a second risk score and the primary dependent variable; and generating by the computer profiles in the risk tiers for the second segment of the second attribute-based independent variable with a profile dependent variable having two classes to complete the tree, wherein values of a profile model are selected that create two groups that minimize misclassification of the two classes of the profile dependent variable. 6. The method of claim 1 , wherein only a portion of the population characterized as bad is used to define the profiles.
| 0.859629 |
8. The system of claim 1 , wherein said dialog delivery system includes a dialog analysis processor.
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8. The system of claim 1 , wherein said dialog delivery system includes a dialog analysis processor. 11. The system of claim 8 , wherein said dialog analysis processor provides a tree representation of said dialog identifying paths and logic associated with decisions within the tree.
| 0.852381 |
6. The method of claim 1 wherein weighting of collaborative filtering favorites metadata is R cf
R cf,l =W sim ( S max,l )+(1− W sim ) P 1 , where: W sim = similarity weighting factor = C ma x sim ( 1 - 1 1 + n i ) , where: 0≦C max sim ≦1.
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6. The method of claim 1 wherein weighting of collaborative filtering favorites metadata is R cf
R cf,l =W sim ( S max,l )+(1− W sim ) P 1 , where: W sim = similarity weighting factor = C ma x sim ( 1 - 1 1 + n i ) , where: 0≦C max sim ≦1. 7. The method of claim 6 wherein R cf is a weighted sum of the maximum user similarity for an item l and the popularity of item l among K-Nearest Neighbors such that 0≦R cf ≦1.
| 0.918508 |
17. A speech recognition method comprising: initiating, by a computer system, a state of a computer program; selecting, by the computer system, a state recognition set based on the state of the computer program; detecting, by the computer system a gesture of at least one part of a human body; receiving, by the computer system, a speech input signal; and recognizing, by the computer system, the speech input signal in the context of a recognition set, the recognition set being a subset of the state recognition set, the recognizing resulting in a first recognition result; weighting, by the computer system, the first recognition result according to a function associated with the gesture; and determining, by the computer system, a second recognition result based on the weighting.
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17. A speech recognition method comprising: initiating, by a computer system, a state of a computer program; selecting, by the computer system, a state recognition set based on the state of the computer program; detecting, by the computer system a gesture of at least one part of a human body; receiving, by the computer system, a speech input signal; and recognizing, by the computer system, the speech input signal in the context of a recognition set, the recognition set being a subset of the state recognition set, the recognizing resulting in a first recognition result; weighting, by the computer system, the first recognition result according to a function associated with the gesture; and determining, by the computer system, a second recognition result based on the weighting. 20. The method of claim 17 wherein the gesture includes motion.
| 0.668515 |
11. A method of interacting through speech with a web-connected server system using a browser program, the method comprising the steps of: establishing a connection between a client device and the web-connected server for communicating speech related data; providing a variable distributed speech recognition engine configured to generate a recognized speech query from an utterance; wherein said variable distributed speech recognition engine can be configured to permit partial or full recognition of said utterance at said client device and/or a server device based on respective resources available to said client device and server device and further considering a latency requirement specified for said speech query; presenting data content associated with one or more web pages to the browser program, such that data content transmitted to the browser program is controlled by said recognized speech query.
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11. A method of interacting through speech with a web-connected server system using a browser program, the method comprising the steps of: establishing a connection between a client device and the web-connected server for communicating speech related data; providing a variable distributed speech recognition engine configured to generate a recognized speech query from an utterance; wherein said variable distributed speech recognition engine can be configured to permit partial or full recognition of said utterance at said client device and/or a server device based on respective resources available to said client device and server device and further considering a latency requirement specified for said speech query; presenting data content associated with one or more web pages to the browser program, such that data content transmitted to the browser program is controlled by said recognized speech query. 19. The method of claim 11 , wherein said speech recognition engine is distributed between a client device and a server device which receives streaming speech data having reduced latency data content before silence is detected and the utterance is complete.
| 0.5 |
43. A microprocessor-based device with improved user input capability comprising: a device having a microprocessor, a memory, a display, and a set of input keys, said device requiring input of information by a user, said display for displaying input controls for receiving input in response to user activation of at least some of said input keys said input including user-supplied information for input into said device; initialization logic for initializing all input controls to an activated and an unfilled state; control logic operating to: set focus of input to a first located input control that is activated and unfilled if one is located, and otherwise transfer control to navigation logic of the device; entry logic operating to: process input by a user at an input control currently having focus and thereafter mark the input control as filled and transfer control to the control logic of the device, and otherwise transfer focus to a prior input control that is activated and unfilled; and navigation logic operating to: set, in response to a forward navigation request from the user, focus of input to a next located input control that is activated and unfilled if one exists, set, in response to a backward navigation request from the user, focus of input to a prior input control that is activated and unfilled if one exists, and transfer, in response to an edit request from the user, control to the entry logic of the device.
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43. A microprocessor-based device with improved user input capability comprising: a device having a microprocessor, a memory, a display, and a set of input keys, said device requiring input of information by a user, said display for displaying input controls for receiving input in response to user activation of at least some of said input keys said input including user-supplied information for input into said device; initialization logic for initializing all input controls to an activated and an unfilled state; control logic operating to: set focus of input to a first located input control that is activated and unfilled if one is located, and otherwise transfer control to navigation logic of the device; entry logic operating to: process input by a user at an input control currently having focus and thereafter mark the input control as filled and transfer control to the control logic of the device, and otherwise transfer focus to a prior input control that is activated and unfilled; and navigation logic operating to: set, in response to a forward navigation request from the user, focus of input to a next located input control that is activated and unfilled if one exists, set, in response to a backward navigation request from the user, focus of input to a prior input control that is activated and unfilled if one exists, and transfer, in response to an edit request from the user, control to the entry logic of the device. 44. The device of claim 43, wherein said set of input keys comprises a terse key set.
| 0.694998 |
16. The apparatus of claim 1, wherein the document framework includes retrieval framework means for providing indexing and query processing.
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16. The apparatus of claim 1, wherein the document framework includes retrieval framework means for providing indexing and query processing. 17. The apparatus of claim 16, wherein the retrieval framework means includes background indexing.
| 0.955191 |
1. A processor-implemented method for automatic labeling of natural language text, the method comprising: receiving text from at least one natural language document in electronic form; performing, using a processor, a basic linguistic analysis of the text that includes recognizing cause-effect relationships in the text and generating cause-effect labels for words or phrases in the text that form part of the cause-effect relationships; matching the linguistically analyzed text and the generated cause-effect labels against stored target semantic relationship patterns, wherein the stored target semantic relationship patterns generically describe semantic relationships between words or phrases, the stored target semantic relationships being derived in part from cause-effect relationships between words or phrases; producing additional semantic relationship labels for the linguistically analyzed text based on the matching of the linguistically analyzed text and the generated cause-effect labels against the stored target semantic relationship patterns, wherein the additional semantic relationship labels are tagged to words or phrases from sentences within the linguistically analyzed text in order to identify semantic relationships between those words or phrases by identifying those words or phrases as components of semantic relationships of the stored target semantic relationship patterns; and storing the linguistically analyzed text and the additional semantic relationship labels in a non-transitory storage medium.
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1. A processor-implemented method for automatic labeling of natural language text, the method comprising: receiving text from at least one natural language document in electronic form; performing, using a processor, a basic linguistic analysis of the text that includes recognizing cause-effect relationships in the text and generating cause-effect labels for words or phrases in the text that form part of the cause-effect relationships; matching the linguistically analyzed text and the generated cause-effect labels against stored target semantic relationship patterns, wherein the stored target semantic relationship patterns generically describe semantic relationships between words or phrases, the stored target semantic relationships being derived in part from cause-effect relationships between words or phrases; producing additional semantic relationship labels for the linguistically analyzed text based on the matching of the linguistically analyzed text and the generated cause-effect labels against the stored target semantic relationship patterns, wherein the additional semantic relationship labels are tagged to words or phrases from sentences within the linguistically analyzed text in order to identify semantic relationships between those words or phrases by identifying those words or phrases as components of semantic relationships of the stored target semantic relationship patterns; and storing the linguistically analyzed text and the additional semantic relationship labels in a non-transitory storage medium. 2. The method according to claim 1 , further comprising: applying parts-of-speech tags to at least portions of the text to generate tagged portions of the text; parsing the tagged portions of the text to generate parsed and tagged portions of the text; and wherein performing, using the processor, the basic linguistic analysis of the text includes semantically analyzing the parsed and tagged portions of the text to generate semantically analyzed, parsed and tagged portions of the text.
| 0.603244 |
9. A server computer system comprising: at least one processor; and memory storing instructions that, when executed by the at least one processor, cause the computer system to: receive, from a client system distinct from the server computer system, a search query having one or more query terms; in response to receiving the search query: identify a preliminary set of search result documents in accordance with the search query; produce a set of query expansion terms based on terms found within a predetermined number of terms before and/or after the appearance of one or more of the one or more query terms in at least one of the search result documents that belong to the preliminary set of search result documents; combine the one or more query terms with query expansion terms from the set of produced query expansion terms to form an expanded search query; identify a second set of search result documents in accordance with the expanded search query; generate a content snippet corresponding to content in a respective search result document of the identified second set of search result documents, the content snippet associated with at least one query term of the one or more query terms in the search query; and return to the client system a response to the search query, the response including information identifying at least the respective search result document and including the content snippet of the respective search result document.
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9. A server computer system comprising: at least one processor; and memory storing instructions that, when executed by the at least one processor, cause the computer system to: receive, from a client system distinct from the server computer system, a search query having one or more query terms; in response to receiving the search query: identify a preliminary set of search result documents in accordance with the search query; produce a set of query expansion terms based on terms found within a predetermined number of terms before and/or after the appearance of one or more of the one or more query terms in at least one of the search result documents that belong to the preliminary set of search result documents; combine the one or more query terms with query expansion terms from the set of produced query expansion terms to form an expanded search query; identify a second set of search result documents in accordance with the expanded search query; generate a content snippet corresponding to content in a respective search result document of the identified second set of search result documents, the content snippet associated with at least one query term of the one or more query terms in the search query; and return to the client system a response to the search query, the response including information identifying at least the respective search result document and including the content snippet of the respective search result document. 12. The server computer system of claim 9 , wherein the memory further stores instructions that, when executed by the at least one processor, cause the server computer system to: generate a respective preliminary content snippet for each of a plurality of documents in the preliminary set of search result documents, each respective preliminary content snippet corresponding to content in the respective preliminary document, and associated with at least one query term of the one or more query terms in the search query; and produce the set of query expansion terms from the preliminary content snippets.
| 0.501634 |
1. A computer-implemented method comprising: accessing, by a computer system, a plurality of documents that each include a plurality of hyperlinks; identifying, for one document of the plurality of documents, portions of the plurality of hyperlinks of the one document; adding, for the one document, the identified portions of the plurality of hyperlinks as entries to a dictionary along with an associated reference for each of the added entries, wherein the dictionary and associated references for the one document are different than dictionaries and associated references for other documents of the plurality of documents, and wherein each associated reference defines a shortened representation for an entry in the dictionary that corresponds to the reference; compressing, by the computer system, each of the plurality of hyperlinks of the one document by replacing portions of the plurality of hyperlinks of the one document that are provided by entries in the dictionary for the one document with corresponding references to the entries in the dictionary; modifying the one document to include the dictionary and the associated references for the one document as a base hyperlink and replacing the plurality of hyperlinks of the one document with corresponding compressed hyperlinks; and providing the modified one document to a computing device for presentation to a user of the computing device.
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1. A computer-implemented method comprising: accessing, by a computer system, a plurality of documents that each include a plurality of hyperlinks; identifying, for one document of the plurality of documents, portions of the plurality of hyperlinks of the one document; adding, for the one document, the identified portions of the plurality of hyperlinks as entries to a dictionary along with an associated reference for each of the added entries, wherein the dictionary and associated references for the one document are different than dictionaries and associated references for other documents of the plurality of documents, and wherein each associated reference defines a shortened representation for an entry in the dictionary that corresponds to the reference; compressing, by the computer system, each of the plurality of hyperlinks of the one document by replacing portions of the plurality of hyperlinks of the one document that are provided by entries in the dictionary for the one document with corresponding references to the entries in the dictionary; modifying the one document to include the dictionary and the associated references for the one document as a base hyperlink and replacing the plurality of hyperlinks of the one document with corresponding compressed hyperlinks; and providing the modified one document to a computing device for presentation to a user of the computing device. 11. The computer-implemented method of claim 1 , wherein each of the associated references is represented by a fixed number of bits of data.
| 0.607338 |
30. A method for controlling a motion control system including a handheld device and a processing apparatus, the method comprising: receiving information from a three-axis acceleration sensor; receiving information from a camera; detecting movement of the handheld device via a motion detector operable to detect a tilt and translation motion based on the information received from the three-axis acceleration sensor and the camera, wherein the information received from the three axis acceleration sensor and the camera comprises a set of points traversed by the handheld motion device between a starting point base reference position and a stopping point; identifying and selecting a device to be controlled from among a plurality of devices based on a direction of movement of the motion detector, wherein the starting point base reference position is associated with an orientation of the handheld motion device relative to the device identified and selected to be controlled; and communicating information obtained by the motion detector to a processing apparatus of the selected device configured to obtain the information from the wireless communication interface to process the information.
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30. A method for controlling a motion control system including a handheld device and a processing apparatus, the method comprising: receiving information from a three-axis acceleration sensor; receiving information from a camera; detecting movement of the handheld device via a motion detector operable to detect a tilt and translation motion based on the information received from the three-axis acceleration sensor and the camera, wherein the information received from the three axis acceleration sensor and the camera comprises a set of points traversed by the handheld motion device between a starting point base reference position and a stopping point; identifying and selecting a device to be controlled from among a plurality of devices based on a direction of movement of the motion detector, wherein the starting point base reference position is associated with an orientation of the handheld motion device relative to the device identified and selected to be controlled; and communicating information obtained by the motion detector to a processing apparatus of the selected device configured to obtain the information from the wireless communication interface to process the information. 48. The method of claim 30 , further comprising giving a vibratory feedback.
| 0.627414 |
13. A system comprising: a processor-implemented search engine module configured to process a query to identify item listings that satisfy the query, each item listing comprising data representing one or more attributes of a product or service offered for sale; a processor-implemented ranking score assignment module configured to assign a ranking score to each item listing that satisfies the query, the ranking score derived as the product of two or more component scores including a first component score representing a measure of relevance between search terms in the query and the item listing, the second component score being independent of the query and representing a measure of quality for the item listing, the measure of quality being based at least in part on at least one of (i) an attribute of the item listing determinable at a time of listing, or (ii) an observed sales performance of the item listing or an item listing similar thereto; and a processor-implemented presentation module to present the item listings that satisfy the query in a search results page, the item listings positioned in the search results page based on the ranking score assigned to each item listing.
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13. A system comprising: a processor-implemented search engine module configured to process a query to identify item listings that satisfy the query, each item listing comprising data representing one or more attributes of a product or service offered for sale; a processor-implemented ranking score assignment module configured to assign a ranking score to each item listing that satisfies the query, the ranking score derived as the product of two or more component scores including a first component score representing a measure of relevance between search terms in the query and the item listing, the second component score being independent of the query and representing a measure of quality for the item listing, the measure of quality being based at least in part on at least one of (i) an attribute of the item listing determinable at a time of listing, or (ii) an observed sales performance of the item listing or an item listing similar thereto; and a processor-implemented presentation module to present the item listings that satisfy the query in a search results page, the item listings positioned in the search results page based on the ranking score assigned to each item listing. 19. The system of claim 13 , wherein the second component score representing a measure of quality for the item listing is calculated as a probability that the item listing will conclude a transaction if displayed in a search results page, the probability derived based on an analysis of observed metrics representing a measure of performance for the item listing.
| 0.52592 |
10. A method for reformatting closed caption text containing a sequence of closed caption characters comprising the steps of: identifying each control code within the sequence of closed caption characters; inspecting each control code and each closed caption character to identify a new caption or a new speaker; and inserting a carriage return prior to the new caption or new speaker.
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10. A method for reformatting closed caption text containing a sequence of closed caption characters comprising the steps of: identifying each control code within the sequence of closed caption characters; inspecting each control code and each closed caption character to identify a new caption or a new speaker; and inserting a carriage return prior to the new caption or new speaker. 15. The method of claim 10 further comprising the step of a mapping each closed caption character into a modified character set.
| 0.798611 |
2. The computer system of claim 1 , wherein the user interface is configured to query the user regarding interests of the user.
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2. The computer system of claim 1 , wherein the user interface is configured to query the user regarding interests of the user. 3. The computer system of claim 2 , wherein the query includes at least one of the following query portions: a first query portion regarding selecting the product, a second query portion regarding an intended use for the product, a third query portion regarding a request for technical information, and a fourth query portion regarding selecting a product option by the user.
| 0.904762 |
1. A computerized method of determining the complete latitude and longitude values of a geographic address, based on input data pertaining to said addresses' lower significant digit latitude and longitude values, and at least one context hint pertaining to the addresses' higher significant digit latitude and longitude values, said method comprising: obtaining an encoded version of said addresses' lower significant digit latitude and longitude values; obtaining or determining a latitude and longitude granularity value; obtaining at least one context hint; wherein said at least one context hint is related to said higher significant digit latitude and longitude values of said address within the error limits defined by said granularity value; using at least one computerized device comprising at least one processor, memory, and software, and said at least one context hint, to determine the higher significant digits of the latitude and longitude associated with said at least one context hint; using said at least one computerized device to parse or decode said encoded lower significant digit latitude and longitude values, thereby producing decoded lower significant digit latitude and longitude values; combining said decoded lower significant digit latitude and longitude values with said higher significant digit latitude and longitude values associated with said context hint, thereby determining a complete address with both higher significant and lower significant latitude and longitude values.
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1. A computerized method of determining the complete latitude and longitude values of a geographic address, based on input data pertaining to said addresses' lower significant digit latitude and longitude values, and at least one context hint pertaining to the addresses' higher significant digit latitude and longitude values, said method comprising: obtaining an encoded version of said addresses' lower significant digit latitude and longitude values; obtaining or determining a latitude and longitude granularity value; obtaining at least one context hint; wherein said at least one context hint is related to said higher significant digit latitude and longitude values of said address within the error limits defined by said granularity value; using at least one computerized device comprising at least one processor, memory, and software, and said at least one context hint, to determine the higher significant digits of the latitude and longitude associated with said at least one context hint; using said at least one computerized device to parse or decode said encoded lower significant digit latitude and longitude values, thereby producing decoded lower significant digit latitude and longitude values; combining said decoded lower significant digit latitude and longitude values with said higher significant digit latitude and longitude values associated with said context hint, thereby determining a complete address with both higher significant and lower significant latitude and longitude values. 8. The method of claim 1 , wherein said context hint is derived from either GPS location, GeoLocation result, center or focus of interactive map, IP address location, telephone number, last known address, location in user profile, or other geographic location parameter communicated from or stored in the memory of said at least one computerized device.
| 0.626706 |
1. A computer-implemented method comprising: accessing listing titles of one or more item listings on a marketplace website, the item listings being associated with a particular product category in a product category structure of the marketplace website; converting words in each of the listing titles to semantic tokens in a token symbol space, based on a tokenization process; performing n-gram modeling on the tokens corresponding to each of the listing titles of the item listings in the particular product category; and identifying, by a machine having a memory and at least one processor, one or more dominant n-gram models associated with the listing titles of the item listings in the particular product category, each dominant n-gram model identifying a sequence of one or more semantic tokens that appear in a statistically significant portion of the listing titles of the item listings in the particular product category.
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1. A computer-implemented method comprising: accessing listing titles of one or more item listings on a marketplace website, the item listings being associated with a particular product category in a product category structure of the marketplace website; converting words in each of the listing titles to semantic tokens in a token symbol space, based on a tokenization process; performing n-gram modeling on the tokens corresponding to each of the listing titles of the item listings in the particular product category; and identifying, by a machine having a memory and at least one processor, one or more dominant n-gram models associated with the listing titles of the item listings in the particular product category, each dominant n-gram model identifying a sequence of one or more semantic tokens that appear in a statistically significant portion of the listing titles of the item listings in the particular product category. 5. The method of claim 1 , wherein the particular product category is an accessory items product category.
| 0.639924 |
15. The computer system of claim 14 , wherein the processor is further configured to compare a part of speech tag of the key term in the first language with a part of speech tag of one or more terms included in the translation of the computing string in the second language if the translation of the key term in the second language does not match one or more terms included in the translation of the computing string in the second language.
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15. The computer system of claim 14 , wherein the processor is further configured to compare a part of speech tag of the key term in the first language with a part of speech tag of one or more terms included in the translation of the computing string in the second language if the translation of the key term in the second language does not match one or more terms included in the translation of the computing string in the second language. 16. The computer system of claim 15 , wherein the processor is further configured to classify the translation of the one or more terms of the translation of the computing string in the second language as incorrect if the part of speech tag of the key term in the first language matches the part of speech tag of the one or more terms included in the translation of the computing string in the second language.
| 0.711459 |
1. A method, comprising: receiving, by a computing device, a request from a user for one or more recommendations; determining a location distribution from historical location information associated with the user, wherein the location distribution indicates one or more probability distributions for one or more locations; determining a time distribution from historical context information associated with the user, wherein the time distribution indicates one or more probability distributions for one or more contexts, wherein a respective context includes contextual variables corresponding to at least one of: a location; a time; a weather condition; and a venue type; determining a joint distribution of two or more of the contextual variables that are based on the location distribution and the time distribution, wherein the joint distribution comprises statistical attributes that characterize dependent relationships between the two or more of the contextual variables, the statistical attributes including one or more of: a mean value; a median value; a mode; a maximum value; and a minimum value of the contextual variables; determining a hypothetical context based on the statistical attributes of the joint distribution and a current context, wherein the hypothetical context indicates one or more user preferences that are outside of the user's current context and explicit historical contexts; producing one or more recommendations for the user based on the hypothetical context; constructing a mapping function that maps a user context to a hypothetical context, wherein constructing the mapping function involves using one or more of: historical contexts associated with the request; prior hypothetical contexts; and the user's interactions associated with the user's past requests for a recommendation; and providing the one or more recommendations to the user.
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1. A method, comprising: receiving, by a computing device, a request from a user for one or more recommendations; determining a location distribution from historical location information associated with the user, wherein the location distribution indicates one or more probability distributions for one or more locations; determining a time distribution from historical context information associated with the user, wherein the time distribution indicates one or more probability distributions for one or more contexts, wherein a respective context includes contextual variables corresponding to at least one of: a location; a time; a weather condition; and a venue type; determining a joint distribution of two or more of the contextual variables that are based on the location distribution and the time distribution, wherein the joint distribution comprises statistical attributes that characterize dependent relationships between the two or more of the contextual variables, the statistical attributes including one or more of: a mean value; a median value; a mode; a maximum value; and a minimum value of the contextual variables; determining a hypothetical context based on the statistical attributes of the joint distribution and a current context, wherein the hypothetical context indicates one or more user preferences that are outside of the user's current context and explicit historical contexts; producing one or more recommendations for the user based on the hypothetical context; constructing a mapping function that maps a user context to a hypothetical context, wherein constructing the mapping function involves using one or more of: historical contexts associated with the request; prior hypothetical contexts; and the user's interactions associated with the user's past requests for a recommendation; and providing the one or more recommendations to the user. 10. The method of claim 1 , further comprising saving the hypothetical context to a calendar to facilitate subsequent hypothetical context determinations.
| 0.66495 |
12. A method for processing activity records, the method comprising: establishing, by a computing system, an anonymization dictionary based on user activity encountered by the computing system, by: obtaining, by an endpoint agent executing on the computing system, an activity record, wherein the activity record comprises metadata documenting the user activity; generating, by an activity monitoring engine of the computing system that is operatively connected to the endpoint agent, the anonymization dictionary, wherein generating the anonymization dictionary comprises: detecting, in the activity record, a plurality of target entities, wherein each of the plurality of target entities is metadata related to the user activity and requires anonymization; assigning an anonymized identity to each unique target entity of the plurality of target entities; generating dictionary entries for the plurality of target entities, wherein each dictionary entry comprises a target entity and a corresponding anonymized identifier comprising the anonymized identity for the target entity; generating, by the computing system, an equivalence map, by: making a determination that a resource is associated with a subset of the target entities of the plurality of target entities; storing, in the equivalence map, an identity relationship specifying that the subset of the target entities is associated with the resource; anonymizing user activity, based on the anonymization dictionary previously generated by the computing system, by: processing, by an anonymization engine executing on the computing system, the activity record using the anonymization dictionary to obtain an anonymized activity record, by: replacing, in the activity record, target entities with their corresponding anonymized identifiers, specified in the anonymization dictionary; and storing the anonymized record.
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12. A method for processing activity records, the method comprising: establishing, by a computing system, an anonymization dictionary based on user activity encountered by the computing system, by: obtaining, by an endpoint agent executing on the computing system, an activity record, wherein the activity record comprises metadata documenting the user activity; generating, by an activity monitoring engine of the computing system that is operatively connected to the endpoint agent, the anonymization dictionary, wherein generating the anonymization dictionary comprises: detecting, in the activity record, a plurality of target entities, wherein each of the plurality of target entities is metadata related to the user activity and requires anonymization; assigning an anonymized identity to each unique target entity of the plurality of target entities; generating dictionary entries for the plurality of target entities, wherein each dictionary entry comprises a target entity and a corresponding anonymized identifier comprising the anonymized identity for the target entity; generating, by the computing system, an equivalence map, by: making a determination that a resource is associated with a subset of the target entities of the plurality of target entities; storing, in the equivalence map, an identity relationship specifying that the subset of the target entities is associated with the resource; anonymizing user activity, based on the anonymization dictionary previously generated by the computing system, by: processing, by an anonymization engine executing on the computing system, the activity record using the anonymization dictionary to obtain an anonymized activity record, by: replacing, in the activity record, target entities with their corresponding anonymized identifiers, specified in the anonymization dictionary; and storing the anonymized record. 13. The method of claim 12 , wherein generating the equivalence map may be performed prior to storing the anonymized record.
| 0.570031 |
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